Search Results (10,545)

Against the backdrop of the United Nations Sustainable Development Goals (SDGs), innovation-driven development serves as the core engine of long-term sustainable economic development, while resource misallocation has emerged as a critical bottleneck constraining sustainable innovation and coordinated regional development. Grounded in the neoclassical theory of factor allocation, this paper incorporates capital misallocation, labor misallocation and the digital economy into a unified analytical framework. Using China’s provincial panel data spanning 2001 to 2024, we systematically investigate the impact effects, underlying transmission mechanisms and regional heterogeneity of resource misallocation and the digital economy on scientific and technological innovation through benchmark regression, robustness tests and heterogeneity analysis. The results show that resource misallocation exerts a significant and robust inhibitory effect on technological innovation, with the inhibitory effect of capital misallocation being more pronounced than that of labor misallocation. The digital economy has a significant positive driving effect on technological innovation, and it can also indirectly boost technological innovation by alleviating resource misallocation, with its mitigating effect on resource misallocation presenting obvious structural differences and a stronger correction effect on capital misallocation than on labor misallocation. Economic growth and technological innovation form a mutually reinforcing “growth-innovation” virtuous cycle. In addition, the innovation effects of both resource misallocation and the digital economy exhibit significant regional heterogeneity, where the digital economy’s innovation-driven effect and misallocation-mitigating effect are notably stronger in eastern China than in the central and western regions. The theoretical contribution of this paper lies in constructing a transmission mechanism framework of “digital economy to resource misallocation to technological innovation”, which enriches the connotations of factor allocation and innovation theories. Its practical value is to provide policymakers with differentiated development paths for the digital economy and optimization strategies for factor allocation, thus facilitating the effective implementation of the innovation-driven development strategy. Full article

There are four representative commentaries on the Duren jing from the Southern Song and Yuan Dynasties, authored by Qingyuan Zhenren, Xiao Yingsou, Chen Guanwu, and Xue Jizhao. These four commentaries combine both philological interpretation and philosophical interpretation, but each emphasizes one over the other. The Qingyuan and Xue focus on philological interpretation, aiming to reveal the original meaning of the text. The former offers detailed and in-depth philological analysis, occasionally integrating ideas on self-cultivation; the latter provides concise explanations, avoiding speculation and forced analogies. The Xiao and Chen commentaries, on the other hand, emphasize philosophical interpretation. Though grounded in philology, they primarily use the scripture as a medium to construct and develop the theory of internal alchemy. Xiao’s commentary pioneered a systematic approach to internal alchemy, while Chen’s work inherited and further developed this approach. In terms of interpretive strategy, the Qingyuan and Xue commentaries primarily use Taoist texts to support philological mutual verification, while the Xiao and Chen commentaries widely reference Confucian, Buddhist, and Taoist resources to conduct philosophical mutual verification. The differences in their interpretive approaches essentially originate from the commentators’ distinctly different pre-understandings. Through textual interpretation, they achieved varying degrees of “fusion of horizons” between the text’s original historical horizon and the contemporary horizon of the Song and Yuan Dynasties. The evolution from “explaining the text based on its original meaning” to “elucidating new philosophical ideas through the scripture” not only reflects a shift in Taoism from external ritual practices to internal alchemical cultivation, but also demonstrates the dialectical relationship between objective explanation and creative understanding, and provides significant intellectual resources for the development of contemporary Chinese hermeneutics. Full article

This article examines the question of under what conditions justice-learning in German-language Christian religious education (CRE), and thus in religious instruction (CRI)—both as content and as form—can live up to its normative self-image as a language school of freedom. The thesis pursued here is that this requires a self-enlightened approach to justice that critically receives the analytical power of postcolonial theories, but resists their epistemological relativism and remains anchored in the biblical heritage of God’s universal and at the same time preferential justice. After exploring the philosophical and theological heritage of reflections on justice and the resulting aporias in the theory and practice of CRE, postcolonial theories are examined in terms of their potential and their own theoretical limitations. This makes it possible to outline orientations for a self-enlightened, difference-sensitive, and at the same time universally-oriented reflection on justice that productively integrates postcolonial insights without abandoning the constitutive subject-orientation of CRE. Full article

