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Background Diabetes nephropathy (DN) is a common complication of diabetes patients. The prediction and validation of its risk will help identify high-risk patients in advance and take intervention measures to avoid or delay the progress of nephropathy. Objective To analyze the risk factors affecting the complication of DN in patients with type 2 diabetes mellitus (T2DM) , construct a risk prediction model for the risk of DN in T2DM patients and validate it. Methods A total of 5 810 patients with T2DM admitted to the First Affiliated Hospital of Xinjiang Medical University from January 2016 to June 2021 were selected as the study subjects and divided into the DN group (n=481) and non-DN group (n=5 329) according to the complication of DN. A 1∶1 case-control matching was performed on 481 of these DN patients and non-DN patients by gender and age (±2 years) , and the matched 962 T2DM patients were randomly divided into the training group (n=641) and validation group (n=321) based on a 2∶1 ratio. Basic data of patients, such as clinical characteristics, laboratory test results and other related data, were collected. LASSO regression was applied to optimize the screening variables, and a nomogram prediction model was developed using multivariate Logistic regression analysis. The discriminability, calibration and clinical validity of the prediction model were evaluated by using the receiver operating characteristic (ROC) curve, Hosmer-Lemeshow calibration curve, and decision curve analysis (DCA) , respectively. Results There were significant differences in gender, age, BMI, course of diabetes, white blood cell count, total cholesterol, triacylglycerol, low-density lipoprotein cholesterol, serum creatinine, hypertension, systolic blood pressure, diastolic blood pressure, glycosylated hemoglobin, apolipoprotein B, 24-hour urinary micro total protein, qualitative urinary protein between the DN and non-DN group (P

This study aims to explore how the Metaverse platform could be applied to the field of online education, the benefits it brings, and the challenges posed by the application of Metaverse to online education. The study analyzes the benefits of immersive learning brought about by Metaverse and its potential to save education costs, enhance efficiency and students' interest in learning, and explores the application of Metaverse technology in education in relation to the characteristics of online education. The results show that Metaverse technology can support several aspects of online classrooms with realistic senses, personalized teaching models, realistic 3D identities, interactive communication, virtual reality (VR) technology, and gamified learning. This research also presents the problems faced by the Edu-Metaverse, including technology development difficulties, interaction issues, content production, game addiction, privacy, and ethics. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive switching anti-disturbance attitude control scheme based on improved snake optimizer (SO) is proposed for quadrotor attitude control when a quadrotor unmanned aerial vehicle is affected by measurement noise. The adaptive switching disturbance rejection controller (AWDRC) is composed of linear active disturbance rejection control and adaptive switching extended state observer which is used to achieve accurate signals reconstruction performance under measurement noise. Then, the improved SO (ISO) algorithm is developed with quadratic interpolation and comprehensive learning strategies to obtain the optimal parameters of the quadrotor attitude controller. The performance validity of ISO is demonstrated here by experiments on the CEC-2017 and the CEC-2020 benchmark functions with several state-of-the-art meta-heuristic algorithms. Secondly, the proposed ISO-based AWDRC algorithm is used in quadrotor attitude tracking control and compared with three other excellent active disturbance rejection controllers in a comparative experiment, and the experimental results show the effectiveness of the proposal. Finally, the robustness of the proposed method to parameters perturbation of the quadrotor attitude system is analyzed by Monte Carlo experiments. [ABSTRACT FROM AUTHOR]

This study explores how blockchain technology can be applied in the area of training in organizations, the benefits it brings, and the management challenges that blockchain technology raises. By exploring the decentralized, transparent, and intelligent contract nature of blockchain technology, we analyzed the application of blockchain technology to organizational training. The results show that organizations can achieve training resource sharing, supply and demand balancing, training certification, and intelligent contract enforcement based on blockchain technology. However, it also presents potential challenges, mainly regarding engagement across sectors, support from all members, global technology rollout, staff competency, data confidentiality, and return on investment. Case and industry analysis further validates the content of our research and demonstrates the potential and challenges of blockchain technology in the field of organizational training. [ABSTRACT FROM AUTHOR]

Distribution grid network has problems such as long mileage, large scale, complex surrounding environment, and aging of equipment. It is the development trend of power distribution network operation and maintenance to use unmanned aerial vehicles to patrol and combine with image processing technology for intelligent detection of equipment status. Image segmentation is well-known technique for extracting defect regions of equipment from distribution network inspection images. Therefore, this paper proposes an efficient a novel multilevel thresholding segmentation method to improve the fault diagnosis process with an improved weighted mean of vectors optimization (IINFO) algorithm. The IINFO algorithm adopts various measures to improve the optimization results, including Gaussian mutation to increase the local search ability and range of the optimal individual, Cauchy mutation to enhance the global search ability of its vector individual, reflective learning operators to strengthen self-learning and avoid local optimal solutions, and parallel operation to improve the utilization of computational resources. Moreover, two-dimensional Kapur cross-entropy is used as an objective function to solve the multilevel thresholding problem. The proposed method is evaluated using benchmark functions and distribution network inspection image datasets and is compared with 12 other metaheuristic algorithms. The results demonstrate that the proposed method has better performance and a higher ability to find optimal solutions compared to the other algorithms. These findings suggest that our method may be useful in improving the accuracy and efficiency of distribution network inspections and have significant potential for practical applications. [ABSTRACT FROM AUTHOR]

