Search Results (58,031)

Periodic visual inspections are currently conducted to maintain the condition of railway bridges. These inspections rely on direct visual assessments by human inspectors, often requiring specialized equipment such as aerial ladders. However, this method is not only time-consuming and costly but also involves significant safety risks. Therefore, there is a growing need for a more efficient and reliable alternative to traditional visual inspections of railway bridges. In this study, we evaluated and compared the performance of damage detection using U-Net-based deep learning models on images captured by unmanned aerial vehicles (UAVs). The target damage types include cracks, concrete spalling and delamination, water leakage, exposed reinforcement, and paint peeling. To enable multi-class segmentation, the U-Net model was trained using three different loss functions: Cross-Entropy Loss, Focal Loss, and Intersection over Union (IoU) Loss. We compared these methods to determine their ability to distinguish actual structural damage from environmental factors and surface contamination, particularly under real-world site conditions. The results showed that the U-Net model trained with IoU Loss outperformed the others in terms of detection accuracy. When applied to field inspection scenarios, this approach demonstrates strong potential for objective and precise damage detection. Furthermore, the use of UAVs in the inspection process is expected to significantly reduce both time and cost in railway infrastructure maintenance. Future research will focus on extending the detection capabilities to additional damage types such as efflorescence and corrosion, aiming to ultimately replace manual visual inspections of railway bridge surfaces with deep-learning-based methods. Full article

This study focuses on cultural and urban development policies under China’s 14th Five-Year Plan, exploring the content and semantic structure of discussions on the “East Asian Cultural Capital” project on the Weibo platform. It analyzes how national cultural development policies are reflected in the discourse system related to the “East Asian Cultural Capital” on social media and emphasizes the guiding role of policies in the dissemination of online culture. When China announced the 14th Five-Year Plan in 2021, the strategic direction and policy framework for cultural development over the five-year period from 2021 to 2025 were clearly outlined. This study employs text mining and semantic network analysis methods to analyze user-generated content on Weibo from 2023 to 2024, aiming to understand public perception and discourse trends. Word frequency and TF-IDF analyses identify key terms and issues, while centrality and CONCOR clustering analyses reveal the semantic structure and discourse communities. MR-QAP regression is employed to compare network changes across the two years. Findings highlight that urban cultural development, heritage preservation, and regional exchange are central themes, with digital media, cultural branding, trilateral cooperation, and cultural–economic integration emerging as key factors in regional collaboration. Full article

Polynucleotide (PN) and polydeoxyribonucleotide (PDRN) are DNA-derived biopolymers increasingly recognized for their potential in dermatology. Despite their structural similarities, PN and PDRN exhibit distinct functions due to differences in polymer length and molecular weight. PN, composed of longer DNA fragments, plays a key role in extracellular matrix remodeling. Conversely, PDRN, composed of relatively shorter oligonucleotide sequences than those of PN, enhances skin condition through adenosine receptor activations and supports nucleotide synthesis via both the salvage and de novo pathways. This review provides a critical comparison of the molecular characteristics and functions of PN and PDRN with particular emphasis on their dermatological applications. By delineating their respective roles in esthetic and regenerative medicine, we aim to highlight recent advances that may guide the development of optimized treatment strategies and foster evidence-based clinical practice. Full article

A synthetic methodology of the CuAAC “click” approach was exploited for the construction of 1,2-azolyltriazole quinine derivatives by the reaction of O-propargylquinine with azidomethyl-1,2-azoles in methanol. Quinine–piperidine and quinine–anabasine conjugates were obtained using a chloroacetate linker by reacting quinine chloroacetate with piperidine or anabasine in a diethyl ether medium. Cinchophene ester was obtained by the acylation of quinine with cinchophen acid chloride in methylene chloride. The antibacterial, fungicidal, analgesic and cytotoxic properties of the obtained compounds were examined. Full article

