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    61829 research outputs found

    Towards a qualitative theory of the interruption of eating behavior change

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    International audienceThe poor maintenance of eating behavior change is one of the main obstacles to minimizing weight regain after weight loss during diets for non-surgical care of obese or overweight patients. We start with a known informal explanation of interruption in eating behavior change during severe restriction and formalize it as a causal network involving psychological variables, which we extend with energetic variables governed by principles of thermodynamics. The three core phenomena of dietary behavior change, i.e., non-initiation, initiation followed by discontinuation and initiation followed by non-discontinuation, are expressed in terms of the value of the key variable representing mood or psychological energy, the fluctuation of which is the result of three causal relationships. Based on our experimental knowledge of the time evolution profile of the three causal input variables, we then proceed to a qualitative analysis of the resulting theory, i.e., we consider an overapproximation of it which, after discretization, can be expressed in the form of a finite integer-based model. Using Answer Set Programming, we show that our formal model faithfully reproduces the three phenomena and, under a certain assumption, is minimal. We generalize this result by providing all the minimal models reproducing these phenomena when the possible causal relationships exerted on mood are extended to all the other variables (not just those assumed in the informal explanation), with arbitrary causality signs. Finally, by a direct analytical resolution of an under-approximation of our theory, obtained by assuming linear causalities, as a system of linear ODEs, we find exactly the same minimal models, proving that they are also equal to the actual minimal models of our theory since these are framed below and above by the models of the underapproximation and the over-approximation. We determine which parameters need to be person-specific and which can be considered invariant, i.e., we explain inter-individual variability. Our approach could pave the way for universally accepted theories in the field of behavior change and, more broadly, in other areas of psychology

    CEGAR-Based Approach for Solving Combinatorial Optimization Modulo Quantified Linear Arithmetics Problems

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    International audienceBioinformatics has always been a prolific domain for generating complex satisfiability and optimization problems. For instance, the synthesis of multi-scale models of biological networks has recently been associated with the resolution of optimization problems mixing Boolean logic and universally quantified linear constraints (OPT+qLP), which can be benchmarked on real-world models. In this paper, we introduce a CounterExample Guided Abstraction Refinement (CEGAR) to solve such problems efficiently. Our CEGAR exploits monotone properties inherent to linear optimization in order to generalize counterexamples of Boolean relaxations. We implemented our approach by extending Answer Set Programming (ASP) solver Clingo with a quantified linear constraints propagator. Our prototype enables exploiting independence of sub-formulas to further exploit the generalization of counterexamples. We evaluate the impact of refinement and partitioning on two sets of OPT+qLP problems inspired by system biology. Additionally, we conducted a comparison with the state-of-the-art ASP solver Clingo[lpx] that handles non-quantified linear constraints, showing the advantage of our CEGAR approach for solving large problems

    Two families of indexable partially observable restless bandits and Whittle index computation

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    International audienc

    A Unified Approach to Emotion Detection and Task-Oriented Dialogue Modeling

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    International audienceIn current text-based task-oriented dialogue (TOD) systems, user emotion detection (ED) is often overlooked or is typically treated as a separate and independent task, requiring additional training. In contrast, our work demonstrates that seamlessly unifying ED and TOD modeling brings about mutual benefits, and is therefore an alternative to be considered. Our method consists in augmenting SimpleToD, an endto-end TOD system, by extending belief state tracking to include ED, relying on a single language model. We evaluate our approach using GPT-2 and Llama-2 on the EmoWOZ benchmark, a version of MultiWOZ annotated with emotions. Our results reveal a general increase in performance for ED and task results. Our findings also indicate that user emotions provide useful contextual conditioning for system responses, and can be leveraged to further refine responses in terms of empathy

    Impact of the Sars-Cov-2 outbreak on the initial clinical presentation of new solid cancer diagnoses: a systematic review and meta-analysis

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    International audienceBackground The COVID-19 pandemic might have delayed cancer diagnosis and management. The aim of this systematic review was to compare the initial tumor stage of new cancer diagnoses before and after the pandemic. Methods We systematically reviewed articles that compared the tumor stage of new solid cancer diagnoses before and after the initial pandemic waves. We conducted a random-effects meta-analysis to compare the rate of metastatic tumors and the distribution of stages at diagnosis. Subgroup analyses were performed by primary tumor site and by country. Results From 2,013 studies published between January 2020 and April 2022, we included 58 studies with 109,996 patients. The rate of metastatic tumors was higher after the COVID-19 outbreak than before (pooled OR: 1.29 (95% CI, 1.06-1.57), I 2 : 89% (95% CI, 86-91)). For specific cancers, common ORs reached statistical significance for breast (OR: 1.51 (95% CI 1.07-2.12)) and gynecologic (OR: 1.51 (95% CI 1.04-2.18)) cancers, but not for other cancer types. According to countries, common OR (95% CI) reached statistical significance only for Italy: 1.55 (1.01-2.39) and Spain: 1.14 (1.02-1.29). Rates were comparable for stage I-II versus III-IV in studies for which that information was available, and for stages I-II versus stage III in studies that did not include metastatic patients. Conclusions Despite inter-study heterogeneity, our meta-analysis showed a higher rate of metastatic tumors at diagnosis after the pandemic. The burden of social distancing policies might explain those results, as patients may have delayed seeking care