Continuous-flow microfluidic biochips are a type of biochip technology based on microfluidic channels that enable various biological experiments and analyses to be performed on a tiny chip. They have the advantages of a high throughput, high sensitivity, high precision, low cost, and quick response. In the architectural synthesis of continuous-flow microfluidic biochips (CFMBs), prior work has not considered reducing component interconnection requirements, which led to an increase in the number of connection pairs. In this paper, we propose an architectural synthesis flow for continuous-flow microfluidic biochips with connection pair optimization, which includes high-level synthesis, placement, and routing. In the high-level synthesis stage, our method reduces the need for component interconnections, which reduces the number of connection pairs. Our method performs fine-grained binding, ultimately obtaining high-quality binding and scheduling results for flow paths. Based on the high-quality binding results, we propose a port placement strategy based on port correlation and subsequently use a quadratic placer to place the components. During the routing stage, we employ a conflict-aware routing algorithm to generate flow channels to reduce conflicts between liquid transportation tasks. Experimental results on multiple benchmarks demonstrate the effectiveness of our method. Compared with the existing work, the proposed algorithm obtains average reductions of 35.34% in connection pairs, 24.30% in flow channel intersections, 21.71% in total flow channel length, and 18.39% in the execution time of bioassays. [ABSTRACT FROM AUTHOR]

This research focuses on the implementation of youth football policies in China following the 2015 national football reform. It asks the question 'To what extent have contextual and organisational factors facilitated and/or constrained the effective implementation of Chinese youth football policies?' Guided by a critical realist ontology, we conducted 23 semi-structured interviews with key stakeholders involved in the implementation process of the youth football policy including members of the national and local football associations, schools, and professional football clubs. The findings reveal a number of policy conflicts that restricted an effective implementation of the youth football policies. The main conflict lay in the ambiguous intertwinement of two dominant policy coalitions (i.e. sport and education), which consequently led to confusion and conflicts among key implementers in the three pathways. Other factors such as the continuous mismatch of traditional values and beliefs held by actors towards youth football participation, as well as the emphasis on excellence over participation by some actors are also identified as having potentially inhibited effective implementation. This paper contributes to the debate of the positioning of youth sport in an increasingly elite-driven sporting context. It argues that policymakers, implementers, and the overall society, even if they are willing to foster a positive youth sport development, can also generate an adverse effect if they do not work together. [ABSTRACT FROM AUTHOR]

Blockchain technology is anticipated to have a significant impact on human resource management (HRM) in the era of Industry 4.0. This study employs a literature review methodology and examines 42 relevant publications to identify key areas where blockchain technology can be applied in HRM. The findings reveal several crucial applications of Blockchain in HRM. Firstly, blockchain technology can effectively prevent interview fraud and enhance the reliability of the recruitment process. Secondly, it can improve training and certification processes, address pay equity issues, ensure fair performance evaluations, and facilitate employee relations. These applications are vital in enhancing the efficiency and accuracy of HRM practices. However, the study also highlights certain management concerns related to adopting blockchain technology, such as management's commitment, stakeholder collaboration, and data breach risks. Building upon these findings, a comprehensive discussion is initiated, summarising the contributions and critical findings of the research and emphasising the potential advantages of integrating blockchain technology into HRM. Additionally, the study examines the contributions made by existing literature and proposes directions for future research. Finally, a research agenda is put forth to explore the effective implementation of blockchain technology in practical HRM. [ABSTRACT FROM AUTHOR]

The study explores the opportunities and challenges that the cross-border integration of "Metaverse + hotel" brings to visitors and the hospitality industry. The study analyses the engagement differences between Metaverse hotels and traditional online/offline strategies regarding engagement immersion, community interaction, personalization, environmental perception, and participation. Metaverse hotel brings the impact of realistic environmental simulation, personalized service, customer engagement, and consumer follow-up feedback. Further, it brings to the hospitality industry the impact of enhancing organizational performance, co-creating value for stakeholders, influencing customer relationship management, and changing how managers communicate. Finally, Metaverse technology raises challenges of security issues, technical barriers, high costs, and uncertain user needs. [ABSTRACT FROM AUTHOR]

