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Purpose: With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas. Design/methodology/approach: The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process. Findings: The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF). Originality/value: This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities. [ABSTRACT FROM AUTHOR]

BACKGROUND: Java tea is widely consumed and has multiple health effects. This study established a steam explosion (SE) pretreatment method to prepare Java tea‐leaf powders. The physicochemical, functional properties, phenolic extraction, and antioxidant activity of Java tea‐leaf powders produced by simple and SE‐assisted milling methods were investigated. RESULTS: In comparison with simple milling, SE pretreatment broke the cell wall effectively and reduced the particle size of Java tea‐leaf powders. Steam explosion‐treated powders showed higher values for sensory signals, bulk and tap density, and for the water solubility index. After SE treatment, the adsorption capacities to glucose, soybean oil, and cholesterol of leaf powders were increased by up to 55, 95, and 80% respectively. The extracts from SE‐treated powders also showed higher total polyphenol content and antioxidant activity. CONCLUSION: Steam explosion treatment is helpful for the improvement of functional properties and antioxidant activity, which can benefit the development and application of Java tea‐leaf powders. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

BACKGROUND: Garlic is a promising source of antimicrobial peptide separation, and chemical modification is an effective method for activity improvement. The present study aimed to improve the antifungal activity of a peptide extracted from garlic. Chemical modifications were conducted, and the structure–activity relationship and antifungal mechanism were investigated. RESULTS: The results indicated that the cationic charge induced by Lys residue at the N‐terminal was important for the antimicrobial activity, and the modified sequence exhibited significant antifungal activity with low mammalian toxicity and a low tendency of drug resistance (p < 0.05). The structure–activity relationship analysis revealed that the modified active peptide had a predominant α‐helical structure and an inner cyclic correlation. Transcriptomic analysis showed that peptide KMLKKLFR (Lys‐Met‐Leu‐Lys‐Lyse‐Leu‐Phe‐Arg) affected the rRNA processing and carbon metabolism process of Candida albicans. In addition, the membrane potential study indicated a non‐membrane destruction mechanism, and molecular docking analysis and a DNA interaction assay suggested promising inner targets. CONCLUSION: The results of the present study indicate that chemical modification by amino acid substitution was effective for antimicrobial activity improvement. The present study would benefit future antimicrobial peptide development and suggests that garlic is a great source of antibacterial peptides and peptide template separations for coping with antibiotic resistance. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

This paper presents a performance text, crafted by university researchers and teachers from a primary school in China. The "embodied narrative" is explored as theory, method, practice, event, and action within this collaborative inquiry. Through vignettes, we delve into the positionalities of teachers and teacher educators, highlighting the fluidity between participant, researcher, and performer roles. Our endeavor challenges the dominance of textualism in educational research, emphasizing "culture as performance" and "practice as research." This embodied narrative approach allows teachers and teacher educators to bridge theoretical and practical divides, merge personal and public realms, and take proactive actions. [ABSTRACT FROM AUTHOR]

Carbon nanotube/epoxy resin (CNE) coatings and carbon nanotube/carboxy iron powder/epoxy resin (CIE) coatings were applied on the surface of Q235 steel, and their corrosion, absorption properties and other characteristics were measured in this work. The results indicate that the average thickness of a single application was approximately 400 μm, and the surface of the CNE coating was still smooth and intact after a 3000 h copper ion accelerated salt spray test without bubbles, falling off or other corrosion phenomena. The same was true for 28 days of full immersion in solutions of 10% hydrochloric acid (HCl) and 10% sodium hydroxide (NaOH) of the coating. The electrochemical testing exhibited the corrosion current of the CNE coating as being markedly lower than that of Q235 steel, with a protection efficiency of 81.68% for the Q235 steel. The CNE-0.6 coating had the maximum corrosion voltage (−0.390 V), and the CNE-0.3 coating had the minimum corrosion current of 2.07 × 10−6 A·cm2. The adhesion between the coating and Q235 could reach level 0, and the tensile strength of the coating was up to 18.75 MPa. The coating was observed to remain intact and free from detachment upon undergoing a drop test from a height of 50 cm. In addition, the CIE-0.6 coating exhibited an effective absorption band of 9.1 GHz, covering the range from 8.2 to 13.7 GHz, and it achieved a maximum reflection loss of −15.1 dB at a frequency of 8.6 GHz. [ABSTRACT FROM AUTHOR]

Background: Exercise training is fundamental in pulmonary rehabilitation (PR), but patients with chronic obstructive pulmonary disease (COPD) often struggle with exercise intolerance. Respiratory support during exercise in COPD patients may be a beneficial adjunct therapy. In this study, the effect of different respiratory support therapy during pulmonary rehabilitation exercise training in COPD patients was assessed through a network meta-analysis. Methods: Five databases were searched to obtain randomized controlled trials involving different respiratory support therapies during PR exercise training in COPD patients. The Cochrane Handbook tool was employed to assess the risk bias of included studies. Network meta-analysis was performed using the STATA software. The study protocol was registered at PROSPERO (CRD42023491139). Results: A total of 35 studies involving 1321 patients and 6 different interventions were included. Network meta-analysis showed that noninvasive positive pressure ventilation (NPPV) is superior in improving exercise capacity (6-Minute Walk Test distance, peak work rate, endurance time), dyspnea, and physiological change (peak VO2, tidal volume, minute ventilation and lactate level) in stable COPD patients who were at GOLD stage III or IV during PR exercise training. The final surface under the cumulative ranking curve value indicated that NPPV therapy achieved the best assistive rehabilitation effect. Conclusions: The obtained results indicate that NPPV is most powerful in assisting exercise in severe COPD patients under stable condition. Researchers should focus more on the safety, feasibility, and personalization of interventions. Furthermore, there is a need for additional high-quality trials to assess the consistency of evidence across various respiratory support approaches. Trial registration: The study was registered at PROSPERO (CRD42023491139). [ABSTRACT FROM AUTHOR]

Under the wave of Industry 4.0, traditional pharmaceutical manufacturing enterprises are in urgent need of intelligent manufacturing transformation and upgrading, and exploring the optimal realization path of intelligent manufacturing transformation can help accelerate the transformation process of pharmaceutical manufacturing enterprises. This paper uses grounded theory research methods to conduct a multi-case study to summarize six influencing factors of the intelligent manufacturing transformation of Chinese pharmaceutical manufacturing enterprises; and then analyzes the correlation between the intelligent manufacturing influencing factors based on the DEMATEL method and the NK model, and identifies the key influencing factors according to this, and then draws the fitness landscape map of the intelligent manufacturing transformation, and finally arrives at the optimal path selection of the intelligent manufacturing transformation of pharmaceutical manufacturing enterprises. The study enriches and extends the research paradigm of intelligent manufacturing transformation, and provides lessons for pharmaceutical manufacturing enterprises to realize intelligent manufacturing transformation and upgrading. [ABSTRACT FROM AUTHOR]

Background: In response to environmental degradation and the associated health challenges, the Chinese government has implemented a comprehensive array of environmental protection measures. Given the health enhancement objective of environmental protection measures and the considerable costs involved in the implementation process, evaluating whether environmental regulation is beneficial to reducing the health costs of the population is of great significance for enhancing environmental governance efficiency and social welfare. The data from the Chinese Family Panel Survey (CFPS) is applied to examine the effect of environmental regulation on the reduction of residents' health costs from a microscopic perspective. Results: The results indicate that for a 1% increase in total investment in environmental governance, residents' health costs will decrease by 0.189%. The examination of the causal pathway suggests that implementing environmental regulation can diminish residents' health costs through improving air quality and residents' health status. Concurrently, there exist significant heterogeneities in the role of environmental regulation in reducing residents' health costs. The effect of environmental regulation is more pronounced for the young, males, and individuals with better self-perceived health. Furthermore, the outcome of environmental regulation exhibits greater efficacy in urban areas compared to rural areas. Lastly, market-incentive environmental regulation in reducing health costs is more effective than command-controlled regulation. Conclusions: Enhancing the intensity of environmental regulation contributes to decreasing residents' health costs. The findings can provide policy reference for implementing environmental governance and achieving tangible enhancements in individuals' life quality. [ABSTRACT FROM AUTHOR]

