Search Results (5,836)

The rapid rise in the use of Liquefied Petroleum Gas (LPG) as an alternative vehicle fuel in Ghana presents both opportunities and risks within the national energy transition agenda. This study investigates LPG safety as well as environmental and regulatory implications using a multi-method quantitative approach that combines structured survey data, exploratory multivariate analysis (MCA), and machine learning classification (Random Forest) to uncover emerging associations and patterns in LPG safety practices. Primary data were obtained from 384 respondents, including vehicle operators, auto-technicians, regulatory officials, and LPG station attendants across five major transport zones: Kejetia, Asafo, Ahodwo, Bantama, and Suame Magazine. The MCA identified four distinct behavioural and safety profiles—At-Risk, Proactive Safety, Compliant and Equipped, and Formal and Reported—reflecting diverse compliance and risk patterns across socio-occupational groups. The Random Forest classifier achieved a predictive accuracy of 96.5% based on cross-validated performance. Sensitivity and specificity values were high, indicating reliable discrimination among incident types. To reduce the risk of overfitting, k-fold cross-validation and monitored error convergence were performed across increasing numbers of trees. While the model shows strong predictive capability, we present these results cautiously and emphasize observed associations and emerging patterns rather than definitive predictive conclusions. The findings reveal that while economic motivations underpin LPG adoption, weak institutional enforcement and widespread informal installations heighten safety vulnerabilities. Comparisons with sub-Saharan and Asian contexts underscore the need for a structured regulatory framework, mandatory certification of installers, and periodic vehicle inspections. The study contributes to the broader discourse on informal energy transitions in developing economies by demonstrating how technical and behavioural determinants interact within weak regulatory systems. Policy recommendations emphasize the integration of data-driven risk assessment tools into regulatory oversight to enhance vehicular LPG safety and sustainability. Full article

Managing electronic waste (e-waste) in the Philippines is a critical challenge, no with roughly 80% handled by an informal sector using hazardous methods. This study develops a context-specific Circular Economy (CE) framework for urban Manila by quantifying the behavioral, institutional, and socio-economic factors influencing recycling efficiency. Using a hybrid methodology, quantitative data were collected from 435 informal recyclers. Structural Equation Modeling (SEM) supported 16 of 18 hypothesized pathways from the Theory of Planned Behavior (TPB), though Perceived Behavioral Control did not directly affect Intention. An Artificial Neural Network (ANN) sensitivity analysis identified economic factors, Income Level (84.01%) and Financial Incentives (82.86%), as the dominant predictors of behavior, followed by the Cultural–Cognitive Pillar (80.98%). This necessitates modifying the TPB for subsistence economies, where economic survival acts as a super-moderator. The resulting CE framework mandates inclusive policies, prioritizing “Economic First Interventions” like buy-back schemes to equitably integrate informal recyclers into formal Extended Producer Responsibility systems. Full article

Urban community children’s play spaces play a crucial role in promoting both physical and mental health, significantly influencing children’s development and fostering a sense of belonging to the community. However, existing design practices often fail to adequately address the complex behavioral and emotional needs of children in these spaces. To overcome this gap, there is an urgent need for a system that can effectively respond to these complexities, thereby enhancing children’s play experiences and their attachment to the space. This study seeks to optimize the design of children’s play spaces in urban communities through a quantitative approach based on Exploratory Factor Analysis (EFA) and Structural Equation Modeling (SEM). First, multi-dimensional data concerning children’s physical environment, subjective perceptions, play behaviors, and satisfaction were gathered through field surveys and questionnaires. Reliability and validity assessments were conducted to ensure data quality. Subsequently, EFA was applied to perform dimensionality reduction and identify the underlying structure, resulting in the extraction of six key factors that influence children’s play experiences. Finally, SEM was utilized to construct a structural model, test hypotheses, and quantify the relationships between the identified dimensions. The results demonstrate that the EFA-SEM framework effectively transforms subjective concepts into actionable design parameters, meeting user needs and providing a solid scientific foundation for the design of children’s play spaces in urban communities. Full article

