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Soybean is considered one of the most drought-sensitive crops, and ROS homeostasis can regulate drought tolerance in these plants. Understanding the mechanism of H2O2 homeostasis and its regulatory effect on drought stress is important for improving drought tolerance in soybean. We used different concentrations of polyethylene glycol (PEG) solutions to simulate the progression from weak drought stress (0.2%, 0.5%, and 1% PEG) to strong drought stress (5% PEG). We investigated the responses of the soybean plant phenotype, ROS level, injury severity, antioxidant system, etc., to different weak drought stresses and subsequent strong drought stresses. The results show that drought-treated plants accumulated H2O2 for signaling and exhibited drought tolerance under the following stronger drought stress, among which the 0.5% PEG treatment had the greatest effect. Under the optimal treatment, there was qualitatively describable H2O2 homeostasis, characterized by a consistent increasing amplitude in H2O2 content compared with CK. The H2O2 signal formed under the optimum treatment induced the capacity of the antioxidant system to remove excess H2O2 to form a primary H2O2 homeostasis. The primary H2O2 homeostasis further induced senior H2O2 homeostasis under the following strong drought and maximized the improvement of drought tolerance. These findings might suggest that gradual drought training could result in stepwise H2O2 homeostasis to continuously improve drought tolerance. [ABSTRACT FROM AUTHOR]

Craniotomies are intricate neurosurgical procedures susceptible to post‐operative complications, among which surgical site infections (SSIs) are particularly concerning. This study sought to elucidate the potential risk factors and pathogenetic characteristics associated with SSIs following craniotomy procedures in a clinical setting. A retrospective study was conducted from May 2020 to May 2023, examining patients subjected to elective or emergency craniotomies. The cohort underwent post‐operative surveillance for SSIs, facilitating patient classification into SSI and Non‐SSI groups based on infection occurrence. Data collection encapsulated demographic and clinical parameters, including American Society of Anesthesiologists (ASA) classifications, and operative factors. SSIs were diagnosed via an integrated approach combining clinical symptoms, microbiological culture findings and pertinent laboratory tests. A rigorous statistical methodology employing IBM's SPSS version 27.0 was utilised for data analysis. In a univariate analysis, significant risk factors for post‐craniotomy SSIs were identified, with patients aged over 60 displaying a pronounced susceptibility. Moreover, surgeries exceeding a duration of 4 h heightened infection risks. Elevated ASA grades denoted an increased prevalence of SSIs, as did emergency procedures and higher National Nosocomial Infections Surveillance scores. Multivariate analysis pinpointed epidural/subdural drainage as a protective measure against SSIs, whereas emergency surgeries, operative times beyond 4 h and subsequent surgeries within the hospital stay amplified infection risks. Notably, coagulase‐negative Staphylococcus dominated the identified pathogens at 28.09%, followed by Escherichia coli (17.98%), Klebsiella pneumoniae (10.11%) and Staphylococcus aureus (11.24%), underscoring the need for diverse prophylactic measures. SSIs following craniotomies present a multifaceted challenge influenced by a confluence of patient‐related, operative and post‐operative determinants. Understanding these risk factors is paramount in refining surgical protocols and post‐operative care strategies to mitigate SSI incidence. [ABSTRACT FROM AUTHOR]

Here an IR‐heating chemical vapor deposition (CVD) approach enabling fast 2D‐growth of WSe2 thin films is reported, and the great potential of metal contact doping in building CVD‐grown WSe2‐based lateral homojunction is demonstrated by contacting with TiN/Ni metals in favor of holes/electrons injection. Shortening nanosheet channel to ≈2 µm leads to pronounced enhancement in the performance of diode. The fabricated WSe2‐based diode exhibits high rectification ratios without the need of gate modulation and can work efficiently as photovoltaic cell, with maximum open circuit voltage reaching up to 620 mV and a high power conversion efficiency over 15%, empowering it as superb self‐powered photodetector for visible to near‐infrared lights, with photoresponsivity over 0.5 A W−1 and a fast photoresponse speed of 10 µs under 520 nm illumination. It is of practical significance to achieve well‐performed photovoltaic devices with CVD‐grown WSe2 using fab‐friendly metals and simple processing, which will help pave the way toward future mass production of optoelectronic chips. [ABSTRACT FROM AUTHOR]

In order to improve the cathodic protection and wear resistance of cold spraying Zn-based coatings, Zn–Ni/Cu–Al2O3 composite coating was prepared by co-depositing Zn powders, nickel-coated Cu powders, and Al2O3 powders on the steel substrate using the low-pressure cold spraying method. The structure and composition of Zn–Ni/Cu–Al2O3 coatings were analyzed by scanning electron microscopy, energy dispersive spectrum analysis, and X-ray diffraction, respectively. And their wear and corrosion resistance were tested. The results show that the structure of the Zn–Ni/Cu–Al2O3 composite coating is compact and the nickel powder is evenly distributed in the coating. Compared with the Zn–Al2O3 coating and Zn–Cu–Al2O3 coating, the Zn–Ni/Cu–Al2O3 composite coating has better wear resistance in air and stronger corrosion resistance in the 3.5 wt.% NaCl solutions. The Zn–Ni/Cu–Al2O3 coating has the lowest corrosion rate and maximum impedance after the immersion and scratch tests. Due to the promoting effect of Ni, the Zn–Ni/Cu–Al2O3 coating can quickly form a dense protective layer of corrosion products, which makes the Zn–Ni/Cu–Al2O3 composite coating has better cathodic protection and defect self-repair performance. [ABSTRACT FROM AUTHOR]

Recently, graph-based semisupervised learning methods have been widely applied in multimedia research area. However, for the application of video semantic annotation in multilabel setting, these methods neglect an important characteristic of video data: The semantic concepts appear correlatively and interact naturally with each other rather than exist in isolation. In this paper, we adapt this semantic correlation into graph-based semisupervised learning and propose a novel method named correlative linear neighborhood propagation to improve annotation performance. Experiments conducted on the Text REtrieval Conference VIDeo retrieval evaluation data set have demonstrated its effectiveness and efficiency. Index Terms--Graph-based method, label propagation, semantic correlation, video annotation.