To enhance the wear resistance of artillery barrels in harsh environments, TaC and Ta/TaC coatings were prepared on 30CrNi2MoVA steel using double-glow plasma surface metallurgy technology. These coatings, of which their surfaces consisted of almost pure TaC phases, showed defect-free interfaces with the substrate. The Ta/TaC coating demonstrated excellent integration, forming a nearly homogeneous structure. The coatings exhibited a gradient cross-sectional hardness, affecting a depth of approximately 20 μm. The Ta transition layer significantly enhanced the microhardness and adhesive strength of the TaC coating, with about 16.7% and 68.5% increases in the Ta/TaC coating, respectively. Both coatings markedly improved the wear resistance, showing slight wear at room temperature and minor oxidative wear at high temperatures. The Ta/TaC coating had more stable friction coefficient curves and a lower specific wear rate, with an 11.4% wear rate of the substrate at 500 °C. Thermal mismatch and stress concentration under wear loads caused extensive cracks and edge chipping in the TaC coating. In contrast, the good compatibility between the Ta transition layer and the TaC layer allowed for cooperative deformation with the substrate, creating a plastic deformation zone that reduced internal stresses and stress concentration, maintaining the intact structure. This study provides insights into applying Ta/TaC coatings for artillery barrel protection and broadens the possible application scenarios of the preparation technology. [ABSTRACT FROM AUTHOR]

The contamination of soil by potentially toxic elements has attracted global attention. Soil pollution caused by Cr, one of the toxic elements, poses a great threat to human health and ecosystem security. In order to clarify the flow direction of Cr pollutants and achieve accurate restoration of soil Cr pollution, it is very important to analyze the whole life cycle from pollution source to extinction. Therefore, this work analyzed the source of soil Cr pollutants, the migration and transformation behavior of Cr after entering the soil under the action of hydraulics, soil and microorganisms to clarify its flow and enrichment patterns. The biogeochemical and anthropogenic effects on Cr distribution and its biotoxicity were analyzed. Finally, recent advanced restoration techniques and future challenges were assessed. Improper disposal of all Cr-containing wastes will lead to soil pollution. The migration capacity of Cr(VI) was higher than that of Cr(III) and was affected by soil properties. Cr undergoes a continuous redox cycle between soil, microorganisms, and the atmosphere. Almost all Cr(VI) compounds are biotoxic. Serious Cr pollution areas were distributed around human production and living areas. In the future, in situ bioremediation based on genetically engineered bacteria and hyperaccumulator plants with high-biomass is the cleanest, efficient, and safe alternative. [ABSTRACT FROM AUTHOR]

Garlic has long been used as an antimicrobial spice and herbal remedy. The aim of this study was to isolate the antimicrobial agent in garlic water extract against Staphylococcus aureus (S. aureus) and investigate its antimicrobial mechanism. By an activity-guided separation, garlic lectin-derived peptides (GLDPs) with main molecular weight of around 12 kDa were extracted by liquid nitrogen grinding and identified with high bactericidal activity toward S. aureus, and the MIC was determined as 24.38 μg/mL. In-gel digestion-based proteomic analysis indicated that the peptide sequences were highly identical to the B strain of garlic protein lectin II. Structure analysis suggested that the secondary structure was strongly affected by lyophilization and thus resulted in the inactivation of GLDPs (P < 0.05). Mechanism study revealed that treatment of GLDPs resulted in cell membrane depolarization in a dose-dependent manner, and the disruptions of the cell wall and membrane integrities were observed under electric microscopies. GLDPs could successfully dock with cell wall component lipoteichoic acid (LTA) via van der Waals and conventional bonds in molecular docking analysis. These results suggested that GLDPs were responsible for the S. aureus targeting activity and might be promising candidates for antibiotic development against bacterial infection. [ABSTRACT FROM AUTHOR]

The objective of this study is to develop a remediation technology for composited heavy metal-contaminated soil. Biochars (BC300, BC400, and BC500) derived from corn were combined with potassium dihydrogen phosphate (KH2PO4) to immobilize and remove heavy metal ions, including mercury (Hg2+), cadmium (Cd2+), and lead (Pb2+). The adsorption kinetics of metal ions in aqueous solutions with different concentrations was tested, and the fitting effects of the two models were compared. The findings demonstrate that the joint application of biochar and KH2PO4 could markedly enhance the immobilization efficacy of Pb2+, whereas the utilization of KH2PO4 on its own exhibited a more pronounced immobilization impact on Cd2+. Furthermore, the present study underscores the shortcomings of various remediation techniques that must be taken into account when addressing heavy metal-contaminated soils. It also emphasizes the value of comprehensive remediation techniques that integrate multiple remediation agents. This study offers a novel approach and methodology for addressing the intricate and evolving challenges posed by heavy metal contamination in soil. Its practical value and potential for application are significant. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) is a common chronic metabolic disease worldwide. The disturbance of the gut microbiota has a complex influence on the development of DM. Polysaccharides are one type of the most important natural components with anti-diabetic effects. Gut microbiota can participate in the fermentation of polysaccharides, and through this, polysaccharides regulate the gut microbiota and improve DM. This review begins by a summary of the sources, anti-diabetic effects and the gut microbiota regulation functions of natural polysaccharides. Then, the mechanisms of polysaccharides in regulating the gut microbiota to exert anti-diabetic effects and the structure–activity relationship are summarized. It is found that polysaccharides from plants, fungi, and marine organisms show great hypoglycemic activities and the gut microbiota regulation functions. The mechanisms mainly include repairing the gut burrier, reshaping gut microbiota composition, changing the metabolites, regulating anti-inflammatory activity and immune function, and regulating the signal pathways. Structural characteristics of polysaccharides, such as monosaccharide composition, molecular weight, and type of glycosidic linkage, show great influence on the anti-diabetic activity of polysaccharides. This review provides a reference for the exploration and development of the anti-diabetic effects of polysaccharides. [ABSTRACT FROM AUTHOR]

In the present study, flat cellulose acetate ultrafiltration membranes were prepared first by nonsolvent induced phase separation method. Then chiral membranes for separating the enantiomers were prepared by grafting the ultrafiltration membranes using ethylenediamine‐β‐cyclodextrin as the chiral selector and epichlorohydrin as the spacer arm. The pure water permeability of the ultrafiltration membrane was around 115 L·m−2·h−1·bar−1. The properties of the chiral membranes were characterized using infrared spectroscopy (ATR‐FTIR), X‐ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). The chiral membrane performance in enantiomer separation was evaluated with racemates, such as mandelic acid (MA), 2‐chloromandelic acid (2‐ClMA), 4‐chloromandelic acid (4‐ClMA), and methyl mandelate (MM). The influence of feed concentration on the separation efficiency was also investigated. The results indicated that the enantiomeric excess percentages (e.e%) of the racemic mixtures for these four chiral compounds were up to 31.8%, 25.4%, 17.8%, and 32.6%, respectively. The binding free energy of the chiral selector with the (S)‐enantiomer calculated by molecular dynamics simulations was stronger than that with the (R)‐enantiomer, which was consistent with the experimental results (higher concentration of (R)‐enantiomer in the permeate). This supports the affinity absorption‐separation mechanism. [ABSTRACT FROM AUTHOR]

This research proposes a face detection algorithm named LighterFace, which is aimed at enhancing detection speed to meet the demands of real-time community applications. Two pre-trained convolutional neural networks are combined, namely Cross Stage Partial Network (CSPNet), and ShuffleNetv2. Connecting the optimized network with Global Attention Mechanism (GAMAttention) extends the model to compensate for the accuracy loss caused by optimizing the network structure. Additionally, the learning rate of the detection model is dynamically updated using the cosine annealing method, which enhances the convergence speed of the model during training. This paper analyzes the training of the LighterFace model on the WiderFace dataset and a custom community dataset, aiming to classify faces in real-life community settings. Compared to the mainstream YOLOv5 model, LighterFace demonstrates a significant reduction in computational demands by 85.4% while achieving a 66.3% increase in detection speed and attaining a 90.6% accuracy in face detection. It is worth noting that LighterFace generates high-quality cropped face images, providing valuable inputs for subsequent face recognition models such as DeepID. Additionally, the LighterFace model is specifically designed to run on edge devices with lower computational capabilities. Its real-time performance on a Raspberry Pi 3B+ validates the results. [ABSTRACT FROM AUTHOR]

