Segmenting Multivariate Time Series of Water Flow : a Prior Tool for Contamination Warning Systems

International audienceDrinking Water Distribution Networks (WDN) are critical infrastructures exposed to the risk of accidental and intentional contaminations. To ensure protection of drinking water, there is an important need to design automatic and secure Early Warning Systems (EWS). Online monitoring of water quality into a WDN is a challenging problem due to the complexity of hydraulic networks. Conventional detection methods deal with specific contaminants and usually assume a stationary state of the WDN meanwhile such problem is hardly addressed when operational conditions are changing. This paper introduces a generic methodology based on a temporal analysis in order to extract prior knowledge for warning detectors. Frequent types of operating period are extracted and for each period, upstream / downstream relationships into the WDN can be found. The procedure is fully data-driven and prevents to use heavy hydraulic-quality simulations during the monitoring stage. In fact, the method can be used as a preprocessing step by any detector in order to help dealing with multiple quality sensors and to avoid false alarms due to operating changes. The proposed approach is illustrated on a large real-world network in France and the experimental results are very promising

A Role of the Fast ATP-gated P2X1 Cation Channel in Thrombosis of Small Arteries In Vivo

The P2X1 receptor is a fast ATP-gated cation channel expressed in blood platelets, where its role has been difficult to assess due to its rapid desensitization and the lack of pharmacological tools. In this paper, we have used P2X1−/− and wild-type mouse platelets, treated with apyrase to prevent desensitization, to demonstrate the function of P2X1 in the response to thrombogenic stimuli. In vitro, the collagen-induced aggregation and secretion of P2X1-deficient platelets was decreased, as was adhesion and thrombus growth on a collagen-coated surface, particularly when the wall shear rate was elevated. In vivo, the functional role of P2X1 could be demonstrated using two models of platelet-dependent thrombotic occlusion of small arteries, in which blood flow is characterized by a high shear rate. The mortality of P2X1−/− mice in a model of systemic thromboembolism was reduced and the size of mural thrombi formed after a laser-induced vessel wall injury was decreased as compared with normal mice, whereas the time for complete thrombus removal was shortened. Overall, the P2X1 receptor appears to contribute to the formation of platelet thrombi, particularly in arteries in which shear forces are high

Three non-autonomous signals collaborate for nuclear targeting of CrMYC2, a Catharanthus roseus bHLH transcription factor

<p>Abstract</p> <p>Background</p> <p>CrMYC2 is an early jasmonate-responsive bHLH transcription factor involved in the regulation of the expression of the genes of the terpenic indole alkaloid biosynthesis pathway in <it>Catharanthus roseus</it>. In this paper, we identified the amino acid domains necessary for the nuclear targeting of CrMYC2.</p> <p>Findings</p> <p>We examined the intracellular localization of whole CrMYC2 and of various deletion mutants, all fused with GFP, using a transient expression assay in onion epidermal cells. Sequence analysis of this protein revealed the presence of four putative basic nuclear localization signals (NLS). Assays showed that none of the predicted NLS is active alone. Further functional dissection of CrMYC2 showed that the nuclear targeting of this transcription factor involves the cooperation of three domains located in the C-terminal region of the protein. The first two domains are located at amino acid residues 454-510 and 510-562 and contain basic classical monopartite NLSs; these regions are referred to as NLS3 (KRPRKR) and NLS4 (EAERQRREK), respectively. The third domain, between residues 617 and 652, is rich in basic amino acids that are well conserved in other phylogenetically related bHLH transcription factors. Our data revealed that these three domains are inactive when isolated but act cooperatively to target CrMYC2 to the nucleus.</p> <p>Conclusions</p> <p>This study identified three amino acid domains that act in cooperation to target the CrMYC2 transcription factor to the nucleus. Further fine structure/function analysis of these amino acid domains will allow the identification of new NLS domains and will allow the investigation of the related molecular mechanisms involved in the nuclear targeting of the CrMYC2 bHLH transcription factor.</p

Maternal Environment Influences Cocaine Intake in Adulthood in a Genotype-Dependent Manner

Background: Accumulating epidemiological evidence points to the role of genetic background as a modulator of the capacity of adverse early experiences to give rise to mental illness. However, direct evidence of such gene-environment interaction in the context of substance abuse is scarce. In the present study we investigated whether the impact of early life experiences on cocaine intake in adulthood depends on genetic background. In addition, we studied other behavioral dimensions associated with drug abuse, i.e. anxiety- and depression-related behaviors. Methodology/Principal Findings: For this purpose, we manipulated the maternal environment of two inbred mouse strains, the C57BL/6J and DBA/2J by fostering them with non-related mothers, i.e. the C3H/HeN and AKR strains. These mother strains show respectively high and low pup-oriented behavior. As adults, C57BL/6J and DBA/2J were tested either for cocaine intravenous self-administration or in the elevated plus-maze and forced swim test (FST). We found that the impact of maternal environment on cocaine use and a depression-related behavior depends upon genotype, as cocaine self-administration and behavior in the FST were influenced by maternal environment in DBA/2J, but not in C57BL/6J mice. Anxiety was not influenced by maternal environment in either strain. Conclusions/Significance: Our experimental approach could contribute to the identification of the psychobiological factor