    SuperRail − World-first HTS cable to be installed on a railway network in France

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    We would like to thank our colleagues at SNCF, Nexans, Absolut System, University Paris-Saclay and the University of Lorraine for the valuable insights they provided and the in-depth discussions we had.International audienceThe SuperRail project consists in the development, manufacturing, installation and long-term operation of a high temperature superconducting (HTS) DC cable system for railway applications. The objectives of the project are to reinforce the power supply of the Montparnasse railway station in Paris, to increase the traffic and to participate to the reduction of CO2 emission. The saturated underground in the center of Paris does not allow to create new right of ways and only the HTS cable technology allows to carry the required power to railway tracks using the few available 100 mm conduits left. The HTS cable system must answer to a load chart with a high level of requirements corresponding to the connection of a substation to a set of railways tracks in very constraints areas. In the case of SuperRail, two 60-meter long 1.5 kV-3.5 kA HTS DC cables made of second-generation (2G) conductors will be installed in parallel. They need to sustain a 67 kA-200 ms short-circuit current. The cryogenic system is specifically designed for this project. It is based on a Reverse Turbo-Brayton cycle producing cooling power of about 1700 W at 67 K. This system intends to ensure low maintenance during life cycle, high reliability and would be scalable for future application (not limited to railways). In parallel, prospective studies are being carried out to simulate superconducting cables in railway networks, and to find original solutions to replace the current leads. SuperRail is a landmark project, as it is the first time that a DC HTS cable system is installed on a commercially operated railway network. The technologies developed have the potential to be reproduced in similar cases existing in large cities

    Spectroscopie optique de boîtes quantiques de graphène et de nanocristaux de pérovskites halogénées

