Search Results (9,538)

Simulated room impulse responses (RIRs) are important tools for studying architectural acoustics. Many methods exist to generate RIRs, each with unique properties that need to be considered when choosing an RIR synthesis technique. Despite the variation in synthesis techniques, there is a dearth of comparisons between these techniques. To address this, a comprehensive comparison of four major categories of RIR synthesis techniques was conducted: wave-based methods (hybrid FEM and modal analysis), geometrical acoustics methods (the image source method and ray tracing), delay-network reverberators (SDNs), and statistical methods (Sabine-NED). To compare these techniques, RIRs were recorded in a simple shoebox-shaped racquetball court, and we compared the synthesized RIRs against these recordings. We conducted both objective analyses, such as energy decay curves, normalized echo density, and frequency-dependent decay times, and a perceptual assessment of synthesized RIRs, which consisted of a listening assessment with 29 participants that utilized a MUSHRA comparison methodology. Our results reveal distinct advantages and limitations across synthesis categories. For example, the Sabine-NED technique was indistinguishable from the recorded IR, but it does not scale well with increasing geometric complexity. These findings provide valuable insights for selecting appropriate synthesis techniques for applications in architectural acoustics, immersive audio rendering, and virtual reality environments. Full article

A mill relining manipulator is key maintenance equipment for liners exchanged and operated by workers inside a grinding mill. To improve the operation efficiency and safety, real-time path planning and end deformation compensation should be performed prior to actual execution. This paper proposes a five-dimensional digital twin framework to realize virtual–real interaction between a physical manipulator and virtual model. First, a real-time digital twin scene is established based on OpenGL. The involved technologies include scene rendering, a camera system, the light design, model importation, joint control, and data transmission. Next, different solving methods are introduced into the service space for relining tasks, including a kinematics model, collision detection, path planning, and end deformation compensation. Finally, a user application is developed to realize real-time condition monitoring and simulation analysis visualization. Through comparison experiments, the superiority of the proposed path planning algorithm is demonstrated. In the case of a long-distance relining task, the planning time and path length of the proposed algorithm are 1.7 s and 15,299 mm, respectively. For motion smoothness, the joint change curve exhibits no abrupt variation. In addition, the experimental results between original and modified end trajectories further verified the effectiveness and feasibility of the proposed end effector compensation method. This study can also be extended to other heavy-duty manipulators to realize intelligent automation. Full article

This study presents a comprehensive analysis of Speed Climbing athletes by examining motion parameters critical to elite performance. As such, several key values are extracted from about 900 competition recordings in order to generate a dataset for the identification of patterns in athletes’ technique and efficiency. A CNN-based framework is used to automate the detection of human keypoints and features, enabling a large-scale evaluation of climbing dynamics. The results revealed significant variations in performance for single sections of the wall, particularly in relation to start reaction times (with differences of up to 0.27 s) and increased split times the closer the athletes are to the end of the Speed Climbing wall (from 0.39 s to 0.45 s). In addition, a more detailed examination of the movement sequences was carried out by analyzing the velocity trajectories of hands and feet. The results showed that coordinated and harmonic movements, especially of the lower limbs, correlate strongly with the performance outcome. To ensure an individualized view of the data points, a comparison was made between multiple athletes, revealing insights into the influence of individual biomechanics on the efficiency of movements. The findings provide both trainers and athletes with interesting insights in relation to tailoring training methods by including split time benchmarks and limb coordination. Full article

Since the Great East Japan Earthquake, floriculture has expanded in Namie Town, Fukushima Prefecture, as part of agricultural recovery. Growth surveys are essential for floriculture production, cultivation management, and trials as they help assess plant growth. However, these surveys are labor-intensive, and the standards used can vary owing to subjective judgments and individual differences. To address this issue, image-processing technologies are expected to enable more consistent and objective evaluations. In this study, we explored image processing in growth surveys by estimating plant growth parameters from three-dimensional (3D) point clouds acquired using a smartphone-based 3D scanner. Focusing on lisianthus (Eustoma grandiflorum), we estimated the plant height and the number of nodes above the bolting. The results showed that plant height could be estimated with high accuracy, with a root mean square error (RMSE) of 1.2 cm. By contrast, the node number estimation showed a mean error exceeding one node. This error was attributed to the challenges in handling variations in point cloud density, which stem from the 3D point cloud generation method and leaf occlusion caused by dense foliage. Future work should focus on developing analysis methods that are robust to point-cloud density and capable of handling complex vegetative structures. Full article

