Search Results (3,337)

We present a novel method for deriving radially resolved dynamical chronometers from galaxy rotation curves, allowing galaxy assembly histories to be reconstructed directly from kinematic data. In the Nexus Paradigm, the baryonic Tully–Fisher relation is used to estimate the dynamical mass profile. We compare this profile with independently derived intrinsic baryonic mass distributions obtained from stellar Sérsic fits and gas surface-density measurement yields. This yields a radial ratio that maps to formation redshift with radial resolution. Inverting this ratio within a standard cosmological framework produces a radial lookback-time profile, representing the time since each radial shell last experienced dynamical reconfiguration. Applying the method to a pilot sample of seven SPARC galaxies, including both high- and low-surface-brightness systems as well as the Milky Way, reveals diverse age structures: stratified profiles associated with inside-out growth and flatter profiles consistent with coherent disk assembly. The method requires no dark-matter halo fitting and offers a kinematic chronometer that complements stellar population and chemical evolution approaches. The NP rotation-curve parameters were determined by minimizing the chi-squared statistic between the observed and predicted velocities using a two-stage optimization consisting of a global differential-evolution search followed by nonlinear least-squares refinement. Observational uncertainties were taken from the published rotation-curve data, supplemented by a 5 km s⁻¹ systematic error floor added in quadrature to account for non-circular motions and other unresolved systematics. We also show that the governing dynamical equation admits a gravitoelectromagnetic interpretation, in which a velocity-dependent term generates disk-wide torques that regulate angular momentum transport. This leads to a unified stability framework in which galaxy morphology emerges from a single parameter regime: balanced conditions favor a coherent spiral structure, whereas dynamically hot regimes naturally produce diffuse and ultra-faint systems. The cosmological scaling of the effective gravitomagnetic field further suggests that the spiral structure is partly regulated by cosmic time. Although the inferred ages depend on the accuracy of the baryonic mass reconstruction and on the local validity of the evolving baryonic Tully–Fisher relation, our results show that rotation curves encode time-resolved dynamical information. This establishes the radial dynamical chronometer as a new observable for studying galaxy evolution and testing gravitational frameworks. Full article

This study claims that the Nigerian tourism and hospitality industry must shift from traditional business practices to innovative, knowledge-based approaches to remain competitive and achieve long-term wealth creation. Facing volatility, evolving consumer demands, technological change, and sustainability pressures, the sector cannot rely on outdated models. Through a quantitative survey of 391 staff and top-level managers from the Nigerian Tourism Development Corporation and tourism organizations in Southwest and North-Central Nigeria, this research tests how creativity, knowledge management, and innovation operations, defined as value creation, environment, and capability, drive wealth creation. Findings through the Partial Least Squares Structural Equation Modeling show that innovation and knowledge management both directly and, through the mediating role of innovation operations, significantly enhance wealth creation. By highlighting how these factors interact, the study advances understanding of wealth creation dynamics between emerging and developed economies and delivers actionable recommendations for managers and policymakers to institutionalize innovation for sustainable industry growth. Full article

Microplastics (MPs) are widely recognized as emerging contaminants in freshwater environments. Their identification often relies on extensive sample preparation and chemical treatments, which increase analysis time, reagent use, and overall resource consumption. Consequently, there is a growing need for sustainable analytical approaches enabling reliable MP detection while minimizing sample handling. This study proposes an analytical workflow based on hyperspectral imaging (HSI) as a proof-of-concept approach for direct identification of MPs in freshwater samples. Water samples collected from three different rivers, containing heterogeneous natural materials, were spiked with MPs (250–1000 μm) of three common polymers, namely high-density polyethylene (HDPE), polystyrene (PS), and polypropylene (PP), to simulate realistic contamination scenarios. HSI acquisitions were performed in the short-wave infrared range (SWIR: 1000–2500 nm). Spectral preprocessing and principal component analysis (PCA) were applied for data exploration, while a hierarchical partial least squares-discriminant analysis (Hi-PLS-DA) model was developed to classify five target classes: natural materials, water, HDPE, PS, and PP. Despite sample complexity, the proposed workflow achieved satisfactory classification results, as demonstrated by the predicted class map and the corresponding statistical metrics (sensitivity, specificity, precision, and F1-score: 0.900–0.999). These results highlight the potential of the SWIR-HSI-based approach as a rapid and sustainable method for direct MP identification in freshwater samples and provide methodological insights for rapid MP screening strategies requiring minimal sample preparation. Full article

