Search Results (3,002)

Background/Objectives: Mental health issues pose a growing public health burden in aging societies, a challenge particularly accentuated in rural China. This study investigated whether the establishment of rural community organizations—specifically volunteer groups, agricultural cooperatives, cultural and sports clubs, senior dance troupes, and senior associations—influences depressive symptoms and life satisfaction among rural older adults. Methods: Data were obtained from the Well-being of Elderly Survey in Anhui Province (WESAP) across three waves (2015, 2018, and 2021). The final sample comprised a balanced panel of 511 older adults, providing 1533 observations. A two-way fixed-effects model was employed to analyze the data. Results: Empirical results show that the establishment of agricultural cooperatives was associated with lower depressive symptoms. Cultural and sports clubs were associated with reduced depressive symptoms and positively correlated with life satisfaction. Mechanism analysis revealed associations consistent with a dual “economic–social” pathway: establishing agricultural cooperatives was associated with greater economic resilience and stronger social bonds. The establishment of cultural and sports clubs correlated with higher mental well-being, accompanied by increased time spent in social interaction. Notably, volunteer groups and senior associations showed no significant association with mental health outcomes. Conclusions: Rural community organizations are critical drivers of mental health equity. Policymakers should prioritize support for organizations that are deeply embedded in rural daily life and integrate economic functions with social interaction to maximize mental health benefits for older adults. Full article

In this study, a comprehensive mathematical method for modeling the operational reliability of mine hoisting equipment under conditions of incomplete and heavily censored data is developed. The analyzed dataset includes 259 observations collected over a five-year period for six critical components, with the overall level of censoring reaching 62% and exceeding 70% for long life mechanical subsystems. Considering right, left, and interval censoring, the paper proposes a unified statistical procedure that combines empirical estimation of failure rates with parametric identification using Weibull, exponential, normal, and lognormal distributions. Model parameters are estimated using censored data–aware fitting procedures, while model selection is performed based on likelihood-based criteria, supplemented by correlation analysis to assess agreement between empirical and fitted reliability curves. The methodology is implemented computationally in the Mathcad Prime environment and is supplemented with mathematical tools for reconstructing survival curves, analyzing parameter sensitivity, and evaluating robustness at different censoring levels. In addition, an economic optimization model is formulated to determine cost-effective maintenance intervals by minimizing an integral functional that accounts for preventive maintenance, repair, and downtime costs. The results demonstrate that the proposed approach provides stable reliability estimates and reliable forecast intervals, enabling the construction of generalized life cycle curves for individual subsystems. The study establishes a rigorous mathematical basis for the transition from fixed-interval maintenance to adaptive, reliability-oriented maintenance strategies in industrial mine hoisting systems. Full article

Background/Objectives: Clinical reasoning is essential in neurological rehabilitation, in which patient management is complex and multifactorial. However, existing models lack operationalization for neurophysiotherapy practice. This paper proposes the Biopsychosocial Reasoning Approach In Neurophysiotherapy (BRAIN) framework, a unified clinical reasoning model that integrates the International Classification of Functioning, Disability, and Health (ICF) with neurophysiotherapy-specific domains of physical function. Methods: The BRAIN framework was developed by integrating previously validated models: the ICF, the American Physical Therapy Association (APTA) patient-management process, and Kisner and Colby’s interrelated aspects of physical function, adapted for neurological populations. The model employs a biopsychosocial, patient-centered, and goal-oriented approach, thereby providing a structured workflow for examination, evaluation, diagnosis, prognosis, intervention, and outcomes assessment. Results: The BRAIN framework provides an operationalized mapping between ICF body functions and neurophysiotherapy-specific impairment domains, a clear separation between body functions and body structures, tiered assessment pathways addressing patient heterogeneity, and a unified language for interdisciplinary communication. The model incorporates shared decision-making and goal-oriented reasoning within the clinical workflow. Conclusions: The BRAIN framework offers a structured, teachable template for clinical reasoning in neurological physiotherapy. As a theoretical proposal, there is a need for empirical validation through expert consensus and clinical implementation studies. Full article

