Search Results (258)

Background: Understanding the drivers of sustained volunteering among university students is crucial, as their continued participation yields significant individual and societal benefits. However, a notable decline in participation underscores the need to investigate the factors that underpin and sustain volunteering motivation. Methods: Using snowball sampling, 15 university students with volunteer experience were recruited for semi-structured interviews. A thematic analysis, guided by the Ecological Systems Theory (EST), was performed, with the mesosystem excluded from the analytical framework due to its indirect and less observable nature in participants’ self-reports. Results: Based on the interview responses, we identified 15 themes across the four systems (microsystem, exosystem, macrosystem, and chronosystem) influencing university students’ participation in volunteering. We further explored the restrictive factors that hinder their participation. To advance the analysis, we introduced a controllability framework (“controllable, partially controllable, minimally controllable”) as an analytical lens. This framework emphasizes that while behaviors are shaped by various factors, behavior change can be most effectively promoted by focusing intervention efforts on those within the immediate control of the individual or relevant actors. Implications: This study demonstrates the EST’s applicability to university students’ volunteering research and provides practical insights for the design of volunteer programs. Full article

In China’s stock-based renewal agenda, many old residential communities display pronounced intergenerational overlap, in which grandparental childcare becomes a dominant pattern of outdoor-space use. Against the backdrop of age-structure shifts, population ageing, and persistently low fertility, community-level outdoor-space supply, distributive equity, and environmental adaptability have become key concerns in renewal practice. Yet, practitioners still lack a rankable, low-cost, and implementable evaluation-to-decision workflow. Using Xingshe Community in Dalian, China as an empirical case, this study establishes and tests an integrated “NLP–AHP–GBDT” assessment framework. Guided by policy discourse and planning theory, over 50 semi-structured interviews were processed via NLP-based semantic analysis and keyword mining to derive a two-tier indicator set (criterion and indicator layers). Seven specialists then applied the analytic hierarchy process to elicit indicator weights, and a resident survey was administered to generate weighted performance scores for diagnosing deficiencies. In the feedback-validation stage, we adopted both a qualitative Framework Method and a quantitative GBDT approach, first using the Framework Method to conduct feedback validation based on community residents’ open-ended evaluations. Subsequently, gradient boosting decision trees were used for supervised verification with renewal-scenario data, providing empirical backing for the weighting scheme and the resulting priority order for interventions. The findings suggest that outdoor spaces are broadly serviceable but fall short in intergenerational friendliness, reflecting a structural misalignment between intergenerational activity patterns and spatial provision. Based on the validated priorities, the study proposes modular, incremental micro-renewal measures focusing on safety and emergency accessibility, environmental comfort and caregiving–recreation coupling, and place identity with community organizational mobilization. Full article

This study examines the governance of digitalization in municipal administration, with a focus on city planning services, specifically spatial planning, building permits, and geodata management, in a large Swedish municipality. Digitalization is understood here not as the adoption of isolated technologies, but as organizational and process-oriented transformation enabled by digital systems such as GIS platforms, case management systems, and digital planning information. While national policy frameworks set ambitious digitalization goals, previous research shows that local authorities often face significant obstacles, including fragmented processes, technical limitations, and complex governance structures. These challenges create a persistent gap between strategic ambitions and daily work practices. This study employs a qualitative case study approach drawing on semi-structured interviews with employees in technical, operational, and strategic roles, as well as an analysis of policy documents and internal process descriptions. Using a socio-technical perspective, the analysis applies the Technology–Organization–Environment (TOE) framework to examine how digital systems, organizational structures, and external institutional demands interact in practice. The findings highlight substantial challenges related to system integration, data quality, uneven digital competencies, and the ongoing disconnect between strategic goals and operational realities. The study emphasizes the need for clearer governance structures, stronger cross-functional collaboration, and work practices that bridge technical and organizational dimensions. Building on the empirical analysis, the study proposes a conceptual framework that extends the TOE framework by identifying three interrelated structural mechanisms: technological lock-in, organizational inertia, and institutional uncertainty. This framework contributes theoretically by deepening the understanding of socio-technical digitalization dynamics in local government. Practically, it provides municipalities with an analytical tool to assess and reflect on their digitalization conditions. Full article