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    This work focuses on the optical spectroscopy of two classes of materials using fluorescence microscopy at room temperature.First, halide perovskites, a class of semiconductors that have known a surge in interest in the last ten years because of their outstanding optoelectronic properties, making them a promising platform for photovoltaic applications, but also light emission in diodes, lasers, and quantum devices. These crystalline materials consist of corner-sharing octahedra with a metallic ion at the center, often lead, and halide ions at the corners: Cl, Br, or I. A cation completes the structure. It is either organic, for example, methylammonium (MA) or formamidinium, or inorganic, for example, cesium. In the context of light emission, halide perovskites are an excellent choice to address the problem of the green gap, that is, the lack of efficient emitters in the green region of the optical spectrum, because of the possibility to tune their band gap thanks to an informed choice of the halide during the synthesis.Moreover, because the synthesis is done at room temperature and involves soft chemistry steps, they are promising for industrial applications. The synthesis and characterization of CsPbBr₃ nanocrystals emitting in the optical spectrum's green region using a new reprecipitation-based method is reported. In particular, the nanocrystals' high calibration and good stability are highlighted.The second part of this study is about graphene quantum dots. Those low-dimensional objects allow the opening of the band gap of graphene, making them fluorescent. These emitters are promising because their atomically-thin structure and tunability make them suitable for realizing nano-sensors. Building on the recently studied structure-properties relationship of rod-shaped graphene quantum dots, a thorough single-molecule study of highly fluorescent graphene quantum dots with 96 sp² carbon atoms is reported. The excellent purity of the samples was highlighted. The study of the time dynamics of those single-photon emitters in a polystyrene matrix allowed estimating the characteristic times of the transient dynamic of the quantum dots.Finally, the third part reports the study of the graphene quantum dots on a perovskite surface. The surface of perovskites is of peculiar interest for the realization of devices with these semiconductors, making it an interesting playground to use graphene quantum dots. To that end, the quantum dots were deposited on a millimetric MAPbBr₃ single-crystal surface. - As thin films deposited on the perovskite, the graphene quantum dots present photophysics compatible with the formation of excimers. - As the concentration of quantum dots on the surface is lowered, diffraction-limited spots are observed. The time-domain study of the photoluminescence reveals jumps between discrete states of the system. - The frequency-domain investigation of the intensity of photoluminescence of these diffraction-limited emitters is dominated by 1/f noise, which highly contrasts the stable, shot-noise-dominated dynamics of the single emitters when studied in a polystyrene matrix.Ce travail se concentre sur la spectroscopie optique de deux classes de matériaux en utilisant la microscopie de fluorescence à température ambiante.Tout d'abord, les pérovskites halogénées, une classe de semi-conducteurs qui ont connu un regain d'intérêt au cours des dix dernières années en raison de leurs propriétés optoélectroniques exceptionnelles, ce qui en fait une plate-forme prometteuse pour les applications photovoltaïques, mais aussi pour l'émission de lumière dans les diodes, les lasers et les dispositifs quantiques. Ces matériaux cristallins sont constitués d'octaèdres dont les sommets sont partagés. Un ion métallique est positionné au centre, souvent du plomb, et des ions halogénures aux sommets : Cl, Br ou I. Un cation complète la structure. Il est soit organique, par exemple le méthylammonium (MA) ou le formamidinium, soit inorganique, par exemple le césium. Dans le contexte de l'émission de lumière, les pérovskites halogénées constituent un excellent choix pour résoudre le problème du green gap, c'est-à-dire le manque d'émetteurs efficaces dans la région verte du spectre optique, en raison de la possibilité d'ajuster leur bande interdite grâce à un choix éclairé de l'halogénure lors de la synthèse.De plus, comme la synthèse se fait à température ambiante et implique des étapes de chimie simples, ils sont prometteurs pour les applications industrielles. La synthèse et la caractérisation de nanocristaux de CsPbBr₃ émettant dans la région verte du spectre optique à l'aide d'une nouvelle méthode basée sur la précipitation est rapportée. En particulier, la calibration élevé et la bonne stabilité des nanocristaux sont mis en évidence.La deuxième partie de cette étude porte sur les boîtes quantiques de graphène. Ces objets de faible dimension permettent d'ouvrir la bande interdite du graphène, ce qui les rend fluorescents. Ces émetteurs sont prometteurs parce que leur structure atomiquement fine et leur accordabilité les rendent aptes à réaliser des nanocapteurs. En s'appuyant sur la relation structure-propriétés récemment étudiée des boîtes quantiques de graphène rectangulaires, une étude approfondie au niveau de l'objet unique de ces boîtes quantiques hautement fluorescentes avec 96 atomes de carbone sp² est rapportée. L'excellente pureté des échantillons a été mise en évidence. L'étude de la dynamique temporelle de ces émetteurs de photons uniques dans une matrice de polystyrène a permis d'estimer les temps caractéristiques de la dynamique transitoire des points quantiques.Enfin, la troisième partie rapporte l'étude des points quantiques de graphène sur une surface de pérovskite. La surface des pérovskites présente un intérêt particulier pour la réalisation de dispositifs avec ces semi-conducteurs, ce qui en fait un terrain de jeu intéressant pour l'utilisation des boîtes quantiques de graphène. À cette fin, les boîtes quantiques ont été déposés sur la surface de monocristaux millimétriques de MAPbBr₃. - En tant que films minces déposés sur la pérovskite, les boîtes quantiques de graphène présentent une photophysique compatible avec la formation d'excimères. - Lorsque la concentration de boîtes quantiques sur la surface est réduite, des taches limitées par la diffraction sont observées. L'étude de la photoluminescence dans le domaine temporel révèle des sauts entre des états discrets du système. - L'étude dans le domaine des fréquences de l'intensité de la photoluminescence de ces émetteurs limités par la diffraction est dominée par le bruit en 1/f, ce qui contraste fortement avec la dynamique stable, dominée par le bruit de grenaille, des émetteurs uniques lorsqu'ils sont étudiés dans une matrice de polystyrène

    Extending nonstandard finite difference schemes rules to systems of nonlinear ODEs with constant coefficients

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    International audienceIn this paper, we present a reformulation of Mickens' rules for nonstandard finite difference (NSFD) scheme to adapt them to systems of ODEs. This leads to exact schemes in the linear case, and also improve the accuracy in the nonlinear case. In the Hamiltonian nonlinear case, it consists in adding correction terms to schemes derived by Mickens


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    In the framework of the privacy-preserving concerns of the SOTERIA project, and concerning future Machine Learning (ML) implementations, we explore hardware-based privacy computations for secure and private data storage and ML computations. Current supported hardware on cloud and consumer devices most notably include Trusted Execution Environments (TEEs), which have emerged as a critical technology in modern computing, offering hardware-enforced security measures to protect sensitive data and computations from potential threats. This report presents a comprehensive review of TEEs, focusing on the advantages, vulnerabilities, and implementations of prominent TEE technologies, and the state-of-the-art on TEE-based methods for privacy-preserving sensitive data storage and ML operations. Finally, we provide a discussion on these commercial implementations, methods, possible implementations for improving the security and privacy on the SOTERIA platform for current and future applications, and our conclusion


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