Search Results (504)

Background: Health literacy has become an important determinant of population health. Understanding health literacy levels among physical examination populations in China and examining their associations with social support and quality of life can provide evidence to guide preventive health strategies. Methods: A cross-sectional survey was conducted from May 2023 to May 2024 among 416 individuals undergoing routine physical examinations at a tertiary hospital in Xi’an, China. Participants completed a socio-demographic characteristics questionnaire, the Health Literacy Surveillance Rapid Assessment Questionnaire, the Social Support Rating Scale and the Euro-Qol five-dimension questionnaire. Descriptive statistics, correlation analyses, and multiple linear regression models were used to examine health literacy status, associated factors, and the former’s relationships with social support and quality of life. Results: Health literacy in the physical examination population was higher than the national average, and the proficiency rate was 52.4%. The findings indicate a significant and positive association between social support and health literacy (r = 0.398, p < 0.01); health literacy was found to be significantly and positively associated with quality of life (r = 0.216, p < 0.01). According to the multiple linear regression analysis, factors correlated with health literacy included age, gender, place of residence, marital status, educational level, monthly household income, payment method for physical examinations, frequency of physical examinations, and social support. Conclusions: Enhancing the health education competencies of medical personnel to enable effective dissemination of health information during physical examinations, promoting family involvement in health management to cultivate collective health awareness and practices, and improving the medical insurance system to encourage regular physical examinations are effective strategies for strengthening public health literacy. Full article

Background: Sarcopenia, characterized by age-related loss of muscle mass and strength, is a growing public health concern requiring early detection; this exploratory study evaluated a range of anthropometric measurements and indices to identify those most suitable for screening low muscle strength in hospitalized geriatric patients and to determine preliminary cut-off values that may support screening in settings with limited access to specialized equipment or trained personnel. Materials and Methods: In this cross-sectional study, 390 hospitalized geriatric-ward patients aged ≥ 60 years were included. The median age was 77.00 years (72.00, 82.00), and 258 participants (66.2%) were women. Anthropometric and body composition measurements were performed, and handgrip strength was assessed. Low muscle strength was defined according to The European Working Group on Sarcopenia in Older People 2 (EWGSOP2) criteria. Logistic regression analyses were used to assess associations between anthropometric measurements and low muscle strength, and receiver operating characteristic (ROC) curve analysis was used to evaluate their screening performance. Results: Among 390 participants, 67 (17.2%) had low muscle strength. Low muscle strength was associated with older age, lower body weight, BMI (Body Mass Index), fat-free mass, and smaller arm and calf circumferences. Higher arm and calf circumferences were significantly associated with a lower risk of low muscle strength in both women (OR = 0.913 and 0.884) and men (OR = 0.793 and 0.769; all p < 0.05). ROC analysis identified optimal screening cut-offs: arm 26.5 cm and calf 31.5 cm in women, and arm 29.5 cm and calf 33 cm in men, showing moderate screening performance, with an area under the ROC curve (AUC) of 0.63–0.78. Conclusions: Calf and arm circumferences are simple, quick, and non-invasive measurements that may be useful for screening low muscle strength in hospitalized geriatric patients, particularly in settings with limited access to specialized equipment. These measurements may help identify individuals who require further assessment for sarcopenia according to current clinical guidelines, with age being an important factor to consider. The proposed cut-off values should be considered hypothesis-generating rather than diagnostic thresholds for sarcopenia and require external validation in independent populations before they can be recommended for routine clinical use. Full article

