Search Results (13,537)

Compliant mechanisms have contributed to many advances in soft robotics, and there is strong motivation to translate these ideas to assistive devices where adaptive motion at the human interface is required. This work presents novel reconfigurable compliant joints (RCJs) as a parameterized joint element for functional biomimicry in lower-extremity joints for prosthetic knees and ankle–foot orthoses, with concepts that extend to other limb joints. The RCJ uses a rigid hub and outer ring joined by an array of flexible links with centerlines defined by cubic Bézier curves. Link shapes are organized into four Bézier classes (A–D), with base types using 10, 12, or 14 uniformly distributed link slots and variants generated by modifying active-link count and distribution, forming a structured morphology space of 12 configurations for machine design. Dual-extrusion 3D-printed prototypes are characterized by a custom testing apparatus using a 2.2 kN load cell at 25 mm/s over a 0–90° rotation range across six recorded load cycles to measure torque–angle curves and stiffness under large deformations. Angle-dependent stiffness is evaluated over three fixed intervals (0–30°, 30–60°, and 60–90°) to quantify multi-stage behavior. A 2-dimensional corotational frame model and a Simscape Multibody model, including a rolling-contact knee configuration, use the same parameterization to relate geometry, nonlinear mechanics, and system-level motion. Experiments and simulations show multi-stage torque–angle profiles and predictable stiffness modulation across all configurations, with both magnitude and transition angle tunable through Bézier class and active-link distribution, positioning the RCJ as a CAD/CAE-compatible joint architecture for assistive devices or wearable robotic systems and a basis for advancing functional biomimicry in compliant mechanism design. Full article

Against the backdrop of uneven educational development and structural constraints in rural Mainland China, teacher agency is critical for driving professional growth and instructional improvement. Rural educators face distinct challenges—limited resources, isolated work contexts, and systemic pressures—that shape their capacity to enact change. While scholarship has documented the roles of contextual resources and individual beliefs in shaping teacher agency, less is known about the mediating mechanisms linking job resources and self-efficacy to agency within China’s rural educational landscape. This study examines how perceived job resources (teaching resources, administrative support, colleague support, parental support) and teaching self-efficacy collectively shape rural teachers’ agency, to inform policy and practice for strengthening their professional capacity. Drawing on a quantitative survey of 625 rural teachers, we employ a two-stage analytical approach: first, descriptive statistics, t-tests, ANOVA, and Pearson correlations to map baseline variable relationships; second, Hayes’ PROCESS macro (Model 4) with bootstrapping to test the mediating role of teaching self-efficacy between job resources and teacher agency. Findings reveal the following: (1) Rural teachers report moderate agency (M = 3.53/5), indicating room for growth; (2) All four job resource dimensions significantly and positively predict agency (β = 0.099–0.163); (3) Teaching self-efficacy is a robust predictor of agency (β = 0.785–0.822, p < 0.001) after controlling for resources; (4) Self-efficacy partially mediates the links between each job resource and agency, with indirect effects ranging from 0.269 (teaching resources) to 0.451 (colleague support), highlighting its central role in translating contextual resources into agentic action. We conclude that fostering rural teacher agency requires a holistic approach addressing both external job resources and internal self-efficacy. Policymakers and administrators should prioritize investments in teaching resources, collaborative support structures, and professional development to build educators’ confidence and competence. Limitations include self-report bias, cross-sectional design constraints on causal inference, and limited generalizability. Future research should use longitudinal designs and broader samples to deepen understandings of agency in structurally constrained educational settings. Full article

