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Abstract Silicon-vacancy (SiV) centers in diamond are emerging as promising quantum emitters in applications such as quantum communication and quantum information processing. Here, we demonstrate a sub-μs pulsed annealing treatment that dramatically increases the photoluminescence of SiV centers in diamond. Using a silane-functionalized adamantane precursor and a laser-heated diamond anvil cell, the temperature and energy conditions required to form SiV centers in diamond were mapped out via an optical thermometry system with an accuracy of ±50 K and a 1 μs temporal resolution. Annealing scheme studies reveal that pulsed annealing can obviously minimize the migration of SiV centers out of the diamond lattice, and a 2.5-fold increase in the number of emitting centers was achieved using a series of 200-ns pulses at a 50 kHz repetition rate via acousto-optic modulation. Our study provides a novel pulsed annealing treatment approach to improve the efficiency of the creation of SiV centers in diamond.

Abstract Microstructural changes in conductive materials induced by electric current treatments, such as electromigration and electroplasticity, are critical in semiconductor and metal processing. However, owing to the inevitable thermal effect (Joule heating), the athermal effect on microstructural modifications remains obscure. This paper presents an approach of utilizing pre-micromachined structures, which obstruct current flow but maintain a thermal history similar to that of the matrix, effectively disentangling the thermal and athermal effects. A duplex stainless-steel material is selected to validate the feasibility of this method. Microstructural characterizations show that the athermal effect, especially the electron wind force (EWF), primarily governs the element diffusion and phase transformation in this study. Moreover, many σ phases (Cr-enriched) are precipitated in the micromachined structures, whereas no precipitation occurred in the matrix, suggesting that the directional EWF disrupts the Cr aggregation caused by Joule heating. Furthermore, we present a critical formula for determining the dimensions of micromachined structures of commonly used metallic materials. The proposed method may serve as an effective and powerful tool for unveiling the athermal effect on microstructural alterations.

Accurate prediction of electric vehicle (EV) charging loads is a foundational step in the establishment of expressway charging infrastructures. This study introduces an approach to enhance the precision of expressway EV charging load predictions. The method considers both the battery dynamic state-of-charge (SOC) and user charging decisions. Expressway network nodes were first extracted using the open Gaode Map API to establish a model that incorporates the expressway network and traffic flow features. A Gaussian mixture model is then employed to construct a SOC distribution model for mixed traffic flow. An innovative SOC dynamic translation model is then introduced to capture the dynamic characteristics of traffic flow SOC values. Based on this foundation, an EV charging decision model was developed which considers expressway node distinctions. EV travel characteristics are extracted from the NHTS2017 datasets to assist in constructing the model. Differentiated decision-making is achieved by utilizing improved Lognormal and Sigmoid functions. Finally, the proposed method is applied to a case study of the Lian-Huo expressway. An analysis of EV charging power converges with historical data and shows that the method accurately predicts the charging loads of EVs on expressways, thus revealing the efficacy of the proposed approach in predicting EV charging dynamics under expressway scenarios.

Agro-based small and medium enterprises (SMEs) are currently receiving top priority among policymakers of the South Asian Association for Regional Cooperation (SAARC) nations due to their great contribution to employment and GDP growth. This study examines the impact of financial literacy on the sustainable competitive performance of agro-based SMEs, with a focus on the mediating role of access to digital finance and the moderating role of business experience. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), we analysed data from 345 SME owner-managers. The results indicate that financial literacy positively affects sustainable competitive performance, with access to digital finance serving as a significant mediator. However, business experience does not moderate the relationship between financial literacy and access to digital finance. These findings suggest that improving financial literacy and enhancing digital finance access are critical for the sustainable development of agro-based SMEs in the SAARC region.

Abstract Electrochemical carbon dioxide/carbon monoxide reduction reaction offers a promising route to synthesize fuels and value-added chemicals, unfortunately their activities and selectivities remain unsatisfactory. Here, we present a general surface molecular tuning strategy by modifying Cu2O with a molecular pyridine-derivative. The surface modified Cu2O nanocubes by 4-mercaptopyridine display a high Faradaic efficiency of greater than 60% in electrochemical carbon monoxide reduction reaction to acetate with a current density as large as 380 mA/cm2 in a liquid electrolyte flow cell. In-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy reveals stronger *CO signal with bridge configuration and stronger *OCCHO signal over modified Cu2O nanocubes by 4-mercaptopyridine than unmodified Cu2O nanocubes during electrochemical CO reduction. Density function theory calculations disclose that local molecular tuning can effectively regulate the electronic structure of copper catalyst, enhancing *CO and *CHO intermediates adsorption by the stabilization effect through hydrogen bonding, which can greatly promote asymmetric *CO-*CHO coupling in electrochemical carbon monoxide reduction reaction.

Wind turbine generator output cables are subjected to alternating torsional loads during long-term operation, combined with electrothermal stress, which may lead to insulation failure and other serious issues. Currently, the electrothermal aging mechanism under torsional stress is not fully understood. This study explores the synergistic degradation mechanism of electrothermal aging and nonlinear torsion by constructing a multi-stress aging test platform in the laboratory environment. This study involved accelerated aging tests with thermal, electrothermal, and electrothermal–torsional alternating stresses. The aged cable samples were analyzed for their physical and chemical properties using differential scanning calorimetry and Fourier transform infrared spectroscopy, while dielectric spectroscopy and mechanical tests were employed to evaluate their dielectric and mechanical performance. The results indicate that torsional stress induces physical changes at the molecular level in the ethylene–propylene rubber (EPR), leading to reduced strength, hardening, and increased brittleness, resulting in decreased mechanical strength. In addition, torsional stress promotes oxidation reactions and chain scission processes in the insulation layer, reducing crystallinity and causing a decline in mechanical performance. Increased oxidation and chain scission reactions result in an increase in polar groups, leading to an increase in the dielectric loss factor of the EPR. The findings of this study provide valuable insights for the design, manufacturing, and operational monitoring of wind turbine generator output cables.

