Search Results (6,760)

Chromium–aluminum nitride (CrAlN) coatings were deposited on polished H13 tool steel substrates using direct current (DC) magnetron sputtering. The Cr/Al composition in the target was varied by inserting either four or eight chromium (Cr) plugs into cavities machined into an aluminum (Al) plate target. Nitrogen was introduced as a reactive gas to facilitate the formation of the nitride phase. Coatings were deposited at substrate bias voltages of −30 V, −50 V, and −60 V to study the combined effects of composition and ion energy on coating properties. Compositional analysis of coatings deposited at a −50 V bias revealed Cr/Al ratios of approximately 0.8 and 1.7 for the 4- and 8-plug configurations, respectively. This increase in the Cr/Al ratio led to a 2.6-fold improvement in coating hardness. Coatings produced using the eight-Cr-plug target exhibited a nearly linear increase in hardness with increasing substrate bias voltage. Cross-sectional scanning electron microscopy revealed a uniform bilayer structure consisting of an approximately 0.5 µm metal interlayer beneath a 2–3 µm CrAlN coating. Surface morphology analysis indicated the presence of coarse microdroplets in coatings with the lower Cr/Al ratio. These microdroplets were significantly suppressed in coatings with higher Cr/Al content, especially at increased bias voltages. This suppression is likely due to enhanced ion bombardment associated with the increased Cr content, attributed to Cr’s relatively higher atomic mass compared to Al. Coatings with lower hardness exhibited greater scratch resistance, likely due to the influence of residual compressive stresses. The findings highlight the critical role of both Cr/Al content and substrate bias in tailoring the tribo-mechanical performance of PVD CrAlN coatings for wear-resistant applications. Full article

Background: Plantar fasciitis (PF) is a common enthesopathy in patients with ankylosing spondylitis (AS). Shear wave elastography (SWE) and the Belgrade ultrasound enthesitis score (BUSES) may detect PF, but their comparative diagnostic performance is unclear. Objective: To compare SWE with the BUSES for identifying PF in individuals with and without AS. Methods: In this cross-sectional study, 96 participants were stratified into AS and non-AS populations, each further divided based on the presence or absence of clinical PF. Demographic data, the American Orthopedic Foot and Ankle Society Score (AOFAS), and the BASDAI score were recorded. All subjects underwent grayscale ultrasonography, the BUSES scoring, and SWE assessment of the plantar fascia. Logistic regression models were constructed for each population, controlling for age, body mass index (BMI), and fascia–skin distance. ROC curve analyses were performed to evaluate diagnostic accuracy. Results: In both AS and non-AS groups, SWE and the BUSES were significant predictors of PF (p < 0.05). SWE demonstrated slightly higher diagnostic accuracy, with area under the curve (AUC) values of 0.845 (AS) and 0.837 (non-AS), compared to the BUSES with AUCs of 0.785 and 0.831, respectively. SWE also showed stronger adjusted odds ratios in regression models. The interobserver agreement was good to excellent for both modalities. Conclusions: Both SWE and the BUSES are effective for PF detection, with SWE offering marginally superior diagnostic performance, particularly in AS patients. SWE may enhance the early identification of biomechanical changes in the plantar fascia. Full article

The purpose of this study was to examine vegetable consumption and its relationship with lifestyle characteristics among children and adolescents. Data from a health survey administered to a representative sample of 177,091 schoolchildren between the ages of 8 and 17 were employed in this observational, cross-sectional investigation. Physical activity level, screen time, and sleeping patterns were assessed using self-completed questionnaires. Vegetable consumption and dietary habits were analyzed using the Mediterranean Diet Quality Index for Children and Adolescents. Participants consuming vegetables more than once daily were categorized as consumers vs. non-consumers. Physical education teachers measured anthropometric and physical fitness factors. Descriptive statistics and binary logistic regression analysis were conducted, and the odds ratio with the corresponding 95% confidence interval was calculated and adjusted for confounders. Vegetables were consumed once or more times a day by more females than males (25.5% vs. 24.0%, p < 0.001). In both sexes, vegetable consumers slept more, ate healthier, spent less time on screens, and had better anthropometric and aerobic fitness measurements than non-consumers. Healthy eating practices, such as regularly consuming fruits, legumes, nuts, and dairy products, were strongly correlated with vegetable intake. For every one-year increase in age, the odds of being a vegetable consumer decreased by 8% and 10% in boys and girls, respectively. Overweight/obese participants had lower odds of being a vegetable consumer by 20%. Increased screen time, inadequate physical activity, and insufficient sleeping hours decreased the odds of being a vegetable consumer by 22%, 30%, and 25%, respectively (all p-values < 0.001). Overall, a healthier lifestyle profile was associated with higher vegetable intake for both sexes among children and adolescents. Full article

