Search Results (7,359)

Residential college (RC) activities represent a creative form of engagement beyond formal classroom teaching, integrating experiential, social, and community-based learning. China is promoting holistic education through the RC activities. Student motivation directly influences their engagement in practice-based learning. Yet, the motivation profile of Chinese students’ participation in RC activities remains largely unexplored. To address this gap, the exploratory cross-sectional study involved 403 undergraduates from an RC-based university in the Guangdong–Hong Kong–Macao Greater Bay Area. Based on a standardized questionnaire, we explored descriptive patterns of three forms of motivation, namely intrinsic motivation, extrinsic motivation, and amotivation, as well as four influencing factors: activity logistics, experiential value, outcome expectations, and social context. We then conducted hierarchical linear regression analyses with the three motivation types as outcomes. The primary results indicated that intrinsic motivation was the dominant motivation type among RC students. Experiential value emerged as a key influencing factor, positively associated with intrinsic and extrinsic motivation, and negatively associated with amotivation. Additionally, activity hosting experience was identified as another important correlate, positively linked to both intrinsic and extrinsic motivation. Motivational patterns further varied across gender, academic year, ID place, weekly RC stay duration, and part-time employment. The findings provide empirical support for more targeted RC activity planning aimed at boosting student motivation in the Chinese context. Full article

Interactive digital commerce environments increasingly rely on influencers as algorithmically amplified intermediaries between brands and consumers. However, the process through which influencer attributes translate into brand trust remains theoretically underdeveloped. Drawing on Social Influence Theory and Source Credibility Theory, this study develops a process-based model in which consumer engagement operates as a psychological mechanism linking influencer characteristics, namely credibility, brand alignment, interactivity, and authenticity, to brand trust. Using survey data from 400 active social media users in Lebanon and partial least squares structural equation modeling (PLS-SEM), the findings reveal that all four influencer attributes significantly enhance consumer engagement, which in turn strongly predicts brand trust. Influencer–brand alignment emerges as the strongest driver of engagement, suggesting that value congruence functions as a heuristic cue in interactive digital commerce contexts. By conceptualizing engagement as a trust-internalization mechanism within platform-mediated environments, this study advances electronic commerce theory and provides context-sensitive insight into digital trust formation in emerging markets. Full article

Photocatalysts have emerged as a promising approach for the treatment of contaminated water, particularly for the removal of dyes and pharmaceutical residues that pose risks to human health. In addition, they can be employed for the generation of chemical fuels such as H₂ and oxidizers such as H₂O₂, which have been proposed as sustainable energy carriers to reduce reliance on fossil fuels. The first part of this brief review provides a detailed overview of the fundamental concepts of photocatalysis, including reaction pathways and reported mechanisms. The second part explores the main design strategies for enhancing photocatalytic performance, including morphology control and structural modification. Then, the third section highlights the benefits of theoretical modeling, including first-principles calculations and molecular simulations. The document culminates with a section on challenges and future perspectives, highlighting major issues in photocatalyst development such as large-scale synthesis, material stability, and reusability. This brief review is intended to provide young researchers with a concise understanding of the most effective strategies for enhancing photocatalytic performance, as well as the mechanisms influencing morphology and structural parameters. This work presents an integrated framework linking synthesis strategies, particle growth mechanisms, multidimensional nanostructures, in situ and operando characterization, and computational modeling to guide the rational design of next-generation photocatalysts. Full article

Prosignification is defined as the process through which the subject generates new meanings by engaging in aesthetic experience, critical reflection, and creative action. Unlike general theories of meaning-making, which primarily describe the cognitive organization of experience, prosignification foregrounds the symbolic–expressive dimension as the central site of meaning production. It refers to the individual and collective capacity to construct meaning from expressive and symbolic experiences, integrating cognitive, emotional, social, and cultural dimensions of learning through intentional creative mediation. Prosignification operates between knowledge construction and subjective experience, enabling learners to connect conceptual understanding with personal interpretation and emotional involvement. Whereas knowledge construction emphasizes epistemic development and transformative learning focuses on perspective transformation through critical reflection, prosignification centers on the aesthetic reconfiguration of experience through symbolic creation and interpretation. Rooted in constructivist and experiential approaches, it unfolds through active, student-centred methodologies, particularly in Project-Based Learning contexts. However, its distinctive contribution may lie in integrating reflection, expression, and creation as interdependent mechanisms of meaning generation. Art education constitutes a particularly relevant context for this process, as its symbolic nature fosters the embodied and shared construction of meaning. Thus, prosignification cannot be reduced to cognitive restructuring or attitudinal change but involves the expressive re-symbolization of lived experience. Full article