During circumferential tensioning of prestressing strands in U-shaped aqueducts, longitudinal tensile stresses may develop and impair crack resistance. Most existing studies rely on three-dimensional finite element (FE) simulations. Although accurate, FE modeling is time-consuming and unsuitable for rapid scheme evaluation during construction. To overcome this limitation, the U-shaped aqueduct was first simplified as a cylindrical shell and the feasibility of this idealization was verified. An approximate analytical solution was then derived from cylindrical shell theory to predict the longitudinal stress induced by circumferential prestressing. Practical factors, including non-uniform wall thickness, non-equidistant strand spacing, and strand positional deviations, were incorporated to improve engineering applicability. FE results confirm good agreement, with RMSE of 0.055–0.169 MPa and NRMSE of 2.3–19.6%, where the upper bound occurs only in localized regions. The method was further applied to an engineering project to optimize the tensioning scheme. With a rational interval-tensioning procedure, the peak longitudinal tensile stress was reduced by 31.6%. Overall, the proposed approach enables rapid stress estimation and supports preliminary screening and optimization of circumferential tensioning schemes. Full article

Digital technologies are widely recognized for their potential to support active learning and foster higher-order cognitive skills, including critical thinking. However, limited research has examined the extent to which students are directly involved in selecting digital tools that shape their learning. This study investigates teachers’ ability to engage students in the selection and pedagogical use of digital technologies, with attention to practices supporting active, personalized learning and critical thinking. Data were collected from 156 educators across diverse disciplines in five teacher-training colleges in Israel using an online questionnaire assessing levels of digital tool use, from non-use to active student involvement. Item Response Theory (IRT) was applied to model teachers’ proficiency and examine differences across tools and background characteristics. Results indicate substantial variability in teachers’ ability to involve students, with particularly low involvement in tools related to problem-solving, differentiation, and personalized learning. Gender and institutional role were significant predictors, with female educators and those holding additional roles demonstrating higher proficiency. These findings highlight the importance of teachers’ techno-pedagogical competence in enabling student participation in digital decision-making and suggest that involving students in tool selection can support the development of critical thinking and learner agency in digitally mediated learning environments. Full article

In this work, an adaptive event-triggered-based consensus control strategy is proposed for the quadrotor unmanned aerial vehicle (QUAV) formation system in the presence of external disturbances and state constraints. Firstly, the disturbed QUAV formation system dynamic model is established. Then, to address the initial peaking explosion problem in the traditional active disturbance rejection control method, a time-varying gain extended state observer (TGESO) is designed to suppress external disturbances. Meanwhile, a novel barrier Lyapunov function (BLF) is constructed to cope with the adverse effects caused by state constraints. Furthermore, aiming to alleviate network congestion and reduce communication burden, the adaptive event-triggered mechanism (AETM) is adopted to design the formation flight controller. Finally, the stability of the developed consensus controller and the boundedness of all error signals are proved via Lyapunov theory. Comparative simulation results demonstrate the practicality of the presented control algorithm. Full article

The evolution of future Internet and sixth-generation (6G) networks is driving a paradigm shift from classical bit-centric communication toward meaning-aware and task-oriented communication models. Traditional information theory, while fundamental for ensuring reliable symbol transmission, does not account for semantic relevance or task effectiveness, which are critical for emerging applications such as autonomous systems, immersive services, and ultra-low-latency communications. This article presents a comprehensive review of Semantic Communications (SemCom) from a future Internet perspective. The review systematically analyses representative extensions of classical information theory aimed at quantifying semantic information, including semantic information measures, semantic channel capacity, and semantic rate–distortion formulations. In addition, the main mathematical and computational frameworks enabling practical semantic communication systems are examined, including the Information Bottleneck principle, learning-based end-to-end communication architectures, and reinforcement learning approaches for task-oriented optimization under network constraints. The review further discusses the role of semantic metrics, contextual modelling, and task-driven performance evaluation in the design of semantic-aware communication systems. The analysis identifies key open challenges, particularly the lack of a unified theoretical framework, the need for robust and context-aware semantic performance metrics, and the integration of semantic awareness into network-level design. Overall, this review highlights Semantic Communications as a promising paradigm for future Internet and 6G networks, where communication efficiency is increasingly determined by semantic relevance and task effectiveness rather than bit-level fidelity alone. Full article

This study investigates the psychological mechanisms through which coaching leadership influences employees’ bootlegging innovation behavior. Drawing on leadership and organizational behavior theories, we propose a serial mediation model in which work meaning and organizational psychological ownership jointly transmit the effects of coaching leadership on employees’ informal innovative behavior. Using survey data collected from 427 employees, the results demonstrate that coaching leadership positively predicts bootlegging innovation behavior. Moreover, both work meaning and organizational psychological ownership independently mediate this relationship. Importantly, the findings further support a sequential mediation pathway, indicating that coaching leadership enhances employees’ perceptions of work meaning, which subsequently fosters stronger organizational psychological ownership and, in turn, stimulates bootlegging innovation behavior. By elucidating the intertwined motivational and ownership-based psychological processes underlying informal innovation, this study advances the literature on coaching leadership and employee-driven innovation. The findings also offer practical insights for managers seeking to cultivate grassroots innovation by fostering meaningful work experiences and a sense of psychological ownership among employees. Full article