Background/Objectives: Despite growing interest in oral frailty as a public health issue, no nationwide study has assessed regional differences in oral frailty awareness, and the factors associated with such differences remain unclear. This study investigated regional differences in oral frailty awareness among older adults in Japan and identified the associated individual- and municipal-level factors, focusing on local policy measures and community-based oral health programs. Methods: A cross-sectional analysis was conducted using data from the 2022 wave of the Japan Gerontological Evaluation Study. The analytical sample comprised 20,330 community-dwelling adults aged ≥65 years from 66 municipalities. Awareness of oral frailty was assessed via self-administered questionnaires. Individual- and municipal-level variables were analyzed using multilevel Poisson regression models to calculate prevalence ratios (PRs). Results: Awareness of oral frailty varied widely across municipalities, ranging from 15.3% to 47.1%. Multilevel analysis showed that being male (PR: 1.10), having ≤9 years (PR: 1.10) or 10 to 12 years of education (PR: 1.04), having oral frailty (PR: 1.04), and lacking civic participation (PR: 1.06) were significantly associated with lack of awareness. No significant associations were found with municipal-level variables such as dental health ordinances, volunteer training programs, or population density. Conclusions: The study found substantial regional variation in oral frailty awareness. However, this variation was explained primarily by individual-level characteristics. Public health strategies should focus on enhancing awareness among socially vulnerable groups—especially men, individuals with low educational attainment, and those not engaged in civic activities—through targeted interventions and community-based initiatives. Full article

Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. Existing approaches, whether classical vision pipelines or recent deep-learning paradigms, struggle to simultaneously satisfy the stringent demands of industrial scenarios: high accuracy on sub-millimeter flaws, insensitivity to texture-rich backgrounds, and real-time throughput on resource-constrained hardware. Although contemporary detectors have narrowed the gap, they still exhibit pronounced sensitivity–robustness trade-offs, particularly in the presence of scale-varying defects and cluttered surfaces. To address these limitations, we introduce MBY (MBDNet-Attention-YOLO), a lightweight yet powerful framework that synergistically couples the MBDNet backbone with the YOLO detection head. Specifically, the backbone embeds three novel components: (1) HGStem, a hierarchical stem block that enriches low-level representations while suppressing redundant activations; (2) Dynamic Align Fusion (DAF), an adaptive cross-scale fusion mechanism that dynamically re-weights feature contributions according to defect saliency; and (3) C2f-DWR, a depth-wise residual variant that progressively expands receptive fields without incurring prohibitive computational costs. Building upon this enriched feature hierarchy, the neck employs our proposed MultiSEAM module—a cascaded squeeze-and-excitation attention mechanism operating at multiple granularities—to harmonize fine-grained and semantic cues, thereby amplifying weak defect signals against complex textures. Finally, we integrate the Inner-SIoU loss, which refines the geometric alignment between predicted and ground-truth boxes by jointly optimizing center distance, aspect ratio consistency, and IoU overlap, leading to faster convergence and tighter localization. Extensive experiments on two publicly available steel-defect benchmarks—NEU-DET and PVEL-AD—demonstrate the superiority of MBY. Without bells and whistles, our model achieves 85.8% mAP@0.5 on NEU-DET and 75.9% mAP@0.5 on PVEL-AD, surpassing the best-reported results by significant margins while maintaining real-time inference on an NVIDIA Jetson Xavier. Ablation studies corroborate the complementary roles of each component, underscoring MBY’s robustness across defect scales and surface conditions. These results suggest that MBY strikes an appealing balance between accuracy, efficiency, and deployability, offering a pragmatic solution for next-generation industrial quality-control systems. Full article