Objects thrown from tall buildings in communities are characterized by their small size, inconspicuous features, and high speed. Existing algorithms for detecting such objects face challenges, including excessive parameters, overly complex models that are difficult to implement, and insufficient detection accuracy. This study proposes a lightweight detection model for objects thrown from tall buildings in communities, named S-YOLOv5, to address these issues. The model is based on the YOLOv5 algorithm, and a lightweight convolutional neural network, Enhanced ShuffleNet (ESNet), is chosen as the backbone network to extract image features. On this basis, the initial stage of the backbone network is enhanced and the simplified attention module (SimAM) attention mechanism is added to utilize the rich position information and contour information in the shallow feature map to improve the detection of small targets. For feature fusion, the sparsely connected Path Aggregation Network (SCPANet) module is designed to use sparsely connected convolution (SCConv) instead of the regular convolution of the Path Aggregation Network (PANet) to fuse features efficiently. In addition, the model uses the normalized Wasserstein distance (NWD) loss function to reduce the sensitivity of positional bias. The accuracy of the model is further improved. Test results from the self-built objects thrown from tall buildings dataset show that S-YOLOv5 can detect objects thrown from tall buildings quickly and accurately, with an accuracy of 90.2% and a detection rate of 34.1 Fps/s. Compared with the original YOLOv5 model, the parameters are reduced by 87.3%, and the accuracy and rate are improved by 0.8% and 63%, respectively. [ABSTRACT FROM AUTHOR]

Objective: Tracheal transplantation could be a better option for patients with long segmental laryngotracheal stenosis or defects, but the need for immunosuppressants limits its widespread use due to the antigenicity of the tracheal epithelium. Chemically treated or cryopreserved nonviable tracheal allografts have no immunogenicity but lead to necrosis and stenosis in long-term outcomes. The present report describes the 5-year outcomes of de-epithelialized viable tracheal allotransplantation without immunosuppressants in a patient with severe laryngotracheal stenosis. Methods: The recipient was a 47-year-old female with relapsing polychondritis affecting the larynx and cervical trachea and producing a 5 cm long stenosis that could not be repaired using resection and anastomosis. A tracheal allograft was obtained from a 45-year-old male donor and treated with a combination of 3% sodium dodecyl sulfate (SDS) and organ preservation solution for 138 hours. The allograft was revascularized by heterotopical implantation in the infrahyoid muscles of the recipient for 3 months and then transplantation to the laryngotracheal defect with a split-thickness skin graft sutured to the lumen and a silicon T-tube. No immunosuppressants were used postoperatively. Results: The allograft was de-epithelialized, and most of the cartilage rings remained viable after the treatment. The allograft was revascularized, viable, and mechanically stable after 3 months of heterotopic implantation. No apparent signs of rejection or destruction were observed. The T-tube was removed, and the internal lining of the allograft was repopulated 4 months after orthotopic transplantation, despite the skin graft necrotizing at 2 weeks. Endoscopy and computed tomography showed a patent airway 5 years after orthotopic transplantation. The patient was able to resume her usual quality of life. Conclusion: The present study demonstrates that transplantation of the de-epithelialized viable tracheal allograft without immunosuppressants is safe and promising for patients with long laryngotracheal stenosis or defects, especially for those with malignant tumor resections. [ABSTRACT FROM AUTHOR]

Water rights transactions are an important way for countries to use market mechanisms to optimize the allocation of water resources. Taking the South-North Water Transfer East Project (SNWDP-ER) in China as an example, a full cost pricing model (FCPM) is used to construct an accounting framework for water rights transactions. Water quality factors are innovatively introduced into the model to carry out a study on water rights trading pricing (WRTP) from the perspective of combining water quantity and quality. The results show that: (1) the actual WRTP (1.25 yuan/m3) for the first phase of the SNWDP-ER was low and in fact not sufficient to cover the corresponding costs. (2) By calculating the ability of water users to pay, and comparing this situation with advanced overseas cases, the conclusion was reached that the FCPM of WRTP (1.63 yuan/m3) is reasonable. (3) The method of accounting for the WRTP for major projects that take into account water quantity and quality and that are conducive to strengthening ecological protection in river basins is generally feasible. Reasonable WRTP for major projects can promote water market reform by bringing user fees, improving the competition mechanism in the water market, and reducing the financial payments pressure. [ABSTRACT FROM AUTHOR]

This study investigates the synergistic effect and mechanism of gelling materials with blast furnace slag (BFS), steel slag (SS) and desulphurization gypsum (DG) as the main components on the hardening of heavy metal ions by lead and zinc tailings. It is found that lead and zinc tailing (LZT) is mainly composed of dolomite and quartz and contain small amounts of calcium, aluminum, iron, magnesium and other elements as well as heavy metals such as lead and zinc. By the mechanical activation method, it is found that the lead and zinc tailings powder has the largest specific surface area and the highest activity index when the ball milling time is 2 h. At a hardening timepoint of 28 d, the calcite crystals in the samples are intertwined with the amorphous C-S-H gel (C-S-H gels are mainly composed of 3CaO∙SiO2 and 2CaO∙SiO2), which enhances the structural strength of the samples. The chemical reaction analysis confirmed that the formation of calcite is a major driver for the hydration reaction of the steel slag–desulphurization gypsum (SSSDG) system. Overall, the slag, steel slag and desulphurization gypsum solid waste-based gelling materials have synergistic effects in hardening heavy metals by limiting the leaching of metal ions, adsorbing metal ions and hardening heavy metals, and facilitating the hydration process through the formation of compound salt precipitates. [ABSTRACT FROM AUTHOR]

Purpose: Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution. Design/methodology/approach: This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses. Findings: The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior. Research limitations/implications: Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution. Originality/value: This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the "Motivation-Behavior-Result" framework. [ABSTRACT FROM AUTHOR]

Precise determination of the tectonothermal events at the Qinling–Qilian junction is significant for understanding the tectonic evolution of the eastern branch of the Paleo-Tethys. The Banpo pluton outcrops in the northern margin of the North Qinling were chosen as the research subject and their formation and tectonic environment were investigated using zircon U-Pb age and geochemical compositions. The weighted average values of 206Pb/238U ages of samples from three sites of the Banpo pluton corresponded to 213.4 ± 2.1 Ma (MSWD = 0.56), 213.0 ± 1.6 Ma (MSWD = 0.92), and 216.3 ± 2.3 Ma (MSWD = 2.0). All the samples are rich in light rare earth elements, exhibiting a seagull-type right-leaning partitioning curve, with obviously negative Eu anomalies. In addition, based on the regional geological data, it can be concluded that the Banpo pluton was formed during the transition period from a post-Orogenic environment to an anorogenic environment. The results indicated the final stage of the Triassic orogeny and the closure phase of the Paleo-Tethys. Also, it shows closure of the Paleo-Tethys-Mianxian-Lueyang Ocean by the Late Triassic period as well as the completion of the collision between the North China and Yangtze Blocks along the Qinling Orogenic Belt. [ABSTRACT FROM AUTHOR]

The evaluation of water resources management performance (WRMP) can provide guidance for water resources management. This paper constructs a scientific WRMP evaluation index system based on "water resources–water environment–water ecology". Secondly, the game variable weight matter–element extension model is appropriately introduced to dynamically evaluate the WRMP level of the provinces (cities) in the YREB from 2012 to 2021, and Arcgis is used to analyze the spatial and temporal variations in the performance level of each sub-system. Lastly, a geographical detector model is used to explore the main factors influencing the WRMP in the Yangtze River Economic Balt (YREB). The main findings are as follows: (1) The overall provincial WRMP level in the YREB has been improving from 2012 to 2021, and the performance of water resource utilization (WRU) and water environment treatment (WET) are high in the east and low in the west, while the performance of water ecological protection (WEP) shows a trend of continuous improvement. (2) Compared with the model without variable weight modification, the game variable weight matter–element extension model can reflect the influence of the measured value of the index on the evaluation result as much as possible. (3) The top eight factors that have a greater impact on the WRMP level are the industrial water conservation rate, water resource development and utilization rate, water resource sustainability index, sewage diameter ratio, urban water penetration rate, industrial wastewater treatment completion rate, ecological construction and protection of the year to complete the investment in GDP, and the water ecological carrying capacity growth rate. The interaction types of each influence factor are nonlinear enhancement and two-factor enhancement. [ABSTRACT FROM AUTHOR]

