Scientific Publications of the University of Toulouse II Le Mirail
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Aesthetics Matter: Driving Credibility, Purchase Intent, and Learning Motivation in Digital Education by using Aesthetic Experience
No full textIn a progressively competitive landscape, particularly in online education and training, it is essential to distinguish oneself to attract learners and, consequently, customers. Research indicates the significance of a website's credibility in shaping the intention to purchase a service, while other studies demonstrate the effect of a teacher's credibility on learning motivation. Researchers have demonstrated that a significant role in an individual's evaluation of believability is contingent upon visual appearance, or "aesthetics." Other researchers have also demonstrated that individuals' aesthetic experience impacts how they perceive and evaluate aesthetic. This is why we wanted to find out if an individual would be more predisposed to select a site deemed aesthetically pleasing over one that was not perceived as such, given identical training content. Consequently, we assessed two training websites, one deemed "aesthetic" and the other "non-aesthetic," randomly assigned to two groups of participants (totalling 82). We also evaluated the aesthetic experience of the participants. The findings of the study indicate a preference for the "aesthetic" site regarding the assessment of site credibility, training credibility, purchase intention, and learning motivation. We also found that having artistic expertise impacted evaluations: While experts were generally more critical, this effect was primarily observed for the non-aesthetic website. The positive impact of aesthetics on perceived credibility, purchase intention, and motivation to learn was consistent regardless of the individual's level of artistic expertise.</div
MEDICAL KNOWLEDGE INTEGRATION INTO REINFORCEMENT LEARNING ALGORITHMS FOR DYNAMIC TREATMENT REGIMES
No full textThe goal of precision medicine is to provide individualized treatment at each stage of chronic diseases, a concept formalized by Dynamic Treatment Regimes (DTR). These regimes adapt treatment strategies based on decision rules learned from clinical data to enhance therapeutic effectiveness. Reinforcement Learning (RL) algorithms allow to determine these decision rules conditioned by individual patient data and their medical history. The integration of medical expertise into these models makes possible to increase confidence in treatment recommendations and facilitate the adoption of this approach by healthcare professionals and patients. In this work, we examine the mathematical foundations of RL, contextualize its application in the field of DTR, and present an overview of methods to improve its effectiveness by integrating medical expertise
Tracking objects that change in appearance with phase synchrony
No full textInternational audienceObjects we encounter often change appearance as we interact with them. Changes in illumination (shadows), object pose, or movement of nonrigid objects can drastically alter available image features. How do biological visual systems track objects as they change? It may involve specific attentional mechanisms for reasoning about the locations of objects independently of their appearances -- a capability that prominent neuroscientific theories have associated with computing through neural synchrony. We computationally test the hypothesis that the implementation of visual attention through neural synchrony underlies the ability of biological visual systems to track objects that change in appearance over time. We first introduce a novel deep learning circuit that can learn to precisely control attention to features separately from their location in the world through neural synchrony: the complex-valued recurrent neural network (CV-RNN). Next, we compare object tracking in humans, the CV-RNN, and other deep neural networks (DNNs), using FeatureTracker: a large-scale challenge that asks observers to track objects as their locations and appearances change in precisely controlled ways. While humans effortlessly solved FeatureTracker, state-of-the-art DNNs did not. In contrast, our CV-RNN behaved similarly to humans on the challenge, providing a computational proof-of-concept for the role of phase synchronization as a neural substrate for tracking appearance-morphing objects as they move about
LapisGS: Layered Progressive 3D Gaussian Splatting for Adaptive Streaming.