Against the backdrop of a technological revolution centered on green and low-carbon development, the deep integration of digitalization and greening has become a core engine for high-quality progress. Moving beyond linear perspectives of environmental governance, this study constructs tripartite evolutionary game models to dissect the strategic interactions among government, enterprises, and consumers. Focusing on the institutional context of e-commerce, we examine how platform-enabled transparency mechanisms (e.g., blockchain traceability and carbon labeling) shape these interactions through key parameters: greenwashing detection (θ), premium loss coefficient (η), and information screening cost (C_D). The analysis reveals that the long-term trajectory is fundamentally determined by the intrinsic economic viability of corporate transformation. Government intervention acts as an equilibrium selector, influencing the speed of convergence, while product value (consumer utility and premium) and platform transparency determine the sustainability of the equilibrium. Critically, the tripartite model shows that the optimal outcome—full enterprise transformation and consumer adoption—can be achieved without sustained government intervention when product fundamentals are sufficiently attractive. This demonstrates the potential for market self-regulation to sustain digital–green synergy. The study makes three contributions: it captures the full tripartite feedback loop, reveals the saturation effect of policy intensity, and embeds platform transparency mechanisms into an evolutionary framework. The findings reframe the government’s role as a temporary enabler and position e-commerce platforms as key governance intermediaries, offering a theoretical basis for adaptive governance strategies in digital commerce. Full article

Olive cultivation represents a key pillar of rural economies and cultural heritage in Mediterranean regions, including western Greece. Despite its socio-economic importance, the sector faces increasing pressures from climate change, market volatility, and technological transformation, while progress toward environmentally sustainable production remains uneven. This study investigates how olive farmers’ perceptions of carbon footprint and climate risks are influenced by their demographic characteristics. Primary data were collected through 402 structured questionnaires distributed to olive producers in the Aetolia–Acarnania region. The sample was designed to represent farmers directly engaged in olive production, ensuring the relevance and reliability of the collected data. The findings, based on descriptive statistics, reveal significant heterogeneity in producers’ perceptions of climate risks and their capacity to respond through sustainable practices. Demographic characteristics appear to play an important role in shaping awareness of carbon footprint and the potential adoption of environmentally responsible farming strategies. These results suggest that sustainability transitions in perennial cropping systems depend not only on technological availability but also on social, informational, and institutional capacities. Strengthening agricultural advisory services, farmer training, and climate adaptation strategies may therefore support the adoption of climate-smart practices in olive cultivation. Furthermore, cooperation and value-chain integration are identified as potentially important mechanisms for facilitating knowledge transfer and supporting the adoption of sustainable practices (e.g., efficient irrigation and optimized input use). However, their contribution to environmental performance and greenhouse gas mitigation cannot be directly inferred from the present perception-based analysis and should be examined in future research using appropriate quantitative or environmental assessment frameworks. Full article

Effective hemostasis in deep and irregular wounds remains a critical clinical challenge. To address this, we developed a bioresorbable chitosan composite hydrogel reinforced with short eggshell membrane (ESM) nanofibers, which were obtained through cryogenic grinding. The resulting ESM/CCS hydrogel, crosslinked with citric acid, exhibited significantly enhanced properties compared to pure CCS hydrogel, including a 63% increase in mechanical strength, a two-fold improvement in shape memory, a 25.31% reduction in hemolysis, over 2% higher cytocompatibility, and more than 48% greater hemostatic efficiency. Structural characterization confirmed the successful integration of bioactive chitosan with collagen mimetic ESM nanofibers. This biomimetic approach synergistically combines mechanical reinforcement with biological functionality, highlighting its strong potential as an advanced hemostatic dressing for complex wound management. Full article

Salicylic acid (SA) is a key endogenous regulator involved in plant defense responses to biotic and abiotic stresses. The increasing resistance of pathogens to chemical plant protection products and growing environmental restrictions have intensified the search for alternative strategies to enhance plant health and stress tolerance. Among these strategies, the induction of natural defense mechanisms, in which SA plays a central signaling role, has gained particular attention. This review summarizes current knowledge on the role of SA in shaping plant resistance to environmental factors. The fundamental mechanisms of plant defense, including innate immunity, induced systemic resistance (ISR), and systemic acquired resistance (SAR), are discussed, with emphasis on the signaling function of SA and its interaction with other phytohormones, especially jasmonic acid and ethylene. The role of SA in regulating physiological processes associated with stress tolerance, such as antioxidant system activity, photosynthesis, plant growth, and senescence, is highlighted. The review of research results indicates that appropriately selected doses and timing of SA treatments can enhance resistance to selected pathogens and improve plant tolerance to adverse environmental conditions. However, treatment effectiveness depends on multiple factors, particularly SA concentration and plant–pathogen interactions. Salicylic acid is a promising component of integrated and sustainable plant protection strategies. Further research, especially under field conditions, is necessary to optimize its practical use and fully determine its potential in modern agriculture. Full article

