Search Results (20,745)

Education and post-licencing training programmes for novice drivers are widely implemented to improve road safety, yet their effectiveness remains debated. This study evaluates short-term attitudinal changes relating to participation in a mandatory post-licencing training programme for novice drivers in Slovenia. A within-subject pre–post survey methodology was used to evaluate self-reported driving attitudes across six safety-related domains among 225 novice drivers at a Slovenian driving training centre in 2024. Paired t-tests revealed minor yet statistically significant improvement following the programme in perceived support for the additional driver training, lowered overconfidence, heightened care in speeding and intersection behaviour, and enhanced attitudes towards vehicle operation and utilization of safety equipment. Attitudes regarding attention and adherence to traffic regulations showed negligible shifts, indicating a strong baseline attitude towards safe driving. The findings indicate a modest but fairly consistent short-term change in attitudes after programme participation. Due to the lack of a control group and dependence on self-reported data, the findings should be seen as evaluative rather than causative, necessitating more longitudinal and behavioural research to evaluate long-term and behavioural effects. Full article

Artificial intelligence (AI) is now embedded across many aspects of healthcare, yet most implementations remain fragmented, task-specific, and layered onto legacy workflows. This paper does not review AI applications in healthcare per se; instead, it examines what an AI-first healthcare system would look like, one in which AI functions as a foundational organizing principle of care delivery rather than an adjunct technology. We synthesize evidence across ambulatory, inpatient, diagnostic, post-acute, and population health settings to assess where AI capabilities are sufficiently mature to support system-level integration and where critical gaps remain. Across domains, the literature demonstrates strong performance for narrowly defined tasks such as imaging interpretation, documentation support, predictive surveillance, and remote monitoring. However, evidence for longitudinal orchestration, cross-setting integration, and sustained impact on outcomes, costs, and equity remains limited. Key barriers include data fragmentation, workflow misalignment, algorithmic bias, insufficient governance, and lack of prospective, multi-site evaluations. We argue that advancing toward AI-first healthcare requires shifting evaluation from accuracy-centric metrics to system-level outcomes, emphasizing human-enabled AI, interoperability, continuous learning, and equity-aware design. Using hypertension management and patient journey exemplars, we illustrate how AI-first systems can enable proactive risk stratification, coordinated intervention, and continuous support across the care continuum. We further outline architectural and governance requirements, including cloud-enabled infrastructure, interoperability, operational machine learning practices, and accountability frameworks—necessary to operationalize AI-first care safely and at scale, subject to prospective validation, regulatory oversight, and post-deployment surveillance. This review contributes a system-level framework for understanding AI-first healthcare, identifies priority research and implementation gaps, and offers practical considerations for clinicians, health systems, researchers, and policymakers. By reframing AI as infrastructure rather than isolated tools, the AI-first approach provides a pathway toward more proactive, coordinated, and equitable healthcare delivery while preserving the central role of human judgment and trust. Full article

Due to a number of advantages, such as the high power-to-weight ratio of the system, the possibility of easy control and the freedom of arrangement of the system components on the machine, hydrostatic drive is one of the most popular methods of machine drive. The actuators in such a system are hydraulic cylinders that convert fluid pressure energy into mechanical energy for reciprocating motion. One disadvantage of conventional actuators is their weight, so research is being conducted to make them as light as possible. Directions for this research include the use of modern engineering materials such as composites and plastics. This paper presents the possibility of using new lightweight yet strong materials for the design of a hydraulic cylinder. The base of the hydraulic cylinder were designed and subjected to FEM numerical analyses. The base was made of PET. In addition, a composite cylinder made of wound carbon fibre was subjected to numerical analyses and experimental validation. The numerical calculations were verified in experimental studies. To improve the reliability of the numerical calculations, the material parameters of the composite materials were determined experimentally instead of being taken from the manufacturer’s data sheets. The composite cylinder achieved a weight reduction of approximately 94.4% compared to a steel cylinder (95.5 g vs. 1704 g). Under an internal pressure of 20 MPa, the composite cylinder exhibited markedly higher circumferential strain (4329 μm/m) than the steel cylinder (339.6 μm/m), and axial strain was also greater (−1237 μm/m vs. −96.4 μm/m). Full article

