Effects of landscape structure on vegetation and some animal groups after agriculture abandonment

This research was carried out on the montane belt of a south-exposed watershed in the Intermediary Alps which have been hit by agriculture abandonment. The aim of the study was to study the relationships between vegetation, landscape mosaic, and two kinds of animals using this space at different scales: roe deer (Capreolus capreolus) and earthworms (lumbricids). Landscape dynamics (post-cultural recolonisation) and landscape structure have been approached by means of the Arc/Info geographical information system (GIS). Several methods used to study on one hand roe deer distribution, and, on the other, earthworm abundance and diversity are developed. Of these, in particular, GIS processing is used to sample earthworms according to vegetation dynamics, and roe deer distribution is related to landscape heterogeneity. Earthworms are more abundant and diversified in the key steps of vegetation dynamics. These lumbricids can be considered as functional indicators of these dynamics. Results also demonstrate that both the vegetation type and the landscape heterogeneity have a direct influence on the use of the space by the roe deer. They show themselves to be structural indicators of the landscape.     

Un environnement de conception de systèmes distribués basé sur UML

This paper introduces a new environment for developing distributed systems. It is based on theTurtle uml profile. Analysis and design phases, described in previous papers, have been extended with an additional deployment phase. In this new step,Turtle components are deployed over hardware execution nodes, and nodes are connected together throughout links,Turtle deployment diagrams are given a formal semantics inRt-lotos, therefore following the approach used forTurtle analysis and design diagrams. Moreover, the paper presents a Java code generator which outputs appropriate Java code forTurtle deployment diagrams. This code is automatically deployable on networks because it implements node communication using network protocols such asUdp orRmi. ttool, the turtle toolkit has been extended to support these new diagrams and code generators. The attack of protected data exchanged throughout securedHttp sessions serves as example.     

20-Gb/s PolDM Duobinary Transmission Over 350-km SSMF Supported by a Polarization Stabilizer and an Optical Dispersion Compensator

A 20-Gb/s transmission over 350-km standard single-mode fiber exploiting duobinary dispersion robustness and polarization-division multiplexing has been demonstrated. The system performance is evaluated employing an automatic endless polarization stabilizer and a suitably designed transmitter-side optical dispersion compensator.     

The ProteoMiner and the FortyNiners: searching for gold nuggets in the proteomic arena

The present review covers modern aspects of combinatorial peptide ligand libraries (CPLL), as used to analyze the "low-abundance proteome" in association with mass spectrometry. First, the capturing properties of baits of different lengths (from single amino acid to hexa-peptides) are described to show that a plateau is rapidly reached above a tetra-peptide in length, thus confirming the validity of having adopted hexapeptides for the considered application. The mechanism of interaction with proteins from very complex proteomes and the ability to decrease the dynamic concentration range is demonstrated with the help of mass spectrometry analysis. Examples are given on how treatment with CPLLs dramatically improves the detectability of peptides in mass spectrometry analysis, permitting detection of a very large number of proteins as compared with control, untreated samples. The use of complementary libraries is discussed with the aim to discover additional low-abundance species that escaped the first library. A discussion on the possibility to discover extremely rare gene products, and the quantitative aspect of the technology when associated with mass spectrometry is also provided. Some insights on the applications for hidden, low-abundance biomarkers are also presented.     

Modern strategies for protein quantification in proteome analysis: advantages and limitations

Over the last 3 years, a number of mass spectrometry-based methods for the simultaneous identification and quantification of individual proteins within complex mixtures have been reported. Most, if not all, of such strategies apply a two-step approach: the first for the separation of proteins or peptides, and the second uses mass spectrometry to identify and quantify the individual components. To simplify the outcome of both steps, certain chemicals and heavy-isotope-labeling are commonly used in the early stages of sample preparation (except in differential fluorescence labeling protocols). The ultimate goal of these strategies is to be able to identify every protein expressed in a cell or tissue, and to determine each protein's abundance, state of modification, and possible involvement in multi-protein complexes. In this review, an attempt is made to highlight the salient characteristics of the existing strategies with particular attention to their strengths and weaknesses.     

Study of haptoglobin-hemoglobin complexes by titration curves, capillary electrophoresis and capillary isoelectric focusing

A novel method is described for monitoring complex formation between macromolecules, based on combined isoelectric focusing-electrophoresis in capillaries. The example studied is the binding of serum haptoglobin (Hp) to hemoglobin (Hb). A known amount of Hb is focused in a capillary in a pH 6-8 range (pI of Hb = 7.0) and thus kept temporarily "immobilized" in the electrophoretic chamber. Subsequently, increasing amounts of ligand (Hp) are loaded cathodically and allowed to sweep past the focused Hb zone. As the complex formed has a pI value well-outside the bounds of such a pH gradient (the 1:1 molar Hb-Hp complex has a pI of 5.5, the 1 to 1/2 molar Hp-Hb complex has a pI of 5.0) it escapes immobilization and moves past the detector window, where it is monitored and quantified. Since the detector is set at 416 nm, where only Hb absorbs, and since the molar extinction coefficient of Hb is well known, it is quite easy to calculate the molar amount of Hb bound to the complex. As an additional check, the amount of unreacted Hb can now be mobilized by disrupting the pH gradient and allowing this residual free Hb to also reach the detector and be quantified. The method is easy, fast, simple and fully automated and thus could represent a valid alternative to existing methods in clinical chemistry for quantifying the amount of Hp in human sera in pathological conditions, such as hemolytic anemias and transfusion reactions.     