Rural tourism agglomerations are increasingly viewed as catalysts for diversified regional growth, integrated rural revitalization, and improved farmer prosperity. However, most studies focus on urban and developed regions, leaving spatial patterns and evolutionary mechanisms in underdeveloped rural areas poorly understood. This study takes Jilin Province, an economically lagging region, as an example, measuring rural tourism agglomeration using spatial analysis methods including the Gini coefficient, nearest-neighbor index, Ripley’s K function, kernel density, and buffer analysis. Results show that agglomeration is significant and strengthening over time, with clear regional variations. All types of rural tourism products exhibit an “increase followed by decrease” pattern across spatial scales, evolving from isolated “nodes” to continuous “areas”. Agglomeration is subject to triple constraints from natural, economic, and social dimensions. This study suggests that high-quality rural tourism development should leverage point–axis spillover from flagship scenic areas, promote surface expansion of characteristic villages and towns, and strengthen network connectivity through roads and talent-information channels. Full article

Objective: Stroke is one of the leading causes of death and disability worldwide. Compared to developed countries, the prognosis of stroke is less favourable in developing countries. The objective of this study is to identify inter-ethnic variation in risk profiles and stroke outcomes amongst Bangladeshi, Indian, Nepalese, Pakistani, and Sri Lankan expatriates living in Qatar. Methods: Data from the Qatar Stroke Registry were retrospectively analyzed from April 2014 to June 2025. A total of 8825 patients were included. The chi-square test was used to analyze sociodemographic variables, while the Kruskal–Wallis test was used to analyze continuous variables. Post hoc analysis was performed. Multivariate logistic regression and multivariate multiple regression were used to identify the predictors associated with poor clinical outcomes and mortality at 90 days. Results: Ischemic stroke was the predominant stroke type in all groups, with Nepalese patients presenting with stroke at a younger age, whilst Pakistanis tended to be older (p < 0.001). In terms of stroke outcomes, Nepalese patients had the highest proportion of a poor functional outcome at 90 days as well as NIHSS at discharge (p < 0.05). However, Bangladeshis had the highest proportion of mortality at 90 days compared to the other cohorts. Multivariable logistic regression revealed that undiagnosed dyslipidemia, Nepalese ethnicity, and moderate and severe NIHSS admission scores were independent predictors of a poor functional outcome at 90 days, whilst male sex and prior antidiabetic therapy were protective factors (p < 0.001). In terms of mortality at 90 days, only a severe NIHSS admission score (>10) was a significant predictor (p < 0.001). A severe NIHSS admission score was also the only predictive factor of mortality and poor functional outcome at 90 days (p < 0.05). Conclusions: There was a significant variation in stroke presentation and outcomes among South Asian subpopulations in Qatar, suggesting the importance of tailored public health strategies as a uniform approach to stroke care is insufficient for this diverse population. Full article

Introduction: Small Bowel Obstruction (SBO) accounts for 15% of emergency department (ED) admissions. While conservative management is recommended, surgery becomes necessary when strangulation is suspected. Identifying which patients need surgery remains a challenge, as traditional imaging lacks sufficient sensitivity and specificity. This study aimed to explore radiomic features to identify potential predictors of strangulation. Methods: This retrospective study included patients admitted to a tertiary referral hospital ED between 2019 and 2023, diagnosed with Adhesion Small Bowel Obstruction (aSBO) via contrast-enhanced abdominal CT scans. Two patient groups were examined: those who underwent surgery with bowel resection and ischemic changes confirmed histologically (operative management—OM) and those successfully treated with conservative management (CM). All CT scans were reviewed blindly by a general surgeon and an experienced radiologist. Pre-obstructive loop segmentation was performed using 3D Slicer software, with slice-by-slice contouring of intestinal borders on images of suspected strangulated bowel. Radiomic features were extracted, followed by univariate and multivariate regression analysis. Results: A total of 55 patients were included: 27 CM and 28 OM. Significant differences emerged in GLCM (Gray Level Co-occurrence Matrix), GLDM (Gray Level Dependence Matrix), GLRLM (Gray Level Run Length Matrix), and GLSZM (Gray Level Size Zone Matrix), particularly involving entropy and uniformity. These metrics reflect subtle variations in gray levels not visible to the naked eye. Conclusions: Differences in entropy, uniformity, and energy align with imaging and histopathological findings, supporting the development of radiomic models and future AI-based prediction tools. Full article

