Remote-sensing reflectance of turbid sediment-dominated waters. Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios

Variations of sediment type (grain size and refractive index) and changing illumination conditions affect the reflectance signal of coastal waters and limit the accuracy of sediment-concentration estimations from remote-sensing measurements. These effects are analyzed from numerous in situ remote-sensing measurements carried out in the Gironde and Loire Estuaries and then reduced and partly eliminated when reflectance ratios between the near infrared and the visible are considered. These ratios showed high correlation with the sediment concentration. On the basis of the obtained relationships, performing correspondence functions were established that allow an accurate estimation of suspended sediments in the estuaries from Système Probatoire d'Observation de la Terre, Landsat, and Sea-Viewing Wide Field-of-View Sensor data, independently of the date of acquisition.     

Curved finite element methods for the solution of singular integral equations on surfaces in R3

We have shown in [1]that the singular integral equation (1.2) on a closed surface Γ of R³ admits a unique solution q and is variational and coercive in the Hilbert space $\text{H}{}^{\mathrm{<mtext>?</mtext><mtext>1</mtext><mtext>2</mtext>}}$(Γ). In this paper, with the help of curved finite elements, we introduce an approximate surface Γ_h, and an approximate problem on Γ_h, whose solution is q_h. Then we study the error of approximation |q ? q_h| in some Hubert spaces and also the associated error |u ? u_h| of the potential.     

On extended P4-reducible and extended P4-sparse graphs

A graph G was defined in [16] as P₄-reducible, if no vertex in G belongs to more than one chordless path on four vertices or P₄. A graph G is defined in [15] as P₄-sparse if no set of five vertices induces more than one P₄, in G. P₄-sparse graphs generalize both P₄-reducible and the well known class of p₄-free graphs or cographs. In an extended abstract in [11] the first author introduced a method using the modular decomposition tree of a graph as the framework for the resolution of algorithmic problems. This method was applied to the study of P₄-sparse and extended P₄-sparse graphs.

In this paper, we begin by presenting the complete information about the method used in [11]. We propose a unique tree representation of P₄-sparse and a unique tree representation of P₄-reducible graphs leading to a simple linear recognition algorithm for both classes of graphs. In this way we simplify and unify the solutions for these problems, presented in [16–19]. The tree representation of an n-vertex P₄-sparse or a P₄-reducible graph is the key for obtaining O(n) time algorithms for the weighted version of classical optimization problems solved in [20]. These problems are NP-complete on general graphs.

Finally, by relaxing the restriction concerning the exclusion of the C₅ cycles from P₄-sparse and P₄-reducible graphs, we introduce the class of the extended P4-sparse and the class of the extendedP₄-reducible graphs. We then show that a minimal amount of additional work suffices for extending most of our algorithms to these new classes of graphs.     

Evaluation of the quality of collaboration between the client and the therapist in phobia treatments

A growing number of empirical studies evaluate the influence of Mental Health (MH) technology on the clinical effectiveness, the therapeutic relationship (i.e., therapeutic alliance), and usability issues. However, to the authors’ knowledge, no studies have yet been performed regarding the influence of technology on the therapeutic process in terms of collaboration. This study evaluates the quality of collaboration between the client and therapist in Augmented Reality Exposure Therapy (ARET) context and the traditional, In Vivo Exposure Therapy (IVET) context with the Therapeutic Collaborative Scale (TCS). Twenty participants received an intensive session of cognitive behavioral therapy in either a technology-mediated therapeutic context or in a traditional therapeutic context. The results indicate that both therapeutic conditions show high collaboration scores. However, the asymmetry of roles between the therapist and the client under both conditions were detected. Also, a greater level of distraction was observed for therapists in ARET, which affected the quality of the therapists’ involvement in the therapeutic session. The implications of these results are discussed.     

