Scientific Publications of the University of Toulouse II Le Mirail
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Toulouse (31), 1-3 rue Alfred Rambaud: Rapport Final d'Opération d'Archéologie Préventive
No full textAchevée au mois de mai 2023, la fouille préalable à l’aménagement d’un immeuble d’habitation au 1-3 rue Alfred Rambaud à Toulouse est intervenue à la suite d’un diagnostic réalisé par Toulouse Métropole (Verrier 2022). Sur les 830m² ouverts, le site a livré des vestiges essentiellement datés de La Tène D qui se rattachent à l’agglomération gauloise de Toulouse, dans le quartier Saint Roch, connue depuis le 19e siècle. Globalement les structures fouillées sont des niveaux de d’amphores fragmentés à plat ayant eu pour fonction de stabiliser et/ou drainer des niveaux de circulation, des sols d’habitation ou des espaces ouverts. Ces épandages d’amphore se retrouvent partout dans le quartier au travers des diverses opérations archéologiques menées depuis plusieurs décennies. Sur l’emprise concernée, l’état de conservation de ces sols est mauvais à moyen et la densité faible peut être liée au caractère périphérique de la parcelle dans l’agglomération gauloise ou au fait que l’on se trouve en zone peu densément habitée avec des espaces dédiés au pacage d’animaux et à de la culture à échelle domestique.Un puits qui avait été repéré et testé lors du diagnostic a également été fouillé intégralement. Un sondage mécanique a été ouvert à la tangente de l’arc NO de la structure afin de la fouiller manuellement couche par couche depuis l’extérieur. Le creusement du puits est de forme circulaire dans le premier mètre et demi, avant de devenir quadrangulaire pour enfin s’achever en cuvette circulaire dans le fond. La partie supérieure du puits était comblée par des rejets massifs d’amphores, dont plusieurs individus entiers. Les niveaux inférieurs d’abandon et d’utilisation recelaient du mobilier céramique, amphorique et faunique moins dense
Représentations sociales autour de la citoyenneté dans l’enfance : une analyse lexicométrique de publications européennes
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Prolonged acyclovir therapy for Herpes simplex virus (HSV)-1–associated hepatitis in an immunocompetent man
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Soliciting sex : how far is it acceptable to go ?
No full textInternational audienceThe acceptability of sexual solicitation is a complex issue shaped by societal norms, relationship dynamics, and attitudes toward consent. Despite its importance, the application of Information Integration Theory to the study of sexual solicitation acceptability remains unexplored, which is the focus of the present study. A sample of 434 French laypeople read 42 scenarios depicting situations in which a man initiates a sexual interaction with his partner. The scenarios included five factors: duration of the relationship, type of sexual act requested, partner's behavior, verbal consent, and discernment. Verbal consent and partner behavior were the most influential factors in respondents' judgments, followed by the type of sexual act requested and the duration of the relationship. Cluster analysis revealed five groups: “Always Acceptable”, “Need for Audible and Visible Consent”, “Depends on Behavior”, “Depends on Verbal Consent”, and “Never Acceptable”. Most participants showed sensitivity to the situational context, which played a key role in shaping their judgments about the acceptability of sexual solicitation. These findings highlight the nuanced ways in which contextual factors influence perceptions of sexual solicitation, providing valuable insights for future research and public education on consent
Evolution of Measures in Nonsmooth Dynamical Systems: Formalisms and Computation
No full textInternational audienceThis article develops mathematical formalisms and provides numerical methods for studying the evolution of measures in nonsmooth dynamical systems using the continuity equation. The nonsmooth dynamical system is described by an evolution variational inequality and we derive the continuity equation associated with this system class using three different formalisms. The first formalism consists of using the {superposition principle} to describe the continuity equation for a measure that disintegrates into a probability measure supported on the set of vector fields and another measure representing the distribution of system trajectories at each time instant. The second formalism is based on the regularization of the nonsmooth vector field and describing the measure as the limit of a sequence of measures associated with the regularization