HAL Portal Cnam (French National Conservatory for Arts and Crafts)
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First principles investigation of Radio-oxidation mechanisms in polyethylene
No full textInternational audienceKinetic simulations of radio-oxidation in polymers follows schemes developed several decades ago; recent updates on the list of relevant mechanisms as well as corresponding rates are mostly indirectly extracted from experiment [1]. In this paper we describe some recent advances in the investigation of atomic scale mechanisms relevant for aliphatic polymer oxidation taking the example of polyethylene. Based on a polymer model manageable by first principles calulations, but stil containing the main features of a semi-crystalline polymer, we determine relevant energy barriers and we corroborate our findings with first principles molecular dynamics simulations. Our calculations are based on density functional theory with a van der Waals exchange-correlation functional and, in some cases, we resort to a hybrid functional for comparison.After verifying the main reactions involved in the standard basis coxidation scheme [1], in particular the formation and decomposition of hydroperoxides [2], we investigate several reactions involving alkoxy radicals, which can originate from bimolecular reactions between peroxy radicals [3]. The results clearly show the crucial role of this radical in the whole radio-oxidation kinetic path.Furthermore, we consider the radical scavenging capacities of phenolic antioxidants, taking butylated hydroxy-toluene (BHT) as a prototype. Using static and dynamic simulations, we highlight the fact that BHT can easily eliminate alkoxy radicals which trigger the initiation of radio-oxidation [4].[1] J. L. Bolland, G. Gee, Trans. Faraday Soc. 42, 236 (1946).[2] Y. Ahn, X. Colin, G. Roma, Polymers 13, 2143 (2021).[3] Y. Ahn, G. Roma, X. Colin, Macromol. 55, 8676 (2022).[4] Y. Ahn, G. Roma, X. Colin, J. Phys. Chem. B 128, 12258 (2024)
Dietary consumption trajectory profiles over time of French adults from the NutriNet-Santé cohort (2014-2022): Multicriteria analysis of sustainability
No full textInternational audienceDietary patterns significantly impact climate change and morbidity, making transitions to sustainable diets urgent. Few studies explore repeated dietary measures collected over several years or variations across distinct consumer profiles characterized by sociodemographic and dietary patterns.Objective: Our study aims to identify dietary trajectory profiles in French adults (2014-2022), assessing environmental, nutritional, and health outcomes.Methods: Consumption data from 17,187 NutriNet-Santé cohort participants (52% women, average age 48y, SD = 16) were collected via food frequency questionnaires in 2014 (weighted to the French Census), 2018, and 2022. Dietary trajectory profiles were modeled using Group-based multi-trajectory modeling based on principal component analysis of energy-adjusted consumption data. Associations with environmental (greenhouse gas (GHG) emissions) and nutritional (adherence to French dietary guidelines, diet quality index) dimensions were assessed via multivariable mixed models. Health impacts were evaluated as Disability-Adjusted Life Years (DALYs)avoided, using the Comparative Risk Assessment approach.Results: Six dietary trajectory profiles (P) with distinct starting diets and evolutions were identified. P0 had average intakes, while P1 and P5 were meat-focused, with P5 showing the highest animal consumption. P3 and P4 leaned plant-based, with P4 maintaining high fish and plant intakes, and P3 increasing ruminant meat. P2 initially high in salty or sweet fatty foods, shifted significantly toward plant-based diets. Over time, GHG emissions decreased (-5% to -14%), diet quality (PNNS-GS2 score) improved (+12% to +174%), and health risks declined in four profiles due to reduced red meat and higher whole grains/fruits but increased for P4 and P5 due to processed meat.Conclusion: These profiles reflect diverse population segments with distinct dietary profiles and degrees of sustainability improvements. However, significant advancements remain limited, highlighting the need for further research on economic, psychological, and cultural factors to guide sustainable changes.</p
"Quand les techniques fabriquent la ville (XIVe-XXIe siècle)" : Table ronde des Rendez-vous de l’histoire à Blois,le 11 octobre 2024
No full textTable ronde des Rendez-vous de l’histoire à Blois, le 11 octobre 2024International audienc
Flow matching pour la super-résolution d'images satellitaires Sentinel-2
No full textInternational audienceFlow matching pour la super-résolution d'images satellitaires Sentinel-
Unstripping Cloud Container ELF binaries
No full textInternational audienceEvaluating the security of containers, as part of the supply chain of Cloud services, has become compulsory with the European Directive NIS2. The binaries used within containers are typically stripped, meaning they do not possess debug symbols, making the evaluation of their security posture more complex. This article focuses on automated ways to recover some of this critical debugging information, a process named unstripping, on Linux x86 64 binaries, such as those presently overwhelmingly used within containers
Musculoskeletal disorders in type 1 diabetes: Clinical phenotyping and associations with quality of life and glucose control - The French SFDT1 cohort study
