Les goûts et les odeurs dans l’eau potable : revue des composés responsables et des techniques de mesure

L’évaluation de la qualité de l’eau potable d’un réseau de distribution est souvent faite en tenant compte des normes physico-chimiques et microbiologiques édictées par les réglementations nationales. L’approche par barrières multiples permet aussi d’assurer aux consommateurs une eau avec une sécurité sanitaire optimale. Cependant, malgré les sommes investies par les municipalités pour se conformer à ces normes, les consommateurs renoncent fréquemment à consommer l’eau du robinet.Ce refus peut être attribué, entre autres, à la qualité organoleptique (goût, odeur) de l’eau distribuée par les réseaux d’aqueduc. Toutefois, cet aspect est peu pris en compte par les législations actuelles et, conséquemment, est peu considéré par les gestionnaires des réseaux d’eau potable. De plus, les méthodes utilisées pour évaluer les molécules responsables des goûts et des odeurs de l’eau distribuée exigent de l’équipement spécialisé et coûteux. Cet article présente une revue de la problématique des composés responsables des goûts et des odeurs. Les aspects concernant les origines de ces composés, les méthodes quantitatives et qualitatives développées jusqu’à présent pour les analyser et la faisabilité d’application desdites méthodes, selon leurs avantages et leurs limites, seront abordés.The assessment of drinking water quality in a distribution system is generally based on physicochemical and microbiological standards set by government regulations. Although municipalities often invest considerable amounts to comply with regulations, an increasing proportion of citizens prefer alternatives to tap water. This situation may be in part explained by the organoleptic quality of distributed water in municipal systems and, in particular, by taste and odours. However, taste and odours are rarely considered as water quality criteria by municipal water managers. Moreover, analytical methods used to analyze molecules related to taste and odours in drinking water require specialized and costly equipment. This article presents the state of the art in terms of taste and odour issues in the drinking water area. The paper focuses on the origins of taste and odours and on the methods (qualitative and quantitative) available for the analysis of the compounds from which they originate. The feasibility of applying these methods to water quality surveillance is discussed, along with their advantages and drawbacks

Electrical modeling of InAs/GaSb superlattice mid-wavelength infrared pin photodiode to analyze experimental dark current characteristics

Dark current characteristics of 7 Monolayers (ML) InAs/ 4 ML GaSb SL pin photodiodes are simulated using ATLAS software. Using appropriate models and material parameters, we obtain good agreement between the simulated and the experimental dark current curves of photodiodes grown by molecular beam epitaxy. The n-type non-intentionally-doped (nid) SL samples exhibit a dependence of the lifetime with temperature following the T−12 law, signature of Shockley-Read-Hall (SRH) Generation-Recombination current. We also studied the dependence of the dark current with the absorber doping level. It appears that the absorber doping level must not exceed a value of 2 × 1015 cm−3, above this value the dark current is increasing with increased doping level. However for this doping value, a dark current as low as 5 × 10−9 A/cm2, at 50 mV reverse bias at 77 K can be obtained

Multiphysic FEMLAB modelling to evaluate mid-infrared photonic detector performances

National audienceInfrared photo detectors operating in the mid infrared region find application in pollution monitoring, high speed infrared imaging systems and free space telecommunications. Currently the dominant infrared detector technology are based on HgCdTe or InSb photovoltaic devices. Because of their narrow band gap these devices show at room temperature (RT) high dark reverse current and small R0.A product, which significantly restrict the getting of high ambient performances. To reduce the darkness current and increase R0.A product, we suggested studying structures with large band gap energy. The objective of the photo detector structures modelling presented in this paper is double. It allows first to simulate and to estimate the theoretical performances of previously introduced large band gap components. As such we shall calculate, the product R0.A and the quantum efficiency to end in the specific detectivity D*. It is also a support to help in the understanding and in the interpretation of the made photo detectors characterizations

Self-supervised Vision Transformers for 3D Pose Estimation of Novel Objects

Object pose estimation is important for object manipulation and scene understanding. In order to improve the general applicability of pose estimators, recent research focuses on providing estimates for novel objects, that is objects unseen during training. Such works use deep template matching strategies to retrieve the closest template connected to a query image. This template retrieval implicitly provides object class and pose. Despite the recent success and improvements of Vision Transformers over CNNs for many vision tasks, the state of the art uses CNN-based approaches for novel object pose estimation. This work evaluates and demonstrates the differences between self-supervised CNNs and Vision Transformers for deep template matching. In detail, both types of approaches are trained using contrastive learning to match training images against rendered templates of isolated objects. At test time, such templates are matched against query images of known and novel objects under challenging settings, such as clutter, occlusion and object symmetries, using masked cosine similarity. The presented results not only demonstrate that Vision Transformers improve in matching accuracy over CNNs, but also that for some cases pre-trained Vision Transformers do not need fine-tuning to do so. Furthermore, we highlight the differences in optimization and network architecture when comparing these two types of network for deep template matching

