Search Results (2,686)

Icing on eight-bundled conductors can significantly alter their aerodynamic behavior, potentially leading to structural instabilities such as galloping. This study employed wind tunnel experiments and numerical simulations to analyze the aerodynamic parameters of each iced conductor across various angles of attack. The simulations incorporated detailed stranded conductor geometries to assess their influence on aerodynamic accuracy. Incorporating stranded geometry in simulations reduced average errors in lift and drag coefficients by 45–50% compared to smooth models. The Den Hartog coefficient prediction error decreased from 15.6% to 3.9%, indicating improved reliability in oscillation predictions. Additionally, conductors with larger windward areas exhibited more pronounced wake effects, with lower sub-conductors experiencing greater wake interference than upper ones. The above results illustrate that explicit modeling of stranded conductor surfaces enhances the precision of aerodynamic simulations, providing a more accurate framework for predicting icing-induced galloping in multi-bundled conductors. Full article

Currently, Poland is witnessing a dynamic development of the offshore wind energy sector, which will be a key component of the national energy mix. While many international studies have addressed wind energy deployment, there is a lack of research that compares the energy and economic performance of both onshore and offshore wind farms under Polish climatic and spatial conditions, especially in relation to turbine spacing optimization. This study addresses that gap by performing a computer-based simulation analysis of three onshore spacing variants (3D, 4D, 5D) and four offshore variants (5D, 6D, 7D, 9D), located in central Poland (Stęszew, Okonek, Gostyń) and the Baltic Sea, respectively. The efficiency of wind farms was assessed in both energy and economic terms, using WAsP Bundle software and standard profitability evaluation metrics (NPV, MNPV, IRR). The results show that the highest NPV and MNPV values among onshore configurations were obtained for the 3D spacing variant, where the energy yield leads to nearly double the annual revenue compared to the 5D variant. IRR values indicate project profitability, averaging 14.5% for onshore and 11.9% for offshore wind farms. Offshore turbines demonstrated higher capacity factors (36–53%) compared to onshore (28–39%), with 4–7 times higher annual energy output. The study provides new insight into wind farm layout optimization under Polish conditions and supports spatial planning and investment decision making in line with national energy policy goals. Full article

The introduction of mobile banking is essential in today’s financial sector, where technological innovation plays a critical role. To remain competitive in the current market, businesses must analyze client attitudes and perspectives, as these influence long-term demand and overall profitability. While previous studies have explored general adoption behaviors, limited research has examined how individual factors such as social influence, lifestyle compatibility, financial technology self-efficacy, and perceived usage cost affect mobile banking adoption among specific generational cohorts. This study addresses that gap by offering insights into these variables, contributing to the growing literature on mobile banking adoption, and presenting actionable recommendations for financial institutions targeting younger market segments. Using a structured questionnaire survey, data were collected from both users and non-users of mobile banking among the Gen Z population in the United States. The regression model significantly predicts mobile banking adoption, with an intercept of $-0.548$ ($p < 0.001$). Among the independent variables, perceived cost of usage has the strongest positive effect on adoption ($B=0.857$, $\beta =0.722$, $p < 0.001$), suggesting that adoption increases when mobile banking is perceived as more affordable. Social influence also has a significant positive impact ($B=0.642$, $\beta =0.643$, $p < 0.001$), indicating that peer influence is a central driver of adoption decisions. However, self-efficacy shows a significant negative relationship ($B=-0.343$, $\beta =-0.339$, $p < 0.001$), and lifestyle compatibility was found to be statistically insignificant ($p=0.615$). These findings suggest that reducing perceived costs, through lower fees, data bundling, or clearer communication about affordability, can directly enhance adoption among Gen Z consumers. Furthermore, leveraging peer influence via referral rewards, Partnerships with influencers, and in-app social features can increase user adoption. Since digital self-efficacy presents a barrier for some, banks should prioritize simplifying user interfaces and offering guided assistance, such as tutorials or chat-based support. Future research may employ longitudinal designs or analyze real-life transaction data for a more objective understanding of behavior. Additional variables like trust, perceived risk, and regulatory policies, not included in this study, should be integrated into future models to offer a more comprehensive analysis. Full article

