Search Results (3,309)

Oversized rock fragments (boulders) produced during bench blasting adversely affect the efficiency of mining downstream processes such as loading, hauling, and crushing, thus leading to regularly requiring costly secondary breakage and the use of mechanized rock breakers. This study presents a probabilistic framework for forecasting boulder size in surface mining operations by employing Gaussian Process Regression (GPR), benchmarked against the Kuznetsov–Cunningham–Ouchterlony (KCO) empirical fragmentation model and a Multivariate Regression Analysis (MVRA) equation. The research study has analyzed blasting datasets, comprising Geological Strength Index (GSI), number of holes (NH), hole depth (HD), maximum charge per delay (MCPD), total explosive mass (TEM), and boulder size determined by Split-Desktop image analysis. Eight Gaussian Process Regression kernels—squared exponential, rational quadratic, matern with ν = 3/2, and matern with ν = 5/2, both with and without automatic relevance determination (ARD)—were assessed. The GPR model with the ARD matern 3/2 kernel attained superior validation performance of R² = 0.9016 and RMSE = 4.2482, outperforming the KCO and MVRA models, which displayed significant prediction errors for boulder size. In addition, the sensitivity analysis results demonstrated that GSI and HD were the most influential parameters on boulder size, followed by NH, MCPD, and TEM, accordingly. The findings indicate that GPR, especially when employing ARD matern kernels, precisely estimates the boulder size, and thus can serve as a viable method for optimizing blast design and facilitate efficient boulder management in surface mining operations. Full article

Marine ports located in regions of moderate seismicity can face high Natech (natural hazard-triggered technological) risk because large inventories of hazardous materials are stored near dense urban populations. This study proposes and applies a Natech risk framework to a representative port on the Saint-Laurence River in Quebec, Canada. Site-specific peak ground accelerations (PGA) are first estimated for 12 earthquake scenarios using regional ground motion prediction equations adjusted for local site conditions. These hazard levels are combined with a damage probability matrix to estimate Hazardous Release Likelihood Index (HRLi) scores for atmospheric steel storage tanks. Offsite consequences are then evaluated to obtain Maximum Distances of Effect (MDEs) for different types of hazardous materials. MDE footprints are intersected with block-level demographic data and complemented by a domino-effect based on inter-tank spacing, yielding a tank-level Natech Risk Index $NR{\mathrm{I}}_{\mathrm{i},\mathrm{s}}$ for each storage tank ($\mathrm{i}$) and seismic scenario ($\mathrm{s}$). These values are then averaged over all tanks to obtain a scenario-level mean Natech Risk Index ($\overline{NRI}$) for each tank substance. Regression equations relating $\overline{NRI}$ to PGA are provided as a practical tool for defining critical intensity thresholds for seismic Natech risk management in marine ports. Full article

In 90° elbows, abrupt turning induces strong secondary flow, separation, and turbulence, increasing pressure loss and degrading velocity uniformity. A hydrogen pipeline elbow is optimized by combining a nature-inspired cross-section with a guide vane, while tuning vane position/angle and geometric radii/offsets using a multi-objective genetic algorithm (MOGA). Three-dimensional CFD is performed for compressible gaseous hydrogen using the Peng–Robinson equation of state and the SST k–ω turbulence model. Design points are generated by Latin hypercube sampling, and response surface models based on non-parametric regression (NPR) and genetic aggregation (GA) guide the search. Relative to the reference elbow, the GA-based optimum improves velocity uniformity by 5.825% and reduces the total pressure-drop coefficient by 0.470%; the NPR-based optimum yields 4.021% and 0.229%, respectively. Flow-field analysis shows reduced separation area, axial vorticity, turbulent kinetic energy, and dissipation, indicating suppressed secondary flow and smoother turning. These gains translate to lower pumping power and enhanced energy efficiency, supporting cost-effective deployment of carbon-neutral hydrogen infrastructure. Full article

