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Score MAS et variables biomécaniques : degré d'accord entre deux kinésithérapeutes sur un même patient
No full textInternational audienc
Charte de mutualisation et ouverture des données du projet Flex-Mediation
No full textThe charter applies to all researchers contributing to or supporting the research activities of the Flex-Mediation project, and participants undertake to respect the principles set out in the charter. The charter sets out a framework to facilitate collaborative research, the sharing of resources between team members (documents, raw data, etc.) and opening up research data.La charte concerne l’ensemble des chercheur.es contribuant à l’activité de recherche ou y apportant un appui dans le cadre du projet Flex-Mediation. Les participant.es s’engagent à respecter les principes énoncés dans la charte. Cette dernière fixe un cadre pour faciliter la recherche en collectif, la mutualisation des ressources (documents, données brutes, etc.) et l'ouverture des données
BA.1 breakthrough infection elicits distinct antibody and memory B cell responses in vaccinated-only versus hybrid immunity individuals
No full textInternational audienceImmune memory is influenced by the frequency and type of antigenic challenges. Here, we performed a cross-sectional comparison of immune parameters following a BA.breakthrough infection in individuals with prior hybrid immunity (conferred by infection and vaccination) versus those solely vaccinated in a cohort of health care workers in Lyon, France. The results showed higher levels of serum anti-RBD antibodies and neutralizing antibodies against BA.1 post-infection in the vaccine-only group. Individuals in this group also showed a decrease in memory B cells against the ancestral strain but an increase in those specific and cross-reactive to BA.1, suggesting a more limited immune imprinting. Conversely, hybrid immunity prevents the decrease in ADCC response, possibly by limiting IgG4 class-switching, and enhanced anti-N responses post-infection. This highlights that BA.1 breakthrough infection induces different immune responses depending on prior history of vaccination and infection, which should be considered for further vaccination guidelines
Joint Modelling and Robustness Analysis of Multimodal Transportation and Electricity Networks
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Les besoins en logements : un indicateur révélateur des transformations de la politique du logement en France
No full textInternational audienceA travers une approche historique de la façon dont sont quantifiés les "besoins en logements", l'article montre comment l'évolution de cet indicateur reflète les transformations de la politique du logement en France entre 1950 et 2025
L’effondrement ou l’éloge (involontaire) de la logistique contemporaine
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A comprehensive investigation of variational auto-encoders for population synthesis
No full textInternational audienceThe use of synthetic populations has grown considerably over the recent years, in revolutionizing studies conducted within various fields, including social science research, urban planning, public health and transportation modeling. These synthetic populations prove to be valuable, as substitutes for the often missing or sensitive real data, and moreover are capable of preserving both privacy and representativeness. They are typically constructed from aggregate and/or sample data. Recently, new methods for generating synthetic populations based on deep learning, notably Variational Autoencoders (VAEs), have been developed. Such methods serve to overcome the limitations of traditional methods, such as Iterative Proportional Fitting (IPF), which are unable to generate agents with cross-modalities not found in the sample data. As such, IPF requires large samples to generate a synthetic population closely resembling the actual one. Conversely, the advantage of VAE lies in their ability to generate agents not found in the sample data, albeit with the risk of creating agents not existing in the actual population. However, the practical documentation as well as detailed analyses of the architectures and results from implementation of these deep learning approaches, in particular VAE, are limited, thus making these methods difficult to appropriate for practitioners. This paper focuses on generating synthetic populations using VAE. First, an in-depth and accessible theoretical explanation of how VAEs function is provided. Next, a detailed study of these methods is carried out by testing the various architectures, parameters, sample sizes and evaluation indicators necessary to guarantee high-quality results. Highlighted herein is the ability of VAEs to generate large datasets with a small training sample, in addition to VAE performance in generating new realistic individuals not present in the learning base. Certain limitations are identified, including the difficulties encountered by VAEs in managing numerical attributes and the need for post-processing to eliminate unrealistic individuals. In conclusion, despite a number of limitations, VAE constitutes a very promising methodology for generating synthetic populations, in offering practitioners numerous advantages. This paper is accompanied by a Python notebook to assist interested readers implement this new methodology
Brasser les milliards de l’État grâce au carrousel de la TVA: un guide pratique avec la série d’argent et de sang
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Failure mechanism in recycled sand mortars and recycled aggregate concretes: Experimental and multiscale approaches
No full textInternational audienceIn the present work, the mechanisms controlling the uniaxial compressive strength of recycledsand mortars (RSM) and recycled aggregate concretes (RAC) are investigated consideringexperimental and multiscale modeling approaches. First of all, RSM and RAC (with differentamounts of recycled sand and recycled aggregates respectively) are formulated with a fixedwater to cement ratio of 0.42 and the key parameters (properties of old/new interfaces andmortars, micro-cracks) ruling the strength properties of RSM and RAC at different scalesthoroughly analyzed and discussed. Among many other results, one notices a drop of around30% of the compressive strength between 100% RSM (containing recycled sand only) and areference mortar (without recycled sand) whereas in RAC, the impact of the total substitutionof coarse natural aggregates by recycled ones is found to induce a decrease of around 16%(compared to a reference concrete). Moreover, a quite linear decrease of the compressivestrength is detected from a certain replacement rate of natural sand or coarse aggregates byrecycled ones (beyond 10% for RSM and 20% for RAC). As for the brittleness and the failuremechanism of RAC, they are found to be strongly related to the water to cement ratio, thecontent of the recycled aggregates and the compressive strength of the parent concrete. At theend, a multiscale model devoted to the prediction of the compressive strength of RSM andRAC is developed in the framework of quasi-brittle failure mechanism using the well-knownDrucker–Prager criterion. The uniaxial compressive strength of RSM and RAC with differentwater to cement ratios and recycled sand/aggregates contents are therefore investigated andthe theoretical results discussed. Fed with input data collected on the microstructure, the modelis shown to predict with a good accuracy, the uniaxial compressive strength of recycled sandmortars and recycled aggregate concretes
A Data-Driven-based homogenization method to simulate the anisotropic damage of brittle heterogeneous structures
No full textInternational audienceAn efficient data-driven multiscale framework for modeling anisotropic damage (M-DDHAD) in heterogeneous structures is proposed, where the anisotropic damage model at the macro scale is constructed purely on the knowledge of Representative Volume Elements (RVE) of the material microstructure. The technique involves three main steps: the construction of a database, obtained by performing off-line calculations of crack propagation on Representative Volume Elements (RVE); the construction of an anisotropic damage model constructed from the database using Harmonic Analysis of Damage and off-line calculations, where damage is computed using the constructed model in tandem with a strain-gradient regularization technique. Using Harmonic Analysis of Damage, an anisotropic damage model defining the evolution of the macroscopic elastic tensor as a function of macro internal variables is provided without specific assumptions about the anisotropy related to the RVE geometry. A surrogate model is constructed to define their evolution. The macroscopic problem uses the constructed anisotropic damage model, and a modified strain-gradient regularization is applied to guarantee mesh-independence. The technique accuracy and robustness has been assessed on several structural problems with different microstructures, involving a strong initial and induced anisotropic fracture behavior, and compared with direct crack numerical simulations (DNS) of heterogeneous structures. Very good accuracy has been obtained both regarding the force-displacement curves as well as crack paths, while keeping the efficiency of classical Finite Element simulations