Temperature variability and weather-related fluctuations significantly affect the energy, agricultural, and industrial sectors that are highly sensitive to meteorological changes. These conditions may lead to financial losses caused by demand fluctuations and operational disruptions. This study aims to develop a fractional weather-derivative pricing model based on temperature dynamics by integrating the Ornstein–Uhlenbeck (OU) process, the classical Black–Scholes model (BSM), and the fractional Black–Scholes model (fBSM). Daily temperature data from 2016 to 2025 obtained from the Bandung Geophysical Station, West Java, Indonesia, were used as the basis of analysis. Temperature dynamics were modeled using an OU process, and parameter estimation was conducted using Ordinary Least Squares (OLS). The strike price was determined using Historical Burn Analysis (HBA), whereas weather-derivative pricing was performed using call and put option approaches under both the BSM and fBSM frameworks, incorporating the Hurst parameter to capture long-term memory effects. The results indicate that the fractional Black–Scholes model analytical solution is obtained using the Daftardar–Gejji Aboodh method. Furthermore, the OU process successfully captured daily temperature dynamics, yielding a Mean Absolute Percentage Error (MAPE) of 4.344% and a Root Mean Square Error (RMSE) of 1.396 C, indicating high predictive accuracy across both relative and absolute error measures. In addition, the fBSM consistently generated higher option values than the classical BSM, particularly under higher observed temperatures during the study period and at higher strike prices. These findings demonstrate that long-term memory significantly influences effective volatility and option valuation. This study is expected to contribute to the development of weather derivative models that more realistically represent temperature dynamics and to serve as a reference for weather derivative pricing, hedging, and decision-making, as well as for more measurable, systematic, and sustainable climate-related financial analysis using derivative pricing frameworks. Full article

Vermicomposting is an eco-friendly biotechnology for organic waste valorization. As the primary product of earthworm biotransformation, vermicompost is a high-value bio-organic fertilizer abundant in diverse biologically active components. To date, most studies have focused on quality variation during the earthworm transformation process, while research on quality variations in the resulting vermicompost fertilizer during long-term storage remains scarce. To explore the shelf-life of vermicompost fertilizer and its key influencing indicators, this study investigated the changes in quality indicators in sealed-packaged vermicompost over a 180-day period using two typical vermicompost, namely cattle manure vermicompost (CM) and straw-amended cattle manure vermicompost (CMS). The temporal dynamics of physicochemical properties, nutrient contents, humification indices, enzyme activities, and microbial communities were monitored. The vermicompost quality was evaluated, and core quality drivers were identified using an integrated principal component analysis-partial least squares (PCA-PLS) approach. The results indicated that moisture content (MC), total organic carbon (TOC), and total nitrogen (TN) declined progressively, whereas available phosphorus (AP) and available potassium (AK) peaked at day 150 and day 120, respectively, and the humification rate (HR) increased by 2.6–4.0-fold. Bacterial diversity and relative abundance slightly decreased, accompanied by taxonomic differentiation, whereas fungal communities maintained stable diversity. Most enzyme activities, including urease, phosphatase, catalase, and dehydrogenase, reached their maxima at day 120. Comprehensive quality scores peaked at day 150, with a marked decline observed by day 180. The recommended shelf-life of vermicompost fertilizer is 150 days. The key quality determinants include TN, electrical conductivity (EC), pH, actinomycete abundance, TOC, TP, bacterial abundance, AP, AK, and HR. These findings provide theoretical support and references for the storage management and quality control of commercial vermicompost products in practice. Full article

Flow-cell ultrasonication of gelatinized rice flour slurries alters cultivar-dependent water solubility, viscosity, and retrogradation of pregelatinized rice flour, properties important for plant-based beverages and convenience foods. We tested whether cultivar-level composition descriptors, amylose, protein, and fiber, can represent cultivar-associated variation in ultrasonication responses while separating process-only prediction, within-domain cultivar representation, and unseen-cultivar transfer. Six rice cultivars were processed across nine amplitude-time combinations and two slurry concentrations. Water solubility index, apparent viscosity at a shear rate of 50 s⁻¹, and setback viscosity were modeled using ElasticNet, partial least squares regression, support vector regression, random forest, and extreme gradient boosting. Three input formulations were compared: process variables alone, process variables plus composition descriptors, and process variables plus cultivar identity. Repeated nested group cross-validation showed insufficient process-only prediction and substantial improvement from composition descriptors. Within-domain validation showed comparable composition-descriptor and cultivar-identity performance under nonlinear algorithms. However, because cultivar identity is undefined for absent cultivars, leave-one-cultivar-out transfer of the composition-descriptor model remained uncertain. Cross-fitted Shapley additive explanations showed predictions used process and composition variables. For the validated cultivar-process domain, this approach can screen cultivar-process combinations for beverage and convenience-food applications, but replacing categorical source identifiers with continuous descriptors requires explicit transfer validation. Full article

