Search Results (16,775)

Against the backdrop of an urgent energy crisis, solar energy has attracted sufficient attention as one of the most inexhaustible and friendly types of environmental energy. Faced with long service and harsh environment, the poor performance ratios of photovoltaic arrays and safety hazards are frequently boosted worldwide. In particular, the hot spot effect plays a vital role in weakening the power generation performance and reduces the lifetime of photovoltaic (PV) modules. Here, our research reports a spatial–temporal hot spot management system integrated with fiber Bragg grating (FBG) temperature sensor arrays and cooling hydrogels. Through finite element simulations and indoor experiments in laboratory conditions, a superior cooling effect of hydrogels and photoelectric conversion efficiency improvement have been demonstrated. On this basis, field tests were carried out in which the FBG arrays detected the surface temperature of the PV module first, and then a classifier based on an optimized artificial neural network (ANN) recognized hot spots with an accuracy of 99.1%. The implementation of cooling hydrogels as a feedback mechanism achieved a 7.7 °C reduction in temperature, resulting in a 5.6% enhancement in power generation efficiency. The proposed strategy offers valuable insights for conducting predictive maintenance of PV power plants in the case of hot spots. Full article

The literature has shown extensive interest in exploring the factors of subjective well-being (SWB). However, most research has conducted cross-sectional analysis of the built environment (BE), commute, and SWB, and little is known about gender differences in their connections. Based on two periods of survey data of 4297 respondents from China, the study performs a cross-sectional and longitudinal examination of whether the BE and commute have effects on SWB, and how the effects differ between men and women. The results reveal that BE features, including destination accessibility and residential density, significantly affect SWB, with stronger impacts observed among men. Men benefit more from greater accessibility and are more negatively affected by higher residential density than women. In contrast, commute mode and duration influence SWB in similar ways for both genders. A shift from nonactive to active commuting improves well-being for men and women alike. Furthermore, certain life events produce gender-specific effects. For instance, childbirth increases SWB for men but decreases it for women. These findings highlight the importance of gender-sensitive planning in building inclusive urban and transportation environments that enhance population well-being. Full article

Phosphorus (P) release from reservoir sediments critically influences water quality and ecosystem stability. This study analyzed surface sediments from four representative zones to investigate phosphorus fraction distribution, key influencing factors, and implications for water quality. Results showed that total phosphorus (TP) content in sediments from main and tributary inflow zones was significantly higher than in open-water and transition zones. Inorganic phosphorus (IP) was the dominant form, with iron-bound phosphorus (Fe-P) accounting for 33.2–42.0% of IP. A strong correlation existed between P release and the Fe/P molar ratio; notably, when the ratio approached 10, phosphorus desorption increased significantly, indicating a shift from sink to source. Sediments with grain sizes <0.01 mm had the highest P release rates, suggesting particle size, Fe content, and hydrodynamics jointly regulate P mobilization. Using the Diffusive Gradients in Thin Films (DGT) technique, phosphorus release in inflow zones exceeded 1 g/m² in all hydrological periods, contributing substantially to internal loading. Sediment-derived P primarily influenced bottom water, while surface water was more affected by external inputs. These findings highlight the spatial heterogeneity of P release and underscore the need for zone-specific management strategies in reservoir systems. Full article

Magnetic 2D materials offer a compelling platform for next-generation electrocatalysis by enabling spin-dependent reaction pathways. Among them, layered ferromagnets such as Fe₃GeTe₂ (FGT) have garnered attention for combining intrinsic ferromagnetism with high predicted oxygen evolution activity. However, the stability of non-oxide ferromagnets in electrochemical environments remains an unresolved challenge, limiting their envisioned applications. In this study, we introduce a structural homolog approach to investigate the origin of FGT’s catalytic behavior and the mechanisms underlying its degradation. By comparing FGT with its isostructural analog Fe₃GaTe₂ (FGaT), we demonstrate that the electrochemical activity of FGT arises primarily from Fe orbitals and is largely insensitive to changes in sublayer composition. Although both materials exhibit similar basal-plane hydrogen evolution performance, FGaT demonstrates significantly lower long-term stability. Density functional theory calculations reveal that this instability arises from weaker Te bonding introduced by Ga substitution. These findings establish structural homologs as a powerful strategy for decoupling catalytic activity from electrochemical deterioration and for guiding the rational design of stable magnetic electrocatalysts. Full article

