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Einstein Gyrogroup and Quantum Measurements in Spin Factor State Spaces
No full textEinstein velocity addition endows the unit ball of Rn with the structure of a gyrocommutative gyrogroup together with the hyperbolic Hilbert-Klein Riemannian metric. First, we propose a self-contained derivation of these properties by rewriting Einstein addition in the Clifford algebra of the Euclidean space R^n , in which gyroautomorphisms are given by spinors. Then, our main result shows that the Einstein gyrogroup arises naturally in the context of quantum measurements in real spin factors. By embedding the state space of the Jordan algebra R ⊕ R^n into a multipartite rebit system realized as a tensor product of the algebra of 2 × 2 real symmetric matrices, we prove that Lüders state-update operations induce a gyrogroup morphism from the unit ball endowed with Einstein addition to a gyrogroup of density matrices. This extends known results in the low-dimensional case for the rebit and the qubit, and confirms that relativistic velocities and quantum state-updates in real spin factor share a common algebraic structure in arbitrary dimensions
Diet composition and trophic ecology of two Antarctic storm-petrel species
No full textInternational audienceAvailability and quality of food shape the distribution and movements of animal populations. In sympatric species, sharing limited resources, coexistence is typically achieved through niche segregation. However, information on dietary niches is lacking particularly for small and elusive seabirds, which often forage in remote oceanic areas. In this study, we aimed to characterize the trophic ecology of two highly pelagic seabird species, Wilson’s storm-petrel Oceanites oceanicus and Black-bellied storm-petrel Fregetta tropica, breeding sympatrically on King George Island, maritime Antarctica, using a combination of methods. Prey species, assayed via metabarcoding of faecal and regurgitate samples, were dominated by teleost fish, primarily lanternfish (Myctophidae), and zooplanktonic crustaceans, mainly krill (Euphausiidae), but also included other prey with lower frequencies of occurrence, such as salps and amphipods. We used carbon and nitrogen bulk stable isotopes and compound-specific isotope analyses of amino acids of blood samples to derive isotopic niches and trophic positions, showing that Black-bellied storm-petrels prey on a slightly higher trophic position than Wilson’s storm petrels(3.7 and 3.5, respectively). Combining results of stable isotope and molecular diet analysis, indicate a diet richer in fish for Black-bellied storm-petrels and thus a potential niche segregation not in regards of general prey spectrum but proportion of specific prey types (prey composition). Additionally, intraspecific segregation in prey spectrum was observed in Wilson’s storm-petrels concerning their breeding stage (incubation vs. chick-rearing), suggesting selective chick provisioning. Future studies should investigate a potential interspecific spatial segregation in foraging areas
DilatedSkinNet: A feature fusion induced intelligent framework for skin lesion extraction
No full textInternational audienc
Diversity of helminths parasitising North-East Atlantic and Antarctic seabirds
No full textInternational audienceSeabirds are largely used as indicators of Ocean health and are final hosts of several helminth parasites. However, the helminth fauna of seabirds is still poorly studied. Here, we quantified the diversity of gastrointestinal parasites in 52 individuals belonging to 10 seabird species with different habitat preferences and feeding strategies from the North-East Atlantic and Antarctica. Fresh carcasses were collected in Northern France and at Svarthamaren (Dronning Maud Land, Antarctica), helminth parasites were extracted from the gastrointestinal tract, and were identified by morphological inspection and DNA barcoding. In total, we identified 13 helminth taxa. North-East Atlantic seabirds hosted parasites from four helminth groups (Acanthocephala, Cestoda, Nematoda, Trematoda), while Antarctic seabirds hosted Acanthocephala and Cestoda only. The largest parasite diversity was found in northern fulmars Fulmarus glacialis (9 species), European shags Gulosus aristotelis (5 species), razorbills Alca torda (4 species), and black-legged kittiwakes Rissa tridactyla (4 species). Co-infections with multiple parasite species in single hosts were common. Oceanic diving species were found to be the most parasite-poor, with common guillemots Uria aalge and Atlantic puffins Fratercula arctica hosting no parasites. In contrast, oceanic surface-feeding seabirds had a large parasite diversity, which notably included trematodes, and was comparable to that of coastal species. To the best of our knowledge, this study identified 9 new host-parasite associations: Andracantha sp. in northern fulmars and south polar skuas Stercorarius maccormicki, C. septentrionale in northern fulmars and black-legged kittiwakes, a species of Microphallidae in black-legged kittiwakes, Cardiocephaloides longicollis in European shags, Cryptocotyle lingua in Sandwich terns Thalasseus sandvicensis, and a clophyllidean species in south polar skuas and Antarctic petrels Thalassoica antarctica
La suite de l'affaire Shein : le tribunal judiciaire prononce une injonction sans suspension
No full textInternational audienc
First baseline study on polymetallic passive biomonitoring of Polycarpa aurata in coral reef ecosystems in Southeast Sulawesi, Indonesia.