Since 2000, the flipped classroom model has been widely adopted in higher education within the context of digital transformation; however, a comprehensive historical synthesis of review evidence remains limited. This study addresses this gap by conducting a review of reviews to clarify developmental trends, theoretical foundations, instructional designs, research methods, outcome variables, reported effects and implementation challenges, with the aim of informing sustainable education practices. Following the PRISMA framework, we systematically searched Web of Science Core Collection, Scopus, and Google Scholar for studies published between 2000 and 2024. Predefined inclusion and exclusion criteria were applied, and 25 systematic reviews met the eligibility requirements. Risk of bias and reporting quality were assessed descriptively at the review level. The results indicate generally positive perceptions among students and teachers, particularly regarding learning performance, collaboration and motivation, with the strongest evidence observed at the teaching and learning levels rather than at pedagogical or institutional levels. Substantial variation in flipped classroom designs and inconsistent reporting limited cross-study effect size synthesis. Further analysis reveals a fragmented theoretical basis and uneven attention to post-class learning processes. In response, two integrative frameworks—the Instructional Design Analysis Model for Flipped Classrooms (IDAMFC) and the Transformative Activation Theory for Flipped Classrooms (TAT-FC) are proposed to align pre-, in-, and post-class phases with learning strategies, cognitive engagement, and assessment in digitally supported environments. This study highlights the need for longitudinal designs and more comprehensive outcome measures to support sustainable educational development. Full article

The world evolves continuously across space and time. Massive volumes of data are generated through sensing, simulation, remote observation, and human activities, capturing dynamic processes in environmental, social, economic, and engineered systems. Critical insights are embedded within these large-scale spatiotemporal datasets. Spatiotemporal Data Science provides a conceptual and methodological framework for analyzing such data by integrating spatiotemporal thinking, computational infrastructure, artificial intelligence, and domain knowledge. The field advances methods for data acquisition, harmonization, modeling, visualization, and decision support, enabling applications in natural disaster response, public health, climate adaptation, infrastructure resilience, and geopolitical analysis. By leveraging emerging technologies—including generative Artificial Intelligence (AI), large-scale cloud platforms, Graphics Processing Unit (GPU) acceleration, and digital twin systems—Spatiotemporal Data Science enables scalable, interoperable, and solution-oriented research and innovation. It represents a critical frontier for scientific discovery, engineering advancement, technological innovation, education, and societal benefit. Spatiotemporal Data Science is a transdisciplinary field that studies and models dynamic phenomena across space and time by integrating spatial theory, temporal reasoning, artificial intelligence, and scalable computational infrastructure. It enables the development of adaptive, predictive, and increasingly autonomous systems for understanding and managing complex real-world processes. Full article

The expansion of digital connectivity has reshaped contemporary work environments, increasing flexibility while simultaneously blurring the boundaries between work and personal life. In such contexts, employees may experience difficulties in psychologically detaching from work during off-job time. Drawing on the Effort–Recovery model and Conservation of Resources theory, this study examined whether affective work-related rumination indirectly explained the association between Fear of Missing Out (FoMO) and psychological detachment. A cross-sectional survey was conducted with 228 employees from diverse occupational sectors who completed validated measures of FoMO, affective rumination, and psychological detachment. Indirect effect analyses using bootstrapping procedures indicated that FoMO was positively associated with affective rumination, and affective rumination was negatively associated with psychological detachment. The indirect effect was significant, whereas the direct association between FoMO and detachment was not. These findings are consistent with an indirect association pattern whereby FoMO is related to lower psychological detachment through higher levels of affective rumination. However, given the cross-sectional design, the results should be interpreted as correlational evidence rather than as demonstrating a causal mediation process. The model accounted for approximately 10% of the variance in psychological detachment. Overall, the findings suggest that FoMO may be indirectly related to reduced recovery experiences via emotionally charged repetitive thinking that sustains cognitive activation beyond working hours. Addressing rumination and supporting healthier digital boundary management may therefore represent promising avenues for supporting occupational mental health in increasingly connected work environments. Full article

