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Tunable Structural Color in Au-Based One-Dimensional Hyperbolic Metamaterials
No full textInternational audienceStructural coloration arising from nanoscale light–matter interactions has emerged as a key research area in nanophotonics. Among the various materials investigated, noble metals—particularly gold—play a central role due to their well-defined plasmonic response and chemical stability, but their structural coloring typically requires complex and highly engineered nanostructures. However, modern photonic technologies demand scalable approaches to produce structural colors that can be finely tuned. In this contribution, we experimentally and numerically demonstrate the fine tunability of structural color in gold-based one-dimensional hyperbolic metamaterials (1D-HMMs) by varying their structural parameters: number of layers (N), period (T), and filling fraction (p). Our results show that variations in N lead to changes in luminance with minimal shifts in chromaticity, while variations in T introduce moderate color shifts without affecting luminance. In contrast, changes in p produce the largest modifications in chromaticity, though the trend is non-monotonic and less predictable. These findings highlight the potential of 1D-HMMs for achieving finely controlled gold-based coloration for advanced photonic technologies
From progress to precision: a decadal reassessment of national particulate matter footprint across industries and regions
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Emerging mixed electronic-ionic conductivity in double perovskite (La2/3Sr1/3)2(Sn1/3Fe1/3Cu1/3)2O6-δ: Phase transitions, structural, optical and dielectric study
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An SDN-based Adaptive Ensemble Learning Framework for Intrusion Mitigation in Wireless Networks
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Aluminum Nanoparticles For Photobleaching Resistance Of Quantum Dots In Solution
No full textInternational audienceWe investigated aluminum nanoparticles (2–20 nm) synthesized via ion reduction in alkane solvents. Extinction spectroscopy revealed UV-range plasmon resonances matching Mie theory. These nanoparticles enhanced quantum dot emission by 1.75 times and reduced photobleaching, absorbing emitted light. They hold promise as building blocks for nanophotonics and protecting emitters from degradation
Les outils de hiérarchisation des usagers dans les dispositifs sociotechniques gamifiés : des manifestations de e-réputation
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Classifying Conventions: a Conceptual Framework and Practical Guide to Reflect on Digitally-Supported Cooperative Work Practices
No full textInternational audienceThe growing use of digital tools and communication media combined with the rise of hybrid work practices impact daily collaboration, contributing to information and communication overload, a sense of lost control, and the growing difficulty in maintaining work-life balance, factors affecting the quality of life at work. Organizations have tried to solve these problems with technical solutions such as inbox disconnection systems or charters to standardize practices, but these often prove too rigid for real work practices. Building on work conducted in Computer-Supported Cooperative Work (CSCW), we suggest that identifying and discussing digital conventions among workers could reduce coordination issues. We propose a classification of digital conventions in four categories: organizational, procedural, space and time, and relational. It serves both as a conceptual framework and a practical guide for conducting interventions in an organization to support reflection on digital work practices and potentially improve the quality of life at work. We are currently evaluating it in the regional branch of a public agency where most of the employees are hybrid workers
Étude des relations entre le refus scolaire anxieux et les caractéristiques des établissements scolaires
No full textInternational audienceSchool refusal anxiety (SRA) arises from multiple causes, among which performance anxiety may play a key role. Its prevalence, estimated between 1% and 5%, remains difficult to determine precisely, particularly in France, due to the lack of in-depth research. This study explores its link with social factors, notably the Social Position Index (SPI) and the Distance Index (DI), based on data collected from 3,722 students across 26 middle schools in the Île-de-France region. The results show that SRA is associated with the school's SPI, DI, and school size, but has no significant link with the IVAC, class size, or the presence of specialized classes. Screening using the SCREEN scale suggests that SRA may be underreported in disadvantaged populations, where cultural norms could hinder the expression of emotional vulnerability, leading to confusion with school dropout.Le refus scolaire anxieux (RSA) résulte de multiples causes, parmi lesquelles l’anxiété de performance pourrait jouer un rôle clé. Sa prévalence, estimée entre 1 et 5 %, reste difficile à établir précisément, notamment en France, en raison du manque de recherches approfondies. Cette étude explore son lien avec des facteurs sociaux, notamment l’Indice de Position Sociale (IPS) et l’Indice d’Éloignement (IE), à partir de données recueillies auprès de 3 722 élèves de 26 collèges d’Île-de-France. Les résultats montrent que le RSA est associé à l’IPS de l’établissement, à l’IE et à la taille des établissements, mais qu’il n’a pas de lien significatif avec l’IVAC, le nombre d’élèves par classe ou la présence de classes spécialisées. Le dépistage via l’échelle SCREEN suggère une sous-déclaration du RSA dans les populations défavorisées, où les normes culturelles peuvent freiner l’expression de la vulnérabilité émotionnelle, entraînant une confusion avec le décrochage scolaire
A sentiment analysis of the Ukraine-Russia War tweets using knowledge graph convolutional networks
No full textInternational audienceNowadays, social networks play a critical role in online social discourse, particularly during major events such as elections, health crises, and wars. Furthermore, individuals have spent significant time on social networks that consume news and express their opinions and viewpoints on various topics, namely, the Russia-Ukraine War. The Ukraine-Russia War is one of the most complicated and unfortunate events of this decade, with many aspects to be considered to have an informed opinion. For this reason, sentiment analysis research can be useful in analyzing sentiments or opinions about the Ukraine-Russia war, such as Twitter (X) posts. In this study, we propose a new deep learning-based sentiment classification model called "Knowledge Graph Convolutional Networks" that predicts and analyzes sentiments concerning the Russia-Ukraine war. There were 500,000 tweets collected in total, however only 410,428 were left for sentiment analysis after cleaning, lemmatization stemming, and deleting duplicate tweets. Results show that "war", "people", "world", "putin", "energy", "gas", "weapon", and "peace" were some of the most frequently occurring words in the tweets. The main aim of this work is to develop a robust system that provides an understanding of public sentiment towards the Russia-Ukraine war on the X platform. Experimental results demonstrate that it is possible to obtain more accurate sentiment classification results by the proposed method. They also have managerial, economic, and research implications