During the COVID-19 pandemic, there has been a growing prevalence of mental disorders, particularly in China, where anti-epidemic measures have been more stringent compared to other countries. This has resulted in a heightened psychological burden on individuals. However, the actual psychological impacts of COVID-19 on Chinese residents have not been clearly established. In this study, we aimed to investigate the effects of various factors, including personal and household characteristics, social networks, and epidemic-related variables (such as rural residents' knowledge of COVID-19 virus transmission and prevention), on rural residents' depression. Using a two-year balanced panel dataset encompassing 152 villages and 676 samples in both 2019 and 2020, we employed the Ordinary Least Squares (OLS) model to estimate the influence of these factors and compare their coefficients to examine the changes in rural residents' depression between the pre-epidemic and during-epidemic periods. Our study highlights significant factors contributing to rural residents' depression during the COVID-19 pandemic, including isolation (2.063, p

BackgroundMajor depressive disorder (MDD) is the leading cause of disability among all mental illnesses with increasing prevalence. The diagnosis of MDD is susceptible to interference by several factors, which has led to a trend of exploring objective biomarkers. Electroencephalography (EEG) is a non-invasive procedure that is being gradually applied to detect and diagnose MDD through some features such as functional connectivity (FC).MethodsIn this research, we analyzed the resting-state EEG of patients with MDD and healthy controls (HCs) in both eyes-open (EO) and eyes-closed (EC) conditions. The phase locking value (PLV) method was utilized to explore the connection and synchronization of neuronal activities spatiotemporally between different brain regions. We compared the PLV between participants with MDD and HCs in five frequency bands (theta, 4–8 Hz; alpha, 8–12 Hz; beta1, 12–16 Hz; beta2, 16–24 Hz; and beta3, 24–40 Hz) and further analyzed the correlation between the PLV of connections with significant differences and the severity of depression (via the scores of 17-item Hamilton Depression Rating Scale, HDRS-17).ResultsDuring the EO period, lower PLVs were found in the right temporal-left midline occipital cortex (RT-LMOC; theta, alpha, beta1, and beta2) and posterior parietal-right temporal cortex (PP-RT; beta1 and beta2) in the MDD group compared with the HC group, while PLVs were higher in the MDD group in LT-LMOC (beta2). During the EC period, for the MDD group, lower theta and beta (beta1, beta2, and beta3) PLVs were found in PP-RT, as well as lower theta, alpha, and beta (beta1, beta2, and beta3) PLVs in RT-LMOC. Additionally, in the left midline frontal cortex-right temporal cortex (LMFC-RT) and posterior parietal cortex-right temporal cortex (PP-RMOC), higher PLVs were observed in beta2. There were no significant correlations between PLVs and HDRS-17 scores when connections with significantly different PLVs (all p > 0.05) were checked.ConclusionOur study confirmed the presence of differences in FC between patients with MDD and healthy individuals. Lower PLVs in the connection of the right temporal-left occipital cortex were mostly observed, whereas an increase in PLVs was observed in patients with MDD in the connections of the left temporal with occipital lobe (EO), the circuits of the frontal-temporal lobe, and the parietal-occipital lobe. The trends in FC involved in this study were not correlated with the level of depression.LimitationsThe study was limited due to the lack of further analysis of confounding factors and follow-up data. Future studies with large-sampled and long-term designs are needed to further explore the distinguishable features of EEG FC in individuals with MDD.

In order to play the important role of safety culture in accident prevention, we use the method of safety culture improvement based on accident causation “2-4” model (24Model) to study the status quo of safety culture construction in a coal enterprise and put forward improvement measures. Firstly, the applicability of the safety culture level improvement method in our country under the vision of 24Model is clarified. Then, starting with the current situation of safety culture level and safety concepts, we carry out practical research. Finally, the improvement measures are put forward. The results show that the safety culture level of the enterprise is generally better than that of the domestic or the same industry with poor safety performance, and worse than that of the enterprise with good safety performance; the enterprise’s safety concepts involves 13 aspects of 32 elements; the first-line workers, monitors, professionals and management of the enterprise have a poor understanding of some elements, and only elements 3, 4, 6, 13 and 16 of these poorly understood elements are reflected in the enterprise’s safety concepts; fourteen improved safety concepts are proposed to improve the enterprise’s safety culture level.

Abstract Objective To identify the distinct profiles of work alienation among Chinese nurses, examine the demographic factors associated with profile memberships, and then explore the relationship between latent categories of work alienation and job embeddedness. Methods A cross-sectional survey of 523 nurses was conducted from July to August 2023. Latent profile analysis (LPA) was performed to identify distinct profiles of nurses based on three aspects: powerlessness, helplessness, and meaningfulness. A multinomial logistic regression analysis was conducted to explore the predictors of profile membership. Hierarchical regression analysis was carried out to examine the association between profile memberships and job embeddedness. Results Three subgroups of work alienation of nurses were identified: 23.1%, 57.8%, and 19.1% in the low work alienation group (profile 1), the moderate work alienation group (profile 3), and the high work alienation group (profile 2), respectively. Nurses with college degrees were more likely to be grouped into moderate work alienation. Nurses who did not work night shifts were more likely to have low or moderate levels of work alienation. Nurses earning 2,000–3,000 and 3,001–5,000 yuan per month were likely to be in the low work alienation group. The different categories of work alienation significantly predicted job embeddedness among nurses (ΔR 2 = 0.103, p

Abstract The Li-S battery is a promising next-generation battery chemistry that offers high energy density and low cost. The Li-S battery has a unique chemistry with intermediate sulphur species readily solvated in electrolytes, and understanding their implications is important from both practical and fundamental perspectives. In this study, we utilise the solvation free energy of electrolytes as a metric to formulate solvation-property relationships in various electrolytes and investigate their impact on the solvated lithium polysulphides. We find that solvation free energy influences Li-S battery voltage profile, lithium polysulphide solubility, Li-S battery cyclability and the Li metal anode; weaker solvation leads to lower 1st plateau voltage, higher 2nd plateau voltage, lower lithium polysulphide solubility, and superior cyclability of Li-S full cells and Li metal anodes. We believe that relationships delineated in this study can guide the design of high-performance electrolytes for Li-S batteries.

Abstract The meticulous design of active sites and light absorbers holds the key to the development of high-performance photothermal catalysts for CO2 hydrogenation. Here, we report a nonmetallic plasmonic catalyst of Mo2N/MoO2-x nanosheets by integrating a localized surface plasmon resonance effect with two distinct types of active sites for CO2 hydrogenation. Leveraging the synergism of dual active sites, H2 and CO2 molecules can be simultaneously adsorbed and activated on N atom and O vacancy, respectively. Meanwhile, the plasmonic effect of this noble-metal-free catalyst signifies its promising ability to convert photon energy into localized heat. Consequently, Mo2N/MoO2-x nanosheets exhibit remarkable photothermal catalytic performance in reverse water-gas shift reaction. Under continuous full-spectrum light irradiation (3 W·cm−2) for a duration of 168 h, the nanosheets achieve a CO yield rate of 355 mmol·gcat−1·h−1 in a flow reactor with a selectivity exceeding 99%. This work offers valuable insights into the precise design of noble-metal-free active sites and the development of plasmonic catalysts for reducing carbon footprints.

