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On Analytical Modeling for Fast Multi-Objective Torque Allocation in Over-Actuated IWM Vehicles
No full textInternational audienceEfficient torque allocation in over-actuated vehicles poses a central challenge in the domain of advanced vehicle control. These vehicles, featuring redundant actuators, provide an exceptional avenue for enhancing performance, stability, and efficiency. This paper presents a pioneering tendency for torque allocation in the context of over-actuated vehicles, particularly in-wheel motor (IWM) driven electric vehicles. We introduce a systematic methodology grounded in analytical modeling, allowing for the efficient reconciliation of multiple, often conflicting objectives. The explicit functions are analytically modeled to enhance stability and energy economy. Additionally, a fuzzy logic-based torque allocation strategy is developed and compared, along with other literature methods, with the analytical models. Simulations are conducted in a joint simulation between Simulink/Matlab and SCANeR Studio vehicle dynamics simulator, followed by validation on a real-world dataset. Our findings elucidate the proficiency of the analytical models on vehicle performance, stability, computational efficiency, and energy consumption
Design of molecularly imprinted nanogels-based electrochemical sensor for the early detection of a myocardial damage biomarker
No full textInternational audienceMolecularly imprinted nanoparticles (MIP-NPs) are recognition elements obtained upon the polymerization of functional monomers around the target template, that, once removed, reveal selective binding sites in the polymeric matrix enabling the target binding with high specificity. Due to their small size, the binding sites are mostly located at the surface of the polymer, which definitely improves the binding kinetics. Solid-phase synthesis with an excess of the functional monomer NIPAm (N-isopropylacrylamide) confers a thermoresponsive character to the polymers, thus acquiring a solvated gel-like nanometer-sized feature, while the use of a protein epitope avoids the challenging issues related to the whole protein imprinting. Once produced, epitope-imprinted nanogels (MIP-NGs) can be anchored onto the surface of electrochemical transducers, thus leading to the development of selective electrochemical sensors.In this work, MIP-NGs for the cardiac cell damage biomarker cardiac troponin T (cTnT) were anchored onto screen-printed carbon electrodes, enabling a linear impedimetric response in the concentration range 0.01-0.3 ng/mL with a LOD of 0.004 ng/mL. The sensor showed a negligible response towards interfering proteins and a reliable detection of the target protein in undiluted serum. To the best of our knowledge, for the first time an electrochemical sensor based on molecularly imprinted nanogels produced by solid-phase synthesis in aqueous environment with a protein epitope as template was developed for the detection of cTnT. The sensor featured analytical performances comparable to currently available immunoassays, thus showing a striking potential application as alternative tool for myocardial damage biomarker detection
Ordonnancement prédictif/réactif des parcours patients aux urgences
No full textInternational audienceOrdonnancement prédictif/réactif des parcours patients aux urgence
Storage Location Assignment with Mergeable Locations
No full textInternational audienceStorage Location Assignment with Mergeable Location
Multivariate spatial conditional quantiles on hyperspheres in the presence of measurement error
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Lire la romance. Femmes, patriarcat et littérature populaire
No full textInternational audienceÉcrit au début des années 1980, dans un contexte d’émergencedes women studies et des feminist studies au sein des universités améri-caines, Lire la romance s’intéresse à un phénomène culturel alors en pleinessor, qui se décline presque exclusivement au féminin : la consomma-tion de romances. Devenu un véritable best-seller des sciences socialesanglo-américaines, l’ouvrage déploie une méthodologie inédite qui luipermet de saisir les tenants et les aboutissants de ce genre littérairepopulaire, depuis sa production jusqu’à sa réception. Lire la romanceconstitue en particulier la première enquête sociologique sur les lectricesde romances, et contribue par conséquent à démystifier cette pratiquedénigrée et prise en tenaille entre le mépris culturel et la condamnationféministe. La démonstration de l’ouvrage s’articule autour d’une questioncentrale : la lecture de romances renforce-t-elle la culture patriarcale et lessystèmes de croyances qui la soutiennent, ou bien dote-t-elle les femmesd’une forme de pouvoir résultant de la revendication d’une pratique peuconforme à leurs rôles sociaux d’épouses et de mères ?Cette traduction inédite de l’édition de 1991 de Reading the Romancemet à la disposition d’un lectorat francophone un texte majeur pour com-prendre les ressorts d’une culture plus vivante que jamais, à l’heure où lanew et la dark romance rencontrent un succès prodigieux auprès du publicféminin
Phosphorylated lignin: Recent advances in synthesis through chemical functionalization, structural properties, and emerging applications: A review
