Biphotonic Microscopy for in vitro, in vivo tissue phenotyping and cell tracking

Biphotonic Microscopy for [i]in vitro[/i], [i]in vivo[/i] tissue phenotyping and cell tracking. Gen2bio201

Choisir son Nuage à l'Aide des Modèles de Caractéristiques

National audienceIl existe de nombreuses solutions d'informatique dans les nuages (cloud computing). Nous proposons une approche tirant profit des modèles de caractéristiques pour choisir la solution qui répond au mieux aux besoins techniques et non fonctionnels de l'application à déployer

Leveraging Feature Models to Configure Virtual Appliances

International audienceCloud computing is a major trend in distributed computing environments. Software virtualization technologies allow cloud Infrastructure-as-a-Service (IaaS) providers to instantiate and run a large number of virtual appliances. However, one of the major challenges is to reduce the disk space footprint of such virtual appliances to improve their storage and transfer across cloud servers. In this paper, we propose to use a Software Product Line (SPL) approach and describe the virtual appliance as a set of common and variable elements modeled by means of Feature Model (FM). We describe a solution to reverse engineer a FM from a virtual appliance and we show how we take advantage of the SPL configuration mechanisms to signifi cantly reduce the size of a virtual appliance

Macchiato : vers un système de panier unique pour le e-commerce

Journées du GDR GPLNational audienceLe e-commerce est un domaine qui a explosé ces dernières années avec la multiplication des sites de vente en ligne. Cependant, face à cette explosion des sites de e-commerce, l'utilisateur final perd petit à petit ses repères et éprouve les plus grandes difficultés à trouver les meilleures offres pour ses achats. Les sites de comparaison en ligne--tels que Kelkoo1 --ne sont pas toujours fiables car les résultats qu'ils fournissent ne sont pas nécessairement objectifs et ne prennent pas en compte les préférences de l'utilisateur. Dans ce contexte, Macchiato se présente comme une solution de nouvelle génération des sites de e-commerce, basée sur les principes de l'Internet des Objets. En particulier, Macchiato vise à mettre l'utilisateur au cœur du système en lui donnant la capacité de composer des services personnalisés pour mieux répondre à ses besoins. Pour ce faire, dans Macchiato, les services et les produits sont exposés sous la forme de ressources sémantiquement riches et connectées entre elles. Cette richesse sémantique facilite la compréhension des informations échangées entre les services et les utilisateurs tout en renforçant le typage des compositions de services

Comparative Fear-Related Behaviors to Predator Odors (TMT and Natural Fox Feces) before and after Intranasal ZnSO4 Treatment in Mice

The possibility that synthetic 2,4,5-trimethylthiazoline (TMT), frequently used to induce unconditioned fear in rodents, could be more a pungent odor activating intranasal trigeminal nerve fibers rather than a predator odor index is currently discussed. In order to explore this question, the present study compared fear-related behaviors to predator odors (synthetic 10% TMT and natural fox feces) and toluene (as an irritant compound without ecological significance) before and after intranasal ZnSO4 perfusion which is known to provoke transient anosmia. Results show that natural fox feces could be consider as a pure olfactory (CN I) nerve stimulant while 10% TMT appeared to be a mixed olfactory (CN I) and trigeminal (CN V) nerves stimulant with a great olfactory power and a low trigeminal power. These findings suggest that behavioral neuroscience studies should use concentrations lower than 10% TMT to obtain fear-related behaviors similar to those obtained with natural fox feces odor

Towards Multi-Cloud Configurations Using Feature Models and Ontologies

International audienceConfiguration and customization choices arise due to the heterogeneous and scalable aspect of the cloud computing paradigm. To avoid being restricted to a given cloud and ensure application requirements, using several clouds to deploy a multi-cloud configuration is recommended but introduces several challenges due to the amount of providers and their intrinsic variability. In this paper, we present a model-driven approach based on Feature Models originating from Software Product Lines to handle cloud variability and then manage and create cloud configurations. We combine it with ontologies, used to model the various semantics of cloud systems. The approach takes into consideration application technical requirements as well as non-functional ones to provide a set of valid cloud or multi-cloud configurations and is implemented in a framework named Saloon

A study of composite material damage induced by laser shock waves

A laser shock wave technique has been used to study the damage tolerance of T800/M21 CFRP (Carbon Fiber Reinforced Polymer) composite material with different lay_ups. Different levels of damage have been created according to various laser irradiation conditions. Several characterization methods such as Optical Microscopy, X-ray Radiography, or Interferometric Confocal Microscopy have been used to quantify these defects. The nature of the defects induced by the shock wave propagation has been studied. The sensitivity of the composite material damage to the shock conditions has been shown and quantified. Moreover, the experimental results gathered with each technique have been compared to each other and it leads to a better understanding of the CFRP behavior under high dynamic loading. These original results have enabled the definition of a specific damage criterion for CFRP under dynamic loading

Construction Grammar and Language Models

Recent progress in deep learning and natural language processing has given rise to powerful models that are primarily trained on a cloze-like task and show some evidence of having access to substantial linguistic information, including some constructional knowledge. This groundbreaking discovery presents an exciting opportunity for a synergistic relationship between computational methods and Construction Grammar research. In this chapter, we explore three distinct approaches to the interplay between computational methods and Construction Grammar: (i) computational methods for text analysis, (ii) computational Construction Grammar, and (iii) deep learning models, with a particular focus on language models. We touch upon the first two approaches as a contextual foundation for the use of computational methods before providing an accessible, yet comprehensive overview of deep learning models, which also addresses reservations construction grammarians may have. Additionally, we delve into experiments that explore the emergence of constructionally relevant information within these models while also examining the aspects of Construction Grammar that may pose challenges for these models. This chapter aims to foster collaboration between researchers in the fields of natural language processing and Construction Grammar. By doing so, we hope to pave the way for new insights and advancements in both these fields