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Transformation
No full textInternational audienceThe 2030 Agenda and its 17 Sustainable Development Goals provide a normative framework and vision for a sustainable society. They call for deep transformations of our societies and economies from the current unsustainable state to more sustainable courses of development. Sustainability transformation refers to fundamental changes in the structural, functional, relational and cognitive aspects of how societies operate that lead to new patterns of interactions and outcomes. This transformation is aimed at addressing the interconnected global challenges of poverty, inequality, environmental degradation and climate change.L’Agenda 2030 et ses 17 Objectifs de développement durable fournissent un cadre normatif et une vision pour une société durable. Ils appellent à des transformations profondes de nos sociétés et de nos économies, depuis un état actuel non durable vers des trajectoires de développement plus soutenables. La transformation vers la durabilité renvoie à des changements fondamentaux dans les dimensions structurelles, fonctionnelles, relationnelles et cognitives du fonctionnement des sociétés, conduisant à de nouveaux modes d’interaction et à de nouveaux résultats. Cette transformation vise à répondre aux défis mondiaux interconnectés que sont la pauvreté, les inégalités, la dégradation de l’environnement et le changement climatique
Disparity in operation decision in Maxillofacial surgery: influence of gender and social status.
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Machine learning-driven discovery of bioactive peptides from duckweed (Lemnaceae) protein hydrolysates: Identification and experimental validation of 20 novel antihypertensive, antidiabetic, and/or antioxidant peptides
No full textInternational audienceDuckweed, a sustainable, protein-rich aquatic plant, has recently emerged as a promising source of bioactive peptides. However, their identification remains limited and challenging in such complex mixtures. Following duckweed hydrolysis with pepsin, chymotrypsin, trypsin and papain, and a centrifugation step producing two fractions: supernatant (DS) and pellet (DP), interesting half-maximal inhibitory concentration (IC50) for dipeptidyl peptidase (DPP)-IV and angiotensin-converting enzyme (ACE) inhibition were obtained for DS fractions, especially with pepsin (IC50 = 0.7 and 0.07 mg/mL, respectively). Using partial least squares-discriminant analysis (PLS-DA) combined with quantitative structure-activity relationship (QSAR) models, five new DPP-IV inhibitors (most active: API, IC50 = 126.88 μM), eleven new ACE inhibitors (most active: FAR, IC50 = 13.54 μM) and four new antioxidants (>200 μM) were identified. Two sequences were active across all three tested bioactivities, revealing promising multi-target peptides. These findings highlight the potential of duckweed-derived peptides to support health and metabolic balance
Conception et développement d'étalons de paramètres S pour la caractérisation des nanodispositifs haute fréquence
No full textThis thesis arises from work undertaking to establish reliable and traceable methods for S-parameter measurements of planar circuits. The LNE, in partnership with IEMN, is committed to continually meeting the growing needs of the RF and microwave industry, with a particular focus on the miniaturization of electronic devices.While reducing component size is essential for technological advancement, it also impacts electrical performance. These performance characteristics are assessed using measurement instruments such as vector network analyzers (VNAs), which typically operate with a nominal impedance of 50 Ω. These instruments are optimized for this impedance and are especially sensitive to variations introduced by the device under test.Miniaturization can significantly alter the impedance range, sometimes resulting in extreme values. Measuring a nanocomponent with a VNA therefore introduces challenges related to impedance matching and measurement sensitivity. For example, a high impedance nanodevice might be interpreted by the instrument as either a short or open circuit, or something close to these conditions, making accurate detection difficult and leading to highly noisy measurements.In response to these challenges, LNE is expanding its research on VNA measurement methodologies. The work aims to cover a wider frequency range, target specific impedance domains, and operate at the nanoscale. The objective is to design and develop traceable coplanar nanostructures for vector calibration, supporting an extended impedance range including extreme, low, and high values and to establish associated calibration methods that ensure the metrological verification of the measurement system.This thesis is devoted entirely to the design of new coplanar nanocomponents in a Ground–Signal–Ground (GSG) configuration for VNA calibration, specifically for on-wafer S-parameter measurements.The work addresses the key challenges and advances in RF and microwave on-wafer measurements, with special emphasis on the precise characterization of nanodevices up to 110 GHz. It covers the overall scientific context, motivations, and objectives, the state of the art in RF metrology including the fundamentals of transmission lines and S-parameters RF measurement systems, calibration and de-embedding methods, and uncertainty assessment according to the GUM. A particular focus is placed on on-wafer measurement techniques, the influence of device miniaturization, and issues related to high-impedance measurements.The thesis details the steps involved in designing and fabricating dedicated calibration kits, including the choice of technology, materials, and dimensions, electromagnetic simulations, and validation of calibration algorithms. It also presents the experimental setup for characterizing devices from DC to 