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    Giovanni Antonio Rusconi, illustrateur du Discours historial de l’antique et illustre cité de Nismes ?

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    ConvNeXt based semi-supervised approach with consistency regularization for weeds classification

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    International audienceWeed recognition is an essential step for automatic weed control systems. Identifying weeds enables targeted control measures to be implemented, minimizing the use of chemicals and reducing the impact on the environment. Deep learning-based approaches proved to be e↵ective for addressing various complex classification problems. However, to benefit fully from their capabilities, large amounts of labeled data are required, which represents a limitation for agricultural applications, consequence of the tedious and time-consuming process of data labeling. Conversely, unlabeled data could be acquired in large quantities, with relative ease. Hence, our aim is to develop robust and precise deep learning models, to carry-out the recognition and identification of weed species, using both types of data. To this end, we propose a method, that adopts the semi-supervised learning paradigm, to optimally combine labeled and unlabeled data. The method is based on a new deep neural networks architecture, which consists of a modernized convolutional encoder belonging to the family ConvNeXt and a thoroughly designed deep decoder network. This architecture, enables a successful integration of consistency regularization. The conducted experiments on DeepWeeds and 4-Weeds, showed that the semi-supervised models trained through our proposed method provide a stable and high classification performance, compared to other state-of-the-art deep learning models, which were a↵ected negatively by the amount of labeled data available, and the presence of noise during inference. Furthermore, the e↵ectiveness of the proposed method was demonstrated in comparison to other semi-supervised learning methods. The results obtained demonstrate the benefits of adopting the semi-supervised learning paradigm, especially in scenarios with very limited labeled data

    Modeling compartmentalization within intracellular signaling pathway

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    We present a novel approach to modeling receptor-activated signaling pathways that take into account the compartmentalization of receptors and their effectors, both on the cell surface and in dynamic intracellular vesicles called endosomes. The first building block of the model concerns compartment dynamics. It takes into account creation of de novo endosomes, i.e. endocytosis, and further recycling of endosomes to the cell surface or degradation, as well as fusion of endosomes via coagulation dynamics. The second building block concerns biochemical reactions on the cell surface and within intra-cellular compartments. Both building blocks are coupled by the transfer of molecules that occurs at each event that modifies the compartments.The model is formulated as a integro-partial differential equation, with transport and coagulation operators, and source terms, coupled to an integro-differential equation. In this work, we prove sufficient conditions to obtain exponential ergodicity for the size distribution of intracellular compartments. We further design a finite volume scheme to simulate our model. Finally, we show two application cases that show qualitative agreement with recently published data, proving that our model can help capture the spatio-temporal complexity of receptor-activated signaling pathway.Nous présentons une nouvelle approche de modélisation des voies de signalisation activées par les récepteurs, qui prend en compte la compartimentation des récepteurs et de leurs effecteurs, à la fois à la surface cellulaire et dans des vésicules intracellulaires dynamiques appelées endosomes. Le premier élément constitutif du modèle concerne la dynamique des compartiments. Il prend en compte la création d'endosomes de novo, c'est-à-dire l'endocytose, puis le recyclage des endosomes à la surface cellulaire ou leur dégradation, ainsi que la fusion des endosomes via une dynamique de coagulation. Le deuxième élément constitutif concerne les réactions biochimiques à la surface des cellules et dans chaque compartiment intracellulair. Les deux parties du modèles sont couplées par le transfert de molécules qui se produit à chaque événement modifiant les compartiments.Le modèle est formulé comme une équation aux dérivées partielles avec terme intégrale, avec des opérateurs de transport, de coagulation et des termes sources, couplée à une équation intégro-différentielle. Dans ce travail, nous prouvons des conditions suffisantes pour obtenir une ergodicité exponentielle pour la distribution en taille des compartiments intracellulaires. Nous concevons en outre un schéma de volumes finis pour simuler notre modèle. Enfin, nous montrons deux cas d'application qui montrent un accord qualitatif avec des données publiées récemment, prouvant que notre modèle peut aider à capturer la complexité spatio-temporelle de l'activation des voies de signalisation

    Exponential mixing of all orders for Arnol'd cat map lattices

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    22 pages LaTeX, uses utphys.bst for bibliography styleWe show that the recently introduced classical Arnol'd cat map lattice field theories, which are chaotic, are exponentially mixing to all orders. Their mixing times are well-defined and are expressed in terms of the Lyapunov exponents, more precisely by the combination that defines the inverse of the Kolmogorov-Sinai entropy of these systems. We prove by an explicit recursive construction of correlation functions, that these exhibit ll-fold mixing for any l= 3,4,5... This computation is relevant for Rokhlin's conjecture, which states that 2-fold mixing induces l-fold mixing for any l>2. Our results show that 2-fold exponential mixing, while being necessary for any ll-fold mixing to hold it is nevertheless not sufficient for Arnol'd cat map lattice field theories. The correspondence principle implies that these mixing times, also, control the scrambling of the underlying quantum system for short times

    Vocal complexity in a socially complex corvid: gradation, diversity and lack of common call repertoire in male rooks

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    International audienceVocal communication is widespread in animals, with vocal repertoires of varying complexity. The social complexity hypothesis predicts that species may need high vocal complexity to deal with complex social organization (e.g. have a variety of different interindividual relations). We quantified the vocal complexity of two geographically distant captive colonies of rooks, a corvid species with complex social organization and cognitive performances, but understudied vocal abilities. We quantified the diversity and gradation of their repertoire, as well as the inter-individual similarity at the vocal unit level. We found that males produced call units with lower diversity and gradation than females, while song units did not differ between sexes. Surprisingly, while females produced highly similar call repertoires, even between colonies, each individual male produced almost completely different call repertoires from any other individual. These findings question the way male rooks communicate with their social partners. We suggest that each male may actively seek to remain vocally distinct, which could be an asset in their frequently changing social environment. We conclude that inter-individual similarity, an understudied aspect of vocal repertoires, should also be considered as a measure of vocal complexity