This paper presents a systematic application of the Homotopy Perturbation Method (HPM) to the nonlinear static analysis of cantilever beams subjected simultaneously to three coplanar follower loads: an axial force H, a transverse force V, and a bending moment M₁. The studied configuration introduces complex mathematical self-coupling, as the bending moment depends on the solution of the differential equation even in its boundary conditions (γ₁), transforming the problem into a nonlinear one that is resistant to standard analytical methods. The primary methodological contribution of this work is the successful extension of the HPM framework to treat, within a unified mathematical formalism, this complete loading case, which has practical applications in compliant mechanisms, micro-electromechanical systems (MEMSs), and auxetic structures. The paper provides a complete mathematical formulation and explicit derivation of the HPM solution terms up to the third order and a rigorous demonstration of the method’s convergence, with quantitative error estimates and the establishment of a practical domain of validity, γ₁ < 30°, for an accuracy below 0.5%. As a direct consequence of this analytical advancement, we derive a series of practical engineering tools: nomograms, simplified empirical formulas, interaction diagrams, and a systematic six-step design procedure, which includes an adaptive algorithm for selecting the auxiliary parameter η to optimize convergence. The solution’s structure also lends itself to AI-based optimization frameworks, demonstrating how HPM solutions can serve as a foundation for machine learning surrogates and automated multi-objective optimizations. HPM proves to be a robust and efficient alternative, providing semi-analytical solutions in the form of convergent series without requiring an explicitly small physical parameter. This enables a direct parametric understanding of the structural response and offers rapid tools for the conceptual and preliminary sizing phases, thereby complementing the intensive numerical methods used in the final design stages. Full article

Precision Agriculture (PA) is increasingly applied to nutraceutical cropping systems, where agronomic productivity must be integrated with the stabilization of phytochemical quality and environmental sustainability. This structured narrative review synthesizes scientific evidence (primarily 2010–2025) on the use of Unmanned Aerial Vehicle (UAV)-based multispectral and thermal sensing, LiDAR-derived canopy characterization, Internet of Things (IoT) monitoring, and artificial intelligence (AI)-driven analytics in medicinal, aromatic, and functional crops. The literature indicates that PA enhances high-resolution monitoring of crop–environment interactions, supporting site-specific irrigation, nutrient management, and stress detection. Under validated conditions, these interventions are associated with improved yield stability, resource-use efficiency, and modulation of secondary metabolite accumulation. However, reported outcomes vary substantially across species, agroecological contexts, and experimental scales, and most studies remain plot-scale or pilot-scale, limiting large-scale generalization. Moringa oleifera Lam. is examined as a model species for Mediterranean and semi-arid systems. Evidence suggests that integrated spectral, structural, and environmental monitoring can support optimized irrigation scheduling, canopy uniformity, and phytochemical consistency. Nonetheless, genotype-specific calibration, multi-season validation, standardized metabolomic benchmarking, and cross-regional transferability remain significant research gaps. Overall, PA represents a scientifically promising but still maturing framework for nutraceutical agriculture. Future progress will require rigorous multi-site validation, improved model robustness, standardized sustainability metrics, and comprehensive economic assessments to ensure scalability and long-term impact. Full article

