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AZ91 alloy reinforced by carbon nanotubes coated with MgO（AZ91-MgO@CNTs） was prepared by powder metallurgy, hot extrusion and T4 treatment. The influences of MgO@CNTs content and load on the friction and wear property, surface wear morphology and debris topography of AZ91-MgO@CNTs composites were investigated under the dry sliding friction. The results show that MgO@CNTs can improve the wear properties of AZ91-MgO@CNTs. With increasing the content of MgO@CNTs, the strengthening effect of the wear properties of the composite increases and then decreases. Compared with AZ91-CNTs, AZ91-MgO@CNTs has smaller friction coefficient and lower abrasion loss, indicating that the MgO@CNTs is better than CNTs to improve the wear properties of AZ91 alloy. The main wear mechanism of AZ91-MgO@CNTs is abrasive wear under the load of 10 N. When the load is 50 N, there are three wear mechanisms appeared: abrasive wear, oxidation wear and adhesive wear.

The work reports the hydrogen-ion implantation and femtosecond laser ablation in the Er3+-doped germanate glass to make planar and ridge optical waveguides. The energy is 400 keV and the dose is 6 × 1016 ion/cm2 for the ion implantation. The pulse energy is 3 μJ and the scanning speed is 50 μm/s for the femtosecond laser ablation. A microscope is used to observe the cross-section morphologies of the planar and ridge waveguides. A measurement of the near-field intensity distribution at 632.8 nm is performed by the end-face coupling system. The effective refractive indices of the propagation modes are recorded by the m-line technique. It’s the first time that a ridge waveguide is fabricated in the Er3+-doped germanate glass by the proton implantation and femtosecond laser ablation, which is with potential application as new integrated optical devices.

We analyzed the characteristics of main karstic/non-karst reaches of the Lijiang River to uncover the causes behind different flood behaviors by providing a better understanding of the flood formation. Having 63 years of rainfall-runoff data and applying the HEC-HMS model, geo/hydrological features were investigated. The available reservoir capacity of karts (ARCK) was included through soil moisture accounting loss data to assess its impact. In particular, the expected instantaneous peak discharge rates/times were found largely imbalanced with generated unit hydrographs. Moreover, significant gaps among the floods’ features for different subbasins in terms of required peak modifications (2–4 times larger for mid-upstream, respectively) were mainly associated with the unique karst structure and initial condition due to various ARCK in rainy/dry seasons. Besides, notable dissimilarities between the wedge/prism storage volumes and the hydrograph’s wave traveling/receding time were observed owing to the geomorphological conditions. Although the contribution rates of drivers in karst flood formation cannot be quantitively modeled, based on our results the ARCK emerged to play a substantial role on the forecasted results, comparatively. Our results suggest that since ARCK varies, taking it into account (as initial abstraction) results in a more reliable estimation. This was underpinned by the results in which the unmodified simulations had a qualified rate of 52% accuracy on average and increased to 67.5% after the ARCK inclusion. This work adds to the body of evidence illustrating that in karst hydrology, ignoring the situational circumstances in modeling might lead to inaccuracies in flood forecasting for such dynamic watersheds. HIGHLIGHTS Hydrological models inaccurately forecast flood features in karst basins.; The seasonality of available karst reservoir capacity drives flood peaks.; Initial conditions must be considered in model calibration for karstic areas.;

Engineering rock mass often involves bedding planes and U-shaped defects. Under the combined influence of bedding planes and defects, the fracture mode of engineering rock mass is more complicated. To better understand the failure law of U-shaped defects in rock mass with bedding planes and better control or predict the crack propagation morphology, three-point bending tests were conducted on semicircular disk specimens with U-shaped notches under three different notch radii. The load variation law, different stages of the load–displacement curve, and fracture characteristics of specimens under five bedding angles were analyzed. Then, numerical models of semicircular three-point bending tests were established in particle flow code 2D (PFC2D). The influence of notch radius and bedding angle on the failure path of semicircular specimens was simulated and analyzed, and the three failure modes were verified again. In addition, the stress at the notch tip of the model was monitored by the measurement circle in the discrete-element method, and the fracture toughness of the model specimen was calculated, which provides a new calculation idea for fracture toughness. The research results help us more comprehensively understand the mechanical behavior and failure characteristics of layered rock mass with notch under external load. [ABSTRACT FROM AUTHOR]