Calcium silicate-based sealers are widely used in contemporary endodontics, but their strong interaction with dentinal substrates may complicate their removal during nonsurgical retreatment and potentially hinder canal disinfection. This ex vivo study evaluated the effectiveness of different irrigation activation techniques in removing a calcium silicate-based sealer from oval-shaped root canals. Sixty extracted single-rooted teeth were instrumented and obturated using the single-cone technique with NeoSealer Flo, followed by retreatment using a reciprocating system. Specimens were randomly assigned to four final irrigation protocols: conventional needle irrigation (CNI) with NaOCl/EDTA, ultrasonic activation (US), diode laser activation (LI), and Er:YAG laser activation using the SWEEPS mode (SW) (n = 15). Residual filling material was quantified before and after final irrigation using stereomicroscopic imaging and ImageJ (version 1.54) analysis. Dentinal surface morphology and residual sealer were further evaluated using SEM–EDS. Statistical analysis included one-way ANOVA and chi-square tests (p < 0.05). All protocols significantly reduced residual filling material compared with mechanical retreatment alone (US 15.08%, CNI 7.89%, LI 8.01%, SW 7.20%) (p < 0.01). US resulted in significantly greater sealer removal compared with CNI, LI, and SW, with mean differences ranging from 7.08% to 7.88% (p < 0.05). These findings indicate that irrigation activation enhances the removal of NeoSealer Flo calcium silicate-based sealer, with ultrasonic activation demonstrating greater effectiveness among the evaluated techniques, under the conditions of this experimental setup. Full article

The mean annual change in aboveground biomass (ΔAGB) is a pivotal indicator for assessing forest carbon cycle dynamics. This study analyzed 791 independent Abies Mill. forest patches across China to elucidate their driving mechanisms by integrating abiotic, anthropogenic, and biotic factors. We employed a spatially explicit framework, including spatial error regression and structural equation modeling (SEM), to account for significant spatial autocorrelation (Moran’s I = 0.375, p < 0.001). Our results show that abiotic factors predominantly dictate ΔAGB, with soil fertility (pH and Total Nitrogen), elevation (DEM), and soil physical properties (Coarse Fragments and Thickness) explaining the majority of deterministic variance. This relatively low explanatory variance (marginal R² = 0.09) likely reflects the high environmental stochasticity inherent in alpine ecosystems. Specifically, soil fertility exerted the strongest positive influence (Std. Estimate = 0.33), while elevation and soil physical constraints were the primary limiting factors. Biotic factors (Stand Age, Height, and Tree Cover) played a subordinate role, contributing only a marginal 2% gain in explained variance (increasing marginal R² from 0.07 to 0.09). Path analysis revealed an “environmental filtering” hierarchy where abiotic factors shape stand structure, which in turn has limited impact on growth dynamics. These findings underscore that carbon management in alpine forests should prioritize habitat quality conservation over simple biotic structural manipulation. Full article

This study aimed to investigate how score status and playing position affect the most demanding passages (MDPs) in elite women’s football. Data from ten matches from eighteen outfield players of the Turkish Women’s National Team were collected during UEFA Nations League fixtures in the 2024–2025 seasons. Players were monitored using wearable GPS sensors, and all locomotor variables were segmented into one-minute windows to identify peak demands. The analysed variables included total distance (TD), high-speed running (HSR), sprint distance (SD), high-acceleration distance (HIAccD), high-deceleration distance (HIDecD), high metabolic power distance (HMPD), and player load (PL). Generalised Estimating Equations (GEE) were used to assess the effects of score status and playing position. Wingers (WG) showed the highest TD, HSR, and HMPD values, while centre backs covered less TD and HSR than WG. Full-backs and forwards (FW) also recorded lower TD, although FW exceeded WG in sprinting (p = 0.045, d values = 0.66 [moderate effect]). Score status influenced MDPs, with TD decreasing when the match was tied and further declining when the team was behind; similar reductions occurred in HSR, HIAccD, HIDecD, and HMPD. In conclusion, both score status and position significantly shaped peak locomotor and mechanical demands. These findings may inform individualised training, recovery programmes, and score-dependent tactical planning in elite women’s football. Full article