Reservoir Management Using a Network Flow Optimization Model Considering Quadratic Convex Cost Functions on Arcs

The allocation of water resources between different users is a hard task for water managers because they must deal with conflicting objectives. The main objective is to obtain the most accurate distribution of the resource and the associated circulating flows through the system. This induces the need for a river basin optimization model that provides optimized results. This article presents a network flow optimization model to solve the water allocation problem in water resource systems. Managing a water system consists in providing water in the right proportion, at the right place and at the right time. Time expanded network allows to take into consideration the temporal dimension in the decision making. Since linear cost functions on arcs present many limitations and are not realistic, quadratic convex cost functions on arcs are considered here. The optimization algorithm developed herein extend the cycle canceling algorithm developed for linear cost functions. The methodology is applied to manage the three reservoirs of La Haute-Vilaine’s watershed located in the north west of France to protect a three vulnerable areas from flooding. The results obtained with the algorithm are compared to a reference scenario which consists in considering reservoirs transparent. The results show that the algorithm succeeds in managing the reservoir releases efficiently and keeps the flow rates below the vigilance flow in the vulnerable areas.     

3D Point Cloud Analysis for Detection and Characterization of Defects on Airplane Exterior Surface

Three-dimensional surface defect inspection remains a challenging task. This paper describes a novel automatic vision-based inspection system that is capable of detecting and characterizing defects on an airplane exterior surface. By analyzing 3D data collected with a 3D scanner, our method aims to identify and extract the information about the undesired defects such as dents, protrusions or scratches based on local surface properties. Surface dents and protrusions are identified as the deviations from an ideal, smooth surface. Given an unorganized point cloud, we first smooth noisy data by using Moving Least Squares algorithm. The curvature and normal information are then estimated at every point in the input data. As a next step, Region Growing segmentation algorithm divides the point cloud into defective and non-defective regions using the local normal and curvature information. Further, the convex hull around each defective region is calculated in order to englobe the suspicious irregularity. Finally, we use our new technique to measure the dimension, depth, and orientation of the defects. We tested and validated our novel approach on real aircraft data obtained from an Airbus A320, for different types of defect. The accuracy of the system is evaluated by comparing the measurements of our approach with ground truth measurements obtained by a high-accuracy measuring device. The result shows that our work is robust, effective and promising for industrial applications.     

Participatory Bayesian modelling for sustainable and efficient river restoration projects: Feedback from the case study of the Gave de Pau River,Hautes‐Pyrénées,France

Through the diversity of criteria and stakes, the uncertain nature of the entailed phenomena and the multi‐scale aspects to be taken into account, a river restoration project can be considered as a complex problem. Integrative approaches and modelling tools are thus needed to help river managers make predictions on the evolution of hydromorphological, socio‐economic, safety and ecological issues. Such approach can provide valuable information for handling long‐term management plans that consider the interaction and the balance of stakeholders interests and river system functioning. In this paper, we present a probabilistic participatory modelling (PM) method that assesses the effects of given restoration actions, knowing the hydromorphological modifications that they may induce on the safety, ecological and socio‐economic aspects with the help of local stakeholders through several workshops. To support this strategy, we used Bayesian networks (BNs) as modelling tools as their causal graphs can combine multidimensional knowledge and data from diverse natures. We introduce the causal graphs elaborated with the help of the stakeholders and convert it into BNs that can assist restoration decisions by considering the available decision and utility functions to provide guidance to decision‐makers. This was applied to the “Lac des Gaves” reach in the Hautes‐Pyrénées, France, a reach that has gone through severe sediment extractions for over 50 years. Each network represents possible restoration decisions linked to one of the observed issues. The paper demonstrates how BNs used as a decision support system (DSS) can help to assess the influence of given management strategies on the river system with the consideration of stakeholders’ knowledge and integration in all the modelling process.     

Swelling behavior of polymeric membranes to metalworking fluids

In some working places, such as metal manufacturing or automotive services, mechanical hazards commonly occur along with chemical hazards, particularly metalworking fluids (MWFs). The presence of these chemicals could modify the properties of gloves made from polymeric materials and thus reduce their protective properties against chemical contamination (solvent, MWFs) and mechanical risks (puncture and cutting). This work focused on determining the swelling characteristics and the resistance of six polymeric membranes which were exposed to seven industrial MWFs. We found that the swelling tests can be used to classify the potential of coating polymers in descending order of their resistance to MWFs: nitrile, polyurethane > poly(vinyl chloride), neoprene > butyl, latex. The analysis by multiple linear regression showed, for the first time, that the density or the viscosity‐gravity constant of the fluid and Hansen's solubility parameters of the polymers have a significant impact on the swelling of polymer. For the first time, two new multiple regression models have been proposed, to predict the swelling phenomena of polymers under various MWFs with an accuracy of ≈80%. The effect of temperature on mechanical properties and morphology of material was also examined. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45717.