In the era of intelligent assessment, psychometric tests are becoming increasingly important for personnel selection, career development, and mental health assessment. Forced-choice tests are common in personality assessments because they require participants to select from closely related options, lowering the risk of response distortion. However, traditional latent trait models for forced-choice tests suffer from severe computational bottlenecks in high-dimensional settings. Furthermore, existing deep learning-based cognitive diagnosis models are primarily designed for independent items in educational scenarios (predicated on absolute scoring), making them structurally maladapted to the ipsative data (relative preference comparisons) generated by forced-choice tests. To address these challenges, this study presents a deep learning-based Forced-Choice Neural Latent Trait (FCNLT) Model that overcomes the limitations of traditional models and is applicable to the three most common item block types found in forced-choice tests. To account for the unidimensionality of items, participants’ latent trait levels and item characteristics are represented as interpretable latent embeddings. FCNLT mines these features through nonlinear mapping and introduces a weighted BPR-based ranking loss to natively align with the relative-scoring nature of forced-choice data. Additionally, the monotonicity assumption is utilized to improve the interpretability of the trait estimates. The FCNLT’s effectiveness is validated by experiments on real-world and simulated datasets that show its accuracy, interpretability, and robustness. Full article

Fixed-bottom or floating offshore structures are the foundations, platforms, and associated infrastructure that allow for oil and gas production systems, offshore wind turbines, and cabling. The remote nature of these structures and the harsh environment with high variability in wind, waves, currents, and weather make construction activity very difficult and unpredictable; the cost of variation in the schedule can lead to high construction vessel and personnel costs. The adoption of artificial intelligence using trends observed in historical data can help achieve more accurate construction costs and schedule predictions, reducing the capital expenditure cost of installation. A resource-significant activity, sometimes called a resource-critical activity or high-resource-demand activity, is an activity on a construction or project schedule that consumes a disproportionately large share of one or more resources compared with others. Plant Design Modelling (PDM) is a digital process that creates and manages a detailed 3D model of a building’s physical and functional characteristics and semantic information, such as cost and schedule. PDM serves as a single source of truth for multidisciplinary activities and, therefore, serves as a rich data source for various construction applications, including project scheduling and cost estimation. Neural networks (NNs), a subset of machine learning algorithms inspired by the human brain, excel at identifying patterns in complex datasets and making predictions, such as forecasting costs based on non-linear relationships and historical trends. Data from an offshore structure modification project were extracted from Aveva’s Everything PDM, focusing on installation activities to create a dataset for machine learning model training. The structured data extracted exhibit non-linear patterns; therefore, linear, regularised linear, robust linear, and the ensemble (tree-based) models and supervised neural network models with varied architecture and hyperparameter values were evaluated and compared. The best performance was obtained using the deep-optimised ANN model. The result obtained is consistent with previous studies. The neural network models show a superior ability to predict the non-linear nature of offshore construction activities’ time. Full article

During CO₂ pipeline transportation, factors such as third-party interference, pipeline corrosion, and material defects may cause pipeline rupture and CO₂ leakage, posing a threat to the safety of surrounding personnel. Therefore, it is of great significance to study the leakage and dispersion characteristics of CO₂ pipelines. Based on the similarity theory, this study established an offshore platform experimental system, measured the CO₂ concentration variation patterns at different positions on the offshore platform during leakage and dispersion, and identified the influence laws of leakage direction (0°~90°), leakage pressure (1.5~3 MPa), leakage time (1~4 min), and environmental wind speed (0~0.5 m/s) on the leakage and dispersion characteristics of pipeline stations. The results show that when leakage pressure increases, the reading of sensor No. 15 remains unaffected and the maximum concentration is measured at a certain distance from the leakage port; leakage duration has minimal impact; ambient wind speed mainly affects near-field concentration; increasing leakage orifice diameter significantly increases far-field concentration; all sensor readings are zero during vertical leakage; and sensor No. 15 shows the highest reading during 45° upward leakage, while sensor No. 5 shows the highest reading during horizontal leakage. The research results can provide guidance for CO₂ transportation and storage on offshore platforms. Full article