A clear understanding of the number of pigs plays a crucial role in breeding management. Computer vision technology possesses several advantages, as it is harmless and labour-saving compared to traditional counting methods. Nevertheless, the existing methods still face some challenges, such as: (1) the lack of a substantial high-precision pig-counting dataset; (2) creating a dataset for instance segmentation can be time-consuming and labor-intensive; (3) interactive occlusion and overlapping always lead to incorrect recognition of pigs; (4) existing methods for counting such as object detection have limited accuracy. To address the issues of dataset scarcity and labor-intensive manual labeling, we make a semi-auto instance labeling tool (SAI) to help us to produce a high-precision pig counting dataset named Count1200 including 1220 images and 25,762 instances. The speed at which we make labels far exceeds the speed of manual annotation. A concise and efficient instance segmentation model built upon several novel modules, referred to as the Instances Counting Network (ICNet), is proposed in this paper for pig counting. ICNet is a dual-branch model ingeniously formed of a combination of several layers, which is named the Parallel Deformable Convolutions Layer (PDCL), which is trained from scratch and primarily composed of a couple of parallel deformable convolution blocks (PDCBs). We effectively leverage the characteristic of modeling long-range sequences to build our basic block and compute layer. Along with the benefits of a large effective receptive field, PDCL achieves a better performance for multi-scale objects. In the trade-off between computational resources and performance, ICNet demonstrates excellent performance and surpasses other models in Count1200, A P of 71.4% and A P 50 of 95.7% are obtained in our experiments. This work provides inspiration for the rapid creation of high-precision datasets and proposes an accurate approach to pig counting. [ABSTRACT FROM AUTHOR]

Background: This study explores the association between chronotypes and adolescent health risk behaviors (HRBs) by testing how genetic background moderates these associations and clarifies the influence of chronotypes and polygenic risk score (PRS) on adolescent HRBs. Methods: Using VOS-viewer software to select the corresponding data, this study used knowledge domain mapping to identify and develop the research direction with respect to adolescent risk factor type. Next, DNA samples from 264 students were collected for low-depth whole-genome sequencing. The sequencing detected HRB risk loci, 49 single nucleotide polymorphisms based to significant SNP. Subsequently, PRSs were assessed and divided into low, moderate, and high genetic risk according to the tertiles and chronotypes and interaction models were constructed to evaluate the association of interaction effect and clustering of adolescent HRBs. The chronotypes and the association between CLOCK-PRS and HRBs were examined to explore the association between chronotypes and mental health and circadian CLOCK-PRS and HRBs. Results: Four prominent areas were displayed by clustering information fields in network and density visualization modes in VOS-viewer. The total score of evening chronotypes correlated with high-level clustering of HRBs in adolescents, co-occurrence, and mental health, and the difference was statistically significant. After controlling covariates, the results remained consistent. Three-way interactions between chronotype, age, and mental health were observed, and the differences were statistically significant. CLOCK-PRS was constructed to identify genetic susceptibility to the clustering of HRBs. The interaction of evening chronotypes and high genetic risk CLOCK-PRS was positively correlated with high-level clustering of HRBs and HRB co-occurrence in adolescents, and the difference was statistically significant. The interaction between the sub-dimensions of evening chronotypes and the high genetic CLOCK-PRS risk correlated with the outcome of the clustering of HRBs and HRB co-occurrence. Conclusions: The interaction of PRS and chronotype and the HRBs in adolescents appear to have an association, and the three-way interaction between the CLOCK-PRS, chronotype, and mental health plays important roles for HRBs in adolescents. [ABSTRACT FROM AUTHOR]

Behavior is one of the important factors reflecting the health status of dairy cows, and when dairy cows encounter health problems, they exhibit different behavioral characteristics. Therefore, identifying dairy cow behavior not only helps in assessing their physiological health and disease treatment but also improves cow welfare, which is very important for the development of animal husbandry. The method of relying on human eyes to observe the behavior of dairy cows has problems such as high labor costs, high labor intensity, and high fatigue rates. Therefore, it is necessary to explore more effective technical means to identify cow behaviors more quickly and accurately and improve the intelligence level of dairy cow farming. Automatic recognition of dairy cow behavior has become a key technology for diagnosing dairy cow diseases, improving farm economic benefits and reducing animal elimination rates. Recently, deep learning for automated dairy cow behavior identification has become a research focus. However, in complex farming environments, dairy cow behaviors are characterized by multiscale features due to large scenes and long data collection distances. Traditional behavior recognition models cannot accurately recognize similar behavior features of dairy cows, such as those with similar visual characteristics, i.e., standing and walking. The behavior recognition method based on 3D convolution solves the problem of small visual feature differences in behavior recognition. However, due to the large number of model parameters, long inference time, and simple data background, it cannot meet the demand for real-time recognition of dairy cow behaviors in complex breeding environments. To address this, we developed an effective yet lightweight model for fast and accurate dairy cow behavior feature learning from video data. We focused on four common behaviors: standing, walking, lying, and mounting. We recorded videos of dairy cow behaviors at a dairy farm containing over one hundred cows using surveillance cameras. A robust model was built using a complex background dataset. We proposed a two-pathway X3DFast model based on spatiotemporal behavior features. The X3D and fast pathways were laterally connected to integrate spatial and temporal features. The X3D pathway extracted spatial features. The fast pathway with R(2 + 1)D convolution decomposed spatiotemporal features and transferred effective spatial features to the X3D pathway. An action model further enhanced X3D spatial modeling. Experiments showed that X3DFast achieved 98.49% top-1 accuracy, outperforming similar methods in identifying the four behaviors. The method we proposed can effectively identify similar dairy cow behaviors while improving inference speed, providing technical support for subsequent dairy cow behavior recognition and daily behavior statistics. [ABSTRACT FROM AUTHOR]

Animal resources are significant to human survival and development and the ecosystem balance. Automated multi-animal object detection is critical in animal research and conservation and ecosystem monitoring. The objective is to design a model that mitigates the challenges posed by the large number of parameters and computations in existing animal object detection methods. We developed a backbone network with enhanced representative capabilities to pursue this goal. This network combines the foundational structure of the Transformer model with the Large Selective Kernel (LSK) module, known for its wide receptive field. To further reduce the number of parameters and computations, we incorporated a channel pruning technique based on Fisher information to eliminate channels of lower importance. With the help of the advantages of the above designs, a real-time animal object detection model based on a Large Selective Kernel and channel pruning (RTAD) was built. The model was evaluated using a public animal dataset, AP-10K, which included 50 annotated categories. The results demonstrated that our model has almost half the parameters of YOLOv8-s yet surpasses it by 6.2 A P . Our model provides a new solution for real-time animal object detection. [ABSTRACT FROM AUTHOR]

Feature selection is crucial in classification tasks as it helps to extract relevant information while reducing redundancy. This paper presents a novel method that considers both instance and label correlation. By employing the least squares method, we calculate the linear relationship between each feature and the target variable, resulting in correlation coefficients. Features with high correlation coefficients are selected. Compared to traditional methods, our approach offers two advantages. Firstly, it effectively selects features highly correlated with the target variable from a large feature set, reducing data dimensionality and improving analysis and modeling efficiency. Secondly, our method considers label correlation between features, enhancing the accuracy of selected features and subsequent model performance. Experimental results on three datasets demonstrate the effectiveness of our method in selecting features with high correlation coefficients, leading to superior model performance. Notably, our approach achieves a minimum accuracy improvement of 3.2% for the advanced classifier, lightGBM, surpassing other feature selection methods. In summary, our proposed method, based on instance and label correlation, presents a suitable solution for classification problems. [ABSTRACT FROM AUTHOR]

