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The bridge girder’s aerodynamic configuration substantially governs its aerodynamic loading and wind-induced vibration characteristics. Extensive research has been performed to optimize the configuration of girders and implement aerodynamic measures to enhance the bridge’s wind resistance. In some practical bridge engineering projects, the aerodynamic configuration of the bridge girder is asymmetric. However, studies investigating the aerodynamic properties of asymmetric girders are limited. In this paper, the aerodynamic loading and vibration characteristics of the Π-shaped girders and box girders with asymmetric bikeways are experimentally studied. Through an extensive series of wind tunnel experiments, the static wind loading coefficients, flutter derivatives, vortex-induced vibration (VIV) responses, and the critical flutter velocities are compared across varying wind direction angles (WDAs). The experimental results demonstrate that the asymmetric girder configurations have different characteristics in both the static wind loading coefficient and flutter derivative in different WDAs. The influence of WDAs on the above-mentioned aerodynamic force coefficients of the asymmetric Π-shaped girder is more pronounced than that on the asymmetric box girder. For the asymmetric Π-shaped girder, the heaving VIV responses at a 0° WDA are smaller than those at a 180° WDA, but the torsional VIV responses at a 0° WDA are larger. Experimental results for critical flutter velocities indicate that the flutter performance at a 0° WDA is better than that at a 180° WDA, especially at positive angles of attack (AOAs) for the two types of asymmetric bridge girders.

Background The incidence of atherosclerosis markedly rises following menopause. Our previous findings demonstrated that elevated follicle-stimulating hormone (FSH) levels in postmenopausal women accelerate atherosclerosis progression. Plaque instability, the fundamental pathological factor in acute coronary syndrome, primarily results from vascular embolism due to plaque rupture. Recent evidence highlights that endothelial-to-mesenchymal transition (EndMT) exacerbates plaque instability, although the link between FSH and EndMT has not been fully established. This investigation sought to explore the possible influence of FSH in modulating EndMT. Methods In this study, apolipoprotein E -deficient ( ApoE −/− ) mice served as an atherosclerosis model, while human umbilical vascular endothelial cells (HUVECs) were used as cellular models. Protein levels were assessed through immunochemical techniques, gene expression was quantified via RT-qPCR, and nucleic acid–protein interactions were evaluated using immunoprecipitation. The m6A modification status was determined by MeRIP, and cellular behaviors were analyzed through standard biochemical assays. Results Our results indicate that FSH induces EndMT both in vitro and in vivo. Additional investigation suggested that FSH upregulates the transcription factor Forkhead box protein M1 (FOXM1) at both protein and mRNA levels by enhancing the expression of AlkB homolog 5, RNA demethylase (ALKBH5). FSH reduces m6A modifications on FOXM1 through ALKBH5, leading to increased nascent transcript levels and mRNA stability of FOXM1 . Dual-luciferase reporter assays highlighted cAMP-response element binding protein (CREB)’s essential function in facilitating the FSH-induced upregulation of ALKBH5. Conclusions These findings suggest that FSH promotes ALKBH5 expression, facilitates N 6 -methyladenosine (m6A) demethylation on FOXM1 , and consequently, induces EndMT. This study elucidates the impact of FSH on plaque instability and provides insights into potential strategies to prevent acute coronary syndrome in postmenopausal women. Graphical Abstract

Effective railway freight transportation relies on a well-designed train service network. This paper investigates the train service network design problem at the tactical level for the Chinese railway system. It aims to determine the types of train services to be offered, how many trains of each service are to be dispatched per day (service frequency), and by which train services shipments are to be transported. An integer programming model is proposed to address this problem. The optimization model considers both through train services between nonadjacent yards, and two classes of service between two adjacent yards ( i.e., shuttle train services directly from one yard to its adjacent yard, and local train services that make at least one intermediate stop). The objective of the model is to optimize the transportation of all the shipments with minimal costs. The costs consist of accumulation costs, classification coststrain operation costs, and train travel costs. The NP-hard nature of the problem prevents an exact solution algorithm from finding the optimal solution within a reasonable time, even for small-scale cases. Therefore, an improved genetic algorithm is designed and employed here. To demonstrate the proposed model and the algorithm, a case study on a real-world sub-network in China is carried out. The computational results show that the proposed approach can obtain high-quality solutions with satisfactory speed. Moreover, comparative analysis on a case that assumes all the shuttle train services between any two adjacent yards to be provided without optimization reveals some interesting insights.