No full textInternational audienceLignin is the second most abundant renewable source of carbon on earth after cellulose. Large quantities of lignin are generated annually as by-products from pulp mills and biorefinery, motivating extensive efforts toward its valorization and sustainable reuse. Although lignin has been investigated for the production of bio-based materials, chemicals, and advanced biofuels, its low reactivity, structural complexity, and heterogeneity continue to restrict its broader industrial applications. To overcome these limitations, various chemical modification tactics have been developed. Recently, phosphorylation has emerged as a particularly promising method, offering the possibility of introducing phosphorous functional groups that improve thermal stability, increase fire resistance, enhance metal complexation capacity, and promote lignin's compatibility in polymer matrices. This research provides a detailed analysis of recent developments in the chemical modification of lignin by phosphorylation, highlighting advances in synthesis methods, reaction mechanisms, and structure-property relationships. It also explores the multifunctional characteristics of phosphorylated lignin and its potential applications in fire-resistant materials, adsorbents, catalysts, and sustainable composites. Finally, the review discusses contemporary issues and future prospects, highlighting the crucial importance of phosphorylated lignin as a versatile platform for the development of next-generation bio-based materials
Separation and detection of hemicellulose and insights into chemical heterogeneity through capillary electrophoresis
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Feeling Machines: Ethics, Culture, and the Rise of Emotional AI
No full textInternational audienceThis paper explores the growing presence of emotionally responsive artificial intelligence through a critical and interdisciplinary lens. Bringing together the voices of early-career researchers from multiple fields, it explores how AI systems that simulate or interpret human emotions are reshaping our interactions in areas such as education, healthcare, mental health, caregiving, and digital life. The analysis is structured around four central themes: the ethical implications of emotional AI, the cultural dynamics of human-machine interaction, the risks and opportunities for vulnerable populations, and the emerging regulatory, design, and technical considerations. The authors highlight the potential of affective AI to support mental well-being, enhance learning, and reduce loneliness, as well as the risks of emotional manipulation, over-reliance, misrepresentation, and cultural bias. Key challenges include simulating empathy without genuine understanding, encoding dominant sociocultural norms into AI systems, and insufficient safeguards for individuals in sensitive or high-risk contexts. Special attention is given to children, elderly users, and individuals with mental health challenges, who may interact with AI in emotionally significant ways. However, there remains a lack of cognitive or legal protections which are necessary to navigate such engagements safely. The report concludes with ten recommendations, including the need for transparency, certification frameworks, region-specific fine-tuning, human oversight, and longitudinal research. A curated supplementary section provides practical tools, models, and datasets to support further work in this domain
Asymptotic Theory for Multivariate Nonparametric Quantile Regression with Stationary Ergodic Functional Covariates and Missing-at-Random Responses
No full textInternational audienceQuantiles are among the most fundamental constructs in probability theory and statistics, intrinsically linked to order structures, stochastic dominance, and the principles of robust statistical inference. Although the univariate theory of quantiles is by now classical and well developed, their generalization to multivariate settings remains mathematically subtle and methodologically demanding. In particular, extending the notion of “location within a distribution” beyond one dimension raises delicate questions of geometry, ordering, and equivariance. Within this landscape, the spatial—or geometric—formulation of multivariate quantiles has emerged as a rigorous and conceptually unifying framework capable of reconciling these issues. In this work we advance this paradigm by introducing a kernel-based estimation procedure for nonparametric conditional geometric quantiles of a multivariate response Y∈Rq (q≥2) given a functional covariate X that takes values in an infinite-dimensional space. The data are assumed to form a strictly stationary and ergodic process, while the responses may be subject to a missing-at-random mechanism, a feature of substantial practical relevance. Our analysis establishes strong consistency of the proposed estimator, characterizes its optimal convergence rate, and derives its asymptotic distribution. These limit theorems, in turn, provide the theoretical foundation for constructing asymptotically valid confidence regions and for performing inference in multivariate quantile regression with functional covariates. The theoretical developments rest on natural complexity conditions for the involved functional classes together with mild smoothness and regularity assumptions. This balance between generality and mathematical precision ensures that the resulting methodology is not only robust in a rigorous probabilistic sense but also widely applicable to contemporary problems in high-dimensional and functional data analysis. The proposed methodology is numerically investigated through simulations and is implemented in a real data application