The constant growth of IP data traffic, driven by sustained annual increases surpassing 26%, is pushing current optical transport infrastructures towards their capacity limits. Since the deployment of new fiber cables is economically demanding, ultra-wideband transmission is emerging as a promising cost-effective solution, enabled by multi-band amplifiers and transceivers spanning the entire low-loss window of standard single-mode fibers. In this scenario, an accurate modeling of the frequency-dependent fiber parameters is essential to reliably model optical signal propagation. In particular, the combined impact of attenuation variations with frequency and inter-channel stimulated Raman scattering (SRS) fundamentally shapes the power evolution of wide wavelength division multiplexing (WDM) combs and directly affects nonlinear interference (NLI) generation, as well as the amount of ASE noise. In this work, we review a set of analytical approximations, based on phenomenological approaches, for frequency-dependent attenuation and Raman scattering gain, and analyze their impact on achieving an effective balance between computational efficiency and physical fidelity. Through extensive analyses performed with the open-source software GNPy (version 2.12, Telecom Infra Project) on an optical line system exploring multi-band scenarios spanning C+L+S, C+L+E, and U-to-E transmission, we demonstrate that the proposed approximations reproduce the reference SRS power evolution and NLI profiles with root mean square errors (RMSEs) consistently below 0.03 dB, and down to the 10⁻³–10⁻² dB range for the most accurate configurations. Although the current implementation does not yet provide a direct reduction in computational time, the proposed framework lays the groundwork for future developments toward closed-form or semi-analytical solutions, enabling more efficient modeling and optimization of ultra-wideband optical transmission. Full article

This paper develops a functional operator-theoretic framework for nonlinear Erdelyi–Kober (EK) fractional dynamical systems formulated in Banach spaces endowed with the compact-open topology. Within this setting, sufficient conditions for existence, uniqueness, and Ulam–Hyers stability of solutions are established using the Banach and Schaefer fixed-point theorems. The continuity, boundedness, and Lipschitz properties of the associated nonlinear operators are analyzed to ensure well-posedness of the fractional system. As a constructive complement to the theoretical results, a power series iterative method (PSIM) is employed to obtain an explicit fractional series representation of the solution in the case $0<\alpha <1$. The applicability of the theoretical framework is illustrated through a nonlinear fractional dynamical Belousov–Zhabotinsky system (DBZS), where the assumptions of the main theorems are verified and the solution is constructed via the proposed series scheme. The results provide a coherent link between abstract fixed-point analysis and a constructive semi-analytical representation of solutions for EK fractional systems. Full article

Theoretical studies of transonic accretion onto black holes reveal a wide range of possible solutions, broadly classified into smooth flows and flows featuring shocks. Accretion solutions that involve the formation of shocks are particularly intriguing, as they are expected to naturally produce observable variability features. However, despite their theoretical significance, time-dependent studies exploring the stability and evolution of such shocked solutions remain relatively scarce. To address this gap, we perform simulations of transonic accretion flows around a black hole in an ideal magnetohydrodynamic framework. Our simulations are initialized using boundary conditions derived from semi-analytical hydrodynamical models, allowing us to explore the stability of these flows under varying magnetic field strengths. Our results indicate that mildly magnetized flows in a uniform vertical magnetic field alter the accretion dynamics through magnetic pressure, with the resulting force imbalance driving oscillations in the shock front. Variations in the emitted luminosity arising from shock oscillations appear as quasi-periodic oscillations (QPOs), a characteristic feature commonly observed in accreting black holes. We find that the QPO frequency is determined by the radial position of the shock front: oscillations occurring closer to the black hole produce frequencies of tens of hertz, whereas shocks located farther out yield sub-hertz frequencies. Full article

While anisotropic extrudate swell in polymer processing is fundamentally driven by physical viscoelastic recovery, this paper proposes a theoretical framework to explicitly isolate and map the purely geometric and kinematic components of this phenomenon. Serving as a mathematical proof-of-concept, a multi-velocity-centre hypothesis is proposed. By introducing a semi-empirical, lumped material-flow calibration parameter, the macroscopic diameter swell ratio is mathematically extended to the discrete local flow field of a rectangular slit die. To evaluate its validity, the analytical framework is subjected to a numerical test for kinematic consistency utilizing isothermal, inelastic power-law fluid CFD simulations, thereby separating geometric mapping from complex viscoelastic stress relaxation. Results indicate that analytical predictions show good agreement with CFD data (error < 5%) strictly within the core zone of high-aspect-ratio dies. However, due to the infinite-slit assumption, 3D flow kinematics near die edges induce velocity decay, leading to local deviations that require future empirical corrections. Although comprehensive physical extrusion experiments and non-isothermal viscoelastic coupling are required for industrial deployment, this semi-empirical kinematic mapping provides a foundational mathematical basis that could potentially inform future inverse die-profile design and shape distortion compensation. Full article