Background and Objectives: The uric acid to HDL-cholesterol ratio (UHR) has recently emerged as a promising biomarker reflecting systemic inflammation and metabolic disturbances. Elevated liver transaminases are clinical indicators of hepatic injury and underlying metabolic dysfunction. Many Middle Eastern countries face constrained clinical and laboratory resources, where access to comprehensive diagnostic tools may be limited. In such settings, identifying simple and easily accessible markers could offer significant practical value in detecting and monitoring health disorders. This study investigates the potential association between UHR and elevated liver transaminases levels in the Saudi general population. Materials and Methods: This retrospective cross-sectional study included 9618 subjects, and the association between the UHR and elevated liver transaminases, alanine transaminase (ALT), and aspartate transaminase (AST), was comprehensively analysed. In addition, the study assessed risk indicators including the prevalence ratio (PR) and odds ratio (OR) as well as the diagnostic accuracy of UHR and C-reactive protein (CRP) in detecting liver transaminases abnormalities, with analyses stratified by age and gender. Results: UHR was significantly elevated in subjects with increased ALT and AST activities, and this pattern was consistent across all age and gender categories. High UHR was significantly associated with elevated ALT (OR = 2.32, 95% CI: 2.12–2.53, p < 0.001) and AST (OR = 1.38, 95% CI: 1.25–1.52, p < 0.001), with stronger associations observed in males and for ALT activity. In addition, elevated UHR was more prevalent among individuals with increased liver transaminase activities. Receiver operating characteristic (ROC) analysis showed that UHR outperformed CRP in identifying elevated liver transaminases, with better discriminative ability for ALT than AST activity. Conclusions: These findings highlight a significant association between UHR and liver transaminase abnormalities in the general population, underscoring the potential utility of UHR as a simple and accessible indicator for liver function assessment in clinical settings. Full article

Vortex-induced vibrations (VIVs) pose significant risks to the structural integrity of subsea cables and pipelines under free-span conditions. It is extremely helpful to be able to screen for VIV and understand for a particular cable or pipeline what the minimum free-span threshold lengths are beyond which in-line and/or cross-flow VIV can be excited, causing fatigue problems. To date screening is a more complex and detailed task. This paper introduces a universal dimensionless velocity, V*, and one graph that can be used across all types of VIV free spans to quickly assess minimum free-span threshold lengths. Natural frequencies are not required to be calculated for screening each time, as they are implicit in the curve. The universal criteria are developed via non-dimensional analysis to establish the significant physical mechanisms, after which the relationships are populated, forming a single curve for in-line and for cross-flow VIV with a typical mass ratio and a conservative zero as-laid tension case. Full article

This study proposes a novel Deep Reinforcement Learning (DRL) policy network structure for portfolio management called PortRSMs. PortRSMs employs stacked State-Space Models (SSMs) for the modeling of multi-scale continuous regime shifts in financial time series, striking a balance between exploring consistent distribution properties over short periods and maintaining sensitivity to sudden shocks in price sequences. PortRSMs also performs cross-asset regime fusion through hypergraph attention mechanisms, providing a more comprehensive state space for describing changes in asset correlations and co-integration. Experiments conducted on two different trading frequencies in the stock markets of the United States and Hong Kong show the superiority of PortRSMs compared to other approaches in terms of profitability, risk–return balancing, robustness, and the ability to handle sudden market shocks. Specifically, PortRSMs achieves up to a 0.03 improvement in the annual Sharpe ratio in the U.S. market, and up to a 0.12 improvement for the Hong Kong market compared to baseline methods. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease. It has known multifactorial pathophysiology, but the impact of social determinants of health (SDOH) on the rising prevalence of MASLD is poorly understood. We conducted a retrospective cross-sectional study to examine the influence of SDOH on MASLD using nationwide data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES) study. Methods: We identified participants with MASLD based on liver ultrasound-based controlled attenuation parameter measurements consistent with diagnostic guidelines. We then used logistic regression models to examine associations between SDOH variables and MASLD, with a pre-specified focus on education and income, sequentially adjusting for sociodemographic factors, medical comorbidities, and other SDOH. Results: Our study found that higher education (odds ratio [OR] 0.77, 95% confidence interval [CI] 0.62–0.97, p = 0.024) but not higher income (OR 1.12, 95% CI 0.91–1.37, p = 0.3) was associated with lower odds of MASLD in multivariable adjusted models. We also identified a significant interaction between education level and food security, as well as interactions between food security and other significant SDOH. In the stratified analyses, higher education was significantly associated with lower odds of MASLD among participants with food security (OR 0.71, 95% CI 0.55–0.91, p = 0.007) but not among those with food insecurity (OR 1.26, 95% CI 0.76–2.11, p = 0.4). Conclusions: Our findings identify the potential impact of SDOH on odds of MASLD and suggest increased importance of food security relative to other SDOH. Full article

