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Inclusive production at midrapidity in pp collisions at TeV
No full textInternational audienceInclusive production of mesons is measured for the first time at midrapidity () in pp collisions at TeV using the ALICE detector at the LHC. The measurement is performed in the transverse-momentum () range of 4 to 16 GeV/ and is based on events triggered by the Transition Radiation Detector, corresponding to an integrated luminosity of (syst.) pb. The -differential production cross section of the and its ratio to the J/ production cross section are presented. The results extend the accessible range down to 4 GeV/, and a mild rise of the -to-J/ cross section ratio with increasing is observed. The measurements are compared with theoretical predictions based on NRQCD and the ICEM model
SCHC Header Compression for GeoNetworking protocol: Adaptation and Performance Evaluation
No full textInternational audienceThe growing number of autonomous vehicles (AVs) significantly increases wireless network load, mainly due to the frequent exchange of safety messages such as Cooperative Awareness Messages (CAMs). A common strategy to mitigate this congestion is to compress application-layer data in these messages. However, a detailed analysis indicates that the GeoNetworking protocol, used for routing in ITS-G5 networks, represents a substantial part of the message overhead (about 40% of the size of an unsigned CAM). Therefore, we propose compressing this protocol using a generic header compression framework-Static Context Header Compression (SCHC). Our work adapts SCHC framework to the GeoNetworking protocol by defining two distinct compression rules. One of these rules is generic, provides lower compression, and can be pre-installed in all SCHCsupported vehicles. The second rule aggressively compresses the packet by leveraging the local conditions and can be optimised for a group of AVs, providing additional compression. In addition, we assess the effects of SCHC compression on an IEEE 802.11p based ITS-G5 network by estimating the Channel Busy Ratio (CBR) and Packet Delivery Ratio (PDR) using analytical models and measuring the time on-air of SCHC compressed CAMs. Our findings indicate that by reducing time on-air by 13%, the compressed CAMs can decrease CBR by up to 19% and increase PDR by up to 6%. Moreover, they incur an additional overhead of approximately 5% for compression and 2% for decompression on the YoGoKo on-board unit
Reinforcement Learning-Based Antenna and Time Adaptation Energy-Efficient Strategies in 6G Networks
No full textInternational audienceAmong the strategies for improving the energy efficiency of 5G and beyond networks, sleep-mode control remains one of the most promising techniques for reducing the power consumption of base stations (BSs). The recently standardized 3GPP TR 38.864 BS energy model provides a realistic framework for analyzing multi-level sleep modes and energy-saving mechanisms in next-generation networks. Building upon this model, this paper investigates joint antenna and time adaptation for energy-efficient BS control. The proposed approach allows the BS to autonomously adjust both its temporal activity and antenna usage according to the traffic load. To this end, we design a reinforcement learning (RL) framework in which the BS acts as an intelligent agent that jointly selects the sleepmode level and the number of active antennas. The cost function balances energy consumption and achievable throughput, while penalizing excessive power use and rate shortages. Simulation results based on the 3GPP TR 38.864 power model show that the proposed joint antenna-time adaptation achieves up to 50% power savings compared to time-only adaptation and about 94% compared to antenna-only adaptation, while maintaining satisfactory throughput performance. These results confirm that combining antenna deactivation with time adaptation provides an efficient and scalable solution for energy-aware 6G base-station control
Disentangling Initial-State and Evolution Effects in Heavy-Ion Collisions Using EPOS and PHSD
No full textInternational audienceIn this study we examine the impact of the initial stage and dynamical evolution on final-state observables in heavy-ion collisions. For this goal we develop a novel approach, EPOSir+PHSDe, which employs EPOS initial conditions as the starting point for parton and hadron evolution within the PHSD microscopic transport approach. By examining the space-time evolution of matter in this model and comparing to EPOS (which starts with an S-matrix approach for parallel scatterings for the initial conditions and uses a hydrodynamic evolution for the quark-gluon plasma stage with the UrQMD as afterburner) and PHSD (which starts with primary high energy scattering realized via the LUND string model and continues with fully microscopic transport dynamics for strongly interacting partonic and hadronic matter), we identify the key differences in the final particle distributions among the three approaches. Our analysis focuses on rapidity, transverse momentum spectra, and flow harmonics for Au+Au collisions at the invariant energy of GeV. We find a dominant influence of dynamical evolution over the initial conditions on the final observables
