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Metallic trace elements in wild and farmed fish from the Aveiro Region (Portugal)
No full textInternational audienceThis study assessed the concentrations of 11 metallic trace elements (MTEs: As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, Zn) in fish muscle from eight wild and farmed species collected in the Aveiro region of Portugal, an area historically affected by industrial pollution. A total of 66 samples were analyzed by ICP-MS. Mean concentrations (mg/kg ww), arranged in ascending order, were: Ni (0.0001), Cd (0.0015), Co (0.0020), Pb (0.0023), Cr (0.0179), Mn (0.0862), Cu (0.2500), Se (0.2964), Fe (1.9236), As (1.9260, total As), and Zn (3.3701). Significant differences were observed among species and between wild and farmed fish, particularly in Dicentrarchus labrax and Sparus aurata. Although Cd and Pb concentrations remained below current European maximum levels, risk assessment based on safe consumption limits (SCLnc) identified total Se, Cd, and Pb as the most restrictive elements for daily intake, especially in children. For arsenic, only total concentrations were considered, as inorganic As could not be distinguished in this study. No significant non-carcinogenic risks were identified at current national average fish consumption levels; however, the potential cumulative and synergistic effects of multiple metals in chronic exposure warrant further investigation. The Metal Pollution Index (MPI < 1 for all samples) confirmed low overall contamination. These findings underscore the importance of ongoing monitoring of trace elements in fish to ensure food safety and protect vulnerable populations
Zeuxis redivivus. Art et émulation dans l’Europe du XVe au XVIIe siècle
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Alignement d'ontologies frugal pour servients WoT
No full textInternational audienceIn distributed and constrained Web of Things (WoT) infrastructures, servients exchange RDF messages that can rely on compact formats to reduce both bandwidth and memory footprint. To this end, in the context of the CoSWoT project, we adapted the CBOR-LD specification. As servients can connect or appear in these infrastructures, each using a different dialect, there is a need for off-the-shelf interoperability during message exchanges at runtime. This paper presents a frugal workflow to detect semantic similarity among messages encoded in CBOR-LD using heterogeneous vocabularies. We experimented different ML-based approaches: a lightweight neural network, a decision tree-based model and a transformer-based architecture. We present a end-to-end pipeline able to integrate each of these algorithms and provide alignment predictions. We ran our experiments on a catalogue of more than 700 production payloads curated to train the models. Our results show various levels of prediction accuracy regarding approaches and model sizes, leading to appropriate choices depending on available resources on targeted platforms.Dans une infrastructure Web des Objets (WoT) distribuée et contrainte, des servients échangent des messages RDF pouvant s’appuyer sur des formats compacts afin de réduire à la fois la bande passante et l’empreinte mémoire. À cette fin, dans le cadre du projet CoSWoT, nous avons adapté la spécification CBOR-LD. Comme les servients peuvent se connecter ou apparaître au sein de ces infrastructures, chacun utilisant un dialecte différent, il est nécessaire d’assurer à l'exécution et de manière automatique une interopérabilité entre les servients à partir des messages qu'ils échangent. Cet article présente une méthodologie permettant de détecter de manière frugale la similarité sémantique entre des messages encodés en CBOR-LD utilisant des vocabulaires hétérogènes. Nous avons expérimenté différentes approches basée sur l’apprentissage automatique : un réseau de neurones léger, un modèle basé sur des arbres de décision et une architecture transformeur. Nous présentons un pipeline capable d’intégrer chacun de ces algorithmes et de fournir des prédictions d’alignement. Nous avons mené nos expériences sur un catalogue de plus de 700 messages produits par des servients, sélectionnés pour entraîner les modèles. Nos résultats montrent divers niveaux de précision des prédictions selon les approches et la taille des modèles, permettant de choisir une approche en fonction des ressources disponibles sur les plateformes visées
Enhancing data anomaly prediction and real-time physical problem detection with Digital Twins and Cognitive Super Digital Twins