Background: Left bundle branch block (LBBB) following trans-catheter aortic valve implantation (TAVI) has been excluded from same-day discharge. Early identification of patients with stable LBBB can help facilitate same-day discharge. We aim to assess the role of 6-hour ECG to determine development of LBBB in patients undergoing TAVI. Methods: This is a prospective single-centre study of patients who have LBBB following elective TAVI procedures. All patients underwent ECGs pre-TAVI, as well as immediately, 6 h, and 24 h post-TAVI. Changes in ECG were compared at 6 and 24 h with the one immediately post TAVI. Results: The study included 115 patients with uncomplicated procedures. The mean age was 81 ± 7 years, with 54% male. A self-expanding valve was used in 67% of patients. Following TAVI, prolongations of PR interval and QRS duration were dynamic and reduced at 6 h. The change in PR interval at 6 and 24 h was comparable [−11 (−20 to 3) vs. −2 (−24 to 16) ms, p = 0.18]. Similarly, there was no statistical difference in the change of QRS duration at 6 and 24 h compared to the ECG immediately post-TAVI [−10 (−40 to −2) vs. −7 (−34 to 0) ms, p = 0.055]. Changes in ECG were also comparable in patients undergoing balloon-expandable and self-expanding valves. Conclusions: The current study supports that 6-hour ECG has the potential to reduce the need for prolonged continuous monitoring post-TAVI. ECG at 6 h can help optimise patient flow and facilitate early discharge. Future studies with larger sample sizes are required to confirm our findings. Full article

Grapholita molesta is a globally significant fruit pest. Females achieve maximal reproductive output through efficient sperm utilization following a single copulation. Post-mating maturation of eupyrene sperm is a critical step in reproductive success. Here, we report that a male accessory gland-derived serine protease (named GmAGSP1) is essential for this process. GmAGSP1 was only distantly related to other identified sperm-activating SPs, and its transcript was highly expressed in the AG at 48 h after emergence. RNAi-mediated knockdown of GmAGSP1 in males did not affect courtship rate, copulation duration, or mating frequency, whereas male fertility decreased significantly. Mating with GmAGSP1-knockdown males markedly impaired eupyrene sperm maturation in the spermatophores, with phenotypes including failure of eupyrene sperm bundles to dissociate normally and marked reduction in viability of the dissociated eupyrene sperm. Finally, untargeted metabolomic analysis preliminarily demonstrated marked alterations in multiple metabolic pathways within the spermatophore following mating with GmAGSP1-knockdown males. This study advances our understanding of the regulatory mechanism of “sperm activation in the spermatophore’s metabolic microenvironment mediated by male AG-derived SP” while providing critical insights for the development of novel genetic control strategies targeting G. molesta. Full article

By embedding optical fiber sensors into fiber preforms and utilizing liquid molding processes such as resin transfer molding (RTM), intelligent composite materials with self-sensing capabilities can be fabricated. In the liquid molding process of these intelligent composites, the quality of the final product is highly dependent on the resin flow and impregnation effects. The embedding of optical fibers can affect the microscopic flow and impregnation behavior of the resin; therefore, it is necessary to investigate the specific impact of optical fiber embedding on the resin flow and impregnation of fiber bundles. Due to the difficulty of directly observing this process at the microscopic scale through experiments, numerical simulation has become a key method for studying this issue. This paper focuses on the resin micro-flow in RTM processes for intelligent composites with embedded optical fibers. Firstly, a steady-state analysis of the resin flow and impregnation process was conducted using COMSOL 6.0 obtaining the velocity and pressure field distribution characteristics under different optical fiber embedding conditions. Secondly, the dynamic process of resin flow and impregnation of fiber bundles at the microscopic scale was simulated using Fluent 2022R2. This study comprehensively analyzes the impact of different optical fiber embedding configurations on resin flow and impregnation characteristics, determining the impregnation time and porosity after impregnation under different optical fiber embedding scenarios. Additionally, this study reveals the mechanisms of pore formation and their distribution patterns. The research findings provide important theoretical guidance for optimizing the RTM molding process parameters for intelligent composite materials. Full article

Left ventricular systolic dysfunction (LVSD) is associated with increased mortality and is sometimes reversible when found early. Artificial intelligence (AI)-enabled electrocardiogram (ECG) has emerged as an efficient screening tool for LVSD, but has not been validated in left bundle branch block (LBBB) patients. The clinical significance of developing an AI prediction model for LBBB patients lies in the fact that LBBB can be a cause, consequence, or both of LVSD. This pilot study was designed to develop an AI model for LVSD detection in the LBBB population using a limited dataset. ECG data from 508 patients with sinus rhythm and LBBB were labeled based on an LVSD threshold of 35%. To enhance the performance of a model derived from such a small and skewed dataset, we combined an autoencoder-based anomaly detection model with a convolutional neural network (CNN). We used a lead-wise ensemble technique for the final classification. Experimental results showed an accuracy of 0.81, precision of 0.87, recall of 0.56, and an area under the receiver operating characteristic curve of 0.75 in LVSD prediction among LBBB patients. Despite the limited dataset size, our study findings suggest the potential of deep learning techniques in detecting LVSD in patients with LBBB. Full article