Unmitigated communion (UC), the prioritisation of others’ needs over one’s own well-being, is a critical lens for understanding the mental health of female migrants. This qualitative study explores how UC intersects with constructions of strength and vulnerability within this population, particularly amid challenges such as adaptation, discrimination, and gendered roles. Using a feminist participatory methodology, the study was co-produced with 10 migrant women and three professionals. Semi-structured interviews were conducted with 18 female migrants from 13 countries, representing diverse languages, cultures, and lengths of stay in the UK. Data were thematically analysed using the Engaging Marginalised Communities by Building Relationships and Knowledge (EMBaRK) framework, which centres lived experience and equitable collaboration. Through this analytic process, three key themes were generated: (1) perceived strength and resilience shaped by societal pressures and internalised self-reliance; (2) gender roles and self-sacrifice, including traditional caregiving expectations and neglect of personal health; and (3) isolation and reluctance to seek support, marked by concealed mental health struggles and stigma. Participants’ narratives revealed shared tensions between resilience and vulnerability. The findings highlight the central role of unmitigated communion in shaping migrant women’s mental health and underscore the need for gender-responsive, culturally informed interventions that support women to balance caregiving with self-care. Full article

Generative Artificial Intelligence (GenAI) has the potential to bring substantial benefits to language education, making it essential to examine how teachers engage with these technologies in practice. This exploratory qualitative case study draws on semi-structured interviews with four in-service upper-secondary English teachers in Norway to examine the factors shaping their engagement with GenAI. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study examined factors shaping teachers’ engagement with GenAI, including performance expectancy, effort expectancy, social influence, and facilitating conditions. Thematic analysis revealed a pattern of selective, context-sensitive use rather than straightforward adoption. While teachers recognised the potential of GenAI to support planning, idea generation, and formative feedback, their engagement was constrained by concerns about assessment validity, academic integrity, privacy, and institutional guidance. The findings suggest that teachers’ use of GenAI is shaped not only by perceptions of usefulness and ease of use but also by trust, assessment considerations, and the availability of clear policy frameworks. By using UTAUT as a qualitative analytical lens, this study contributes to research on technology acceptance and teacher agency by showing how teachers negotiate the use of GenAI in ways that reshape assessment practices and professional roles. The findings point to the need for clear institutional guidance, AI-resilient assessment practices, and targeted teacher education that supports ethical, pedagogically grounded use of GenAI. Full article

Background: Digital strategy increasingly relies on algorithmic decision systems, yet the mechanisms by which human judgement remains embedded within these systems are poorly theorised. Existing frameworks treat digital tools as either neutral instruments or autonomous agents, overlooking the systems-level conditions under which human accountability is maintained. Methods: This study employs a novel three-stage system-oriented analytical protocol: (1) mechanism-revealing thematic analysis of 50 semi-structured interviews with senior managers across multinational organisations; (2) configurational cross-case mapping against 685 cases from the European Commission’s JRC AI implementation catalogue; and (3) failure mode triangulation comparing interview-reported barriers with 37 documented implementation discontinuations. Results: We introduce Authentic Intelligence as a systems-level construct and develop a socio-technical architecture specifying six primary system functions, three decision loci, four governance mechanisms, and twelve empirically derived failure modes. Triangulation reveals high correspondence (≥20% JRC citation rate) for six failure modes and moderate correspondence for six additional modes. Conclusions: The contribution is a reusable systems architecture and diagnostic framework for maintaining human-accountable decision governance in digital strategy implementation, with direct application to EU AI Act Article 14 compliance requirements. Full article