Satellite-derived parameters for biological modelling in coastal waters: Illustration over the eastern continental shelf of the Bay of Biscay

In biological modelling of the coastal phytoplankton dynamics, the light attenuation coefficient is often expressed as a function of the concentrations of chlorophyll and mineral suspended particulate matter (SPM). In order to estimate the relationship between these parameters over the continental shelf of the northern Bay of Biscay, a set of in situ data has been gathered for the period 1998-2003 when SeaWiFS imagery is available. These data comprise surface measurements of the concentrations of total SPM, chlorophyll, and irradiance profiles from which is derived the attenuation coefficient of the photosynthetically available radiation, K_PAR. The performance of the IFREMER look-up table used to retrieve the chlorophyll concentration from the SeaWiFS radiance is evaluated on this new set of data. The quality of the estimated chlorophyll concentration is assessed from a comparison of the variograms of the in situ and satellite-derived chlorophyll concentrations. Once the chlorophyll concentration is determined, the non living SPM, which is defined as the SPM not related to the dead or alive endogenous phytoplankton, is estimated from the radiance at 555 nm by inverting a semi-analytic model. This method provides realistic estimations of concentrations of chlorophyll and SPM over the continental shelf all over the year. Finally, a relationship, based on non living SPM and chlorophyll, is proposed to estimate K_PAR on the continental shelf of the Bay of Biscay. The same formula is applied to non living SPM and chlorophyll concentrations, observed in situ or derived from SeaWiFS radiance.     

Surface plasmon resonance imaging (SPRi) as an alternative technique for rapid and quantitative screening of small molecules, useful in drug discovery

Surface plasmon resonance imaging (SPRi) is a label free technology for biomolecular interaction, which gives access to binding kinetic parameters from real time acquisition. It offers the possibility to test in a single run a large number of interactions, allowing rapid identification of the most suitable compounds toward a given biological entity. Until now, this technique has proven to be relevant for interaction between relatively large molecules (protein, antibodies, DNA) but has not been challenged yet for the screening of small molecules that can be of interested in the field of drug discovery. As a proof a principle, we have used SPRi to screen for interaction of several small molecules, referred to as G4-ligands on G-quadruplex DNA. This technology allowed to easy discrimination of the binding properties of four G4-ligands on quadruplex DNA models.     

Processing radio frequency ultrasound images: a robust method for local spectral features estimation by a spatially constrained parametric approach

Spectral estimation is a major component in studies aiming at characterizing biological tissues through the analysis of backscattered radio frequency (RF) ultrasonic signals and images. However, conventional spectral estimation techniques yield a well-known trade-off between spatial resolution and variance. The backscattered signals are stochastic by nature, so short-term local analysis results in a high variance of the estimates, which cannot efficiently be reduced through conventional spatial averaging. We address this issue by describing a spectral estimation technique that reduces the variance of the estimates (by smoothing the local estimates in spectrally homogeneous regions) while preserving spectral discontinuities (i.e., the smoothing is not performed across regions with different spectral contents). The proposed approach is set in a Bayesian framework and is based on local autoregressive (AR) estimation, constrained by smoothness priors. These smoothness priors are introduced through a Markov random field in which the associated potential functions are nonquadratic, allowing thereby to preserve discontinuity. The method is validated on simulated RF images and tested on echocardiographic images acquired in vivo. The results are compared to the estimates provided by the conventional Burg technique. These results clearly demonstrate the ability of the proposed approach to improve spectral estimation in terms of variance reduction and discontinuity detection.     

Computational aspects of the workload distribution in the MMPP/GI/1queue

We show how the analysis of Markov modulated rate processes can be used to address the problem of computing the distribution of W, the stationary workload in the MMPP/GI/1 queue. Using the results of papers by Anick et al. (1982); Mitra (1988); and Elwalid et al. (1991), we present the decomposition properties of the Laplace transform of W and efficient computational algorithms for computing its distribution. The techniques are also applied to compute the bounds on the distribution of W developed by Liu et al. (see JACM, vol.44, no.2, p.366-94, 1997). Numerical results illustrating the usefulness of the methods are given for the case of the superposition of independent, nonidentical sources     

High temperature lithium cells using conversion oxide electrodes

Oxidized stainless steel electrodes containing chromium oxides without any conducting additives or binder have been successfully cycled at high temperatures (up to 100 °C) in organic solvent-based electrolytes with high reversibility. Cycling at high temperature results in an enhancement of the capacity at lower voltages, which is maintained upon cycling. After studying different electrolyte candidates, the best results were obtained using lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) dissolved in ethylene carbonate.