Unmanned aerial vehicles (UAVs), commonly known as drones, offer unprecedented flexibility for complex missions such as area surveillance, search and rescue, and cooperative inspection. This paper presents a unified evaluation framework for the comparison of centralized and distributed task allocation algorithms specifically tailored to multi-UAV operations. We first contextualize the classical assignment problem (AP) under UAV mission constraints, including the flight time, propulsion energy capacity, and communication range, and evaluate optimal one-to-one solvers including the Hungarian algorithm, the Bertsekas $ϵ$-auction algorithm, and a minimum cost maximum flow formulation. To reflect the dynamic, uncertain environments that UAV fleets encounter, we extend our analysis to distributed multi-UAV task allocation (MUTA) methods. In particular, we examine the consensus-based bundle algorithm (CBBA) and a distributed auction 2-opt refinement strategy, both of which iteratively negotiate task bundles across UAVs to accommodate real-time task arrivals and intermittent connectivity. Finally, we outline how reinforcement learning (RL) can be incorporated to learn adaptive policies that balance energy efficiency and mission success under varying wind conditions and obstacle fields. Through simulations incorporating UAV-specific cost models and communication topologies, we assess each algorithm’s mission completion time, total energy expenditure, communication overhead, and resilience to UAV failures. Our results highlight the trade-off between strict optimality, which is suitable for small fleets in static scenarios, and scalable, robust coordination, necessary for large, dynamic multi-UAV deployments. Full article

The Silurian marine shale in the Sichuan Basin is currently the main reservoir for shale gas reserves and production in China. This study investigates the reservoir evolution of the Silurian marine shale based on fractal dimension, quantifying the complexity and heterogeneity of the shale’s pore structure. Physical simulation experiments were conducted on field-collected shale samples, revealing the evolution of total organic carbon, mineral composition, porosity, and micro-fractures. The fractal dimension of shale pore was characterized using the Frenkel–Halsey–Hill and capillary bundle models. The relationships among shale components, porosity, and fractal dimensions were investigated through a correlation analysis and a principal component analysis. A comprehensive evolution model for porosity and micro-fractures was established. The evolution of mineral composition indicates a gradual increase in quartz content, accompanied by a decline in clay, feldspar, and carbonate minerals. The thermal evolution of organic matter is characterized by the formation of organic pores and shrinkage fractures on the surface of kerogen. Retained hydrocarbons undergo cracking in the late stages of thermal evolution, resulting in the formation of numerous nanometer-scale organic pores. The evolution of inorganic minerals is represented by compaction, dissolution, and the transformation of clay minerals. Throughout the simulation, porosity evolution exhibited distinct stages of rapid decline, notable increase, and relative stabilization. Both pore volume and specific surface area exhibit a trend of decreasing initially and then increasing during thermal evolution. However, pore volume slowly decreases after reaching its peak in the late overmature stage. Fractal dimensions derived from the Frenkel–Halsey–Hill model indicate that the surface roughness of pores (D1) in organic-rich shale is generally lower than the complexity of their internal structures (D2) across different maturity levels. Additionally, the average fractal dimension calculated based on the capillary bundle model is higher, suggesting that larger pores exhibit more complex structures. The correlation matrix indicates a co-evolution relationship between shale components and pore structure. Principal component analysis results show a close relationship between the porosity of inorganic pores, microfractures, and fractal dimension D2. The porosity of organic pores, the pore volume and specific surface area of the main pore size are closely related to fractal dimension D1. D1 serves as an indicator of pore development extent and characterizes the changes in components that are “consumed” or “generated” during the evolution process. Based on mineral composition, fractal dimensions, and pore structure evolution, a comprehensive model describing the evolution of pores and fractal dimensions in organic-rich shale was established. Full article