Amid rising climate risks, geopolitical uncertainty, and global supply disruptions, strengthening sustainable supply chain resilience has become a critical policy priority for emerging economies. This study scrutinises how digitalisation and circular-economy practices jointly shape national-level supply chain resilience and sustainability performance. Using a balanced panel of 32 emerging economies from 2010 to 2023, the analysis draws on the Resource-Based View and Dynamic Capability Theory to test a serial mediation framework linking digitalisation, circularity, resilience, and sustainability. Fixed-effects panel regressions, mediation analysis, and Structural Equation Modelling (SEM) are employed using internationally comparable indicators from the World Bank, OECD, UN SDG Database, and UNIDO. The results show that digitalisation is positively associated with circular-economy adoption and supply chain resilience, while circularity further fortifies resilience. Resilient supply chains, in turn, are strongly associated with improved sustainability performance. The serial mediation results propose that sustainability outcomes emerge through a cumulative capability-building pathway rather than isolated technological effects. The findings highlight the importance of integrated digital and circular policy frameworks for enhancing resilience and advancing sustainable development in emerging economies. Full article

Lumbar shear forces are increasingly recognized as critical contributors to lower-back injury risk, yet most ergonomic assessment tools—most notably the Revised NIOSH Lifting Equation (RNLE)—do not directly estimate shear loading. This study develops and evaluates a family of linear mixed-effects regression models that statistically predict L4/L5 lumbar shear force exposure using traditional NIOSH lifting parameters combined with posture descriptors extracted from digital human models. A harmonized dataset of 106 peak-shear lifting postures was compiled from five controlled laboratory studies, with lumbar shear forces obtained from validated biomechanical simulations implemented in the Siemens JACK (Siemens software, Plano, TX, USA) platform. Twelve model formulations were examined, varying in fixed-effect structure and hierarchical random effects, to quantify how load magnitude, hand location, sex, and joint posture relate to simulated task-level anterior–posterior shear exposure at the lumbar spine. Across all models, load magnitude and horizontal reach emerged as the strongest and most stable predictors of shear exposure, reflecting their direct mechanical influence on anterior spinal loading. Hip and knee flexion provided substantial additional explanatory power, highlighting the role of whole-body posture strategy in modulating shear demand. Upper-limb posture and coupling quality exhibited minimal or inconsistent effects once load geometry and lower-body posture were accounted for. Random-effects analyses demonstrated that meaningful variability arises from individual movement strategies and task conditions, underscoring the necessity of mixed-effects modeling for representing hierarchical structure in lifting data. Parsimonious models incorporating subject-level random intercepts produced the most stable and interpretable coefficients while maintaining strong goodness-of-fit. Overall, the findings extend the NIOSH framework by identifying posture-dependent determinants of lumbar shear exposure and by demonstrating that simulated shear loading can be reliably predicted using ergonomically accessible task descriptors. The proposed models are intended as statistical predictors of task-level shear exposure that complement—rather than replace—comprehensive biomechanical simulations. This work provides a quantitative foundation for integrating shear-aware metrics into ergonomic risk assessment practices, supporting posture-informed screening of manual material-handling tasks in field and sensor-based applications. Full article

In today’s corporate environment, employees’ proactive engagement in environmental behaviors is crucial for the effective implementation of corporate environmental regulations. Leadership is crucial in motivating such behaviors. This study, grounded in self-determination theory, explores how Environmental Responsible Leadership enhances employees’ Organizational Citizenship Behavior for the Environment through Psychological Empowerment. Additionally, we analyze the moderating role of Green Culture. Using a multi-wave survey design, data were collected from 262 corporate employees in China via the Credamo platform and analyzed through structural equation modeling (SEM) with AMOS 24.0 and hierarchical regression analysis with SPSS 26.0. The results reveal that Environmental Responsible Leadership significantly promotes the enhancement in Organizational Citizenship Behavior for the Environment. Psychological Empowerment serves as a significant mediator in this relationship, while Green Culture, as a supportive organizational context, amplifies the positive effects of Environmental Responsible Leadership on employees’ environmental behaviors. By elucidating the mechanisms and boundary conditions of Environmental Responsible Leadership, this study provides practical insights for organizations seeking to advance ecological conservation through leadership development and cultural nurturing. Full article

