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Adaptive federated control: An event-driven MARL framework for fair and efficient traffic management
No full textInternational audienceNext-generation networks require distributed traffic management to handle dynamic loads, but frequent interagent coordination consumes scarce bandwidth. We propose an adaptive federated multi-agent reinforcement learning (Fed-MARL) framework that triggers model synchronization only when congestion is near. Our congestion index combines queue occupancy, latency, and utilization to detect network stress. When the threshold is exceeded, federated learning aggregates distributed agent models using FedAdam. For fairness, we introduce empathy-weighted reward shaping, where agents balance individual rewards with peer performance, aligning selfish routing with system-wide welfare. DDPG agents deployed at edge switches make routing and load balancing decisions. Evaluated on Fat-Tree K=4 topology, Fed-MARL achieves 93% latency reduction vs. RL-MR (7.77 vs 105 ms), 57% vs. DRAMA (18.15 ms), 192.6 Mbps throughput, and perfect delivery with minimal communication overhead
Safety and efficacy of the Atalante exoskeleton in the rehabilitation of French patients with amyotrophic lateral sclerosis: a prospective, monocentric, open, uncontrolled, interventional protocol, EXALS
No full textInternational audienceIntroduction Robotic rehabilitation on locomotion is a new approach in amyotrophic lateral sclerosis (ALS) and previous studies showed its feasibility. In this study, we aim to evaluate safety, patient’s experience and efficacy of a gait training programme with the Atalante exoskeleton, compared with usual care, on walking ability, functional capacity and other symptoms associated with ALS. Methods and analysis EXALS is a monocentric, prospective, interventional, open trial. 20 slowly progressing patients with gait deficits will be recruited. The study is conducted in three phases, each lasting 6 weeks, following the ABA procedure. Phase B represents the intervention phase, during which patients practise their gait training at a rhythm of three sessions/week, as an add-on to usual care. In the two phases A, patients receive usual care with no additional treatment. An evaluation is planned before, in the middle and at the end of each phase. The primary outcome of the study is safety and tolerability of the Atalante exoskeleton. Secondary outcomes include: participants’ subjective impact and experience, attitude and motivation, efficacy and interactivity of the exoskeleton, walking ability, functional capacity, spasticity, balance, postural stability, lower limb muscle strength, quality of life, pain, fatigue, anxiety and depression. Statistical analyses will include descriptive methods for all variables and adverse events. Quantitative outcomes are analysed using repeated-measures ANOVA (analysis of variance) across the seven visits, with post hoc tests applied when appropriate. Nominal outcomes are evaluated using Cochran’s Q test with McNemar pairwise comparisons when significant. Associations between variables are examined using Spearman correlation coefficients. Missing data will be replaced using linear interpolation, and sensitivity analyses will be planned. Qualitative interview data are analysed using thematic analysis. Ethics and dissemination This study was approved by the French ethics committee CPP Nord-Ouest I (no. 23.02378.000201). Participant data are anonymised and securely stored in the laboratory’s database, accessible only to the research team. Results will be disseminated through peer-reviewed journals and conferences
Canadian net forest CO2 uptake enhanced by heat drought via reduced respiration
No full textInternational audienc
Collaborative Action on Timing InterferenCes: Summary and Perspectives at Mid-term
No full textTo appear in Embedded Real Time Systems (ERTS) 2026International audienceCAOTIC is an ambitious initiative aimed at pooling and coordinating the efforts of major French research teams working on timing analysis of multicore real-time systems, with a focus on interference due to shared resources. The objective is to enable the efficient use of multicores in critical systems. Based on a better understanding of timing anomalies and interference, considering the specificities of applications (structural properties and execution model), and revisiting the links between timing analysis and synthesis processes (code generation, mapping, scheduling), we target significant progresses in timing analysis models and techniques for critical systems, as well as in methodologies for their application in industry. In this paper, at project mid-term, we show the progress of the project. We also present some original work, about the use of a Tricore plaform and its timing model, and discuss open questions and future work
Diagonal boundary conditions in critical loop models
No full textInternational audienceIn critical loop models, we define diagonal boundaries as boundaries that couple to diagonal fields only. Using analytic bootstrap methods, we show that diagonal boundaries are characterised by one complex parameter, analogous to the boundary cosmological constant in Liouville theory. We determine disc 1-point functions, and write an explicit formula for disc 2-point functions as infinite combinations of conformal blocks. For a discrete subset of values of the boundary parameter, the boundary spectrum becomes discrete, and made of degenerate representations. In such cases, we check our results by numerically bootstrapping disc 2-point functions. We sketch the interpretation of diagonal and non-diagonal boundaries in lattice loop models. In particular, a loop can neither end on a diagonal boundary, nor change weight when it touches it. In bulk-to-boundary OPEs, numbers of legs can be conserved, or increase by even numbers
Harnessing the XMM-Newton data: X-ray spectral modelling of 4XMM-DR11 detections and 4XMM-DR11s sources
