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Assessing the impact of human error factors on railway accident severity: Evidence from accident investigation reports in Korea
This study investigates the role of human error factors in shaping the severity of railway accidents. Using a structured coding scheme to transform qualitative accident investigation reports into quantitative variables, the analysis reveals that deficiencies in managerial oversight, shortcomings in maintenance practices, and failures in equipment and system reliability are consistently associated with higher accident costs. These findings underscore the organizational and technical dimensions of human error as critical factors linked to accident severity, rather than merely front line worker mistakes. At the modeling level, the explanatory variables collectively account for a meaningful portion of the variation in accident costs, indicating that such outcomes are not purely random but systematically related to underlying human and organizational conditions. By identifying the relative importance of managerial, maintenance, and equipment-related deficiencies, this study provides empirical evidence for prioritizing these factors in railway safety management. The results highlight the need to strengthen organizational accountability, improve maintenance regimes, and ensure the reliability of technical systems as essential strategies for mitigating high-consequence accidents. These insights contribute to a deeper understanding of the organizational and systemic correlates of accident severity and can inform targeted interventions aimed at enhancing overall railway safety.
Risk assessment for type 2 diabetes mellitus and its association with knowledge and health beliefs among university students in three Arab countries
Abstract Type 2 diabetes mellitus (T2DM) is a growing concern in the Arab world, with university students increasingly at risk due to lifestyle factors. This study aims to assess T2DM risk, knowledge, and beliefs among university students aged ≥ 18 years in Egypt, Saudi Arabia, and Yemen. A multinational, cross-sectional study was conducted from January to April 2025 among university students aged ≥ 18 years in Egypt (lower-middle-income), Saudi Arabia (high-income), and Yemen (low-income). A multistage, stratified purposive sampling technique was used to recruit students equally from medical and non-medical faculties in at least three universities per country. Data were collected via structured, interview-based questionnaires consisting of four components: (1) socio-demographic and anthropometric data; (2) the Diabetes Knowledge Questionnaire-18 (DKQ-18); (3) the Health Belief Model Scale (HBMS); and (4) the validated Arabic version of the Australian type 2 diabetes risk assessment tool (AUSDRISK). Among 2787 university students, the mean age was 21.0 years, with the majority being female (74.9%), and enrolled in medical faculties (58.2%). Diabetes knowledge was significantly higher in Egyptians (72.6% with good knowledge) compared to Saudis (63.9%) and Yemenis (59.8%) ( p < 0.001). Health beliefs followed a similar trend, while diabetes risk was significantly higher among Yemeni students (22.0% with severe risk; p < 0.001). Multiple regression analysis revealed that a higher academic year was a positive predictor of both diabetes knowledge (β = 0.155, p < 0.001) and health beliefs (β = 0.152, p < 0.001), and was negatively associated with diabetes risk (β = − 0.061, p < 0.001). Medical faculty enrollment was also positively associated with knowledge (β = − 0.411 for non-medical faculty, p < 0.001) and beliefs (β = − 0.228 for non-medical faculties, p < 0.001). Parental education and income were positively associated with knowledge and beliefs. Specifically, father’s higher education predicted greater knowledge (β = 0.047, p < 0.001), and household income was a significant predictor of both knowledge (β = 0.042, p < 0.001) and beliefs ( p < 0.001). In contrast, diabetes risk was independently associated with male gender (β = 0.305, p < 0.001), older age (β = 0.123, p < 0.001), higher BMI (β = 0.284, p < 0.001), and Yemeni nationality (β = 0.080, p < 0.001). Marked differences in diabetes risk, knowledge, and beliefs were observed among students from the three countries. Interventions targeting high-risk groups are essential to improve diabetes awareness and prevention in young adults. Countries like Yemen may benefit from urgent preventive measures, while countries with moderate risk profiles may focus on health promotion and sustained education to avert future disease burdens.