In this paper, the antifungal activity of medium-chain fatty acids with 8 to 11 carbon atoms in their chemical structures, medium-chain fatty acid lactones, and a partially fluorinated medium-chain fatty acid was determined. As the length of the alkyl chain increased in medium-chain fatty acids with 8 to 11 carbon atoms, the MIC and MFC became smaller, with increased antifungal activity (octanoic acid, 225 µg/mL(MIC), 450 µg/mL (MFC); nonanoic acid, 225 µg/mL (MIC), 450 µg/mL (MFC); decanoic acid, 112.5 µg/mL (MIC), 225 µg/mL (MFC); undecanoic acid, 112.5 µg/mL (MIC), 225 µg/mL (MFC)), whereas the antifungal activity of γ-undecalactone, in which the carboxyl group of the medium-chain fatty acid with 11 carbon atoms was converted to a five-membered lactone ring, also had antifungal activity (γ-undecalactone, 112.5 µg/mL (MIC), 225 µg/mL (MFC)). The antifungal activity of the partially fluorinated fatty acid with 11 carbon atoms and δ-undecalactone was not observed and their MICs were not evaluated in this study. The equation derived through multiple regression analysis revealed that the polarizability value was significantly related to the MICs or MFCs of fatty acids containing 8 to 11 carbon atoms and γ-undecalactone (R² = 0.78, p < 0.05). C. albicans cultured at 37 °C with γ-undecalactone at the MIC formed hyphae or biofilms, which were observed using scanning electron microscopy in this study. Dead C. albicans were observed when cultured at 37 °C with γ-undecalactone at the MFC, indicating that in order to demonstrate complete killing, C. albicans must be killed at or above the MFC of γ-undecalactone when cultured at 37 °C. γ-undecalactone exhibited no hemolytic activity at the MFC, similar to negative controls. Our results show that γ-undecalactone has an antifungal effect against C. albicans over the MFC, without hemodialysis as the observed cytotoxicity. Full article

This study presents an integrated framework that couples three-dimensional geotechnical ground modeling with a HAZUS-based urban seismic vulnerability assessment for Seoul, Korea. Over 63,000 boreholes, in situ seismic tests, and building inventory records were compiled into a unified relational database following rigorous multi-stage quality control. A multi-parameter N–Vs regression model was calibrated to supplement missing shear-wave velocity (Vs) data, reducing prediction errors by more than 20% relative to conventional empirical equations. Based on the quality-controlled Vs dataset, a high-resolution three-dimensional Vs–ground model was constructed to represent subsurface heterogeneity and associated uncertainty across the metropolitan area. The building inventory, comprising approximately 700,000 structures, was standardized according to the HAZUS structural taxonomy and mapped to Korean seismic design eras, enabling a Seoul-adapted vulnerability assessment in which exposure characterization and seismic demand are localized. Site-specific ground-motion amplification and response spectra derived from the 3D ground model were used to modify the spectral acceleration input to the HAZUS fragility functions. Results reveal pronounced spatial variability in site conditions, with northern mountainous zones corresponding primarily to NEHRP Site Class B, central districts to Class C, and southern alluvial basins to Classes D–E, producing amplification differences of up to 1.7 under identical input spectral accelerations. High-risk zones such as Gangnam, Songpa, and Yeouido exhibit concentrated expected damage where thick alluvial deposits coincide with dense stocks of mid-rise reinforced-concrete buildings. Overall, the study demonstrates that integrating high-resolution 3D geotechnical ground models with HAZUS-based fragility analysis provides a physically consistent and data-driven basis for urban-scale seismic risk assessment and resilience planning. Full article

