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Landé factors for selected levels of the e 6 Π and a 6 Δ states of FeH
No full textInternational audienceWe investigate the Zeeman effect in the 0-0 band of the e 6 Π-a 6 ∆ system of FeH, producing the molecule at near-ambient temperatures and recording Dopplerlimited laser excitation spectra, using selective detection. We provide a set of effective Landé factors for the three lowest spin components of both states, extracted from the analysis of partially-resolved Zeeman patterns seen in magnetic flux denisities of 0.4 -0.7 T. Landé factors in the upper state show strong variations with parity, unlike the lower state level, which is close to having a single electronic configuration. Landé factors for two Fe(I) lines at 18611.635 cm -1 and 19573.056 cm -1 , recorded for magnetic flux density calibration, have been refined in the process
Hotspots Analysis and Prediction for Mobile Networking Applications
No full textInternational audienceUnderstanding the dynamics of mobile traffic is highly valuable for a variety of fields, such as transportation and networking. In particular, analyzing hotspots, i.e., areas presenting an increased popularity at certain times, is crucial for adequate planning and management operations. Yet, despite its importance, we lack today a precise definition of the term hotspot in the community. The essential of this contribution is based on a unique mobile phone dataset collected by a French mobile operator in the city of Paris. In this work, we propose a new definition for the hotspot concept while highlighting the major weaknesses of the literature. Moreover, we provide an extensive benchmarking for the hotspot forecasting problem. Our results show that Long Short-Term Memory (LSTM) gives the best performance for the hotspot prediction problem, and we consider it for a robotic aerial base station (RABS) deployment application. In order to minimize the RABSs travel distance, we mathematically model the problem and introduce a greedy and Particle Swarm Optimization (PSO) algorithms to solve it. The results in terms of coverage ratio and travel distance showcase the difference between a prediction-based approach and a non-prediction-based approach
Quatre profils de DRH engagés dans le bien-être au travail : une analyse par la méthode QCA
No full textInternational audienceCet article explore l’influence des actions mises en place par les directeurs des ressources humaines (DRH) sur le bien-être au travail. S’appuyant sur la théorie de l’échelon supérieur, l'étude analyse les dynamiques décisionnelles et opérationnelles par lesquelles les DRH contribuent à la mise en place de dispositifs favorisant le bien-être au travail. À partir d'un questionnaire administré auprès de 250 DRH et mobilisant la méthode QCA (Qualitative Comparative analysis), la recherche identifie les configurations d’actions à la fois nécessaires et suffisantes à l’amélioration du bien-être des salariés. Les résultats mettent en évidence quatre configurations distinctes, permettant de dégager quatre profils types de DRH, différenciés par leurs logiques d’action et leurs modes d’engagement en faveur du bien-être au travail. Ces résultats apportent une contribution théorique et empirique à la compréhension des politiques et pratiques de gestion des ressources humaines orientées vers le bien-être au travail
POPP. An OCR-Generated Database of the Population Censuses of Paris (1926–1936)
No full textInternational audienceEmpirical research in historical demography is usually time-consuming and labour-intensive. Recent developments in machine learning offer new possibilities for building very large databases with reduced time and costs, though these new methods raise new challenges as well. This article describes the process of constructing the POPP database, a data collection project based on the exploitation of the nominative lists of the Parisian population censuses of 1926, 1931, and 1936. This database provides a host of information for almost 9 million individuals: their name and surname, year and location of birth, nationality, relation to the household head, and occupation. The article discusses the digitisation of archival sources — several hundred thousand handwritten pages — their transformation into a database by computer scientists using machine learning techniques, and the work required on the part of social scientists to correct and adapt the resulting data for statistical purposes. Beyond its methodological contribution, this article also discusses the various ways in which the POPP database will improve our knowledge of the economic, social, and demographic evolution of an important European urban population
Permanent degradation of p-GaN HEMTs due to repetitive overvoltage stress during hard turn-off switching
No full textInternational audienceThis study investigates the long-term impact of dynamic overvoltage stress on GaN HEMTs using a newly designed test circuit, UIS3, a variant of classic UIS, which isolates key stress factors. Devices were subjected to short-duration repetitive overvoltage stress near and below their dynamic breakdown voltage. Characterization before and after stress reveals permanent degradation in CDS, CDS and IGSS, suggesting deep-trapping or structural damage within the device. A distinct alteration in the CDS curve is observed, may indicate less spreading of the electric-field within the device. RDS,on degradation is also noted, likely due to trapping effects, with partial recovery at room temperature. Higher stress levels accelerate failure. Waveform analysis and post-failure characterization indicate a short-circuit failure mode, likely due to partial dielectric breakdown during overvoltage events. These results provide new insights into GaN HEMT degradation mechanisms under high-voltage stress
Mediating the Sacred through Technology and the Body in the Age of Artificial Intelligence
No full textInternational audienceFor centuries, the transmission of the Torah has relied on a model of embodied memory: oral recitation, hevruta study, and communal interpretation form a living chain in which divine speech is received through human voice. The emergence of digital environments and generative artificial intelligence now reshapes these traditional modes of transmission. Online platforms such as Sefaria and TorahBox, along with AI-assisted interfaces for Hebrew learning and textual analysis, have expanded access to sacred study, including for individuals with visual, linguistic, or geographic disabilities. Yet this technological mediation raises profound theological and hermeneutical questions. Can a machine-mediated act of study still be considered kabbalat haTorah, the living reception of Revelation? What becomes of the embodied, sensory, and communal dimensions of Torah learning when they pass through non-human interfaces?Drawing on rabbinic and talmudic sources alongside contemporary digital practices, this paper examines how artificial intelligence transforms both the experience and authority of sacred study. It explores the tension between resistance and adaptation within Jewish traditions, and how accessibility and automation alter the very categories of body, voice, and transmission. By situating digital mediation as both a challenge and a continuation of scriptural embodiment, the study proposes a theological reflection on how technology redefines—not replaces—the human relationship to divine text
Insights into the cognitive evolution of genus Homo: Eye-tracking analysis of stone tool recognition in trained versus novice modern humans
No full textInternational audienceEye tracking technologies have recently been used to analyze the visual exploration of stone tool stimuli by modern humans to investigate the cognition of our ancestors. As a tooling species, modern humans show remarkable abilities when it comes to understanding and manipulating complex tools, such as a microscope. Nevertheless, our earliest technological steps, at least the first ones for which we have archaeological evidence, were stone tools, which today might appear easier to grasp than a highly sophisticated surgical telemanipulator. However, the complexity and diversity of lithic industries require a certain level of knowledge to be fully understood. Thus, the question remains whether modern humans can truly extract relevant features from stone tools to distinguish them, for example, from stones fractured by uncontrolled percussion (broken stones), which might look like the first lithic industries. Naive participants, divided into two groups with one receiving a training about stone tool features and the other not, were asked to distinguish stone tools from broken stones. Results show that participants needed a minimal level of knowledge to distinguish choppers or handaxes from broken stones. Nevertheless, trained participants were still not able to correctly classify unknown types of stone tools as tools, suggesting that they needed deeper knowledge to transfer their skills. Our findings underline the important role of technical knowledge in our ancestors’ expertise in stone knapping