No full textInternational audienceThe increasing reliance on Internet of Things (IoT) systems has highlighted the need for effective strategies to detect data anomalies and address physical malfunctions in real time. This paper proposes a Cognitive Super Digital Twin (CSDT) to detect data anomalies and flag physical problems in IoT systems. The framework augments a standard DT with a synthetic data layer that balances rare events and improves model learning. We validate the method on an environmental-sensing and robot actuation case study, showing higher recall and F1 when training with augmented data, and a practical DT that detects incomplete robot motions. The approach improves resilience while keeping costs low by prioritizing digital experiments before physical changes
Non-verbal predication in Old Zamuco
No full textInternational audienceThis chapter describes non-verbal predication in †Old Zamuco, the language that gave its name to the Zamucoan family (southeastern Bolivia, northern Paraguay). Old Zamuco is the most conservative Zamucoan language, which is also reflected in non-verbal predication. After introducing Old Zamuco and its main features, the chapter is organized according to the semantic types of non-verbal predication: identity and inclusion predication, adverbial predication, existential predication, possessive predication, quantification and ostension. It then addresses the interaction of non-verbal predication with word classes, negation, TAM features and complex constructions
Women’s Europeanist networks and the gendering of EEC labour policies during the long 1960s (1957–74)
No full textInternational audienceHistorians and political scientists have long traced the introduction of a reflection on the gendered impact of European public policies back to the mid-1970s. This was linked in particular to the attempt to reduce inequalities between men and women at work, and to the adoption of European legislation in this area, based on directives designed to ensure the application of Article 119 of the Treaty of Rome. This legal approach provides little explanation of the reasons, actors and modalities for putting gender issues on the agenda of the European Economic Communities (EEC). Based mostly on the archives of women’s associations linked to the European Movement, and secondarily on the holdings of several European institutions (Commission, Parliament, Council, Economic and Social Committee), this article offers an original top-down and bottom-up analysis of the process of gendering EEC policies between 1957 and 1974. It contributes to the analysis of the economisation of the EEC social policies and shows that, for women Europeanist activists of the 1960s, gender equality could not be reduced to the issue of wages. Gendering European policies neither represented a linear process of framing of social policies under the economic goals of the EEC, nor was it an insignificant tool in the affirmation of the European institutions vis-à-vis the Member States. Eventually, studying the agency of women’s associations in the inclusion of gender in EEC labour policies allows the article to shed new light on the citizen impulses in the European integration process, from the 1960s onwards
Does subsidy increase the use of carpooling via platforms? The case of short-distance carpooling in France
No full textInternational audienceMany initiatives have been introduced worldwide by governments and industry to promote the use of carpooling. In France, some local authorities have introduced carpooling subsidy policies since 2019 to encourage carpooling trips. We estimate the effect of local carpooling subsidies on the usage of platform-organized short-distance carpooling, using a difference-in-differences design that exploits variation across French “Communautés de Communes” (i.e. local authorities) in both the amount of subsidy and the timing of subsidy policy start. We find that, on average, the introduction of the subsidy increases the number of monthly short-distance carpool trips organized by platforms by approximately 5.2 trips per 1,000 inhabitants in the area covered by the local authority, and this effect increases over time. The study of the effect of the subsidy amount shows that a €1 increase in the carpooling subsidy improves the number of monthly carpool trips organized by platforms by 3.9 trips per 1,000 inhabitants. These average effects mask considerable heterogeneity, with subsidy increasing carpooling use more in larger and more densely populated local authority areas, and the effect being negligible in the smallest and least densely populated local authority areas. We also use survey results to investigate opportunity, windfall and environmental effects of the policy. It indicates our estimates of subsidy effects should be reduced by one-third or one-half to obtain the net new carpoolers effect, as between half and a third of the new carpoolers joining the platforms after the introduction of the subsidy are due to the opportunity effect. We find that carpooling subsidy amount needed to save one ton of CO2 is roughly between €1000 and €1300