Optimization of injection molding process parameters is essential for improving product quality and production efficiency. Traditional methods, which rely heavily on operator experience, often result in inconsistencies, high time consumption, high defect rates, and suboptimal energy consumption. In this study, an improved particle swarm optimization (IPSO) algorithm was proposed, integrating dynamic inertia weight adjustment, adaptive acceleration coefficients, and position constraints to address the issue of premature convergence and enhance global search capabilities. A dual-model architecture was implemented: a constraint validation mechanism based on support vector machine (SVM) was enforced per iteration cycle to ensure stepwise quality compliance, while a fitness function derived by extreme gradient boosting (XGBoost) was formulated to minimize cycle time as the optimization objective. The results demonstrated that the average injection cycle time was reduced by 9.41% while ensuring that the product was qualified. The SVM and XGBoost models achieved high performance metrics (accuracy: 0.92; R²: 0.93; RMSE: 1.05), confirming their robustness in quality classification and cycle time prediction. This method provides a systematic and data-driven solution for multi-objective optimization in injection molding, significantly improving production efficiency and energy utilization. Full article

The integration of AI into online platforms is reshaping consumer experience and behavior. While existing research has largely focused on the role of AI in search services and experience services, few studies have examined the role of AI in the context of credence services. This study fills this gap by investigating an AI-powered preview tool in the context of online medical aesthetic platforms. Specifically, this study investigates how the AI Magic Mirror influences consumer purchase intentions in medical aesthetic services. Using secondary data analysis and two experimental studies, we examine the main effects, as well as mediation and moderation effects. The findings consistently demonstrate that the AI Magic Mirror significantly increases consumer purchase intentions. This relationship is positively mediated by perceived value and negatively mediated by perceived risk. In addition, the main effect is stronger for procedures with higher fit uncertainty and is more pronounced for those with lower popularity. These results provide theoretical insights into AI application in credence service contexts and offer practical implications for the design of AI-enhanced online service platforms. Full article

Anthracnose, a significant disease of aloe with characteristics of contact transmission, poses a considerable threat to the economic viability of aloe cultivation. To address the challenges of accurately detecting and classifying crop diseases in complex environments, this study proposes an enhanced algorithm, YOLOv11-seg-DEDB, based on the improved YOLOv11-seg model. This approach integrates multi-scale feature enhancement and a dynamic attention mechanism, aiming to achieve precise segmentation of aloe anthracnose lesions and effective disease level discrimination in complex scenarios. Specifically, a novel Disease Enhance attention mechanism is introduced, combining spatial attention and max pooling to improve the accuracy of lesion segmentation. Additionally, the DCNv2 is incorporated into the network neck to enhance the model’s ability to extract multi-scale features from targets in challenging environments. Furthermore, the Bidirectional Feature Pyramid Network structure, which includes an additional p2 detection head, replaces the original PANet network. A more lightweight detection head structure is designed, utilizing grouped convolutions and structural simplifications to reduce both the parameter count and computational load, thereby enhancing the model’s inference capability, particularly for small lesions. Experiments were conducted using a self-collected dataset of aloe anthracnose infected leaves. The results demonstrate that, compared to the original model, the improved YOLOv11-seg-DEDB model improves segmentation accuracy and mAP@50 for infected lesions by 5.3% and 3.4%, respectively. Moreover, the model size is reduced from 6.0 MB to 4.6 MB, and the number of parameters is decreased by 27.9%. YOLOv11-seg-DEDB outperforms other mainstream segmentation models, providing a more accurate solution for aloe disease segmentation and grading, thereby offering farmers and professionals more reliable disease detection outcomes. Full article

