Water Quality Prediction Method Based on OVMD and Spatio-Temporal Dependence

Water quality changes at one monitoring spot are not only related to local historical data but also spatially to the water quality of the adjacent spots. Additionally, the non-linear and non-stationary nature of water quality data has a significant impact on prediction results. To improve the accuracy of water quality prediction models, a comprehensive water quality prediction model has been initially established that takes into account both data complexity and spatio-temporal dependencies. The Optimal Variational Mode Decomposition (OVMD) technology is used to effectively decompose water quality data into several simple and stable time series, highlighting short-term and long-term features and enhancing the model\u27s learning ability. The component sequence and spot adjacency matrix are used as the input of Graph Convolutional Network (GCN) to extract the spatial characteristics of the data, and the spatio-temporal dependencies of water quality data at different spots are obtained by combining GCN into the neurons of Gated Recurrent Unit (GRU). The attention model is added to automatically adjust the importance of each time node to further improve the accuracy of the training model and obtain a multi-step prediction output that more closely aligns with the characteristics of water quality change. The proposed model has been validated with real monitoring data for ammonia nitrogen (NH3-N) and total phosphorus (TP), and the results show that the proposed model is better than ARIMA, GRU and GCN+GRU models in terms of prediction results and it shows obvious advantages in the benchmark comparison experiment, which can provide reliable evidence for water pollution source traceability or early warning

Confocal laser endomicroscopy in gastrointestinal diseases

Confocal laser endomicroscopy (CLE) is a novel endoscopic technique permitting in vivo microscopy (optical biopsies) of the gastrointestinal mucosa. CLE has been studied in a multitude of diseases of the upper and lower gastrointestinal tract, including Barrett's esophagus, gastric inflammation and cancer, celiac disease, colorectal adenoma and carcinoma, and inflammatory bowel diseases. CLE has recently evolved and been studied for bile duct and liver imaging. CLE has shown overall high accuracy and enabled smart, targeted biopsies rather than untargeted sampling. Furthermore, the availability of real time microscopic information during endoscopy has immediate impact on therapeutic decisions and guides endoscopic interventions. CLE is also a unique tool for observation of (patho-)physiologic events in their natural environment (functional imaging) and has been linked to molecular imaging of gastrointestinal neoplasia in vivo, thereby broadening our understanding of mucosal pathology in clinical and basic science

The EUI flight instrument of Solar Orbiter: from optical alignment to end-to-end calibration

The Extreme Ultraviolet Imager (EUI) instrument for the Solar Orbiter mission will image the solar corona in the extreme ultraviolet (17.1 nm and 30.4 nm) and in the vacuum ultraviolet (121.6 nm) spectral ranges. The development of the EUI instrument has been successfully completed with the optical alignment of its three channels’ telescope, the thermal and mechanical environmental verification, the electrical and software validations, and an end-toend on-ground calibration of the two-units’ flight instrument at the operating wavelengths. The instrument has been delivered and installed on the Solar Orbiter spacecraft, which is now undergoing all preparatory activities before launch

Alectinib: a novel second generation anaplastic lymphoma kinase (ALK) inhibitor for overcoming clinically-acquired resistance

The development of inhibitors for the tyrosine anaplastic lymphoma kinase (ALK) has advanced rapidly, driven by biology and medicinal chemistry. The first generation ALK inhibitor crizotinib was granted US FDA approval with only four years of preclinical and clinical testing. Although this drug offers significant clinical benefit to the ALK-positive patients, resistance has been developed through a variety of mechanisms. In addition to ceritinib, alectinib is another second-generation ALK inhibitor launched in 2014 in Japan. This drug has a unique chemical structure bearing a 5H-benzo[b]carbazol-11(6H)-one structural scaffold with an IC50 value of 1.9 nmol/L, and is highly potent against ALK bearing the gatekeeper mutation L1196M with an IC50 of 1.56 nmol/L. In the clinic, alectinib is highly efficacious in treatment of ALK-positive non-small cell lung cancer (NSCLC), and retains potency to combat crizotinib-resistant ALK mutations L1196M, F1174L, R1275Q and C1156Y

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Crashes that occur on curved roadways are often more severe than straight road accidents. Previously, most studies focused on the associations between curved sections and roadway geometric characteristics. In this study, significant factors such as driver behavior, roadway features, vehicle factors, and environmental characteristics are identified and involved in analyzing traffic accident severity. Bayesian network analysis was conducted to deal with data, to explore the associations between variables, and to make predictions using these relationships. The results indicated that factors including point of impact, site of location, accident side of road, alcohol/drugs condition, etc., are relatively critical in crashes on horizontal curves. Accident severity increases when crashes occur on bridges. The sensitivity of accident severity to vehicle use, traffic control, point of impact, and alcohol/drugs condition is relatively high. Moreover, a combination of negative factors will aggravate accident severities. The results also proposed some suggestions regarding the design of vehicles, as well as the construction and improvement of curved roadways

Gold Nanoclusters@Ru(bpy)₃²⁺-Layered Double Hydroxide Ultrathin Film as a Cathodic Electrochemiluminescence Resonance Energy Transfer Probe

Herein, it is the first report that a cathodic electrochemiluminescence (ECL) resonance energy transfer (ERET) system is fabricated by layer-by-layer (LBL) electrostatic assembly of CoAl layered double hydroxide (LDH) nanosheets with a mixture of blue BSA–gold nanoclusters (AuNCs) and Ru­(bpy)₃²⁺ (denoted as AuNCs@Ru) on an Au electrode. The possible ECL mechanism indicates that the appearance of CoAl–LDH nanosheets generates a long-range stacking order of the AuNCs@Ru on an Au electrode, facilitating the occurrence of the ERET between BSA–AuNC donors and Ru­(bpy)₃²⁺ acceptors on the as-prepared AuNCs@Ru–LDH ultrathin films (UTFs). Furthermore, it is observed that the cathodic ECL intensity can be quenched efficiently in the presence of 6-mercaptopurine (6-MP) in a linear range of 2.5–100 nM with a detection limit of 1.0 nM. On the basis of these interesting phenomena, a facile cathodic ECL sensor has successfully distinguished 6-MP from other thiol-containing compounds (e.g., cysteine and glutathione) in human serum and urine samples. The proposed sensing scheme opens a way for employing the layered UTFs as a platform for the cathodic ECL of Ru­(bpy)₃²⁺