This study evaluates the applicability and accuracy of coarse-grain modeling (CGM) in discrete-element method (DEM)–based simulations, focusing on particle-mixing efficiency in five representative industrial mixers: the tumbling V mixer, ribbon-blade mixer, paddle-blade mixer, vertical-blade mixer, and conical-screw mixer. Although the DEM is widely employed for particulate system simulations, the high computational cost associated with fine particles significantly hinders large-scale applications. CGM addresses these issues by scaling up particle sizes, thereby reducing particle counts and allowing longer simulation timesteps. We utilized the Lacey mixing index (LMI) as a statistical measure to quantitatively assess mixing uniformity across various CGM scaling factors. Based on the results, CGM significantly reduced computational time (by over 90% in certain cases) while preserving acceptable accuracy levels in terms of LMI values. The mixing behaviors remained consistent under various CGM conditions, based on both visually inspected particle distributions and the temporal LMI trends. Although minor deviations occurred in early-stage mixing, these discrepancies diminished with time, with the final LMI errors remaining below 5% in most scenarios. These findings indicate that CGM effectively enhances computational efficiency in DEM simulations without significantly compromising physical accuracy. This research provides practical guidelines for optimizing industrial-scale particle-mixing processes and conducting computationally feasible, scalable, and reliable DEM simulations. Full article

The rapid growth of e-commerce and advances in information and communication technologies have placed increasing pressure on last-mile delivery companies to enhance operational productivity. As investments in logistics infrastructure require long-term planning, maximizing the efficiency of existing terminal operations has become a critical priority. This study proposes a mathematical model for inbound truck scheduling that simultaneously minimizes truck waiting times and balances workload across temporary inventory storage located at outbound chutes in cross-docking terminals. The model incorporates a dynamic rescheduling strategy that updates the assignment of inbound trucks in real time, based on the latest terminal conditions. Numerical experiments, based on real operational data, demonstrate that the proposed approach significantly outperforms conventional strategies such as First-In First-Out (FIFO) and Random assignment in terms of both load balancing and truck turnaround efficiency. In particular, the proposed model improves workload balance by approximately 10% and 12% compared to the FIFO and Random strategies, respectively, and it reduces average truck waiting time by 17% and 18%, thereby contributing to more efficient workflow and alleviating bottlenecks. The findings highlight the practical potential of the proposed strategy for improving the responsiveness and efficiency of parcel distribution centers operating under fixed infrastructure constraints. Future research may extend the proposed approach by incorporating realistic operational factors, such as cargo heterogeneity, uncertain arrivals, and terminal shutdowns due to limited chute storage. Full article

In this study, we sought to improve the productivity of Far Eastern catfish (Silurus asotus) and tropical eel (Anguilla bicolor), which are high-value fish species in the Republic of Korea, as well as that of associated crops by applying biofloc technology (BFT)-based aquaponics systems. The following three systems were used: the flow-through system (FTS), BFT, and BFT aquaponics system (BAPs). Caipira lettuce (Lactuca sativa) was utilized and hydroponics (HP) was implemented to compare crop productivity. After 42 days of treatment, the BAPs and BFT systems improved fish productivity, with weight gain rates of 134.47 ± 1.80% in BAPs-cat, 130.38 ± 0.95% in BFT, and 114.21 ± 6.62% in FTS for S. asotus, and 70.61 ± 3.26% in BAPs-eel, 62.37 ± 7.04% in BFT, and 47.83 ± 1.09% in FTS for A. bicolor. During the experiment, the total ammonia nitrogen and NO₂⁻-N concentrations were stable in all plots. In the case of NO₃⁻-N, BFT showed an increasing tendency while both BAPs showed a decrease compared with that of the BFT. BAPs-cat (total weight: 224.1 ± 6.37 g) and HP (220.3 ± 7.17 g) resulted in similar growth. However, in BAPs-eel was 187.7 ± 3.46 g due to root degradation. Water content analysis showed that BAPs-cat and BAPs-eel contained sufficient K, Ca, P, and S, which are important for crop growth. Overall, the effect of BAPs on fish growth was higher than that of FTS. This study reveals that integrating BFT with aquaponics improves productivity for high-value fish and associated crops while maintaining stable water quality. This method offers sustainable, efficient production, reduces environmental impact, and provides insights for future research in sustainable aquaculture practices. Full article

Under intensified downward economic pressures on the economy, technological innovation is playing a pivotal role in the development of Chinese enterprises. Employees’ psychological safety significantly influences their innovative behaviors, as a climate of psychological safety fosters greater willingness among staff to engage in voice behaviors. Guanxi with a team leader may decrease this effect. This study analyzed survey data from 263 employees of China’s private manufacturing enterprises to explore the moderating role of guanxi with a team leader in the relationship between psychological safety climate and voice behavior. Results showed that psychological safety climate was positively correlated with promotive and prohibitive voices, and employees with a higher psychological safety climate were more likely to develop voice behavior. Guanxi with team leaders negatively moderated the relationship between psychological safety climate and promotive and prohibitive voices, and the association between psychological safety climate and promotive and prohibitive voices was strong when guanxi with a team leader was weak. This study expands the scope of the application of guanxi, with team leaders as a moderating variable. It helps leaders focus on the psychological safety climate of employees, maintain harmonious and friendly interpersonal relationships with employees, enable employees to spontaneously contribute to the development of the organization, and enhance cohesion in the organization. Full article

