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L'éthique des likes : les influenceurs face aux défis de la durabilité
No full textInternational audienceEn se basant sur la consultation publique menée en France en 2023 sur le marketingd’influence, cet article examine la perception par le grand public des influenceurs et de leurspratiques face aux défis environnementaux. L’analyse des réponses à la consultation révèle unecritique significative des influenceurs s’agissant de leur rôle dans la promotion de lasurconsommation et de leur impact sur l'environnement. Il en ressort une demande pour une plusgrande transparence et authenticité de la part des influenceurs en matière de placement de produits,ainsi qu'une sensibilisation accrue aux enjeux environnementaux. In fine, notre recherche met enlumière l'importance pour les influenceurs de contribuer à la durabilité et à la responsabilitéenvironnementale, tout en répondant aux attentes croissantes des consommateurs en matière decomportements éthiques et durables
Verification Gestures by Twitter Users: Media Materials and Vernacular Investigations
No full textInternational audienceThis article summarises a four-year research experiment (2018-2022) conducted as part of the ANR VIJIE project, exploring information verification practices. It focuses on the vernacular practices of Twitter users engaged in independent investigations and critical actions on the platform. Taking inspiration from digital ethnography, the authors provide insights into their methodology, which involved collecting diverse media materials related to “fake news” and fact-checking, emphasising the significance of private messages (DMs) in this project’s aims. The article outlines three key dimensions for analysing these vernacular investigations—figures, events, and gestures—that reflect on the evolving landscape of information verification and fact-checking practices using socio-semiotic and documentary perspectives. This study and its thematic collections of screenshots and publications contribute to a deeper cultural understanding of verification gestures within digital spaces
Physics-based reverse recovery modelling of ultrafast recovery Si diodes with carrier lifetime control
No full textInternational audienceUltrafast recovery diodes are often used in high frequency switching applications because of their ability to switch from the ON-state to OFF-state very quickly. However, ultrafast recovery diode switching performances are very difficult to predict using Technology Computer-Aided Design (TCAD) simulation tools, especially when carrier lifetime is adjusted. To model carrier lifetime, the Shockley-Read-Hall (SRH) recombination theory is used in TCAD tools as a standard simulation model. This model is not sufficient as it considers the presence of only one deep energy level located at the material mid-gap. Used as a carrier lifetime killer, platinum doping introduces several deep energy levels facilitating the minority carrier recombination. Thus, this paper presents a new approach based on trap physical modelling. Trap characteristics are determined using Deep Level Transient Spectroscopy (DLTS) measurement technique. This approach can significantly reduce the large mismatch observed between the ultrafast recovery diode turn-off measurements and the standard simulation model results
Comparison Between CNN and GNN Pipelines for Analysing the Brain in Development
No full textInternational audienceIn this study, we present a new pipeline designed for the analysis and comparison of non-conventional animal brain models, such as sheep, without relying on neuroanatomical priors. This innovative approach combines an automatic MRI segmentation with graph neural networks (GNNs) to overcome the limitations of traditional methods. Conventional tools often depend on predefined anatomical atlases and are typically limited in their ability to adapt to the unique characteristics of developing brains or non-conventional animal models. By generating regions of interest directly from MR images and constructing a graph representation of the brain, our method eliminates biases associated with predefined templates. Our results show that the GNN-based pipeline is more efficient in terms of accuracy for an age prediction task (63.22%) compared to a classical CNN architecture (59.77%). GNNs offer notable advantages, including improved interpretability and the ability to model complex relational structures within brain data. Overall, our approach provides a promising solution for unbiased, adaptable, and interpretable analysis of brain MRIs, particularly for developing brains and non-conventional animal models
Can the Protection of Legal Vulnerability Go Too Far? When Well-meaning Policies Backfire in Recent French Constitutional Case Law on Property Law.