This study aims to develop high-performance biocomposites for structural applications using kenaf, bagasse, hemp, and softwood fibers bonded with phenol-formaldehyde (PF) and phenol-urea-formaldehyde (PUF) adhesives, commonly used in particleboard manufacturing. A simple, low-cost fiber treatment was applied by adjusting the fiber pH to 11 and 13 using a 33% NaOH solution, following standard protocols to enhance fiber–adhesive interaction. The effects of alkaline treatment on the chemical structure of bagasse, kenaf, and hemp fibers were investigated using Fourier Transform Infrared Spectroscopy (FTIR) and correlated with composite mechanical performance. PF and PUF were applied at 13% (w/w), while polymeric diphenylmethane diisocyanate (pMDI) at 5% (w/w) served as a control for untreated fibers. The fabricated panels were evaluated for mechanical properties; modulus of elasticity (MOE), modulus of rupture (MOR), and internal bond strength (IB), and physical properties such as thickness swelling (TS) and water absorption (WA) after 24 h of immersion. FTIR analysis revealed that treatment at pH 11 increased the intensity of O–H, C–O–C, and C–O bands and led to the disappearance of the C=O band (~1700 cm⁻¹) in all fibers. Bagasse treated at pH 11 showed the most significant spectral changes and the highest IB values with both PF and PUF adhesives, followed by kenaf at pH 13, exceeding EN 312:6 (2010) standards for heavy-duty load-bearing panels in dry conditions. The highest MOE and MOR values were achieved with kenaf at pH 11, meeting EN 312:4 (2010) requirements, followed by bagasse, while softwood and hemp performed less favorably. In terms of thickness swelling, bagasse consistently outperformed all other fibers across pH levels and adhesives, followed by Kenaf and Hemp, surpassing even pMDI-based composites. These results suggest that high-pH treatment enhances the reactivity of PF and PUF adhesives by increasing the nucleophilic character of phenolic rings during polymerization. The performance differences among fibers are also attributed to variations in the aspect ratio and intrinsic structural properties influencing fiber–adhesive interactions under alkaline conditions. Overall, kenaf and bagasse fibers emerge as promising, sustainable alternatives to industrial softwood particles for structural particleboard production. PF and PUF adhesives offer cost-effective and less toxic options compared to pMDI, supporting their use in eco-friendly panel manufacturing. FTIR spectroscopy proved to be a powerful method for identifying structural changes caused by alkaline treatment and provided valuable insights into the resulting mechanical and physical performance of the biocomposites. Full article

Global warming is attributed to anthropogenic emissions of CO₂ and the contribution from the transport sector is significant. Estimating on-road vehicle CO₂ emission factors is essential for guiding carbon-reduction efforts in transportation. In order to accurately calculate carbon emission factors from vehicles, this study built a multi-scenario model for open, semi-enclosed, and enclosed road environments based on Fick’s second law and the law of conservation of mass. During the model optimization phase, it was found that the model’s applicability domain effectively encompassed most urban roadway scenarios, making it suitable for estimating urban traffic CO₂ emissions. The spatiotemporal heterogeneity analysis of field measurements indicated that this method can effectively distinguish variations in CO₂ emission factors across different road types and time periods. The method proposed in this study offers an effective solution for the real-time monitoring of large-scale on-road vehicle carbon emissions. Full article

Based on molecular simulation methods, this paper constructs a molecular model of the CH₄-drilling fluid system to conduct an in-depth analysis of the microscopic dissolution behavior of CH₄ in drilling fluids. By utilizing key parameters such as molecular motion trajectories, interaction energies and solubility free energies, the mechanisms of CH₄ dissolution and diffusion are revealed. The factors influencing CH₄ solubility and their variation mechanisms are elucidated at the molecular level. Through gas solubility experiments, the variation patterns of CH₄ solubility in drilling fluids under different temperature and pressure conditions are investigated, and optimized solubility models for CH₄-drilling fluid systems are selected. The results indicate that the dissolution and diffusion behavior of CH₄ in drilling fluids can be described using free volume, interaction energy and solubility free energy, with the degree of influence ranked as follows: interaction energy > free volume > solubility free energy. The interaction and free volume of CH₄ in oil-based drilling fluids are both greater than those in water-based drilling fluids, suggesting a higher solubility of CH₄ in oil-based drilling fluids. Solubility models of CH₄ in drilling fluids under conditions of 30~120 °C and 10~60 MPa are obtained by regression. The research findings not only deepen the understanding of the dissolution and diffusion behavior of CH₄ in drilling fluids for shale gas horizontal wells, but also provide crucial parameters for establishing wellbore pressure models in managed pressure drilling. Full article

