The High-Resolution Imaging (HRI) Portable Array: A Seismic (and Internet) Network Dedicated to Kilometric-scale Seismic Imaging

International audienceWe have developed a network of portable seismic stations dedicated to the high resolution imaging of geological, potentially hazardous, targets. These targets - volcanoes, fault zones, landslide areas - are characterized by strong medium heterogeneities, rugged topography, rough field conditions, and require dedicated equipment in order to maximize the number of recording points. This new network is designed to a) operate experiments with a limited size crew, b) run on low power for possible use in remote areas and difficult conditions, c) record both active and passive seismic sources. The actual network consists of 30 clusters of 9 channels digital acquisition system (DAS), equipped with 6 vertical sensors plus 1 three-component sensor. Each DAS uses Ethernet and 802.11 (WiFi) connections that permit to a single operator to remotely control the entire network. We present the main characteristics of this new portable array, describe the calibration method developed for our sensors and show examples of configuration and recordings for two recent experiments

Adjustments in the forcing-feedback framework for understanding climate change

The traditional forcing-feedback framework has provided an indispensable basis for discussing global climate changes. However, as analysis of model behavior has become more detailed, shortcomings and ambiguities in the framework have become more evident and physical effects unaccounted for by the traditional framework have become interesting. In particular, the new concept of adjustments, which are responses to forcings that are not mediated by the global mean temperature, has emerged. This concept, related to the older ones of climate efficacy and stratospheric adjustment, is a more physical way of capturing unique responses to specific forcings. We present a pedagogical review of the adjustment concept, why it is important, and how it can be used. The concept is particularly useful for aerosols, where it helps to organize what has become a complex array of forcing mechanisms. It also helps clarify issues around cloud and hydrological response, transient vs. equilibrium climate change, and geoengineering

The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

Artificial Intelligence and Wastewater Treatment: A Global Scientific Perspective through Text Mining

The concept of using wastewater as a substitute for limited water resources and environmental protection has enabled this sector to make major technological advancements and, as a result, has given us an abundance of physical data, including chemical, biological, and microbiological information. It is easier to comprehend wastewater treatment systems after studying this data. In order to achieve this, a number of studies use machine learning (ML) algorithms as a proactive approach to solving issues and modeling the functionalities of these processing systems while utilizing the experimental data gathered. The goal of this article is to use textual analysis techniques to extract the most popular machine learning models from scientific documents in the “Web of Science” database and analyze their relevance and historical development. This will help provide a general overview and global scientific follow-up of publications dealing with the application of artificial intelligence (AI) to overcome the challenges faced in wastewater treatment technologies. The findings suggest that developed countries are the major publishers of articles on this research topic, and an analysis of the publication trend reveals an exponential rise in numbers, reflecting the scientific community’s interest in the subject. As well, the results indicate that supervised learning is popular among researchers, with the Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), Linear Regression (LR), Adaptive Neuro-Fuzzy Inference System (ANFIS), Decision Tree (DT), and Gradient Boosting (GB) being the machine learning models most frequently employed in the wastewater treatment domain. Research on optimization methods reveals that the most well-known method for calibrating models is genetic algorithms (GA). Finally, machine learning benefits wastewater treatment by enhancing data analysis accuracy and efficiency. Yet challenges arise as model training demands ample, high-quality data. Moreover, the limited interpretability of machine learning models complicates comprehension of the underlying mechanisms and decisions in wastewater treatment

Cadmium Complexed with β2-Microglubulin, Albumin and Lipocalin-2 rather than Metallothionein Cause Megalin:Cubilin Dependent Toxicity of the Renal Proximal Tubule

