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With the increasing adoption of technology, more and more systems become target to information security breaches. In terms of readily identifying zero-day vulnerabilities, a substantial number of news outlets and social media accounts reveal emerging vulnerabilities and threats. However, analysts often spend a lot of time looking through these decentralized sources of information in order to ensure up-to-date countermeasures and patches applicable to their organisation’s information systems. Various automated processing pipelines grounded in Natural Language Processing techniques for text classification were introduced for the early identification of vulnerabilities starting from Open-Source Intelligence (OSINT) data, including news websites, blogs, and social media. In this study, we consider a corpus of more than 1600 labeled news articles, and introduce an interpretable approach to the subject of cyberthreat early detection. In particular, an interpretable classification is performed using the Longformer architecture alongside prototypes from the ProSeNet structure, after performing a preliminary analysis on the Transformer’s encoding capabilities. The best interpretable architecture achieves an 88% F2-Score, arguing for the system’s applicability in real-life monitoring conditions of OSINT data.

Published in OA on RESSI (http://www.ressi.ch/) on the 15.02.22. We present here highlights from an enquiry on the innovations in scholarly writing in the Humanities and Social Sciences in the H2020 project OPERAS-P. This article explores the theme of Open Research Data and its role in the emergence of new models of scholarly writing. We examine more closely the obstacles and fostering conditions to the publication of research data, both from a social and a technical perspective. International audience

AbstractDuring its first days of existence, the Vichy regime ordered a review of recent naturalizations. In accordance with a law passed on July 22, 1940, denaturalization decisions were made on a ...

Marine phytoplankton are believed to account for more than 45% of photosynthetic net primary production on Earth, and hence are at the base of marine food webs and have an enormous impact on the entire Earth system. Their members are found across many of the major clades of the tree of life, including bacteria (cyanobacteria) and multiple eukaryotic lineages that acquired photosynthesis through the process of endosymbiosis. Our understanding of their distribution in marine ecosystems and their contribution to biogeochemical cycles have increased since they were first described in the 18th century. Here, we review historical milestones in marine phytoplankton research and how their roles were gradually understood, with a particular focus on insights derived from large-scale ocean exploration. We start from the first observations made by explorers and naturalists, review the initial identification of the main phytoplankton groups and the appreciation of their function in the influential Kiel and Plymouth schools that established biological oceanography, to finally outline the contribution of modern large-scale initiatives to understand this fundamental biological component of the ocean. Fil: Pierella Karlusich, Juan José. Centre National de la Recherche Scientifique. Ecole Normale Supérieure; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Ibarbalz, Federico Matias. Centre National de la Recherche Scientifique. Ecole Normale Supérieure; Francia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Bowler, Chris. Centre National de la Recherche Scientifique. Ecole Normale Supérieure; Francia. Centre National de la Recherche Scientifique; Francia

The topic of my research is "Learning and Upgrading in Global Value Chains: An Analysis of India's Manufacturing Sector". To analyse India's learning and upgrading through position, functions, specialisation & value addition of manufacturing GVCs, it is required to quantify the extent, drivers, and impacts of India's Manufacturing links in GVCs. I have transformed this overall broad objective into three fundamental questions: (1) What is the extent of India's Manufacturing Links in GVCs? (2) What are the determinants of India's Manufacturing Links in GVCs? (3) What are the impacts of India's Manufacturing Links in GVCs? These three objectives represent my three chapters in my PhD thesis. 26 pages, PhD Proposal

The last glacial period is characterized by a number of millennial climate events that have been identified in both Greenland and Antarctic ice cores and that are abrupt in Greenland climate records. The mechanisms governing this climate variability remain a puzzle that requires a precise synchronization of ice cores from the two hemispheres to be resolved. Previously, Greenland and Antarctic ice cores have been synchronized primarily via their common records of gas concentrations or isotopes from the trapped air and via cosmogenic isotopes measured on the ice. In this work, we apply ice core volcanic proxies and annual layer counting to identify large volcanic eruptions that have left a signature in both Greenland and Antarctica. Generally, no tephra is associated with those eruptions in the ice cores, so the source of the eruptions cannot be identified. Instead, we identify and match sequences of volcanic eruptions with bipolar distribution of sulfate, i.e. unique patterns of volcanic events separated by the same number of years at the two poles. Using this approach, we pinpoint 82 large bipolar volcanic eruptions throughout the second half of the last glacial period (12–60 ka). This improved ice core synchronization is applied to determine the bipolar phasing of abrupt climate change events at decadal-scale precision. In response to Greenland abrupt climatic transitions, we find a response in the Antarctic water isotope signals (δ18O and deuterium excess) that is both more immediate and more abrupt than that found with previous gas-based interpolar synchronizations, providing additional support for our volcanic framework. On average, the Antarctic bipolar seesaw climate response lags the midpoint of Greenland abrupt δ18O transitions by 122±24 years. The time difference between Antarctic signals in deuterium excess and δ18O, which likewise informs the time needed to propagate the signal as described by the theory of the bipolar seesaw but is less sensitive to synchronization errors, suggests an Antarctic δ18O lag behind Greenland of 152±37 years. These estimates are shorter than the 200 years suggested by earlier gas-based synchronizations. As before, we find variations in the timing and duration between the response at different sites and for different events suggesting an interaction of oceanic and atmospheric teleconnection patterns as well as internal climate variability. International audience

Décembre 2019. Version 5 remise aux Annales. Ne pas diffuser. Résumé L'objectif de cet article est de proposer un examen détaillé des apports et des limites de la modélisation en histoire à partir du cas de la Shoah. Il s'appuie sur une enquête qui a permis de reconstituer les « trajectoires de persécution » des 992 Juifs de Lens pendant la Seconde Guerre mondiale, dont 527 seulement ont survécu à la Seconde Guerre mondiale. 491 ont été arrêtés, 468 ont été déportés et 449 ont été exterminés. Les données prosopographiques sont utilisées ici pour répondre à une question simple : est-il possible de modéliser la persécution ? En d'autres termes, est-il possible de construire une représentation simplifiée mais heuristique des processus causaux complexes qui ont déterminé les chances de survie face à la persécution nazie à partir de données standardisées sur un nombre relativement important d'individus ? Pour répondre à cette question, l'article discute les apports et les limites d'une succession de méthodes quantifiées : celles qui s'inscrivent dans ce qu'Andrew Abbott appelle le « programme standard » des sciences sociales mais aussi l'analyse des réseaux et l'analyse séquentielle. Pour chacune d'entre elle, nous montrons leurs apports et leurs limites, en discutant plus particulièrement les manières de rendre compte à la fois des interactions entre les individus et de l'historicité des comportements et des processus déterminant ces chances de survie. Les tentatives de modélisation à partir de données historiennes apportent ainsi de véritables renouvellements de connaissances, notamment lorsqu'on les mène de manière cumulative sur une même enquête. En passant d'une logique de propriétés individuelles à une logique de trajectoires interconnectées, ces approches permettent de mieux comprendre les interactions sociales et locales, et offre ainsi des perspectives stimulantes pour la microhistoire de l'Holocauste. International audience