Background: Vitamin E has been studied for its role in reducing the growth of colorectal cancer (CRC). CRC is a worldwide health concern. A meta-analysis reported that CRC patients have a lower concentration of serum vitamin E, suggesting it to be a risk factor. Although rodent models are widely used in disease research, their application in studying vitamin E as a preventive or therapeutic agent in CRC is not well characterized. To address this gap, we conducted a scoping review to examine the available evidence, adhering to the PRISMA-ScR checklist. Methods: We searched PubMed, Google Scholar, Scopus, and Web of Science (WoS) for full-text English original articles published before May 2024, using Medical Subject Headings (MeSH) terms and free text. The following search string strategy was applied: (Vitamin E OR tocopherol$ OR tocotrienol$) AND (Colo$ cancer OR colo$ carcinoma) AND (Rodentia OR mouse OR Rodent$ OR mice OR murine OR rats OR guinea OR rabbit OR hamsters OR Animal model OR Animal testing OR animals) AND (neoplasm$ OR “tumor mass” OR tumor volume OR tumor weight OR tumor burden). Data were charted into five categories using a standardized, pretested form. The charted data were synthesized using descriptive and narrative methods. Conclusions: This study highlights that γ- and δ-tocopherols, as well as δ-tocotrienol and its metabolites, were reported to reduce tumor volume and formation in various rodent models. While these results are promising, this scoping review identifies a need for further research to address translational barriers such as dosing, bioavailability, and long-term safety before clinical application. Full article

The ecological network serves as a vital spatial strategy for addressing climate change, biodiversity loss, and habitat fragmentation. Addressing limitations in existing ecological network studies—such as strong subjectivity and insufficient accuracy in structural element identification, cross-regional integration, and resistance surface weighting—this research uses the Zhengzhou–Kaifeng–Luoyang region (ZKLR) as a case study. It introduces the self-organizing map (SOM) model to identify ecological sources and employs the XGBoost-SHAP model to optimize resistance surface weights, thereby reducing subjective weighting biases. Subsequently, the Linkage Mapper tool is utilized to construct the regional ecological network. The superiority of the SOM model for identifying ecological sources was confirmed by comparison with a traditional network based on morphological spatial pattern analysis (MSPA). Further integrating complex network topology theory, nodes attack the simulations-assessed network resilience and proposed optimization strategies. The results indicate the following: (1) The area of ecological sources identified by the SOM model is three times that of the MSPA model; (2) SHAP feature importance analysis revealed that elevation (DEM) exerted the greatest influence on the composite resistance surface, contributing over 40%, followed by land use and slope, with each contributing approximately 15%. High-resistance areas were primarily distributed in western and central mountainous regions and built-up urban areas, while low-resistance areas were concentrated in the central and eastern plains; (3) topological analysis indicates that the integrated ecological network (IEN) exhibits superior robustness compared to the structural ecological network (SEN). The edge-adding strategy generated 22 additional ecological corridors, significantly enhancing the overall resilience of the integrated ecological network; and (4) based on ecological network construction and optimization results, a territorial spatial protection strategy of “one belt, two cores, two zones, and three corridors” is proposed. This study provides a novel methodological framework for ecological network construction, with findings offering reference for ecological conservation and spatial planning in the ZKLR and similar areas. Full article