Association of long-term exposure to air pollution with sleep among middle-aged and older adults in China: A nationwide study from 2015 to 2018
Background This study aims to evaluate the associations of long-term exposure to five major air pollutants (PM 2.5 , PM 10 , NO 2 , SO 2 , and CO) with sleep duration and quality among middle-aged and older Chinese adults. Methods This study used data from 14856 adults aged 45 and above participating in the China Health and Retirement Longitudinal Study (CHARLS). Changes in nocturnal sleep duration between baseline (2015) and follow-up (2018) were categorized into three groups: reductions ≥1 h, 1.5 h, or 2 h. The increase in the number of days with restless sleep at follow-up was defined as a deterioration in sleep quality. We used the STET model to estimate air pollution exposure and calculate the concentration differences over 1- or 2-year periods preceding each interview. We investigated the associations of exposure differences to five pollutants with sleep duration and quality through generalized linear mixed and ordinal logistic regression models. Interaction analyses were employed to identify potential effect modifiers. Results All 1-year exposure differences to air pollution positively correlated with reductions in sleep duration of both ≥1.5 h and ≥2 h. CO exposure demonstrated the highest risk for a ≥ 1.5 h reduction (OR = 1.451; 95% CI: 1.065–1.975) and a ≥ 2 h reduction (OR = 1.557; 95% CI: 1.135–2.135) per 1 μg/m 3 increment. Higher exposure levels to PM 2.5 , PM 10, NO 2 and SO 2 correlated with elevated risks of sleep quality deterioration. NO 2 exposure demonstrated the highest risk, with a 22.3% higher risk per 10 μg/m 3 increment (95% CI: 1.039–1.439). Pollutants affected sleep duration and quality in varying temporal patterns. Overall, 1-year exposure difference considerably impacted the sleep duration, while 2-year exposure difference significantly impacted the sleep quality. We also found that the air pollution’s adverse impacts on sleep quality were especially significant for those living in urban areas. Conclusion Long-term exposure to air pollution is associated with adverse sleep outcomes in middle-aged and older populations.
pH profiling reveals progressive wound acidification during healing and higher pH in chronic non-healing wounds: a prospective, multicenter cohort study
Abstract The local microenvironment of wounds plays a crucial role in healing, with pH and temperature emerging as promising biomarkers. This prospective, multi-center, observational study assessed pH and temperature in acute and chronic wounds to identify physicochemical patterns associated with healing. A total of 117 patients with various wound etiologies underwent 226 pH and 181 temperature measurements at the wound center, edge, and surrounding skin. With a pH of 7.113 ± 0.659 and 7.043 ± 0.694, chronic and non-healing wounds exhibited significantly higher pH values than acute (6.592 ± 0.617) and healing wounds (6.820 ± 0.814; p <.05), with the wound center showing the largest difference (Δ pH = 0.52). A pH gradient was observed, decreasing from wound center to surrounding skin. Longitudinal analysis revealed a weekly pH decline of 0.05 units in healing wounds. Temperature showed a similar downward trend over time, though differences between groups were less pronounced. These findings indicate that progressive acidification of the wound environment correlates with healing, while alkaline pH is associated with chronicity and infection. Local pH, more so than temperature, may serve as a non-invasive, dynamic biomarker for wound monitoring and as a potential therapeutic target. Further interventional studies are warranted to evaluate pH-monitoring and potential modulation by wound therapies.
Measuring cerebral glucose metabolism by chemical exchange-sensitive spin-lock (CESL) MRI of 2-deoxy-D-glucose in rodents
Magnetic resonance imaging (MRI) of glucose metabolism shows significant potential for identifying disease biomarkers and monitoring therapeutic responses in neurological conditions. Here, we present a protocol utilizing chemical exchange-sensitive spin-lock (CESL) MRI with the glucose analogue 2-deoxy-D-glucose (2DG) in the rat brain. We employed this method to characterize metabolic changes in ischemic tissue in a rat model of stroke. However, the utility of the technique is not limited to stroke and may be adapted to other disease models with minimal modifications. Previous research has demonstrated that CESL MRI is sensitive to various glucose analogs, including regular D-glucose, which is suitable for human application. Consequently, our protocol provides a foundation for a wide range of future applications in both basic and translational research, with potential utility in animal models and, eventually, human studies.
Synthesis, Crystal Structure, and Enantiomeric Resolution of a Chiral (18,15) Carbon Nanobelt
ABSTRACT Chiral carbon nanotubes (CNTs) show significant potential for applications in electronics and optics, yet the selective synthesis of single‐chirality CNTs remains a major challenge. Furthermore, enantiopure chiral carbon nanobelts, which constitute conjugated segments of chiral CNTs, have not been reported to date. Here, we present the first synthesis and successful enantiomeric resolution of a chiral (18,15) carbon nanobelt, representing a sidewall segment of the corresponding (18,15) CNT. Single‐crystal x‐ray diffraction analysis unambiguously confirms its belt‐shaped structure and the presence of a pair of enantiomers. Both enantiomers have been successfully isolated, and further studies reveal notable chiroptical properties.