LPG fuel supply systems are increasingly important for improving energy efficiency and reducing carbon emissions in the shipping industry. The primary objective of this research is to investigate the heat transfer phenomena to enhance the thermal performance of double-pipe heat exchangers (DPHEs) in LPG fuel supply systems. This study investigates the heat transfer performance of a glycol–steam double-pipe heat exchanger (DPHE) within an LPG fuel supply system under varying operating conditions. A computational model and methodology were developed and validated by comparing the numerical results with experimental data obtained from commissioning tests. Additionally, the effects of turbulence models and parametric variations were evaluated by analyzing the glycol–water mixing ratio and flow direction—both of which are critical operational parameters for DPHE systems. Numerical validation against the commissioning data showed a deviation of ±2% under parallel-flow conditions, confirming the reliability of the proposed model. With respect to the glycol–water mixing ratio and flow configuration, thermal conductance (UA) decreased by approximately 11% in parallel flow and 13% in counter flow for every 20% increase in glycol concentration. Furthermore, parallel flow exhibited approximately 0.6% higher outlet temperatures than counter flow, indicating superior heat transfer efficiency under parallel-flow conditions. Finally, the heat transfer behavior of the DPHE was further examined by considering the effects of geometric characteristics, pipe material, and fluid properties. This study offers significant contributions to the engineering design of double-pipe heat exchanger systems for LPG fuel supply applications. Full article

Background/Objectives: Pressure injuries are a significant concern among older adults, particularly in community-based long-term care settings where prolonged immobility is prevalent. This study aimed to identify factors influencing sacral interface pressure in community-dwelling older adults, with an emphasis on support surface usage and clinical risk indicators. Methods: A total of 210 participants aged 65 years and older, all receiving long-term care services in South Korea, were enrolled in this study. Sacral interface pressure was measured in the supine position using a portable pressure mapping device (Palm Q7). General characteristics, Braden Scale scores, Huhn Scale scores, and mattress usage were assessed. Data were analyzed using descriptive statistics, t-tests, chi-square tests, and logistic regression. Results: Mattress non-use was identified as the strongest predictor of elevated sacral interface pressure (OR = 6.71, p < 0.001), followed by Braden Scale scores indicating moderate risk (OR = 4.8, p = 0.006). Huhn Scale scores were not significantly associated with interface pressure. These results suggest that support surface quality and skin condition have a stronger impact on interface pressure than mobility-related risk factors. Conclusions: The findings highlight the importance of providing high-quality pressure-relieving mattresses and implementing standardized nursing assessments to reduce the risk of pressure injuries. Integrating smart technologies and expanding access to advanced support surfaces may aid in developing tailored preventive strategies for vulnerable older adults. Full article

Sensor selection in IoT-based smart healthcare systems is a complex fuzzy decision-making problem due to the presence of numerous uncertain and interdependent evaluation criteria. Traditional fuzzy multi-criteria decision-making (MCDM) approaches often assume independence among criteria and rely on aggregation operators that impose sharp transitions between preference levels. These assumptions can lead to decision outcomes with insufficient differentiation, limited discriminatory capacity, and potential issues in consistency and sensitivity. To overcome these limitations, this study proposes a novel fuzzy decision-making framework by integrating Quasi-D-Overlap functions into the fuzzy MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) method. Quasi-D-Overlap functions represent a generalized extension of classical overlap operators, capable of capturing partial overlaps and interdependencies among criteria while preserving essential mathematical properties such as associativity and boundedness. This integration enables a more intuitive, flexible, and semantically rich modeling of real-world fuzzy decision problems. In the context of real-time health monitoring, a case study is conducted using a hybrid edge–cloud architecture, involving sensor tasks such as heartrate monitoring and glucose level estimation. The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments. Full article