    Scalable 3D Panoptic Segmentation With Superpoint Graph Clustering

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    Accepted at 3DV 2024, Oral presentationInternational audienceWe introduce a highly efficient method for panoptic segmentation of large 3D point clouds by redefining this taskas a scalable graph clustering problem. This approach can be trained using only local auxiliary tasks, thereby eliminating the resource-intensive instance-matching step during training. Moreover, our formulation can easily be adapted to the superpoint paradigm, further increasing its efficiency. This allows our model to process scenes with millions of points and thousands of objects in a single inference. Our method, called SuperCluster, achieves a new state-of-the-art panoptic segmentation performance for two indoor scanning datasets: 50.1 PQ (+7.8) for S3DIS Area 5, and 58.7 PQ (+25.2) for ScanNetV2. We also set the first state-of-the-art for two large-scale mobile mapping benchmarks: KITTI-360 and DALES. With only 209k parameters, our model is over 30 times smaller than the best-competing method and trains up to 15 times faster. Our code and pretrained models are available at https://github.com/drprojects/superpoint_transformer

    NaDES-based biorefinery of Spirulina (Arthrospira platensis): A new path for sustainable high value-added metabolites

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    International audienceTo meet the criteria of modern extraction, it is essential to use solvents that simultaneously reach the standards of green chemistry and allow the extraction of a wide spectrum of bio-compounds. Natural Deep Eutectic Solvents (NaDES), as a green solution, meet this difficult task and represent a satisfactory alternative to organic solvents. Microalgae are recognized as a sustainable resource to produce polar and non-polar metabolites, such as carotenoids, free fatty acids (FFA) and phycobiliproteins. Among them, Spirulina (Arthrospira platensis) is one of the most studied, due to its strong potential for food, health and cosmetic. In this work, two biorefinery scenarios were investigated using polar and non-polar NaDES. The first one is a combination of a polar/non-polar sequential solid/liquid extraction together with a liquid-liquid extraction of the polar extract. The second scenario implements an innovative triphasic solid/liquid/liquid approach, based on the simultaneous use of polar and non-polar NaDES in the solid/liquid extraction step. Several NaDES were screened in this study to identify the best polar/non-polar NaDES pair. According to the results, the use of the triphasic approach allowed an increase of the productivity by a factor 4 for chlorophylls and FFA, and by a factor 2 for carotenoids. It was also interesting to note that the phycocyanin-enriched polar fraction achieves much higher levels of purity than the corresponding single-phase extraction for both applied biorefinery scenarios. These results pave the way for the first time for a microalgae biorefinery entirely based on the use of NaDES and industrially credible

    Low concentrations of ethylene bisdithiocarbamate pesticides maneb and mancozeb impair manganese and zinc homeostasis to induce oxidative stress and caspase-dependent apoptosis in human hepatocytes

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    International audienceThe worldwide and intensive use of phytosanitary compounds results in environmental and food contamination by chemical residues. Human exposure to multiple pesticide residues is a major health issue. Considering that the liver is not only the main organ for metabolizing pesticides but also a major target of toxicities induced by xenobiotics, we studied the effects of a mixture of 7 pesticides (chlorpyrifos-ethyl, dimethoate, diazinon, iprodione, imazalil, maneb, mancozeb) often detected in food samples. Effects of the mixture was investigated using metabolically competent HepaRG cells and human hepatocytes in primary culture. We report the strong cytotoxicity of the pesticide mixture towards hepatocytes-like HepaRG cells and human hepatocytes upon acute and chronic exposures at low concentrations extrapolated from the Acceptable Daily Intake (ADI) of each compound. Unexpectedly, we demonstrated that the manganese (Mn)-containing dithiocarbamates (DTCs) maneb and mancozeb were solely responsible for the cytotoxicity induced by the mixture. The mechanism of cell death involved the induction of oxidative stress, which led to cell death by intrinsic apoptosis involving caspases 3 and 9. Importantly, this cytotoxic effect was found only in cells metabolizing these pesticides. Herein, we unveil a novel mechanism of toxicity of the Mn-containing DTCs maneb and mancozeb through their metabolization in hepatocytes generating the main metabolite ethylene thiourea (ETU) and the release of Mn leading to intracellular Mn overload and depletion in zinc (Zn). Alteration of the Mn and Zn homeostasis provokes the oxidative stress and the induction of apoptosis, which can be prevented by Zn supplementation. Our data demonstrate the hepatotoxicity of Mn-containing fungicides at very low doses and unveil their adverse effect in disrupting Mn and Zn homeostasis and triggering oxidative stress in human hepatocytes

    Oral Lichen Planus: An Update on Diagnosis and Management

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    International audienceOral lichen planus (OLP) is a chronic inflammatory disease whose pathogenesis involves a T-cell mediated, epithelium-directed inflammation in response to unknown antigen(s). The disease evolves by intermittent flares and displays polymorphous clinical features (reticular, erosive, atrophic, plaque, papular, bullous, etc.). When present, symptoms vary depending on the clinical form and range from discomfort to severe pain. Topical superpotent corticosteroids constitute the first-line treatment of symptomatic flares, whereas a wide range of second/third-line treatments are available among topical calcineurin inhibitors, systemic corticosteroids, systemic retinoids, topical/systemic immunomodulators, etc. Follow-up of patients is necessary to detect transformation into squamous cell carcinoma, occurring in approximately 1% of patients

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