Drawing on institutional theory and agency theory, this study examines whether venture capital (VC) and private equity (PE) ownership acts as a complement to, or substitute for, investor protection in shaping equity financing, debt financing, and leverage decisions in high-tech entrepreneurial firms. The analysis is based on a panel dataset of 403 high-tech entrepreneurial firms from 11 European countries over the period 2009–2013. To address potential endogeneity and reverse causality between external finance and VC/PE investment, the study employs two-stage least squares (2SLS) regression models using an instrumental-variable approach. The results provide tentative evidence that VC/PE ownership is associated with stronger debt-related financing outcomes, particularly leverage, in countries characterised by weaker investor protection, suggesting a possible substitutive relationship in debt-related financing outcomes. However, these findings should be interpreted cautiously given the limitations associated with the instrumental-variable strategy. The study contributes to the literature on entrepreneurial finance, corporate governance and law and finance by showing how firm-level governance mechanisms interact with national institutional settings in shaping financing decisions. Full article

Wildfires increasingly contribute to urban particulate matter (PM) exposure, particularly fine particles (PM_2.5), through atmospheric transport processes influenced by meteorological conditions and terrain complexity. This study investigated wildfire impacts on PM₁₀ and PM_2.5 concentrations in Split, Solin, and Kaštela (Croatia) using a terrain-aware wildfire transport framework combined with statistical and machine learning (ML) approaches. Daily PM observations (2016–2024) from three air quality monitoring stations were integrated with meteorological data from six stations, wildfire polygons, and a digital elevation model (DEM). A wildfire influence index accounting for fire size, transport distance, wind conditions, and terrain-modified airflow was evaluated using Ordinary Least Squares (OLSs) regression, Random Forest (RF) modelling, and SHAP (SHapley Additive exPlanations) analysis. Results showed stronger wildfire-related effects for PM_2.5 than for PM₁₀, while meteorological variables remained the dominant predictors of PM variability. RF models improved predictive performance relative to OLS, achieving $R^2$ = 0.474 for PM_2.5 and $R^2$ = 0.416 for PM₁₀. SHAP analysis identified precipitation, temperature, and lagged wildfire transport variables as important predictors. A total of 84 wildfire events were classified as effective wildfires, with most measurable impacts occurring within approximately 30–70 km of monitoring stations, indicating that wildfire impacts on urban air quality in Mediterranean coastal environments are strongly mediated by atmospheric transport and meteorological conditions. The proposed framework demonstrates the potential of explainable and geospatially informed ML for environmental monitoring and wildfire-related urban air quality risk assessment. Full article

The factor structure of the Utrecht Work Engagement Scale (UWES) has been debated, with studies alternately supporting unidimensional and three-factor solutions. This inconsistency may reflect a methodological limitation: conventional confirmatory factor analysis (CFA) cannot always separate general from dimension-specific variance, producing similar fit indices across competing models when a dominant general factor is present. We examined the dimensionality of the UWES-17 and UWES-9 in a sample of 755 Chilean university students, comparing unidimensional, three-factor, second-order, and bifactor models using weighted least squares mean and variance adjusted (WLSMV) estimation appropriate for ordinal data. Bifactor indices, explained common variance (ECV), percent of uncontaminated correlations (PUC), and hierarchical omega (ω_h), were computed to evaluate essential unidimensionality. Results indicated that a general engagement factor explained approximately 85% of common item variance in both versions (ECV ≈ 0.85; ω_h > 0.90), while specific factors for vigor, dedication, and absorption retained negligible reliable variance, particularly absorption (ω_h ≈ 0.00). Measurement invariance by sex was supported for the UWES-9 at the metric level, whereas classical UWES-17 solutions showed instability, including factor collapse and non-convergence of the second-order model. Taken together, findings suggest that the apparent multidimensionality of the UWES may be, at least partly, an artifact of conventional CFA modeling rather than a substantive property of the construct in this student sample. For applied monitoring of student well-being, the UWES-9 total score appears to be the most pragmatic and psychometrically defensible approach for assessing general academic engagement in this Chilean university sample, while institutional well-being monitoring would ideally be further supported by criterion-related, predictive, and sensitivity-to-change evidence. Full article

