Modèle de caractérisation des visualisations de données complexes en grandes quantités

International audienceVisualizing large and complex datasets is an issue that must be tackled more and more often in the domain of professional systems, given the increasing capacity of data providers. In this paper, we introduce a model supporting the characterization of all the dimensions that have an impact on big and/or complex data representation solutions, which enables us to highlightthe limits of existing visualization solutions.La visualisation de grandes quantités données complexes est un problème de plus en plus courant dans le domaine des systèmes professionnels, en raison des capacités de création et de stockage de données qui augmentent sans cesse. Dans cet article nous présentons un modèle permettant de caractériser l'ensemble des dimensions qui ont un impact sur la représentation de données complexes et/ou en grandes quantités, ce qui nous permet de mettre en avant les limites des solutions de visualisation existantes

Étude des propriétés de rétention en eau des sols argileux

La rétention de l'eau par un sol est un phénomène complexe qui dépend de la nature des constituants minéraux et organiques mais aussi de leur mode d'assemblage à différentes échelles. Les constituants minéraux argileux développent une surface spécifique très grande et interagissent très fortement avec l'eau. Ils jouent par conséquent un rôle privilégié pour la rétention de l'eau des sols

Expert evaluation of the usability of HeloVis: a 3D Immersive Helical Visualization for SIGINT Analysis

International audienceThis paper presents an evaluation of HeloVis: a 3D interactive visualization that relies on immersive properties to improve user performance during SIGnal INTelligence (SIGINT) analysis. HeloVis draws on perceptive biases, highlighted by Gestalt laws, and on depth perception to enhance the recurrence properties contained in the data. In this paper, we briefly recall what is SIGINT, the challenges that it brings to visual analytics, and the limitations of state of the art SIGINT tools. Then, we present HeloVis, and we evaluate its efficiency through the results of an evaluation that we have made with civil and military operators who are the expert end-users of SIGINT analysis

Localization and cooperative communication methods for cognitive radio

We study localization of nearby nodes and cooperative communication for cognitive radios. Cognitive radios sensing their environment to estimate the channel gain between nodes can cooperate and adapt their transmission power to maximize the capacity of the communication between two nodes. We study the end-to-end capacity of a cooperative relaying scheme using orthogonal frequency-division modulation (OFDM) modulation, under power constraints for both the base station and the relay station. The relay uses amplify-and-forward and decodeand-forward cooperative relaying techniques to retransmit messages on a subset of the available subcarriers. The power used in the base station and the relay station transmitters is allocated to maximize the overall system capacity. The subcarrier selection and power allocation are obtained based on convex optimization formulations and an iterative algorithm. Additionally, decode-and-forward relaying schemes are allowed to pair source and relayed subcarriers to increase further the capacity of the system. The proposed techniques outperforms non-selective relaying schemes over a range of relay power budgets. Cognitive radios can be used for opportunistic access of the radio spectrum by detecting spectrum holes left unused by licensed primary users. We introduce a spectrum holes detection approach, which combines blind modulation classification, angle of arrival estimation and number of sources detection. We perform eigenspace analysis to determine the number of sources, and estimate their angles of arrival (AOA). In addition, we classify detected sources as primary or secondary users with their distinct second-orde one-conjugate cyclostationarity features. Extensive simulations carried out indicate that the proposed system identifies and locates individual sources correctly, even at -4 dB signal-to-noise ratios (SNR). In environments with a high density of scatterers, several wireless channels experience non-line-of-sight (NLOS) condition, increasing the localization error, even when the AOA estimate is accurate. We present a real-time localization solver (RTLS) for time-of-arrival (TOA) estimates using ray-tracing methods on the map of the geometry of walls and compare its performance with classical TOA trilateration localization methods. Extensive simulations and field trials for indoor environments show that our method increases the coverage area from 1.9% of the floor to 82.3 % and the accuracy by a 10-fold factor when compared with trilateration. We implemented our ray tracing model in C++ using the CGAL computational geometry algorithm library. We illustrate the real-time property of our RTLS that performs most ray tracing tasks in a preprocessing phase with time and space complexity analyses and profiling of our software

Étude des propriétés de rétention en eau des sols argileux

International audienceLes propriétés physiques et notamment les propriétés de rétention en eau des sols argileux sont liées à la teneur en argile et à ses caractéristiques comme la minéralogie, la taille des particules élémentaires et la nature des cations échangeables (Tessier et Pédro, 1987 ; Quirk, 1994). Dans le sol, les particules finement divisées comme les argiles ont la particularité de développer une grande surface spécifique au contact avec l'eau et de posséder une charge électrique superficielle importante. Ces fractions, grâce à leur petite taille (<2µm) jouent un rôle privilégié dans la rétention en eau, la structuration des sols, mais aussi dans la rétention et biodisponibilité des éléments chimiques indispensables aux plantes