110 GHz, measurement protocols, data correction procedures, reproducibility studies, and uncertainty analysis using the TRL method based on both measured and modeled standards.Furthermore, the work focuses on developing new approaches for high-impedance measurements. These approaches are experimentally validated using different calibration kits based on the multiline-TRL method. The new approaches include the well-known Short-Open-Load-Thru (SOLT) method, as well as derivative methods that integrate offsets into the standards, including Short-Short-Short-Thru (SSST), Open-Open-Open-Thru (OOOT), and Highimpedance-Highimpedance-Highimpedance-Thru (HHHT).The thesis concludes by outlining prospects for extending these methods to new applications. Overall, this research makes both theoretical and experimental contributions aimed at improving the accuracy, repeatability, and applicability of RF and microwave on-wafer measurements, particularly for increasingly miniaturized and high-impedance devices.Cette thèse s’inscrit dans le cadre de travaux visant à établir des méthodes fiables et traçables pour la mesure des paramètres S de circuits planaires. Le Laboratoire National de Métrologie et d’Essai (LNE), en partenariat avec l’Institut d’Électronique, de Microélectronique et de Nanotechnologie (IEMN), répond aux besoins croissants de l’industrie des radiofréquences (RF) et des micro-ondes, avec une attention particulière à la miniaturisation des dispositifs électroniques.La réduction de la taille des composants constitue un facteur clé du progrès technologique, mais influence aussi fortement les performances électriques. Celles-ci sont évaluées grâce à des instruments comme les analyseurs de réseaux vectoriels (VNA), optimisés pour une impédance nominale de 50 Ω, et sensibles aux variations introduites par le composant testé.La miniaturisation peut entraîner des plages d’impédance extrêmes. Mesurer un nanocomposant avec un VNA pose donc des défis majeurs d’adaptation et de sensibilité. Ainsi, un dispositif à haute impédance peut être interprété comme un court-circuit, un circuit ouvert ou une condition similaire, compliquant la détection et générant du bruit de mesure.Pour relever ces défis, le LNE développe de nouvelles méthodologies par VNA, visant à élargir la bande de fréquences, cibler des domaines d’impédance spécifiques et travailler à l’échelle nanométrique. Ce travail conçoit et développe des nanostructures coplanaires traçables pour l’étalonnage vectoriel, capables de couvrir une large gamme d’impédances, y compris extrêmes. Il s’agit aussi de mettre en place des méthodes d’étalonnage assurant la vérification métrologique du système de mesure.La thèse est consacrée à la conception de nanocomposants coplanaires en configuration Ground–Signal–Ground (GSG) pour l’étalonnage des VNAs, spécifiquement pour les mesures de paramètres S sur wafer. Elle traite des principaux défis et avancées dans la mesure RF et micro-ondes sur wafer, avec un accent sur la caractérisation précise des nanodispositifs jusqu’à 110 GHz.Le document présente le contexte scientifique, les motivations et objectifs, l’état de l’art en métrologie RF (lignes de transmission, systèmes de mesure de paramètres S), les méthodes d’étalonnage et de de-embedding, ainsi que l’évaluation des incertitudes selon le GUM. Une attention particulière est portée aux techniques sur wafer, à l’influence de la miniaturisation et aux problématiques liées aux mesures à haute impédance.La thèse détaille la conception et la fabrication de kits d’étalonnage : choix technologiques, matériaux, dimensions, simulations électromagnétiques, et validation des algorithmes. Elle présente aussi le dispositif expérimental utilisé pour caractériser les dispositifs de DC à 110 GHz, les protocoles de mesure, les corrections de données, les études de reproductibilité et l’analyse des incertitudes via la méthode TRL, sur la base de standards mesurés et modélisés.Le travail introduit également de nouvelles approches pour les mesures à haute impédance. Validées expérimentalement avec divers kits basés sur la méthode multiline-TRL, elles incluent la méthode Short-Open-Load-Thru (SOLT) et des variantes intégrant des offsets, telles que Short-Short-Short-Thru (SSST), Open-Open-Open-Thru (OOOT) et Highimpedance-Highimpedance-Highimpedance-Thru (HHHT).La thèse se conclut par des perspectives d’extension de ces méthodes à de nouvelles applications. Globalement, cette recherche apporte des contributions théoriques et expérimentales pour améliorer la précision, la répétabilité et l’applicabilité des mesures RF et micro-ondes sur wafer, notamment pour des dispositifs miniaturisés et à haute impédance
Networks of Networks in 6G: A Key Enabler for Mission-Critical Applications
No full textInternational audienceThe railway industry is rapidly transitioning toward full automation and enhanced safety, driven by the need to reduce greenhouse gas emissions and revitalize secondary lines. While 5G promises improved latency, reliability, and throughput, its high deployment costs and limited coverage hinder universal adoption. Emerging research advocates the transition to 6G, supported by a vision of Networks of Networks that would allow the transparent use of different access networks (e.g. satellite, IoT). This paper extends that paradigm by introducing a broader vision centred on multi-operator resource federation, hybrid classical/quantum communications, and distributed artificial intelligence. We propose a five-layer architecture that integrates these pillars by federating infrastructure across operators for seamless coverage and combining quantum-secure channels with conventional links for robust security. Additionally, our design leverages federated artificial intelligence at the edge for real-time decision-making. Finally, we outline the primary technical challenges and research directions necessary to realize resilient, adaptive, and secure railway connectivity in the 6G era