Studies on aspirin's effects on metabolic-associated fatty liver disease (MAFLD) are limited. The aim of this study was to assess the association between aspirin and all-cause and cardiovascular disease (CVD) mortality in individuals with MAFLD. Data were acquired from the National Health And Nutrition Examination Survey (NHANES) III. MAFLD diagnosis was consistent with that of international expert consensus. The independent association between aspirin and all-cause and CVD mortality in participants with MAFLD was evaluated by multiple Cox regression. Stratified analyses and interaction tests were performed to investigate whether covariates modified the association between aspirin and MAFLD mortality. Of 4594 eligible participants, 3,162 (68.83%) never took aspirin (0 times/month), 962 (20.94%) took it occasionally (1–14 times/month) and 470 (10.23%) took it regularly (≥15 times/month). Multiple cox regression showed that aspirin was not associated with overall mortality for MAFLD individuals. Stratified analysis revealed that in middle-aged (45–59 years) participants with MAFLD, occasional aspirin use was associated with low all-cause mortality risk (HR = 0.61, 95% CI = 0.43–0.86), while there was no significant association between aspirin and all-cause mortality among the young or the elderly. We found that the association between aspirin and all-cause MAFLD mortality varies by both age and frequency of administration. More prospective studies are needed to explore aspirin's influence on MALFD mortality. [ABSTRACT FROM AUTHOR]

A phosphorylcholine polymer (poly(MPC–co–BMA–co–TSMA), PMBT) was prepared by free radical polymerization and coated on the surface of the polymethylpentene hollow fiber membrane (PMP–HFM). ATR–FTIR and SEM analyses showed that the PMBT polymer containing phosphorylcholine groups was uniformly coated on the surface of the PMP–HFM. Thermogravimetric analysis showed that the PMBT had the best stability when the molar percentage of MPC monomer in the polymer was 35%. The swelling test and static contact angle test indicated that the coating had excellent hydrophilic properties. The fluorescence test results showed that the coating could resist dissolution with 90% (v/v%) ethanol solution and 1% (w/v%) SDS solution. The PMBT coating was shown to be able to decrease platelet adherence to the surface of the hollow fiber membrane, and lower the risk of blood clotting; it had good blood compatibility in tests of whole blood contact and platelet adhesion. These results show that the PMBT polymer may be coated on the surface of the PMP–HFM, and is helpful for improving the blood compatibility of membrane oxygenation. [ABSTRACT FROM AUTHOR]

Glioblastoma is the most common glioma with high mortality and poor prognosis. Radiation resistance is one of the large challenges in the treatment of glioma. The study aimed to identify whether DNA polymerase ζ affects glioma cell radiosensitivity. The mRNA and protein levels of REV3L and REV7 were examined using quantitative real-time PCR and western blot. After REV3L and REV7 knockdown in a GBM cell line (A172), we assessed cell viability, colonies, apoptosis, and immune escape. The underlying mechanisms were evaluated using western blot and were confirmed using rescue experiments. The results showed that REV3L and REV7 levels were increased in glioma and related to poor survival. γ-ray treatment inhibited cell viability, survival fraction, and immune escape, and induced apoptosis of glioma cells from a GBM cell line, whereas knockdown of REV3L or REV7 enhanced these effects. Mechanically, silencing of REV3L or REV7 inactivated the PI3K/AKT/mTOR pathway. IGF-1 treatment abrogated the effects on cell viability, colonies, and apoptosis induced by REV3L or REV7 knocking down. Taken together, silencing of REV3L and REV7 inhibited radiation resistance via inactivating the PI3K/AKT/mTOR pathway, suggesting that targeting DNA polymerase ζ may be a new strategy to reduce the radiotherapy resistance of glioma. [ABSTRACT FROM AUTHOR]

System-architecture design optimization of flow-based microfluidic biochips has been extensively investigated over the past decade. Most of the prior work, however, is still based on chip architectures with dedicated storage units and this, not only limits the performance of biochips, but also increases their fabrication cost. To overcome this limitation, a distributed channel-storage architecture can be implemented, where fluid samples can be cached temporarily in flow channels instead of using a dedicated storage. This new concept of fluid storage, however, requires a careful arrangement of fluid samples to enable the channels to fulfill the dual functions of transportation and caching. Moreover, to avoid cross-contamination between different fluidic flows, wash operations are necessary to remove the residue left in flow channels. In this article, we formulate the first practical system level design and wash optimization problem for microfluidic biochips with distributed channel storage architecture, considering high-level synthesis, physical design, and wash optimization simultaneously, and present a top-down design flow to solve this problem systematically. Given the protocol of a biochemical application and the corresponding design requirements, our goal is to generate a chip architecture with low fabrication cost. Meanwhile the biochemical application can be executed efficiently with an optimized wash scheme. Experimental results on multiple benchmarks confirm that our approach leads to short completion time of biochemical applications, low chip cost, as well as high wash efficiency. [ABSTRACT FROM AUTHOR]

The pandemic has changed the way people work, and more and more people are choosing to work from home (WFH). Unlike traditional work patterns, this approach has limitations and has had a significant impact on both organizations and individuals. It also brings many challenges to the work of HR practitioners. HR practitioners, as key players in strategic human resource management, need to take advantage of management innovations under the crisis to improve employees' work flexibility and effectively address the impact of working from home. This study aims to address the need for employee skill improvement, psychological stress relief, work-family balance, and company culture reinforcement from an HRM perspective because of the impact of WFH work patterns during the COVID-19 crisis. [ABSTRACT FROM AUTHOR]