Search Results (9,669)

Enterprise architecture (EA) principles provide normative guidance for architectural evolution, yet validating whether EA models comply with such principles is typically performed manually and does not scale to continuous governance. This paper presents an ontology-based validation approach that enables automated compliance checking of ArchiMate models against EA principles. The approach (i) creates ontology-native representations of ArchiMate models grounded in an enterprise knowledge graph, (ii) structures natural-language principles using SBVR Structured English to reduce ambiguity and support traceability, (iii) enriches the resulting knowledge graph with inferred architectural relations through derivation rules, and (iv) operationalizes validation using SHACL constraints and SPARQL queries that produce explainable violation reports linked to concrete model elements. The approach is developed following Design Science Research and evaluated in three case studies (two real-world organizational settings and one controlled educational setting). The evaluation demonstrates that the approach supports repeatable execution of principle checks on evolving models, improves traceability of violations for architecture review and decision-making, and reduces manual effort by shifting substantial parts of compliance checking from human interpretation to automated constraint validation. Full article

Mine water treatment remains a long-term challenge due to high suspended solids, wide particle size distributions, and inflow variability, all of which stress solid–liquid separation systems. Hydrocyclones and filtration often fail not from insufficient capacity, but from the inability to handle dynamic influent behavior. This review integrates existing studies and reinterprets mine water treatment as a system performance issue, focusing on maintaining operability under fluctuating conditions. Evidence shows that high-solids mine water behaves as a concentrated multiphase flow, where particle interactions and flow changes lead to gradual shifts in separation behavior. For example, hydrocyclone efficiency ranges from 85 to 95%, and pressure drop increases by 0.5–5 kPa/h under continuous operation. Wear, clogging, and flow redistribution develop together, impacting the operational window of integrated treatment units. Key gaps remain in system performance under fluctuating loads and reliable performance under high-solids loading. The complexity of these interactions often leads to significant operational risk and performance variability in real-world conditions. Future research should focus on dynamic control strategies, multi-stage pre-separation, and advanced filtration designs to enhance system performance, long-term stability, and adaptability in real mining environments. Emerging technologies and new system configurations may further improve efficiency and reduce operational failure risks under extreme conditions. Full article

Background: Job satisfaction among nursing staff is a key determinant of workforce stability, quality of care, and healthcare system sustainability. Nurses are increasingly exposed to high workload, staffing shortages, and complex organizational demands, which may adversely affect satisfaction and retention. The aim of this study was to examine job satisfaction among nursing staff working across different levels of healthcare in Slovenia and to identify organisational and sociodemographic factors associated with job satisfaction. Methods: A cross-sectional quantitative study was conducted among nursing staff employed in Slovenian healthcare settings. Data were collected using an online questionnaire that included the Job Satisfaction Survey (JSS) and sociodemographic, occupational, and organizational variables. Differences in job satisfaction across professional groups were examined using non-parametric tests. Associations between job satisfaction dimensions and explanatory variables were analysed using Spearman’s correlation coefficients, and multiple linear regression analyses were performed to identify independent predictors of job satisfaction. Results: Organizational and workload-related factors emerged as the most consistent determinants of job satisfaction across all JSS dimensions and total satisfaction. Unclear job task definitions, high workload, insufficient staffing, continuous healthcare provision, unfavourable work schedules, and limited opportunities for rest were associated with lower job satisfaction. In contrast, financially compensated overtime, supportive supervision, higher perceived employer quality, longer tenure in the current position were associated with higher satisfaction in several domains. Sociodemographic variables showed weaker and less consistent effects after adjustment for organizational characteristics. Intentions to change jobs within or outside the healthcare system were strongly associated with lower satisfaction across nearly all dimensions. Conclusions: Job satisfaction among nursing staff is shaped predominantly by modifiable organizational factors rather than demographic characteristics. Interventions aimed at improving task clarity, staffing adequacy, work organization, leadership practices, and recovery opportunities may enhance job satisfaction and contribute to a more sustainable nursing workforce. Full article

Inadvertent perioperative hypothermia increases susceptibility to surgical site infection (SSI) through impaired immune function, reduced oxidative killing, and altered collagen deposition. We performed a narrative review of recent clinical and translational studies evaluating active thermal management for SSI prevention, with emphasis on forced-air warming (FAW) and conductive systems, and on high-risk settings (prolonged surgery, elevated BMI, and pediatric patients). Across studies, active warming more reliably maintains intraoperative normothermia than passive insulation; however, evidence for a consistent reduction in SSI rates is strongest in vulnerable cohorts and lengthy procedures and remains heterogeneous across specialties. FAW demonstrates high warming efficiency, yet its use in implant-based operations continues to be debated because of potential airflow disruption and bacterial mobilization concerns. The literature increasingly supports precision approaches, including pre-warming protocols, improved perioperative temperature monitoring, and predictive models to identify patients at greatest risk of hypothermia. In conclusion, effective SSI prevention requires procedure- and patient-specific thermal strategies, selecting devices that balance warming performance with sterility considerations while integrating perioperative risk stratification and real-time monitoring. Full article

