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Negative refraction of elastic waves on a metamaterial with anisotropic local resonance
No full textInternational audienceWave propagation through a locally resonant metamaterial characterized by anisotropic dynamic mass density is studied. The polarizations and velocities of waves are obtained from an extended Christoffel matrix. The set of waves induced by a body wave coming through the interface with an elastic material is described. Reflexion and refraction coefficients corresponding to the ratio of real Poynting vectors are obtained, showing that some of these coefficients are singular. In this case, the Poynting vector of the set of coupled waves must be used. This Poynting vector can display a negative refraction. The conditions leading to negative refraction are described and several examples of negative refraction are displayed
Convexity preserving deformations of digital sets: Characterization of removable and insertable pixels
No full textIn this paper, we are interested in digital convexity. This notion is applied in several domains like image processing and discrete tomography. We choose to study the inflation and deflation of digital convex sets while maintaining the convexity property. Knowing that any digital convex set can be read and identified by its boundary word, we use the combinatorics on words perspective instead of a purely geometric approach. In this context, we characterize the points that can be added or removed over the digital convex sets without loosing its convexity. Some algorithms are given at the end of each section with examples on each process
On the Design of Artificial Neural Networks for solving Statistical Inverse Problems in Computational Biomechanics
No full textInternational audienceThis work deals with the statistical inverse identification of geometrical and mechanical properties of a biological tissue (cortical bone) using artificial neural networks (ANNs). The stochastic computational model (SCM) corresponds to a random elasto-acoustic multilayer model [1] for the ultrasonic characterization of cortical bone properties with the axial transmission technique. It allows for simulating the propagation of ultrasonic waves through a three-layer biological system made up of two deterministic homogeneous acoustic fluid layers (soft tissues and marrow bone) surrounding a random heterogeneous elastic solid layer (weaken cortical bone). A probabilistic model of the random elasticity field is introduced to take into account the uncertainties induced by the experimental configuration. The input hyperparameters of the SCM are the thicknesses of healthy and weaken parts of cortical bone, a dispersion parameter controlling the statistical fluctuations of the random elasticity field, and a spatial correlationlength along the thickness direction characterizing the spatial correlation structure of the random elasticity field. The output quantities of interest of the SCM are the scattered acoustic energies stored at 14 receivers located inside the soft tissues layer. The statistical inverse problem related to the identification of these hyperparameters from given quantities of interest may be solved using classical stochastic optimization algorithms that usually require many calls to the SCM, thus resulting in a high computational cost. Alternatively, an ANN-based identification method [2] is proposed here and applied to the identification of the hyperparameters from the quantities of interest of the SCM. An initial database is first generated by using forward simulations of the SCM and allows a dataset of hyperparameters and quantities of interest to be collected. A processed database is then constructed by conditioning the hyperparameters with respect to the quantities of interest using classical kernel density estimation methodsfor improving the ANN performance. A multilayer ANN is finally designed and trained from the processed database to learn the nonlinear mapping between the quantities of interest (ANN inputs) and the corresponding expected mean value of the hyperparameters (ANN outputs). Lastly, the trained ANN can be used to directly perform the identification of the hyperparameters from given quantities of interest.REFERENCES[1] C. Desceliers, C. Soize, S. Naili, and G. Haiat. Probabilistic model of the human cortical bone withmechanical alterations in ultrasonic range. Mechanical Systems and Signal Processing, 32:170–177,2012.[2] F. Pled, C. Desceliers, and T. Zhang. A robust solution of a statistical inverse problem in multiscalecomputational mechanics using an artificial neural network. Computer Methods in AppliedMechanics and Engineering, 373:113540, 2021
Severity features of suicide attempters with epilepsy