The Land Use and Land Cover (LULC) of many regional landscapes are changing due to natural effects and anthropogenic activities, impacting biodiversity and ecosystem services. LULC dynamics reflect the altered flow of energy, water, and greenhouse gases, influencing the pillars of sustainability: society, environment, and economy. Thus, assessing LULC changes is vital for understanding the relationship between nature and society. This study used multi-temporal remotely sensed imagery to examine LULC change between 1990 and 2019 in the context of Forest Transition Theory (FTT) across the Greater Shawnee National Forest (GSNF) area of southern Illinois, USA, using a random forest algorithm, and projecting change to 2050 with a Land Change Model integrated with IPCC temperature and precipitation scenarios. From 1990 to 2019, LULC analysis showed increases in deciduous forest (1.35%), mixed forest (26.40%), agriculture (2.15%), and built-up areas (6.70%), while hay/grass/pasture declined (16.0%). LULC change intensity was highest from 1990 to 2001 (2.35% annually), slowing to 0.23% (2001–2010) and 0.18% (2010–2019). The overall accuracy (OA) of LULC classification ranged from 0.9 to 0.95 at a 95% confidence interval (CI). Projections to 2050 showed consistent increases in built-up areas (17.12–42.61%), water (28.75–39.70%), and hay/grass/pasture (6.23–38.38%), while overall forest cover declined in all scenarios. Deciduous forests decreased by 3.11–19.87% and were replaced by mixed forests in some scenarios (12.45–23.63%), while evergreen forests showed mixed responses, ranging from a decline of up to 17.13% to an increase of 2.90%. The OA of projected LULC ranged from 0.71 to 0.83 (95% CI) across SSP-RCP-based temperature and precipitation scenarios. The results showed that the GSNF broadly follows the FTT framework: forest recovery since 2001 coincided with rural depopulation, slow agricultural expansion, and rising incomes. However, climate change is expected to disrupt this recovery, pushing transitions toward mixed and evergreen forests. Findings demonstrate the importance of integrating remote sensing-based LULC with socio-economic trends and climate adaptation strategies to sustain forests and ecosystem services under future environmental pressures. Full article

Background: Young men experience substantial mental health and mortality-related risks, yet they often do not engage in conventional health promotion programs. This highlights the need for gender-specifc interventions that are acceptable, engaging, and feasible for young men. Purpose of Research: Guided by self-determination theory, this single-group proof-of-concept study evaluated the feasibility and acceptability of a dual-component intervention combining an in-person nature-based intervention (NBI; two days of group activities and guided reflection in a forested park) and a subsequent virtually supported resistance training (RT) program for young men and explored secondary, exploratory pre- to post-changes in depressive and anxiety symptoms. Methods: Eight men aged 18–34 not meeting RT recommendations (i.e., <2 sessions/week) completed a two-day, in-person NBI followed by six weeks of virtually supported RT with weekly group check-ins. Primary feasibility outcomes were satisfaction and qualitative acceptability for NBI/RT, recruitment, retention, and adherence. Secondary, exploratory quantitative outcomes were pre- to post-changes in depressive and anxiety symptom scores. Brief semi-structured exit interviews were conducted at the study end and audio-recorded for analysis. Results: Satisfaction met a priori thresholds for both components (NBI = 3.4/4; RT = 4.3/5; criteria ≥ 3.0 and ≥ 3.5). Recruitment was 46% and retention 100%, exceeding the 42% and 80% criteria, respectively. Exit interview themes highlighted guided learning, accountability, and feeling more connected to nature as acceptability drivers, with the scheduling burden noted but manageable. Depressive and anxiety symptom scores were lower post-intervention. Conclusions: Challenges in recruitment, group dynamics, and participant selection require refinement before the next phase; however, high satisfaction with both the NBI and RT segments, together with improvements in anxiety and depression symptom scores, supports progressing to a feasibility trial once these enhancements are in place. Full article

The study reconsiders the architectural production associated with Russian Suprematism (which was speaking of “the supremacy of pure artistic sensation” rather than the veritable figurative depiction of real-life subjects) in the early Soviet period as a coherent and conceptually rigorous mode of speculative world-making rather than as a marginal or unrealized appendix to avant-garde art history and theory. By examining the architectural propositions articulated by Kazimir Malevich and then elaborated by his younger colleagues Lazar Khidekel, Ilya Chashnik, and Nikolai Suetin, the study advances the claim that Russian Suprematist architecture constituted an epistemic experiment aimed at redefining the very ontological premises of architecture. Far from functioning as a mere transposition of abstract pictorial language into three-dimensional form, Suprematist planits, architectons, and aerocentric projects operated as instruments for thinking spatiality beyond terrestrial gravity, anthropocentric utility, and historical typology. Situating these projects within the intellectual horizon of Russian cosmism and early aerospace thought, the article demonstrates how Suprematist architecture intersected with contemporary philosophical, scientific, and technological discourses that envisioned humanity’s active participation in the reorganization of cosmic space. The architectural imagination of Suprematism emerges here as inseparable from broader debates on excitation, non-objectivity, transformation of matter, and the reconfiguration of human corporeality. Through close analysis of formal strategies, pedagogical frameworks, and theoretical writings, the paper reveals the internal plurality of avant-garde Suprematist architectural inquiry, ranging from ecological proto-urbanism and hovering settlements to magnetic and cruciform spatial systems. Ultimately, the paper argues that the historical non-realization of these projects should not be interpreted as a failure but as an intrinsic feature of their speculative methodology. Suprematist architecture is thus redefined as an anticipatory practice whose unresolved propositions continue to resonate with contemporary discussions on space habitation, planetary design, ecological responsibility, and post-human architectural thought, challenging inherited assumptions about the scope and function of architecture as such. Full article