Background/Objectives: Patients with hepatic glycogen storage disease (GSD) require frequent nighttime intake of uncooked corn starch (UCCS) to prevent fasting hypoglycemia, which imposes a substantial burden. Glycosade, an extended-release cornstarch, was developed to prolong overnight glucose availability. However, data regarding South Korean patients are limited. Therefore, we aimed to evaluate the efficacy and safety of Glycosade in South Korean patients with hepatic GSD. Methods: In this single-center prospective observational study, patients with hepatic GSD underwent laboratory evaluations before and 1 month after Glycosade administration. Continuous glucose monitoring (CGM) was performed during UCCS and Glycosade administration periods. The nocturnal mean glucose, coefficient of variation, time in range (70–180 mg/dL), and time below the range (<70 and <54 mg/dL) were compared between the periods using paired analyses. Results: No significant differences were observed in the nocturnal CGM metrics between the treatment periods. However, time-aligned CGM profiles revealed distinct temporal patterns, with a decline in glucose levels approximately 3–4 h after UCCS intake, whereas Glycosade showed a more sustained glucose profile over an extended period. Liver enzyme and lipid levels improved significantly after 1 month of Glycosade supplementation. Conclusions: In a cohort of South Korean patients with hepatic GSD, Glycosade maintained nocturnal glycemic stability comparable to that of conventional cornstarch without increasing the risk of hypoglycemia. Glycosade was also associated with improved biochemical parameters, supporting its role in nighttime dietary management. Full article

Infrastructure drainage projects play a critical role in urban development but are increasingly exposed to environmental, operational, and climate-related risks that challenge their long-term sustainability. Despite this, decision-makers continue to lack risk-informed, structured methods to assess sustainability performance in an uncertain environment. In order to facilitate evidence-based decision-making and sustainable risk management, this study suggests a risk-informed sustainability index for infrastructure drainage projects. The study first points out a weakness in the methods currently used for sustainability assessments, specifically the lack of risk-sensitive, standardized frameworks designed for drainage infrastructure systems. Altogether, 28 sustainability indicators are identified, with 22 indicators retained after the application of fuzzy set theory criteria. The sustainability index is developed by normalizing, weighting, and combining these indicators using a multi-criteria decision analysis (MCDA) method. To show the usefulness and practicality of the suggested approach in assessing sustainability performance and pinpointing risk-critical improvement areas, it is used for a long-term infrastructure drainage project. In order to improve infrastructure resilience, the findings emphasize the significance of early integration of sustainability and risk considerations, stakeholder engagement, and ongoing performance monitoring. The suggested approach offers a flexible and transferable framework for risk-informed decision-making, assisting engineers, project managers, and policymakers in enhancing the resilience and sustainability of infrastructure drainage systems. Full article

Soil compaction and reduced infiltration capacity are critical constraints limiting soil physical quality and hydraulic functioning in semi-arid vineyard systems subjected to repeated machinery traffic. This study aimed to develop and evaluate a geometry-optimized strip tillage tool designed to improve structural functionality within the compacted root zone while minimizing inter-row disturbance. A U-shaped working body configuration, consisting of two oppositely inclined shanks and a central chisel, was theoretically substantiated and optimized using multifactor analysis. Field experiments were conducted to assess changes in penetration resistance, bulk density, and infiltration rate within the 20–40 cm soil layer under semi-arid conditions. The optimized geometry significantly reduced penetration resistance and bulk density in the trafficked strip, indicating alleviation of mechanical impedance and improved root-relevant physical conditions. Infiltration capacity increased after treatment, indicating enhanced hydraulic continuity within the root zone. Unlike full-width subsoiling, the localized strip intervention preserved inter-row soil stability and limited unnecessary disturbance, which is consistent with conservation-oriented soil management. The results indicate that geometry-optimized strip tillage is associated with improved soil physical quality and hydraulic function within compacted vineyard strips. The operational applicability of the developed implement may also depend on vineyard layout and terrain conditions. The prototype tool was tested under conditions representative of vineyards with standard row spacing and relatively moderate slopes typical for the experimental site. In vineyards with very narrow row spacing, steep slopes, or highly heterogeneous soil conditions, adjustments in working width, shank spacing, or tractor–implement configuration may be required. Future studies should therefore investigate the performance of the optimized geometry under contrasting vineyard configurations, including steep hillside vineyards and high-density planting systems. By linking implement design to quantitative soil structural and hydraulic indicators, this study contributes to the development of vineyard soil management practices for semi-arid perennial cropping systems. Full article