Background: Non-Hodgkin lymphoma (NHL) is the most common hematologic malignancy among U.S. military service members (SMs), yet the impact of deployment and deployment-related factors on survival remains unclear. Modern military service involves potential exposure to environmental hazards and trauma that could plausibly influence lymphoma biology, treatment tolerance, or long-term outcomes. Methods: Tricare beneficiaries with NHL diagnosed between 2001 and 2022 were identified from the Defense Health Agency Cancer Registry. Deployment history, demographics, lymphoma subtype, and mortality data were obtained from linked Department of War and National Death Index sources. Survival was compared between previously deployed (9/11 DEP) and non-deployed (NON-9/11 DEP) SMs using multivariable Cox models. Among deployed SMs, associations between deployment characteristics and mortality were evaluated. Results: Among 745 SMs, 378 had deployed, and 367 had not. There were no significant differences in all-cause, lymphoma-specific, or non-lymphoma mortality between cohorts. Deployment location, duration, number of deployments, and occupational category did not affect survival. Histologic differences between cohorts, higher diffuse large B-cell lymphoma and follicular lymphoma in deployed SMs, and higher T-cell lymphomas and marginal zone lymphoma in non-deployed SMs, were more consistent with unmeasured confounding and differential deployability than with deployment-related risk. Conclusions: These findings do not suggest major survival differences attributable to deployment status. Given the lack of publicly available validated exposure assessment tools for military personnel, as current military operations expand, including recent deployments to the Middle East, proactive and systematic approaches to exposure assessment are urgently needed. Strengthening military cancer registries and embedding validated exposure tools will be essential to proactively anticipate, identify, and manage exposure-related hematologic concerns in future Veterans. Full article

Addressing the problems of complex forms, low structurization and insufficient reliability of automatic acquisition of professional knowledge sources in the manufacturing industry, this paper proposes an improved multi-person collaborative knowledge acquisition method for professional fields. Drawing on the quality control concept of “three reviews and three proofs” in the publishing industry and combining the characteristics of professional knowledge acquisition tasks, this method constructs a knowledge acquisition process with the collaborative participation of editors and professionals. This paper designs a quality assurance mechanism from three dimensions, namely personnel quality, process quality and result quality; introduces triangular fuzzy numbers to evaluate personnel quality; and establishes a process quality control model under multi-level inspection. Taking the knowledge acquisition project of CNC Machining Manual as an example, 39 professionals completed large-scale professional knowledge processing tasks within 60 working days. Compared with the traditional manual knowledge acquisition method, under similar workload conditions, the proposed method reduces the task completion time by approximately 40% and improves knowledge quality by approximately 10%. The research results show that this method can enhance the organization, inspectability and result stability of the complex professional knowledge acquisition process, and is suitable for constructing vertical domain knowledge bases with high quality requirements. Full article

Background/Objectives: Retention of healthcare professionals in the workforce, their employment, and the improvement of working conditions largely depend on identifying the factors that influence their departure and their health. The study was conducted during the period from January to June 2021. This study aimed to examine the association between specific work-related stressors and work ability. The initial hypothesis was that general and specific occupational stressors negatively associate with work ability among healthcare professionals in emergency medical intervention teams. Methods: The study was designed as a cross-sectional comparative study. It was conducted among nurses and physicians in pre-hospital emergency medical services, employed full-time in intervention teams, while the control group consisted of employees from dispatch and call-receiving units. The study was conducted on the 840 participants, representing 43.3% of all healthcare professionals employed in pre-hospital emergency medical services in the Republic of Croatia. In addition to questions on participants’ personal characteristics, the following instruments were used: 1. a validated Questionnaire on Workplace Stressors among hospital healthcare professionals; and 2. the international standardized Work Ability Index (WAI) questionnaire for assessing work ability. Participants completed the questionnaires in paper form. Results: On average, the participants demonstrated lower levels of stress compared to reference values, both for overall stress and for individual stress factors, while their work ability, assessed using the Work Ability Index (WAI), ranged from very good to excellent. The control group showed higher levels of stress across all factors and lower work ability. However, the control group was older on average, generally had lower levels of education, and consisted more often of women—personal characteristics that may influence the examined variables. Lower stress levels and better work ability were associated with job satisfaction, ambition, and the fact that participants were working in their desired profession. Frequent sick leave (absenteeism) was highly correlating with both higher stress levels and poorer work ability. Conclusions: Greater job satisfaction and higher motivation have a positive impact on stress levels and employees’ work ability. The study results can serve as a starting point for institutional management in designing feasible decisions aimed at improving satisfaction, health, the work environment, and the work ability of emergency medical service personnel, as well as making these institutions more attractive for recruitment and retention of employees both in their positions and within the profession. Full article