Named Data Networking (NDN) represents a promising Information-Centric Networking architecture that addresses limitations of traditional host-centric Internet protocols by emphasizing content names rather than host addresses for communication. While NDN offers advantages in content distribution, mobility support, and built-in security features, its stateful forwarding plane introduces significant vulnerabilities, particularly Interest Flooding Attacks (IFAs). These IFA attacks exploit the Pending Interest Table (PIT) by injecting malicious interest packets for non-existent or unsatisfiable content, leading to resource exhaustion and denial-of-service attacks against legitimate users. This survey examines research advances in IFA detection and mitigation from 2013 to 2024, analyzing seven relevant published detection and mitigation strategies to provide current insights into this evolving security challenge. We establish a taxonomy of attack variants, including Fake Interest, Unsatisfiable Interest, Interest Loop, and Collusive models, while examining their operational characteristics and network performance impacts. Our analysis categorizes defense mechanisms into five primary approaches: rate-limiting strategies, PIT management techniques, machine learning and artificial intelligence methods, reputation-based systems, and blockchain-enabled solutions. These approaches are evaluated for their effectiveness, computational requirements, and deployment feasibility. The survey extends to domain-specific implementations in resource-constrained environments, examining adaptations for Internet of Things deployments, wireless sensor networks, and high-mobility vehicular scenarios. Five critical research directions are proposed: adaptive defense mechanisms against sophisticated attackers, privacy-preserving detection techniques, real-time optimization for edge computing environments, standardized evaluation frameworks, and hybrid approaches combining multiple mitigation strategies. Full article

The rapid adoption of electric vehicles (EVs) has driven a strong need for optimizing locations of electric vehicle charging stations (EVCSs). Previous methods for locating EVCSs rely on statistical and optimization models, but these methods have limitations in capturing complex nonlinear relationships and spatial dependencies among factors influencing EVCS locations. To address this research gap and better understand the spatial impacts of urban activities on EVCS placement, this study presents a spatially aware machine learning (SAML) method that combines a multi-layer perceptron (MLP) model with a spatial loss function to optimize EVCS sites. Additionally, the method uses the Shapley additive explanation (SHAP) technique to investigate nonlinear relationships embedded in EVCS placement. Using the city of Wuhan as a case study, the SAML method reveals that parking site (PS), road density (RD), population density (PD), and commercial residential (CR) areas are key factors in determining optimal EVCS sites. The SAML model classifies these grid cells into no EVCS demand (0 EVCS), low EVCS demand (from 1 to 3 EVCSs), and high EVCS demand (4+ EVCSs) classes. The model performs well in predicting EVCS demand. Findings from ablation tests also indicate that the inclusion of spatial correlations in the model’s loss function significantly enhances the model’s performance. Additionally, results from case studies validate that the model is effective in predicting EVCSs in other metropolitan cities. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) begins with hepatic lipid accumulation and triggers insulin resistance. Hibiscus leaf extract exhibits antioxidant and anti-atherosclerotic activities, and is rich in (−)-epicatechin gallate (ECG). Despite ECG’s well-known pharmacological activities and its total antioxidant capacity being stronger than that of other catechins, its regulatory effects on MASLD have not been fully described previously. Therefore, this study attempted to evaluate the anti-MASLD potential of ECG isolated from Hibiscus leaves on abnormal lipid and glucose metabolism in hepatocytes. First, oleic acid (OA) was used as an experimental model to induce lipid dysmetabolism in human primary hepatocytes. Treatment with ECG can significantly (p < 0.05) reduce the OA-induced cellular lipid accumulation. Nile red staining revealed, compared to the OA group, the inhibition percentages of 29, 61, and 82% at the tested doses of ECG, respectively. The beneficial effects of ECG were associated with the downregulation of SREBPs/HMGCR and upregulation of PPARα/CPT1 through targeting AMPK. Also, ECG at 0.4 µM produced a significant (p < 0.01) decrease in oxidative stress by 83%, and a marked (p < 0.05) increase in glycogen synthesis by 145% on the OA-exposed hepatocytes with insulin signaling blockade. Mechanistic assays indicated lipid and glucose metabolic homeostasis of ECG might be mediated via regulation of lipogenesis, fatty acid β-oxidation, and insulin resistance, as confirmed by an AMPK inhibitor. These results suggest ECG is a dual modulator of lipid and carbohydrate dysmetabolism in hepatocytes. Full article