Background: Global immunization programs continue to rely on needle-based injections despite persistent concerns regarding sharps disposal, accidental injuries, and the technical skill required for accurate intradermal administration. Needle-free jet injectors (NFJIs) are an alternative delivery method in which narrow, high-velocity liquid jets penetrate the skin without a needle. Contemporary designs, ranging from single-use disposable-syringe injectors to digitally controlled electromechanical devices, address historical safety issues and meet current WHO and FDA device expectations. Methods: Evidence from engineering analyses, preclinical modeling, and clinical trials was reviewed to characterize how jet velocity, nozzle structure, and formulation rheology influence skin penetration and drug dispersion. Published vaccine studies were examined for antibody responses, seroconversion, and reactogenicity compared with needle–syringe injection. Field vaccination campaign data from national campaigns and operational reports were evaluated to describe implementation steps, acceptability, and implementation constraints. Results: Published studies evaluating vaccines, including inactivated influenza, hepatitis B, typhoid, rabies, and measles, report antibody titers and seroconversion rates after NFJI administration that are comparable to those achieved with conventional intramuscular or intradermal needle injection. Needle-free delivery was associated with operational advantages in several immunization programs, including reduced sharps waste and improved vaccination rate during high-volume immunization campaigns. Local and systemic reactogenicity follows expected patterns, with slightly higher injection-site responses in some NFJI studies. Imaging and mechanical data confirm that jet performance depends on nozzle geometry and controlled pressure pulses. At the same time, formulation stability remains a critical determinant of successful jet-based vaccine administration, particularly for protein antigens, adjuvanted formulations, and emerging mRNA vaccines that may experience transient shear stress during high-velocity injection. Evidence from vaccination campaigns further indicates that needle-free jet injectors reduce sharps waste, simplify vaccine handling and administration procedures, and support rapid vaccine delivery in large-scale immunization programs. Conclusions: Needle-free jet injectors are a practical alternative to traditional needle-based injections for some vaccines. Their main benefits include enabling intradermal dose-sparing strategies, reducing reliance on sharps disposal methods, and enabling the efficient vaccination of large groups without compromising immunogenicity. Future research should define the physicochemical stability limits of biologic formulations subjected to jet injection and evaluate digitally controlled injectors capable of precise pressure modulation and adjustable delivery parameters. In addition, needle-free jet injection eliminates needle penetration and sharps handling, which may reduce needle-associated anxiety and improve vaccine acceptability among individuals with needle aversion. Full article

Background: Extracorporeal membrane oxygenation (ECMO) is commonly used for temporary support in patients with severe cardiogenic shock and may serve as a bridge to heart transplantation. In recent years, outcomes have improved with better timing, patient management and advances in ECMO technology. Case presentation: We describe the case of a 61-year-old man who developed refractory cardiogenic shock after an extensive acute myocardial infarction complicated by recurrent ventricular arrhythmias. After an initial period of stabilization following complex percutaneous coronary intervention, the patient suddenly deteriorated with acute pulmonary edema and severe hypoxemia. A peripheral femoro-femoral veno-arterial ECMO with distal limb perfusion was promptly implanted using the ECMOLIFE system and the Landing Advance system (Eurosets s.r.l., Medolla, MO, Italy) to stabilize the patient and enable continuous monitoring. Due to severe left ventricular distension, surgical left ventricular venting was performed through a minimally invasive approach. ECMO support allowed rapid hemodynamic stabilization without major complications. During ECMO support, the patient remained stable and after less than 48 h a suitable donor heart became available. The patient was safely transferred to a transplant center while on ECMO and successfully underwent heart transplantation. Conclusions: This case shows that early ECMO implantation, combined with appropriate ventricular unloading and careful management with an advanced monitoring system, can be an optimal support as a bridge to heart transplantation. Limiting the duration of ECMO support and ensuring timely referral to a transplant center may improve outcomes in patients with refractory cardiogenic shock. Full article