Abstract Background Lipids are regulators of insulitis and β-cell death in type 1 diabetes development, but the underlying mechanisms are poorly understood. Here, we investigated how the islet lipid composition and downstream signaling regulate β-cell death. Methods We performed lipidomics using three models of insulitis: human islets and EndoC-βH1 β cells treated with the pro-inflammatory cytokines interlukine-1β and interferon-γ, and islets from pre-diabetic non-obese mice. We also performed mass spectrometry and fluorescence imaging to determine the localization of lipids and enzyme in islets. RNAi, apoptotic assay, and qPCR were performed to determine the role of a specific factor in lipid-mediated cytokine signaling. Results Across all three models, lipidomic analyses showed a consistent increase of lysophosphatidylcholine species and phosphatidylcholines with polyunsaturated fatty acids and a reduction of triacylglycerol species. Imaging assays showed that phosphatidylcholines with polyunsaturated fatty acids and their hydrolyzing enzyme phospholipase PLA2G6 are enriched in islets. In downstream signaling, omega-3 fatty acids reduce cytokine-induced β-cell death by improving the expression of ADP-ribosylhydrolase ARH3. The mechanism involves omega-3 fatty acid-mediated reduction of the histone methylation polycomb complex PRC2 component Suz12, upregulating the expression of Arh3, which in turn decreases cell apoptosis. Conclusions Our data provide insights into the change of lipidomics landscape in β cells during insulitis and identify a protective mechanism by omega-3 fatty acids. Video Abstract

Over the past few decades, the Internet has rapidly diffused across China. The spread of the Internet has had a profound economic and social impact on Chinese rural areas. Existing research shows that Internet access significantly impacts agricultural production and improves smallholder farmers’ income. Beyond these, the Internet can affect other dimensions of social welfare. However, research about the impact of Internet access on dietary quality in rural China remains scarce. This study utilizes multi-period panel data from Fixed Observation Point in rural China from 2009 to 2015 to estimate the impact of Internet access on dietary quality and food consumption of rural households and conducts a causal analysis. Regression models with time and household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity. The estimates show that Internet access has significantly increased rural household dietary quality (measured by the Chinese Diet Balance Index). Further research finds that Internet access has increased the consumption of animal products, such as aquatic and dairy products. We also examine the underlying mechanisms. Internet access improves dietary quality and food consumption mainly through increasing household income and food expenditure. These results encourage the promotion of Internet access as a valuable tool for nutritional improvements, especially in rural areas.

Abstract Optoelectronic properties of semiconductors are significantly modified by impurities at trace level. Oxygen, a prevalent impurity in organic semiconductors (OSCs), has long been considered charge-carrier traps, leading to mobility degradation and stability problems. However, this understanding relies on the conventional deoxygenation methods, by which oxygen residues in OSCs are inevitable. It implies that the current understanding is questionable. Here, we develop a non-destructive deoxygenation method (i.e., de-doping) for OSCs by a soft plasma treatment, and thus reveal that trace oxygen significantly pre-empties the donor-like traps in OSCs, which is the origin of p-type characteristics exhibited by the majority of these materials. This insight is completely opposite to the previously reported carrier trapping and can clarify some previously unexplained organic electronics phenomena. Furthermore, the de-doping results in the disappearance of p-type behaviors and significant increase of n-type properties, while re-doping (under light irradiation in O2) can controllably reverse the process. Benefiting from this, the key electronic characteristics (e.g., polarity, conductivity, threshold voltage, and mobility) can be precisely modulated in a nondestructive way, expanding the explorable property space for all known OSC materials.

This study employs artificial neural networks (ANNs) to predict the structural compliance of randomly generated irregular geometries derived from Finite Element (FE) calculations. By imposing volume constraints, the scope of the study is confined to applying ANNs for learning from structural data generated by considering either multiple random walks of a circle or a set of randomly placed circles with allowed overlaps. Numerical results indicate that the learning outcomes of the former approach are more satisfactory than those of the latter. This suggests that the effectiveness of employing ANNs for predicting the structural compliance of irregular geometries is contingent upon how the random geometries are generated and the material volume ratio. The learning outcomes of irregular structures generated by the former approach with a higher volume ratio exhibit greater satisfaction due to a higher degree of structural connectivity.

Accurate monitoring of alpine wetland areas and scientific evaluation of alpine wetland restorability play important roles in revealing the changing mechanism of the ecological environment. However, because of the complexity and lack of spatial data, few studies on evaluation index system of restorability of alpine wetland considered wild animal habitat, such as habitat suitability index of black necked crane. Based on Landsat images of seven periods from 1990 to 2020, this study adopts the methods of spectral mixture analysis and change vector analysis to quantitatively demonstrate the variations and distribution patterns of alpine wetland ecosystem in the eastern edge of Qinghai–Tibet Plateau. The study focuses on determining the abundance of water, vegetation and soil, which the interannual variations represent as the shapes of ‘√’, mirror ‘N’ and normal ‘N’, respectively. In terms of natural ecological condition and human activity interference, we construct a comprehensive evaluation model of restorability of alpine wetland, separate the restorability district and construct the Bayesian network model to discuss the causal relationship between the restorability value and evaluation factor. Results show that the regions of alpine wetland in the study area changed most drastically from 1995 to 2000 and from 2000 to 2005. In addition, the total areas classified as suitable, relatively suitable and suitable for restoration account for 63.69 % of the study area, with a large potential for wetland restorability. Moreover, the prioritisation scheme of wetland restoration action includes the valley swamps of Heihe River in the middle, followed by the flat wetlands and grasslands in the south and lastly by uneven wetlands in the north.

Autism spectrum disorder (ASD) is a group of developmental diseases characterized by social dysfunction and repetitive stereotype behaviors. Besides genetic mutations, environmental factors play important roles in the development of ASD. Valproic acid (VPA) is widely used for modeling environmental factor induced ASD in rodents. However, traditional VPA modeling is low-in-efficiency and the phenotypes often vary among different batches of experiments. To optimize this ASD-modeling method, we tested “two-hit” hypothesis by single or double exposure of VPA and poly:IC at the critical time points of embryonic and postnatal stage. The autistic-like behaviors of mice treated with two-hit schemes (embryonic VPA plus postnatal poly:IC, embryonic poly:IC plus postnatal VPA, embryonic VPA plus poly: IC, or postnatal VPA plus poly:IC) were compared with mice treated with traditional VPA protocol. The results showed that all single-hit and two-hit schemes produced core ASD phenotypes as VPA single treatment did. Only one group, namely, mice double-hit by VPA and poly:IC simultaneously at E12.5 showed severe impairment of social preference, social interaction and ultrasonic communication, as well as significant increase of grooming activity and anxiety-like behaviors, in comparation with mice treated with the traditional VPA protocol. These data demonstrated that embryonic two-hit of VPA and poly:IC is more efficient in producing ASD phenotypes in mice than the single-hit of VPA, indicating this two-hit scheme could be utilized for modeling environmental factors induced ASD.