Influence of environmental conditions, operational procedures, and filter material on robotic gravimetric weighing of particulate matter filters
Ensuring end-to-end privacy in IoT-based healthcare systems through hyperledger fabric and identity mixer
Healthcare information is often sensitive and confidential, and any unauthorized disclosure can jeopardize patient privacy. Centralized approaches currently used to protect patient information are vulnerable to a single point of failure and the risk of data breaches from central servers. Conversely, distributed blockchain-based methods tend to focus only on safeguarding data privacy for certain segments of the communication path from sensors to end users. This leaves a gap in methodologies that ensure both location and data privacy throughout the entire communication from sensors to healthcare data users via blockchain technology. In this paper, we propose using Hyperledger Fabric to ensure the immutability of patient data and to address the single point of failure issue. Additionally, to maintain end-to-end data and location privacy, our proposed scheme integrates the Idemix protocol suit alongside Hyperledger Fabric and employs a lightweight communication protocol for interactions between healthcare sensors and gateways. Compared to previous methods, our approach not only facilitates privacy features such as patient anonymity and untraceability but also guarantees data integrity, confidentiality, mutual authentication, and resilience against a variety of security threats, including collusion among internal entities. While the implementation of blockchain may introduce additional computational overhead for service providers compared to centralized systems, this trade-off is outweighed by the significant enhancements in security as evidenced by our analyses and evaluations.
The fluoroquinoline compound exerts anti-erythroleukemic effects by dual-targeting GLUT1 and the PI3K/AKT signaling pathway
Effects of two side-by-side camera trap deployments on estimations of richness, abundance, and the detection of medium- and large-sized mammals
Medium- and large-sized mammals play key ecological roles but remain difficult to monitor due to low detectability and logistical constraints. Camera traps are widely used to address these challenges; however, survey outcomes are strongly influenced by sampling design. In this study, we evaluated how deploying two side-by-side camera traps per site, compared with a single-camera configuration, affects sampling efficiency and information gain in a small-scale monitoring grid. We quantified differences in detected species richness, number of photographic records, and time to first detection between single- and double-camera deployments. Using two cameras per site significantly increased detected species richness and the number of records per species and reduced time to first detection. Survival analyses showed that detection occurred more than twice as fast under the double-camera design, with particularly strong gains for rarely detected species. Comparisons with a conservative single-camera scenario further highlighted the risk of delayed or missed detections under limited sampling effort. Rather than testing novel ecological hypotheses, our results provide empirically grounded guidance on how site-level camera-trap deployment choices influence detection efficiency, inventory completeness, and the reliability of commonly used biodiversity metrics.
Effect of change-of-direction vs. linear repeated sprint training on physical performance in female college basketball players
Major Trauma Triage Study (MATTS): Diagnostic accuracy of major trauma triage tools in English regional trauma networks – A case-cohort study
Background Major trauma is a leading cause of death and disability. Specialised care in major trauma centres has been associated with improved outcomes and prehospital triage tools are used to ensure injured patients are treated in the right place and the right time. However, there is a trade-off between under- and over-triage, and this study aimed to externally validate current and newly developed major trauma triage tools. Methods A diagnostic case-cohort study was performed between November 2019 and February 2020 in 4 English regional trauma networks as part of the Major Trauma Triage Study (MATTS). The accuracy of 22 adult major trauma triage tools, including 3 newly developed MATTS tools was evaluated. Consecutive patients with acute non-trivial injury presenting to participating ambulance services were included and matched to data from the English national major trauma database. Theoretical accuracy was examined, with index tests assessed according to objective ambulance service data, regardless of the final triage decision or hospital destination. The primary reference standard was a consensus definition of serious injury that would benefit from expedited major trauma centre care. Results The case-cohort sample consisted of 2,607 patients, including 928 primary reference standard positive patients. The population weighted prevalence of major trauma meeting the primary reference standard definition was 3.1% (95% CI 2.3–4.0). Four optimally performing triage tools were identified with Pareto decision analysis: the Trauma score (sensitivity 0.1, specificity 0.99), MATTS specific tool (sensitivity 0.37, specificity 0.95), MATTS balanced tool (sensitivity 0.58, specificity 0.87), and the MATTS sensitive tool (sensitivity 0.72, specificity 0.76). This finding was unchanged in subgroup analyses of different age-groups and injury mechanisms; secondary analyses examining alternative reference standards (ISS ≥ 16, US consensus definition); and sensitivity analyses exploring missing data. Conclusions Four optimal triage tools, demonstrating a trade-off between sensitivity and specificity, were identified by this validation study. The choice of ideal tool will depend on prevalence of major trauma, and valuation of false positive and false negative cases. Further prospective investigation of real-life triage tool performance, including compliance and clinical judgment, is necessary.
