Desynchronization and inhibition of Kuramoto oscillators by scalar mean-field feedback

Motivated by neuroscience applications, and in particular by the deep brain stimulation treatment for Parkinson’s disease, we have recently derived a simplified model of an interconnected neuronal population under the effect of its mean-field proportional feedback. In this paper, we rely on that model to propose conditions under which proportional mean-field feedback achieves either oscillation inhibition or desynchronization. More precisely, we show that for small natural frequencies, this scalar control signal induces an inhibition of the collective oscillation. For the closed-loop system, this situation corresponds to a fixed point which is shown to be almost globally asymptotically stable in the fictitious case of zero natural frequencies and all-to-all coupling and feedback. In the case of an odd number of oscillators, this property is shown to be robust to small natural frequencies and heterogencities in both the coupling and feedback topology. On the contrary, for large natural frequencies, we show that scalar proportional mean-field feedback is able to induce desynchronization. After having recalled a formal definition for desynchronization, we show how it can be induced in a network of originally synchronized oscillators.     

Cognitive conflict in human-automation interactions: a psychophysiological study

The review of literature in sociology and distributed artificial intelligence reveals that the occurrence of conflict is a remarkable precursor to the disruption of multi-agent systems. The study of this concept could be applied to human factors concerns, as man-system conflict appears to provoke perseveration behavior and to degrade attentional abilities with a trend to excessive focus. Once entangled in such conflicts, the human operator will do anything to succeed in his current goal even if it jeopardizes the mission. In order to confirm these findings, an experimental setup, composed of a real unmanned ground vehicle, a ground station is developed. A scenario involving an authority conflict between the participants and the robot is proposed. Analysis of the effects of the conflict on the participants' cognition and arousal is assessed through heart-rate measurement (reflecting stress level) and eye-tracking techniques (index of attentional focus). Our results clearly show that the occurrence of the conflict leads to perseveration behavior and can induce higher heart rate as well as excessive attentional focus. These results are discussed in terms of task commitment issues and increased arousal. Moreover, our results suggest that individual differences may predict susceptibility to perseveration behavior.     

Identification and Molecular Cloning of Putative Odorant-Binding Proteins from the American Palm Weevil, Rhynchophorus palmarum L.

We have identified and cloned the cDNAs encoding two odorant-binding proteins (OBPs) from the American palm weevil (APW) Rhynchophorus palmarum (Coleoptera, Curculionidae). Degenerate primers were designed from the N-terminal sequences and were used in polymerase chain reaction (PCR) in order to obtain full-length sequences in both males and females. In both sexes, two different cDNAs were obtained, encoding 123 and 115 amino acid-deduced sequences. Each sequence showed few amino acid differences between the sexes. The proteins were named RpalOBP2 and RpalOBP4 for male, RpalOBP2' and RpalOBP4' for female, with the types 2 and 4 presenting only 34% identities. These proteins shared high identity with previously described coleopteran OBPs. In native gels, RpalOBP2 clearly separated into two bands and RpalOBP4 into three bands, suggesting the presence of several conformational isomers. Thus, OBP diversity in this species may rely on both the presence of OBPs from different classes and the occurrence of isoforms for each OBP.     

Effective Tension Active Cross-Section of Reinforced Concrete Beams After Cracking

In the design of concrete structures, estimation of the deflection of the structural members under the service loads is often a critical factor. Strains and displacements are linked to the tension stiffening effect, which is not quantified in the standards. The CEB-FIP model code proposes an interesting simplified method for evaluating the concrete tension stiffening effect on reinforced concrete behavior. One of the parameters which enables the mechanical contribution of the concrete to be quantified is the effective tensile active section of the reinforced concrete beams. In this paper, a new method for calculating the effective tensile active section A _ct.ef is proposed. The calculation is based on an analytical model of stress distribution in the full depth of the concrete section. An experimental study on several reinforced concrete beams is reported. The results show that the new proposed model enhances the accuracy of the beam deflection predictions significantly.     