High-grade gliomas (HGG) pose significant challenges in modern tumour therapy due to the distinct biological properties and limitations of the blood-brain barrier. This review discusses recent advancements in HGG treatment, particularly in the context of immunotherapy and cellular therapy. Initially, treatment strategies focus on targeting tumour cells guided by the molecular characteristics of various gliomas, encompassing chemotherapy, radiotherapy and targeted therapy for enhanced precision. Additionally, technological enhancements are augmenting traditional treatment modalities. Furthermore, immunotherapy, emphasising comprehensive tumour management, has gained widespread attention. Immune checkpoint inhibitors, vaccines and CAR-T cells exhibit promising efficacy against recurrent HGG. Moreover, emerging therapies such as tumour treating fields (TTFields) offer additional treatment avenues for patients with HGG. The combination of diverse treatments holds promise for improving the prognosis of HGG, particularly in cases of recurrence.

Abstract General reductions in lubricant viscosities and increasing loads in machine components highlight the role of tribofilms in providing surface protection against scuffing. However, the relationship between the scuffing process and the growth and removal of tribofilm is not well understood. In this study, a multiphysics coupling model, which includes hydrodynamic lubrication, asperity contact, thermal effect, tribochemistry reaction, friction, and surface wear, was developed to capture the initiation of surface scuffing. Simulations and experiments for a piston ring and cylinder liner contact were conducted following a step-load sequence under different temperature conditions. The results show that high temperature and extreme load could induce the lubricant film collapse, which in turn triggers the breakdown of the tribofilm due to the significantly increased removal process. The failures of both lubricant film and tribofilm progress instantaneously in a coupling way, which finally leads to severe scuffing.

This study focuses on the ecological and environmental safety of Ta-pieh Mountain. Drought episodes can lead to ecological problems such as vegetation damage. Therefore, quantifying the response of vegetation to drought is essential for ecological management. The study utilized normalized difference vegetation index (NDVI) and precipitation datasets from 1999 to 2019 to derive seasonal NDVI and standardized precipitation index (SPI) data. Using Theil-Sen median trend analysis and Mann-Kendall significance test analysis, we initially examined the characteristics of vegetation and drought for the 21-year time series. SPI is used to investigate and assess the occurrence and severity of drought in the research region. Then, the strength and variability of cropland, woodland, and grassland drought resistance in the Ta-pieh Mountains were discussed using the ratio of coefficient of variation (RCV). Finally, the cross-spectrum was used to calculate the vegetation lag time to drought. The study found that NDVI increased across all seasons, while SPI increased in spring and autumn and decreased in summer and winter. The spring drought had the most significant impact on vegetation. Cropland showed the highest improvement in drought tolerance and woodland showed the highest drought tolerance. The lagged response periods of cropland, woodlands, and grassland to drought were 1.62 months, 8.94 months, and 2.49 months, respectively. These findings provide a scientific basis for the management and preservation of the ecology of the Ta-pieh Mountains. HIGHLIGHTS Ecological function of the Ta-pieh Mountain is important but receives less attention.; Study on the effect of drought on vegetation in different seasons.; Study on the change of drought resistance of vegetation.; The phase spectrum in cross-spectrum analysis was used to calculate the lagged response time of vegetation and drought.;

Abstract Background Dietary management has been recommended as the cornerstone of type 2 diabetes mellitus (T2DM) management. However, low adherence to dietary recommendations has been identified in both developed and developing countries. Previous research suggests that inhibitory control influences eating behavior, but few studies have been conducted in patients with T2DM. Thus, we aimed to explore the relationship between inhibitory control and dietary adherence among patients with T2DM. Methods A total of 393 patients with T2DM from the endocrinology departments of three tertiary hospitals in China were enrolled by the convenience sampling method. Dietary adherence was measured by the Dietary Behavior Adherence Scale for Patients with Type 2 Diabetes Mellitus. Additionally, inhibitory control was subjectively measured by the Behavior Rating Inventory of Executive Function-Adult version (BRIEF-A) and objectively assessed by the stop signal task (SST) and the Stroop task. The relationship between inhibitory control and dietary adherence was analyzed using Pearson correlation analysis and hierarchical regression analysis. Results Subjectively measured inhibitory control had a significant predictive effect for dietary adherence after controlling for demographic and clinical variables. Adding the inhibitory control variable to the regression equation resulted in the following values: overall model F (19, 373) = 7.096, p

Objective: To broaden the selection of strains for fermenting fresh rice noodle and develop the application of different strains in fresh rice noodle （FRN）. Methods: With gelatinization, texture, cooking stretching, electronic nose, electronic tongue and sensory evaluation as evaluation indexes, and L. fermentum FR-21, A. orientalis AO-21, L. plantarum YI-Y2013 and blank samples as influencing factors, the eating quality of FRN fermented by different strains was analyzed. Results: L. fermentum FR-21 fermentation improved the gelatinization indexes of indica rice flour, such as valley viscosity, disintegration value, final viscosity and retrogradation value, and reduced the texture viscosity of FRN, and improved its sensory hardness and typical fermented flavor （smell 4.0 points）. The FRN fermented by A. orientalis AO-21 had the lowest cooking loss （1.63%）, high texture hardness and chewability, relatively strong aftertaste, and obvious acidic odor （smell 3.7 points）. L. plantarum YI-Y2013 was similar to L. fermentum FR-21 in gelatinization index and textural viscosity, such as valley viscosity, disintegration value, final viscosity and retrogradation value （P＜0.05）, while the FRN fermented by L. plantarum YI-Y2013 had the highest extensibility （48.83±1.00）, and the smell was fragrant and pure （smell 4.6 points）. Conclusion: The controlled fermentation of three different strains can make FRN present different taste qualities, and rice noodles with different flavor qualities can be produced by using their fermentation characteristics.

Automated region of interest detection in histopathological image analysis is a challenging and important topic with tremendous potential impact on clinical practice. The deep learning methods used in computational pathology may help us to reduce costs and increase the speed and accuracy of cancer diagnosis. We started with the UNC Melanocytic Tumor Dataset cohort which contains 160 hematoxylin and eosin whole slide images of primary melanoma (86) and nevi (74). We randomly assigned 80% (134) as a training set and built an in-house deep learning method to allow for classification, at the slide level, of nevi and melanoma. The proposed method performed well on the other 20% (26) test dataset; the accuracy of the slide classification task was 92.3% and our model also performed well in terms of predicting the region of interest annotated by the pathologists, showing excellent performance of our model on melanocytic skin tumors. Even though we tested the experiments on a skin tumor dataset, our work could also be extended to other medical image detection problems to benefit the clinical evaluation and diagnosis of different tumors.