At present, most of face super-resolution (SR) networks cannot balance the visual quality and the pixel accuracy. The networks with high objective index values often reconstruct too smooth images, while the networks which can restore texture information often introduce too much high-frequency noise and artifacts. Besides, some face super-resolution networks do not consider the mutual promotion between the extracting face prior knowledge part and the super-resolution reconstruction part. To solve these problems, we propose the double discriminative face super-resolution network (DDFSRNet). We propose a collaborative generator and two discriminators. Specifically, the collaborative generator, including the face super-resolution module (FSRM) and the face alignment module (FAM), can strengthen the reconstruction of facial key components, under the restriction of the perceptual similarity loss, the facial heatmap loss and double generative adversarial loss. We design the feature fusion unit (FFU) in FSRM, which integrates the facial heatmap features and SR features. FFU can use the facial landmarks to correct the face edge shape. Moreover, the double discriminators, including the facial SR discriminator (FSRD) and the facial landmark heatmap discriminator (FLHD), are used to judge whether face SR images and face heatmaps are from real data or generated data, respectively. Experiments show that the perceptual effect of our method is superior to other advanced methods on 4x reconstruction and fit the face high-resolution (HR) images as much as possible.

Magnesium-based hydrogen storage materials have attracted widespread attention due to their natural abundance, high hydrogen storage capacity, and low cost, making them among the most promising solid-state hydrogen storage materials in terms of overall performance. However, a major bottleneck limiting their practical application is the slow hydrogen absorption and desorption kinetics. Hydrogen diffusion, as the rate-determining step in the hydrogen absorption/desorption process, plays a crucial role in understanding and addressing this issue. In this study, classical molecular dynamics simulations were employed to investigate the dynamic diffusion behavior of hydrogen in the interstitial sites of magnesium hydride lattices. Furthermore, the effect of an external electric field on hydrogen diffusion was explored. The results indicate that hydrogen diffusion is dependent not only on temperature but also on hydrogen concentration; the diffusion coefficient increases with rising temperature and decreasing concentration. Non-Arrhenius behavior of hydrogen diffusion in magnesium hydride was also observed. Moreover, the application of an external electric field significantly enhances the hydrogen diffusion rate, thereby improving both kinetic and thermodynamic performance. This study provides deeper insights into the intrinsic mechanisms of hydrogen diffusion and offers valuable guidance for enhancing the hydrogen storage performance of magnesium-based materials, contributing to the effective design of hydrogen storage systems.

The SARS-CoV-2 airborne virus outbreak has once again drawn attention from researchers to the features of viral cross-transmission, particularly the numerous cross-transmissions that took place in hospitals. Autodesk Computational Fluid Dynamics (CFD) is the most widely used simulation software; nevertheless, technical limitations hinder it from effectively reproducing the dispersion and transmission properties of viruses in naturally ventilated rooms under actual conditions. As a result, there is no established way to prevent the spread of viruses across rooms rely only on natural airflow currently. In this thesis, a CFD simulation approach is proposed to investigate the diffusion characteristics of airborne viruses/pollutants in multiple rooms on the same level, considering different window statuses (opening angles). This novel simulation approach combines a window state prediction algorithm and CFD simulation technology. The first approach predicts the window angle based on indoor and outdoor environmental factors obtained from fieldwork measurements. Stepwise polynomial regression has been validated as a novel algorithm that can effectively predict window opening angles. The second approach develops a dynamic CFD model for the target building. The UDF was used to compile dynamic boundary conditions. By combining these two models, more realistic and dynamic characteristics of indoor pollutant dispersion are simulated and extracted. The study found that using this novel CFD simulation framework allows for a relatively accurate description of velocity and concentration fields in naturally ventilated buildings. Specifically, the simulation accuracy for the velocity field is approximately 75%. The accuracy for the concentration field is even higher, with a maximum APE of only 25% and an average prediction accuracy of 97.2%. Furthermore, the study found that if the window opening direction is improperly set, window-opening behavior may lead to severe pollutant dispersion rather than effectively reducing indoor pollutant levels. This study not only clarified the practical application of the window-opening behavior prediction model but also provided a valuable reference for future dynamic CFD simulation studies on buildings with central corridors.

