Homogenization of heat diffusion in a cracked medium

We develop in this note a homogenization method to tackle the problem of a diffusion process through a cracked medium. We show that the cracked surface of the domain induces a source term in the homogenized equation. We assume that the cracks are orthogonal to the surface of the material, where an incoming heat flux is applied. The cracks are supposed to be of depth 1, of small width, and periodically arranged.Comment: 28 pages, 10 figure

CSP dynamiques pour la génération de tests de systèmes réactifs

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Bounded Expectations: Resource Analysis for Probabilistic Programs

This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials of the inputs. The new technique combines manual state-of-the-art reasoning techniques for probabilistic programs with an effective method for automatic resource-bound analysis of deterministic programs. It can be seen as both, an extension of automatic amortized resource analysis (AARA) to probabilistic programs and an automation of manual reasoning for probabilistic programs that is based on weakest preconditions. As a result, bound inference can be reduced to off-the-shelf LP solving in many cases and automatically-derived bounds can be interactively extended with standard program logics if the automation fails. Building on existing work, the soundness of the analysis is proved with respect to an operational semantics that is based on Markov decision processes. The effectiveness of the technique is demonstrated with a prototype implementation that is used to automatically analyze 39 challenging probabilistic programs and randomized algorithms. Experimental results indicate that the derived constant factors in the bounds are very precise and even optimal for many programs

Détection de recombinaisons génomiques et protéomiques homologues par alignement multiple local et partiel

International audienceDoctoralPhages are viral microorganisms that infect bacteria. Their genome is structured in many functional modules, frequently mixed by recombination. These recombinations, encouraged by the homology between sequences, result in new combinations of modules and thus in potentially new and viable phages, but make them difficult to annotate with in-silico methods. In particular, classical multiple alignment methods are unable to handle recombinations. The aim of my internship is to use a new multiple alignment tool, Paloma, to study recombinations between homologous proteins of 32 phages, whose some have already been recombined according to the literature. The visualization of the generated alignments allowed to find recombined regions in 8 phages described by the past in 3 phages, and the presence of 4 conserved sequences between these 8 phages around the recombined region. These could be recombination fingerprints. These results are encouraging and demonstrate the ability of Paloma to take into account recombinations in a multiple alignment. In the future, it is planned to couple Paloma with an automata learning tool to predict the unknown function of phage proteins.Les phages sont des micro-organismes viraux qui infectent les bactéries. Leur génome est structuré sous la forme de modules fonctionnels, fréquemment mélangés par recombinaison. Ces recombinaisons, favorisées par l’homologie entre séquences, donnent lieu à de nouvelles combinaisons de modules et donc à des phages potentiellement nouveaux et viables, mais les rend difficile à annoter avec des méthodes in-silico. Plus particulièrement, les méthodes classiques d’alignement multiple n’arrive pas à prendre en charge les recombinaisons. Le but de mon stage est d’utiliser un nouvel outil d’alignement multiple, Paloma, pour étudier les recombinaisons entre protéines homologues de 32 phages, dont certaines ont déjà fait l’objet de recombinaison d’après la littérature. La visualisation des alignements généré a permis de retrouver des régions recombinées chez 8 phages décrites par le passé chez 3 phages, et la présence de 4 séquences conservées entre ces 8 phages autour de la région recombinée. Il pourrait s’agir d’empreintes de recombinaison. Ces résultats sont encourageants et démontre la capacité de Paloma à tenir compte de recombinaisons lors d’un alignement multiple. À terme, il est prévu de coupler Paloma avec un outil d’apprentissage d’automates pour prédire la fonction inconnue de protéines de phage

Inflation and Dark Energy from spectroscopy at z > 2

The expansion of the Universe is understood to have accelerated during two epochs: in its very first moments during a period of Inflation and much more recently, at z < 1, when Dark Energy is hypothesized to drive cosmic acceleration. The undiscovered mechanisms behind these two epochs represent some of the most important open problems in fundamental physics. The large cosmological volume at 2 < z < 5, together with the ability to efficiently target high-$z$ galaxies with known techniques, enables large gains in the study of Inflation and Dark Energy. A future spectroscopic survey can test the Gaussianity of the initial conditions up to a factor of ~50 better than our current bounds, crossing the crucial theoretical threshold of $\sigma(f_{NL}^{\rm local})$ of order unity that separates single field and multi-field models. Simultaneously, it can measure the fraction of Dark Energy at the percent level up to $z = 5$, thus serving as an unprecedented test of the standard model and opening up a tremendous discovery space

Investigating the impact of atmospheric boundary layer stratification on wind farm noise propagation

The expansion of wind farm installations has been hindered by annoyance issues resulting from the noise emitted by wind turbines. Understanding the factors that affect sound propagation is crucial to mitigate the impact of noise. Atmospheric boundary layer (ABL) stratification strongly affects the noise propagation of isolated wind turbines. However, few studies have looked at the influence of atmospheric conditions on wind farm noise propagation. This study aims to investigate this through numerical simulations. Large eddy simulations (LES) are used to predict the mean flow inside and around the wind farm. The noise from each wind turbine is computed from an extended source model that determines the wind turbine sound production based on its geometry, and on the flow characteristics (wind speed and turbulence intensity). A model based on the parabolic equation is employed to compute the sound propagation based on the flow fields obtained from LES. Neutral, stable and unstable stability conditions are considered for an idealized wind farm layout. The results of this study provide insight into the influence of atmospheric conditions on wind farm sound propagation and can inform the development of effective noise mitigation strategies.</p