AlGaN/GaN high-electron-mobility transistors (HEMTs) are widely used in high-frequency and high-power applications owing to the high two-dimensional electron gas (2DEG) concentration. However, the microscopic origin of the 2DEG remains unclear. This hinders the development of device fabrication technologies, such as threshold voltage modulation, current collapse suppression, and 2DEG concentration enhancement technologies, as well as AlGaN/GaN sensors with very high sensitivity to polar liquids. To clarify the 2DEG microscopic origin, we studied the effects of gas molecules on AlGaN/GaN surfaces through various experiments and first-principles calculations. The results indicated that the adsorption of gas molecules on the AlGaN/GaN surface is an important phenomenon, clarifying the microscopic origin of the 2DEG. This study elucidates the properties of AlGaN/GaN heterojunctions and promotes the development of new fabrication technologies for AlGaN/GaN devices.

To effectively reveal the disaster-causing mechanism between water stress and yield loss under different drought combinations during multiple growth periods of winter wheat, based on biennial wheat drought experiments, a crop growth analysis method was used to quantitatively identify and assess wheat yield loss sensitivity. The results showed that there was a significant negative correlation between the total dry matter relative growth rate (RGR) of wheat and the daily average degree of drought stress. The average determination coefficients of logarithmic fitting for 2017 and 2018 were 0.7935 and 0.7683, respectively. Wheat dry matter accumulation differed under the different drought combination scenarios. The yield loss sensitivity response relationship between the decrease in the RGR of wheat dry matter (relative to no drought stress) and the daily average degree of drought stress could be quantitatively identified by an S-shaped curve, and the 2017 and 2018 average coefficients of determination R2 were 0.859 and 0.849, respectively. Mild drought stress at the tillering stage stimulates adaptability and has little effect on yield. The soil water content (SWC) can be controlled to 65–75% of the field water holding capacity; the SWC at the jointing and booting stage can be controlled to be higher than the field water holding capacity of 55%. The SWC was maintained at a level higher than 75% of the field water holding capacity during the heading and flowering stages and the grain-filling and milky stages to achieve a harmonization of yields and water savings. In addition, during the production process, continuous severe drought during the jointing and booting stage and the heading and flowering stage should be avoided. This study elucidates the response relationship between drought intensity and drought-induced losses from the perspective of physical genesis, provides effective irrigation guidance for regional wheat planting, lays the foundation for the construction of quantitative agricultural drought loss risk curves, and provides technical support for predicting the trend of yield losses in wheat under different drought stresses.

The augmented prevalence of Se (Se) pollution can be attributed to various human activities, such as mining, coal combustion, oil extraction and refining, and agricultural irrigation. Although Se is vital for animals, humans, and microorganisms, excessive concentrations of this element can give rise to potential hazards. Consequently, numerous approaches have been devised to mitigate Se pollution, encompassing physicochemical techniques and bioremediation. The recognition of Se volatilization as a potential strategy for mitigating Se pollution in contaminated environments is underscored in this review. This study delves into the volatilization mechanisms in various organisms, including plants, microalgae, and microorganisms. By assessing the efficacy of Se removal and identifying the rate-limiting steps associated with volatilization, this paper provides insightful recommendations for Se mitigation. Constructed wetlands are a cost-effective and environmentally friendly alternative in the treatment of Se volatilization. The fate, behavior, bioavailability, and toxicity of Se within complex environmental systems are comprehensively reviewed. This knowledge forms the basis for developing management plans that aimed at mitigating Se contamination in wetlands and protecting the associated ecosystems.

BackgroundMajor Depressive Disorder (MDD) is a pervasive mental health issue with significant diagnostic challenges. Electroencephalography (EEG) offers a non-invasive window into the neural dynamics associated with MDD, yet the diagnostic efficacy is contingent upon the appropriate selection of EEG features and brain regions.MethodsIn this study, resting-state EEG signals from both eyes-closed and eyes-open conditions were analyzed. We examined band power across various brain regions, assessed the asymmetry of band power between the hemispheres, and integrated these features with clinical characteristics of MDD into a diagnostic regression model.ResultsRegression analysis found significant predictors of MDD to be beta2 (16–24 Hz) power in the Prefrontal Cortex (PFC) with eyes open (B = 20.092, p = 0.011), beta3 (24–40 Hz) power in the Medial Occipital Cortex (MOC) (B = −12.050, p

Background. Diabetic keratopathy (DK) poses a significant challenge in diabetes mellitus, yet its molecular pathways and effective treatments remain elusive. The aim of our research was to explore the pyroptosis-related genes in the corneal epithelium of the streptozocin-induced diabetic rats. Methods. After sixteen weeks of streptozocin intraperitoneal injection, corneal epithelium from three diabetic rats and three normal groups underwent whole-transcriptome sequencing. An integrated bioinformatics pipeline, including differentially expressed gene (DEG) identification, enrichment analysis, protein-protein interaction (PPI) network, coexpression, drug prediction, and immune deconvolution analyses, identified hub genes and key drivers in DK pathogenesis. These hub genes were subsequently validated in vivo through RT-qPCR. Results. A total of 459 DEGs were screened out from the diabetic group and nondiabetic controls. Gene Set Enrichment Analysis highlighted significant enrichment of the NOD-like receptor, Toll-like receptor, and NF-kappa B signaling pathways. Intersection of DEGs and pyroptosis-related datasets showed 33 differentially expressed pyroptosis-related genes (DEPRGs) associated with pathways such as IL-17, NOD-like receptor, TNF, and Toll-like receptor signaling. A competing endogenous RNA network comprising 16 DEPRGs, 22 lncRNAs, 13 miRNAs, and 3 circRNAs was constructed. After PPI network, five hub genes (Nfkb1, Casp8, Traf6, Ptgs2, and Il18) were identified as upregulated in the diabetic group, and their expression was validated by RT-qPCR in streptozocin-induced rats. Immune infiltration characterization showed that diabetic corneas owned a higher proportion of resting mast cells, activated NK cells, and memory-resting CD4 T cells. Finally, several small compounds including all-trans-retinoic acid, Chaihu Shugan San, dexamethasone, and resveratrol were suggested as potential therapies targeting these hub genes for DK. Conclusions. The identified and validated hub genes, Nfkb1, Casp8, Traf6, Ptgs2, and Il18, may play crucial roles in DK pathogenesis and serve as therapeutic targets.