In this study, the electrochemical reduction of CO₂ to CO within a bilayer cobalt phthalocyanine (CoPc)₂ confinement system was systematically investigated using density functional theory (DFT). The results reveal that the (CoPc)₂ architecture creates a well-defined catalytic microenvironment, in which the synergy between vertical spacing (regulated by moderate interlayer interactions) and lateral displacement gives rise to an optimal “Goldilocks zone”. This zone is characterized by a vertical distance (D) of 4.25–4.5 Å and a parallel displacement (L) of approximately 1 Å. Within this confined environment, the adsorption and desorption of key intermediates are optimally balanced, leading to enhanced catalytic activity. Electronic structure analysis further demonstrates that such spatial confinement induces asymmetric charge redistribution in the CO₂ molecule, resulting in distinct regioselectivity. This work provides a general design strategy for developing high-performance and site-selective catalysts through precise engineering of interlayer geometric environments. Full article

Physical inactivity is a major preventable cause of non-communicable disease and premature mortality. Mobile health interventions can promote physical activity, but their effectiveness depends on the ability to adapt to user’s context and motivation. Reinforcement learning (RL), particularly contextual bandits (CBs), offers a promising framework for such adaptive personalization. However, in practice, RL-based models face the cold start problem (CSP), due to the lack of initial training data. This study examines whether theory-driven simulated data can mitigate the CSP in training RL systems for personalized physical activity recommendations. A scoping review of 18 empirical studies on the Integrated Behavioral Change Model (IBC) provided population parameters for key constructs, used to simulate 2000 virtual users via multivariate modeling and structural equation calibration. A CB algorithm with an ε-greedy policy was trained with this dataset and compared with data from real world pilot using the Apptivate mHealth web-app (n = 588). Results showed close alignment between simulated and real behaviors. Our findings demonstrate that behaviorally informed synthetic data can effectively be used to train RL algorithms, offering an interpretable, sustainable, scalable, and privacy-safe solution to the CSP in personalized digital health interventions. Full article

This paper investigates an optimal cooperative guidance strategy for the active defense of an early-warning aircraft (EWA) escorted by two fighters against an incoming missile. The proposed framework extends classical three-body defense models (Target–Missile–Interceptor) into a more realistic four-body engagement (Target–Missile–Interceptor 1–Interceptor 2), allowing explicit coordination among multiple defenders. By projecting the 3D engagement kinematics onto two orthogonal 2D planes—a validated simplification for typical aerial combat geometries—a tractable dynamic model is obtained. Within this model, an analytical cooperative guidance law is derived using optimal control theory and the calculus of variations, minimizing a multi-objective cost function that combines miss distance, control effort, intercept geometry, and coordination terms. Extensive Monte Carlo simulations across 23 attack directions and multiple initial ranges demonstrate that the proposed method achieves an interception success rate of 99%, with an average miss distance of below 5 m. Robustness tests further confirm stable performance under target maneuver uncertainty, sensor noise, and modeling deviations. The algorithm features closed-form control commands with low computational complexity, enabling real-time onboard implementation. Full article

Commercially available wearable health devices (WHDs) carry the potential to decentralize healthcare systems. These devices can empower individuals with health knowledge by offering a low-cost and accessible way to monitor physical activity, sedentary behavior, cardiac health, and sleep. However, a lack of standardization in design, health, and safety regulations means that consumer-grade WHDs on the market vary in efficacy to affect positive behavior change in users, as user compliance alone does not indicate whether these devices actually influence wellbeing outcomes long term. We use a grounded theory analysis of the experiences of seven long-term informed users of the same wearable, the Oura Ring, to propose a substantive theory describing the tacit challenges that these users face in order to truly benefit from their device even after extended use. We provide recommendations as to how designers of wearable devices can facilitate the user’s journey to surpass these obstacles. Full article

The relationship between individual health considerations and environmental outcomes remains insufficiently explored in economic theory. This paper examines how concern for personal health influences private environmental investment and long-run environmental quality. We develop an overlapping generations model in which an individual’s overall health status depends jointly on intrinsic health capital and environmental quality, allowing for limited substitutability between the two. Individuals allocate income between consumption, savings, health investment, and green investment, while environmental quality evolves endogenously through production-driven pollution and both private and public abatement activities. The analysis shows that stronger concern for personal health increases private environmental investment and improves steady-state environmental quality, even though it reduces physical capital accumulation by diverting resources towards health- and environment-related uses. Public environmental spending and improvements in the effectiveness of green initiatives further enhance environmental quality and indirectly stimulate private health investment, despite partially crowding out private green effort. These findings highlight health preferences as an important behavioral channel for environmental sustainability and suggest that policies raising awareness of environmental health risks can effectively complement the standard mechanisms of environmental regulation. Full article