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A novel fluorescent nanoprobe was prepared to measure H2S in plasma and tissue samples from ASD patients and model mice.

Given the unpredictability and challenges brought about by the 2019 novel coronavirus (COVID-19) pandemic, this study aimed to investigate the impact trend of the prolonged pandemic on the mental health of parents of children with autism spectrum disorder (ASD). The 8112 participants included parents of children with ASD and parents of typically developing (TD) children at two sites (Heilongjiang and Fujian province, China). The parents completed a set of self-report questionnaires covering demographic characteristics, influences related to COVID-19, COVID-19 concerns and perceived behaviors, as well as the Connor-Davidson resilience scale (CD-RISC), self-rating anxiety scale (SAS), and self-rating depression scale (SDS) by means of an online survey platform. Data were collected by three cross-sectional surveys carried out in April 2020 (Time 1), October 2020 (Time 2), and October 2021 (Time 3). The results of quantitative and qualitative comparisons showed that: (i) parents of children with ASD had lower levels of resilience, and more symptoms of anxiety and depression than parents of TD children at each time point (all P 0.05); and (ii) there were significant time-cumulative changes in resilience, anxiety, and depression among all participants (all P 0.05). The logistic regression analyzes after adjusting for demographic characteristics revealed that the following factors were significantly associated with poor resilience and a higher rate of anxiety and depression in parents of children with ASD: time-point, the effect of COVID-19 on children's emotions and parents' emotions, changes in relationships, changes in physical exercise, changes in daily diet during the COVID-19 pandemic, and COVID-19-related psychological distress. In conclusions, the parents did not report improvements in resilience, anxiety, or depression symptoms from Time 1 to Time 2 or 3, indicating that cumulative mental health issues increased when, surprisingly, the COVID-19 restrictions were eased. The psychological harm resulting from the COVID-19 pandemic is far-reaching, especially among parents of children with ASD.

Awakening n→π* electronic transition in graphitized carbon nitride can extend the visible light absorption range of the original g-C3N4, which will contribute to improve the photocatalytic activity of carbon dioxide reduction. Here we report that the n→π* transition in g-C3N4 is activated by the cooperation of steam etching and alkali treatment. The CO and CH4 evolution yields of the NaOH/Vc‐CN sample are 4.3 and 16 times higher than those of original g-C3N4, respectively. The planar asymmetry structure of heptazine was fabricated due to the hydroxyl groups reacting with terminal N-H content produced by the construction of carbon vacancy and the Na+ ions insert into the interlayer. Therefore, n→π* electronic transition in g-C3N4 was awakened, extending the optical absorption range with light wavelengths longer than 470 nm. At the same time, the ability of CO2 chemisorption and activation was improved due to the NaOH modification. Therefore, the extended visible light absorption, the improved crystallinity and the increased active sites are beneficial to optimizing the utilization efficiency of photogenerated carriers and enhancing photocatalytic activity.

The pipeline safety management system is crucial to transfer oil and gas because the phenomena of leakage commonly occurs in the long-distant pipelines. Hidden safety hazards can be caused by design and construction defects, affected by natural disasters, or corroded by the transmission fluid. Therefore, quick detection will not only reduce the loss of transported oil and gas but also can protect the local environment. In this study, we develop a new method to detect the pipeline leak by analyzing pressure distribution through the leak. Pipeline leak detection tests are operated using a flow loop. Through the experiments, four parameters which are pressures and flow rates of pipeline inlet and outlet are recorded. Then the specific location of the leak is determined by dimensionless analysis of flow parameters. To generate the solution to locate the leak, we introduce three dimensionless variables, which are dimensionless leak location, dimensionless leak rate, and dimensionless pressure drop. Then the relationship of pressure distribution and leak parameters is built through the simulation models. After running 3D computational fluid dynamics (CFD) simulations with commercial software (FLUENT), the pressure distribution in the pipeline with leakage in the experiments will be verified by the experimental data. Finally, the mathematical models are developed to detect and evaluate the leakage through the pipeline. CFD simulation results show that both the leak rate and location have significant effects on the pressure distribution through the pipe, which is identical to the outcome from the experiments. When the dimensionless leak location is smaller or the dimensionless leak rate is larger, the dimensionless pressure drop is smaller. The mathematical model which is based on these dimensionless variables can be applied in locating the leak point in the real accident.

Pipeline blockage, which results from solid and hydrocarbon deposition caused by changes in pressure, temperature, or composition, is a critical issue in oil and gas production and transportation systems. Sometimes blockage, which extends several miles in the long-distance pipe, can be approximated as a pipe with a smaller diameter. While the earlier work focused on treating pipeline blockage as a choke for its limited size and length, this study attempts to analyze the relationship between the pressure distribution and the blockage size/length when analyzing the blockage characteristics under different situations. This paper explores the distribution of pressure and pressure gradient around the pipeline blockage under different operating conditions. Three-dimension (3D) computational fluid dynamic (CFD) simulations under steady-state are carried out to examine the effects of blockage diameter, blockage length, and blockage location. The relationship between the pressure drop and blockage characterization is predicted. A forecasting model for blockage sensing and localization is proposed. Lab experiments are conducted to compare the simulation results to measured data and the accuracy of forecasting model is evaluated. The study indicates that CFD simulation results match the experiment data and the model is a useful tool in detection of pipeline blockage.

A novel visible-light-driven Cu 2 MoS 4 photocatalyst was prepared by a facile hydrothermal method using Ammonium Tetrathiomolybdate reacting with cuprous chloride in aqua ammonia. The synthetic catalysts were characterized by XRD, UV–vis spectra, XRF and SEM techniques. The influence of the reaction temperature and time on the activities of the catalysts and the morphology of particles was investigated. The results showed that the catalysts exhibited strong absorption in visible light region. It was found that the photocatalyst prepared under hydrothermal condition at 140 °C for about 24 h showed good crystallinity with regular shape, and the highest activity for hydrogen production under visible light irradiation in an aqueous Na 2 S–Na 2 SO 3 solution. The reason for its better performance has been discussed in detail.