On approximation of processing times of semiconductor manufacturing Research & Development operations

International audienceOn approximation of processing times of semiconductor manufacturing Research & Development operation

Hadron Physics Opportunities at FAIR

International audienceThis White Paper outlines a coordinated, decade-spanning programme of hadron and QCD studies anchored at the GSI/FAIR accelerator complex. Profiting from intense deuteron, proton and pion beams coupled with high-rate capable detectors and an international theory effort, the initiative addresses fundamental questions related to the strong interaction featuring confinement and dynamical mass generation. This includes our understanding of hadron-hadron interactions and the composition of hadrons through mapping the baryon and meson spectra, including exotic states, and quantifying hadron structure. This interdisciplinary research connects topics in the fields of nuclear, heavy-ion, and (nuclear) astro (particle) physics, linking, for example, terrestrial data to constraints on neutron star structure. A phased roadmap with SIS100 accelerator start-up and envisaged detector upgrades will yield precision cross sections, transition form factors, in-medium spectral functions, and validated theory inputs. Synergies with external programmes at international accelerator facilities worldwide are anticipated. The programme is expected to deliver decisive advances in our understanding of non-perturbative (strong) QCD and astrophysics, and high-rate detector and data-science technology

Study of β\boldsymbolβ Decay Shape Factors in First-Forbidden Transitions with ΔIπ=0−\boldsymbol{ΔI^π= 0^-} for Reactor Antineutrino Spectra Predictions

International audienceThe electron spectra of the $β$ decays of $^{92}$Rb and $^{142}$Cs, key contributors to the reactor antineutrino spectrum, were measured at the IGISOL facility using radioactive beams of high isotopic purity. The shapes of the measured $β$ spectra were compared with various $β$ shape models, including first-forbidden correction factors for $ΔI^π= 0^-$ ground-state to ground-state transitions. Comparisons with previous experimental results are also provided. The shapes of the newly measured $β$ spectra are well reproduced employing feedings extracted from total absorption gamma spectroscopy measurements

A Review on Modified Montmorillonite-Based Catalysts for Biofuel and Recycled Carbon Fuel Production

International audienceThe maritime transport sector’s reliance on fossil-based fuels remains a major contributor to global greenhouse gas emissions, underscoring the urgent need for sustainable alternatives such as marine biofuels. Thermochemical pyrolysis of biomass and plastic waste represents a promising route for producing renewable and recycled marine fuel feedstocks. This review provides an integrated analysis of the full production and upgrading chain, encompassing pyrolysis of lignocellulosic biomass and polymer-derived resources, catalytic upgrading, and qualitative evaluation of product distribution and yield trends. Particular emphasis is placed on montmorillonite-based catalysts as naturally abundant, low-cost, and environmentally benign alternatives to conventional zeolites. The review systematically examines the influence of key montmorillonite modification strategies, including acid activation, pillaring, and ion-exchanged, on acidity, textural properties, and catalytic performance in catalytic cracking and hydrodeoxygenation processes. The analysis shows that catalyst modification strongly governs the yield, selectivity, and reproducibility of biofuels. By adopting this integrated perspective, the review extends beyond existing works focused on isolated upgrading steps or zeolitic catalysts. Key research gaps are identified, particularly regarding long-term catalyst stability, deep deoxygenation of real bio-oils, and compliance with marine fuel standards

Modélisation et analyse de la dynamique de confiance dans une assistance de type IA : analyse et modélisation de l’effet du feedback différé sur la confiance d’un opérateur envers une intelligence artificielle d’aide à la décision au fil du temps

In order to promote optimal use of decision support systems by human operators, we examined the effect of trust in artificial intelligence (AI) on usage behavior, as well as how this trust evolves over time. In particular, we studied how trust can be modulated over time to achieve optimal usage, based on the concept of delayed feedback. To do this, we proposed a conceptual framework structuring the evolution of trust according to three levels: the individual, the session, and the inter-session. Based on this framework, we conducted three experiments involving repeated sessions over time to assess the impact of the type and content of delayed feedback on trust and interaction behaviors. Our results show that these elements can effectively influence trust and behavior depending on the phase of interaction in which the operator finds themselves. We also highlighted a combined effect between trust in AI and self-confidence, which influences certain behaviors over the course of the sessions. Finally, we explored the automatic estimation of trust using six regression models. The best of these, a regression decision tree, explains up to 70% of the variance observed in our experimental context.Afin de favoriser un usage optimal des systèmes d'aide à la décision par les opérateurs humains, nous nous sommes intéressés à l'effet de la confiance envers l'intelligence artificielle (IA) sur les comportements d'utilisation, ainsi qu'à son évolution au fil du temps. Nous avons notamment étudié la manière dont la confiance peut être modulée dans le temps afin de tendre vers un usage optimal, en nous appuyant sur la notion de feedback différé. Pour ce faire, nous avons proposé un cadre conceptuel structurant l’évolution de la confiance selon trois niveaux : l’individu, la session et l’inter-session. À partir de ce cadre, nous avons mené trois expérimentations comprenant des sessions répétées dans le temps afin d'évaluer l'impact du type et du contenu du retour différé sur la confiance et les comportements d'interaction. Nos résultats montrent que ces éléments peuvent effectivement influencer les comportements en fonction de la phase d’interaction dans laquelle se trouve l’opérateur. Nous avons également mis en évidence un effet combiné entre la confiance envers l'IA et la confiance en soi, qui influence certains comportements au fil des sessions. Enfin, nous avons exploré l’estimation automatique de la confiance à l’aide de six modèles de régression. Le meilleur d'entre eux, un arbre de décision régressif, explique jusqu'à 70% de la variance observée dans notre contexte expérimental