The article presents issues related to fossil fuel energy consumption and CO₂ emissions from motor vehicles. It identifies the main areas of research in this field in the context of motor vehicles, namely driver behavior, fuel consumption, and OBD systems. The research sample consisted of experimental data containing records of a series of test drives conducted with a passenger vehicle equipped with a gasoline-powered internal combustion engine, collected via an OBD diagnostic interface. Three subsets related to engine operation and energy demand patterns were distinguished for the study: during vehicle start-up and low-speed driving (vehicle start-up mode), during urban driving, and during extra-urban driving. Multiple regression models were constructed for the analyzed subsets to predict CO₂ emissions based on engine energy output parameters (power, load) and vehicle kinematic parameters. The developed models were subjected to detailed evaluation and mutual comparison, taking into account their predictive performance and the interpretability of the results. The analysis made it possible to identify the variables with the most substantial impact on CO₂ emissions and fuel energy consumption. The models allow individual drivers to monitor and optimize vehicle energy efficiency in real-time. The extra-urban driving model achieved the highest predictive accuracy, with a mean absolute error (MAE) of 19.62 g/km, which makes it suitable for real-time emission monitoring during highway driving. Full article

Compared to traditional marine productivity, marine new-quality productivity (MNQP) is composed of advanced productive forces driven by the deepening application of new technologies, is characterized by the rapid emergence of new industries, new business models, and new modes of operation, and is marked by a substantial increase in total factor productivity in the marine economy. It has, therefore, become a new engine and pathway for China’s development into a maritime power. The main research approaches and conclusions of this paper are as follows: ① Using a combined order relation analysis method–Entropy Weight Method (G1-EWM) weighting method that integrates subjective and objective factors, we measured the development level of China’s MNQP from 2006 to 2021 across two dimensions: “factor structure” and “quality and efficiency”. The findings indicate that China’s MNQP is developing robustly and still holds considerable potential for improvement. ② Utilizing Gaussian Kernel Density Estimation and Spatial Markov Chain analysis to examine the dynamic evolution of China’s MNQP, the study identifies breaking the low-end lock-in of MNQP as crucial for accelerating balanced development. Spatial imbalances in China’s MNQP may exist both at the national level and within the three major marine economic zones. ③ To further examine potential spatial imbalances, Dagum Gini decomposition was employed to assess regional disparities in China’s MNQP. The DER polarization index and EGR polarization index were used to analyze spatial polarization levels, revealing an intensifying spatial imbalance in China’s MNQP. ④ Finally, geographic detectors were employed to identify the factors influencing spatial imbalances in China’s MNQP. Results indicate that these imbalances result from the combined effects of multiple factors, with marine economic development emerging as the core determinant exerting a dominant influence. The core conclusions of this study provide theoretical support and practical evidence for advancing the enhancement of China’s MNQP, thereby contributing to the realization of the goal of building a maritime power. Full article

Background/Objective: Current treatments for peripheral nerve injury (PNI) lack robust evidence to suggest complete recovery; hence, alternative therapeutics offer new opportunities to develop more effective protocols. Mushroom species and their related components are considered potential candidates for peripheral nerve repair, but their specific effects and underlying mechanisms are not fully understood. This systematic review presents the available evidence on the use of mushroom species for PNI therapy, including the bioactive components and mechanisms of action. Methodology: A comprehensive literature search in three databases (PubMed, Scopus, and Google Scholar) led to the synthesis of 11 records published between 2010 and 2024. Qualitative analysis revealed the neuroregenerative potential of four mushrooms: Amanita muscaria (n = 2), Hericium erinaceus (n = 5), Lignosus rhinocerotis (n = 3), and Flammulina velutipes (n = 1), with aqueous extracts as the most common type of ingredients used (n = 4) relative to specific components such as muscimol, polysaccharide, Erinacine S, and nerve-guided conduits (NGCs). Results: These mushroom-derived treatments enhanced the migration of Schwann cells mainly via the FGF-2 signalling and MAPK pathway. In vivo studies also revealed the ability of H. erinaceus, A. muscaria, and L. rhinocerotis to promote peripheral nerve repair and functional recovery, with evidence suggesting the role of neurotrophic factors, anti-apoptotic signalling, and pro-inflammatory substances. H. erinaceus was identified as the most promising for potential clinical applications, given the stronger evidence-based data and its relatively safer components compared to A. muscuria and other mushroom species. Conclusions: Despite presenting the potential use of mushrooms in managing PNIs, the existing approaches need to be subjected to clinical research to accelerate the development of future therapeutics and preventive measures for PNIs. Full article