Modeling heat transfer in gas-particle mixtures: Calculation of the macro-scale heat exchange in Eulerian–Lagrangian approaches using spatial averaging

Heat transfers in dilute gas-particle mixtures are often modeled using hybrid Euler–Lagrange descriptions, treating the carrier fluid via an Eulerian representation and following each particle in a Lagrangian framework. One of the focal issues in these models is the calculation of the macro-scale heat transfer between the continuous phase and particles. In the standard approach, the heat transfer for each particle is considered to vary linearly with the average temperature difference between the particle and the fluid. Here, we use the method of volume averaging with closure to filter the heat transfer equations at the micro-scale and derive a closed form of the heat transfer rate, which is significantly different from the standard case. The primary difference is that the heat transfer for a given particle does not only depend on the temperature of the particle but also depends on the temperatures of all other particles within the averaging volume. This yields a matrix of heat exchange coefficients that captures indirect particle–particle exchanges at macro-scale. Using simple model cases, we validate our approach, compare it to the standard heat transfer model and show that it degenerates toward the standard model only in specific cases

Investigating the impact of the molecular charge-exchange rate on detached SOLPS-ITER simulations

Plasma-molecular interactions generate molecular ions which react with the plasma and contribute to detachment through molecular activated recombination (MAR), reducing the ion target flux, and molecular activated dissociation (MAD), both of which create excited atoms. Hydrogenic emission from these atoms have been detected experimentally in detached TCV, JET and MAST-U deuterium plasmas. The TCV findings, however, were in disagreement with SOLPS-ITER simulations for deuterium indicating a molecular ion density ($D_2^+$) that was insufficient to lead to significant hydrogenic emission, which was attributed to underestimates of the molecular charge exchange rate ($D_2 + D^+ \rightarrow D_2^+ + D$) for deuterium (obtained by rescaling the hydrogen rates by their isotope mass). In this work, we have performed new SOLPS-ITER simulations with the default rate setup and a modified rate setup where ion isotope mass rescaling was disabled. This increased the $D_2^+$ content by $> \times 100$. By disabling ion isotope mass rescaling: 1) the total ion sinks are more than doubled due to the inclusion of MAR; 2) the additional MAR causes the ion target flux to roll-over during detachment; 3) the total $D\alpha$ emission in the divertor increases during deep detachment by roughly a factor four; 4) the neutral atom density in the divertor is doubled due to MAD, leading to a 50\% increase in neutral pressure; 5) total hydrogenic power loss is increased by up to 60\% due to MAD. These differences result in an improved agreement between the experiment and the simulations in terms of spectroscopic measurements, ion source/sink inferences and the occurrence of an ion target flux roll-over

Upregulation of the Mevalonate Pathway through EWSR1-FLI1/EGR2 Regulatory Axis Confers Ewing Cells Exquisite Sensitivity to Statins

Ewing sarcoma (EwS) is an aggressive primary bone cancer in children and young adults characterized by oncogenic fusions between genes encoding FET-RNA-binding proteins and ETS transcription factors, the most frequent fusion being EWSR1-FLI1. We show that EGR2, an Ewing-susceptibility gene and an essential direct target of EWSR1-FLI1, directly regulates the transcription of genes encoding key enzymes of the mevalonate (MVA) pathway. Consequently, Ewing sarcoma is one of the tumors that expresses the highest levels of mevalonate pathway genes. Moreover, genome-wide screens indicate that MVA pathway genes constitute major dependencies of Ewing cells. Accordingly, the statin inhibitors of HMG-CoA-reductase, a rate-limiting enzyme of the MVA pathway, demonstrate cytotoxicity in EwS. Statins induce increased ROS and lipid peroxidation levels, as well as decreased membrane localization of prenylated proteins, such as small GTP proteins. These metabolic effects lead to an alteration in the dynamics of S-phase progression and to apoptosis. Statin-induced effects can be rescued by downstream products of the MVA pathway. Finally, we further show that statins impair tumor growth in different Ewing PDX models. Altogether, the data show that statins, which are off-patent, well-tolerated, and inexpensive compounds, should be strongly considered in the therapeutic arsenal against this deadly childhood disease. Keywords: Ewing sarcoma; MVA pathway; new therapeutic strategy; statin