Live case studies are widely used in higher education to support active learning; however, their pedagogical potential is often limited by weak integration with learning theories and assessments. This research-to-practice study examines the systematic design of live case studies by integrating Kolb’s experiential learning cycle (ELC) and authentic assessment (AA) principles. This paper presents a framework that conceptualises live cases as the learning context, ELC as the learning process, and AA as evaluative logic. The framework is illustrated through a case study of an undergraduate Quality Management module in industrial engineering at a Mexican university, involving 31 final-year students. The study is design-oriented and illustrative, aiming to demonstrate framework enactment rather than evaluating causal effectiveness. Using a case study methodology, the instructional design and enactment were documented using the ADDIE model. Data were obtained from educational artefacts, assessment results, and student feedback surveys. The findings suggest that aligning teaching and assessment activities with the ELC stages and the AA principles effectively supports learning trajectories. This support covers experience, reflection, conceptualisation, and application. Live case studies enabled the integration of multiple assessment methods around shared organisational problems and supported personalised learning through students’ case selection. This study contributes a design logic and operational framework for distributing authentic assessment across Kolb’s experiential learning stages within live case pedagogy. Rather than offering statistical generalisation, the framework serves as a foundation for adaptation and research, emphasising transferability across disciplines, educational levels, and delivery modes. Limitations are acknowledged regarding the conceptual scope, methodological design, and empirical context. Full article

With the increasing importance of cultural consumption and the sustainable revitalization of intangible cultural heritage (ICH), visual communication has become a key mechanism for translating cultural meanings into contemporary branding contexts. This study develops a semiotics-informed structural model that integrates semiotic theory with consumer behavior frameworks to explain how cultural visual symbols influence brand preference through cultural cognition and cultural identity. Using Wufangzhai as an empirical case, partial least squares structural equation modeling (PLS-SEM) is applied to survey data from 274 consumers. The results indicate that different visual elements exert differentiated effects on cultural cognition, with color and packaging showing stronger influences, while typography plays a more significant role in shaping cultural identity. Cultural identity is also found to mediate the relationship between cultural cognition and brand preference. These findings contribute to cultural branding research and provide practical insights for the design of ICH visual communication systems. Full article

The complex architecture and stacking patterns of deepwater turbidite channel sandbodies introduce significant uncertainty in injector–producer connectivity. This uncertainty affects both the mechanisms and the quantitative evaluation of the waterflood sweep. In this study, a representative reservoir in the Niger Delta Basin is selected as a case study. Injector–producer well groups are first classified into three connectivity patterns—coeval, cross-stage, and hybrid based on geological and seismic constraints. Time-lapse seismic data are then interpreted to delineate sweep morphology and to infer the controlling mechanisms associated with each pattern. Coeval connectivity exhibits a relatively uniform and continuous front advance with minimal barriers. Cross-stage connectivity shows fragmented swept regions with pronounced bypassing, and localized preferential breakthrough caused by discontinuous sandbodies and pervasive barriers. Hybrid connectivity is characterized by intermediate behavior, combining features of both patterns. To translate these mechanistic differences into quantitative metrics for development evaluation, an oil–water relative permeability ratio correlation for low viscosity oil is established that remains valid across the full water cut range, thereby overcoming the limitations of conventional semi-log linear correlations at both low and ultra-high water cut stages. Based on this framework, a production data-driven predictive model for waterflood sweep efficiency is derived using production data and steady state flow theory. The model is validated across well groups representing different connectivity patterns. Field application yields a consistent ranking of sweep efficiency: coeval > hybrid > cross-stage, with group average values of 0.86, 0.80, and 0.70, respectively. These results agree with the mechanistic interpretation derived from time-lapse seismic analysis. The proposed methodology provides a practical quantitative framework for evaluating injector–producer connectivity and comparing development strategies in deepwater turbidite channel reservoirs. Full article