It is of great significance for accident prevention to explore the causes and evolution laws of ship collisions at sea. The paper aims to constructs a systematic MMEM-FTA integrated analysis framework and applies the framework to analyze the causes of ship collisions in Taizhou coastal waters. Ship collision cases in Taizhou coastal waters from 2017 to 2025 are collected, and a statistical analysis is conducted on the characteristics of collision accidents. Under the MMEM frame, 16 accident influencing factors are identified from four aspects: personnel negligence, ship failure, management failure and environmental degradation. Based on FTA, a fault tree diagram of ship collision accidents in Taizhou coastal waters is constructed. Results of both quantitative and quantitative analysis show that the structural importance of ship failure, management failure and complex environment is the largest and an event with higher probabilistic and critical importance is “Unseaworthiness.” These mentioned events are main reasons for ship collision accidents. Suggestions on risk control options (RCOs) for accident prevention are put forward under the MMEM frame. The proposed MMEM-FTA integrated analysis framework is feasible for accident causation analysis. This research can provide theoretical and practical supports for identifying causes of ship collisions, for elucidating the evolution mechanism of accidents and for taking targeted measures to prevent accidental risks. Full article

Safety management evaluation in highway tunnel construction involves significant complexity due to multi-level, multi-indicator, and uncertain characteristics. To address these challenges, this study proposes an integrated evaluation approach combining the Analytic Hierarchy Process (AHP), Entropy Weight Method (EWM), and Set Pair Analysis (SPA). An evaluation index system is established from the perspective of system defensive capability, encompassing four dimensions—organizational, personnel, material, and information management—with 19 indicators. SPA is employed to quantify the relationships among indicators through identity, discrepancy, and opposition, while a hybrid weighting scheme combines subjective judgments and objective data. A confidence-based identification criterion is further introduced to improve the robustness of classification. The proposed model is applied to a highway tunnel project, and the results show good agreement with observed field conditions. The analysis indicates that the method effectively captures intermediate states and uncertainty in safety management systems while reducing bias associated with single weighting strategies and maximum membership-based decisions. The proposed framework provides a practical and reliable approach for safety management evaluation and supports risk-informed decision-making in tunnel construction. Full article

In response to the issues of subjective weighting of indicators and insufficient consideration of the temporal dimension of risk factors in current operational safety risk assessments for electric utilities, this paper proposes a method for assessing operational safety risks in electric utilities based on the Accident-Calibrated Cumulative Risk Index (ACCRI). First, in accordance with current standards and operational guidelines, a multi-level indicator system covering four dimensions, namely human resources and personnel behavior, equipment and facilities, environment and conditions, and management and systems, is established to provide a systematic characterization of operational safety risks in electric utilities. On this basis, the ACCRI is defined by weighted accumulation of the average risk exposure values of tertiary indicators within their characteristic periods. Historical accident sample importance is used to calibrate and identify tertiary indicator weights and characteristic periods, thereby reducing the subjectivity of traditional expert-based weighting. Furthermore, considering the differing temporal-scale characteristics of various risk indicators, a characteristic-period identification model is established and solved using an improved sparrow search algorithm to balance the timeliness and accuracy of risk assessment. By incorporating chaotic initialization, Gaussian mutation, and adaptive weighting mechanisms, this algorithm enhances population diversity and balances global search capability with local optimization capability across different solution stages, thereby improving the solution efficiency and accuracy of the model. Finally, the case study preliminarily demonstrates that the proposed method can characterize the temporal-scale differences among risk factors and shows potential for engineering application under the available enterprise data. Full article

