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Semer les graines du futur : L’Assemblée de la Terre – France, un modèle pour un avenir en harmonie avec la Nature
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Impact of (a)synchronism on ECA: towards a new classification
No full textInternational audienceIn this paper, we study the effect of (a)synchronism on the dynamics of elementary cellular automata. Within the framework of our study, we choose five distinct update schemes, selected from the family of periodic update modes: parallel, sequential, block-sequential, block-parallel, and local clocks. Our main measure of complexity is the maximum period of the limit cycles in the dynamics of each rule. In this context, we present a classification of the ECA rule landscape. We classified most elementary rules into three distinct regimes: constant, linear, and superpolynomial. Surprisingly, while some rules exhibit more complex behavior under a broader class of update schemes, others show similar behavior across all the considered update schemes. Although we are able to derive upper and lower bounds for the maximum period of the limit cycles in most cases, the analysis of some rules remains open. To complement the study of the 88 elementary rules, we introduce a numerical simulation framework based on two main measurements: the energy and density of the configurations. In this context, we observe that some rules exhibit significant variability depending on the update scheme, while others remain stable, confirming what was observed as a result of the classification obtained in the theoretical analysis
The Influence of Wind on the Spatial Distribution of Pelagic Sargassum Aggregations in the Tropical Atlantic
No full textInternational audienceSince 2011, Sargassum seaweed has spread widely outside the Sargasso Sea, causing massive strandings on the coasts of the West Indies and Mexico, causing serious economic, ecological, and health problems. This Atlantic pelagic alga has the characteristic of moving in rafts. According to in situ observations, their size and shape can vary with the wind. To better understand the effect of wind on Sargassum coverage and aggregation size, we conducted a large temporal (2019–2022) and spatial scale study in the West Indies using OLCI/Sentinel-3 satellite imagery. During this period, a database of nearly 1 million Sentinel-3 aggregations, including their geometric and wind characteristics, was established. Analysis of the size distribution showed that wind has a dual effect on disaggregation and agglomeration depending on wind speed and aggregation size: (1) low winds favor agglomeration for the smallest aggregations and disaggregation for the largest aggregations; (2) high winds favor disaggregation for all aggregation sizes. In addition, topography also plays a role in size distribution: the Caribbean arc favors agglomeration over offshore zones, and coastal areas favor disaggregation over offshore zones
Règlement (UE) n°1143/2014 — Espèces exotiques envahissantes — Système de surveillance — Plan d’action: CJUE, 14 novembre 2024, Commission / Bulgarie (espèces exotiques envahissantes), aff. C-165/23, ECLI:EU:C:2024:958
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Unitarity of the Leptonic Mass Matrix
No full textInternational audienceThe experimental data gathered to date have provided evidence for massive neutrinos that mix. The Cabibbo Kobayashi Maskawa quark mixing matrix is a unitary matrix that contains information on the strength of the flavour-changing weak interaction. It can be parameterized by three mixing angles and a CP-violating phase. Similarly one can build a 3x3 leptonic mixing matrix,called the Pontecorvo Maki Nakagawa Sakata matrix (PMNS matrix), to describe the standard neutrino-mixing paradigm. Its unitarity is a critical assumption. Neutrino oscillation experiments have improved and stabilised the precision on the measurements of the three angles and the CP violating phase, constraining strongly unitarity violation. In this work, we will use the most recent Nu-Fit of the PMNS parameters at in normal and inverted hierarchies to calculate the degree of precision of the unitarity of the matrix elements and the sensitivity in weak decays involving neutrinos
Data-driven Crack Detection in the Realm of Structural Health Monitoring: An Overview
No full textInternational audienceThe advancements of sensor technologies, improvements in computational power, and massive amounts of data from the increasing number of sensors deployed on structures have augmented the need for data-driven techniques in structural health monitoring (SHM), particularly for fatigue crack detection. Data-driven methods and tools are increasingly used in analyzing structures to ensure the absence of any fatigue crack in various engineering fields including civil, mechanical, aerospace, and maritime engineering. This overview aims to present the most recent research that utilizes data-driven methods for fatigue crack detection in engineering structures that fall within the realms of signal processing (SP) and machine learning (ML). It focuses on studies utilizing Deep Learning (DL) for crack detection, highlighting the importance of Transfer Learning (TL)
Le compte courant est un contrat en cours dans la liquidation judiciaire !
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