While existing research analyzes AI’s impact on platform enterprises’ competitive advantages from technological or organizational perspectives, it fails to adequately account for how multiple factors combined shape competitive advantages. From the perspective of situated AI theory, this study examines how the combinations among AI application characteristics, situated AI activities, platform enterprise attributes, and environmental characteristics collaboratively build platform enterprises’ competitive advantages. Drawing on panel data from Chinese listed platform enterprises and employing fuzzy-set Qualitative Comparative Analysis (fsQCA), this study reveals that (1) AI technology innovation and recasting AI are necessary conditions for platform enterprises to establish competitive advantages; (2) AI-enabled competitive advantages emerge from three types of configurations, the situated AI dominance type, the situated AI subsidiary type, or the collaborative drive type; (3) the AI-enabled combinations result in competitive advantages by three paths, AI internalization, AI leverage, and AI collaboration; and (4) the AI-enabled competitive advantages are more likely to be achieved by innovation platforms than by transaction platforms. These research findings fill the knowledge gap in AI-enabled competitive strategy, enrich the literature on situated AI theory, and offer practical guidance for platform enterprises’ AI applications. Full article

Crowdsourcing contest platforms provide enterprises with opportunities to seek external resources at a lower cost. Increasing the participation of solvers is the key to improving the success of crowdsourcing contests. Many previous studies attempt to use participation intention as a proxy for exploring participation behavior, using surveys to examine participation intention or continued participation intention. However, participation intention and participation behavior differ significantly, and the dynamic nature of influencing factors has a more complex effect on solvers’ participation. Therefore, based on social exchange theory, we use the dynamic data of winvk.com to construct a two-stage model of view and submission. The effect of dynamic competition on participation intention and participation behavior is explored. The results show that external competition has a consistent negative effect on both participation intention and participation behavior. However, the effect of internal competition is different. It has no significant effect on participation intention, but has a significant positive effect on participation behavior. In addition, rewards exacerbate the effect of competition on participation behavior. These findings provide empirical evidence for exploring differences in participation intention and behavior, and offer practical suggestions for enterprises and platforms to improve solvers’ participation in a short time. Full article

During the mid-to-late Qing Dynasty, the folk-belief text Yuli constructed a systematic “underworld legal code” via its image–text system, distinct from traditional religious karma and religious law. This study focuses on Yuli’s core image system, exploring its unique legal characteristics and social governance functions through an interdisciplinary approach integrating religious studies, art history, and legal history. Yuli transforms real judicial symbols, such as government offices and prison gates, into underworld visual elements, establishing the core legal principles of “correspondence between crime and punishment” and “universal equality” while reflecting contemporary legal thought. The formation of this “underworld legal code” is closely linked to the creative practices of Qing Confucian scholars, who utilized folk beliefs as a vehicle to disseminate secular legal concepts and respond to social demands for behavioral norms. The Yuli thus became the primary behavioral norm for its grassroots audience, who, due to low literacy, could not understand the formal laws of the Qing Dynasty, and guided them to refrain from criminal acts. Yuli’s “underworld legal code” not only supplemented the national legal system but also reflected the pluralistic pattern of social governance in late imperial China, providing crucial empirical support for the theory of legal pluralism. This study deepens the understanding of the interactive relationship between folk beliefs and legal order in traditional China, and further clarifies the unique mode of grassroots social governance in the Qing Dynasty. Full article

Knowledge Tracing, which estimates how students’ knowledge evolves during interactions with educational content, is a cornerstone of Intelligent Tutoring Systems. While deep learning models achieve superior predictive performance in this task, they lack interpretability, a limitation that is particularly critical in educational contexts. We introduce gTransformer, a new type of grounded Transformer model bridging deep learning performance with intrinsic interpretability through representational grounding. It adds theory-based parameters to input interaction sequences and uses attention mechanisms to transform them into latent representations. These are projected into enriched parameters that incorporate historical learning context while preserving semantics. Validation demonstrates: (1) structural encoding around theoretical concepts (probing selectivity $\Delta R^2>0.5$); (2) semantic alignment; and (3) functional alignment with quantified confidence. Results show that gTransformer achieves predictive performance competitive with state-of-the-art architectures while offering intrinsically interpretable predictions. The trade-off is characterised by a significant Area Under the Curve (AUC) gain over traditional theory-based models (+19.9%), with a minimal cost (3.9%) relative to non-interpretable configurations. Critically, gTransformer enables context-aware personalisation by differentiating students based on longitudinal learning trajectories rather than immediate responses, capturing patterns that traditional models cannot represent. This offers a practical path toward adaptive instruction driven by artificial intelligence that is both accurate and interpretable. Full article