Extreme rainfall, also known as heavy rainfall or intense precipitation, is a weather event characterized by a significant amount of rainfall within a short period. This study analyzes the trends in extreme precipitation indices at 17 stations in four main regions in Cambodia—the Tonle Sap, coastal, Mekong Delta, and Upper Mekong regions—between 1991 and 2021. Analyzing the data with RClimDex v1.9 reveals diverse spatial and temporal variations. The statistical analysis of the extreme rainfall indices in Cambodia from 1991 to 2021 reveals significant trends. In the Tonle Sap region, consecutive dry days (CDDs) increased at most stations, except Battabang, Kampong Thmar, and Pursat, while consecutive wet days (CWDs) increased at most stations. These trends align with rising temperatures and reduced forest cover. In the coastal region, particularly at the Krong Khemarak Phummin station, most rainfall indices increased, with a slope value of 89.94 mm/year. The extreme rainfall indices max. 1-day precipitation (RX1day) and max. 5-day precipitation (RX5day) also increased, suggesting higher precipitation on days exceeding the 95th (R95p) and 99th percentiles (R99p). The Kampot station showed a significant increase in CDDs, indicating a heightened drought risk. In the Mekong Delta, the Prey Veng station recorded a decrease in the CDDs slope value by −4.892 days/year, indicating potential drought risks. The Stung Treng station, which is the only station in Upper Mekong, showed a decreasing trend in CDDs with a slope value of −1.183 days/year, indicating a risk of extreme events. These findings underscore the complex interplay between climate change, land use, and rainfall patterns in Cambodia. [ABSTRACT FROM AUTHOR]

This study aimed to enhance flood forecasting accuracy in the Liangfeng River basin, a small karst watershed in Southern China, by incorporating the Available Reservoir Capacity of Karst (ARCK) into the HEC-HMS model. This region is often threatened by floods during the rainy season, so an accurate flood forecast can help decision-makers better manage rivers. As a crucial influencing factor on karstic runoff, ARCK is often overlooked in hydrological models. The seasonal and volatile nature of ARCK makes the direct computation of its specific values challenging. In this study, a virtual reservoir for each sub-basin (total of 17) was introduced into the model to simulate the storage and release of ARCK-induced runoff phenomena. Simulations via the enhanced model for rainfall events with significant fluctuations in water levels during 2021–2022 revealed that the Nash–Sutcliffe efficiency coefficient (NSE) of the average simulation accuracy was improved by more than 34%. Normally, rainfalls (even heavy precipitations) during the dry season either do not generate runoff or cause negligible fluctuations in flow rates due to long intervals. Conversely, relatively frequent rainfall events (even light ones) during the wet season result in substantial runoff. Based on this observation, three distinct types of karstic reservoirs with different retaining/releasing capacities were defined, reflecting variations in both the frequency and volume of runoff during both seasons. As a real-time environmental variable, ARCK exhibits higher and lower values during the dry and rainy seasons, respectively, and we can better avoid the risk of flooding according to its special effects. [ABSTRACT FROM AUTHOR]

Aims Rabson-Mendenhall syndrome (RMS) is a rare autosomal, recessive disorder characterized by severe insulin resistance due to mutations in the insulin receptor (INSR) gene. This study aims to analyze the clinical features and gene mutations in RMS, which have not been extensively studied. Methods PubMed, Embase, the China National Knowledge Infrastructure, and Wanfang were searched for "Rabson-Mendenhall syndrome" or "Black acanthosis hirsutism insulin resistance syndrome." Results A total of 42 cases from 33 articles were included. The body mass index ranged from 18.50 to 20.00 kg/m2 with an average of 16.00 kg/m2. There were no overweight (25.00∼29.90 kg/m2) or obese (≥30.00 kg/m2) patients. Acanthosis was present in 29 cases (29/42, 69.05%); growth retardation in 25 cases (25/42, 59.52%); dental anomalies including absence of teeth, crowding, and malocclusion in 23 cases (23/42, 54.76%); and hirsutism in 17 cases (17/42, 40.48%). The average glycosylated hemoglobin was 9.35%, and the average fasting blood-glucose was 8.44 mmol/L; the mean fasting insulin was 349.96 μIU/mL, and the average fasting C-peptide was 6.00 ng/mL. Diabetes was reported in 25 cases (25/33, 75.76%) all of which were diagnosed before 23 years old. All 42 patients had recorded gene mutations, with 22 patients (22/42, 52.38%) having ≥ 2 mutations and 20 cases (20/42, 47.62%) having only 1 mutation. No statistical differences were found in clinical features and laboratory parameters between patients with different mutations. Conclusion The study indicates that RMS should be considered in young patients with hyperinsulinemia, hyperglycemia with low weight, acanthosis nigricans, growth retardation, dental anomalies, and hirsutism. [ABSTRACT FROM AUTHOR]