Stainless steel (SS) remains widely used in orthopedic implants but is susceptible to corrosion and implant-associated infections in physiological environments. This study aimed to develop a multifunctional multilayer coating combining corrosion resistance, bioactivity, and antimicrobial performance. A ZnO base layer was deposited on 316L SS via pulsed laser deposition, followed by matrix-assisted pulsed laser evaporation of a lovastatin-functionalized bioactive glass (BG57 + LOV) top layer. Two LOV concentrations were initially evaluated, and BG57+0.1LOV was selected based on structural homogeneity, cytocompatibility, and antimicrobial balance. Physicochemical characterization confirmed preservation of chemical integrity and formation of continuous, moderately rough coatings. Electrochemical impedance spectroscopy in simulated body fluid demonstrated progressive improvement in corrosion resistance from bare SS to ZnO-coated and finally to the BG57+0.1LOV/ZnO multilayer, which exhibited the most electropositive corrosion potential and effective suppression of charge-transfer reactions. Biological assays revealed high viability of osteoblasts, fibroblasts, keratinocytes, and macrophages without significant oxidative or nitrosative stress. Antimicrobial testing showed strain-dependent activity, with enhanced efficacy against MRSA and significant reduction in P. aeruginosa, associated with increased ROS/RNS generation. Overall, the BG57+0.1LOV/ZnO system represents a promising multifunctional coating strategy for corrosion-resistant and infection-resistant SS implants. Full article

Electrical imaging logging images play a crucial role in petroleum exploration; however, in practical applications, blank strips frequently appear due to instrument malfunctions or data transmission failures, severely compromising geological interpretation and hydrocarbon evaluation. Existing image inpainting methods have limited adaptability to blank strips at different depth scales and exhibit blurred high-resolution geological textures. To address these issues, this paper proposes a blank strip filling method that integrates Arbitrary Kernel Convolution (AKConv) with the Aggregated Contextual-Transformations Generative Adversarial Network (AOT-GAN). Specifically, the adaptive sampling mechanism of AKConv is incorporated into the generator network of AOT-GAN, enabling the model—to effectively capture long-range contextual information and adaptively handle blank strips of varying scales and shapes through multi-scale feature fusion. Experimental results on real oilfield datasets demonstrate that the proposed method achieves significant improvements in PSNR, SSIM, and MAE, exhibiting superior structural preservation and texture sharpness—especially in restoring deep and large-scale blank strips. Furthermore, visual comparisons confirm the method’s superior performance in recovering key geological features, such as bedding continuity and fracture structures, thus providing an effective approach for electrical imaging logging image restoration. Full article

Shared autonomous vehicle (SAV) services are gaining attention as an innovative urban transportation paradigm due to their potential to lower travel costs and improve operational efficiency. Unlike manually operated vehicles, SAVs exhibit unique behavioral dynamics, including safe passenger pick-up and drop-off processes, as well as strategic repositioning and autonomous parking to anticipate future travel demands. Consequently, effective and dynamic route planning is paramount to optimizing SAV safety and operational efficiency. This study proposes a novel traffic information, termed Autonomous Driving Stress (ADS), designed to enhance the safety and efficiency of SAV route planning by quantitatively capturing the level of driving challenge encountered during autonomous operation. To predict ADS, a machine learning framework was developed, utilizing microscopic traffic simulation data that incorporates a comprehensive set of 22 input features describing SAV driving behavior, roadway characteristics, and prevailing traffic conditions. Among five machine learning algorithms evaluated, Random Forest exhibited superior predictive performance, achieving an accuracy of 80.9%. The proposed framework enables real-time ADS level prediction by continuously integrating streaming traffic data into the trained model. The dissemination of this real-time ADS information to SAVs supports proactive, informed, and dynamic route planning decisions, thereby enhancing operational safety, traffic flow, and the sustainability of SAV operations within urban mobility systems. Full article