The artificial freezing method can effectively improve the stability of strata and provide favorable conditions for the construction safety of shield tunnel in water-rich strata. Based on the frozen shield tunneling project of a metro station, which is close to important buildings, a reasonable freezing method and parameters are proposed in this paper. The simulation model was established by using Plaxis 3D finite element software (Version 2017). The numerical model was verified based on a large amount of field data. The characteristics of segment deformation, ground surface settlement and vertical displacement of buildings were compared between frozen layer and nonfrozen layer during shield tunnel excavation. It was found that segment deformation in the nonfrozen layer is three times that in the frozen layer. The surface settlement above the frozen layer is less than 2 mm. Expansion excavation of shield tunnel was carried out to meet the space function of subway station using artificial freezing method. The deformation of frozen layer was compared between full section excavation and partial excavation. It was found that the deformation of the former is 4.5 times that of the latter, so the partial excavation was chosen as the main research object. Subsequently, the characteristics of vertical displacement and surface settlement of buildings under partial excavation were studied. It was found that the vertical settlement of buildings away from the frozen layer is greater than that of buildings near the frozen layer. All settlement values meet the requirements, thus ensuring the feasibility of partial excavation and ensuring the safety of construction. [ABSTRACT FROM AUTHOR]

Existing deep learning methods usually adopt deeper and wider network structures to achieve better performance. However, we found that this rule does not apply well to crop disease identification tasks, which inspired us to rethink the design paradigm of disease identification models. Crop diseases belong to fine-grained features and lack obvious patterns. Deeper and wider network structures will cause information loss of features, which will damage identification efficiency. Based on this, this paper designs a very lightweight disease identification network called VLDNet. The basic module VLDBlock of VLDNet extracts intrinsic features through 1 × 1 convolution, and uses cheap linear operations to supplement redundant features to improve feature extraction efficiency. In inference, reparameterization technology is used to further reduce the model size and improve inference speed. VLDNet achieves state-of-the-art model (SOTA) latency-accuracy trade-offs on self-built and public datasets, such as equivalent performance to Swin-Tiny with a parameter size of 0.097 MB and 0.04 G floating point operations (FLOPs), while reducing parameter size and FLOPs by 297 times and 111 times, respectively. In actual testing, VLDNet can recognize 221 images per second, which is far superior to similar accuracy models. This work is expected to further promote the application of deep learning-based crop disease identification methods in practical production. [ABSTRACT FROM AUTHOR]

In order to alleviate the structural vibrations induced by traffic loads, in this paper, a phonon crystal plate with functionally graded materials is designed based on local resonance theory. The vibration damping performance of the phonon crystal plate is studied via finite element numerical simulation and the band gap is verified via vibration transmission response analysis. Finally, the engineering application mode is simulated to make it have practical engineering application value. The results show that the phonon crystal plate has two complete bandgaps within 0~150 Hz, the initial bandgap frequency is 0.00 Hz, the cut-off frequency is 128.32 Hz, and the internal ratio of 0~100 Hz is 94.13%, which can effectively reduce the structural vibration caused by traffic loads. Finally, stress analysis of the phonon crystal plate is carried out. The results show that phonon crystals of functionally graded materials can reduce stress concentration through adjusting the band gap. The phonon crystal plate designed in this paper can effectively suppress the structural vibration caused by traffic loads, provides a new method for the vibration reduction of traffic infrastructure, and can be applied to the vibration reduction of bridges and their auxiliary facilities. [ABSTRACT FROM AUTHOR]

Simple Summary: The use of computer vision technology has improved the effectiveness of individual sheep identification, but existing methods face challenges such as large parameter sizes, slow recognition speeds, and difficult deployment. To address this issue, we have made improvements and optimizations based on the Retinaface face recognition model to create a balanced speed-accuracy sheep face recognition model. The optimized model has fewer parameters, simpler computations, faster inference speeds, and higher recognition accuracy, making it well-suited for deployment on resource-constrained edge devices. This research is expected to promote the application of deep learning-based sheep face recognition methods in production. The recognition of sheep faces based on computer vision has improved the efficiency and effectiveness of individual sheep identification, providing technical support for the development of smart farming. However, current recognition models have problems such as large parameter sizes, slow recognition speed, and difficult deployment. Therefore, this paper proposes an efficient and fast basic module called Eblock and uses it to build a lightweight sheep face recognition model called SheepFaceNet, which achieves the best balance between speed and accuracy. SheepFaceNet includes two modules: SheepFaceNetDet for detection and SheepFaceNetRec for recognition. SheepFaceNetDet uses Eblock to construct the backbone network to enhance feature extraction capability and efficiency, designs a bidirectional FPN layer (BiFPN) to enhance geometric location ability, and optimizes the network structure, which affects inference speed, to achieve fast and accurate sheep face detection. SheepFaceNetRec uses Eblock to construct the feature extraction network, uses ECA channel attention to improve the effectiveness of feature extraction, and uses multi-scale feature fusion to achieve fast and accurate sheep face recognition. On our self-built sheep face dataset, SheepFaceNet recognized 387 sheep face images per second with an accuracy rate of 97.75%, achieving an advanced balance between speed and accuracy. This research is expected to further promote the application of deep-learning-based sheep face recognition methods in production. [ABSTRACT FROM AUTHOR]

Background: Health risk behaviors (HRBs) is a kind of phenomenon behavior that often occurs in adolescence, and also often appears in clusters. Previous studies suggested an association between social ecological risk factors (SERFs) and HRBs. This study explored 1) whether chronotype moderates the risk of HRBs associated with SERFs and 2) whether mental health is a mediator in this relationship. Methods: Adolescents were recruited from 39 junior or senior schools (three cities, 13 schools per city) using a multistage cluster sampling method conducted between October, 2020 and June, 2021. The Social Ecological System, Morningness–Eveningness Questionnaire, Brief Instrument on Psychological Health Youths, and Youth Risk Behavior Surveillance questionnaires were used to measure the SERFs, chronotype, mental health and HRBs. Latent category analysis was used to explore the clustering mode of HRBs. The primary exposure was SERFs, and the primary outcome was HRBs; chronotype was a moderator, and mental health was a mediator. The multivariable logistic regression model was used to determine the relationship between SERFs and chronotype and mental behavioral health status. Mediation moderate analysis using the PROCESS method was used to explore the relationship between these variables. Sensitivity analysis was conducted to evaluate the robustness of the model. Results: In total, 17,800 individuals were initially enrolled. After excluding 947 individuals with invalid questionnaires, 16,853 participants were finally included in the analysis. The mean age of participants was 15.33 ± 1.08 years. After adjusting for covariates, multivariable logistic regression found that high levels of SERFs (odds ratio [OR] = 10.10, 95% confidence interval [CI]: 8.88–11.43, P < 0.01), intermediate chronotype (OR = 5.24, 95% CI: 4.57–6.01, P < 0.01), and eveningness (OR = 1.83, 95% CI: 1.64–2.05, P < 0.01) were associated with higher HRBs frequency. This study also assessed the interaction between chronotype, SERFs and HRBs (OR = 27.84, 95% CI: 22.03–35.19, P < 0.01) and mental health (OR = 18.46, 95% CI: 13.16–25.88, P < 0.01). The moderated mediation analyses examined the relationship between chronotype, SERFs, mental health and HRBs. Conclusions: SERFs may be important variables in measuring the effect of the adolescent psychosocial environment on HRBs; this effect is mediated by mental health and moderated by chronotype. [ABSTRACT FROM AUTHOR]

Xu, Z.; Zhao, J.; Li, S., and Shan, J., 2023. Investigating resident participation in pro-environmental behaviors (PEBs) for marine protection in coastal China. Journal of Coastal Research, 39(3), 455–470. Charlotte (North Carolina), ISSN 0749-0208. Marine environments are currently faced with unprecedented challenges of marine pollution and ecological destruction in China. A good marine environment is inseparable from individual's pro-environmental behaviors. This study investigates residents' willingness to perform four types of pro-environmental behaviors in marine environmental protection in Qingdao, China. The results indicate that most respondents express a strong willingness to protect marine environment. However, a remarkable discrepancy in residents' preference for different pro-environmental behaviors is observed. Residents hold the strongest participation willingness and the most positive attitudes towards the recycling behaviors. Additionally, this study identifies the determinants of residents' pro-environmental behaviors from the perspective of cultural belief, and focuses on the influences of Chinese pastoral and bureaucratic culture. The findings confirm that cultural belief cannot exert influences on pro-environmental behaviors directly; however, can prompt an individual's pro-environmental behaviors through self-identity, perceived responsibility, and attitudes. This study has important implications for policymakers to take measures to boost the public participation in marine environmental protection. [ABSTRACT FROM AUTHOR]

