Temporal Deep Learning for Drone Micro-Doppler Classification

International audienceOur work builds temporal deep learning architectures for the classification of time-frequency signal representations on a novel model of simulated radar datasets. We show and compare the success of these models and validate the interest of temporal structures to gain on classification confidence over time

Complex-valued neural networks for fully-temporal micro-Doppler classification

International audienceMicro-Doppler analysis commonly makes use of the log-scaled, real-valued spectrogram, and recent work involving deep learning architectures for classification are no exception. Some works in neighboring fields of research directly exploit the raw temporal signal, but do not handle complex numbers, which are inherent to radar IQ signals. In this paper, we propose a complex-valued, fully temporal neural network which simultaneously exploits the raw signal and the spectrogram by introducing a Fourier-like layer suitable to deep architectures. We show improved results under certain conditions on synthetic radar data compared to a real-valued counterpart

Genetic diversity, linkage disequilibrium and power of a large grapevine (Vitis vinifera L) diversity panel newly designed for association studies

UMR-AGAP Equipe DAVV (Diversité, adaptation et amélioration de la vigne) ; équipe ID (Intégration de Données)International audienceAbstractBackgroundAs for many crops, new high-quality grapevine varieties requiring less pesticide and adapted to climate change are needed. In perennial species, breeding is a long process which can be speeded up by gaining knowledge about quantitative trait loci linked to agronomic traits variation. However, due to the long juvenile period of these species, establishing numerous highly recombinant populations for high resolution mapping is both costly and time-consuming. Genome wide association studies in germplasm panels is an alternative method of choice, since it allows identifying the main quantitative trait loci with high resolution by exploiting past recombination events between cultivars. Such studies require adequate panel design to represent most of the available genetic and phenotypic diversity. Assessing linkage disequilibrium extent and panel power is also needed to determine the marker density required for association studies.ResultsStarting from the largest grapevine collection worldwide maintained in Vassal (France), we designed a diversity panel of 279 cultivars with limited relatedness, reflecting the low structuration in three genetic pools resulting from different uses (table vs wine) and geographical origin (East vs West), and including the major founders of modern cultivars. With 20 simple sequence repeat markers and five quantitative traits, we showed that our panel adequately captured most of the genetic and phenotypic diversity existing within the entire Vassal collection. To assess linkage disequilibrium extent and panel power, we genotyped single nucleotide polymorphisms: 372 over four genomic regions and 129 distributed over the whole genome. Linkage disequilibrium, measured by correlation corrected for kinship, reached 0.2 for a physical distance between 9 and 458 Kb depending on genetic pool and genomic region, with varying size of linkage disequilibrium blocks. This panel achieved reasonable power to detect associations between traits with high broad-sense heritability (> 0.7) and causal loci with intermediate allelic frequency and strong effect (explaining > 10 % of total variance).ConclusionsOur association panel constitutes a new, highly valuable resource for genetic association studies in grapevine, and deserves dissemination to diverse field and greenhouse trials to gain more insight into the genetic control of many agronomic traits and their interaction with the environment

Solution techniques for anisotropic diffusion operators arising in magnetized edge plasma physics

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Numerical fluid modelling of the plasma edge response to a 3D object and application to mach probe measurements

International audienceThe penalization method is used to model the interaction of 3D probe with an isothermal plasma. Density maps show that the region perturbed by the obstacle, is not restricted to its near neighbourhood, but can extend to the whole SOL. In the particular case of a probe, which is used to measure local plasma parameters, this impact can lead to violation of assumptions of locality of the perturbation usually used in determining Mach number from the imbalance in density on both sides of the probe

Global fluid simulations of edge plasma turbulence in tokamaks: a review

International audienceWith ITER, the largest tokamak ever built, and the growing number of fusion energy startups in the world, the need for numerical simulations has never been more crucial to progress towards the successful operation of fusion reactors. From fundamental plasma physics to engineering, a hierarchy of models exists from high-fidelity (gyro-)kinetic models in (5D) 6D to 0D fluid transport models. In this paper, we review the state-of-the-art of 3D turbulence fluid simulations in edge tokamak configurations. The widely used drift-reduced Braginskii equations are introduced together with the dedicated boundary conditions modelling plasma wall interactions. If until recently most of the models were focused on electrostatic turbulence driven by interchange-like instabilities, in recent years models have incorporated electromagnetic effects allowing fluctuations of the magnetic field. Specific features of the edge plasma configurations, which make these equations specially challenging to resolve and stressful for the numerical methods, are detailed. In particular, the strong anisotropy of the flow as well as the complex geometric characteristics lead to the development of dedicated discretization schemes and meshing, which are implemented in state-of-the-art codes reviewed here. It appears that the latter can be differentiated by their mesh construction as well by the manner in which they handle parallel gradients (aligned or not along the magnetic field). The review shows that no consensus on the optimal combination between meshing and discretization schemes, if it exists, has been found. Finally, examples of recent achievements show that 3D turbulence simulations of medium-sized tokamaks are currently achievable, but that ITERsize tokamaks and thermonuclear plasmas still require significant progress

What was the surface temperature in central Antarctica during the last glacial maximum?

The temperature increase at Vostok (Antarctica) from the last glacial maximum to the present warm period is about 8°C based on the deuterium isotope profile. The bore hole temperature (temperature profile in the ice sheet) indicates that the temperature difference may have been much larger, about 15°C. The temperature dependent gas occlusion process is the key to evaluate the two scenarios. Atmospheric air penetrates the porous firn layer of the ice sheet and gets trapped at the firn ice boundary. Consequently the air is younger than the surrounding ice when it gets enclosed in bubbles. This age difference (Δage) between ice and enclosed gas is temperature and accumulation rate dependent. Therefore it is possible to estimate paleotemperatures from a known Δage. We use the linkage between chronologies of CH4 and water isotopes from Byrd station and Vostok to obtain an experimental Δage for Vostok. This experimental Δage is then compared to modeled Δage for the two temperature scenarios. Our results indicate that the temperature reconstruction deduced from the water isotopic composition is the more probable one

Modélisation numérique du plasma du bord d'un tokamak

Ce travail porte sur la modélisation numérique 3D du plasma de bord d'un Tokamak. Dans une approche fluide, un plasma isotherme est décrit comme un fluide compressible soumis à une faible diffusion. Une méthode de pénalisation est mise en place pour modéliser les obstacles (limiteurs) à l'intérieur d'un tokamak. Cette méthode permet de retrouver les conditions limites requises (Mach = 1) au bord des limiteurs avec la flexibilité inhérente à la pénalisation, et d'étudier différentes configurations de limiteurs, ainsi que leur effet sur les distributions de densité et nombre de Mach

A Hermitian Positive Definite neural network for micro-Doppler complex covariance processing

International audienceIn its raw form, micro-Doppler radar data takes the form of a complex time-series, which can be seen as multiple realizations of a Gaussian process. As such, a complex covariance matrix constitutes a viable and synthetic representation of such data. In this paper, we introduce a neural network on Hermitian Positive Definite (HPD) matrices, that is complex-valued Symmetric Positive Definite (SPD) matrices, or complex covariance matrices. We validate this new architecture on synthetic data, comparing against previous similar methods