Introduction: Although Brazil includes industrialized regions, such as the Southeast, it also has underdeveloped areas with poor sanitation, such as the North and Northeast, resembling regions in Africa and Asia where HEV is endemic. In Brazil, HEV is suspected to occur mainly as a zoonosis. Given the wide variation in HEV prevalence across the five regions, a scoping review was conducted to systematically evaluate its prevalence and circulating genotypes. Aim: To investigate the epidemiological characteristics of HEV in Brazil, including modes of transmission, by reviewing genotyping studies in humans and swine. Methods: This scoping review followed the methodological framework of the Joanna Briggs Institute (JBI) and the PRISMA-ScR checklist. Gray literature was retrieved from Google Scholar, the Brazilian Digital Library of Theses and Dissertations, and the Thesis and Dissertation Catalog of the Coordination for the Improvement of Higher Education Personnel. Searches were performed in June and July 2025 in MEDLINE and LILACS. The evidence on HEV epidemiology in Brazil was mapped using the Population, Concept, and Context strategy. Results: Among 57 studies on HEV prevalence in Brazil, 45 (78.9%) involved humans and 12 (21.1%) involved swine. IgG prevalence ranged from 0.5% in the North to 59.4% in the South. IgM prevalence was lowest in the Northeast (0.1%) and highest in the North (16.3%). In swine, HEV was detected in all regions, with variation in sample types, husbandry practices, and prevalence. Genotyping revealed exclusively HEV-3 in all regions where analysis was performed. Conclusions: HEV infection is present throughout Brazil, with higher prevalence in the South and Southeast. The circulating genotype is HEV-3, and transmission is likely linked to swine breeding and consumption. Full article

Purpose: To evaluate the prevalence and cancer-specific patterns of kidney stones among U.S. cancer survivors compared to non-cancer adults. Methods: This was a serial cross-sectional, descriptive epidemiologic analysis of a US nationally representative sample from the National Health and Nutrition Examination Survey from 2007 to 2020. Weighted prevalence of kidney stones was estimated for both non-cancer adults and cancer survivors by study cycle. Multivariable logistic regression was conducted to examine factors associated with higher probability of kidney stones in both non-cancer adults and cancer survivors. Results: From 2007–2008 to 2017–2020, kidney stone prevalence rose in both non-cancer adults (8.5% to 9.2%, p for trend = 0.013) and cancer survivors (13.1% to 17.3%, p for trend = 0.033). Throughout the study period, prevalence was consistently higher in cancer survivors. The overall prevalence from 2007 to 2020 was 15.8% (95% CI: 14.0–17.5%) in cancer survivors and 9.2% (95% CI: 8.8–9.6%) in non-cancer adults. After adjusting for sociodemographic, lifestyle, and health factors, cancer survivors had higher odds of kidney stones (OR = 1.28, 95% CI: 1.10–1.49). Compared with non-cancer adults, survivors of ovarian (OR = 3.71, 95% CI: 1.77–7.78), kidney (OR = 2.88, 95% CI: 1.46–5.68), bone and soft tissue (OR = 2.86, 95% CI: 1.12–7.30), uterine (OR = 1.94, 95% CI: 1.17–3.22), cervix (OR = 1.68, 95% CI: 1.08–2.61) and prostate (OR = 1.41, 95% CI: 1.06–1.87) cancers were statistically more likely to report kidney stones. The prevalence was numerically highest among survivors of kidney cancer (34.7%), followed by bone and soft tissue (29.9%), ovarian (29.8%), and testicular (26.3%) cancers. Conclusions: The higher prevalence of kidney stones in cancer survivors, with substantial variation by cancer type, highlights the urgent need for effective clinical management of kidney stones in oncology settings and mechanistic research. Full article