Aiming at the lightweight design of a bridge-shed integration structure, this paper presents a three-layered absorbing system in which a part of the sand cushion is replaced by expanded polystyrene (EPS) geofoam and the reinforced concrete (RC) protective slab is arranged above the sand cushion to enhance the composite system’s safety. A three-dimensional Smoothed Particle Hydrodynamics–Finite Element Method (SPH-FEM) coupled numerical model is developed in LS-DYNA (Livermore Software Technology Corporation, Livermore, CA, USA, version R13.1.1), with its validity rigorously verified. The dynamic response of rockfall impacts on the shed slab with composite cushions of various thicknesses is analyzed by varying the thickness of sand and EPS materials. To optimize the cushion design, a specific energy dissipation ratio (SEDR), defined as the energy dissipation rate per unit mass (η/M), is introduced as a key performance metric. Furthermore, the complicated interactional mechanism between the rockfall and the optimum-thickness composite system is rationally interpreted, and the energy dissipation mechanism of the composite cushion is revealed. Using logistic regression, the ultimate stress state of the reactive powder concrete (RPC) slab is methodically analyzed, accounting for the speed and mass of the rockfall. The results are indicative of the fact that the composite cushion not only has less dead weight but also exhibits superior impact resistance compared to the 90 cm sand cushions; the impact resistance performance index SEDR of the three-layered absorbing system reaches 2.5, showing a remarkable 55% enhancement compared to the sand cushion (SEDR = 1.61). Additionally, both the sand cushion and the RC protective slab effectively dissipate most of the impact energy, while the EPS material experiences relatively little internal energy build-up in comparison. This feature overcomes the traditional vulnerability of EPS subjected to impact loads. One of the highlights of the present investigation is the development of an identification model specifically designed to accurately assess the stress state of RPC slabs under various rockfall impact conditions. Full article

Background: Papillary thyroid microcarcinoma (PTMC) is associated with certain features that carry an increased risk of local recurrence, underscoring the importance of preoperative risk assessment. This study investigated the clinicopathological factors associated with high-risk lymph node metastasis (HRLNM) and patient outcomes. HRLNM is defined as ≥5 metastatic lymph nodes and/or lateral neck metastasis. Methods: We conducted a retrospective review of 985 patients with PTMC who underwent thyroidectomy at the Kaohsiung Chang Gung Memorial Hospital from 2013 to 2022. Results: Among the 985 patients, 100 (10.2%) had lymph node metastasis (LNM), and 27% of these were classified as having HRLNM. Male sex (OR 3.61, p = 0.04) and extranodal extension (OR 3.76, p = 0.043) were independent predictors of HRLNM. Patients with LNM exhibited lower rates of excellent treatment response (75% vs. 87%, p = 0.001), higher recurrence rates (9.0% vs. 0.6%, p = 0.001), and an increased risk of distant metastasis (2.0% vs. 0%). Recurrence-free survival (RFS) was significantly shorter in patients with LNM (120.9 vs. 198.6 months, p < 0.001). Although HRLNM showed a trend toward reduced RFS (113.5 vs. 124.6 months, p = 0.177), its impact on long-term survival remains uncertain. Conclusions: Male sex and extranodal extension were significant risk factors for HRLNM in patients with PTMC. These findings highlight the need for individualized risk stratification to guide treatment strategies and improve patient outcomes. Full article