BackgroundThe move away from investigating mental disorders as whole using sum scores to the analysis of symptom-level interactions using network analysis has provided new insights into comorbidities. The current study explored the dynamic interactions between depressive and anxiety symptoms in older Chinese adults with diabetes mellitus (DM) and identified central and bridge symptoms in the depression-anxiety network to provide potential targets for prevention and intervention for depression and anxiety.MethodsThis study used a cross-sectional design with data from the 2017–2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). A regularized partial correlation network for depressive and anxiety symptoms was estimated based on self-reported scales completed by 1685 older adults with DM aged 65 years or older. Depressive and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Seven-Item Generalized Anxiety Disorder Scale (GAD-7), respectively. Expected influence (EI) and bridge expected influence (BEI) indices were calculated for each symptom.ResultsAccording to cutoff scores indicating the presence of depression and anxiety, the prevalences of depression and anxiety in our sample were 52.9% and 12.8%, respectively. The comorbidity rate of depression and anxiety was 11.5%. The six edges with the strongest regularized partial correlations were between symptoms from the same disorder. “Feeling blue/depressed”, “Nervousness or anxiety”, “Uncontrollable worry”, “Trouble relaxing”, and “Worry too much” had the highest EI values. “Nervousness or anxiety” and “Everything was an effort” exhibited the highest BEI values.ConclusionCentral and bridge symptoms were highlighted in this study. Targeting these symptoms may be effective in preventing the comorbidity of depressive and anxiety symptoms and facilitate interventions in older Chinese adults with DM who are at risk for or currently have depressive and anxiety symptoms.

Abstract The lack of available protons severely lowers the activity of alkaline hydrogen evolution reaction process than that in acids, which can be efficiently accelerated by tuning the coverage and chemical environment of protons on catalyst surface. However, the cycling of active sites by proton transfer is largely dependent on the utilization of noble metal catalysts because of the appealing electronic interaction between noble metal atoms and protons. Herein, an all-non-noble W/WO2 metallic heterostructure serving as an efficient solid-acid catalyst exhibits remarkable hydrogen evolution reaction performance with an ultra-low overpotential of −35 mV at −10 mA/cm2 and a small Tafel slope (−34 mV/dec), as well as long-term durability of hydrogen production (>50 h) at current densities of −10 and −50 mA/cm2 in alkaline electrolyte. Multiple in situ and ex situ spectroscopy characterizations combining with first-principle density functional theory calculations discover that a dynamic proton-concentrated surface can be constructed on W/WO2 solid-acid catalyst under ultra-low overpotentials, which enables W/WO2 catalyzing alkaline hydrogen production to follow a kinetically fast Volmer-Tafel pathway with two neighboring protons recombining into a hydrogen molecule. Our strategy of solid-acid catalyst and utilization of multiple spectroscopy characterizations may provide an interesting route for designing advanced all-non-noble catalytic system towards boosting hydrogen evolution reaction performance in alkaline electrolyte.

The adjoint function of connection number has unique advantages in solving uncertainty problems of water resource complex systems, and has become an important frontier and research hotspot in the uncertainty research of water resource complex problems. However, in the rapid evolution of the adjoint function, some problems greatly limit the application of the adjoint function in the research of water resources. Therefore, based on bibliometric analysis, development, practical application issues, and prospects of the hot directions are analyzed. It is found that the development of the connection number of water resource set pair analysis can be divided into three stages: (1) relatively sluggish development before 2005, (2) a period of rapid advancement in adjoint function research spanning from 2005 to 2017, and (3) a subsequent surge post-2018. The introduction of the adjoint function of connection number promotes the continuous development of set pair analysis of water resources. Set pair potential and partial connection number are the crucial research directions of the adjoint function. Subtractive set pair potential has rapidly developed into a relatively independent and important trajectory. The research on connection entropy is comparatively less, which needs to be further strengthened, while that on adjacent connection number is even less. The adjoint function of set pair potential can be divided into three major categories: division set pair potential, exponential set pair potential, and subtraction set pair potential. The subtraction set pair potential, which retains the original dimension and quantity variation range of the connection number, is widely used in water resources and other fields. Coupled with the partial connection number, a series of new connection number adjoint functions have been developed. The partial connection number can be mainly divided into two categories: total partial connection number, and semi-partial connection number. Among these, the calculation expression and connotation of total partial connection numbers have not yet reached a consensus, accompanied by the slow development of high-order partial connection numbers. Semi-partial connection number can describe the mutual migration movement between different components of the connection number, which develops rapidly. With the limitations and current situation described above, promoting the exploration and application of the adjoint function of connection number in the field of water resources and other fields of complex systems has become the focus of future research.

Abstract Composited cable terminals are critical for reliable power delivery of traditional and traction power supply systems. During its operation, the cable terminal continually undergoes complex circumstances where humidity, temperature, field strength, mechanical stress and other factors continuously change at different levels. In extreme cases, defects or even failures may occur in the cable terminals, leading to catastrophic accidents. This makes the condition monitoring and defect detection of composited cable terminals become an imperative need for the power industry. The “state‐of‐the‐art” technology of cable terminal condition assessment is focussed and a systematic review of the current research progress of cable terminal condition assessment from the operation circumstances to failure mechanisms is provided. It covers both online/offline condition monitoring methods and defects detection approaches. In addition, challenges and future research directions for cable terminal condition assessment are also addressed. It is concluded that the non‐destructive and non‐intrusive methods like terahertz imaging and ultrasonic testing, and multi‐source information fusion methods as well as the digital twin technology have been gaining popularity for cable terminal defect inspection. It is expected the presented work can provide a global field of vision for further advancement of both scholars and industrial engineers in this field.

Abstract The solid-electrolyte interphase (SEI) plays crucial roles for the reversible operation of lithium metal batteries. However, fundamental understanding of the mechanisms of SEI formation and evolution is still limited. Herein, we develop a depth-sensitive plasmon-enhanced Raman spectroscopy (DS-PERS) method to enable in-situ and nondestructive characterization of the nanostructure and chemistry of SEI, based on synergistic enhancements of localized surface plasmons from nanostructured Cu, shell-isolated Au nanoparticles and Li deposits at different depths. We monitor the sequential formation of SEI in both ether-based and carbonate-based dual-salt electrolytes on a Cu current collector and then on freshly deposited Li, with dramatic chemical reconstruction. The molecular-level insights from the DS-PERS study unravel the profound influences of Li in modifying SEI formation and in turn the roles of SEI in regulating the Li-ion desolvation and the subsequent Li deposition at SEI-coupled interfaces. Last, we develop a cycling protocol that promotes a favorable direct SEI formation route, which significantly enhances the performance of anode-free Li metal batteries.