Numb mitigates intestinal epithelial cell senescence induced by radiation through a PLK1-dependent pathway
Correction: Single-item versus scale: Comparing respondent demographic, social, and health characteristics by measure of loneliness using the Canadian Longitudinal Study on Aging (CLSA) data
Multi-omics and network pharmacology reveal the mechanisms of Scutellaria barbata D.Don and Scleromitrion diffusum (Willd.) R.J.Wang against pancreatic cancer
A spatio-temporal self-supervised meta-learning network with dynamic graph learning for traffic flow forecasting
Accurate traffic flow prediction is essential for alleviating urban congestion, improving road network efficiency, and sup-porting sustainable transportation systems. Existing spatio-temporal graph neural networks, however, often struggle to capture dynamically evolving spatial dependencies, effectively integrate spatio-temporal features, and generalize across diverse traffic scenarios. To address the challenges of accurately modeling complex spatio-temporal dependencies in traffic flow forecasting, this study proposes a Spatio-Temporal Self-Supervised Meta-Learning Network (SSML-Net), the model comprises spatial- and temporal-level learners, and integrates self-supervised meta-learning with meta-learning-driven feature fusion and gated coupling mechanisms to enhance spatio-temporal interaction and generalization capabilities. Comprehensive experiments on the PeMS datasets demonstrate that SSML-Net clearly outperforms traditional statistical approaches, deep temporal models, and spatio-temporal graph-based networks. The ablation study validated the effective-ness and necessity of the model’s core components, whilst the small-sample experiments demonstrated its robustness and generalisation capabilities under extreme data conditions. Concurrently, we expanded our training and evaluation experi-ments based on METR-LR and Beijing traffic data, further validating the model’s exceptional transfer learning capability and generalisation performance in cross-domain traffic forecasting scenarios. This approach not only achieved superior prediction accuracy but also substantially reduced model training costs. These results indicate that SSML-Net adapts to varying data scales and dynamic urban scenarios, providing a robust, adaptive, and high-precision spatio-temporal traffic flow prediction framework.
Rapid Assignment of Chemical Shifts From Crystal Structures in Solid‐State NMR
ABSTRACT Chemical shift assignment in solid‐state nuclear magnetic resonance (NMR) is a challenging process that usually relies on a set of 1D and 2D experiments to determine the assignment by establishing connectivities along the covalent backbone. A Bayesian probabilistic assignment method was recently introduced based on a fragment analysis using a database of chemical shifts. Here, we propose a fast 3D structure validation method that utilizes predictions from a crystal structure as a starting point for Bayesian probabilistic chemical shift assignment. We demonstrate the approach with improved confidence in the 1 H and 13 C assignments for the structures of cocaine and Atuliflapon, and finally Lorlatinib which has Z′ = 2.
Neuroimaging insights from Wistar-Kyoto rats under chronic mild stress: morphological and metabolic brain correlates of treatment-resistant depression
Exploring the effectiveness of podcasts in improving sexual health among young people: Findings from a qualitative study
Background Sexual health promotion among young people remains an urgent global priority. Despite robust public health systems, young people living in Australia continue to experience unmet needs in sexual health promotion due to cultural stigma, lack of relatable content, and insufficient inclusivity for marginalised populations. Podcasts are gaining attention as a flexible, relatable medium that may address these gaps, yet little research has explored their effectiveness in sexual health promotion from young people’s perspectives. This study aimed to explore how the On The Couch podcast supports young people’s sexual health. Methods This qualitative study conducted five focus groups with 18 participants aged 18–24 residing in Australia who had listened to the On The Couch sexual health podcast. Participants were recruited via university channels, social media, and podcast platforms, and reflected diverse cultural and educational backgrounds. Data collection involved semi-structured focus groups conducted both online and face-to-face. Transcripts were analysed using Braun and Clarke’s thematic analysis approach to identify themes and sub-themes. Ethical approval was granted by the Greater Western Human Research Ethics Committee (Reference: 2023/ETH02655) with ratification from the University of Technology Sydney Medical Research Ethics Committee. Results Three major themes emerged from the analysis: (1) Podcasts significantly improved knowledge and shifted attitudes toward sexual health through relatable storytelling and emotional resonance. However, translating awareness into sustained behavioural change remained challenging, largely due to cultural and structural barriers. (2) Young people valued podcasts for their conversational tone, accessibility, and convenience, but highlighted the need for multimodal enhancements such as visual aids and transcripts. (3) Participants offered specific recommendations for improving podcast design, advocating for increased youth co-creation, authentic narratives, interactive formats, and culturally sensitive content. Conclusions The study demonstrates that podcasts hold considerable promise for youth-focused sexual health promotion by providing relatable, emotionally engaging content. However, their effectiveness in changing behaviour is contingent upon addressing cultural barriers. Future podcasts should be developed with young people as co-creators, ensuring content aligns closely with their lived experiences, learning preferences, and social realities. This approach may enhance the role of podcasts as an effective medium in digital sexual health promotion.