Short-range internal timing supports coordinated movement, attention, and physiological regulation, yet distortions of time experience are frequently reported across clinical and high-arousal states. Patients with anxiety or acute stress often describe an apparent acceleration of time, whereas depressive states are more commonly associated with a slowing of subjective time. Neurological conditions, including Parkinson’s disease and epilepsy, further demonstrate alterations in temporal processing that cannot be reduced to a single mechanism. This narrative review synthesizes evidence from experimental timing paradigms, subjective passage-of-time judgments, and chronobiological approaches to examine how internal timing varies across biological states. In this study, we highlight the distinction between experiential time distortion and performance-based interval timing and discuss how task characteristics, arousal level, and neural context contribute to heterogeneous findings. Historical and methodological foundations are reviewed, including early chronobiological work linking subjective time estimation to biological rhythms. The reviewed evidence suggests that many timing distortions observed in stress-related, affective, and neurological conditions reflect state-dependent reconfiguration rather than irreversible dysfunction. Framing timing variability as a potential marker of internal state may help reconcile inconsistent results across paradigms and inform future clinical and translational research on temporal processing. Full article

Background/Objectives: Caffeine is a well-established ergogenic aid in many strength- and endurance-based sports, but its efficacy in sport climbing remains underexplored despite the sport’s unique physical demands on grip strength, power, and muscular endurance. Therefore, this study examined the acute impact of a low caffeine dose (3 mg/kg) on climbing-specific performance, including pull-up and grip tests, in intermediate-advanced climbers. Methods: In a triple-blind, randomized, crossover design, thirteen male climbers (age: 28.2 ± 8.6 years) completed two experimental trials (caffeine vs. placebo). Performance was assessed via a pull-up one-repetition maximum (1RM) and power test at various loads, a pull-up muscular endurance test, and grip tests including maximum dead-hang time, maximum dead-hang strength, and rate of force development (RFD). Results: Caffeine did not significantly enhance performance in any measured variable. While a non-significant increase in peak power was observed at 80% 1RM (+8.0%, 95% CI: −0.232 to 0.304, p > 0.05, g = 0.348), effects at other loads and on pull-up endurance were trivial based on effect size (e.g., repetitions: +3.3%, 95% CI: −3.30 to 4.37, p = 0.292, g = 0.061). For grip metrics, caffeine was associated with a modest reduction in endurance time (+7.4%, p = 0.162, g = 0.171) and a slight increase in maximum strength (+2.4%, p = 0.060, g = 0.120). RFD was unaffected (p > 0.169, g < 0.13). Despite the lack of objective improvement, participants reported significantly greater subjective feelings of strength, energy, and alertness with caffeine (p < 0.05). Conclusions: A 3 mg/kg dose of caffeine, while altering psycho-physiological state, did not elicit statistically or practically meaningful ergogenic effects on pull-up or grip performance in climbers. Higher doses or sport-specific performance tests should be investigated in future research. Full article

Background: Craniocervical pain and temporomandibular disorders (TMDs) are prevalent, interconnected conditions. While Movement Representation Techniques (MRTs) are cognitive interventions targeting central pain mechanisms, their specific efficacy here lacks synthesis. This study systematically analyzes the effectiveness of MRTs, such as motor imagery (MI) and action observation (AO), on pain and function in individuals with craniocervical and orofacial pain. Methods: A systematic review of RCTs (PROSPERO: CRD420251155428) was conducted following PRISMA guidelines. Four databases were searched for studies applying MRTs (MI, AO, laterality discrimination) to adults with craniocervical or orofacial pain. Primary outcomes were pain and functionality. Methodological quality was assessed using the PEDro scale and Cochrane RoB 2 tool. Results: Eight RCTs (n = 362) were included. Methodological quality was high (PEDro scores 8–9). MRTs significantly increased Pressure Pain Threshold (PPT) in the masseter, trapezius, and cervical regions. Functional improvements included enhanced cervical range of motion and sensorimotor control. AO consistently demonstrated superior outcomes. However, results for orofacial variables were derived from asymptomatic subjects. Results for cervical muscle strength were inconsistent. Conclusions: MRTs, especially AO, show potential to reduce pain and improve function in craniocervical disorders. Evidence in symptomatic orofacial pain populations is non-existent. Protocol heterogeneity and limited research groups necessitate further high-quality, multicenter RCTs to establish robust clinical guidelines. Full article