Shapley value to rank vulnerabilities on attack graphs: Applications to cyberdeception
No full textInternational audienc
Planning robust routes and charging schedules under energy consumption uncertainty
No full textNational audienceElectric vehicle (EV) routing faces significant operational challenges due to limited driving range, charging constraints, and uncertainty in energy consumption. This project addresses the Electric Vehicle Routing and Overnight Charging Scheduling Problem under energy consumption uncertainty, assuming exclusive depot-based overnight charging. Energy consumption on each arc is modeled as a bounded random variable and incorporated through a budgeted robust optimization framework. The resulting problem is solved using a Branch-and-Price-and-Cut algorithm based on a route-based set partitioning formulation. Robust feasibility is ensured directly within the pricing problem through an adapted labeling algorithm, while subset-row cuts and an enhanced hierarchical branching scheme accelerate convergence. Computational experiments highlight the trade-off between routing cost and protection against uncertainty, and demonstrate how robustness impacts charging schedules and route departure times
Evaluating the Realism of Cyber-Physical Honeynets Against Advanced Attackers
No full textCyber-physical honeynets are increasingly deployed to study adversarial behavior in operational technology (OT) and industrial control systems (ICS), yet their effectiveness depends on their perceived realism. This work presents a multi-stage research program systematically characterizing, measuring, and quantifying the realism of cyber-physical honeynets against advanced attackers. First, we conduct two systematic literature reviews: one on cyber-physical honeynets, producing an updated taxonomy and a reference architecture, and another on anti-honeypot techniques, revealing a critical gap between academic detection methods and real-world adversarial practices. We then empirically investigate attacker behavior through a large-scale Capture-the-Flag (CTF) experiment, analyzing 8,544 shell commands to identify real-world anti-honeypot strategies and behavioral indicators of perceived authenticity. Building on these insights, we propose a novel evaluation methodology using real threat actors and ICS-targeting malware to derive quantitative metrics of honeypot realism. Finally, we outline the design of an automated pentesting framework that operationalizes validated detection techniques to compute a reproducible Realism Score for heterogeneous honeypot deployments
A newly developed selective grafted resin for radium
No full textInternational audienceAbstract Radium analysis in natural waters remains a current challenge in the field of radiological monitoring, as well as for environmental concerns. A new Ra-selective grafted resin was developed in the present work; a calix[4]arene derivative functionalized with a crown-6 ether and two synergistic carboxylic groups serves as the selective chelating agent, while the support consists of SiO 2 . Its properties were investigated in the laboratory by coupling experimental data with a modelling approach. The resin was shown to be efficient for Ra within the pH range typical of natural waters (∼6–8). Its affinity for Ra was significantly higher than for other alkaline earth cations, although it remained sensitive to salt loading. This trend was confirmed by batch sorption tests conducted with both synthetic aqueous media and various natural water samples. The proposed resin appears promising for radium extraction and pre-concentration from natural waters
Analyse du développement cérébral précoce par recalage d'IRM longitudinales basée sur un champ de vélocité stationnaire
No full textNational audienc
Biclique Factorisation of Explanations for a Sparser Implication Graph in Lazy Clause Generation
No full textIn the context of lazy clause generation, we propose factorising bicliques in the implication graph to reduce the associated overhead. This process consists of (1) identifying a set P of prunings that share a common subset L of literals in their reason, (2) introducing an artificial literal f , called a factor, and 3) adding the arcs (L × f ) ∪ (f × P ) to the implication graph instead of the arcs L × P . When P and L are large, biclique factorisation significantly reduces the number of generated arcs. This technique offers two main advantages: (1) faster explanation generation and (2) a sparser implication graph, leading to more efficient conflict analysis and reduced memory usage. We provide tight worst-case bounds on both the time complexity of explanation generation and the maximum number of generated arcs for two global constraints: alldifferent and cumulative. Experiments were also conducted to evaluate and validate our approach.</div