Cadmium (Cd2+) in the environment is a significant health hazard. Chronic low Cd2+ exposure mainly results from food and tobacco smoking and causes kidney damage, predominantly in the proximal tubule. Blood Cd2+ binds to thiol-containing high (e.g., albumin, transferrin) and low molecular weight proteins (e.g., the high-affinity metal-binding protein metallothionein, β2-microglobulin, α1-microglobulin and lipocalin-2). These plasma proteins reach the glomerular filtrate and are endocytosed at the proximal tubule via the multiligand receptor complex megalin:cubilin. The current dogma of chronic Cd2+ nephrotoxicity claims that Cd2+-metallothionein endocytosed via megalin:cubilin causes renal damage. However, a thorough study of the literature strongly argues for revision of this model for various reasons, mainly: (i) It relied on studies with unusually high Cd2+-metallothionein concentrations; (ii) the KD of megalin for metallothionein is ~105-times higher than (Cd2+)-metallothionein plasma concentrations. Here we investigated the uptake and toxicity of ultrafiltrated Cd2+-binding protein ligands that are endocytosed via megalin:cubilin in the proximal tubule. Metallothionein, β2-microglobulin, α1-microglobulin, lipocalin-2, albumin and transferrin were investigated, both as apo- and Cd2+-protein complexes, in a rat proximal tubule cell line (WKPT-0293 Cl.2) expressing megalin:cubilin at low passage, but is lost at high passage. Uptake was determined by fluorescence microscopy and toxicity by MTT cell viability assay. Apo-proteins in low and high passage cells as well as Cd2+-protein complexes in megalin:cubilin deficient high passage cells did not affect cell viability. The data prove Cd2+-metallothionein is not toxic, even at >100-fold physiological metallothionein concentrations in the primary filtrate. Rather, Cd2+-β2-microglobulin, Cd2+-albumin and Cd2+-lipocalin-2 at concentrations present in the primary filtrate are taken up by low passage proximal tubule cells and cause toxicity. They are therefore likely candidates of Cd2+-protein complexes damaging the proximal tubule via megalin:cubilin at concentrations found in the ultrafiltrate

Invasive Group B Streptococcal Disease in Non-pregnant Adults, Réunion Island, 2011

International audienceOBJECTIVES: While the prevalence of Group B streptococcus (GBS) colonization is important, little is known about invasive GBS (iGBS) disease in tropical areas. Our objective was to assess the burden of iGBS disease among non-pregnant adults.METHODS: A prospective hospital-based study of all non-pregnant adult patients with iGBS disease was conducted between January and December 2011 in Saint Pierre, Réunion Island, to assess its cumulative incidence rate (CIR). Capsular serotyping and multilocus sequence typing were performed to characterize GBS isolates. Case-control study was done to identify risk factors.RESULTS: The overall CIR of iGBS disease was 10.1 per 100,000. The CIR in elderly patients (≥ 65 yrs) was estimated at 40.6 per 100.000, and that of adults (15-64 years) at 6.7 per 100.000. Aboriginal origin in the Indian Ocean and overweight were both associated with iGBS disease. The most prominent clinical forms were osteo-articular and skin/soft tissue infections, as a consequence of diabetic foot. The serotypes were classic, type-Ia being the most prevalent. The hyper virulent ST-17 (CC17) was associated with type-III.CONCLUSIONS: The incidence of iGBS disease found in Réunion island is twofold that usually reported. This burden is linked to overweight in aboriginal people from the Indian Ocean

Mitigation of antibioresistance dissemination through the comprehensive optimization of sludge treatment

This project aims to evaluate the dynamics of antibiotics and antibioresistance on (1) 5 sludge treatment trains carried out in the laboratory on a raw sludge and (2) during soil incubations mimicking the spreading of the raw and 5 treated sludge samples. Antibiotics were quantified all along the sludge treatments and during the soil incubation. Antibioresistance was captured using culture-dependent as well as culture-independent methodologies for characterizing the total microbial communities, the abundance and diversity of the resistant bacteria and genes, but also the mobile genetic elements. The main outputs are the hierarchization of the sludge treatment trains according to their ability to mitigate the antibioresistance dissemination, but also the identification of the main factors triggering antibiotic resistance dissemination

Impact of Photoexcited NO2 on Global Air Quality with the NMMB/BSC Chemical Transport Model

Postprint (published version