Objective: To investigate the effects of phillyrin on D-galactose (D-gal)-induced aging in the brain of mice and mechanism. Methods: Institute of Cancer Research mice were intraperitoneally injected with D-gal 150 mg/kg to induce the aging model, and the mice were treated with phillyrin 5, 15, and 45 mg/kg once a day for 8 weeks. Results: The memory impairment induced by D-gal in brain aging was ameliorated by phillyrin treatment, and the oxidative stress in the aging brain and serum was inhibited, as evidenced by increased superoxide dismutase, glutathione peroxidase enzyme activities, and decreased malondialdehyde levels. Additionally, the hippocampus damage has also been well improved by phillyrin. Moreover, the protein expressions of nuclear factor erythroid-2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), and NADPH quinone oxidoreductase 1 (NQO1) were markedly up-regulated and the expression of Keap-1 was down-regulated in the phillyrin group than that in the aging model group. Conclusion: These findings suggest that phillyrin is effective in the prevention of age-related memory impairment, and the attenuation oxidative stress by activating the Nrf2/HO-1 signaling pathway in the hippocampus may be one of the mechanisms. [ABSTRACT FROM AUTHOR]

Background: Childhood maltreatment and problematic mobile phone use are risk factors for depression and anxiety symptoms among college students. However, how the interaction between the two factors affects depression and anxiety has yet to be validated. This study aimed to investigate the independent and interaction effects of childhood maltreatment and problematic mobile phone use on depression and anxiety among college students and explored gender-based differences in these associations. Method: A cross-sectional study was conducted from October to December 2019. We collected data from 7623 students at two colleges in Hefei and Anqing cities in Anhui Province, China. Multinomial logistic regression models were performed to explore the associations of childhood maltreatment and problematic mobile phone use with depression and anxiety symptoms and their interaction effects on depression and anxiety symptoms. Results: Childhood maltreatment and problematic mobile phone use were significantly associated with increased risk of depression and anxiety symptoms (P < 0.001). Moreover, following adjustments for covariates, there was a multiplicative interaction between childhood maltreatment and problematic mobile phone use on depression and anxiety symptoms (P < 0.001). Gender-based differences were also observed in the associations. For instance, depression was more common in males and male students with childhood maltreatment were at higher risk of depression-only symptoms. Conclusion: Focusing on childhood maltreatment and problematic mobile phone use could facilitate a reduction in the occurrence of depression and anxiety symptoms in college students. Furthermore, it is necessary to develop gender-targeted intervention strategies. [ABSTRACT FROM AUTHOR]

Garlic (Allium sativa L.) is a traditional plant with antimicrobial activity. This study aimed to discover new antifungal peptides from garlic, identify their structure, and explore the antimicrobial mechanism. Peptides were separated by chromatography and identified by MALDI-TOF analysis. Structure and conformation were characterized by CD spectrum and NMR analysis. Mechanism studies were conducted by SEM, membrane depolarization, and transcriptomic analysis. The cytotoxicity to mammalian cells as well as drug resistance development ability were also evaluated. A novel antifungal peptide named NpRS with nine amino acids (RSLNLLMFR) was obtained. It was a kind of cationic peptide with a α-helix as the dominant conformation. NOESY correlation revealed a cyclization in the molecule. The peptide significantly inhibited the growth of Candida albicans. The mechanism study indicated that membrane destruction and the interference of ribosome-related pathways might be the main mechanisms of antifungal effects. In addition, the resistance gene CDR1 for azole was down-regulated and the drug resistance was hardly developed in 21 days by the serial passage study. The present study identified a novel antifungal garlic peptide with low toxicity and provided new mechanism information for the peptide at the gene expression level to counter drug resistance. [ABSTRACT FROM AUTHOR]

In order to deal with the problems of resource waste and environmental pollution caused by solid waste, iron tailings (mainly SiO2, Al2O3 and Fe2O3) were used as the main raw material to create a type of lightweight and high-strength ceramsite. Iron tailings, dolomite (industrial grade, purity 98%) and a small amount of clay were combined in a N2 atmosphere at 1150 °C. X-ray fluorescence spectrometry (XRF), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and a themogravimetric analysis (TGA) were performed and the specific surface area was analyzed to determine the strength and adsorption of the ceramsite. The results of the XRF showed that SiO2, CaO and Al2O3 were the main components of the ceramsite, with MgO and Fe2O3 also included. The results of the XRD and SEM-EDS showed that the ceramsite contained several kinds of minerals and was mainly composed of akermanite, gehlenite and diopside, and that the morphology of the internal structure of the ceramsite was mainly massive and contained a small number of particles. The ceramsite could be used in engineering practice to improve the mechanical properties of materials and meet the requirements of actual engineering for the strength of materials. The results of the specific surface area analysis showed that the inner structure of the ceramsite was compact and that there were no large voids. The voids were mainly medium and large, with a high stability and strong adsorption ability. The TGA results showed that the quality of the ceramsite samples will continue to increase within a certain range. According to the XRD experimental results and experimental conditions, it was speculated that in the part of the ore phase containing Al, Mg or Ca in the ceramsite, the elements underwent relatively complex chemical reactions with each other, resulting in the formation of an ore phase with a higher molecular weight. This research provides the basis of characterization and analysis for the preparation of high-adsorption ceramsite from iron tailings and promotes the high-value utilization of iron tailings for waste pollution control. [ABSTRACT FROM AUTHOR]

Microsatellite instability (MSI), a vital mutator phenotype caused by DNA mismatch repair deficiency, is frequently observed in several tumors. MSI is recognized as a critical molecular biomarker for diagnosis, prognosis, and therapeutic selection in several cancers. Identifying MSI status for current gold standard methods based on experimental analysis is laborious, time-consuming, and costly. Although several computational methods based on machine learning have been proposed to identify MSI status, we need to further understand which machine learning model would favor identification for MSI and which feature subset is strongly related to MSI. On this basis, more effective machine learning-based methods can be developed to improve the performance of MSI status identification. In this work, we present MSINGB, an NGBoost-based method for identifying MSI status from tumor somatic mutation annotation data. MSINGB first evaluates the prediction performance of 11 popular machine learning algorithms and 9 deep learning models to identify MSI. Among 20 models, NGBoost, a novel natural gradient boosting method, achieves the overall best performance. MSINGB then introduces two feature selection strategies to find the compact feature subset, which is strongly related to MSI, and employs the SHAP approach to interpreting how selected features impact the model prediction. MSINGB achieves a better prediction performance on both the tenfold cross-validation test and independent test compared with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Photocatalytic antibacterial approach shows great potential in treating multidrug-resistant bacterial infections. However, the bactericidal efficiency heavily depends on the photocatalytic activity of semiconductor materials, which is limited by the fast recombination of photogenerated electron-hole pairs. Janus nano-heterostructures with spatial control growth of TiO2 nanoparticles (NPs) at one end of gold nanorods (Au NRs) are designed via surface ligand regulation for photocatalytic sterilization and infected wound healing. The asymmetric nanostructure of Janus gold nanorod-titanium dioxide nanoparticles (Janus AuNR-TiO2 NPs) promotes the directional migration of charge carriers and is more conducive to the spatial separation of electron—hole pairs. Moreover, the injection of hot electrons and enhancement of plasmon near-fields from the surface plasmon resonance (SPR) effect further improve the photocatalytic efficiency of Janus AuNR-TiO2 NPs. Under simulated sunlight irradiation, large amounts of reactive oxygen species (ROS) are generated for photocatalytic antibacterial activity. Enhanced bactericidal efficiency up to 99.99% against methicillin-resistant Staphylococcus aureus (MRSA) is achieved in vitro. Furthermore, Janus AuNR-TiO2 NPs exhibit superior biocompatibility, structural stability, and also remarkably accelerate MRSA-infected wound healing. Taking the above all into consideration, Janus AuNR-TiO2 NPs, as an efficient antibacterial photocatalyst, offers a promising strategy for MRSA infectious therapy. [ABSTRACT FROM AUTHOR]