Background/Objectives: Ovarian cancer remains a highly lethal malignancy, largely due to the development of therapeutic resistance, particularly in advanced disease. Combination strategies targeting complementary molecular pathways may enhance antitumor efficacy and help overcome resistance. The present study aimed to systematically evaluate the anticancer effects of the PARP1 inhibitor PJ34 and the natural polyphenol curcumin, administered alone and in combination, in platinum-sensitive and relatively platinum-resistant ovarian cancer models, with an emphasis on quantitative synergy assessment and functionally supported, hypothesis-generating mechanistic insight. Materials and Methods: Cell viability was evaluated using the MTT assay, and IC₅₀ values were derived from dose–response curves. Drug interactions were quantitatively analyzed using the Chou–Talalay method, including combination index (CI) and dose reduction index (DRI) calculations. Intracellular reactive oxygen species (ROS) levels were measured using DCFH-DA-based assays. Cell migration was assessed using scratch-wound assays. Apoptosis was evaluated using Annexin V/PI flow cytometry, caspase-3 activity assays, and quantitative real-time PCR (RT-qPCR) analysis of apoptosis-related genes (Bax, Bcl-2, Caspase-3, Caspase-9, and p53). To further validate the findings under physiologically relevant conditions, three-dimensional (3D) tumor spheroid models were employed, and ROS involvement was functionally interrogated using N-acetyl-L-cysteine (NAC) rescue experiments to assess ROS-associated contributions rather than direct causality. Results: PJ34 and curcumin each reduced cell viability in a dose-dependent manner, whereas their combination produced a synergistic antiproliferative effect with reduced IC₅₀ values. Synergism was particularly pronounced in relatively platinum-resistant SKOV-3 cells. Combination treatment significantly enhanced regulated apoptotic cell death, as demonstrated by increased apoptotic fractions, elevated caspase-3 activity, and an increased Bax/Bcl-2 ratio, with minimal necrosis. While PJ34 moderately increased intracellular ROS levels and curcumin reduced oxidative stress, the combination was associated with the normalization of ROS levels to near-control values. In 3D tumor spheroid models, combined treatment induced marked spheroid shrinkage, loss of structural integrity, and reduced viability, indicating a preservation of synergistic cytotoxic effects beyond two-dimensional (2D) conditions. NAC pretreatment partially attenuated, but did not fully rescue, the cytotoxic effects of the combination, indicating a ROS-associated, but not exclusively ROS-dependent, mechanism of action. In addition, the combination markedly inhibited cell migration in both ovarian cancer cell lines. Conclusions: This preclinical provides evidence that combined PARP1 inhibition and curcumin treatment can exert synergistic antitumor effects in ovarian cancer models, including relatively platinum-resistant disease, through the coordinated suppression of proliferation, induction of regulated apoptosis, and inhibition of migration. The integration of quantitative synergy analysis, 3D spheroid validation, and ROS-rescue experiments provides functionally supported, hypothesis-generating mechanistic insight and supports further evaluation of PARP inhibitor–curcumin combinations as a mechanistic proof-of-concept in advanced preclinical models. Full article

Shale gas “sweet spot” prediction serves as a pivotal technical link in shale gas exploration and development, directly governing the efficiency of exploration deployment and the economic viability of development projects. To address the research gap in sweet spot prediction for complex synclinal structures, this study establishes an integrated geology–engineering–economics evaluation framework, incorporating artificial intelligence (AI)-assisted parameter optimization and dynamic weight adjustment. This innovative approach overcomes the inherent limitations of single-parameter and static evaluation methods commonly employed in new exploration areas. Focusing on the Upper Ordovician Wufeng Formation to Lower Silurian Longmaxi Formation shale sequences within the Anchang Syncline of northern Guizhou, a comprehensive geological characterization of shale reservoirs was accomplished through the fine processing of 3D seismic data (dominant frequency: 30 Hz; signal-to-noise ratio: 8.5) and statistical analysis of logging data. Prestack elastic parameter inversion technology was utilized to quantitatively predict key geological sweet spot parameters, including the total organic carbon (TOC) content and total gas content, with model validation conducted using core test data. Coupled with prestack and poststack seismic attribute analysis, engineering sweet spot evaluation indicators—encompassing fracture development, in situ stress, the pressure coefficient, and the brittleness index—were established with well-defined quantitative criteria. By integrating multi-source data from geology, geophysics, and engineering dynamics, a three-dimensional evaluation system encompassing “preservation conditions–reservoir quality–engineering feasibility” was constructed, with the random forest algorithm employed for sensitive parameter screening. Research findings indicate that high-quality shale in the study area exhibits a thickness ranging from 17 to 22 m, characterized by a TOC content ≥ 4%, gas content of 4.3–4.8 m³/t, effective porosity of 3.5–5.25%, and brittleness index of 55–75. These properties collectively manifest the “high organic matter enrichment, high gas content, and high brittleness” characteristics. Through multi-parameter weighted comprehensive evaluation using the Analytic Hierarchy Process (AHP), complemented by sensitivity testing, sweet spots were classified into three grades: Class I (63 km²), Class II (31 km²), and Class III (27 km²). An optimized well placement scheme for the southern region was proposed, taking into account long-term production dynamics and economic assessment. This study establishes a multi-parameter, multi-technology integrated sweet spot evaluation system with strong transferability, providing a robust scientific basis for the large-scale exploration and development of shale gas in northern Guizhou and analogous complex structural regions worldwide. Full article