This study examines how environmental management systems (EMSs) function as information-based organizational capabilities that drive circular product innovation in manufacturing SMEs operating in an emerging economy. Grounded in the resource-based view (RBV) and institutional theory, the study develops and empirically tests a model linking EMSs to circular-oriented product innovation through the mediating role of green transition, while assessing the moderating influence of policy support. Data were collected through a cross-sectional survey administered in two temporally separated phases to mitigate common method bias, targeting senior managers of ISO 14001-certified manufacturing SMEs registered in the Turkish Trade Register Gazette. A total of 511 valid responses were analyzed. Measurement reliability and validity were established using confirmatory factor analysis, and hypotheses were tested via Hayes’ PROCESS macro. The results indicate that an EMS significantly enhances circular product innovation both directly and indirectly. Green transition emerges as a strong partial mediator, explaining a substantial share of the total effect, highlighting its critical role in translating environmental information, routines, and capabilities into product-level circular outcomes. While organizational sustainability policy does not moderate the EMS–green transition relationship, policy support significantly strengthens the impact of green transition on circular product innovation. Firms operating within more supportive policy environments achieve substantially higher levels of circular innovation. Overall, the study advances the understanding of how information system-enabled capabilities and supportive institutional conditions jointly shape sustainability transitions, offering insights for managers and policymakers seeking to foster circular innovation in manufacturing SMEs. Full article

While advanced imaging techniques and ordered porous materials like MOFs have gained prominence, gas sorption remains the indispensable tool for characterizing the multiscale heterogeneity of industrially important disordered solids, such as catalysts and shales. This review examines recent developments in gas sorption methodologies specifically tailored for rigid, disordered porous media. We discuss experimental advances, including the choice of adsorbate and the utility of the overcondensation method for probing macroporosity and ensuring saturation. Furthermore, we critically evaluate theoretical approaches for determining pore size distributions (PSDs), contrasting classical methods with Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) simulations. Special emphasis is placed on the impact of pore-to-pore cooperative effects, such as advanced condensation, cavitation, and pore-blocking, on the interpretation of sorption isotherms. We highlight how complementary techniques, including integrated mercury porosimetry, NMR, and computerized X-ray tomography (CXT), are essential for deconvolving these complex network effects and validating void space descriptors. We conclude that, while “brute force” molecular simulations on image-based reconstructions are progressing, “minimalist” pore network models, which incorporate cooperative mechanisms, currently offer the most empirically adequate approach. Ultimately, gas sorption remains unique in its ability to statistically characterize void spaces from Angstroms to millimeters in a single experiment. Full article

Background/Objectives: Franz Tappeiner (1816–1902) is often celebrated as a pioneer of alpine medicine and the founder of Tappeiner Promenade in Meran (South Tyrol, Italy). However, his legacy extends far beyond the scenic infrastructure, encompassing a comprehensive vision of physical activity as a public health intervention. His multidisciplinary practice anticipated the principles of contemporary rehabilitation, preventive medicine, and climate-sensitive public health. Methods: This historical public health analysis, combining biographical, contextual, and material–spatial approaches, reinterprets Tappeiner’s writings, institutional engagements, and civic projects through the lens of modern public health frameworks. Drawing on primary materials (e.g., published articles, autobiographical fragments, and commemorative texts) and recent evidence from rehabilitation and environmental health research, these contributions were contextualized. Results: Tappeiner’s early focus on infectious disease prevention (e.g., cholera and tuberculosis) transitioned into a strategic emphasis on recovery and behavioral therapy through environmental design. The walking therapy model of Max Joseph Oertel, locally realized in the Tappeiner Promenade, prefigured modern concepts such as structured green rehabilitation, walkability, and urban-health citizenship. His systematic integration of graded walking into civic infrastructure represents one of the earliest documented examples of embedding physical activity promotion at the population level. He contributed substantial personal funds to the path’s construction, embedding therapeutic gradients, curating vegetation, and promoting inclusive design to support convalescence. Contemporary research supports the intuition that green, low- to moderate-intensity walking improves cardiometabolic health, psychological well-being, and functional capacity. Moreover, his integrative ethos, merging clinical medicine, civic ethics, and spatial intervention, parallels contemporary eco-social models of public health. Conclusions: Franz Tappeiner’s career exemplifies a still-relevant model of physician leadership that is empirically grounded, socially accountable, and ecologically attuned, with physical activity promotion embedded as a central element of his public health vision. His work invites reflection on how medical professionals can shape not only individual care but also urban environments and collective health futures. Full article

