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Spatiotemporal modeling of host–pathogen interactions using level-set method
No full textInternational audiencePhenotyping host-pathogen interactions is crucial for understanding infectious diseases in plants. Traditionally, this process has relied on visual assessments or manual measurements, which can be subjective and labor-intensive. Recent advances in image processing and mathematical modeling enable the precise and high-throughput phenotyping of plant symptoms. Among many challenges, considering local deformations of symptoms and host tissues is difficult in plant pathology. In this study, we address this question using a level-set method. We propose an innovative approach in plant pathology that allows one to reconstruct the continuous deformation of leaf and lesion contours from daily image sequences of inoculated leaves. We consider pea stipules inoculated by the fungal pathogen Peyronellaea pinodes as an example pathosystem. After extracting lesion and stipule contours from daily visible images, we use the level-set method to track their deformations within image sequences. The visual assessment of model adequacy, along with the Jaccard Index and relative error metrics, demonstrated strong overall performance. Results showed a gradual decrease in model accuracy over time for leaf contours, while lesion contours exhibited a higher relative error on the first targeted date. These findings highlight the robustness of our method while identifying specific challenges in early lesion detection. We finish by discussing the interest in this method based on partial differential equations for the study of host-pathogen interactions, especially the development of original phenotyping methods in plant pathology.</div
Low temperature reactive spark plasma sintering of yttria-stabilized zirconia from mixture of hydroxides
No full textInternational audienceThis work explores the low-temperature (≤ 1000 °C) densification of Yttria-Stabilized Zirconia (YSZ) using reactive hydroxide precursors. A density of 97 % was achieved by Spark Plasma Sintering (SPS) at only 100 MPa, enabled the high reactivity of a mixture of Y(OH)3 and Zr(OH)4. This reactivity was investigated under two conditions: a) in air, using thermal analyses (TGA, DSC) and in situ high temperature X-ray diffraction (HT-XRD), and b) under vacuum within a SPS device, through degassing analysis and ex-situ XRD. Differences in crystallinity according to the environment and identification of the optimal reactivity window were determined for Y(OH)3 and the hydroxide mixture, in order to determine the SPS conditions to trigger low-temperature densification. The use of SPS combined with specific amorphous hydroxide precursors, exhibiting greater reactivity than their crystalline counterparts, afforded the formation of YSZ at relatively low temperatures (350°C) and very high densification at only 1000°C
Recent Holocene climatic and environmental variability and its impact on pre-Hispanic populations in the Sechura Desert
No full textInternational audienc
Processeur sécurisé et reconfigurable incluant des technologies émergentes
No full textThe Internet of Things (IoT) is a rapidly expanding ecosystem in which intelligent objects interact via communicating networks. This rapid growth leads to a massive increase in the amount of data collected, posing challenges in terms of energy efficiency, particularly at sensor nodes. To improve this efficiency, it is essential to process data as close as possible to the sensors, thus reducing the load of communication and operations on the main computing unit. The Near Sensor Computing approach and the use of non-volatile memories (NV), capable of maintaining the state of sensors in standby mode, make it possible to meet these challenges while significantly increasing the energy efficiency of IoT-related systems.Alongside these energy challenges, data security in the IoT has become a major concern, particularly for applications where security is a crucial aspect, such as connected vehicles and smart healthcare systems. Attacks on secure communications have demonstrated the vulnerability of today's systems to sophisticated threats. Protecting data as soon as it is collected, even before it is transmitted, is therefore crucial. The SECRET project aims to meet this need by applying memory-centric computing paradigms and integrating reconfigurable NV operators as close as possible to the sensors. This provides a first line of defense, while optimizing energy consumption by reducing memory accesses. The emergence of new technologies, such as ferroelectric field-effect transistors (FeFETs) and resistive memories (RRAMs), opens up promising prospects for the design of circuits based on memory-centric architectures.These approaches, which break away from Von Neumann or Harvard architectures, make it possible to limit the bottlenecks associated with data transfers between computing and storage units. However, their integration into complex circuits raises several major technical challenges. On the one hand, the choice of models must be judicious in order to ensure the accuracy of simulations and the reliability of results throughout the design flow. On the other hand, current design tools, mainly developed for conventional architectures, are still poorly adapted to the specificities of circuits exploiting an intrinsic memory effect. In particular, taking into account the NV properties of components and their impact on logic synthesis requires adapted methodologies. This thesis shows that it is possible to design logic gates based on FeFETs, and then proposes an application within NV operators.L'Internet des Objets, raccourcie en IoT pour Internet of Things, est un écosystème en pleine expansion, où des objets intelligents interagissent via des réseaux communicants. Cette croissance rapide entraîne une augmentation massive des données collectées, posant des défis en termes d'efficacité énergétique, notamment au niveau des nœuds de capteurs. Pour améliorer cette efficacité, il est essentiel de traiter les données au plus près des capteurs, ce qui réduit la charge de communication et d'opérations sur l'unité de calcul principale. L'approche du Near Sensor Computing et l'utilisation de mémoires non volatiles (NV), capables de maintenir l'état des capteurs en veille, permettent de répondre à ces défis tout en augmentant significativement l'efficacité énergétique des