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Savoir-faire ou faire savoir ? Une transmission paradoxale face à l’inconnu de la transition démographique
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Understanding Electric Vehicle Range and Charging Needs: Interactions Between Ambient Temperature, Commute Patterns, and State-of-Charge Usage
No full textInternational audienceElectric vehicle (EV) performance can vary substantially under real-world operating conditions, particularly due to ambient temperature effects on energy consumption, battery behavior, and thermal management requirements. This study quantifies how weather conditions, daily driving patterns, and State-of-Charge (SOC) usage strategies jointly influence EV driving range, charging frequency, and overall energy efficiency. A detailed and experimentally validated Autonomie vehicle model is developed, integrating a powertrain, a mono-zonal cabin model, and a battery electro-thermal model. Three battery sizes (200-, 300-, and 400-mile homologated ranges) are assessed across five commute profiles (20-200 miles) and six ambient temperatures (-18 • C to 50 • C), including scenarios with and without preconditioning. Results show that extreme temperatures could significantly decrease the maximum achievable range by up to 55% in cold conditions (-18 • C) and 40% in hot conditions (50 • C), relative to moderate conditions. Larger battery packs retain a greater fraction of their nominal range under thermal stress, while smaller packs experience sharper relative penalties due to the higher contribution of thermal loads to total energy demand. The analysis further demonstrates that limiting operation to partial SOC windows (e.g., 80-20%), a common real-world practice, significantly reduces achievable range and increases charging frequency, particularly in cold weather. Thermal preconditioning while plugged in is shown to mitigate these effects for short trips, reducing energy consumption by up to 31% in hot conditions and 7% in cold conditions. The findings demonstrate how climate, SOC usage behavior, and thermal management jointly shape the practical driving capability of EVs, highlighting the importance of efficient thermal management and realistic user charging strategies for ensuring reliable EV operation across diverse climatic scenarios
Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk
No full textInternational audienceABSTRACT Background Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1 / BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). Methods We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan Results Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3’-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10 -9 ). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). Conclusions This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC
Tunable synthesis of C-SiOxCy monoliths
No full textInternational audienceThis study establishes key structure–property relationships, offering valuable guidelines for designing porous monolithic C-SiOxCy materials for energy storage sensors, and electrocatalysis. We report a tunable sol-gel synthesis of monolithic C-SiOxCy composites with tailored physicochemical and electrical properties. By combining resorcinol, formaldehyde, TEOS, APTES, and kapok fibers, twenty-one formulations were prepared while systematically varying five synthesis parameters: TEOS-to-resorcinol molar ratio, sol concentration, sol pH, drying method, and pyrolysis temperature. The resulting composites exhibited silica contents ranging from 19 to 80 wt%, bulk densities from 0.10 to 1.11 g/cm³, specific surface areas up to 562 m²/g, and electrical conductivities reaching 8 S/cm. Structural analyses (SEM, ²⁹Si NMR, N2 adsorption) revealed that the materials consist of integrated hybrid networks rather than separate carbon and silica domains. Factor analyses highlighted the dominant roles of TEOS/R on composition and porosity, supercritical drying on texture, and pyrolysis temperature on conductivity. Acidic conditions and sol dilution promoted high surface areas and pore volumes, while alkaline pH and carbon-rich environments enhanced electrical transport
Optimal Control of Microswimmers for Trajectory Tracking Using Bayesian Optimization
No full textTrajectory tracking for microswimmers remains a key challenge in microrobotics, where low-Reynolds-number dynamics make control design particularly complex. In this work, we formulate the trajectory tracking problem as an optimal control problem and solve it using a combination of B-spline parametrization with Bayesian optimization, allowing the treatment of high computational costs without requiring complex gradient computations. Applied to a flagellated magnetic swimmer, the proposed method reproduces a variety of target trajectories, including biologically inspired paths observed in experimental studies. We further evaluate the approach on a three-sphere swimmer model, demonstrating that it can adapt to and partially compensate for wall-induced hydrodynamic effects. The proposed optimization strategy can be applied consistently across models of different fidelity, from low-dimensional ODE-based models to high-fidelity PDE-based simulations, showing its robustness and generality. These results highlight the potential of Bayesian optimization as a versatile tool for optimal control strategies in microscale locomotion under complex fluid-structure interactions
GWTC-4.0: Constraints on the Cosmic Expansion Rate and Modified Gravitational-wave Propagation
No full textInternational audienceWe analyze data from 142 of the 218 gravitational-wave (GW) sources in the fourth LIGO-Virgo-KAGRA Collaboration (LVK) Gravitational-Wave Transient Catalog (GWTC-4.0) to estimate the Hubble constant jointly with the population properties of merging compact binaries. We measure the luminosity distance and redshifted masses of GW sources directly; in contrast, we infer GW source redshifts statistically through i) location of features in the compact object mass spectrum and merger rate evolution, and ii) identifying potential host galaxies in the GW localization volume. Probing the relationship between source luminosity distances and redshifts obtained in this way yields constraints on cosmological parameters. We also constrain parameterized deviations from general relativity which affect GW propagation, specifically those modifying the dependence of a GW signal on the source luminosity distance. Assuming our fiducial model for the source-frame mass distribution and using GW candidates detected up to the end of the fourth observing run (O4a), together with the GLADE+ all-sky galaxy catalog, we estimate km s Mpc. This value is reported as a median with 68.3% (90%) symmetric credible interval, and includes combination with the measurement from GW170817 and its electromagnetic counterpart. Using a parametrization of modified GW propagation in terms of the magnitude parameter , we estimate , where recovers the behavior of general relativity