Abstract Climate change can lead to and intensify drought disasters. Quantifying the vulnerability of disaster-affected elements is significant for understanding the mechanisms that transform drought intensity into eventual loss. This study proposed a growth-stage-based drought vulnerability index (GDVI) of soybean using meteorological, groundwater, land use, and field experiment data and crop growth model simulation. The CROPGRO-Soybean model was used to simulate crop growth and water deficit. Four growth stages were considered since the sensitivity of soybean to drought is strictly related to the growth stage. The GDVI was applied to the Huaibei Plain, Anhui Province, China, with the goal of quantifying the spatiotemporal characteristics of soybean drought vulnerability in typical years and growth stages. The results show that: (1) The sensitivity of leaf-related parameters exceeded that of other parameters during the vegetative growth stage, whereas the top weight and grain yield showed a higher sensitivity in the reproductive growth stage; (2) A semi-logarithmic law can describe the relationship between the drought sensitivity indicators and the GDVI during the four growth stages. The pod-filling phase is the most vulnerable stage for water deficit and with the highest loss upper limit (over 70%); (3) The 2001 and 2002 seasons were the driest time during 1997−2006. Fuyang and Huainan Cities were more vulnerable to drought than other regions on the Huaibei Plain in 2001, while Huaibei and Suzhou Cities were the most susceptible areas in 2002. The results could provide effective decision support for the categorization of areas vulnerable to droughts.

Identifying the spatiotemporal characteristics and obstacle factors of the agricultural drought disaster risk is essential to reduce grain losses and ensure food security. However, due to the high uncertainty in drought disaster risk system, there are few effective risk evaluation and diagnosis methods. In this study, the uncertain information contained in sample data was mined and utilized, and a calculation method of the dynamic difference degree coefficients for the five-element connection number was proposed. Then, a quantitative risk evaluation and diagnosis model was established. Furthermore, the spatiotemporal characteristics and key obstacle factors of the agricultural drought disaster risk across Anhui Province, China from 2008 to 2017 were identified. The results indicated that the risk grades of the connection number values of North Anhui, Central Anhui, and South Anhui in 2008 were 0.359 (high risk), 0.072 (medium risk), and 0.097 (medium risk), respectively, and those in 2017 were 0.103 (medium risk), 0.196 (medium risk), and 0.368 (low risk), respectively. Thus, there were salient spatiotemporal characteristics in which the risk decreased from north to south and tended to decrease over time. In addition, the long-term high risk in North Anhui was due to the severe drought hazard, low forest cover, high exposure to drought, and low drought resistance capacity. The worse risk status in Central Anhui was caused by the small precipitation and water resources amount, low relative humidity, and large agricultural population. The factors inhibiting risk reduction in South Anhui were the large paddy field areas, low reservoir regulation and storage, and fewer water-saving irrigation areas. In summary, this method is effective and exhibits high sensitivity to risk change, and it can be applied to other grain production areas. The results can provide a scientific basis for formulating the targeted measures of agricultural drought disaster risk control in Anhui Province.

The information diffusion model is widely used in natural disaster risk assessment because of its operationalization, low data requirements and clear significance of the evaluation results. However, the commonly used normal information diffusion model is based on an average distance assumption, and the diffusion widow with h is directly affected by sample size and extreme values, especially when the sample size is more than 11, which may lead to unstable results of normal diffusion, with typical uncertainty. Considering the influence of the whole samples on the diffusion points, incorporating the connection number method, a connection number structure-based information diffusion model was proposed, and also a relative connection number method is proposed to calculate the connection number, which was applied to the risk assessment of drought disasters in Jianghuai watershed area. The results show that the connection number structure-based information diffusion model reduces the direct influence of sample extremes and sample size, eliminates the constraint of the average distance assumption in the traditional model, and performs more consistently with increasing sample size for risk assessment. And the relative connection number method can contain the traditional connection number expression and offers a wider application. A study of drought risk in the Jianghuai watershed shows that the indices of agriculture drought-suffered, drought-affected and drought-damaged fluctuated greatly, but the trends were generally consistent with each other from 1990 to 2020. It is more likely to suffer from drought in the area, but the disaster rate after drought tends to decrease over time. With the increase in drought intensity, the disaster risk will decrease significantly compared to the drought risk. The connection number structure-based information diffusion model has no two-point proximity principle and the average distance assumption, with better stability in the disaster risk assessment for different samples size compared with the traditional model, which will have more extensive application in risk assessment.

Exploring highly active and durable Ru-based electrocatalysts for acidic water oxidation is challenging. Here authors reported an ion-exchange adsorption strategy to regulate oxygen vacancies and Rh dopant, with a corresponding fundamental investigation on the lattice oxygen oxidation and the oxygen vacancy site.

AIM: To explore the key genes and molecular markers involved in the retinoblastoma development through bioinformatics.METHODS: The mRNA microarray datasets from the Gene Expression Omnibus(GEO)database were obtained, and the differentially expressed gene(DEG)between retinoblastoma cell lines and normal retinal pigment epithelial(RPE)cell lines were analyzed through gene ontology(GO)and KEGG enrichment analysis. To screen key genes, establish protein-protein interaction(PPI)network, and use receiver operating characteristic(ROC)curve to assess clinical diagnostic efficacy. The RNA expressions of key genes in retinoblastoma cell lines and normal RPE cell lines were compared by qRT-PCR.RESULTS: A total of 121 DEGs were obtained from the retinoblastoma dataset of GSE97508 and GSE110811. KEGG pathway analysis showed that DEG were enriched in phototransduction, cell cycle, and p53 signaling pathways. A total of 9 key genes, including MCM6, DTL, UBE2T, TOP2A, NUSAP1, CENPK, RRM2, RLBP1, and RHO, were obtained from the intersection of PPI network analysis and the top 30 DEG from each dataset. The differentially expressed 9 key genes were verified in GSE24673. ROC analysis showed that the area under the curve(AUC)for UBE2T, RRM2, and RHO was ≥80%, and there was a statistical significance(P>0.05). The mRNA level of UBE2T and RRM2 in retinoblastoma was significantly higher than APRE-19 cell line, while the mRNA level of RHO was significantly lower than that of ARPE-19 cell line.CONCLUSION: UBE2T, RRM2, and RHO may be served as potential molecular markers and potential therapeutic targets for retinoblastoma.