Background: Neonatal mortality remains a significant public health challenge in Ethiopia. Despite efforts to implement key evidence-based interventions, their coverage and utilization remain low. The Saving Little Lives (SLL) program aims to scale-up a Minimum Care Package (MCP) of synergistic, life-saving interventions for all liveborn neonates, with a focus on preterm and low birth weight (LBW) infants, across 290 hospitals in Ethiopia (206 primary, 69 general, and 15 referral hospitals), representing 82% of all hospitals in the country at the time of the study, and evaluate the impact on neonatal mortality. Methods: A non-randomized stepped-wedge trial will be conducted to evaluate the impact of implementing the SLL MCP interventions. Quantitative evaluation data will be collected from 36 primary hospitals, selected from 206 primary hospitals across four regions, receiving the interventions. An independent evaluation research assistant will be deployed in each of the hospitals to collect data using Open Data Kit (ODK) through interviewing mothers before discharge, on the 29th day of life if discharged, and reviewing medical records. A mixed-method, cross-sectional formative assessment will be conducted prior to implementation, employing quantitative facility assessment and qualitative interviews with mothers, healthcare providers, and facility managers. This will be followed by continuous program learning assessment once implementation begins. Descriptive data will be presented using numbers, percentages, tables, and graphs. Regression modeling and generalized estimating equations (GEEs) will be used to estimate the impact of the SLL MCP interventions. Qualitative data will be gathered through in-depth interviews, digitally recorded, transcribed, and thematically analyzed using ATLAS.ti Version 7.5 software to assess facility readiness, barriers, and enablers of implementing the SLL MCP interventions. Expected Outcome: We hypothesize that achieving 80% coverage of the SLL MCP interventions among eligible neonates will result in a 35% reduction in neonatal mortality at implementation facilities. Full article

Understanding how different pools of sediment organic carbon (OC) are associated with trace metals is essential for interpreting biogeochemical processes in small freshwater ecosystems. This study examines spatial and interannual patterns of total organic carbon (TOC), water-extractable organic carbon (WEOC), and cadmium (Cd) in sediments collected from streams, natural ponds, and drying ditches across three contrasting regions of Lithuania during 2022–2024. TOC and WEOC exhibited pronounced spatial gradients and a marked increase in 2023, while Cd showed a similar but more moderate temporal response. Correlation analysis, principal component analysis, regression modelling, and structural equation modelling consistently indicated that WEOC is more strongly associated with sediment Cd concentrations than bulk TOC. The results suggest that TOC influences Cd distribution primarily indirectly, through its control on the water-extractable OC pool. Multivariate analyses revealed a dominant organic–metal association gradient shared by TOC, WEOC, and Cd, as well as a secondary axis reflecting partial geochemical independence of Cd. These findings highlight the functional relevance of WEOC as an interface between sediment organic matter and Cd accumulation in small freshwater systems. Incorporating WEOC into sediment monitoring may improve interpretation of trace-metal patterns under conditions of hydrological variability. Full article

The Mun River Basin, the largest Mekong tributary in Northeast Thailand, has experienced extensive agricultural expansion and forest decline, raising concerns over increasing soil erosion and sediment transfer. This study provides an integrated assessment of soil loss, sediment yield (SY), and sediment delivery ratio (SDR) across 19 sub-watersheds using the Universal Soil Loss Equation (USLE), field-based SY data, and multivariate statistical analyses in 2024. Basinwide soil loss was estimated at ~35 million t y⁻¹ (mean 4.96 t ha⁻¹ y⁻¹), with more than 80% of the basin classified in the no erosion to very low erosion classes. Despite substantial hillslope erosion, only 402,405 t y⁻¹ of sediment reaches the river network, corresponding to a low SDR of 1.15%, which falls within the range reported for large tropical watersheds with significant reservoir infrastructure. Soil loss is most strongly influenced by slope and forested terrain, while SY responds primarily to rainfall and tree plantations; urban land, croplands, and reservoirs act as sediment sinks. Principal Component Analysis (PCA) resolved multicollinearity and produced six components explaining over 90% of predictor variance. A PCA-based regression model predicted SY per unit area with high accuracy (r = 0.81). The results highlight the dominant roles of hydroclimate and land-use structure in shaping sediment connectivity, supporting targeted soil and watershed-management strategies. Full article