This study examines the role of circular services in generating economic value within the construction sector, focusing on firms belonging to the Sustainable Habitat Cluster in the Aburrá Valley, Colombia. The research analyzes how circular business model strengthening translates into economic outcomes through the implementation of circular service portfolios. Using a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, the study evaluates the relationships between circular business model capabilities, circular service implementation, and circular revenue generation. The results confirm a sequential mechanism linking strategic capabilities to economic outcomes, where strengthening circular business models significantly enhances the implementation of circular services, which in turn strongly predicts the generation of circular revenues. The findings indicate that circular strategic orientation is a necessary but insufficient condition for economic value creation, as monetization occurs only when circular principles are translated into concrete service offerings. The study highlights the central role of circular services as the operational bridge between strategic readiness and economic performance, contributing to the literature on circular business models and Product–Service Systems (PSS) by providing empirical evidence of how circular strategies translate into revenue generation within the built-environment sector. Full article

This study discusses the influence of Digital Leadership (DL) on Sustainable Innovation Performance (SIP) in telecommunications companies. In addition to examining the direct effect of Digital Leadership, the study focuses on the mediating roles of Knowledge Sharing (KS) and Employee Engagement (EE). A sample of 412 employees was collected by a simple cross-sectional survey. A partial least squares structural equation modeling (PLS-SEM) approach was used for analyzing results. The study reveals that Digital Leadership directly and positively enhanced Knowledge Sharing but did not lead to a significant direct influence on Employee Engagement and Sustainable Innovation Performance. Moreover, Knowledge Sharing did not significantly influencing Sustainable Innovation Performance, a condition that was the strongest predictor of Sustainable Innovation Performance emerging from Employee Engagement. The mediation analysis shows that neither Knowledge Sharing nor Employee Engagement mediates the relationship between Digital Leadership and Sustainable Innovation Performance. The objective contribution of this study is to shed light on the idea that Digital Leadership and Sustainable Innovation Performance are not directly related but may instead reflect other circumstances or contextual conditions. The research offers practice advice in showing that Employee Engagement benefits organizational sustainable innovation results by urging companies to consider not only Digital Leadership strategies but also alternative strategies that foster employee involvement. Full article

Understanding the impact of neighborhood-level factors on stroke prevalence is crucial for addressing existing disparities. However, there is a distinct lack of ecological studies at the census tract level that investigate the social determinants of health (SDOH) influencing stroke prevalence within the U.S. Health and Human Services Region 3 (HHS Region 3: Delaware, Maryland, Pennsylvania, Virginia, West Virginia, and the District of Columbia). This study adopted a multivariate modeling approach to investigate the association between the 13 indicators of the Health Opportunity Index (HOI) and stroke prevalence at the census tract level in HHS Region 3 using four HOI indicator profiles and to highlight the specific SDOHs that are most associated with stroke prevalence. The four HOI indicator profiles include: (a) neighborhood and built environment profile, (b) social and community context profile, (c) resource profile, and (d) economic profile. The methodological approach was quantitative, using secondary data. The sample size was 8021 census tracts. The HOI was estimated for each census tract in the study area. Ordinary least squares regression (OLS) analysis and spatial lag model (SLM) were run to examine whether the 13 indicators of the HOI (categorized into four profiles) reliably predict stroke prevalence and to determine the most appropriate model that best identifies the strongest predictors of stroke prevalence. The results show that affordability, education, spatial segregation, and income inequality indicators were the strongest predictors of stroke prevalence in HHS Region 3. This granular research identifies the neighborhood-level SDOH most strongly linked to stroke prevalence, which can be leveraged to guide the development of targeted public health programs, quality improvement initiatives, resource allocation, and policy creation to combat stroke-related morbidity and mortality across census tracts in HHS Region 3. For example, the built environment, encompassing factors like employment access, affordable housing, and walkability, profoundly influences stroke prevalence and provides urban planners with practical insights for developing healthier, more equitable communities, such as creating neighborhood parks to encourage physical activity, a key factor in stroke prevention. This study also provides neighborhood organizations with the evidence needed to pursue grant funding and raise awareness about the socio-structural influences on stroke outcomes in their respective neighborhoods. Lastly, the insights generated from our study can facilitate collaborative decision-making processes with communities in HHS Region 3 regarding the prioritization of neighborhood-level SDOH for targeted public health interventions. This prioritization should focus on addressing predictors of stroke prevalence that are congruent with the community’s established priorities, thereby maximizing cost savings. Full article