Background: Ovarian tumors (OTs) are common gynecological tumors in women. It is very important to correctly distinguish benign and malignant OTs. Purpose: To assess the diagnostic performance of the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) and evaluate the clinical value of O-RADS combined with serum carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) in differentiating benign from malignant OTs. Material and Methods: A retrospective analysis was performed on 431 cases including pathology and clinical data. The receiver operating characteristic (ROC) curve was drawn, and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. Results: In premenopausal women, O-RADS and O-RADS combined with serum CA125 and HE4 showed sensitivity at 92.2% and 94.8%, specificity at 91.8% and 93.4%, and accuracy at 91.9% and 93.8%, respectively. In postmenopausal women, the sensitivity of O-RADS, O-RADS combined with serum CA125 and HE4 was 94.8% and 95.8%, specificity was 83.9% and 93.6%, and accuracy was 90.5% and 95.6%, respectively. The sensitivity, specificity, and accuracy of O-RADS combined with CA125 and HE4 in premenopausal and postmenopausal women were higher than that of O-RADS (P <0.05). Conclusion: O-RADS has high diagnostic performance in OTs. When O-RADS is combined with CA125 and HE4 in the diagnosis of OTs, the sensitivity and specificity are improved, which is helpful to improve the diagnostic efficiency of OTs and has high clinical application value. [ABSTRACT FROM AUTHOR]

Environmental disclosure has gained momentum in the past decades due to increasing pressure from different stakeholders, especially in Chinese practice. In the background, previous research focused on the financial performance of environmental information disclosure, and little literature discussed the nexus between environmental information disclosure and environmental costs. The paper made an initial attempt to link environmental disclosure to different aspects of environmental costs (i.e., quality, enterprise size, market orientation, and ownership) based on 234 listed enterprises of heavy pollution industry from Shanghai and Shenzhen A-shares in China from 2013 to 2017. The results showed the following: (i) Environmental information disclosure increased environmental costs in the short term, but the long-term effects were not significant; (ii) Enterprise size could weaken the positive impact of environmental information disclosure on environmental costs; (iii) marketization disrupted the positive link between environmental information disclosure and environmental costs; (iv) Enterprise ownership (state-owned vs. private) had an insignificant effect on the environmental information disclosure and environmental costs nexus. This study could identify the causes of inertia in environmental information disclosure from the perspective of environmental costs, so as to provide practical guidance for activating the initiative of corporate environmental information disclosure. [ABSTRACT FROM AUTHOR]

Garlic (Allium sativum L.) is a type of agricultural product that is widely used as a food spice, herb and traditional medicine. White garlic (WG) can be processed into several kinds of products, such as green garlic (GG), Laba garlic (LAG) and black garlic (BG), which have multiple health effects. In this study, GC-MS (gas chromatography-mass spectrometry), DPPH (1,1′-diphenyl-2-propionyl hydrazide) radical scavenging, hydroxyl radical scavenging and MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) in vitro assays were used to compare the composition, antioxidant and antiproliferation effects of different processed garlic extracts. The relationship between the constituents and the bioactivities was analyzed using the principal components analysis (PCA) and heatmap analysis. BG showed the highest antioxidant activity (IC50 = 0.63 ± 0.02 mg/mL) in DPPH radical assays and the highest antioxidant activity (IC50 = 0.80 ± 0.01 mg/mL) by hydroxyl radical assay. Moreover, GC-MS results showed that 12 organosulfur compounds were detected in the extracts of four garlic products, and allyl methyl trisulfide showed a positive relation with the anticancer activity on SMMC-7721 cells (hepatocellular carcinoma cells). The results suggested that the processing of garlic had a significant influence on the constituents and antioxidant effects and that GG, LAG and BG might be better candidates for the related functional food products compared to WG. [ABSTRACT FROM AUTHOR]

Objective. To propose a new dynamic multiparametric magnetic resonance imaging (mpMRI) radiomics method for the detection of prostate cancer (PCa), and establish a combined model using dynamic and static radiomics features based on this method. Approach. A total of 166 patients (82 PCa patients and 84 non-PCa patients) were enrolled in the study, and 31 872 mpMRI images were performed in a radiomics workflow. The whole prostate segmentation and traditional static radiomics features extraction were performed on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI, b value of 10, 50, 100, 150, 200, 400, 600, 800, 1000, 1500 s mm−2 respectively), apparent diffusion coefficient (ADC), and T2-weighted imaging (T2WI) sequences respectively. Through the building of each b -value DWI model and the analysis of the static key radiomics features, three types of dynamic features called standard discrete (SD), parameter (P) and relative change rate (RCR) were constructed. And the b-value parameters used to construct dynamic features were divided into three groups ('Df_', 'Db_' and 'Da_'): the front part (10–200 s mm−2), the back part (400–1500 s mm−2), and all (10–1500 s mm−2) of the b -values set, respectively. Afterwards, the dynamic mpMRI model and combined model construction were constructed, and the PCa discrimination performance of each model was evaluated. Main results. The models based on dynamic features showed good potential for PCa identification. Where, the results of Db_SD, Da_P and Db_P models were encouraging (test cohort AUCs: 90.78%, 87.60%, 86.3%), which was better than the commonly used ADC model (AUC of ADC was 75.48%). Among the combined models, the models using static features of T2WI and dynamic features performed the best. The AUC of Db_SD + T2WI, Db_P + T2WI and Db_RCR + T2WI model was 92.90%, 91.29% and 81.46%. Significance. The dynamic-static combination model based on dynamic mpMRI radiomics method has a good effect on the identification of PCa. This method has broad application prospects in PCa individual diagnosis management. [ABSTRACT FROM AUTHOR]

Background: Serum lipid management is an important health management goal for breast cancer patients with endocrine therapy, and serum lipid knowledge is a substantial factor influencing patients' serum lipid management behavior. The aim of this study was to explore the relationship between family support, serum lipid knowledge and quality of life in breast cancer women with endocrine therapy. Methods: Through convenience sampling, 301 women who had been treated in the First Affiliated Hospital of China Medical University and Liaoning Cancer Hospital were selected to fill in the questionnaire of knowledge-attitude-practice (KAP) on serum lipids, family support questionnaire (FSQ), and the functional assessment of cancer therapy-breast cancer (FACT-B). Pearson correlation coefficient was used to analyze the correlation between the three. Multiple linear regression model was used to analyze the influencing factors of quality of life in breast cancer patients with endocrine therapy. Results: The average score of KAP on serum lipids was 42.62 ± 7.333, the average score of family support was 12.55 ± 2.390, and the average score of quality of life was 97.13 ± 21.347, all above the medium level. Family support of breast cancer women with endocrine therapy was positively correlated with serum lipid knowledge and quality of life. Disease stage, family support, and serum lipid knowledge were the influencing factors of quality of life of breast cancer women with endocrine therapy. Conclusion: Good family support is associated with better serum lipid knowledge in breast cancer women with endocrine therapy. Therefore, interventions that aim to improve the level of family support may be one way to improve the knowledge level of serum lipid, prevent cardiovascular and cerebrovascular diseases, and improve the quality of life. [ABSTRACT FROM AUTHOR]

Investigations have found maternal adverse childhood experiences (ACEs) cause an intergenerational danger to their children's health. However, no study has investigated the effects of maternal ACEs on behavioral problems of preschool children in China and gender differences on these effects. This paper aims to investigate the role of maternal ACEs on behavioral problems of preschool children in China and explore gender differences as related to these behavioral problems. Stratified cluster sampling method was used to select 7318 preschool children from 12 districts in Hefei city, China. A questionnaire survey was conducted to collect information on maternal exposure to ACEs and Conners' Parent Rating Scales. Logistic regression was used to analyze the relationship between maternal ACEs and children's behavioral problems. The prevalence of behavioral problems in preschool children was 16.0%, while it was higher among girls (18.4%) than boys (13.92%) (χ2 = 27.979, p < 0.001). The rate of behavioral problems in children in the group of mothers with ACEs was higher than those without ACEs (all p < 0.05). Maternal ACEs were associated with increased risk of the behavior problems in preschool children (adjusted OR 2.91, 95% CI 2.45–3.45), and no gender difference (in girls 3.01, 2.38–3.81, in boys 2.79, 2.17–3.58, respectively) was found. Maternal ACEs were associated with increased risk of each type of the behavioral problems of preschool children, except that maternal emotional neglect was not associated with psycho-physical problems, impulse-activities, and anxiety. The only gender differences found were higher conduct problems related to maternal emotional abuse and ACEs and higher anxiety related to maternal physical abuse and community violence in girls compared with boys. Mothers exposured to ACEs are more likely to have children with behavioral health problems in preschool period. Further research is needed to explore the mechanisms by which maternal ACEs influence children's behavioral problems. [ABSTRACT FROM AUTHOR]