Background/Objectives: Single-dose pre-operative antibiotic prophylaxis for cardiac-device implantation is recommended but extending antibiotic prophylaxis is common. Locally, 50–60% of patients had extended prophylaxis after pacemaker insertion or generator change. Our antimicrobial stewardship programme (ASP) incorporated behavioural change strategies in implementing a multi-pronged intervention bundle to address this and evaluated its effectiveness and safety. Methods: This single-centre, retrospective cohort study included patients aged 21 years old or older, undergoing uncomplicated pacemaker insertion or generator change at Singapore General Hospital (SGH) from October 2022 to March 2025. To improve antibiotic use, ASP interventions incorporating behaviour change strategies were implemented, namely (1) data-driven feedback, (2) targeted education, (3) identification and engagement of ASP champion, and (4) clinical pathway revision. Results: There were 779 patients evaluated; 380 (48.8%) received standard prophylaxis while 399 (51.2%) received extended prophylaxis with oral antibiotics (mean duration, 3.3 ± 0.8 days). Following ASP interventions, the practice of extended prophylaxis declined significantly from 43.8% to 24.0% (p < 0.01). The incidence of surgical site infections was low and similar in both groups (0.8%, p = 1.000); all infections were superficial. There was also significant reduction in the proportion of patients on all antibiotics from 20.7% to 16.3% (p < 0.01). Identification and engagement of ASP champion proved pivotal in changing prescribing behaviour through peer influence and credibility. Conclusions: The bundled ASP interventions, incorporating behavioural change strategies, have effectively and safely reduced the use of extended prophylaxis post-cardiac device implantation. Behavioural change interventions are essential to achieve sustained stewardship success. Full article

The growing mismatch between ecosystem service (ES) supply and demand underscores the importance of thoroughly understanding their spatiotemporal patterns and key drivers to promote ecological civilization and sustainable development at the regional level in China. This study investigates six key ES indicators across mainland China—habitat quality (HQ), carbon sequestration (CS), water yield (WY), sediment delivery ratio (SDR), food production (FP), and nutrient delivery ratio (NDR)—by integrating a suite of analytical approaches. These include a spatiotemporal analysis of trade-offs and synergies in supply, demand, and their ratios; self-organizing maps (SOM) for bundle identification; and interpretable machine learning models. While prior research studies have typically examined ES at a single spatial scale, focusing on supply-side bundles or associated drivers, they have often overlooked demand dynamics and cross-scale interactions. In contrast, this study integrates SOM and SHAP-based machine learning into a dual-scale framework (grid and city levels), enabling more precise identification of scale-dependent drivers and a deeper understanding of the complex interrelationships between ES supply, demand, and their spatial mismatches. The results reveal pronounced spatiotemporal heterogeneity in ES supply and demand at both grid and city scales. Overall, the supply services display a spatial pattern of higher values in the east and south, and lower values in the west and north. High-value areas for multiple demand services are concentrated in the densely populated eastern regions. The grid scale better captures spatial clustering, enhancing the detection of trade-offs and synergies. For instance, the correlation between HQ and NDR supply increased from 0.62 (grid scale) to 0.92 (city scale), while the correlation between HQ and SDR demand decreased from −0.03 to −0.58, indicating that upscaling may highlight broader synergistic or conflicting trends missed at finer resolutions. In the spatiotemporal interaction network of supply–demand ratios, CS, WY, FP, and NDR persistently show low values (below −0.5) in western and northern regions, indicating ongoing mismatches and uneven development. Driver analysis demonstrates scale-dependent effects: at the grid scale, HQ and FP are predominantly influenced by socioeconomic factors, SDR and WY by ecological variables, and CS and NDR by climatic conditions. At the city level, socioeconomic drivers dominate most services. Based on these findings, nine distinct supply–demand bundles were identified at both scales. The largest bundle at the grid scale (B3) occupies 29.1% of the study area, while the largest city-scale bundle (B8) covers 26.5%. This study deepens the understanding of trade-offs, synergies, and driving mechanisms of ecosystem services across multiple spatial scales; reveals scale-sensitive patterns of spatial mismatch; and provides scientific support for tiered ecological compensation, integrated regional planning, and sustainable development strategies. Full article

Right ventricular apex (RVA) pacing has historically been the default approach for cardiac pacing; however, it is associated with the development of progressive left ventricular dysfunction and heart failure (HF), particularly in patients with high pacing burdens. While advances in device programming and modern algorithms have sought to mitigate these effects, preserving physiological activation has proven to be more critical than reducing ventricular pacing. Conduction system pacing (CSP) techniques—namely, His-bundle pacing (HBP) and particularly left bundle branch area pacing (LBBAP)—have emerged as superior alternatives, enabling improved left ventricular function and reduced rates of pacing-induced cardiomyopathy (PICM). Nevertheless, despite the clinical advantages of these procedures over RVA, they face limitations including variable implantation success rates, increased pacing thresholds and lead revision rates, technical challenges, and occasional procedure prolongation. Thus, while CSP approaches represent the future of physiological pacing, RVA pacing continues to provide a necessary and reliable option in the current clinical practice. Full article