No full textInternational audienceThe XMM-Newton X-ray observatory has played a prominent role in astrophysics, conducting precise and thorough observations of the X-ray sky for the past two decades. The most recent iteration of the 4XMM catalogue and one of its latest data releases DR11 mark significant improvements over previous XMM-Newton catalogues, serving as a cornerstone for comprehending the diverse inhabitants of the X-ray sky. We employ detections and spectra extracted from the 4XMM-DR11 catalogue, subjecting them to fitting procedures using simple models. Our study operates within the framework of the XMM2ATHENA project, which focuses on developing state-of-the-art methods that exploit existing XMM-Newton data. We introduce and publicly release four catalogues containing measurements derived from X-ray spectral modelling of sources. The first catalogue encompasses outcomes obtained by fitting an absorbed power law model to all the extracted spectra for individual detections within the 4XMM-DR11 dataset. The second catalogue presents results obtained by fitting both an absorbed power law and an absorbed blackbody model to all unique physical sources listed in the 4XMM-DR11s catalogue, which documents source detection results from overlapping XMM-Newton observations. For the third catalogue we use the five band count rates derived from the pipe line detection of X-ray sources to mimic low resolution spectra to get a rough estimate of the spectral shape (absorbed power-law) of all 4XMM-DR11 detections. In the fourth catalogue, we conduct spectral analyses for the subset of identified sources with extracted spectra, employing various models based on their classification into categories such as AGN, stars, X-ray binaries, and cataclysmic variables. The scientific potential of these catalogues is highlighted by discussing the capabilities of optical and mid-infrared colours for selecting absorbed AGN. (abridged
Search for exotic Higgs boson decays H with in events with a semi-merged topology in proton-proton collisions at = 13 TeV
No full textInternational audienceA search for exotic Higgs boson decays H , with is presented, using events with a semi-merged topology. One of the hypothetical particles, , is assumed to decay promptly into a semi-merged diphoton system reconstructed as a single photon-like object, while the other decays into two resolved photons. The search is performed using proton-proton collision data collected by the CMS experiment at = 13 TeV, corresponding to an integrated luminosity of 138 fb. The data agree with the standard model background expectation. Upper limits are set on the product of the Higgs boson production cross section and the branching fraction, (pp H)(H 4), which range from 0.264 to 0.005 pb at 95% confidence level, for masses in the range 1 15 GeV. These limits are the most stringent to date in the 15 GeV range
Measurement of inclusive dijet cross-sections in proton-proton collisions at TeV with the ATLAS detector
No full textInternational audienceInclusive dijet cross-sections have been measured in proton-proton collisions at a centre-of-mass energy of 13 TeV using data with an integrated luminosity of 140 fb, recorded by the ATLAS detector at the Large Hadron Collider during 2015-2018. Jets are identified using the anti- algorithm with a radius parameter of . The inclusive dijet double-differential cross-sections are measured first as a function of the invariant dijet mass and the half absolute rapidity separation between the two leading jets, , , and second as a function of the invariant dijet mass and the total longitudinal boost of the dijet system, , . The measured dijet system covers the invariant mass range from 240 GeV to almost 10 TeV, with dijet separation and dijet boost . The results are unfolded to the particle level and compared with state-of-the-art next-to-next-to-leading-order full colour perturbative QCD calculations, corrected for non-perturbative and electroweak effects
Optical Follow-Up Strategies for the Next Neutrino-Detected Galactic Core-Collapse Supernova
No full textInternational audienceCore-collapse supernovae (CCSNe) are expected to produce intense bursts of neutrinos preceding the emergence of their electromagnetic (EM) counterparts. The prompt detection of such neutrino signals offers a unique opportunity to trigger early follow-up observations in the EM domain. We aim to assess the feasibility and efficiency of an optical-NIR follow-up strategy for CCSNe discovered via neutrino bursts, by modelling the spatial distribution of events and simulating realistic observational campaigns taking into account the size of the localization error box generated by triangulating the neutrino burst. We modelled the Galactic distribution of CCSNe, including the effects of interstellar extinction, and considered three main progenitor types: Wolf-Rayet stars, red and blue supergiants. We included the shock breakout in the EM signatures that could be detected following the neutrino burst. A population of CCSNe was generated and detected by different networks of neutrino observatories, including IceCube, KM3NeT, Super-Kamiokande, Hyper-Kamiokande, and JUNO. The resulting skymaps were used as input for GWEMOPT to produce optimized follow-up plans with two optical facilities: LSST and the TAROT robotic telescopes. Both LSST and TAROT exhibit comparable detection efficiencies for the simulated CCSN population. However, the TAROT network achieves similar success rates while requiring fewer pointings to cover the CCSN skymap. Our simulations demonstrate that neutrino follow-up campaigns can effectively CCSN optical counterparts using both large and small facilities. Depending on the neutrino network, the median number of pointings for the two tested optical facilities is of the order of 20 to 100 to find the EM emission. The number of images is larger for LSST than for TAROT by a factor of 2 to 4
Proof of Concept of a Real-Time Fluid Dynamics Model for Immersive Environments Using Artificial Intelligence
No full textInternational audienceReal-time simulation of fluid fields remains a major challenge in virtual and augmented reality (VR/AR)applications due to the high computational cost of traditional Computational Fluid Dynamics (CFD)methods. This work presents a proof of concept for a surrogate model based on artificial intelligencemethods, capable of dynamically predicting the evolution of a fluid field in response to interactions fromoperators or equipment in an interactive simulation.The developed model leverages Graph Neural Networks (GNNs), specifically the MeshGraphNetarchitecture [1]. The model was trained on precomputed CFD datasets of a simple 3D domain, consideringan incompressible low-Reynolds flow. It enables fast inference, compatible with real-timeconstraints—targeting a field update every second. The model was successfully integrated into an interactivesimulation environment (Unity), allowing quasi-real-time visualization of the predicted stationaryfluid field, as represented in figure 1.To improve physical consistency, early efforts were made to incorporate physics-informed loss functions,based on Physics-Informed Neural Networks (PINNs) [2]. A partial residual of the continuityequation was introduced during training, with promising results. Future developments include a morerigorous integration of the full Navier-Stokes equations in the loss function