Bio-based, biodegradable, and renewable polymers offer a promising alternative to traditional synthetic polymers derived from petroleum or other non-renewable resources. However, their use is limited by suboptimal properties and high costs. Incorporating sustainable reinforcements into the polymer matrix significantly improves biopolymer performance while preserving key properties, sustainability, and cost-effectiveness. Bio-based polymeric composites have emerged as a crucial category of biopolymers, playing a key role in advancing a sustainable, circular economy. This review provides an updated overview of bio-based polymer composites and nanocomposites, focusing on reinforcement strategies using natural nanofillers and engineered nanoparticles. We summarize key synthesis and processing methods, discuss structure–property relationships, and highlight recent advances in applications such as food packaging, biomedical devices, energy systems, environmental remediation, 3D printing, and supercapacitors. Polymer nanocomposites are versatile, with their performance depending on the type, size, and interactions between the fillers and the polymer matrix. Progress in metallic, ceramic, carbon-based, natural, and hybrid fillers has improved their properties. Using bio-based polymers and renewable fillers supports sustainability. Natural nanofillers derived from renewable sources and industrial byproducts offer a sustainable approach to developing high-performance, biodegradable nanocomposites. Smart nanocomposites can react to external stimuli by integrating specialized fillers that enhance their mechanical and mobility properties. Shape memory nanocomposites can be remotely activated—using heat, electricity, magnets, or light—enabling advanced applications. Finally, we address major challenges and outline future directions for scalable, circular-material solutions, drawing on perspectives from the circular economy and life cycle assessment (LCA). Full article

In an era of rapid digital transformation, brand activism has emerged as a prominent strategy through which organizations seek to signal social and environmental commitment while engaging increasingly sceptical and digitally empowered consumers. Within this context, perceived authenticity has become a critical evaluative mechanism shaping how digital brand activism is interpreted and whether it contributes to sustainable consumption and trust-based market outcomes. This study examines how perceived authenticity in digital brand activism is associated with consumer trust, attitudes toward socially engaged brands, and behavioral intentions that support sustainable consumption. Grounded in attribution theory and the authentic brand activism framework, the study adopts a quantitative, cross-sectional design based on an online survey of 240 consumers. The findings indicate that perceived authenticity is strongly associated with higher levels of consumer trust and more favorable attitudes toward digitally activist brands, reinforcing authenticity as a key trust-building mechanism in digital environments. Trust and attitudes are, in turn, positively associated with behavioral intentions such as purchasing, recommending, and willingness to pay a premium for sustainable products. However, behavioral intentions are weaker than trust and attitudinal evaluations, providing evidence of a persistent attitude–behavior gap that limits the translation of positive digital evaluations into concrete sustainable consumption outcomes. Exploratory results further suggest that the association between perceived authenticity of brand and behavioral intentions operates primarily through trust and attitudes rather than through a strong direct relationship. By clarifying these indirect pathways, the study advances attribution-based explanations of digital brand activism and contributes to research on smart innovation and digital sustainability by highlighting the role of authenticity in trust-based market outcomes. It also underscores the importance of authentic, data-informed digital strategies for fostering consumer trust, aligning brand activism with ESG principles, and supporting sustainable growth in digitally empowered markets. Full article

Artificial intelligence (AI) is transforming logistics and supply chain management by enhancing operational efficiency, predictive analytics, and decision-making capabilities; however, the determinants of AI adoption in emerging logistics ecosystems remain insufficiently understood. This study develops and empirically examines an integrated framework combining technology-organization-environment (TOE), task-technology fit (TTF), and unified theory of acceptance and use of technology (UTAUT) to explain AI adoption in Thailand. Using survey data from 500 logistics and supply chain professionals, covariance-based structural equation modeling (SEM) was employed to validate the measurement model and test the proposed relationships. The results show that technological, organizational, and environmental factors significantly influence AI adoption at the organizational level, while task and technology characteristics enhance task-technology fit at the operational level. At the behavioral level, performance expectancy, effort expectancy, and social influence positively influence behavioral intention, which in turn drives AI adoption, with facilitating conditions also exerting a direct effect. These findings indicate that AI adoption is shaped by a cross-level mechanism involving structural conditions, operational alignment, and individual acceptance, offering theoretical and practical insights for advancing digital transformation in logistics contexts. Full article