This study develops and validates a three-level model of digital learning conditions that reflects the progression from ICT accessibility (“access”) to pedagogical use (“use”) and their influence on student learning outcomes (“impact”). Drawing on secondary analysis of the PISA 2022 ICT Familiarity Questionnaire and applying complex-sample regression together with the logic of structural equation modelling (SEM), the study examines how ICT resources, usage practices, and digital feedback (ICTFEED) interact and how they are associated with Lithuanian fifteen-year-olds’ achievement in mathematics, reading, and science. The three-level model includes: (1) ICT infrastructure—access to technology at home and at school and students’ perceived quality of technological resources; (2) ICT learning practices—use of digital tools in subject lessons, inquiry-based activities, and school-related work outside the classroom; and (3) digital feedback and its relationship with academic achievement. Results show that neither home nor school ICT availability predicts students’ experience of receiving digital feedback. The only significant infrastructure-level predictor is the perceived quality of school ICT resources (ICTQUAL). Digital feedback is most strongly predicted by ICT use in inquiry-based learning and by ICT-supported schoolwork outside the classroom, whereas ICT use in subject lessons has only a minimal effect. Across all domains, digital feedback is negatively associated with student achievement, even when ICT access, resource quality, learning-use variables, and digital leisure are controlled for. This pattern suggests that ICTFEED functions primarily as a compensatory mechanism, being more frequently used with lower-achieving students rather than serving as a direct enhancer of academic performance. The proposed three-level model offers a structured framework for interpreting students’ digital learning experiences and highlights the key components of school ICT ecosystems that shape digital assessment practices and learning outcomes. Full article

Background and Objectives: Abortion on request, contraceptive access barriers, and mental health may jointly shape women’s quality of life (QoL). We examined how abortion history, structural barriers, and psychosocial factors relate to modern contraceptive use, depressive and anxiety symptoms, and QoL among women attending a Romanian tertiary center. Methods: We conducted a single-center observational study combining retrospective chart review with an online survey of 200 women aged 18–45 years. Validated instruments (Patient Health Questionnaire-9 [PHQ-9], Generalized Anxiety Disorder-7 [GAD-7], World Health Organization Five-Item Well-Being Index [WHO-5], and World Health Organization Quality of Life–BREF [WHOQOL-BREF]) and indices of access barriers, perceived stigma, and social support were used. Analyses included multivariable regression, structural equation modelling, latent class analysis, and moderation analysis. Results: Overall, 55.0% of women reported ≥1 abortion on request. Compared with those without abortion history, they were older (31.2 ± 4.9 vs. 26.8 ± 4.8 years, p < 0.001), more often had lower levels of education (51.8% vs. 33.3%, p = 0.013), and were less likely to use modern contraception at last intercourse (52.7% vs. 71.1%, p = 0.012). PHQ-9 (8.8 ± 4.0 vs. 7.3 ± 4.3) and GAD-7 (7.0 ± 3.2 vs. 5.7 ± 3.4) scores were higher (both p = 0.010), while QoL was lower (55.4 ± 8.1 vs. 59.5 ± 7.8, p < 0.001). In adjusted models, access barriers (OR per point = 1.3, 95% CI 1.1–1.6), but not abortion history, predicted non-use of modern contraception. QoL correlated strongly with PHQ-9 (r = −0.6) and WHO-5 (r = 0.5; both p < 0.001). Latent class analysis identified a “high-barrier, distressed, abortion-experienced” profile with the poorest mental health and QoL. Conclusions: Structural access barriers and current depressive and anxiety symptoms, rather than abortion history alone, were key correlates of contraceptive gaps and reduced QoL, underscoring the need for integrated reproductive and mental health care. Full article