Self-supervised Vision Transformers for 3D pose estimation of novel objects

Object pose estimation is important for object manipulation and scene understanding. In order to improve the general applicability of pose estimators, recent research focuses on providing estimates for novel objects, that is, objects unseen during training. Such works use deep template matching strategies to retrieve the closest template connected to a query image, which implicitly provides object class and pose. Despite the recent success and improvements of Vision Transformers over CNNs for many vision tasks, the state of the art uses CNN-based approaches for novel object pose estimation. This work evaluates and demonstrates the differences between self-supervised CNNs and Vision Transformers for deep template matching. In detail, both types of approaches are trained using contrastive learning to match training images against rendered templates of isolated objects. At test time such templates are matched against query images of known and novel objects under challenging settings, such as clutter, occlusion and object symmetries, using masked cosine similarity. The presented results not only demonstrate that Vision Transformers improve matching accuracy over CNNs but also that for some cases pre-trained Vision Transformers do not need fine-tuning to achieve the improvement. Furthermore, we highlight the differences in optimization and network architecture when comparing these two types of networks for deep template matching.We gratefully acknowledge the support of the EU-program EC Horizon 2020 for Research and Innovation under grant agreement No. 101017089, project TraceBot and the NVIDIA Corporation for supporting this research by providing hardware resources

Electrical properties of short period InAs/GaSb superlattice

International audienc

Large-scale 3D printing with cable-driven parallel robots

Gantry robots and anthropomorphic arms of various sizes have already been studied and, while they are in use in some parts of the world for automated construction, a new kind of wide workspace machinery, cable-driven parallel robots (CDPR), has emerged. These robots are capable of automated movement in a very wide workspace, using cables reeled in and out by winches as actuation members, the other elements being easily stacked for easy relocation and reconfiguration, which is critical for on-site construction. The motivation of this paper is to showcase the potential of a CDPR operating solely on motor position sensors and showing limited collisions from the cables for large-scale applications in the building industry relevant for additive manufacturing, without risk of collisions between the cables and the building. The combination of the Cogiro CDPR (Tecnalia, LIRMM-CNRS 2010) with the extruder and material of the Pylos project (IAAC 2013) opens the opportunity to a 3D printing machine with a workspace of 13.6 × 9.4 × 3.3 m. The design patterns for printing on such a large scale are disclosed, as well as the modifications that were necessary for both the Cogiro robot and Pylos extruder and material. Two prints, with different patterns, have been achieved with the Pylos extruder mounted on Cogiro: the first spanning 3.5 m in length, the second, reaching a height of 0.86 m. Based on this initial experiment, plans for building larger parts and buildings are discussed, as well as other possible applications for CDPRs in construction, such as the manipulation of assembly processes (windows, lintels, beams, floor elements, curtain wall modules, etc.) or brick laying

Identification of dichloroacetic acid degrading Cupriavidus bacteria in a drinking water distribution network model

Aims: Bacterial community structure and composition of a drinking water network were assessed to better understand this ecosystem in relation to haloacetic acid (HAA) degradation and to identify new bacterial species having HAA degradation capacities. Methods and Results: Biofilm samples were collected from a model system, simulating the end of the drinking water distribution network and supplied with different concentrations of dichloroacetic and trichloroacetic acids at different periods over the course of a year. The samples were analysed by culturing, denaturing gradient gel electrophoresis (DGGE) and sequencing. Pipe diameter and HAA ratios did not impact the bacterial community profiles, but the season had a clear influence. Based on DGGE profiles, it appeared that a particular biomass has developed during the summer compared with the other seasons. Among the bacteria isolated in this study, those from genus Cupriavidus were able to degrade dichloroacetic acid. Moreover, these bacteria degrade dichloroacetic acid at 18°C but not at 10°C. Conclusions: The microbial diversity evolved throughout the experiment, but the bacterial community was distinct during the summer. Results obtained on the capacity of Cupriavidus to degrade DCAA only at 18°C but not at 10°C indicate that water temperature is a major element affecting DCAA degradation and confirming observations made regarding season influence on HAA degradation in the drinking water distribution network. Significance and Impact of the Study: This is the first demonstration of the HAA biodegradation capacity of the genus Cupriavidu

Fano-like resonances sustained by Si doped InAsSb plasmonic resonators integrated in GaSb matrix

By using metal-free plasmonics, we report on the excitation of Fano-like resonances in the mid-infrared where the Fano asymmetric parameter, q, varies when the dielectric environment of the plasmonic resonator changes. We use silicon doped InAsSb alloy deposited by molecular beam epitaxy on GaSb substrate to realize the plasmonic resonators exclusively based on semiconductors. We first demonstrate the possibility to realize high quality samples of embedded InAsSb plasmonic resonators into GaSb host using regrowth technique. The high crystalline quality of the deposited structure is confirmed by scanning transmission electron microscopy (STEM) observation. Second, we report Fano-like resonances associated to localized surface plasmons in both cases: uncovered and covered plasmonic resonators, demonstrating a strong line shape modification. The optical properties of the embedded structures correspond to those modeled by finite-difference time-domain (FDTD) method and by a model based on Fano-like line shape. Our results show that all-semiconductor plasmonics gives the opportunity to build new plasmonic structures with embedded resonators of highly doped semiconductor in a matrix of un-doped semiconductor for mid-IR applications