Using 29,278 firm-year observations of Chinese A-share listed firms from 2012 to 2023, this study examines whether data assetisation improves corporate investment efficiency and whether bank fintech conditions shape this relationship. Data assetisation refers to the process through which firms transform data resources into economically valuable, governable, and deployable assets. We construct a text-based proxy from annual reports using a Word2Vec-expanded lexicon and further distinguish between own-use and transactional data assets. The study finds: (1) Data assetisation significantly enhances corporate investment efficiency, with self-use data assets demonstrating a stronger driving effect. (2) Mechanism analysis reveals that data assetisation alleviates underinvestment by easing financing constraints and leveraging the “talent effect”. Concurrently, it mitigates overinvestment by reducing agency problems and accelerating digital transformation, thereby enhancing investment efficiency. (3) Heterogeneity tests indicate that the positive impact of data assetisation on investment efficiency is more pronounced among growth-stage enterprises, technology-intensive firms, and companies operating in regions with high bank liquidity. (4) Banking fintech positively moderates the enhancement of corporate investment efficiency through data assetisation, with a more pronounced effect on alleviating underinvestment. However, it may also exacerbate overinvestment. This study contributes to sustainable economic development by improving resource allocation efficiency, reducing capital misallocation, and supporting high-quality, low-waste, and sustainable growth of the real economy. Consequently, enterprises should vigorously develop data assetisation, applying different types of data assets to specific use cases to unlock data dividends. This approach supports the scientific development of corporate investment decisions and enhances investment efficiency, laying a micro-level foundation for sustainable socio-economic development. Full article

The sustainable conservation of linear industrial heritage corridors remains challenged by a limited understanding of their formation mechanisms and driving forces. Addressing this gap, this study develops a transferable analytical framework to explain the spatio-temporal evolution of such systems. Using Jiangsu Province (China) as a case study and a dataset of 344 industrial heritage sites, we apply an integrated spatial-analytical approach to examine distribution patterns and underlying drivers. The results reveal an evolving dual-axis spatial structure shaped by transportation networks and regional development dynamics, with railway density emerging as a key influencing factor. Furthermore, the interaction of infrastructural, demographic, and institutional variables highlights a synergistic mechanism underpinning corridor formation. Building on these findings, the study proposes a “corridor-as-process” framework, conceptualizing industrial heritage corridors as dynamic socio-spatial products of long-term interactions between institutions, networks, and economic activities. This perspective advances beyond static, descriptive approaches by offering a process-oriented and explanatory understanding of heritage systems. This study contributes to sustainability by providing a spatially explicit basis for adaptive reuse, vulnerability assessment, and differentiated conservation strategies, supporting the integration of heritage preservation within broader regional sustainability transitions. The proposed framework offers a transferable methodological reference for analyzing industrial heritage corridors in comparable global contexts. Full article

Against the backdrop of an accelerated green transition and increasingly stringent climate policies, climate transition risk has emerged as a significant exogenous shock to the financial system. Using a panel of 57 listed commercial banks in China over the period 2010–2024, this study investigates whether and how climate transition risk shapes bank risk-taking behavior and identifies the mechanisms involved. Empirical evidence shows that rising climate transition risk significantly lowers bank risk-taking, a conclusion that holds consistently under various endogeneity and robustness checks. Second, the evidence suggests that climate transition risk may indirectly reduce bank risk-taking by impairing growth capacity and increasing operational costs per unit. Third, moderating effect analysis reveals that higher levels of digital transformation and the implementation of the Paris Agreement help alleviate the adverse effects of climate transition risk, whereas increased economic policy uncertainty amplifies this effect. Fourth, heterogeneity analysis shows that large banks exhibit greater resilience, while banks with higher carbon-intensive exposure are more sensitive to climate transition risk. Overall, these findings provide empirical evidence and policy implications for enhancing climate-related financial regulation and facilitating the green transformation of the financial system. Full article