Recently, diffractive optics systems have garnered increasing attention due to their myriad benefits in various applications, such as creating vortex beams, Bessel beams, or optical traps, while refractive optics systems still exhibit some disadvantages related to materials, substrates, and intensity shapes. The manufacturing of diffractive optical elements has become easier due to the development of lithography techniques such as direct laser writing, photo lithography, and electron beam lithography. In this paper, we improve the results from previous research and propose a new methodology to design and fabricate advanced binary diffractive optical elements that achieve a square focal spot independently, reducing reliance on additional components. By integrating a binary square zone plate with an axicon zone plate of the same scale, we employ machine learning for laser path optimization and direct laser lithography for manufacturing. This streamlined approach enhances simplicity, accuracy, efficiency, and cost effectiveness. Our upgraded binary diffractive optical elements are ready for real-world applications, marking a significant improvement in optical capabilities. Full article

Addressing global challenges such as climate change and inequality requires convergence competencies that enable learners to devise sustainable solutions. Such competencies have been emphasized in Science, Technology, Engineering, Mathematics (STEM) fields, but empirical research and assessment tools tailored to Humanities, Arts, and Social Sciences (HASS) remain scarce. This study aimed to develop and validate a self-assessment tool to measure convergence competencies among HASS learners. A three-round Delphi survey with domain experts was conducted to evaluate and refine an initial pool of items. Items with insufficient content validity were revised or deleted, and all retained items achieved a Content Validity Ratio (CVR) of ≥0.800, with most scoring 1.000. The validated instrument was administered to 455 undergraduates participating in a convergence education program. Exploratory factor analysis identified five key dimensions: Convergent Commitment, Future Problem Awareness, Future Efficacy, Convergent Learning, and Multidisciplinary Inclusiveness, explaining 69.72% of the variance. Confirmatory factor analysis supported the model’s goodness-of-fit (χ² (160) = 378.786, RMSEA = 0.054, CFI = 0.952), and the instrument demonstrated high internal consistency (Cronbach’s α = 0.919). The results confirm that the tool is both reliable and valid for diagnosing convergence competencies in HASS contexts, providing a practical framework for interdisciplinary learning and reflective engagement toward sustainable futures. Full article

Skeletal muscle atrophy is a critical health issue affecting the quality of life of elderly individuals and patients with chronic diseases. These conditions induce dysregulation of glucocorticoid (GC) secretion. GCs play a critical role in maintaining homeostasis in the stress response and glucose metabolism. However, prolonged exposure to GC is directly linked to muscle atrophy, which is characterized by a reduction in muscle size and weight, particularly affecting fast-twitch muscle fibers. The GC-activated glucocorticoid receptor (GR) decreases protein synthesis and facilitates protein breakdown. Numerous antagonists have been developed to mitigate GC-induced muscle atrophy, including 11β-HSD1 inhibitors and myostatin and activin receptor blockers. However, the clinical trial results have fallen short of the expected efficacy. Recently, several emerging pathways and targets have been identified. For instance, GC-induced sirtuin 6 isoform (SIRT6) expression suppresses AKT/mTORC1 signaling. Lysine-specific demethylase 1 (LSD1) cooperates with the GR for the transcription of atrogenes. The kynurenine pathway and indoleamine 2,3-dioxygenase 1 (IDO-1) also play crucial roles in protein synthesis and energy production in skeletal muscle. Therefore, a deeper understanding of the complexities of GR transactivation and transrepression will provide new strategies for the discovery of novel drugs to overcome the detrimental effects of GCs on muscle tissues. Full article

Ready-to-eat meat products face quality challenges during storage and reheating. This study aimed to (i) characterize the physicochemical/microbiological changes in stewed mutton during storage (4 °C/−18 °C, 0–28 days) and (ii) evaluate reheating methods (boiling vs. microwaving) on day-7 samples. The nutritional analysis confirmed moisture reduction (57.32 vs. 72.12 g/100 g)-concentrated protein/fat levels. Storage at −18 °C suppressed microbial growth (the total plate count (TPC), 3.73 vs. 4.80 log CFU/g at 28 days; p < 0.05) and lipid oxidation (thiobarbituric acid reactive substances (TBARS): 0.14 vs. 0.19 mg/kg) more effectively than storage at 4 °C. The total volatile basic nitrogen (TVB-N) kinetics projected a shelf life ≥90 days (4 °C) and ≥120 days (−18 °C). Microwave reheating after frozen storage (−18 °C) maximized the yield (86.21% vs. 75.90% boiling; p < 0.05) and preserved volatile profiles closest to those in the fresh samples (gas chromatography–mass spectrometry (GC-MS)/electronic nose). The combination of freezing storage and subsequent microwave reheating has been demonstrated to be an effective method for preserving the quality of a precooked lamb dish, thereby ensuring its nutritional value. Full article