Slope stability assessment is a critical component of engineering safety. Conventional analytical methods frequently struggle to integrate heterogeneous slope data and model intricate failure mechanisms, thereby constraining their efficacy in practical engineering scenarios. To tackle these issues, this study presents a novel slope stability classification model grounded in the Optuna-TPE-CatBoost framework. By leveraging the Tree-structured Parzen Estimator (TPE) within the Optuna framework, the model adaptively optimizes CatBoost hyperparameters, thus enhancing prediction accuracy and robustness. It incorporates six key features—slope height, slope angle, unit weight, cohesion, internal friction angle, and the pore pressure ratio—to establish a comprehensive and intelligent assessment system. Utilizing a dataset of 272 slope cases, the model was trained with k-fold cross-validation and dynamic class imbalance strategies to ensure its generalizability. The optimized model achieved impressive performance metrics: an area under the receiver operating characteristic curve (AUC) of 0.926, an accuracy of 0.901, a recall of 0.874, and an F1-score of 0.881, outperforming benchmark algorithms such as XGBoost, LightGBM, and the unoptimized CatBoost. Validation via engineering case studies confirms that the model accurately evaluates slope stability across diverse scenarios and effectively captures the complex interactions between key parameters. This model offers a reliable and interpretable solution for slope stability assessment under complex failure mechanisms. Full article

CT scanners are essential tools in modern medical imaging. Sudden failures of their X-ray tubes can lead to equipment downtime, affecting healthcare services and patient diagnosis. However, existing prediction methods based on a single model struggle to adapt to the multi-stage variation characteristics of tube lifespan and have limited modeling capabilities for temporal features. To address these issues, this paper proposes an intelligent prediction architecture for CT tubes’ remaining useful life based on a dual-branch neural network. This architecture consists of two specialized branches: a residual self-attention BiLSTM (RSA-BiLSTM) and a multi-layer dilation temporal convolutional network (D-TCN). The RSA-BiLSTM branch extracts multi-scale features and also enhances the long-term dependency modeling capability for temporal data. The D-TCN branch captures multi-scale temporal features through multi-layer dilated convolutions, effectively handling non-linear changes in the degradation phase. Furthermore, a dynamic phase detector is applied to integrate the prediction results from both branches. In terms of optimization strategy, a dynamically weighted triplet mixed loss function is designed to adjust the weight ratios of different prediction tasks, effectively solving the problems of sample imbalance and uneven prediction accuracy. Experimental results using leave-one-out cross-validation (LOOCV) on six different CT tube datasets show that the proposed method achieved significant advantages over five comparison models, with an average MSE of 2.92, MAE of 0.46, and R² of 0.77. The LOOCV strategy ensures robust evaluation by testing each tube dataset independently while training on the remaining five, providing reliable generalization assessment across different CT equipment. Ablation experiments further confirmed that the collaborative design of multiple components is significant for improving the accuracy of X-ray tubes remaining life prediction. Full article

Background: Chlamydia trachomatis is the most prevalent bacterial sexually transmitted infection (STI) globally, linked to severe complications such as pelvic inflammatory disease and infertility. In the Brazilian Amazon, socioeconomic vulnerability and the absence of screening policies exacerbate risks, particularly among female sex workers (FSWs). Objective: This study aimed to determine the seroprevalence of anti-C. trachomatis IgG antibodies among FSWs in five municipalities of Pará State, Brazilian Amazon, and identify epidemiological factors associated with infection. Methods: A retrospective cross-sectional study (2005–2007) included 348 FSWs recruited via convenience sampling. Sociodemographic and behavioral data were collected through questionnaires, and blood samples were analyzed by ELISA for anti-C. trachomatis IgG. Statistical analyses included Fisher’s exact tests, odds ratios (ORs), and 95% confidence intervals (CIs), using SPSS 21.0. Results: Overall seroprevalence was 93.9% (327/348; 95% CI: 83.1–90%). Significant associations included a household income of 1–3 minimum wages (98.4%; p = 0.0002), sexual partners from the same region (98.8%; p = 0.0421), and age >42 years (96.3%). Most reported inconsistent condom use (43.7%), multiple monthly partners (54.6%), and illicit drug use (53.4%). Discussion: The extremely high seroprevalence reflects chronic C. trachomatis exposure, driven by socioeconomic deprivation and limited healthcare access. Comparisons with global data underscore the urgent need for screening policies, absent in Brazil for FSWs, and highlight the vulnerability of this population. Conclusions: The findings reveal an alarming burden of C. trachomatis exposure among Amazonian FSWs. Integrated strategies, including routine screening, sexual health education, and inclusion of FSWs in priority health programs, are critical to reduce transmission and associated complications. Full article