Quality Zones Automatically Identified in Water Distribution Networks by applying Data Clustering Methods to Conductivity Measurements

This paper presents a clustering study showing how conductivity measured every five minutes by 215 probes over four years can be used to determine specific quality zones for a large Water Distribution Network (WDN): 8500 km of pipes, 4.6M customers. Conductivity time-series are compared using Dynamic Time Warping. Then, probes are ordered using a density-based method, and probe clusters are extracted automatically. The clusters are a sound representation of water quality in the WDN, both in terms of water origin and water residence time. More specifically, zones directly impacted by plants or by external water imports, mixing zones and zones influenced by tanks, can be isolated and analyzed. Globally, 82% of the probes were found to be clustered, consistent with expert knowledge on the WDN operation; 13% were unclassified; 3% were erroneously clustered; and 1% seemed to be reasonably clustered, without any physical understanding yet. Besides providing users with an increased understanding of water quality in WDNs, conductivity-based clusters offer an interesting prior tool for contamination warning systems

Kinetic development of biofilm on NF membranes at the Méry-sur-Oise plant, France

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Effect of storage of NF membranes on fouling deposits and cleaning efficiency

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Upscaling fixed bed adsorption behaviors towards emerging micropollutants in treated natural waters with aging activated carbon Model development and validation

International audienceA scale-up procedure was assessed in this study to predict the fixed bed adsorption behaviors with aging granular activated carbon (GAC) for various micropollutants (pesticides, pharmaceuticals). Two assumptions of this upscaling methodology (i.e., involving equal adsorption capacities and surface diffusivities between the batch test and the fixed bed) were studied for the first time to investigate the aging effect on the adsorption capacity and kinetics of carbon at full scale. This study was conducted in natural waters (the Seine River) treated by Veolia Eau d'Ile de France in Choisy-Le-Roi, a division of Syndicat des Eaux d'Ile de France, aiming to monitor real industrial conditions. The isotherms showed that the adsorption capacity for most compounds was significantly affected by aging. For the mass transfer coefficients (i.e., as determined by the homogeneous surface diffusion model (HSDM)), different patterns of adsorbate/adsorbent behaviors were observed, suggesting different competition mechanisms. The model predictions (i.e., HSDM) performed with all parameters obtained during the batch tests tended to overestimate the full-scale pilot adsorption performance. This overestimation could be compensated for by applying a scaling factor. Finally, an empirical pseudo-first order function was used to model the impact of the GAC service time on the characteristic adsorption parameters. Thus, our scale-up procedure may enable the prediction of long-term fixed bed adsorption behaviors and increase the model efficiency for practical implementation

Analysis and occurrence of odorous disinfection by-products from chlorination of amino acids in three different drinking water treatment plants and corresponding distribution networks

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Un algorithme glouton pour le positionnement de capteurs qualité sur un grand réseau de distribution d'eau

International audienceOperating modern drinking water distribution systems requires the ability to monitor water quality within production plants and the distribution network in order to mitigate damaging events like accidental or malicious contaminations. The surveillance systems are usually based on a sensor network deployed at strategic locations to minimize the contamination impact on the population. Such problem consists in selecting sensing locations with the best protection with a given number of sensors which is complex in theory and very challenging in practice. We describe here a methodology using an efficient greedy-like algorithm, designed during a Franco-German project3. This approach uses an extensive number of contaminations simulated by hydraulic modeling software and selects iteratively the best positions according to a given criterion to optimize. The method is evaluated with the deployment of multiparameters quality sensors (chlorine, temperature, conductivity and pressure) on the SEDIF network, the largest drinking water distribution network in France.L'exploitation d'un système moderne d'alimentation en eau potable nécessite une surveillance permanente de la qualité de l'eau au sein des usines de production et sur le réseau de distribution, face à des risques de contamination accidentelle ou terroriste. Cette surveillance s'appuie usuellement sur un ensemble de capteurs déployés en des points stratégiques du réseau afin de minimiser l'impact de toute contamination. La localisation de capteurs consiste à déterminer des points du réseau avec la meilleure protection pour un nombre limité de capteurs ce qui représente un problème complexe en théorie et très difficile à résoudre en pratique. Nous décrivons ici une méthodologie fondée sur un algorithme efficace de type glouton, élaborée dans le cadre d'un projet franco-allemand . Cette approche utilise un grand nombre de contaminations, simulées par un logiciel de modélisation hydraulique, et sélectionne itérativement les meilleurs positions en fonction d'un critère fixé à optimiser. La méthode est évaluée pour le déploiement de capteurs multiparamètres mesurant chlore, température, pression et conductivité sur le réseau du SEDIF , plus grand réseau français de distribution d'eau potable