Distributed synaptic weights in a LIF neural network and learning rules

Leaky integrate-and-fire (LIF) models are mean-field limits, with a large number of neurons, used to describe neural networks. We consider inhomogeneous networks structured by a connec-tivity parameter (strengths of the synaptic weights) with the effect of processing the input current with different intensities. We first study the properties of the network activity depending on the distribution of synaptic weights and in particular its discrimination capacity. Then, we consider simple learning rules and determine the synaptic weight distribution it generates. We outline the role of noise as a selection principle and the capacity to memorized a learned signal.Comment: Physica D: Nonlinear Phenomena, Elsevier, 201

Le contrôle exercé sur la conjointe : comparaison de quatre groupes d’hommes

This paper presents the results of an exploratory study on the control exerted by men over their spouse. Four groups of 15 men each, were compared: 1) men with no criminal record and who had volontarily taken part in a community program for violent men; 2) men accused of spouse abuse, exclusively; 3) men accused of spouse abuse and other crimes; 4) men selected at random from the community. The type of sample was non probabilistic. Three questionnaires were administered: 1) a demographic questionnaire 2) the "Abusive Behavior Inventory" (Shepard and Campbell, 1992) and 3) the "Psychological Maltreatment of Women Inventory" (Tolman, 1989). The results demonstrated that the control group (group 4) displayed "stability" in comparaison with the groups of accused men (groups 2 and 3) where important difficulties and "marginality" were observed. "Non accused" spouse abusers (group 1) obtained middle ranged scores. Scores from the four sub-scales in the two attitudinal inventories corrrelated significantly and were in the predicted direction. As the level of psychological or physical abuse increased, so did the desire to dominate and isolate women. Given the small sample size and the quasi-experimental nature of the design, the results are not considered as definitive; however, they provide directions for future research

Protostellar birth with ambipolar and ohmic diffusion

The transport of angular momentum is capital during the formation of low-mass stars; too little removal and rotation ensures stellar densities are never reached, too much and the absence of rotation means no protoplanetary disks can form. Magnetic diffusion is seen as a pathway to resolving this long-standing problem. We investigate the impact of including resistive MHD in simulations of the gravitational collapse of a 1 solar mass gas sphere, from molecular cloud densities to the formation of the protostellar seed; the second Larson core. We used the AMR code RAMSES to perform two 3D simulations of collapsing magnetised gas spheres, including self-gravity, radiative transfer, and a non-ideal gas equation of state to describe H2 dissociation which leads to the second collapse. The first run was carried out under the ideal MHD approximation, while ambipolar and ohmic diffusion was incorporated in the second calculation. In the ideal MHD simulation, the magnetic field dominates the energy budget everywhere inside and around the first core, fueling interchange instabilities and driving a low-velocity outflow. High magnetic braking removes essentially all angular momentum from the second core. On the other hand, ambipolar and ohmic diffusion create a barrier which prevents amplification of the magnetic field beyond 0.1 G in the first Larson core which is now fully thermally supported. A significant amount of rotation is preserved and a small Keplerian-like disk forms around the second core. When studying the radiative efficiency of the first and second core accretion shocks, we found that it can vary by several orders of magnitude over the 3D surface of the cores. Magnetic diffusion is a pre-requisite to star-formation; it enables the formation of protoplanetary disks in which planets will eventually form, and also plays a determinant role in the formation of the protostar itself.Comment: 18 pages, 11 figures, accepted for publication in Astronomy & Astrophysic

Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning

Machine learning is being integrated into a growing number of critical systems with far-reaching impacts on society. Unexpected behaviour and unfair decision processes are coming under increasing scrutiny due to this widespread use and its theoretical considerations. Individuals, as well as organisations, notice, test, and criticize unfair results to hold model designers and deployers accountable. We offer a framework that assists these groups in mitigating unfair representations stemming from the training datasets. Our framework relies on two inter-operating adversaries to improve fairness. First, a model is trained with the goal of preventing the guessing of protected attributes' values while limiting utility losses. This first step optimizes the model's parameters for fairness. Second, the framework leverages evasion attacks from adversarial machine learning to generate new examples that will be misclassified. These new examples are then used to retrain and improve the model in the first step. These two steps are iteratively applied until a significant improvement in fairness is obtained. We evaluated our framework on well-studied datasets in the fairness literature -- including COMPAS -- where it can surpass other approaches concerning demographic parity, equality of opportunity and also the model's utility. We also illustrate our findings on the subtle difficulties when mitigating unfairness and highlight how our framework can assist model designers.Comment: 15 pages, 3 figures, 1 tabl

Modeling the three-dimensional pair cascade in binaries. Application to LS 5039

10 pages, 11 figures, accepted for publication in Astronomy and AstrophysicsLS 5039 is a Galactic binary system emitting high and very-high energy gamma rays. The gamma-ray flux is modulated on the orbital period and the TeV lightcurve shaped by photon-photon annihilation. The observed very-high energy modulation can be reproduced with a simple leptonic model but fails to explain the flux detected by HESS at superior conjunction, where gamma rays are fully absorbed. The contribution from an electron-positron pair cascade could be strong and prevail over the primary flux at superior conjunction. The created pairs can be isotropized by the magnetic field, resulting in a three-dimensional cascade. The aim of this article is to investigate the gamma ray radiation from this pair cascade in LS 5039. This additional component could account for HESS observations at superior conjunction in the system. A semi-analytical and a Monte Carlo method for computing three-dimensional cascade radiation are presented and applied in the context of binaries. Three-dimensional cascade radiation contributes significantly at every orbital phase in the TeV lightcurve, and dominates close to superior conjunction. The amplitude of the gamma-ray modulation is correctly reproduced for an inclination of the orbit of about 40 degrees. Primary pairs should be injected close to the compact object location, otherwise the shape of the modulation is not explained. In addition, synchrotron emission from the cascade in X-rays constrains the ambient magnetic field to below 10 G. The radiation from a three-dimensional pair cascade can account for the TeV flux detected by HESS at superior conjunction in LS 5039, but the very-high energy spectrum at low fluxes remains difficult to explain in this model

Novel image analysis method for in situ monitoring the particle size distribution of batch crystallization processes

International audienceThis article presents a new in situ method to monitor the particle size distribution (PSD) during batch solution crystallization processes. Using a new in situ imaging probe, the “EZProbe sensor,” real time acquisition of 2-D images of particles during the batch process is now possible. To analyze these images, a novel image analysis method is carried out. First, segmentation and restoration algorithms are performed to identify the particles and thereafter geometrical particle measurements are achieved to obtained the PSD of the batch crystallization process over time. Satisfactory measurements are obtained provided that the overall solid concentration does not exceed a threshold above which too many overlapping crystals make discrimination between particles impossible