The microorganisms in the water sources are closely related to drip irrigation emitter clogging and clogging substances accumulation. However, few studies quantitatively considered the role of microorganisms in the emitter clogging process, especially in the high-sediment water source. The coupling process and mechanism between solid particles and microorganisms are not clear yet. Based on these, the Yellow River water (CK), general high sediment water (GHS) and artificial simulated Yellow River water (SYR) was applied in an indoor controllable experiment to study the long-term dynamic drip irrigation emitter clogging process, microorganism growth and its secretions as well as clogging substances accumulation. The results showed that the presence of microorganisms could accelerate the clogging process, with smaller discharge ratio variation (Dra) and Christiansen coefficient of uniformity (CU), and higher accumulation of clogging substances. Among them, the Dra and CU of the SYR treatment were the smallest at the end of the experiment (14.7% and 30.5%, respectively) and those of the GHS treatment were the largest (21.2% and 33.9%, respectively). Meanwhile, the total amounts of phospholipid fatty acids (PLFAs), extracellular polymer substances (EPS) and dry weight (DW) in SYR treatment were the highest, which were 110.2%, 23.8% and 16.7% higher than those in GHS treatment, respectively. The clogging parameters and clogging substances accumulated from the CK treatment were in a state of in-betweenness. However, the differences between CK and SYR treatments did not reach a significant level, while they were both significantly different from GHS treatment (p < 0.05). This mainly resulted from the interactions between solid particles and microorganisms in the drip irrigation emitter clogging process. Ignoring the existence of microorganisms may overestimate the Dra and CU by 6.5% and 3.4%, respectively. This offered theoretical references to the application of high-sediment water in the drip irrigation system. [ABSTRACT FROM AUTHOR]

This study aimed to examine the association between childhood maltreatment, parent-child relationship quality with psychological symptoms and to explore the moderating role of parent-child relationship quality in the association between childhood maltreatment and psychological symptoms among adolescents. It also probed to the role of gender differences in this effect. A representative sample of 14,500 middle school students in China were asked to complete a standard questionnaire on the details of childhood maltreatment, parent-child relationship quality, and psychological symptoms. All data were analyzed using SPSS 23.0. The PROCESS program was used to analyze whether parent-child relationship quality moderated the link between childhood maltreatment and psychological symptoms. The analyses revealed significant correlations between childhood maltreatment, parent-child relationship quality, and psychological symptoms (p <.001). Specifically, paternal relationship quality moderated the association between childhood maltreatment and psychological symptoms in the total sample (B = –0.01, p <.05) and the subgroup of girls (B = –0.01, p <.05), while maternal relationship quality moderated only the association between childhood maltreatment and psychological symptoms in the subgroup of boys (B = –0.01, p <.05). As the findings indicate, priority should be given to the quality of parent-child relationship and gender-specific methods employed to effectively reduce the psychological symptoms of adolescents with a history of childhood maltreatment. [ABSTRACT FROM AUTHOR]

Background: Blended learning programs in Kindergarten through Grade 12 (K‐12) classrooms are growing in popularity; however, previous studies assessing their effects have yielded inconsistent results. Further, their effects have not been completely quantitatively synthesized and evaluated. Objectives: The purpose of this study is to synthesize the overall effects of blended learning on K‐12 student performance, distinguish the most effective domains of learning outcomes, and examine the moderators of the overall effects. Methods: For the purpose, this study conducted a meta‐analysis of 84 studies published between 2000 and 2020, and involved 30,377 K‐12 students. Results and Conclusions: Results revealed that blended learning can significantly improve K‐12 students' overall performance [g = 0.65, p < 0.001, 95% CI = (0.54–0.77)], particularly in the cognitive domain [g = 0.74, p < 0.001, 95% CI = (0.61–0.88)). The testing of moderators indicates that the factors moderating the impact of blended learning on student performance in these studies included group activities, educational level, subject, knowledge type, instructor, sample size, intervention duration and region. Implications: The results indicate that blended learning is an effective way to improve K‐12 students' performance compared to traditional face‐to‐face (F2F) learning. Additionally, these findings highlight valuable recommendations for future research and practices related to effective blended learning approaches in K‐12 settings. Lay Description: What is already known about this topic: Blended learning is gaining increased popularity in Kindergarten through Grade 12 (K‐12) settings.Studies have resulted in inconsistent conclusions on the effect of blended learning in K‐12 settings.More rigorous, evidence‐based studies on blended learning are needed in K‐12 settings. What this paper adds: Reports the first meta‐analysis on the effects of blended learning on K‐12 student performance compared to traditional face‐to‐face learning.Blended learning significantly improves K‐12 students' overall performance (g = 0.65), particularly in the cognitive domain (g = 0.74).The effect of blended learning is impacted by the group activities, educational level, subject, knowledge type, instructor, sample size, intervention duration and region. Implications for practice and/or policy: Blended learning is an effective instructional strategy in K‐12 settings.Adding group activities can significantly enhance the overall effect of blended learning.Blended learning developers should develop appropriate blended learning courses for different educational levels, subjects and knowledge types. [ABSTRACT FROM AUTHOR]

Ecological compensation policies for the watershed (ECPW) have played a guiding role in establishing a sound watershed ecological compensation system with Chinese characteristics, and the quantitative evaluation of current policies can provide a reference for policy optimization. Firstly, taking 77 ECPW promulgated in China from 2006 to 2020 as the research objects, this paper extracted keyword frequencies using a text mining method, and then selected the policy indicators by combining the policy characteristics and existing results of watershed ecological compensation. Secondly, the Fuzzy analytic hierarchy process was used to determine the weights of the variables and improve the Policy Modeling Consistency Index (PMC-Index). Finally, the empirical analysis was conducted on six typical policies and the differences among P1, P3, and P5 at the three levels of the national, provincial, and municipal levels were further explored and compared. It was found that (1) the consistency evaluation of P1, P2, P3, and P4 were excellent levels, and that of P5 and P6 were acceptable levels. (2) The mean value of an improved PMC-Index of the six strategies was 0.6287, which indicated that the overall performance of the quality of ECPW was good, but still room for improvement. (3) The quality of China's ECPW showed a trend that the higher the level of government, the better the overall performance of the policy. The more targeted the ECPW, the lower the PMC index score, which is manifested in indicators such as incentive measures, policy mechanisms, policy areas, and policy functions. This study helps to fully understand the strengths and weaknesses of China's single ECPW. [ABSTRACT FROM AUTHOR]

Motivation Accurate annotation of different genomic signals and regions (GSRs) from DNA sequences is fundamentally important for understanding gene structure, regulation and function. Numerous efforts have been made to develop machine learning-based predictors for in silico identification of GSRs. However, it remains a great challenge to identify GSRs as the performance of most existing approaches is unsatisfactory. As such, it is highly desirable to develop more accurate computational methods for GSRs prediction. Results In this study, we propose a general deep learning framework termed DeepGenGrep, a general predictor for the systematic identification of multiple different GSRs from genomic DNA sequences. DeepGenGrep leverages the power of hybrid neural networks comprising a three-layer convolutional neural network and a two-layer long short-term memory to effectively learn useful feature representations from sequences. Benchmarking experiments demonstrate that DeepGenGrep outperforms several state-of-the-art approaches on identifying polyadenylation signals, translation initiation sites and splice sites across four eukaryotic species including Homo sapiens , Mus musculus , Bos taurus and Drosophila melanogaster. Overall, DeepGenGrep represents a useful tool for the high-throughput and cost-effective identification of potential GSRs in eukaryotic genomes. Availability and implementation The webserver and source code are freely available at http://bigdata.biocie.cn/deepgengrep/home and Github (https://github.com/wx-cie/DeepGenGrep/). Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]