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.     

Optimization of Advanced Live-Cell Imaging through Red/Near-Infrared Dye Labeling and Fluorescence Lifetime-Based Strategies

Fluorescence microscopy is essential for a detailed understanding of cellular processes; however, live-cell preservation during imaging is a matter of debate. In this study, we proposed a guide to optimize advanced light microscopy approaches by reducing light exposure through fluorescence lifetime (τ) exploitation of red/near-infrared dyes. Firstly, we characterized key instrumental elements which revealed that red/near-infrared laser lines with an 86x (Numerical Aperture (NA) = 1.2, water immersion) objective allowed high transmission of fluorescence signals, low irradiance and super-resolution. As a combination of two technologies, i.e., vacuum tubes (e.g., photomultiplier) and semiconductor microelectronics (e.g., avalanche photodiode), type S, X and R of hybrid detectors (HyD-S, HyD-X and HyD-R) were particularly adapted for red/near-infrared photon counting and τ separation. Secondly, we tested and compared lifetime-based imaging including coarse τ separation for confocal microscopy, fitting and phasor plot analysis for fluorescence lifetime microscopy (FLIM), and lifetimes weighting for enhanced stimulated emission depletion (STED) nanoscopy, in light of red/near-infrared multiplexing. Mainly, we showed that the choice of appropriate imaging approach may depend on fluorochrome number, together with their spectral/lifetime characteristics and STED compatibility. Photon-counting mode and sensitivity of HyDs together with phasor plot analysis of fluorescence lifetimes enabled the flexible and fast imaging of multi-labeled living H28 cells. Therefore, a combination of red/near-infrared dyes labeling with lifetime-based strategies offers new perspectives for live-cell imaging by enhancing sample preservation through acquisition time and light exposure reduction.     

Complex precipitation pathways in multicomponent alloys

One usual way to strengthen a metal is to add alloying elements and to control the size and the density of the precipitates obtained. However, precipitation in multicomponent alloys can take complex pathways depending on the relative diffusivity of solute atoms and on the relative driving forces involved. In Al-Zr-Sc alloys, atomic simulations based on first-principle calculations combined with various complementary experimental approaches working at different scales reveal a strongly inhomogeneous structure of the precipitates: owing to the much faster diffusivity of Sc compared with Zr in the solid solution, and to the absence of Zr and Sc diffusion inside the precipitates, the precipitate core is mostly Sc-rich, whereas the external shell is Zr-rich. This explains previous observations of an enhanced nucleation rate in Al-Zr-Sc alloys compared with binary Al-Sc alloys, along with much higher resistance to Ostwald ripening, two features of the utmost importance in the field of light high-strength materials.     

Nanoassisted Laser Desorption-Ionization-MS Imaging of Tumors

The ability of nanoassisted laser desorption-ionization mass spectrometry (NALDI-MS) imaging to provide selective chemical monitoring with proper spatial distribution of lipid profiles from tumor tissues after plate imprinting has been tested. NALDI-MS imaging identified and mapped several potential lipid biomarkers in a murine model of melanoma tumor (inoculation of B16/F10 cells). It also confirmed that the in vivo treatment of tumor bearing mice with synthetic supplement containing phosphoethanolamine (PHO-S) promoted an accentuated decrease in relative abundance of the tumor biomarkers. NALDI-MS imaging is a matrix-free LDI protocol based on the selective imprinting of lipids in the NALDI plate followed by the removal of the tissue. It therefore provides good quality and selective chemical images with preservation of spatial distribution and less interference from tissue material. The test case described herein illustrates the potential of chemically selective NALDI-MS imaging for biomarker discovery.     

Extension of the Stokes equation for layered constructions to fluorescent turbid media

Expressions relating the bispectral reflectance of a stack of n fluorescing layers to each individual layer's reflectance and transmittance are derived. This theoretical framework is used together with recently proposed extensions of the Kubelka-Munk model to study the fluorescence from layered turbid media. For one layer over a reflecting background, the model is shown to give the same results as a previous model. The extension to n layers with different optical properties allows simulating the bispectral reflectance from a pad of layered turbid media. The applicability of the model is exemplified with an optimization of fluorophore distribution in layered turbid media.     

Non-culture-based identification of mastitis-causing bacteria by MALDI-TOF mass spectrometry

The purpose of this study was to evaluate the detection limit of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for direct identification, without previous microbiological culture, of bovine mastitis-causing bacteria from milk samples. Milk samples (n = 15) were experimentally contaminated with Staphylococcus aureus, Streptococcus uberis, Streptococcus agalactiae, Streptococcus dysgalactiae, and Escherichia coli to have bacterial counts ranging from 10³ to 10⁹ cfu/mL. These contaminated milk samples were subjected to a preparation protocol for bacterial ribosomal protein extraction using the MALDI Sepsityper kit (Bruker Daltonik, Bremen, Germany), which allowed MALDI-TOF MS coupled with Biotyper software (Bruker Daltonik) to identify bacterial fingerprints based on intact ribosomal proteins. The ability of MALDI-TOF MS to correctly identify bacterial strains from experimentally contaminated milk (without previous microbiological culture) depended on the bacterial count of the samples and on the species of the bacteria evaluated. Adequate identification at the bacterial species level (score ≥2.0) directly from milk samples required bacterial counts in the following ranges: ≥10⁶ cfu/mL of Staph. aureus, ≥10⁷ cfu/mL of E. coli, and ≥10⁸ cfu/mL of Strep. agalactiae, Strep. dysgalactiae, and Strep. uberis. We concluded that direct identification of mastitis-causing pathogens is possible for Staph. aureus, E. coli, Strep. agalactiae, Strep. dysgalactiae, and Strep. uberis, but correct identification depended on the bacterial count in the milk samples.     

Short communication: Identification of Corynebacterium bovis by MALDI-mass spectrometry

Corynebacterium bovis is a mastitis-causing microorganism responsible for economic losses related to decrease in milk production. The aim of the study was identify Corynebacterium spp. strains recovered from milk samples of subclinical mastitis by using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Samples were collected during a 10-mo mastitis-monitoring program in a high-production dairy farm. In this study, 80 strains were analyzed; from these 54 (67.5%) were identified at species level as Corynebacterium bovis, 24 (31.2%) isolates were identified at the genus level as Corynebacterium spp., and only 1 (1.35%) isolated had unreliable identification. Results demonstrated that MALDI-MS could be an important technique for the identification of Corynebacterium spp. in milk.