Gases are prone to accumulating in mines. Untimely gas drainage can easily trigger gas outbursts, which may further lead to gas explosions, directly endangering personnel lives and mine safety. Therefore, gas control during gob-side entry driving (roadway excavation adjacent to the goaf) in high-gas mines is crucial to ensuring successful and safe mining and excavation. The 110505 track haulage gateway is a typical high-gas gob-side driving gateway. The measured maximum gas content of the lower No.5 coal seam is 6.0289 m³/t. At present, without a scientific basis for optimizing core parameters, such as the spacing and diameter of gas drainage boreholes, gas drainage is incomplete, and triangular gas pressure zones are likely to form between boreholes. As a result, the risk of gas accumulation is high. This not only exacerbates the danger of unpredicted gas outbursts but also seriously hinders the rapid excavation of the gateway and the progress of mining and further excavation. Based on a mechanical framework coupling coal seam and methane migration, and focusing on the relationships between factors such as borehole spacing, borehole aperture, methane drainage duration, and overall gas drainage efficiency, a model incorporating dual pore distribution and unified permeability characteristics was constructed. Numerical modeling was performed using the COMSOL Multiphysics platform to examine the influences of different borehole spacings and apertures on underground gas drainage in coal seams. The results indicate that reducing borehole spacing contributes to a more pronounced decline in gas pressure and a lower peak pressure between neighboring boreholes. When an interval spacing of 0.3 m was adopted for the drilling layout arrangement, the peak gaseous potential within the surrounding rock matrix dropped to 0.48 MPa following continuous drainage over a duration of 20 days, a reduction of 44%, and there was no obvious triangular zone of pressure. In contrast, borehole diameter had a minor effect on gas drainage efficiency, and the maximum gas pressure after 20 days was less than 0.52 MPa under different borehole diameters. This work establishes a theoretical foundation and offers practical guidance for high-efficiency gas drainage during gob-side entry driving, which is of vital importance for achieving safe and rapid excavation in high-gas mines. Full article

Background and Objectives: Peripheral artery disease (PAD) is a common manifestation of systemic atherosclerosis associated with significant morbidity and mortality, yet it remains underdiagnosed due to limited routine screening and its often-asymptomatic presentation. Although the ankle–brachial index (ABI) is the gold standard diagnostic tool for PAD, its use may be limited in some settings because it requires specialized equipment and trained personnel. In contrast, the electrocardiogram (ECG) is widely available and routinely performed. Given that ECG abnormalities may reflect systemic cardiovascular disease, we investigated the association between ECG findings and ABI classification. Materials and Methods: This retrospective case–control study analyzed patients with and without PAD who received care from outpatient vascular clinics between March 2018 and February 2022. PAD was defined as ABI ≤ 0.9 or toe–brachial index ≤ 0.67 with abnormal pedal pulses. The most recent ECG performed within one year of ABI measurement was retrieved for each patient and classified as normal, borderline, or abnormal according to standardized guideline recommendations. The association between ECG category and ABI classification was assessed using chi-square testing and multivariable logistic regression adjusted for age and sex, with results reported as odds ratios (ORs) and 95% confidence intervals (CIs). Discriminatory performance of the ability of ECG findings to predict ABI classification was evaluated using the area under the receiver operating characteristic curve (AUROC) with 95% CI. Model calibration was assessed using the Hosmer–Lemeshow test. Results: Overall, 491 patients had paired ECG and ABI data. ECGs were categorized as abnormal (n = 345), borderline (n = 58), or normal (n = 88). The prevalence of abnormal ABI (≤0.9) was highest among patients with abnormal ECGs (45.8%), compared to borderline (34.5%) and normal ECGs (28.4%) (p = 0.0067). On multivariable logistic regression analysis adjusted for age and sex, abnormal ECG findings were associated with increased odds of abnormal ABI compared to normal ECGs (adjusted OR 2.07, 95% CI 1.24–3.46, p = 0.005), whereas borderline ECGs were not (OR 1.31, 95% CI 0.64–2.68, p = 0.455). ECG categorization demonstrated moderate discrimination (AUROC 0.73, 95% CI 0.68–0.78) and good calibration (Hosmer–Lemeshow χ² 5.0, p = 0.76) for predicting abnormal ABI. Conclusions: In this retrospective case–control study, we found an association between abnormal ECG findings and abnormal ABI. These results support the concept that clinically significant ECG abnormalities may reflect systemic atherosclerotic burden rather than isolated cardiac pathology. Given the widespread availability and low cost of ECG testing, ECG interpretation may help identify patients who warrant further investigations, including PAD screening, vascular assessment, and risk-stratification, particularly in lower-resource settings without routine access to ABI testing. Prospective, multicenter studies are needed to validate these findings. Full article