No full textInternational audienceBackgroundMusculoskeletal disorders (MSDs) are common, but overlooked, complications of type 1 diabetes mellitus (T1DM). This study aims to describe MSD phenotypes (clinical, lifestyle, socio-economic) in adults with T1DM.MethodsWe analyzed adult participants in the SFDT1 cohort study. We assessed the following MSDs: stress fractures, non-traumatic upper-limb disorders, and entrapment syndromes. We performed a cross-sectional analysis of the association between MSDs and various factors. After applying multiple imputations for missing data, we computed logistic regression models with progressive adjustments on confounding factors.ResultsOf 1832 participants (53 % men, median age 38 (IQR 22) years), 34 % reported at least one personal history of MSD: 8 % for stress fractures, 24 % for upper-limb disorders and 15 % for entrapment syndromes. A higher prevalence of MSDs was found in women, with aging and with diabetes duration. In a fully adjusted model, we observed a positive association between current smoking (OR [95 %CI] = 1.50 [1.14;1.97]), non-excessive alcohol consumption (1.45 [1.14;1.85]), neuropathy (1.70 [1.35;2.15]), retinopathy (1.30 [1.02;1.65]), use of automated insulin delivery systems (1.53 [1.06;2.21]) and MSDs. MSDs were associated with reduced global quality of life (0.97 [0.95;0.98]). MSDs were not associated with HbA1c, social vulnerability or physical activity.ConclusionWe have shown that MSDs are found in 1 in 3 people with T1DM. They are associated with several lifestyle factors, diabetes complications and the use of automated insulin delivery systems. MSDs should be considered in the T1DM assessment to optimize quality of life
Les transformations du travail face aux avancées technologiques et à l'Intelligence Artificielle (IA) : régulation et compétences au Bénin
No full textInternational audienceArtificial intelligence (AI) is radically transforming the way work is organized, creating new legal, institutional, and human challenges. In Benin, these changes necessitate appropriate regulations and the development of new skills. This article examines issues related to data, legal regulation, institutional frameworks, and skills. It proposes concrete ways to promote the inclusive and sovereign adoption of AI in Benin.L'intelligence artificielle (IA) transforme radicalement les modes d'organisation du travail, posant de nouveaux défis juridiques, institutionnels et humains. Au Bénin, ces mutations exigent une régulation adaptée ainsi que le développement de compétences nouvelles. Cet article examine les enjeux liés à la donnée, à la régulation juridique, au cadre institutionnel, et aux compétences. Il propose des pistes concrètes pour une adoption inclusive et souveraine de l'intelligence artificielle au Bénin
Cross-sensor self-supervised training and alignment for remote sensing
No full textInternational audienceLarge-scale "foundation models'' have gained traction as a way to leverage the vast amounts of unlabeled remote sensing data collected every day. However, due to the multiplicity of Earth Observation satellites, these models should learn "sensor agnostic'' representations, that generalize across sensor characteristics with minimal fine-tuning. This is complicated by data availability, as low-resolution imagery, such as Sentinel-2 and Landsat-8 data, are available in large amounts, while very high-resolution aerial or satellite data is less common. To tackle these challenges, we introduce cross-sensor self-supervised training and alignment for remote sensing (X-STARS). We design a self-supervised training loss, the Multi-Sensor Alignment Dense loss (MSAD), to align representations across sensors, even with vastly different resolutions. Our X-STARS can be applied to train models from scratch, or to adapt large models pretrained on e.g low-resolution EO data to new high-resolution sensors, in a continual pretraining framework.We collect and release MSC-France, a new multi-sensor dataset, on which we train our X-STARS models, then evaluated on seven downstream classification and segmentation tasks. We demonstrate that X-STARS outperforms the state-of-the-art by a significant margin with less data across various conditions of data availability and resolutions
Matériaux architecturés élaborés par fabrication additive
No full textInternational audienceLa fabrication additive offre une liberté inédite pour concevoir des matériaux architecturés, dotés d’une géométrie interne contrôlée. Ils permettent d’optimiser comportement, légèreté ou multifonctionnalité selon un cahier des charges précis. Dans cet article, diverses approches de conception et procédés de fabrication additive sont examinés, mettant l’accent sur la maîtrise de la qualité matière, des temps de cycle et des coûts. Les enjeux industriels portent notamment sur la certification des performances, la réduction de la consommation de ressources et l’intégration à grande échelle. Les secteurs aérospatial, automobile et biomédical exploitent déjà ces solutions pour l’allègement, l’absorption d’énergie ou la personnalisation, annonçant un fort potentiel de développement
Software repository: Automation framework software
No full textThis deliverable reports the content of two software repositories which contain software codes developed in the INTELLIGENTSIA project. The first software repository implements multi-arm bandit algorithms for spreading factor (SF) selection in LoRaWAN networks. This repository includes: (i) source codes used to generate the experimental results associated to a published paper related to the project, (ii) the data of the experiments, and (iii) some useful scripts used to compute metrics and generate plots. The second software repository is related to a LoRaWAN emulator, called ELoRa, developped in the project. This tool allows to emulate LoRaWAN traffic compatible with two widespread open-source implementations of a real LoRaWAN server stack, ChirpStack and The Things Stack. This repository includes: (i) source codes of the tool, (ii) a documentation to install the tool, and (iii) examples to use the tool