Background: Congenital insensitivity to pain with anhidrosis (CIPA) is a rare genetic disorder, often leading to injuries and serious infections. In 2018, we established a multidisciplinary clinic (MDC) to provide structured, proactive care. We assessed the MDC’s impact on hospitalizations, surgeries, and infection rates. Methods: A retrospective study of genetically confirmed CIPA patients, treated from 2014 to 2024. Data from electronic medical records were compared between the pre-MDC (2014–2017) and post-MDC (2018–2024) periods. The core MDC team includes an infectious disease specialist, orthopedic surgeon, and nurses. The patients are stratified according to their carriage of resistant organisms and are managed using strict infection control measures. Follow-ups are scheduled routinely or as needed. Treatment is guided by clinical findings and culture results. Results: A total of 59 patients were included in the study. The baseline age did not differ significantly between the two periods. Hospitalization rates declined by 30.7% (from 57.7 to 40.0 per 1000 days), and clinic visits decreased by 42.9% (25.5 to 14.6). Overall surgical rates remained stable (2.8 to 2.7), with a 61.9% decrease in eye surgeries and a 130.5% increase in elective tooth extractions. Infection rates increased by 52% (from 6.6 to 10.1 per 1000 days). Conclusions: The implementation of the MDC bundle led to reduced hospitalizations, clinic visits, and eye surgeries, alongside the increased use of elective tooth extractions and culture testing. Closer monitoring and early infection management contributed to fewer severe complications. These findings support the value of structured, proactive multidisciplinary care in improving outcomes for children with CIPA. Full article

Background: Long-term right ventricular pacing (RVP) can cause electrical and mechanical dyssynchrony, resulting in adverse outcomes. Recently, left bundle branch area pacing (LBBAP) has emerged as a physiological pacing modality and is considered a promising alternative. To date, the long-term outcomes of LBBAP compared with RVP, particularly with respect to sex differences, remain unclear. Methods: Between January 2017 and July 2024, 1211 patients who underwent de novo pacemaker implantation were enrolled and categorized into RVP (n = 789) and LBBAP (n = 422). The primary outcome was a composite of all-cause mortality, heart failure hospitalization (HFH), and pacing-induced cardiomyopathy (PICM). Propensity score matching (PSM) was employed to minimize the selection bias and achieve comparability among the study population. A post hoc power analysis based on the observed effect size and sample size showed a power of 80%, confirming sufficient sensitivity to detect group differences. Results: After PSM, 764 patients were analyzed. The mean age of the patients was 74.6 ± 10.5 years in RVP and 74.5 ± 9.8 years in LBBAP, respectively, and 52.3% patients were male. Patients with LBBAP had a lower incidence of the primary outcome (8.6% vs. 24.6%, p < 0.001), HFH (2.6% vs. 13.6%, p < 0.001), and all-cause mortality (6.5% vs. 13.9%, p < 0.001) compared with RVP. There were no significant differences in the clinical outcomes, including the primary outcome, HFH and all-cause mortality, between the sexes in the group with either RVP or LBBAP. However, during a 2-year follow-up period for survival analysis, male patients with LBBAP had a significant lower incidence of all the endpoints, whereas female patients with LBBAP had a lower incidence of HFH [HR 0.14 (95% CI 0.06–0.32), p = 0.001] compared with those with RVP. Conclusions: Regardless of sex, patients with LBBAP had a lower risk of poor clinical outcomes, including HFH and all-cause mortality, compared to those with RVP. Moreover, compared with RVP, LBBAP decreased the risks of all the major endpoints in male patients and the risk of HFH particularly in female patients. Further research is needed to establish the sex-specific responses to LBBAP. Full article

The safety and longevity of engineering structures depend on precise and timely monitoring, especially during load testing inspections. Conventional displacement measurement methods—such as LVDT sensors, GNSS, RTS, and levels—each present benefits and limitations in terms of accuracy, applicability, and practicality. Photogrammetry has emerged as a promising alternative, offering non-contact measurement, cost-effectiveness, and adaptability in challenging environments. This study investigates the potential of photogrammetric methods for determining structural displacements during load testing in real-world conditions where such approaches remain underutilized. Two photogrammetric techniques were tested: (1) a single-image homography-based approach, and (2) a multi-image bundle block adjustment (BBA) approach using both UAV and tripod-mounted imaging platforms. Displacement results from both methods were compared against reference measurements obtained by traditional LVDT sensors and robotic total station. The study evaluates the influence of different camera systems, image acquisition techniques, and processing methods on the overall measurement accuracy. The findings suggest that the photogrammetric method, especially when optimized, can provide reliable displacement data with sub-millimeter accuracy, highlighting their potential as a viable alternative or complement to established geodetic and sensor-based approaches in structural testing. Full article