To enhance the early-age properties of steel slag cement mortar and promote the resource utilization of metallurgical solid waste, in this study, nano-SiO₂ (KH-NS) was modified using a KH550 silane coupling agent. The hydration kinetics and microstructure evolution were systematically analyzed by means of a macroscopic performance test (setting time and compressive strength) and multi-scale microscopic characterization (characterized by Fourier Transform Infrared Spectroscopy, Scanning Electron Microscopy, X-ray Diffraction, Thermogravimetry-Differential Thermal Analysis, and isothermal calorimetry). The influence mechanism of its content on the early performance of the steel slag cement system was systematically studied. Research findings indicate that at a given dosage, increasing the proportion of KH-NS results in a shorter setting time for steel slag mortar. When the KH-NS dosage reaches 1.5%, the initial and final setting times of steel slag mortar decrease by 24.21% and 21.20%, respectively. The addition of KH-NS effectively enhances the compressive strength of mortar, with a particularly pronounced effect on early strength prior to 14 h of curing. At a KH-NS dosage of 1.5%, the onset of the accelerated phase of hydration heat release in steel slag cement mortar is advanced by 2.5 h. Mechanistic studies indicate that KH-NS accelerates cement hydration by promoting C₃S dissolution and C-S-H gel nucleation through interactions between surface silanol groups (Si-OH) and amino groups (-NH₂). Furthermore, KH-NS refines the pore structure via a micro-aggregate filling effect, reducing the number of harmful pores and improving the pore size distribution. KH-NS continuously consumes Ca(OH)₂ through pozzolanic reactions to generate C-S-H, with its reactivity increasing with higher dosage. Research confirms that KH-NS significantly enhances the early strength and density of steel slag mortar, providing both theoretical justification and technical support for developing low-carbon building materials based on solid waste with high dosage. Full article

Hypertension is a leading global health risk and requires accurate and continuous monitoring for effective management. Although photoplethysmography (PPG) is a promising non-invasive modality for cuffless blood pressure (BP) assessment, many existing approaches (especially raw-signal deep learning) are vulnerable to data leakage, overfitting on small datasets, limited interpretability, and poor performance on minority BP stages. To address these limitations, we propose a robust and physiologically grounded framework for multi-class BP stage classification based on interpretable PPG features. Our approach centers on a comprehensive multi-domain feature engineering pipeline that extracts 124 PPG features, including demographic, morphological, functional decomposition, spectral, nonlinear dynamics, and clinical composite indices. We apply rigorous preprocessing and feature selection prior to model training. We validate the framework on two datasets: PPG-BP dataset (657 segments, 4 classes) for benchmarking and PulseDB (283,773 segments, 3 classes) to assess scalability. We evaluate the proposed framework using a segment-level train/test split, appropriate for assessing intra-subject BP tracking after initial personalization. For the PulseDB dataset, this follows the protocol established by the dataset creators, while for the PPG-BP dataset, it enables direct comparison with prior work given practical dataset constraints. On PPG-BP, LightGBM trained on the selected features achieved macro-F1 = 0.78 and accuracy = 0.74, outperforming comparable deep-learning models. On the PulseDB, a custom Residual MLP achieved accuracy = 0.81 and macro-F1 = 0.79, supporting generalization at scale. These results show that the proposed feature-based approach can outperform complex end-to-end deep-learning models on small datasets while providing improved interpretability. This work establishes a reliable and transparent pathway toward clinically viable continuous BP staging, moving beyond black-box models toward physiologically grounded decision support. Ablation analysis reveals that engineered features provide most of the predictive power (F1 = 0.911), while raw PPG features alone achieve modest performance (F1 = 0.384). For the minority hypertension stage 2 (HT-2) class, a bootstrap 95% confidence interval of [0.762, 1.000] is reported, reflecting uncertainty due to limited sample size. Full article

Background: Age-related cognitive deccline is a significant health issue in Spain, especially among adults over 60 years of age. Addressing this involves establishing intervention guidelines and identifying early diagnostic biomarkers. Objective: To evaluate changes in urine of Brain-Derived Neurotrophic Factor, concentration and cognitive performance after the implementation of the multicomponent CESPORT program (incorporating a Mediterranean Diet, nutritional education, and continuous support). Methods: This controlled trial included 76 older adults, divided into an experimental group (n = 58; mean age 66.9 years; 75.9% female) that participated in the CESPORT program, and a control group (n = 18; mean age 68.8 years; 72.2% female). Cognitive performance was assessed using the Mini-Mental State Examination (MMSE) and the Cognifit^® battery. Urinary BDNF concentrations were quantified via ELISA. Results: After adjusting for baseline scores via ANCOVA, the experimental group demonstrated significantly higher post-intervention outcomes compared to the control group (p < 0.001). Substantial improvements with medium-to-large effect sizes were observed in global cognition, reasoning, attention, coordination and perception. Furthermore, urinary BDNF levels were significantly elevated in the experimental group. Positive correlations were found between Brain-Derived Neurotrophic Factor concentrations and cognitive performance in multiple domains (p < 0.05), particularly regarding global status and reasoning. Conclusions: The multicomponent CESPORT intervention demonstrates a potential protective effect against age-related cognitive decline. Furthermore, urinary BDNF emerges as a promising, non-invasive early biomarker for cognitive health. Further research is warranted to validate these findings. Full article