The rapid development of the lithium battery industry resulted in a large accumulation of spodumene mining residue (SMR). This paper explored the feasibility of using SMR as mineral admixtures in cement mortar. The properties of cement mortar, including flexural strength, compressive strength, fluidity, hydration characteristics, and durability, were studied. The interaction mechanism between SMR and cement mortar had been explored using the Dinger–Funk model, isothermal calorimetry, X-Ray Diffraction (XRD), fourier Transform Infrared Spectroscopy (FTIR), and thermogravimetry (TG) methods. Additionally, the environmental impact of cement mortar was quantitatively evaluated by the life cycle assessment method. The results showed that, while the dosage of SMR was no more than 20 wt.% replaced cement, the flexural strength, compressive strength, and anti-carbonation and sulfate corrosion resistance properties of S2 and S3 cement mortar were similar to that of the blank group. After curing for 28 d, the compressive strength of S1, S2, and S3 were 44.2 MPa, 43.15 MPa, and 40.32 MPa, respectively. SMR powder could improve the workability and reduce the cumulative hydration heat of cement mortar, which confirmed its application potential in large-volume concrete projects. The appropriate content of SMR incorporation into cement mortar could improve the structure and properties of cement-based materials through particle filling, the induced nucleation effect, and the pozzolanic effect. In addition, the utilization of SMR reduced the environmental emissions and resource consumption of cement-based materials. Using 1 m³ cement mortar as an example, for every 10 wt.% increase in SMR powder replacing cement, the energy consumption, the emissions of CO₂, CO, C_xH_y, NO_x, SO₂, dust, and resource consumption of cement mortar were decreased by approximately 342 MJ, 40 kg, 8.1 g, 5.55 g, 88.3 g, 5.24 g, 1.80 kg, and 74.3 kg, respectively. The research findings of this paper are expected to promote the resource utilization of SMR and reduce the carbon emissions of the building materials industry. Full article

This study presents a surrogate-assisted multi-objective numerical framework to analyze and optimize the coupled effects of geometric parameters on the spray cone angle and discharge coefficient of a pressure swirl nozzle under microgravity conditions. Three-dimensional CFD simulations combined with an orthogonal experimental design were used to construct a structured dataset, on which parameter sensitivity and objective inconsistency were diagnosed using the Analytic Hierarchy Process. Back-propagation neural network surrogate models were then developed and coupled with the NSGA-II algorithm to explore the continuous design space and identify Pareto-optimal solutions. CFD re-evaluations show that, under identical operating conditions, the Pareto-based optimized configuration increases the spray cone angle from 64.71° to 69.14° while improving the discharge coefficient from 0.2736 to 0.3903 relative to the baseline nozzle. The results demonstrate that explicitly accounting for the trade-off between spray spreading and flow capacity enables a more balanced nozzle design than conventional weighted optimization approaches, providing a quantitative reference for microgravity-relevant injector design. Full article

Micro, small and medium-sized enterprises (MSMEs) play a fundamental role in the socio-economic development of Ibero-America. However, they face structural and contextual challenges that constrain their sustainable growth. This study analyses the key determinants of MSMEs’ growth in the region using a quantitative approach based on a Random Forest model applied to a dataset of 1796 observations collected by a team of researchers from different universities affiliated with the Foundation for Strategic Analysis and Development of Small and Medium-Sized Enterprises (FAEDPYME). The results reveal that sound corporate governance, effective human talent management supported by strong organisational communication, the development of skills to reduce the digital divide, innovation, and environmental perception constitute hierarchically significant factors for business development and sustainability. Relevant patterns that enable business sustainability are discussed, and a basis for the formulation of public policies aimed at strengthening the productive fabric is provided. This study offers empirical evidence that contributes to the ongoing discussion on innovation and sustainability among MSMEs in Ibero-America. Full article