parameter. In doing so, we obtain quantitative bounds on the Wasserstein metric between measure solutions of the regularized vector field and the limiting measure associated with the nonsmooth vector field. The third formalism uses a time-stepping algorithm to model a time-discretized evolution of the measures and show that the absolutely continuous trajectories associated with the continuity equation are recovered in the limit as the sampling time goes to zero. We also validate each formalism with numerical examples. For the first formalism, we use polynomial optimization techniques and the moment-SOS hierarchy to obtain approximate moments of the measures. For the second formalism, we illustrate the bounds on the Wasserstein metric for an academic example for which the closed-form expression of the Wasserstein metric can be calculated. For the third formalism, we illustrate the time-stepping based algorithm for measure evolution on an example that shows the effect of the concentration of measures
Towards Designing an Energy Aware Data Replication Strategy for Cloud Systems Using Reinforcement Learning
No full textInternational audienceThe rapid growth of global data volumes has created a demand for scalable distributed systems that can maintain a high quality of service. Data replication is a widely used technique that provides fault tolerance, improved performance and higher availability. Traditional implementations often rely on threshold-based activation mechanisms, which can vary depending on workload changes and system architecture. System administrators typically bear the responsibility of adjusting these thresholds. To address this challenge, reinforcement learning can be used to dynamically adapt to workload changes and different architectures. In this paper, we propose a novel data replication strategy for cloud systems that employs reinforcement learning to automatically learn system characteristics and adapt to workload changes. The strategy's aim is to provide satisfactory Quality of Service while optimizing a trade-off between provider profit and environmental impact. We present the architecture behind our solution and describe the reinforcement learning model by defining the states, actions and rewards
Aux côtés de Claude, Jacqueline Chevalley
No full textC’est au croisement des innombrables documents d’archives du fonds Alexandre Marc aux Archives de l’Union européenne et des photos inédites dévoilées par les nièces de Jacqueline Chevalley que s’écrit cet article. Nous allons nous immerger dans la période de l’entre-deux-guerres et voyager entre les espoirs du mouvement des non-conformistes des années 1930 et l’effervescence des premiers Bourbaki. Cela nous amènera à découvrir l’histoire de la jeunesse de Jacqueline et Claude Chevalley sous un nouveau jour, suivant le parcours d’émancipation de Jacqueline : femme intelligente et déterminée, elle sut trouver son chemin aux côtés du brillant mathématicien Claude Chevalley, dans un monde où beaucoup de femmes avaient encore peu de prise sur leur destin.Les documents du fonds Alexandre Marc m'ont été généreusement confiés par Norbert Schappacher
Detecting fast-ripples on both micro- and macro-electrodes in epilepsy: A wavelet-based CNN detector
No full textInternational audienceFast-ripples (FR) are short (∼10 ms) high-frequency oscillations (HFO) between 200 and 600 Hz that are helpful in epilepsy to identify the epileptogenic zone. Our aim is to propose a new method to detect FR that had to be efficient for intracerebral EEG (iEEG) recorded from both usual clinical macro-contacts (millimeter scale) and microwires (micrometer scale)
Learning Weighted Least Squares Data Term for Poisson Image Deconvolution
No full textInternational audienceWeighted least squares are often used to approximate log-likelihoods when solving inverse problems involving non-Gaussian noise as they are more appealing from an optimization perspective. Although a theoretical expression of the weights can be derived for specific noises, this may become intractable for more general noises. Moreover, such theoretical weights can be detrimental to the efficiency of optimization algorithms. To remedy these issues, we propose in this work to learn the weights from data so as to adapt to any general noise while maintaining the efficiency of optimization. The proposed pipeline combines a weight estimation module with an unrolled optimization algorithm. The weight estimation module and a few parameters of the unrolled algorithm are trained together in an end-to-end manner. We demonstrate the effectiveness of the proposed methodology in the context of Poisson image deconvolution