A finite macro-element for corroded reinforced concrete

This paper proposes a model of the mechanical behaviour of corroded reinforced concrete members subjected to bending under service load. The model is based on the formulation of a macro-element to be used in FEM analysis, having a length equal to the distance between two consecutive flexural cracks and a cross-section equal to the member cross-section. The mechanical formulation is directly written in generalized variables (bending moment and curvature) and is based on the concept of the transfer length necessary for the transmission of tensile load from re-bar to tensile concrete thanks to the bond. It is thus possible to take into account the effect of reinforcement corrosion on the bond between re-bar and concrete, by increasing the transfer length versus intensity of corrosion. The variation of the transfer length versus corrosion is expressed using a scalar damage parameter. A first experimental validation is performed on a 17-year-old beam kept in a chloride environment under its service load.     

L'échelle de dramatisation face à la douleur PCS-CF: Adaptation canadienne en langue fran?aise de l'échelle Pain Catastrophizing Scale.

This study examined the psychometric properties of the PCS-CF, a French-Canadian adaptation of the Pain Catastrophizing Scale (Sullivan, Bishop & Pivik, 1995). One hundred and twenty undergraduate students (83 women; 37 men) completed the PCS-CF and measures of anxiety and depression prior to immersing their hand in ice water for 1-minute. A subset of 39 participants (28 females; 11 males) also completed a second pain task involving an ascending series of electrocutaneous stimulations. Participants' verbal and non-verbal pain behaviours during and immediately after the immersion task were recorded and subsequently independently coded. Reliability analyses revealed that the PCS-CF total score and subscale scores have a high degree of internal consistency and test-retest reliabilities that are comparable to the original Pain Catastrophizing Scale. PCS-CF scores were associated with higher levels of self-reported pain during the ice water immersion task and decreased pain tolerance during electrocutaneous stimulation. Individuals with elevated PCS-CF scores also displayed a more diverse repertoire of pain behaviours than their low PCS-CF counterparts. Previous findings that catastrophizing scores are able to discriminate criterion groups of males and females were also replicated. Given the highly correlated factors obtained in analyses of the dimensionality of the PCS-CF, the structure suggested by the authors of the original scale is only partially supported. However, the results taken together suggest that the PCS-CF is both a reliable and valid measure of the pain catastrophizing construct that is psychometrically comparable to the original PCS. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Neuronal Signal Transduction Aided by Noise at Threshold and at Saturation

A classical model of neuronal signal transmission describing the presence of both a threshold and a saturation in the neuron response is considered. This model is used to analyze the transduction by the neuron of various types of information-carrying input signals in the presence of noise. Improvement by noise of the performance via stochastic resonance is established for transmission in both the threshold and the saturation regimes. Stochastic resonance at saturation is a novel form, expressing that the distortion experienced by large input signals transmitted at saturation, can be reduced by addition of noise.     

Displacement Following of Hidden Objects in a Video Sequence

In a video sequence, computing the motion of an object requires the continuity of the apparent velocity field. This property does not hold when the object is hidden by an occlusion during its motion. The minimization of an energy functional leads to a simple algorithm which allows the recovery of the most likely trajectory of the occluded object from optical flow data at the border of the occlusion. Optical flow used for developing our method is an improvement on any variational technique of computing it. This improvement is based on a multichannel segmentation.     

Probabilistic Approach to Predict Cracking in Lightly Reinforced Microconcrete Panels

The ultimate strength of structures made of brittle materials—such as microconcrete—strongly depends on microstructural defects, the structure size, and the loading pattern. Probabilistic approaches allow one to take account of such dependencies. By using a Weibull model, cracking of ferrocement panels is analyzed. Provided the behavior of the reinforcement remains elastic, it is shown that the Weibull parameters identified on unreinforced microconcrete samples tested in flexure may be used to predict multiple cracking in ferrocement panels tested in tension. A key aspect of the analysis is related to the understanding and modeling of the stress heterogeneity effect on the local failure probability of unreinforced as well as reinforced microconcrete by the use of a so-called Weibull stress.     

Distributed machining control and monitoring using smart sensors/actuators

The study of smart sensors and actuators led, during the past few years, to the development of facilities which improve traditional sensors and actuators in a necessary way to automate production systems. In another context, many studies have been carried out aimed at defining a decisional structure for production activity control and the increasing need of reactivity leads to the autonomization of decisional levels close to the operational system. We study in this paper the natural convergence between these two approaches and we propose an integration architecture, dealing with machine tool and machining control, that enables the exploitation of distributed smart sensors and actuators in the decisional system.