No full textInternational audienceThis pioneering study investigates the use of the tunicate Polycarpa aurata for assessing polymetallic pollution inSoutheast Sulawesi, Indonesia. Over the course of one year, encompassing both rainy and dry seasons, potentiallytoxic elements (PTE) such as metal elements were examined in the tunic and soft body of P. aurata. The researchrevealed site-specific variations in element trace concentrations, with a mining site exhibiting elevated levels ofmultiple metals (like As 12.65 μg/g DW, Cd 0.34 μg/g DW, Co 31.17 μg/g DW, Cu 10.88 μg/g DW and Ni173.50 μg/g DW). A correlation was observed between metal concentrations in P. aurata and those in sedimentand suspended particles. Comparing the 2 tissues analysed (soft body and tunic), we note that certain metalelements, including arsenic (BSAF 8,99), cadmium (6,38), copper (2,84), and zinc (5,28), accumulated preferentiallyin the soft body of P. aurata, while nickel accumulation was minimal compared to sediment levels (BSAFNi 1,12). This study establishes a baseline for passive biomonitoring of Indonesian coral reefs, demonstrating thatascidians like P. aurata are effective candidates for monitoring metal pollution in these marine environments. Thefindings contribute to addressing contemporary environmental challenges by highlighting the potential of marineorganisms in chemical monitoring and biomonitoring programs for pollutant identification and environmentalquality assessment
Moving Vehicle Obstacle Pre-Detection with Telemetry Sensing Signal Prediction by Negative Group Delay Method
No full textInternational audienceThis article develops a vehicle-obstacle anti-collision system based on negative group delay (NGD) function. As theory, the anti-collision pre-detector design and implementation are described by exploiting the NGD time-advance ta to anticipate obstacle positioning relatively to a moving object and required safety distance. The NGD pre-detector design equation and methodology are formulated as function of ta. The NGD anti-collision system is validated with realistic demonstration constituted by a mini-vehicle equipped with a telemetry sensor moving along an 85-cm track towards an obstacle. NGD circuit implemented on microcontroller and Arduino UNO platform in good agreement with theory confirms obstacle pre-detection at 30-cm and 50-cm safety distances with ta={-0.1, -0.2, -0.3} seconds. The NGD anti-collision system has notable benefits as ta flexibility, low-power consumption, learning phase unnecessity and embedding simplicity. As future work, the NGD method will be integrated in anti-accident industrial systems by providing optimal safety distance allowing to react quickly and effectively to obstacle warnings by maximizing response time
Microstructure-property relationships in Ni W alloy coatings: Impact of processing routes and W content
No full textInternational audienc
Split Multi-Task Federated Learning for Battery Health and Capacity Estimation in Electric Vehicles
No full textInternational audienceThe rapid adoption of electric vehicles (EVs) has heightened the need for advanced diagnostic frameworks to ensure the safety, reliability, and longevity of battery systems. Batteries, as the cornerstone of EV performance, are susceptible to capacity degradation, thermal instability, and anomalies that compromise efficiency and safety. Traditional diagnostic approaches, relying on physics-based models and heuristic thresholds, often fail to address the complexity and variability of real-world EV operations, necessitating scalable, efficient, and privacy-preserving solutions. This paper presents a Split Multi-Task Federated Learning (SMTFL) framework that leverages a Transformer-based architecture to address the dual challenges of battery health anomaly detection and capacity estimation. By combining the efficiency of split learning with the collaborative benefits of federated learning, the proposed system enables EVs to train and share partial model updates while retaining sensitive data locally. Experimental results on a recent large-scale EV dataset demonstrate the superior performance of the SMTFL framework, achieving an accuracy of 98.9% for battery health anomaly detection and a mean absolute error (MAE) of 0.32 Ah for capacity estimation, corresponding to a relative error of approximately 1.80%, significantly outperforming state-ofthe-art approaches. By training a single model for both tasks and performing computations during charging sessions, the framework minimizes energy consumption and computational overhead, ensuring practicality for large-scale deployment in real-world EV systems.</div