HVDC technologies based on fully controlled devices offer numerous technical advantages, such as flexible active and reactive power control and black-start capability, making them highly promising for large-scale renewable energy integration and long-distance power transmission. However, their widespread adoption is constrained by high costs and significant power losses. Unlike existing hybrid HVDC schemes predominantly based on LCC-MMC structures, this paper proposes a novel hybrid current source converter-based HVDC (HCSC-HVDC) topology composed of IGCTs and thyristors, which enables power decoupling and achieves an approximate 70.5% reduction in high-voltage capacitor requirements, fundamentally improving system economy and structural efficiency. Firstly, the topological structure of the HCSC is introduced and a mathematical model is established. Then, the power operating range of the hybrid converter is quantitatively analyzed, and an optimization method for AC filter parameters is derived, based on which a power decoupling control strategy and a reactive power coordination control (RPCC) strategy are proposed. Finally, PSCAD electromagnetic transient simulations verify the effectiveness and feasibility of the proposed topology and control methods. Full article

Environmental Health Practitioners (EHPs) play a critical regulatory role within municipal health services, yet their occupational health and safety (OHS) risks remain poorly characterised in the literature. This narrative review synthesises evidence on the physical, biological, chemical, ergonomic, and psychosocial hazards encountered by EHPs during routine municipal inspection and enforcement activities. A structured literature search across major databases was conducted, and findings were synthesised using a risk characterisation framework to examine hazard types, exposure pathways, and associated health outcomes. The review demonstrates that EHPs are exposed to simultaneous and interacting hazards through multiple routes, including inhalation, dermal contact, ingestion, traumatic incidents, and psychosocial strain. Where available, quantitative indicators of exposure magnitude from inspection-relevant environments were identified, highlighting both potential risk severity and significant gaps in direct exposure measurement. Importantly, the findings indicate that occupational risks faced by EHPs are largely systemic, shaped by organisational constraints, resource limitations, enforcement contexts, and broader governance conditions rather than isolated individual behaviours. This review contributes to safety science by providing an integrated conceptual model of EHP occupational exposure pathways and by highlighting the need for system-level OHS interventions within municipal health services. Strengthening PPE provision, organisational support, and exposure monitoring is essential to improving EHPs safety and the effectiveness of environmental health regulation. Full article

The efficient use of resources represents a critical challenge for public healthcare systems facing increasing demand. In this study, an operational analysis was conducted at Hospital del Mar (Barcelona) to demonstrate that persistent bottlenecks and capacity deficits are primarily organizational and not only quantitative. Through a prospective observational study and exploratory data analysis (EDA), it was identified that high apparent workloads often coexist with structural inefficiencies, particularly regarding the unpredictable demand of urgent and inpatient procedures. To address these gaps, a Mixed-Integer Linear Programming (MILP) model was implemented to optimize spatial and temporal resource allocation. Unlike reactive scheduling, this data-driven approach explicitly incorporates capacity reserves for non-programmable activities and ensures realistic time slots without increasing physical or human resources. It is shown that MILP-optimized scheduling significantly balances workload, eliminates artificial overlaps, and improves room utilization—reaching rates of 99.5%. The findings highlight that temporal agenda design constitutes a critical, yet underutilized, lever for hospital management. A scalable tool for evidence-based decision-making is provided by this framework, allowing for a clear distinction between apparent productivity and real efficiency. The proposed model is considered highly transferable to other clinical settings facing similar operational constraints. Full article

Background/Objectives: The aviation sector is characterized by high-density flight operations and chronic stressors that compromise worker health. This study focuses on burnout syndrome as a multidimensional phenomenon resulting from the interaction between high emotional demands and personal resources. The primary objective was to analyze the relationship between job satisfaction and health problems among cabin crew members, testing a structural model where burnout—specifically its dimensions of enthusiasm toward the job, psychological strain, indolence, and guilt—acts as a mediating factor. Methods: A quantitative, cross-sectional design was implemented with a sample of 732 cabin crew members from an international airline. Participants completed the Spanish Burnout Inventory (SBI) and the UNIPSICO subscales for job satisfaction and psychosomatic problems. Data was processed using Structural Equation Modeling (SEM) to evaluate the hypothesized interdependent relationships and global model fit. Results: The structural model demonstrated an acceptable fit (CFI = 0.890; RMSEA = 0.056), confirming that job satisfaction is positively related to enthusiasm toward the job and inversely associated with psychological strain. All burnout dimensions were significantly linked to health outcomes; notably, guilt was identified as a critical mediator between indolence and psychosomatic problems. Conclusions: The findings underscore burnout as an insidiously progressive process that mediates the deterioration of cabin crew health. The study highlights guilt as a determining factor in the syndrome’s severity. Consequently, preventive organizational strategies must move beyond general fatigue management to include emotional labor training and early diagnosis of psychosocial risks to preserve operational safety and crew well-being. Full article