We present a quantum cognitive model that integrates the influence of cognitive control into human perceptual decision-making. The model employs a multiple-square-well potential, where each well corresponds to a distinct decision outcome. In this framework, well depth encodes signal strength, while well width represents the domain generality of the outcome. The probability of particle localization within each well determines the subjective probability, which subsequently drives a standard Markovian evidence accumulation process to predict empirical choice and response times. We validate the model using the classic dot motion two-alternative forced-choice (2AFC) task. The model successfully replicates key empirical findings of the task, such as the correlation between motion coherence and drift rates. Furthermore, we apply the model to the Yerkes–Dodson law, capturing the approximate inverted U-shaped relationship between task accuracy and cognitive arousal. We compare two theoretical approaches to modeling arousal (1) as eigenenergy values and (2) as kinetic energy terms, contrasting their qualitative predictions regarding the Yerkes–Dodson law. Our work provides the first quantitative model of arousal’s influence on human perceptual decision-making and establishes a foundation for determining the exact functional form of the Yerkes–Dodson law. Full article

The public-goods nature of ecological products and heterogeneous stakeholder interests mean that protected areas often face weak coordination, limited incentives, and uneven benefit distribution in the identification, transformation, and return of ecological value. Under increasingly strict conservation objectives, ecological product provision is shifting from direct resource use towards maintaining ecosystem functions and realising experiential value. This helps safeguard ecosystem integrity but raises demands on institutional pathways for value transformation and on the sustainability of community livelihoods. Using Pudacuo National Park in China as a case, this study develops an analytical framework linking supply–demand structures, value chains, and value co-creation, and applies policy document analysis, semi-structured interviews, field observation, and process tracing to examine mechanisms of ecological value realisation under strict conservation. The results show that: (1) a collaborative governance network integrating park authorities, local governments, and concession operators provides a stable organisational basis for ecological value identification and transformation; (2) strengthened provision of non-material ecological products reorients the supply system towards regulating and cultural services, driving a shift from material output to function- and experience-oriented provision; (3) a multi-level community participation model combines labour embedding, livelihood diversification, and institutionalised benefit return to form an ecological value return mechanism grounded in value co-creation. Together, these mechanisms support a relative balance between ecological protection and community development under strict protection and offer empirical insights into the institutional logic of ecological value realisation in strongly protected contexts. Full article

In this study, we developed an SIR-like mathematical model of disease transmission dynamics. Hantavirus is a neglected tropical disease, and this paper presents a mathematical model of hantavirus transmission among rodents and its effect on the number of hantavirus-infected humans. We review an existing SIR-SIR model of hantavirus transmission and analyze it in a standard mathematical epidemiology framework. The original SIR-SIR model is summarized, with emphasis on its structural assumptions, epidemiological interpretation, and analytical results, including the derivation of the basic reproduction number and the characterization of the stability of the disease-free and endemic equilibria. A critical evaluation of the original SIR-SIR model highlights several biological limitations of the baseline model, notably, the unrealistic assumption of homogeneous transmission and the absence of ecological seasonality. To address these gaps, an improved model incorporating periodic forcing in rodent recruitment and disease transmission is proposed. The use of sine and cosine functions introduces a biologically motivated phase shift between rodent recruitment and transmission, reflecting the fact that birth pulses and peak contact rates rarely occur simultaneously in natural rodent populations. The reproduction number for the extended system is constructed using a Floquet-style argument for DFE stability. A theorem connecting the stability of the DFE with the seasonal component is presented, resembling the well-known rule for non-seasonal hantavirus transmission but with more realistic assumptions. Numerical simulations demonstrate that seasonal variation can generate oscillatory outbreak patterns that more closely reflect empirical rodent population dynamics and human risk profiles. Overall, the results underscore the importance of ecological realism in zoonotic disease modeling and provide a foundation for more accurate prediction and control of the disease, especially in NTD elimination programs. Full article