Abstract Introduction To assess the outcomes of double lamellar keratoplasty in the treatment of corneal perforation secondary to various keratopathies. Methods In this prospective non-comparative interventional case series, 15 eyes from 15 consecutive patients with corneal perforation were chosen to undergo double lamellar keratoplasty, which is characterized by two layers of lamellar grafting in the perforated area. The posterior graft was separated from a relatively healthy and thin lamellar graft of the recipient, and the anterior graft was transplanted from the donor lamellar cornea. Preoperative characteristics and postoperative examination and relevant complications throughout the study were recorded. Results Nine men and six women with an average age of 50.73 ± 19.89 (range, 9–84) years were enrolled. The median follow-up period was 18 (range, 12–30) months. In all postoperative patients, the integrity of the eyeball was successfully rebuilt, and the anterior chambers were formed without aqueous leakage. At the last visit, best-corrected visual acuity improved in 14/15 patients (93.3%). Slit-lamp microscopy showed that all treated eyes remained fully transparent. Anterior segment optical coherence tomography revealed that the double-layer structure of the treated cornea was clear in the early postoperative stage. In vivo confocal microscopy revealed intact epithelial cells, sub-basal nerves, and clear keratocytes in the transplanted cornea. No immune rejection or recurrence was detected during the follow-up period. Conclusions Double lamellar keratoplasty presents a new therapeutic option for patients undergoing corneal perforation, and it provides improvement in visual acuity and reduces the risk of postoperative adverse events.

Lipid is an important component except starch and protein in rice, which not only has unique nutritional value but also has a great impact on the functional properties of starch. In this paper, the species, structure, distribution, and content of lipids in rice were summarized, and the mechanism, structure characteristics and influencing factors of starch-lipid interaction were discussed. The interaction effects on the properties of starch, including swelling, gelatinization, rheology, retrogradation and digestive ability were reviewed. This paper provided useful information on understanding the interaction between starch and endogenous lipids in rice as well as its influence on the starch properties, which could promote the improvement of rice quality and the development of functional rice.

Since 2014, the electric vehicle industry in China has flourished and has been accompanied by rapid growth in the power battery industry led by lithium-ion battery (LIB) development. Due to a variety of factors, LIBs have been widely used, but user abuse and battery quality issues have led to explosion accidents that have caused loss of life and property. Current strategies to address battery safety concerns mainly involve enhancing the intrinsic safety of batteries and strengthening safety controls with approaches such as early warning systems to alert users before thermal runaway and ensure user safety. In this paper, we discuss the current research status and trends in two areas, intrinsic battery safety risk control and early warning methods, with the goal of promoting the development of safe LIB solutions in new energy applications.

Fast-charging is highly desired for lithium-ion batteries but is hindered by potential hazardous lithium plating and the associated parasitic reactions. Here, the authors report a nondestructive differential pressure sensing method for early detection and mitigation of lithium plating in fast-charging batteries.

Using groundwater for crop growth plays a key role in the sustainable management of water resources and irrigation and drainage design. Some studies did not consider the influence of different crop growth stages and the non-linear effect of the groundwater depth on groundwater use. In this study, three types of formulae for groundwater use were developed by referencing the phreatic evaporation formula without crops. According to the observation data, groundwater depth and use, and wheat evapotranspiration were fitted using these three non-linear formulae in each crop growth stage. The Accelerated Gene Algorithm (AGA) was used to optimize the parameters, and their performance indices were calculated. We observed that groundwater use increased gradually as the decrease in groundwater depth and the increase in wheat evapotranspiration; the correlation coefficients of wheat evapotranspiration and groundwater use were small (such as 0.539, 0.428) in the seedling stage and mature stage and large (such as 0.631, 0.625) in other stages. The performance of the Aviriyanover formula was the best with a correlation coefficient of 0.686 between the simulation and observation; therefore, this formula was recommended to determine groundwater use. HIGHLIGHTS Three groundwater use formulae were developed: the Aviriyanover, Ye Shuiting, and power function.; Groundwater use increased gradually as groundwater depth decreased increasing wheat evapotranspiration.; The Aviriyanover formula is recommended for groundwater use as it showed the least error.;

The deployment of lithium metal batteries is forestalled by poor control over the deposition morphology of lithium. Here, the authors discover that high electrical resistance can be leveraged for controlling lithium morphology and enabling high-performing lithium metal batteries.

A highly efficient strategy using Copper-Glycyl-L-Histidyl-L-Lysine (GHK-Cu) as a novel inducer was developed to enhance laccase production by Trametes versicolor. After medium optimization, laccase activity increased by 12.77-fold compared to that without GHK-Cu. The laccase production of 1113.8 U L−1 was obtained by scaling-up culture in 5-L stirring tank. The laccase production induced by CuSO4 was poorer than that of GHK-Cu at the same mole concentration. GHK-Cu could increase the permeability of cell membrane with less damage, and it facilitated the adsorption, accumulation, and utilization of copper by fungal cells, which was beneficial for laccase synthesis. GHK-Cu induced better expression of laccase related genes than that of CuSO4, resulting in higher laccase production. This study provided a useful method for induced production of laccase by applying GHK chelated metal ion as a non-toxic inducer, which reduced the safety risk of laccase broth and provided the potential application of crude laccase in food industry. In addition, GHK can be used as the carrier of different metal ions to enhance the production of other metalloenzymes.

Immobilized enzymes are currently being rapidly developed and are widely used in juice clarification. Immobilized enzymes have many advantages, and they show great advantages in juice clarification. The commonly used methods for immobilizing enzymes include adsorption, entrapment, covalent bonding, and cross-linking. Different immobilization methods are adopted for different enzymes to accommodate their different characteristics. This article systematically reviews the methods of enzyme immobilization and the use of immobilized supports in juice clarification. In addition, the mechanisms and effects of clarification with immobilized pectinase, immobilized laccase, and immobilized xylanase in fruit juice are elaborated upon. Furthermore, suggestions and prospects are provided for future studies in this area.

Patch-based methods improve the performance of infrared small target detection, transforming the detection problem into a Low-Rank Sparse Decomposition (LRSD) problem. However, two challenges hinder the success of these methods: (1) The interference from strong edges of the background, and (2) the time-consuming nature of solving the model. To tackle these two challenges, we propose a novel infrared small-target detection method using a Background-Suppression Proximal Gradient (BSPG) and GPU parallelism. We first propose a new continuation strategy to suppress the strong edges. This strategy enables the model to simultaneously consider heterogeneous components while dealing with low-rank backgrounds. Then, the Approximate Partial Singular Value Decomposition (APSVD) is presented to accelerate solution of the LRSD problem and further improve the solution accuracy. Finally, we implement our method on GPU using multi-threaded parallelism, in order to further enhance the computational efficiency of the model. The experimental results demonstrate that our method out-performs existing advanced methods, in terms of detection accuracy and execution time.