This study aimed to adapt and psychometrically validate the Socio-Educational and Cultural Ambivalence Scale (EASC) in the context of Chilean intercultural education, considering teachers, students, and parents/caregivers. Socio-educational ambivalence is defined as the coexistence of contradictory beliefs, emotions, and practices in the relationship between dominant school knowledge and Mapuche educational knowledge. Using a sequential mixed qualitative–quantitative design, we conceptually reviewed the original instrument and administered the adapted version to a sample of 739 participants (266 teachers, 286 students, and 183 parents/caregivers) from the regions of Biobío, La Araucanía, and Los Lagos. We proposed two six-factor scales: one shared by adults (teachers and parents/caregivers) and another with the same structure but fewer indicators for students. Confirmatory factor analysis (CFA) showed good model fit for both teachers and parents/caregivers (χ² = 1100.85, df = 311, p < 0.001; RMSEA = 0.075; SRMR = 0.058; CFI = 0.934; TLI = 0.926) and students (χ² = 378.546, df = 146, p < 0.001; RMSEA = 0.074; SRMR = 0.033; CFI = 0.978; TLI = 0.974). Composite reliability coefficients were ω = 0.702–0.974 for adults and ω = 0.749–0.948 for students. The results support factorial validity, internal consistency, and scalar invariance for the adult category of the instrument (teachers and parents/caregivers), confirming its usefulness for assessing epistemic and cultural tensions in intercultural educational contexts. The EASC contributes to the development of tools that foster a more plural, reflective, and context-sensitive understanding of education in Indigenous territories. Full article

To advance marine thunderstorm forecasting and enhance the operational utility of lightning data, this study developed a novel very low-frequency (VLF) lightning data assimilation scheme for the South China Sea region. The three-dimensional graupel mixing ratio field was successfully inverted from VLF lightning detection data through the application of an empirical formula linking lightning frequency to graupel mass, a database of graupel mixing ratio profiles, and a distance-weighted diffusion scheme. This reconstructed field was then subjected to horizontal diffusion and assimilated into the Weather Research and Forecasting (WRF) model using the Grid Nudging module within the WRF–Four-Dimensional Data Assimilation (WRF-FDDA) system. A quantitative evaluation of 37 nocturnal marine convective cases was conducted using Fengyun-4A(FY-4A) satellite observations. The results demonstrate that the proposed assimilation method significantly enhances short-term (0–6 h) forecast performance. Specifically, the Fractions Skill Score (FSS) derived from the Advanced Geosynchronous Radiation Imager (AGRI) data increased rapidly during the early forecast stage, exceeding a value of 0.9. Meanwhile, the Lightning Mapping Imager Event (LMIE) product evaluation showed a high probability of detection (POD) of 85% for lightning forecasts, with a false alarm ratio (FAR) of only 9%. These findings indicate that the assimilation approach improves the accuracy of capturing the spatial structure and evolution of convective systems. Although the degree of improvement diminished with longer lead times, the results confirm the value of VLF lightning data in initializing convective-scale processes and underscore its practical value in marine nowcasting applications. Full article

Owing to the high pharmacological relevance and multidimensional quality attributes of Panax spp., accurate authentication and quality evaluation of Panax-derived herbal materials remain challenging within traditional Chinese medicine (TCM) quality control systems. Conventional approaches often face trade-offs among analysis speed and throughput, non-destructive measurement, and analytical accuracy, which can limit their suitability for modern, large-scale quality control. This review summarizes recent advances in vibrational and related analytical techniques—infrared (IR) and near-infrared (NIR) spectroscopy, Raman spectroscopy, terahertz (THz) spectroscopy, hyperspectral imaging (HSI), and nuclear magnetic resonance (NMR)—for authentication and quality evaluation of Panax materials. We compare the capabilities of each modality in supporting key tasks, including species authentication, geographical origin tracing, age/cultivation-stage discrimination, and quantitative assessment of major chemical markers, with emphasis on the underlying measurement principles. In general, NIR and HSI are well suited to rapid, high-throughput screening of bulk samples, whereas Raman and NMR provide higher chemical specificity for molecular and structural characterization. To mitigate limitations of single-modality analysis, this review discusses a methodological shift from conventional spectral fingerprinting and chemometric approaches toward model-driven, data-enabled sensing strategies for robust quality evaluation. Specifically, we highlight multimodal data fusion frameworks combined with interpretable machine-learning/deep-learning methods to build robust classification and regression models for quality assessment. This perspective aims to support standardized and scalable authentication and quality evaluation of Panax herbal materials and to facilitate the digitization of quality control workflows for Chinese herbal medicines. Full article