Facing the demands of Human–Robot Collaborative (HRC) assembly for complex products under Industry 5.0, this paper proposes an intelligent assembly method that integrates Large Language Model (LLM) reasoning with Augmented Reality (AR) interaction. To address issues such as poor visibility, difficulty in knowledge acquisition, and strong decision dependency in the assembly of complex aerospace products within confined spaces, an assembly task model and structured process information are constructed. Combined with a retrieval-augmented generation mechanism, the method realizes knowledge reasoning and optimization suggestion generation. An improved ORB-SLAM2 algorithm is applied to achieve virtual–real mapping and component tracking, further supporting the development of an enhanced visual interaction system. The proposed approach is validated through a typical aerospace electronic cabin assembly task, demonstrating significant improvements in assembly efficiency, quality, and human–robot interaction experience, thus providing effective support for intelligent HRC assembly. Full article

This study synthesized FeNiCuAlX high-entropy alloys (HEAs) (where X = Cr, Co, Mn) using arc melting and investigated their high-temperature oxidation behavior in air at 900 °C. The oxidation kinetics of all alloys followed a parabolic rate, with the oxidation rate constants (kp) of FeNiCuAlCr, FeNiCuAlCo, and FeNiCuAlMn being approximately two to three orders of magnitude lower than that of the FeNiCu alloy. Specifically, FeNiCuAlCr exhibited the lowest kp value of 1.72 × 10⁻⁶ mg²·cm⁴/s, which is significantly lower than those of FeNiCuAlCo (3.29 × 10⁻⁶ mg²·cm⁴/s) and FeNiCuAlMn (1.71 × 10⁻⁵ mg²·cm⁴/s). This suggests that the addition of chromium promotes the formation of a dense Al₂O₃/Cr₂O₃ oxide layer, significantly enhancing the oxidation resistance. Furthermore, corrosion resistance was assessed through potentiodynamic polarization and electrochemical impedance spectroscopy in a 3.5% NaCl solution. FeNiCuAlCr demonstrated exceptional resistance to localized corrosion, as indicated by its low corrosion current density (45.7 μA/cm²) and high pitting potential (−0.21 V), highlighting its superior corrosion performance. Full article

Background and Objectives: Hysterectomy is a common non-obstetric procedure. Minimally invasive techniques, such as laparoscopy and robot-assisted surgery, have replaced open surgery for benign gynecologic conditions. Robotic surgery offers reduced blood loss and shorter hospital stays but is limited by high costs. Articulating laparoscopic instruments aim to replicate robotic dexterity cost-effectively. However, comparative data on these two approaches in hysterectomy are limited. Materials and Methods: This multicenter study analyzed the outcomes of hysterectomies for benign gynecological diseases using articulating laparoscopic instruments (prospectively recruited) and robot-assisted surgery (retrospectively reviewed). The surgeries were performed by minimally invasive gynecological surgeons in South Korea, Japan, and Taiwan. The baseline characteristics, operative details, and outcomes, including operative time, blood loss, complications, and hospital stay, were compared. Statistical significance was set at p < 0.05. Results: A total of 151 patients were analyzed, including 67 in the articulating laparoscopy group and 84 in the robot-assisted group. The operating times were comparable (114.9 vs. 119.9 min, p = 0.22). The articulating group primarily underwent dual-port surgery (79.1%), whereas the robot-assisted group required four or more ports in 71.4% of the cases (p < 0.001). Postoperative complications occurred in both groups, without a significant difference (9.0% vs. 3.6%, p = 0.17). No severe complications or significant differences in the 30-day readmission rates were observed. Conclusions: Articulating laparoscopic instruments provide outcomes comparable to robot-assisted surgery in hysterectomy while reducing the number of ports required. Further studies are needed to explore the learning curve and long-term impact on surgical outcomes. Full article