On-site withstand voltage testing is essential for evaluating insulation performance and detecting defects in UHV AC equipment; however, existing safety distance criteria are mainly based on empirical experience or extrapolated from low-altitude and lower-voltage conditions, limiting their applicability. To address this issue, a systematic framework for safety distance calculation and altitude correction is developed. The selection principles and circuit configuration of the test system are analyzed to clarify the constraints between power capacity and tuning under high-voltage, large-capacity conditions. Based on air-gap discharge characteristics, a minimum safety distance model is established for the 1000 kV main transformer with respect to grounded structures and personnel. Meteorological factors and proximity effects are further incorporated to propose correction methods and on-site zoning strategies. Results indicate that a baseline safety distance of approximately 10 m is appropriate at altitudes up to 1000 m, and the model captures the nonlinear degradation of insulation strength in long air gaps at higher altitudes. A case study at 3620 m yields a minimum safety distance of 16.4 m, providing a quantitative basis for safe UHV AC on-site testing under varying altitude conditions. Full article

Background: Coronary angiography and percutaneous coronary intervention are essential procedures for managing coronary artery disease but expose patients and healthcare personnel to ionizing radiation. Radiation exposure varies with procedural complexity and vascular access route, and repeated occupational exposure in catheterization laboratories (cath-labs) has been linked to serious health hazards among operators. Objectives: Given the high procedural volume and limited routine monitoring at Bangladesh Medical University (BMU), Bangladesh, this study aimed to quantify operator radiation exposure and identify factors influencing radiation dose. Methods: This analytical cross-sectional study was conducted from November 2023 to April 2024 in two cardiac cath-labs at BMU using two Siemens Axiom Artis angiography systems. Patient, operator, and procedural data, including demographics, operator experience, procedure type, vascular access route, fluoroscopic view, procedure duration, and radiation exposure, were collected from randomly selected routine procedures. Operator radiation exposure was measured at four working positions using a dosimeter, and cumulative annual exposure was estimated based on procedural workload. Descriptive, univariable, and multivariable analyses were performed to identify factors associated with radiation exposure. Results: The study analyzed 776 procedures, in which most patients were aged 46–65 years and male. The majority of procedures were coronary angiography performed via the femoral route. On average, each procedure required 14.28 fluoroscopic views and lasted 8.16 min, with a mean radiation exposure of 1034.5 mGy. Procedural complexity, radial access, and stent use were associated with higher fluoroscopic views, longer procedure time, and increased radiation exposure. Multivariable analysis showed that procedure type and stent number are primarily determinants for the number of fluoroscopic views, while procedure time was mainly driven by imaging demand and vascular access route. Radiation exposure was strongly associated with both procedure time and the number of views, and was higher among male and older patients but slightly lower with femoral access and among older operators. Direct measurements showed higher radiation levels near the operator’s X-ray beam, while estimated annual operator exposure remained low inside the lead apron (0.03–0.05 mSv) compared with outside the lead apron (0.6–1.1 mSv), which is within the limit of internationally accepted cumulative absorbed radiation. Conclusions: This study provides the first comprehensive evaluation of operator radiation exposure in a cardiac cath-lab in the country and the wider region. Procedural characteristics, particularly fluoroscopy use and procedural complexity, were the primary determinants of radiation exposure, while effective shielding and increased distance substantially reduced operator dose. These findings highlight the importance of imaging optimization and consistent implementation of the ALARA principle through structured radiation safety training and careful procedural planning to further minimize occupational exposure. Full article