Background/Objectives: Personality traits influence motivation, self-regulation, and adaptation in high-performance sports, and are partially modulated by dopaminergic genetic variability. This study aimed to examine the association between the DRD2 Ex8 rs6276 polymorphism and NEO Five-Factor Inventory (NEO-FFI) personality traits in elite athletes and non-athlete controls. Methods: A total of 323 participants were included: 141 athletes and 182 controls. Genomic DNA was isolated from venous blood, and DRD2 Ex8 rs6276 genotypes (A/A, A/G, G/G) were determined using real-time PCR with melting-curve analysis. Personality traits were assessed using the NEO-FFI, and group differences as well as genotype × group interactions were evaluated using multivariate analyses and non-parametric tests. Results: Athletes scored significantly higher on Conscientiousness than controls. A genotype × group interaction was observed for Extraversion, and the main effect of the genotype was found to be Agreeableness. Athletes with the A/A genotype exhibited the highest Extraversion scores, whereas those with the G/G genotype demonstrated higher Agreeableness than other genotypes. Conclusions: These findings indicate that dopaminergic variation contributes to individual differences in social and motivational traits, which may support athletic engagement and adaptation to high-demand environments. The results should be interpreted with caution due to the moderate sample size, deviation from the Hardy–Weinberg equilibrium in the athlete group, and reliance on a single personality assessment tool. Full article

This study considers a robust design methodology to reduce cogging torque in the EPS (Electric Power Steering) of an automotive system. Cogging torque reduction is the key design factor to improve steering feeling and drive stability in an EPS system. For this reason, an SPMSM (Surface Permanent Magnet Synchronous Motor) has been widely applied to drive a motor in an EPS system. Furthermore, two design methods, which are a magnet shape and step-skew design for rotor assembly, have been mainly used to reduce cogging torque in an SPMSM. In this paper, an SPMSM is selected as the drive motor and a robust design methodology is proposed to reduce cogging torque in an EPS system. Firstly, a cycloid curve is used for the magnet shape to reduce cogging torque. An evaluation index δq is also used to compare this with a conventional magnet shape design. Secondly, based on the results of the magnet shape design with the cycloid curve, a step-skew design for rotor assembly is also applied to reduce cogging torque. In order to validate the effectiveness of the robust design for the cycloid curve and conventional magnet shape with rotor step-skew, the results from FEM (Finite Element Method) analysis and prototype tests are compared. The cycloid curve magnet shape model with rotor step-skew was verified to reduce the cogging torque and enhance the robustness for cogging torque variation through the analysis and protype test results. The verified results for the proposed model will be extended to meet the required cogging torque variation for the various applications driven by SPMSM with the robust design model. Full article

PM_2.5 pollution is still serious in densely populated cities with frequent traffic activities, and it continues to threaten public health. Therefore, it is urgent that we obtain ultrahigh-resolution data that can reveal its complex spatiotemporal variation characteristics, supporting more refined environmental governance and health risk prevention and control. This study first carried out ground monitoring based on low-cost sensors combined with observation results, which were corrected with the national environmental monitoring station data. This study also introduced multi-source auxiliary variables and constructed a machine learning model through the stacking ensemble learning method. The model combines corrected low-cost sensor data with high-resolution prediction factors to achieve ultrahigh-spatiotemporal-resolution prediction of PM_2.5 at 100 m × 100 m spatial resolution and hourly temporal resolution. The results show that the constructed model shows good prediction ability in 5-fold cross validation, with an overall R² of 0.93 and a root mean square error (RMSE) of 3.09 μg/m³. The spatiotemporal analysis based on the prediction results further revealed that the PM_2.5 concentration in the city showed significant variation characteristics at both the ultra-local scale and the short-term scale, reflecting the high heterogeneity of urban air pollution. In addition, by comparing and analyzing the monitoring data of a national environmental monitoring station that were not used in the correction, it was found that the corrected low-cost sensor data significantly reduced the prediction uncertainty, reducing the RMSE from 72.068 μg/m³ to 16.759 μg/m³, verifying its effectiveness in high spatiotemporal resolution air quality monitoring. This shows that low-cost sensors are expected to make up for the problem of insufficient spatial coverage in traditional national environmental monitoring stations, supporting the successful assessment of urban-level air pollution and health risk management, and therefore having broad application prospects. Full article