Stress-induced amorphization as a transformation plasticity mechanism demonstrated in forsterite
No full textInternational audienceAlthough stress-induced amorphization has recently been identified as a new and distinctive plasticity mechanism, a formal framework for its systematic application in materials engineering is still lacking. In this study, we establish that stress-induced amorphization in Mg2SiO4 forsterite exhibits all the key features of phase transformation plasticity, a well-known phenomenon that has enabled the development of high-performance materials. By analogy with the Transformation-Induced Plasticity (TRIP) effect, we introduce the concept of amorphous-TRIP (a-TRIP). We demonstrate that the a-TRIP features, in particular the orientation effect of stress-induced amorphization (particularly strong in forsterite), can be exploited to design materials with enhanced toughness, a notable advance for a class of materials traditionally limited by brittle behavior
Toward a Better Understanding of Recrystallization Mechanisms of Single Crystal Nickel Based Superalloys During Turbine Blades Processing
No full textInternational audienceA series of experiments investigating the recrystallization (RX) mechanisms of the single crystalline superalloy AM1 during its manufacture have been carried out. High and very high temperature tensile tests were conducted to investigate the effect of the level of plastic deformation and the temperature at which the strain was applied. These parameters were then analyzed for their influence on RX mechanisms during the subsequent solution heat treatment. The strain threshold for RX under various temperature range has been determined and it has been shown that RX is more likely to occur within the 900-1150 °C deformation temperature range. Some correlations between deformation mechanisms and volume fraction of γ' in this type of alloy over these temperature ranges have been discussed in order to explain these trends. In addition, non-isothermal tensile tests were conducted to reproduce as closely as possible the thermomechanical path experienced during the manufacturing of single-crystalline parts using investment casting. A strong correlation has been demonstrated between the thermomechanical path followed during non-isothermal tests that lead to the appearance of recrystallized grains and the "recrystallization zone" identified from pure isothermal tests. This correlation becomes evident when the thermomechanical path crosses this zone. The effect of nonisothermal thermomechanical loading on microstructure was studied by EBSD analysis. Significant local misorientation was observed around microstructural inhomogeneities such as casting pores and eutectic/casting pore pairs. These local rotations suggest that microstructural inhomogeneities act as stress concentrators leading to the first RX nuclei once a super-solvus solution heat treatment has been applied
Optimization skill: How good is your energy management strategy really?
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Vers une évaluation systémique et bio-inspirée : un cadre matriciel complet pour évaluer la circularité et la durabilité
No full textInternational audienceAcademic interest in circular business model innovation (CBMI) has grown in recent years as organizations seek to design products and services that are more environmentally friendly and sustainable. While significant attention has been given to the exploration, ideation, and implementation stages of CBMI, the evaluation phase remains insufficiently addressed, despite its critical role in ensuring that circularity efforts translate into tangible sustainability outcomes. This article draws on ecological principles and a bio-inspired approach to propose the BICS (Bio Inspired Circularity and Sustainability) matrix: a comprehensive framework for assessing both the circularity and sustainability of business models. Based on a deductive methodology and a dual case study conducted within the retail sector, the research demonstrates how this evaluation tool can support decision-making, foster organizational learning, and enhance the performance of business model innovation processes. The findings highlight the relevance of a systemic and life-cycle perspective in guiding CBMI and offer insights for both practitioners and researchers engaged in the transition toward a circular and sustainable economy.L'intérêt académique pour l'innovation en matière de modèles économiques circulaires (CBMI) s'est accru ces dernières années, les organisations cherchant à concevoir des produits et des services plus respectueux de l'environnement et plus durables. Si une attention considérable a été accordée aux étapes d'exploration, de conceptualisation et de mise en œuvre de la CBMI, la phase d'évaluation reste insuffisamment abordée, malgré son rôle essentiel pour garantir que les efforts en faveur de la circularité se traduisent par des résultats concrets en matière de durabilité. Cet article s'appuie sur des principes écologiques et une approche bio-inspirée pour proposer la matrice BICS (Bio Inspired Circularity and Sustainability) : un cadre complet permettant d'évaluer à la fois la circularité et la durabilité des modèles d'affaires. S'appuyant sur une méthodologie déductive et une double étude de cas menée dans le secteur de la vente au détail, cette recherche démontre comment cet outil d'évaluation peut soutenir la prise de décision, favoriser l'apprentissage organisationnel et améliorer la performance des processus d'innovation en matière de modèles d'affaires. Les résultats soulignent la pertinence d'une perspective systémique et axée sur le cycle de vie pour orienter la CBMI et offrent des perspectives utiles tant aux praticiens qu'aux chercheurs engagés dans la transition vers une économie circulaire et durable