Traditional manual high-altitude operations have problems of safety risks and low efficiency. However, the combination of unmanned aircraft and mechanical arms can improve efficiency and ensure safety. Flight disturbances will affect the precise control of the mechanical arms. This paper proposes a compensation algorithm based on fuzzy PID control to deal with the motion disturbances of the flight platform. Fuzzy PID control combines the advantages of fuzzy control and classical PID control, and can handle the uncertainty and nonlinearity of the system, and real-time compensate for the disturbances of the flight platform. This innovation can solve the problems of accuracy decline and response delay that traditional PID control may encounter when dealing with disturbances or nonlinear systems. According to the deviation data of the end position of the mechanical arm in the simulation results, it can be concluded that after compensation control, the error of the end position is significantly reduced compared with traditional PID control, and the control accuracy reaches within 0.05mm, and the steady-state error is less than 0.1mm after compensation. This research provides technical support for the application of flight mechanical arms in wind turbine group detection, and provides new ideas for the design of control systems for unmanned aircraft platforms carrying mechanical arms. The simulation results show that this control strategy significantly improves the stability and accuracy of the end position of the mechanical arm, especially under the condition of flight platform disturbances, it can effectively maintain the end position of the mechanical arm at the target position.

PurposeThis study aims to examine how implicit distance (cognitive and social) impacts supply chain capabilities, and the roles of information technology (IT) utilization and supply chain flexibility in this process.Design/methodology/approachThe authors designed a conceptual model including the implicit distance, supply chain flexibility, supply chain capability and IT utilization and verified the relationships among variables through a survey that collected data from 104 manufacturing enterprises in China.FindingsThe results show that cognitive and social distances positively and negatively affect supply chain flexibility, respectively. Furthermore, IT utilization strengthens the positive effect of cognitive distance and the negative effect of social distance on supply chain flexibility. Additionally, supply chain flexibility has a positive effect on supply chain capability and mediates the effects of cognitive and social distances on supply chain capability.Practical implicationsEnterprises should prioritize cooperation with different types of partners with whom the enterprises have established good collaborative working experiences. Moreover, if enterprises cooperate with new partners, enterprises should communicate and handle things face to face instead of frequently utilizing IT.Originality/valueThis study links the implicit distance between enterprises with supply chain capability and newly applies social network theory to explain the mechanism. Further, the authors' data confirm the moderating role of IT utilization in this process, supplementing the research on implicit distance. Moreover, this study employs dynamic capability theory to better understand how firms can improve supply chain capabilities.

Traditional villages are the convergence points for rural tourism and cultural heritage, with their uniqueness deriving from their enduring cultural genes. Villagers serve as the continuators of traditional villages, the transmitters of cultural heritage, and active participants in rural tourism, all predisposing villagers to adopt key positions in these areas. However, villager-centered research has not been systematically explored. This gap may be due to the marginalization of villagers in developing rural tourism and cultural heritage, the challenges associated with measuring villager-centered impacts, and the lack of appropriate measurement tools. Therefore, this study aimed to develop a scale to assess the impact of rural tourism on villagers. Using Shangzhuang Village and Guoyu Village in China as case studies, a total of 305 samples were collected. Through construct dimensions, potential item generation, scale purification, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and reliability and validity testing, a villager-centered tourism impact scale was established, encompassing 13 items across three dimensions: economic, social, and cultural. The findings provide a new tool for village leaders, tourism developers, and policymakers to effectively incorporate villagers’ perspectives into rural tourism and heritage preservation efforts, contributing to the sustainable development of traditional villages and their associated tourism.

The therapeutic benefits of targeting follicle-stimulating hormone (FSH) receptor in treatment of ovarian cancer are significant, whereas the role of FSH in ovarian cancer progresses and the underlying mechanism remains to be developed. Tissue microarray of human ovarian cancer, tumor xenograft mouse model, and cell culture were used to investigate the role of FSH in ovarian carcinogenesis. siRNA, lentivirus and inhibitors were used to trigger the inactivation of genes, and plasmids were used to increase transcription of genes. Specifically, pathological characteristic was assessed by histology and immunohistochemistry (IHC), while signaling pathway was studied using western blot, quantitative RT-PCR, and immunofluorescence. Histology and IHC of human normal ovarian and tumor tissue confirmed the association between FSH and Snail in ovarian cancer metastasis. Moreover, in epithelial ovarian cancer cells and xenograft mice, FSH was showed to promote epithelial mesenchymal transition (EMT) progress and metastasis of ovarian cancer via prolonging the half-life of mRNA in a N6-methyladenine methylation (m6A) dependent manner, which was mechanistically through the CREB/ALKBH5 signaling pathway. These findings indicated that FSH induces EMT progression and ovarian cancer metastasis via CREB/ALKBH5/Snail pathway. Thus, this study provided new insight into the therapeutic strategy of ovarian cancer patients with high level of FSH.