Background/aim: Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, based on the data available within 24 h of admission. Design: Prospective observational study. Methods: A prospective cohort was conducted at a university hospital with 523 patients hospitalised for stroke. We built and trained six different machine learning (ML) models, followed by testing and tuning those models to find the best‐suited predictor for discharge disposition, dichotomized into home and non‐home. To evaluate the accuracy, reliability and interpretability of the best‐performing models, we identified and analysed the features that had the greatest impact on the predictions. Results: In total, 523 patients met the inclusion criteria, with a mean age of 61 years. Of the patients with stroke, 30.01% had non‐home discharge. Our model predicting non‐home discharge achieved an area under the receiver operating characteristic curve of 0.95 and a precision of 0.776. After threshold was moved, the model had a recall of 0.809. Top 10 variables by importance were National Institutes of Health Stroke Scale (NIHSS) score, family income, Barthel index (BI) score, FRAIL score, fall risk, pressure injury risk, feeding method, depression, age and dysphagia. Conclusion: The ML model identified higher NIHSS, BI, and FRAIL, family income, higher fall risk, pressure injury risk, older age, tube feeding, depression and dysphagia as the top 10 strongest risk predictors in identifying patients who required non‐home discharge to higher levels of care. Modern ML techniques can support timely and appropriate clinical decision‐making. Relevance to Clinical Practice: This study illustrates the characteristics and risk factors of non‐home discharge in patients with stroke, potentially contributing to the improvement of the discharge process. Reporting Method: STROBE guidelines. [ABSTRACT FROM AUTHOR]

In the vitamin C microbial fermentation system, oxidative stress limits the growth and 2‐keto‐l‐gulonic acid (2‐KLG, the precursor of vitamin C) production of Ketogulonicigenium vulgare. Most Bacillus strains, as helper strains, have been reported to release key biomolecules to reduce oxidative stress and promote the growth and 2‐KLG production of K. vulgare. To understand the specific mechanism by which the helper strain and K. vulgare interact to reduce oxidative stress, a novel helper strain, Rhodotorula mucilaginosa A8, was used to construct a consortium in the co‐culture fermentation system. Based on the activities of the antioxidant enzymes and quantitative polymerase chain reaction (qPCR) analysis, R. mucilaginosa A8 could reduce oxidative stress and increase 2‐KLG production in K. vulgare by upregulating antioxidant enzyme activities and related gene‐expression levels. In addition, the carotenoids of R. mucilaginosa promoted 2‐KLG production in K. vulgare. Coculture of R. mucilaginosa with K. vulgare increased the yield of carotenoids. This study suggested that helper strains with the ability to reduce oxidative stress in K. vulgare would likely act as potential helper strains for facilitating 2‐KLG biosynthesis. This work could provide a theoretical basis for the search for potential helper strains for vitamin C microbial fermentation and for the construction of synthetic microbial communities to produce valuable products. [ABSTRACT FROM AUTHOR]

In this work, MgO-coated carbon nanotubes (MgO@CNTs) were synthesized via the co-deposition technique. The samples of MgO@CNTs were treated by using the high power ultrasonic vibration with a long time to verify their structural stability. Microstructure of the CNTs and MgO@CNTs was characterized by using the FI-IT spectra analysis, scanning electron microscope and transmission electron microscope. The experiment result reveals that the high power ultrasonic vibration and the long-time ultrasonic-treatment can easily cut off the CNTs, while the MgO nanoparticles are still tightly adsorbed on the surface of CNTs without removing away from the surface of CNTs by the ultrasonic vibration. It means that MgO@CNTs is a novel reinforcement for the Mg-based composite because the MgO nanoparticles and CNTs have formed a good interface bonding with high stability. Simultaneously, the stable interfacial bonding between MgO and CNTs is explained by the first- principle calculation.