On dual-mode index modulation in MIMO-OTFS systems

International audienceOrthogonal time frequency space (OTFS) is a two-dimensional (2D) modulation scheme operating in the delay-Doppler domain. By mapping information symbols into this domain, OTFS effectively transforms a time-varying multipath channel into an almost non-fading 2D channel, enabling all symbols in a frame to experience the same channel gain. To further enhance the bit error rate (BER) performance and spectral efficiency compared to conventional MIMO-OTFS schemes, we consider the dual-mode OTFS system with index modulation (OTFS-DM-IM) in a MIMO setting, hereafter referred to as MIMO-OTFS-DM-IM. A novel low-complexity symbol detection algorithm, termed sparse message passing-energy detection (SMP-ED), is developed, and a formal diversity analysis of the proposed system is presented. Analytical and simulation results show that the scheme achieves full diversity in the delay-Doppler domain. In addition, the upper bound of the average bit error probability (ABEP) is derived using the pairwise error probability (PEP) framework. Simulation results confirm that the proposed MIMO-OTFS-DM-IM system outperforms existing schemes in terms of BER while maintaining low complexity, and achieves a higher diversity order than conventional MIMO-OTFS systems, demonstrating its strong potential for practical wireless communication deployments

Simultaneous Dual-Plane Multi-Write-Spot Two-Photon Polymerization Using a Single Diffractive Optical Element

International audienceThe serial nature of two-photon polymerization (2PP) limits fabrication throughput. While diffractive optical elements (DOEs) can be used to generate multiple write spots in a single plane, three-dimensional structures still require sequential layer-by-layer fabrication. We demonstrate a dual-plane multi-spot 2PP approach using a single static DOE capable of generating two independent focal-spot arrays in distinct planes. This configuration enables simultaneous fabrication of two layers during continuous scanning while maintaining a simple scanning strategy compatible with woodpile structures. Using 29 write spots distributed across two planes separated by 1.8 µm, we fabricate four-layer woodpile structures with an effective writing speed of 1 mm 2 in 90 s. The results demonstrate that combining multi-write-spot parallelization with simultaneous multi-plane writing provides a powerful route to significantly increase 2PP fabrication throughput

Statistical Mechanics of Quarkyonic Matter

International audienceWe extend the theoretical formulation of Quarkyonic Matter within the IdylliQ model framework proposed in [Y. Fujimoto et al., Phys. Rev. Lett. 132, 112701 (2024) [1]] for zero temperature to non-zero temperatures. To this end, we develop a consistent statistical mechanics and grand canonical ensemble description of Quarkyonic Matter as a quantum system subject to additional inequality constraints due to the Pauli exclusion principle acting simultaneously on baryons and their constituent quarks. These constraints result in a significant reduction in the number of physically available baryon states compared to an ideal Fermi gas. As a consequence, the one-particle baryon distribution function factorizes into a thermal Fermi-Dirac distribution and a momentum-dependent density of states. This separation allows us to derive a proper definition of the entropy density that satisfies the third law of thermodynamics in the zero-temperature limit. Moreover, we find that inside Quarkyonic Matter the physical temperature and the physical baryon chemical potential differ from the Lagrange multipliers appearing in the Fermi-Dirac distribution which may have important consequences for the thermodynamics of Quarkyonic Matter

Evaluating the Realism of Cyber-Physical Honeynets Against Advanced Attackers

Cyber-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

Joint Optimization of Production and Condition-Based Maintenance with Speed-Dependent Degradation

International audienceMaintenance operations and production parameters are often optimized separately. We consider a system in which the production speed directly influences the system’s degradation. We propose a combined approach to jointly optimize the production speed and the maintenance decisions under a condition-based maintenance policy in order to maximize the average production rate. We show that in a deterministic setting, the optimal strategy consists in operating at a constant production speed until the system reaches the selected degradation threshold. For the specific case where the degradation rate depends on a power of the production speed, we derive a closed-form expression for the optimal speed as well as a simple optimization procedure for determining the optimal degradation threshold. In that case we study the effect of several parameters on the optimal policy and production rate