Old trees function as enduring ecological legacies that preserve historical biodiversity within intensively human-modified landscapes, yet the relative influence of environmental versus anthropogenic drivers on their diversity remains unclear. Here, we aim to disentangle the joint effects of climate, urbanization intensity and cultural preservation on old-tree density and community composition. We analyzed a province-wide census of 21,733 old-tree individuals across 115 counties in Shanxi Province, China, encompassing species origin (native vs. nonnative) and growth form (trees vs. shrubs). Old-tree density was assessed using spatial simultaneous autoregressive error models, while compositional dissimilarity was quantified using generalized dissimilarity modeling. In total, 131 species were recorded, with four dominant species comprising more than 75% of all individuals. Old-tree density increased with mean annual temperature, human population density, and cultural heritage abundance, but declined sharply with cropland coverage. Driver importance varied among groups: native species were primarily governed by climatic conditions, nonnative species by land-use intensity, and tree-form old trees were positively associated with cultural heritage abundance, an effect absent in shrub-form old trees. Compositional dissimilarity was driven mainly by climatic gradients and spatial distance, with additional contributions from human-related variables, particularly for nonnative assemblages. Our findings demonstrate that climate and spatial processes establish the regional framework of old-tree community composition, while cultural and demographic contexts promote local retention of old trees. By explicitly integrating ecological filters with socio-cultural drivers, this study advances old-tree research through a large-scale empirical framework, providing both scientific insight and socially relevant guidance for conservation under land-use intensification and climate warming. Full article

This study aims to examine how e-servicescape dimensions, demographic characteristics and user experience influence consumer perception of Peer-to-Peer (P2P) online platforms. The literature review is focused on servicescape, e-servicescape, and peer-to-peer (P2P) platforms in the hospitality sector. A relevant research model and hypothesis were established. For the empirical study, a questionnaire was developed and conducted on 135 users of P2P online platforms in the hospitality sector. Reliability analysis and hypothesis tests were identified through SPSSv31. Study results and implications were discussed and suggested. The results showed that all six subdimensions such as aesthetics, social presence, perceived personalization, perceived trust and safety, perceived interactivity and superior functionality, overall, create a positive perception in P2P users. While demographic characteristics showed no significant impact on consumer perception of the six e-servicescape dimensions, the user experience (frequency of use) confirmed that individuals that more frequently use P2P online platforms have a more positive perception of the e-servicescape. This study identified the importance of the dimensions of e-servicescape in P2P platforms in the hospitality sector and how they influence consumers’ perceptions, addressing a research gap caused by the limited empirical evidence on the role of demographic characteristics in the e-servicescape within hospitality in the sharing economy. Full article

This study analyses the long-run relationship between governance quality and renewable energy development using a global panel of 174 countries over the period 2000–2023. The objective is to assess whether institutional quality systematically influences renewable energy deployment across heterogeneous development contexts. The empirical analysis employs a panel autoregressive distributed lag (PMG-ARDL) framework, which accommodates mixed integration orders and allows for heterogeneous short-run dynamics while imposing homogeneity on long-run coefficients. Renewable energy consumption, measured as the share of renewable energy in total final energy consumption, is modelled as a function of governance quality indicators, economic development, and environmental pressure, with trade openness and foreign direct investment included as control variables. Panel unit root tests indicate a mixture of I(0) and I(1) variables, supporting the use of the ARDL framework, while panel cointegration tests provide strong evidence of a stable long-run relationship in the estimated model. The results reveal a statistically significant long-run association between governance quality and renewable energy development, although the magnitude and direction of the effects vary across governance dimensions and development levels. In contrast, short-run effects are generally weak, suggesting that governance primarily shapes renewable energy outcomes through gradual, structural channels. These findings highlight the importance of institutional quality for long-term energy transition processes and provide empirically grounded insights for the design of energy and governance policies. The analysis reveals significant heterogeneity across development contexts: governance improvements yield positive effects on renewable energy adoption in low-income countries (β = +3.77), where institutional deficits constitute binding constraints, whilst the effect becomes negative in high-income economies (β = −11.87), reflecting diminishing returns and infrastructure lock-in. These findings suggest that developing countries should prioritise governance reforms—particularly Regulatory Quality and Political Stability—to accelerate energy transitions, whereas advanced economies should shift policy attention toward grid modernisation and market design. International organisations should adopt differentiated climate finance strategies matching institutional support to the development stage. Full article