This paper systematically investigated the mechanical behavior of welded-plate lifting lugs subjected to dynamic and eccentric loadings in steel structure hoisting applications. By integrating on-site stress monitoring throughout the hoisting process with finite element numerical simulations, the dynamic response characteristics of the lugs were comprehensively analyzed. The results indicated that the stress response followed a three-stage evolution comprising elastic growth stage, peak fluctuation stage, and gradual decay stage. Non-uniform loading significantly intensified stress concentrations at the edges of the lifting holes and in the lug–stiffener transition region, with local impact parameters ranging from 1.02 to 1.12 and exhibiting a distinctly non-uniform spatial distribution. A refined finite element model was established, and comparisons with experimental data confirmed that static and dynamic prediction errors were controlled within 5 MPa and 5%, respectively. The optimal lifting angle of 75° was identified, resulting in a significant reduction in dynamic amplification. Furthermore, a small-sample Bootstrap method was introduced to probabilistically correct the dynamic parameter, enhancing design reliability by approximately 10%. Overall, this research provided a more rigorous theoretical foundation and practical design tool for evaluating the safety of lifting lugs subjected to dynamic loading. Full article

As a natural flavonoid, the flavonoid luteolin is characterized by its powerful antioxidant and anti-inflammatory effects. While its precise mechanisms require further elucidation, existing evidence confirms its efficacy in ameliorating myocardial ischemia–reperfusion injury (MIRI). This research was designed to investigate the mechanism through which luteolin protects against MIRI. We established MIRI rat models through the ligation of left anterior descending coronary artery (LAD). To evaluate the cardioprotective effects of luteolin, echocardiographic analysis was performed, Hematoxylin and Eosin (HE) staining, and serum cardiac injury markers creatine kinase-MB (CK-MB) and lactate dehydrogenase (LDH). Cardiac vascular permeability was determined using Evans blue staining. To mimic ischemia–reperfusion injury, endothelial cells (ECs) were subjected to oxygen-glucose deprivation/reoxygenation (OGD/R) in vitro. Endothelial cell barrier function was evaluated through F-actin phalloidin staining and FITC-Dextran fluorescence leakage experiments. To elucidate the molecular mechanism, FOXP1 small interfering RNA (siRNA) and NLRP3 inhibitor MCC950 were administered. In MIRI rats, luteolin significantly improved cardiac function and preserved endothelial barrier integrity. These effects were associated with upregulation of FOXP1 and suppression of NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome. In OGD/R-treated endothelial cells, luteolin restored barrier function and cell viability. The protective effects of luteolin were abolished after FOXP1 silencing. Pharmacological NLRP3 inhibition (MCC950) mirrored luteolin’s protection. Our study indicates that luteolin enhances endothelial barrier function and attenuates MIRI via the FOXP1-NLRP3 pathway. The current study provides a potential drug for MIRI treatment. Full article