Cotton fiber initiation determines the fiber yield, yet the genetic basis underlying lint and fuzz initiation has still not been fully uncovered. Here, map-based cloning was carried out to identify the fiberless mutant genes derived from a cross between Gossypium hirsutum acc. WT and a natural fiberless mutant, fbl_SHZ. The 12:3:1 segregation ratio in F₂ populations (including 1848 and 3100 individuals that were developed in 2016 and 2018, respectively) revealed dominant epistasis, with the fuzz gene exerting dominance over the lint gene. Genetic linkage analysis revealed that GhMYB25like_A12 controls fuzz fiber initiation, while both GhMYB25like_A12 and GhMYB25like_D12 regulate lint fiber development. Sequencing analyses showed that the fbl_SHZ mutant exhibited a K104M mutation in the R2R3 domain of GhMYB25like_A12 and a transposable element insertion in GhMYB25like_D12, leading to fiberless seeds. Knockout of GhMYB25like_A12 produced fuzzless seeds, knockout of GhMYB25like_D12 led to no obvious change in seeds, and knockout of both (GhMYB25like_A12&D12) resulted in fiberless seeds. The 12:3:1 ratio reappeared in the F₂ population developed from the GhMYB25like_A12&D12 mutated plants as female and Jin668 as the male, which further confirmed the genetic interaction observed in fbl_SHZ. RNA-seq analysis revealed that GhMYB25like regulates cotton fiber initiation through multiple pathways, especially fatty acid metabolism. This study elucidates the key genes and their genetic interaction mechanisms governing cotton fiber initiation, providing a theoretical foundation for genetic improvement of cotton fiber traits. Full article

Introduction: Night shift work (NSW) has been increasingly addressed in the scientific literature, as it is considered a probable carcinogen. In this study, we investigated the association of NSW with health problems, unhealthy behaviors, and occupational carcinogens. Methods: Cross-sectional study with a sample of 47,953 workers from the 2019 National Health Survey. NSW prevalence was estimated according to sociodemographic characteristics. To investigate the associations of NSW with all study variables, gender stratified logistic regression models were used. The odds-ratio and 95% confidence intervals were estimated. Results: Among men, there was a significant association of NSW with sleep disorders (OR = 1.39; 95% CI: 1.17–1.65), tiredness (OR = 1.68; 95% CI: 1.41–2.00), obesity (OR = 1.41; 95% CI: 1.20–1.66), unhealthy food consumption (OR = 1.28; 95% CI: 1.12–1.46), handling of radioactive material (OR = 2.45; 95% CI: 1.61–3.72), and biological material (OR = 3.18; 95% CI: 3.15–4.80). Among females, NSW was associated with the same variables except obesity, but depressive feelings (OR = 1.35 95% CI: 1.09–1.67), frequent alcohol intake (OR = 1.48; 95% CI: 1.23–1.78), handling of chemical substances (OR = 1.54; OR = 1.54; 95% CI: 1.20–1.97), and passive smoking at work (OR = 1.45; 95% CI: 1.12–1.86) were highly significant. Conclusion: Night shift workers are more vulnerable to occupational carcinogen exposure, experience greater impacts on their well-being, and are more likely to engage in unhealthy behaviors. These findings should be considered in managing and organizing night work in the workplace. Actions to promote healthy work environments should be encouraged to protect workers’ health. Full article

Background and Objectives: Malnutrition is one of the most common complications in patients undergoing hemodialysis (HD) and is closely linked to increased morbidity and mortality. This study aimed to investigate the nutritional status of HD patients and the clinical relevance of bioelectrical impedance analysis (BIA) parameters such as the percent body fat (PBF), skeletal muscle mass index (SMI), extracellular water-to-total body water ratio (ECW/TBW), and phase angle (PhA) in assessing malnutrition in Vietnamese HD patients. Materials and Methods: This cross-sectional study was conducted among 184 patients undergoing hemodialysis in Hanoi, Vietnam. The BIA parameters were measured by the InBody S10 body composition analyzer, while malnutrition was assessed by the geriatric nutritional risk index (GNRI), with a GNRI <92 classified as a high risk of malnutrition. The independent BIA variables for predicting malnutrition and its cut-off values were explored using logistic regression models and a receiver operating characteristic (ROC) curve analysis, respectively. Results: Among the study population, 42.9% (79/184) of patients were identified as being at a high risk of malnutrition. The multivariate logistic regression analysis revealed that a higher ECW/TBW was independently associated with an increased risk of malnutrition, while the PBF, SMI, and PhA expressed significant and inverse associations with the malnutrition risk after adjusting for multiple confounders. The cut-off values for predicting the high risk of malnutrition in overall HD patients were determined to be 20.45%, 7.75 kg/m², 5.45°, and 38.03% for the PBF, the SMI, the PhA, and the ECW/TBW ratio, respectively. Conclusions: BIA parameters, including the PBF, SMI, PhA, and ECW/TBW ratio, could serve as indicators of malnutrition in general Vietnamese patients with HD. Full article