High-water-content dredged slurry from port dredging requires geotechnical improvement via drainage and consolidation. The small-strain dynamic properties (shear stiffness, damping characteristics) of reconstituted and consolidated clays are critical to the dynamic response and serviceability of overlying infrastructure. This study uses resonant column tests to investigate how initial water content affects the small-strain dynamic behaviour of reconstituted Ningbo soft clay, focusing on the evolution of the dynamic shear modulus ($G$) and damping ratio ($\lambda$) under different initial water contents and confining pressures. The test results indicate that the initial water content exerts a pronounced effect on the maximum small-strain shear modulus ($G_{\mathrm{m}\mathrm{a}\mathrm{x}}$) and on the strain-dependent degradation pattern of $G$. $G_{\mathrm{m}\mathrm{a}\mathrm{x}}$ increases with decreasing water content, and confining pressure exerts a more pronounced enhancing effect on $G_{\mathrm{m}\mathrm{a}\mathrm{x}}$ under low water content conditions. For specimens with different initial water contents, the maximum shear modulus normalised by confining pressure $(G_{\mathrm{m}\mathrm{a}\mathrm{x}}/{({\sigma }_0^{\prime }/P_a)}^n)$ exhibits a consistent, material-specific functional relationship with void ratio ($e$) within the investigated ranges. By contrast, initial water content exerts limited effects on the normalised $G/G_{\mathrm{m}\mathrm{a}\mathrm{x}}-\gamma$ and $\lambda -\gamma$ curves in the tested small-strain range. On this basis, an empirical model for small-strain shear modulus incorporating initial water content effects is proposed to guide dynamic soil parameter selection for geotechnical design under the tested conditions. Full article

This paper develops a unified analytical approach for pricing a broad class of volatility-linked financial derivatives under the sub-mixed fractional geometric Brownian motion model. The proposed framework captures key empirical features of financial markets, including correlated non-stationary Gaussian increments and long-memory dependence, while preserving the semimartingale property required for arbitrage-free pricing. We present the exact distribution of the realized variance as a quadratic form of correlated non-stationary Gaussian increments, which leads to a closed-form expression for the cumulative distribution function via a Laguerre-series expansion. These distributional results enable analytical pricing formulas for an extensive family of volatility-linked derivatives. Monte Carlo simulations confirm the accuracy and computational efficiency of the proposed formulas, while numerical investigations illustrate the significant impact of non-stationarity, long-memory effects, and the Hurst parameter on derivative values. These results contribute to a deeper theoretical understanding and more effective computational methods for pricing nonlinear volatility derivatives in markets characterized by persistent temporal dependence and non-stationary stochastic dynamics. Full article

The integration of Generative Artificial Intelligence (GenAI) into higher education represents a paradigm shift from static skill acquisition to dynamic, human–AI collaboration. However, the psychological mechanisms governing students’ adoption—specifically the interplay between pedagogical novelty, ethical awareness, and habit formation—remain underexplored. To address this, this study develops and implements a dynamic practical curriculum incorporating AI and ethical awareness, aiming to foster responsible behavioral patterns in computer programming education. Employing a quasi-experimental design, we implemented a 16-week dual-track instructional intervention (incorporating AI-integrated pedagogy and ethical scaffolding) for 148 computer science students. Structural Equation Modeling (SEM) was applied to test an extended UTAUT2 framework. The findings reveal three critical theoretical insights that redefine GenAI adoption: (1) The eclipse of utility: contrary to established models, traditional utilitarian drivers of performance expectancy (β = 0.076, p = 0.39) and effort expectancy (β = 0.125, p = 0.13) yielded non-significant effects on behavioral intention. This suggests that for digital natives, algorithmic efficiency has devolved into a baseline hygiene factor, losing its motivational power. (2) The dominance of pedagogical novelty: hedonic motivation emerged as the paramount predictor of both habit (β = 0.457, p < 0.001) and behavioral intention (β = 0.336, p = 0.001). This confirms that adoption is driven by the situational interest and interactional novelty inherent in the human–AI partnership. (3) The cognitive brake mechanism: ethical awareness exhibited a divergent regulatory role. While it significantly legitimized conscious behavioral intention (β = 0.166, p = 0.011), it showed a non-significant, negative association with habit (β = −0.032, p = 0.653). This demonstrates that ethical reasoning functions as a cognitive brake (system 2) and actively disrupts the formation of mindless, automated dependency (system 1). These results provide empirical evidence for a dual regulation model of AI adoption and suggest that sustainable education requires leveraging pedagogical novelty to drive engagement while utilizing ethical awareness to prevent blind habituation. Full article