Hemolysis rate is usually used as the acceptance criterion for stored red blood cells (RBCs) in clinical practice. However, there is a current lack of parameters for the characterization of hemoglobin quality. This study aimed to incorporate oxygen affinity, cooperativity, and the Bohr effect into a parameter system to monitor oxygen supply efficiency in stored RBCs, potentially serving as a basis for quality assessment. Han Chinese blood from plains, Tibetan blood from plateau, bovine hemoglobin (bHb), and a dextran–bovine hemoglobin conjugate (Dex20-bHb) were analyzed using the BLOODOX-2018. Oxygen affinity (P₅₀) was determined by oxygen dissociation curves (ODCs) at pH = 7.4. Cooperativity was assessed through the Hill coefficient, calculated from the fitting range of the Hill equation. The Bohr effect was evaluated by the acid-base sensitivity index (SI) under simulated pH conditions of the lungs (pH = 7.6) and tissues (pH = 7.2) to calculate corresponding P₅₀ values. Oxygen partial pressures (PO₂) simulating lungs (PO₂ = 100 mmHg for plains and 60 mmHg for plateau) and tissues (PO₂ = 40 mmHg for plains and 30 mmHg for plateau) were used to calculate theoretical oxygen-release capacities in both environments. Multiple regression analysis explored relationships among parameters, constructing a system to assess changes in rat RBCs during storage. Optimized test methods determined P₅₀, Hill coefficient, SI, and theoretical oxygen-release capacities for Han Chinese blood, Tibetan blood, bHb, and Dex20-bHb samples in various environments. We constructed a parameter system to characterize blood’s oxygen supply efficiency, revealing the significant influence of the Bohr effect. This influence varied with environmental changes in oxygen affinity. We validated the system using stored rat RBCs, finding consistent P₅₀ trends with predictions, and initial increases in Hill coefficient and SI followed by decreases. Theoretical oxygen-release capacities varied significantly between plateau and plain environments. These results support using oxygen supply efficiency to assess RBC storage quality for developing transfusion strategies. P₅₀, Hill coefficient, SI, and theoretical oxygen-release capacity in different environments can be incorporated into blood oxygen supply efficiency characterization systems to assess the quality changes in RBCs during storage. Full article

In an era increasingly defined by the imperative for sustainable development, the construction sector faces significant challenges, including resource limitations, environmental pressures, and high uncertainty. Within this context, the organizational capabilities of construction projects are widely recognized as a critical endogenous driver, closely linked to sustainable performance outcomes. Yet, empirical research to date has produced inconsistent conclusions, and a systematic understanding of how distinct dimensions of capability influence sustainability remains surprisingly fragmented. To address this gap, we employ a meta-analysis to synthesize 11,881 independent samples from 64 quantitative empirical studies. We systematically examined the overall relationship between organizational capability in construction projects and sustainable performance. It further compares the differential effects of project capabilities and dynamic capabilities across economic, social, and environmental performance. Additionally, the study investigated the moderating effects of key contextual and methodological factors. Our analysis yielded several important findings: (1) A significant, moderately positive correlation exists between organizational capability in construction projects and sustainable performance. (2) Project capability exerts a stronger association with economic and social performance, whereas dynamic capability demonstrates a more pronounced effect on environmental performance. This underscored distinct pathways through which different capability dimensions operate. (3) Moderation analysis revealed that the relationship between organizational capability and sustainable performance is stronger in emerging economies and collectivist cultural contexts. Methodologically, structural equation modeling tended to produce larger effect sizes compared to regression analysis. Although no significant moderation effect emerges across research time points, post-2015 studies generally showed slightly stronger effects. The findings enrich the application of the Resource-Based View and Dynamic Capability Theory within construction project contexts, emphasizing the multidimensional nature of organizational capabilities and their differentiated roles across triple-bottom-line performance. Consequently, this research offers valuable pathways for capability development and a strategic foundation for enhancing managerial practice in construction project management. Full article