The independent application of conventional electrical or thermal models is, generally, not adequate to model the interdependence between temperature distribution, heat transfer mechanisms, and the electrical performance of Photovoltaic (PV) generators. In this context, coupled thermal–electrical modeling approaches have recently gained increasing importance to accurately simulate the PV performance. This work presents a comprehensive and systematic analysis of electrical, thermal, and coupled thermal–electrical models developed for PV modules. Electrical models are classified into analytical/physical, semi-empirical, and empirical classes, highlighting their assumptions, parameter requirements, computational complexity, and applicability at cell, module, and system levels. Thermal modeling approaches are reviewed by distinguishing lumped parameter and thermal network models from spatially distributed numerical methods. Particular emphasis is placed on the ability of these models to represent non-uniform temperature distributions and transient operating conditions. Furthermore, this review critically examines state-of-the-art coupled thermo-electrical models, focusing on different coupling strategies, feedback mechanisms, and levels of spatial resolution. The advantages and limitations of each modeling approach are discussed in relation to accuracy, computational cost, and suitability for performance prediction, fault analysis, and reliability assessment. Finally, current research gaps and future directions are identified, providing a structured framework to guide the selection of the most appropriate model and the development of more accurate and physically consistent PV modeling strategies under complex and realistic operating conditions. Full article

The evaporation of a thin liquid film representative of power-law rheology flowing along an inclined channel wall under the combined influence of gravity and surface tension is investigated using a semi-analytical modelling framework. The evolution of film thickness, heat transfer characteristics, and dry-out behaviour are examined as functions of the power-law exponent, Weber number, and inlet film thickness. The results show that a decrease in the power-law exponent leads to a slower reduction in film thickness, resulting in a significant increase in the dry-out length for a fixed value of consistency. This behaviour is attributed to the large effective viscosity developing near the free surface for shear-thinning fluids, in contrast to the negligible surface viscosity observed for shear-thickening fluids. The local Nusselt number increases gradually along the flow direction, followed by a sharp terminal rise marking the onset of dry-out. The mean Nusselt number decreases with increasing power-law exponent, which is consistent with the dry-out length variation with the power-law exponent. The dry-out length is found to be largely insensitive to surface tension for a fixed normalised inlet film thickness, while exhibiting an approximately linear dependence on the inlet film thickness that is nearly independent of the power-law index. Overall, the study establishes a hierarchy of controlling parameters for evaporating power-law films in inclined micro-channels, demonstrating that inlet film thickness primarily governs the dry-out location, while rheology and surface tension exert secondary influences within the parameter ranges considered. Full article

The syllable is the most fundamental acoustic unit in bird vocalizations and is highly informative of species-specific behavioral characteristics. However, because syllables vary significantly across different species and environments, existing syllable extraction methods still rely on manual or semi-automatic processing, which constrains deep learning-based research on birdsong syllables. This study proposes SFWA-TweetyNet for automatic syllable annotation and applies it to the red-winged blackbird (Agelaius phoeniceus), achieving a validation accuracy of 0.978 and a loss of 0.073. Based on high-quality syllable recognition, this study conducted exploratory cross-regional and cross-seasonal acoustic comparisons at the syllable level to demonstrate a syllable-based analytical framework. Specifically: (1) Acoustic features were extracted from the principal syllables and analyzed using the Kruskal–Wallis test to explore potential variations in acoustic characteristics across regions and seasons; (2) A syllable-based frequency-weighted Acoustic Complexity Index (FW-ACI) was proposed to demonstrate how FW-ACI can be applied for acoustic analysis within the proposed framework, with the Kruskal–Wallis test used as an exploratory statistical tool. In addition, this study constructs a high-quality syllable-level dataset of red-winged blackbird vocalizations, providing important foundational data resources for automatic birdsong annotation, cross-domain soundscape analysis, and avian ecological and behavioral research. Full article