Transformer-Based Lung Infection Severity Prediction with Cross Attention and Conditional TransMix Augmentation
No full textInternational audienceLung infections, particularly pneumonia, pose significant health risks and can rapidly worsen, especially during pandemics. Developing advanced AI-driven tools for severity prediction based on medical imaging is essential for timely decision-making and treatment, ultimately saving lives. In this study, we introduce a novel approach applicable to multiple medical imaging modalities, including CT scans and chest X-rays, for predicting lung infection severity. Our method consists of two key components: a Transformerbased severity prediction model and an augmentation strategy called Conditional Online TransMix, designed to address data imbalance. The proposed model employs parallel encoders, integrating Pyramid Vision Transformers (PVTs) with a cross-gated attention mechanism and a feature aggregation module to generate a scalar severity score. To enhance model generalization across datasets, we introduce a tailored augmentation technique that synthesizes new mixed severity scores linked to image patches. We validate our approach using the RALO CXR and Per-COVID-19 CT datasets, demonstrating superior performance on multiimage modalities compared to several state-of-the-art deep learning models. By incorporating a customized weighted loss function, our method enhances the precision of automated lung disease severity assessment, providing a reliable and adaptable AI tool for clinical diagnosis and treatment planning
Nonlinear modeling of AlN/GaN HEMT accounting for self-biasing effect during RF step stress: analysis and hard-SOA
No full textplateforme PROOF LAASInternational audienceIn this study, we investigate the non-linear (NL) behavior of AlN/GaN HEMT technologies under gain compression when submitted to 10 GHz single-tone RF-step stress, which is crucial for millimetre-wave power application robustness. We evaluate AlN/GaN transistors, targeting high-power amplifiers with operating frequency above 30 GHz. We present here an original method that includes, in a unique NL expression, the varying self-biasing effect caused by RF step-stress sequences. This methodology can be used as a tool for comparative analysis of technological variants and various transistor geometries post RF stress. The step-stresses are conducted on HEMT in saturated mode and in diode operation alone, to assess the electrical origins of defects and the critical Safe Operating Area (SOA) of these devices. We identify the mechanism of failure as stemming from the degradation of the Schottky gate when subjected to critical RF power levels, due to its constrained capacity to handle power signals exceeding 18 dBm. Furthermore, we highlight the remarkable RF robustness of this technology, achieving gain compression of around 10 dB without degradation
Inter-municipal cooperation in drinking water supply: Trade-offs between transaction costs, efficiency and service quality
No full textInternational audienceInter-municipal cooperation (IMC) is frequently promoted as a solution to improve the management of local utilities such as drinking water. Yet its effectiveness remains ambiguous: while IMC can create economies of scale, it may also induce transaction costs that undermine its benefits. In France, drinking water services are managed at the municipal level, where local governments can decide whether to cooperate—and if so, whether to adopt a purely technical cooperative arrangement or a more politically integrated, supra-municipal governance structure. Using a comprehensive panel of French water utilities from 2008 to 2021, we investigate the factors that lead municipalities to remain independent. Our econometric analysis, based on a correlated random effects probit model with a control function approach, yields several key findings. First, while IMC is associated with higher water prices, these increased tariffs are offset by better network performance, as indicated by lower water loss indices and improved water quality. Second, we find that the more politically integrated form of cooperation is more common among publicly managed utilities and among municipalities seeking to reduce their dependence on imported water. These findings provide new insights into the governance of common-pool resources, suggesting that while cooperation can improve service provision, its institutional design must carefully balance organizational costs against expected efficiency gains
A spiking coincidence detector for the ITD and ILD mechanisms of auditory localization
No full textInternational audienceSpike-based neuromorphic technology is spreading into artificial neural network applications, carrying the promise of improved energy efficiency. Indeed, spike neural networks offer the advantage of sparse and energy-efficient information representation. Direct encoding of sensor measurements is generally required for these networks to process information, as is done in human physiology—for example, in the cochlea and hair cells for hearing, or On-Off cells for vision. In auditory localization, mechanisms such as Interaural Level Difference (ILD) and Interaural Time Difference (ITD), also known as Time Difference of Arrival (TDOA), are encoded as spike sequences. By analyzing ILD and ITD, it is then possible to estimate the position of a sound source. This study presents a preprocessing model designed to encode auditory localization mechanisms into spike sequences, with frequency variations corresponding to ILD or ITD values. The output of this encoding can be visualized as spatial iso-contours representing the potential locations of the sound source. This model makes novel use of a coincidence detector topology-typically found in artificial vision-as an innovative and efficient estimator of auditory localization mechanisms