No full textInternational audienceMPs animated by good intentions aim to achieve positive outcomes. However, good-heartedness alone is insufficient to withstand the rigorous test of constitutional review for their reform bill. Three recent case laws in property law illustrate this idea. Each time, the same question returns: has the well-meaning policy of protecting vulnerability gone too far and created a violation of the constitu-tional right of property
Continuous Petri Nets Faithfully Fluidify Most Permissive Boolean Networks
No full textInternational audienceThe analysis of biological networks has benefited from the richness of Boolean networks (BNs) and the associated theory. These results have been further fortified in recent years by the emergence of Most Permissive (MP) semantics, combining efficient analysis methods with a greater capacity of explaining pathways to states hitherto thought unreachable, owing to limitations of the classical update modes. While MPBNs are understood to capture any behaviours that can be observed at a lower level of abstraction, all the way down to continuous refinements, the specifics and potential of the models and analysis, especially attractors, across the abstraction scale remain unexplored. Here, we fluidify MPBNs by means of Continuous Petri nets (CPNs), a model of (uncountably infinite) dynamic systems that has been successfully explored for modelling and theoretical purposes. CPNs create a formal link between MPBNs and their continuous dynamical refinements such as ODE models. The benefits of CPNs extend beyond the model refinement, and constitute well established theory and analysis methods, recently augmented by abstract and symbolic reachability graphs. These structures are shown to compact the possible behaviours of the system with focus on events which drive the choice of long-term behaviour in which the system eventually stabilises. The current paper brings an important keystone to this novel methodology for biological networks, namely the proof that extant PN encoding of BNs instantiated as a CPN simulates the MP semantics. In spite of the underlying dynamics being continuous, the analysis remains in the realm of discrete methods, constituting an extension of all previous work.</div
SGSST: Scaling Gaussian Splatting Style Transfer
No full textApplying style transfer to a full 3D environment is a challenging task that has seen many developments since the advent of neural rendering. 3D Gaussian splatting (3DGS) has recently pushed further many limits of neural rendering in terms of training speed and reconstruction quality. This work introduces SGSST: Scaling Gaussian Splatting Style Transfer, an optimization-based method to apply style transfer to pretrained 3DGS scenes. We demonstrate that a new multiscale loss based on global neural statistics, that we name SOS for Simultaneously Optimized Scales, enables style transfer to ultra-high resolution 3D scenes. Not only SGSST pioneers 3D scene style transfer at such high image resolutions, it also produces superior visual quality as assessed by thorough qualitative, quantitative and perceptual comparisons
Correction: Identifying the needs of natural caregivers caring for a person with dementia: a mixed method study
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Repetitive Transcranial Magnetic Stimulation targeted with MRI based neuro-navigation in major depressive episode: a double-blind, multicenter randomized controlled trial
No full textInternational audienceContext: High-frequency (HF) transcranial magnetic stimulation (rTMS) of the left dorsolateral prefrontal cortex (DLPFC) is widely used in Major Depressive Episode (MDE). Optimization of its efficacy with a neuro-navigation system has been proposed based on a small randomized controlled trial (RCT) supporting a large effect.Method: This evaluator- and patient-blind, multicenter RCT assessed the superiority in terms of efficacy of 10 HF rTMS sessions of the left DLPFC targeted with MRI based neuro-navigation versus similar sessions targeted by the standard 5 cm technique. The study was conducted between January 2013 and April 2017, at 4 hospitals centers in France where both in- and out- patients with MDE were included. Randomization was computer-generated (1:1), with allocation concealment implemented within the e-CRF. The main outcome measure was the percentage of responders 44 days (D44) after the rTMS session. Secondary outcomes were percentage of remitters, Beck Depression Inventory and psychomotor retardation assessed with Salpêtrière retardation rating scale (SRRS) for depression at D14 and D44. The results are presented along with their 95% confidence intervals.Results: 105 patients were randomized and 92 were evaluable with respectively 45 patients in the neuronavigation group and 47 in the standard group. A treatment response was observed for 14 (31.8%) of 44 patients analyzed in the intervention group, and for 16 (35.6%) of 45 patients analyzed in the control group with no statistical difference (relative risk 0.89; 95% confidence interval, [0.50;1.61]). No difference was evidenced for secondary outcomes at D44 whether it concerns remission at D44 (relative risk, 0.82; 95% CI, 0.36 to 1.88), or BDI results (difference in means, 0,01; 95% CI, -3.06 to 3.26), or SRRS results (difference in means, 0.11; 95% CI, -2.42 to 5.02). Similar results were observed at D14. Rates of adverse events were similar in both groups with 23 (47.9%) and 1 (2.1%) of adverse events and serious adverse events in the neuro-navigation group versus 20 (40.8%) and 0 (0%) in the standard group.Discussion: This study failed to reproduce previous findings supporting the use of neuro-navigation system to optimize rTMS efficacy. Limitations of this study includes a small sample size and a number of rTMS sessions that may appear substandard in 2025.Trial registration: NCT01677078
Rho-dependent transcription termination: mechanisms and roles in bacterial fitness and adaptation to environmental changes
No full textInternational audienceThe bacterial transcription termination factor Rho is a rare example of an RNA helicase that functions as a ring-shaped ATP-powered six-subunit motor. Recent studies have linked Rho’s distinctive architecture to a variety of regulatory mechanisms that shape the bacterial transcriptome at the global scale and control the transcription of individual genes in a context-dependent manner. In this review, we provide a comprehensive overview of the molecular mechanisms by which Rho triggers transcription termination. We examine the two prevailing modes of Rho's action: the "catch-up" mode, where Rho actively translocates along RNA and collides with the RNA polymerase to terminate transcription, and the "stand-by" mode where Rho, recruited by transcription elongation factor NusG, remains poised to engage RNA polymerase at specific sites or under particular constraints. Additionally, we highlight Rho’s interplay with nucleoid-structuring protein H-NS in the regulation of bacterial chromatin transcription, as well as the crucial role played by Rho in the conditional regulation of specific genomic loci. We discuss how these mechanisms contribute to the fine-tuning of gene activity and integrate into broader regulatory networks, supporting bacterial adaptation to environmental changes and resilience to external challenges