Background and Objectives: Patients with Sjögren’s disease (SjD) do not experience any improvement in gastroesophageal reflux disease (GERD) symptoms after SjD treatment, and in some patients, reflux even worsens. It is important to note that GERD manifests itself through typical and atypical symptoms, the latter of which may include eye damage, as evidenced by a growing body of research. When SjD patients were prescribed medication to treat GERD, their condition improved at the same time. Therefore, we aim to investigate whether there is a link between ocular dryness and gastroesophageal reflux disease (GERD) in patients with Sjögren’s disease (SjD). Materials and Methods: Our study included 27 patients with SjD according to the 2016 American College of Rheumatology and the European League Against Rheumatism (ACR/EULAR) Sjögren’s syndrome Classification Criteria, and 28 patients with non-autoimmune sicca syndrome due to GERD (nonautoimmSicca). Results: The study involved 55 participants, 48 (87.3%) women and 7 (12.7%) men. The median age was 54 years (IQR 49–64). A total of 41 subjects (74.5%) had GERD, and 20 subjects (36.4%) tested positive for Helicobacter pylori: 13 (48.1%) and 1 (3.7%) in the SjD group, and 28 (100.0%) and 19 (67.9%) in the nonautoimmSicca group, respectively. A significant difference in asymmetric tear secretion (p < 0.001) was found between the nonautoimmSicca and SjD patients, with values of 5 (3–10) mm/5 min and 1 (0–2) mm/5 min, respectively. A low correlation was detected between sialometry results and tear secretion asymmetry (r = 0.48, p < 0.001). An increase of 1 mm/5 min in the tear secretion asymmetry between the eyes was associated with a 2.04-fold increase in the odds ratio for having GERD (95% CI 1.25–3.32, p = 0.004), and was associated with a 1.9-fold increase in the odds ratio for having GERD (95% CI 1.04–3.49, p = 0.038) in patients with SjD. The presence of Helicobacter pylori is associated with asymmetric tear secretion [95% CI 1.22 (1.05–1.41, p = 0.010)]. Conclusions: Asymmetric tear secretion between the eyes is associated with the odds of having GERD. Patients with non-autoimmune sicca syndrome due to GERD have significantly greater asymmetry in tear secretion compared to those diagnosed with Sjögren’s disease. Full article

Background: Accurate assessment of prolonged disorders of consciousness (pDOC) is a critical clinical challenge. Misdiagnosis in pDOC can occur in up to 40% of cases, highlighting the need for more objective and reproducible biomarkers to support neurophysiological scales, thereby improving diagnosis and guiding therapeutic and prognostic decisions. Electroencephalography (EEG) microstate analysis is a promising, non-invasive method for tracking large-scale brain dynamics, but research in pDOC has predominantly relied on a canonical 4-class model. This methodological constraint may limit the ability to capture the full complexity of neural alterations present in these patients. Objective: This pilot study aimed to offer an objective method for assessing consciousness, complementing and enhancing the existing approaches established in the literature. The classical 4-class and an extended 7-class microstate model were compared to determine which more accurately characterizes the complexity of resting-state brain dynamics across different levels of consciousness in pDOC patients and healthy controls (HCs). Methods: Retrospective resting-state EEG (rsEEG) data from a cohort of pDOC patients and HC subjects were analyzed. Microstate analysis was performed using both 4-class and 7-class templates. The models were evaluated and compared based on three criteria: spatial correspondence with canonical maps (shared variance), the number of significant intra-group correlations between temporal features (Spearman test), and their ability to discriminate between the pDOC and HC groups (Wilcoxon test). Results: The 7-class microstate model provided a more accurate description of brain activity for most participants, with a greater number of microstate classes exceeding the 50% shared variance threshold compared to the 4-class model. In the pDOC group, both the 4-class and 7-class models showed a mean shared variance <50% in class D, which is associated with executive functioning across both templates. For the HC group, a prevalence of classes B and D emerged in both models, indicating higher engagement of executive functions. Furthermore, the 7-class model allowed for a group-specific analysis, which demonstrated that microstates A and F were consistently shared among 86% of pDOC patients. This suggests the potential preservation of specific intrinsic brain networks, particularly the sensory and default networks, even in the presence of severely impaired consciousness. Moreover, the 7-class model yielded a higher number of significant correlations within both groups and identified a broader set of temporal features that were significantly different between pDOC patients and HCs. These results highlight the enhanced sensitivity of the 7-class model in distinguishing subtle brain dynamics and improving the diagnostic capability for pDOC. Conclusions: The 7-class microstate model provides a more fine-grained and sensitive characterization of brain activity in both pDOC patients and healthy individuals. It demonstrated better performance in capturing individual brain dynamics, identifying shared network patterns, and discriminating between clinical populations. These findings suggest that the extended 7-class model holds greater potential for clinical utility and could lead to the development of more robust biomarkers for assessing consciousness. Full article