No full textInternational audienceThe rise of Extended Reality (XR) requires efficient streaming of 3D online worlds, challenging current 3DGS representations to adapt to bandwidth-constrained environments. This paper proposes LapisGS, a layered 3DGS that supports adaptive streaming and progressive rendering. Our method constructs a layered structure for cumulative representation, incorporates dynamic opacity optimization to maintain visual fidelity, and utilizes occupancy maps to efficiently manage Gaussian splats. This proposed model offers a progressive representation supporting a continuous rendering quality adapted for bandwidth-aware streaming. Extensive experiments validate the effectiveness of our approach in balancing visual fidelity with the compactness of the model, with up to 50.71% improvement in SSIM, 286.53% improvement in LPIPS with 23% of the original model size, and shows its potential for bandwidth-adapted 3D streaming and rendering applications
Rank conditions for exactness of semidefinite relaxations in polynomial optimization
No full textInternational audienceWe consider the Moment-SOS hierarchy in polynomial optimization. We first provide a sufficient condition to solve the truncated K-moment problem associated with a given degree-2n pseudo-moment sequence φ n and a semi-algebraic set K ⊂ R d . Namely, let 2v be the maximum degree of the polynomials that describe K. If the rank r of its associated moment matrix is less than nv + 1, then φ n has an atomic representing measure supported on at most r points of K. When used at step-n of the Moment-SOS hierarchy, it provides a sufficient condition to guarantee its finite convergence (i.e., the optimal value of the corresponding degree-n semidefinite relaxation of the hierarchy is the global minimum). For Quadratic Constrained Quadratic Problems (QCQPs) one may also recover global minimizers from the optimal pseudo-moment sequence. Our condition is in the spirit of Blekherman's rank condition and while on the one-hand it is more restrictive, on the other hand it applies to constrained POPs as it provides a localization on K for the representing measure
Faire des films en géographie. Prendre (Dés)engagements
No full textInternational audienceQuelques géographes épris(es) d'une envie de liberté (Chenet, 2016), de chemins de traverses et d'horizons incertains, désireux de créativité dans l'écriture scientifique, peutêtre même de poésie, font des films en géographie. Et se lancent comme cela, dans des expériences, géographiques et cinématographiques, qui portent et défendent une autre forme de parcours et de narration des lieux, de restitution et de partage des espaces voyagés. Dans laquelle la pratique du terrain par le regard se fait peut-être plus incarnée et où les savoirs géographiques, construits autrement, sont plus reliés aux sensibles. Dans/avec/et par cette démarche de « géographies filmées », ces « géographes filmeurs » s'insinuent dans les sillons déjà creusés entre autres par Jean Brunhes, Claude Collin Delavaux ou Béatrice Collignon. Cette recherche, visuelle et sonore, marginale et académiquement mal considérée (même si les postures changent doucement), pose précisément cette question de l'engagement à réaliser des films pour chercher. Plutôt même (dés)engagements en ombres portées.(Dés)engagement par exemple à ne limiter la pratique de la recherche, de son sujet à la présentation des résultats, qu'à la seule forme écrite. Alors engagement à « déverrouiller », avec le cinéma, d'autres formes de langages géographiques (Brunhes, 1914).(Dés)engagement encore à ne produire qu'une seule géographie, comptable, plus « sérieuse », dans laquelle les structures, les unités, les mesures, les surfaces en aplats de couleurs, les chiffres en analyses factorielles et en classifications hiérarchiques possèdent l'exclusivité de la validité scientifique, de la preuve par le renseignement quantitatif. Et engagement à porter en géographie filmée ces transparences insaisissables de l'émoi, à réhabiliter ces sens et ces émotions -désignées comme perturbant le raisonnement -en montrant qu'elles accompagnent toujours la pensée, qu'elles en sont indissociables parce qu'explicatives (Damasio, 1995 ; Arnheim, 1969) Ne plus apporter systématiquement de preuves chiffrées mais porter une attention aux perceptions affectives pour témoigner des épreuves vécues. En entrant dans une géographie de plein vent (Schuiten et Peteers, 2012) et peut-être même dans une géographie du bien-être, questionnant le lien entre sciences et bonheur (Bailly 2016).Ce sont donc ici, dans ce chapitre « heureusement libre de forme et de fond », de ces positions en convictions, prises de risques et autres résistances aux chemins académiques tout tracés pour ne pas dire imposés, dont il s'agit de discuter pour interroger l'engagement/le dégagement. Tout cela dans le creux d'une expérience, géographique et</div
Afflecto: A Web Server to Generate Conformational Ensembles of Flexible Proteins from Alphafold Models
No full textIntrinsically disordered proteins and regions (IDPs/IDRs) leverage their structural flexibility to fulfill essential cellular functions, with dysfunctions often linked to severe diseases. However, the relationships between their sequences, structural dynamics and functional roles remain poorly understood. Understading these complex relationships is crucial for therapeutic development, highlighting the need for methods that generate ensembles of plausible IDP/IDR conformers. While AlphaFold (AF) excels at modeling structured domains, it fails to accurately represent disordered regions, leaving a significant portion of proteomes inaccurately modeled. We present AFflecto, a user-friendly web server for generating large conformational ensembles of proteins that include both structured domains and IDRs from AF structural models. AFflecto identifies IDRs as tails, linkers or loops by analyzing their structural context. Additionally, it incorporates a method to identify conditionally folded IDRs that AF may incorrectly predict as natively folded elements. The conformational space is globally explored using efficient stochastic sampling algorithms. AFflecto's web interface allows users to customize the modeling, by modifying boundaries between ordered and disordered regions, and selecting among several sampling strategies. The web server is freely available at https://moma.laas.fr/applications/AFflecto/.</div