This study analyzes the determinants of self-reported behaviours and perceptions associated with pesticide toxicity risk in children using the Social Practice Theory framework, linking individual factors and agricultural practices to understand vulnerability and prevention opportunities. This research was conducted in Pattapang Village, Tinggimoncong District, Gowa Regency, South Sulawesi Province, Indonesia. To examine the relationship between pesticide use patterns, social norms, competence, material, and individual aspects and the risk of sensitive toxicity in children, data were analyzed using structural equation modeling-partial least squares (SEM-PLS) with bootstrapping resampling. Pesticide use patterns had a significant negative effect on toxicity risk. Competence was the strongest predictor of pesticide use patterns, followed by materials and short-term goals. Personal values dominate personal norms and long-term goals, while social norms only influence personal norms. Self-efficacy, personal norms, and long-term goals showed no significant effects. The novelty of this research lies in the integration of a socio-ecological approach with individual psychological factors in a comprehensive structural model that explains the complex mechanisms of children’s protective behavior formation from pesticide toxicity, identifying that personal values—not personal norms or self-efficacy—are the most effective leverage points for farmer behavior change interventions. Full article

While Zanthoxylum bungeanum Maxim. (Z. bungeanum) pericarps are a globally prized spice, their leaves are frequently discarded as agricultural waste. This study systematically characterizes the aromatic potential of leaf by-products compared with traditional pericarps under diverse extraction strategies, utilizing an integrated flavoromics and sensomics approach. Qualitative GC-MS-O analysis revealed that leaf-derived fractions possess superior aromatic diversity: leaf essential oil and volatile solvent extract yielded 71 and 68 odorants, respectively, significantly surpassing pericarp counterparts (65 and 43 compounds). Concurrently, HS-GC-IMS profiling confirmed that targeted extraction allows leaf-derived flavors to replicate and exceed traditional spice complexity. Specifically, the leaf solvent extract achieved aromatic parity with pericarps by effectively mirroring the core spicy–citrus profile through cuminaldehyde and limonene retention. Conversely, distilled leaf essential oil unlocked a distinctive herbal–woody sensory innovation, driven by eucalyptol and a broader variety of aldehydes and ketones. Sensomics validation, incorporating aroma recombination, omission experiments, and partial least-squares regression modeling, conclusively identified β-myrcene, limonene, caryophyllene, and humulene as core molecular markers dictating these perceptual shifts. Ultimately, this research provides a robust theoretical foundation for upcycling Z. bungeanum leaves into valuable flavoring resources, facilitating circular bio-economy practices by delivering functional equivalence and entirely novel sensory experiences for the global food industry. Full article

This study examines the association between corporate governance and financial performance and investigates whether real earnings management (REM) mediates this relationship in an emerging-market context. Using a balanced panel of 434 nonfinancial listed firms in Vietnam from 2020 to 2024, yielding 2170 firm-year observations, the study employs feasible generalized least squares (FGLS) after diagnostic tests indicate heteroskedasticity and autocorrelation. The Durbin–Wu–Hausman test does not indicate significant endogeneity in the current model specification. REM is measured using the Roychowdhury-based approach, and mediation effects are examined through sequential regressions. Tobin’s Q is used for robustness testing, and a two-step System GMM is used as an additional robustness test. The results show that board size, institutional ownership, and state ownership are positively associated with financial performance, while board independence is negatively associated with performance. Board financial expertise has no significant direct relationship with performance. REM is negatively associated with financial performance and serves as a mediating channel in the governance–performance relationship. The study contributes to the corporate governance literature by showing that REM can transmit governance effects to firm performance in an emerging market characterized by evolving enforcement, state ownership, and potential gaps between formal and substantive governance mechanisms. Full article