Optical coherence of a scalar wave influenced by first-order and second-order statistics of its random phase

We analyze a simple model of a scalar optical wave with partial coherence. The model is devised to describe the influence on the coherence of the wave, of the statistical properties of its random phase, including both the second-order statistics (phase correlation) — which is classic, but also the first-order statistics (phase distribution) — which is nonclassic. Expectedly, upon increasing the disorder of the fluctuating phase through a reduction of its correlation duration, the model shows that the coherence of the wave is always reduced. By contrast, upon increasing the disorder of the fluctuating phase through an increase of its dispersion, the model reveals that the coherence of the wave can sometimes be enhanced. This beneficial consequence of an increase in disorder is related to the phenomenon of stochastic resonance or improvement by noise in signal processing

On the value of the Kullback-Leibler divergence for cost-effective spectral imaging of plants by optimal selection of wavebands

The practical value of a criterion based on statistical information theory is demonstrated for the selection of optimal wavelength and bandwidth of low-cost lighting systems in plant imaging applications. Kullback–Leibler divergence is applied to the problem of spectral band reduction from hyperspectral imaging. The results are illustrated on various plant imaging problems and show similar results to the one obtained with state-of-the-art criteria. A specific interest of the proposed approach is to offer the possibility to integrate technological constraints in the optimization of the spectral bands selected

A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans

The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors' data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters

ElonCam : instrumentation et analyse d'images pour le suivi automatisé individualisé du développement de semences et de plantules

Le système ElonCam est en cours de développement dans le cadre d\u27une collaboration entre le LARIS, le GEVES-SNES et l\u27INRA d\u27Angers - IRHS. Il s’agit d’un système de vision, constitué d’un système d’acquisition d’images piloté par ordinateur, et d’un logiciel de traitement et d\u27analyse d\u27images couleur RVB, qui permet de réaliser des mesures automatisées sur les semences et les plantules au cours de leur développement. Le système d’acquisition peut incorporer différentes modalités d\u27imagerie, et il est actuellement employé en imagerie visible (voir Fig. 1). L\u27acquisition des images est effectuée en lumière verte inactinique (censée simuler l\u27obscurité et ne pas influencer le développement des plantules). Afin de minimiser l\u27apport d\u27énergie lumineuse l\u27éclairage intermittent est synchronisé avec la prise de vue. Les graines sont semées dans une boîte de Pétri contenant de la gélose (milieu de culture transparent) placée à la verticale afin de respecter le géotropisme. Le logiciel de traitement d\u27images détecte, isole, labellise puis mesure les semences et les plantules. L\u27analyse numérique des images permet d\u27aboutir à la mesure individuelle automatisée des semences au cours de la germination puis des plantules et de leurs organes d\u27intérêt en fonction du temps, selon les conditions de la croissance. Afin de gérer les croisements de plantules, un algorithme de suivi de structures arborescentes a été développé. Le système de vision vise à contribuer au phénotypage automatisé haut-débit des semences et plantules, afin de tester la capacité à germer et la vitesse de croissance pour différentes espèces et différents génotypes, et en vue d\u27améliorer leurs propriétés et rendement. Le système a été testé pour la caractérisation de différentes espèces comme Medicago truncatula, colza, blé, tournesol, et également la betterave dans le cadre du programme ANR Investissements d\u27Avenir AKER où les coauteurs sont impliqués et qui concerne l\u27amélioration de la betterave sucrière pour laquelle la France est l\u27un des premiers producteurs mondiaux. Ce travail a bénéficié d\u27une aide de l\u27État gérée par l\u27Agence Nationale de la Recherche au titre du programme "Investissements d\u27Avenir" portant la référence ANR-11-BTBR-0007 (programme AKER)

Modeling Epac1 interactions with the allosteric inhibitor AM-001 by co-solvent molecular dynamics

The exchange proteins activated by cAMP (EPAC) are implicated in a large variety of physiological processes and they are considered as promising targets for a wide range of therapeutic applications. Several recent reports provided evidence for the therapeutic effectiveness of the inhibiting EPAC1 activity cardiac diseases. In that context, we recently characterized a selective EPAC1 antagonist named AM-001. This compound was featured by a non-competitive mechanism of action but the localization of its allosteric site to EPAC1 structure has yet to be investigated. Therefore, we performed cosolvent molecular dynamics with the aim to identify a suitable allosteric binding site. Then, the docking and molecular dynamics were used to determine the binding of the AM-001 to the regions highlighted by cosolvent molecular dynamics for EPAC1. These analyses led us to the identification of a suitable allosteric AM-001 binding pocket at EPAC1. As a model validation, we also evaluated the binding poses of the available AM-001 analogues, with a different biological potency. Finally, the complex EPAC1 with AM-001 bound at the putative allosteric site was further refined by molecular dynamics. The principal component analysis led us to identify the protein motion that resulted in an inactive like conformation upon the allosteric inhibitor binding

Recent advances on information transmission and storage assisted by noise

The interplay between nonlinear dynamic systems and noise has proved to be of great relevance in several application areas. In this presentation, we focus on the areas of information transmission and storage. We review some recent results on information transmission through nonlinear channels assisted by noise. We also present recent proposals of memory devices in which noise plays an essential role. Finally, we discuss new results on the influence of noise in memristors.Comment: To be published in "Theory and Applications of Nonlinear Dynamics: Model and Design of Complex Systems", Proceedings of ICAND 2012 (Springer, 2014

Universality of Level Spacing Distributions in Classical Chaos

We suggest that random matrix theory applied to a classical action matrix can be used in classical physics to distinguish chaotic from non-chaotic behavior. We consider the 2-D stadium billiard system as well as the 2-D anharmonic and harmonic oscillator. By unfolding of the spectrum of such matrix we compute the level spacing distribution, the spectral auto-correlation and spectral rigidity. We observe Poissonian behavior in the integrable case and Wignerian behavior in the chaotic case. We present numerical evidence that the action matrix of the stadium billiard displays GOE behavior and give an explanation for it. The findings present evidence for universality of level fluctuations - known from quantum chaos - also to hold in classical physics