systèmes liés à l'IoT.Parallèlement à ces défis énergétiques, la sécurité des données dans l'IoT est devenue une préoccupation majeure, notamment pour des applications où la sécurité est un aspect primordiale comme les véhicules connectés et les systèmes de santé intelligents. Des attaques sur les communications sécurisées ont démontré la vulnérabilité des systèmes actuels face à des menaces sophistiquées. Ainsi, la protection des données dès leur collecte, avant même qu'elles ne soient transmises, est cruciale. Le projet SECRET tente de répondre à ce besoin en appliquant des paradigmes de calcul centrés sur la mémoire et en intégrant des opérateurs reconfigurables et NV au plus près des capteurs. Offrant ainsi une première ligne de défense tout en optimisant la consommation énergétique grâce à la réduction des accès mémoire. L'émergence de technologies émergentes, telles que les transistors à effet de champ ferroélectriques (FeFET) et les mémoires résistives (RRAM), ouvre des perspectives prometteuses pour la conception de circuits basés sur des architectures centrées sur la mémoire.Ces approches, en rupture avec les architectures de Von Neumann ou Harvard, permettent de limiter les goulots d'étranglement liés aux transferts de données entre unités de calcul et de stockage. Cependant, leur intégration dans des circuits complexes soulève plusieurs défis techniques majeurs. D'une part, le choix des modèles doit être judicieux afin d'assurer la précision des simulations et la fiabilité des résultats tout au long du flot de conception. D'autre part, les outils de conception actuels, principalement développés pour des architectures conventionnelles, sont encore peu adaptés aux spécificités des circuits exploitant un effet mémoire intrinsèque. En particulier, la prise en compte des propriétés NV des composants et leur impact sur la synthèse logique nécessitent des méthodologies adaptées. Cette thèse montre qu'il est possible de concevoir des portes logiques basées sur des FeFET puis propose une application au sein d'opérateurs NV
Exploring the Relationship of Transposable Elements and Ageing: Causes and Consequences
No full textInternational audienceAgeing is a gradual biological process marked by a decline in physiological function, increasing susceptibility to disease, and mortality. Transposable elements (TEs) are repetitive DNA sequences capable of moving within the genome and thus potentially inducing mutations and disrupting normal cellular functions. Their mobile nature contributes to genomic variation, as transposition events can alter gene expression, chromosome structure, and the epigenetic landscape. To mitigate TE-induced damage, cells rely on epigenetic mechanisms, such as DNA methylation, histone modifications, and small RNAs, to repress TE activity. However, these silencing mechanisms become less effective with age, leading to increased TE activation. This review explores the dual role of TEs as both a cause and consequence of ageing, suggesting a complex relationship between TEs and the ageing process
ArtSymbioCyc, a metabolic network database collection dedicated to arthropod symbioses: a case study, the tripartite cooperation in Sipha maydis
No full textInternational audienceMost arthropods live in close association with bacteria. The genomes of associated partners have co-evolved creating situations of interdependence that are complex to decipher despite the availability of their complete sequences. We developed ArtSymbioCyc, a metabolism-oriented database collection gathering genomic resources for arthropods and their associated bacteria. ArtSymbioCyc uses the powerful tools of the BioCyc community to produce high quality annotations and to analyze and compare metabolic networks on a genome-wide scale. We used ArtSymbioCyc to study the case of the tripartite symbiosis of the cereal aphid Sipha maydis focusing on amino acid and vitamin metabolisms, as these compounds are known to be important in this strictly phloemophagous insect. We showed how the metabolic pathways of the insect host and its two obligate bacterial associates are interdependent and specialized in the exploitation of Poaceae phloem, for example for the biosynthesis of sulfur-containing amino acids and most vitamins. This demonstrates that ArtSymbioCyc does not only reveal the individual metabolic capacities of each partner and their respective contributions to the holobiont they constitute, but also allows to predict the essential inputs that must come from host nutrition. IMPORTANCE Evolution has driven the emergence of complex arthropod-microbe symbiotic systems, whose metabolic integration is difficult to unravel. With its user-friendly interface, ArtSymbioCyc ( https://artsymbiocyc.cycadsys.org ) eases and speeds up the analysis of metabolic networks by enabling precise inference of compound exchanges between associated partners, and helps unveil the adaptive potential of arthropods in contexts such as conservation or agricultural control
Preliminary numerical study on magnet gate in MOS FD-SOI technology for quantum and sensor applications
No full textInternational audienceConcentrator photovoltaics (CPV) modules are complex, heavy and bulky which hinders the deployment of this technology. Over the past few years, the miniaturization of this technology, called micro-CPV, promises to make more compact and less expensive modules. This article focuses on the design, fabrication and characterization of a 350 × single-stage concentrator optic made of PMMA. A matrix of 16 lenses has been produced, and a prototype module has been fabricated and characterized outdoors, achieving an optical efficiency of over 80%
Assessment of Case Depth Using Spectral Analysis of Low-Frequency Magnetic Incremental Permeability
No full textInternational audienceThis study explores the use of spectral analysis in the Low-Frequency Magnetic Incremental Permeability (LF-MIP) non-destructive testing technique to evaluate thermo-chemical treatments in high-quality low-carbon steel. The detailed spectral analysis identifies specific harmonics that exhibit strong correlations with mechanical indicators of the treatment, such as case depth
Advanced printed ultrasound sensors for structural health monitoring: design, performance, and applications
No full textInternational audienceThis study presents an innovative approach to structural health monitoring (SHM) through the direct printing of ultrasound (US) sensors onto structural components