No full textInternational audienceBackground: After the Food and Drug Administration alert about antiepileptic medication and suicide, incident epilepsy has been associated with first or recurrent suicide attempts independently of psychiatric comorbidities and antiepileptic treatment. Following this thread, the aim of this study was to analyze if epilepsy was associated with a higher severity of lifetime suicide attempts (SAs).Methods: Analyses were carried out on 1677 adults hospitalized between 1999 and 2012 after a SA in a specialized ward for affective episodes. Five severity features were studied: frequent SAs (>2), early onset of first SA (≤26 years), history of violent SA, high suicide intent and high lethality of the SA. Adjusted logistic regression models were used to estimate the association between the lifetime diagnosis of epilepsy and the severity features.Results: Among suicide attempters, ninety-three patients reported a lifetime diagnosis of epilepsy (5.5%). Epileptic patients diagnosed after the first SA were more likely to be frequent suicide attempters than non-epileptic ones. They showed also higher SA planification scores.Limitations: Diagnosis accuracy is limited by the use of self-reports for epilepsy. The lack of precise information about the disease course and treatment have not allowed for further statistical analysis. With regard to psychiatric comorbidities, personality disorders could not be taken into account.Conclusions: Suicide attempters with epilepsy present an increased severity in some aspects of their suicidal behavior regardless of demographic and clinical variables. Our results give support to the existence of a bidirectional association between epilepsy and suicidal behavior
Prédictions de la stabilité et des propriétés électroniques de phases Heusler quaternaires par apprentissage automatique
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Random Geometric Graph: Some recent developments and perspectives
No full textThis is a research report that is part of a Chapter of a PhD thesis. An updated version will be available soon.International audienceThe Random Geometric Graph (RGG) is a random graph model for network data with an underlying spatial representation. Geometry endows RGGs with a rich dependence structure and often leads to desirable properties of real-world networks such as the small-world phenomenon and clustering. Originally introduced to model wireless communication networks, RGGs are now very popular with applications ranging from network user profiling to protein-protein interactions in biology. RGGs are also of purely theoretical interest since the underlying geometry gives rise to challenging mathematical questions. Their resolutions involve results from probability, statistics, combinatorics or information theory, placing RGGs at the intersection of a large span of research communities. This paper surveys the recent developments in RGGs from the lens of high dimensional settings and non-parametric inference. We also explain how this model differs from classical community based random graph models and we review recent works that try to take the best of both worlds. As a by-product, we expose the scope of the mathematical tools used in the proofs
From paper-pencil to tablet-based assessment: a comparative study at the end of primary school
No full textInternational audienceAssessments are increasingly being designed on a digital artefact (computer or tablet), while in France the equipment rate in primary schools is still low. Some computer-based assessment tasks use specific software functionalities (the dynamic aspect of a geometric figure for example), while others "migrate" from paper and pencil (PP) to digital artefact without using specific functionalities of dedicated software. In this research, we are interested in the validity of assessment tasks designed on tablet (especially when students do not usually use a tablet in the classroom and/or in assessment situations) and in the effects of migration (from PP to tablet) on student performance and procedures from one medium to another
On models to describe the volume in the context of establishing high-pressure Gibbs energy databases
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Species-Specific Molecular Barriers to SARS-CoV-2 Replication in Bat Cells
No full textInternational audienceBats are natural reservoirs of numerous coronaviruses, including the potential ancestor of SARS-CoV-2. Knowledge concerning the interaction between coronaviruses and bat cells is sparse. We investigated the ability of primary cells from Rhinolophus and Myotis species, as well as of established and novel cell lines from Myotis myotis, Eptesicus serotinus, Tadarida brasiliensis, and Nyctalus noctula, to support SARS-CoV-2 replication. None of these cells were permissive to infection, not even the ones expressing detectable levels of angiotensin-converting enzyme 2 (ACE2), which serves as the viral receptor in many mammalian species. The resistance to infection was overcome by expression of human ACE2 (hACE2) in three cell lines, suggesting that the restriction to viral replication was due to a low expression of bat ACE2 (bACE2) or the absence of bACE2 binding in these cells. Infectious virions were produced but not released from hACE2-transduced M. myotis brain cells. E. serotinus brain cells and M. myotis nasal epithelial cells expressing hACE2 efficiently controlled viral replication, which correlated with a potent interferon response. Our data highlight the existence of species-specific and cell-specific molecular barriers to viral replication in bat cells. These novel chiropteran cellular models are valuable tools to investigate the evolutionary relationships between bats and coronaviruses