Awe, a self-transcendent emotion, has been theoretically posited as a precursor to wise reasoning. However, direct empirical evidence supporting this relationship and the underlying mechanism has been limited. In four studies (N = 3700), we examined the relationship between awe and wise reasoning, as well as the mediating effect of self-transcendence, employing cross-sectional, longitudinal, and experimental designs. We consistently found that awe had a lagged effect on (Study 1), enhanced (Studies 2 & 3), and was associated with (Study 4) wise reasoning. Furthermore, self-transcendence mediated this relationship (Studies 3 & 4). The impact of awe on wise reasoning and mediating effect of self-transcendence could not solely be attributed to awe’s predominantly positive nature, and the mediation model was established beyond the influence of self-smallness (Studies 3–4). These findings contribute to understanding the emotional trigger of wise reasoning, the cognitive implications of awe, and its role in promoting wise conflict resolution.
As artificial intelligence-generated content (AIGC) continues to evolve, video-to-audio (V2A) generation has emerged as a key area with promising applications in multimedia editing, augmented reality, and automated content creation. While Transformer and Diffusion models have advanced audio generation, a significant challenge persists in extracting precise semantic information from videos, as current models often lose sequential context by relying solely on frame-based features. To address this, we present TA-V2A, a method that integrates language, audio, and video features to improve semantic representation in latent space. By incorporating large language models for enhanced video comprehension, our approach leverages text guidance to enrich semantic expression. Our diffusion model-based system utilizes automated text modulation to enhance inference quality and efficiency, providing personalized control through text-guided interfaces. This integration enhances semantic expression while ensuring temporal alignment, leading to more accurate and coherent video-to-audio generation.
The asymmetrical global higher education and knowledge systems ordered by Euro–American hegemony have been increasingly interrogated, especially by scholars in the humanities and social sciences (HSS). With gathering awareness, growing HSS scholars from non-Western backgrounds have called for global intellectual pluriversality. Responding to such a trend, this article sheds new light on the status quo of East Asian and other non-Euro–American intellectual traditions by taking Chinese intellectual traditions as a case. Since the nineteenth century, generations of Chinese intellectuals have strived to transform their intellectual traditions into modern resources. This historical mission has been carried on by contemporary scholars and become even more complex in the current global era. By unpacking the real perceptions and recent experiences of Chinese HSS scholars, this study demonstrates that Chinese intellectual traditions deeply influence today’s knowledge production and have been transformed into three kinds of academic resources: approaches, methodologies/paradigms, and theories. However, the transformation process has never been smooth. Domestically, the great endeavours of Chinese HSS scholars are often impeded by the dominant intellectual extraversion and coercive audit culture; internationally, they feel constrained by epistemic injustice. This article proposes an empirical approach to examining and presenting intellectual traditions in the individual experiences of scholars. It reveals the high complexities of navigating through asymmetrical globalisation to achieve intellectual pluriversality.
This study aims to identify the associations between teacher mental health and student mental health. Cross-sectional data were collected from 127,877 students aged 9–20 years and 2,759 teachers across 31 provinces in China. The mental health of students and teachers were assessed by well-being (life satisfaction and positive mental health), and psychological distress (depression and anxiety). Controlling for demographic variables, multilevel regression analyses suggest that higher teacher positive mental health was linked to higher student positive mental health and lower student depression; higher teacher depression were correlated with higher student depression; and teacher life satisfaction and anxiety were not correlated with any indicators of student mental health. The study highlights the significant association between teacher mental health and student mental health.
Trust in artificial intelligence (AI) has become a central issue due to the opacity and unpredictability of AI decision-making processes. However, existing studies often produce inconsistent results and fail to provide a unified understanding of the underlying factors, making a comprehensive review necessary. To address this gap, we conducted a systematic review of 562 empirical studies to explore the antecedents and consequences of human trust in AI. The review identified key antecedents of trust, including AI capability, anthropomorphism, individual factors, and explainability, and associated consequences, such as behavioral intention, attitude, and acceptance. A cross-cultural analysis revealed significant differences in how cultural contexts influence the perception and prioritization of factors, such as capability, transparency, and anthropomorphism. These findings emphasize the need for a multidimensional approach to developing trustworthy AI systems, highlighting the importance of cultural sensitivity in AI design. The review also suggests several promising avenues for future research, including dynamic trust formation, reciprocal trust relationships, and the evolution of trust over time. Addressing these areas will enhance our understanding of trust in AI and contribute to the development of culturally adapted and ethically sound AI technologies.
Two-dimensional (2D) van der Waals ferroelectric materials have emerged as promising candidates for miniaturized devices due to their atomically thin structures and unique ability to maintain ferroelectricity even at reduced dimensions. Recent research indicates that the interfacial barriers between semiconductors and ferroelectrics can be modulated by polarization charges, with ferroelectric polarization—reversible by an external electric field—playing a crucial role in the switchable diode effect. In this work, we investigate a room-temperature switchable ferroelectric diode (Fe-diode) based on a MoS2/α-In2Se3 heterojunction. The out-of-plane ferroelectric properties of the α-In2Se3 layer enable efficient modulation of the Schottky barriers at the MoS2/α-In2Se3 interface through external voltage application, thereby achieving a notable switchable diode effect with a nonlinearity of up to 934. By exploiting the inherent nonlinearity, the ferroelectric diode can effectively generate complex signal waveforms, making it highly suitable for secure communication systems. These findings make the ferroelectric diode a potential candidate for enhancing confidentiality in future communication technologies, protecting data against eavesdropping and unauthorized access.
The global knowledge asymmetries are increasingly interrogated by non-Western humanities and social sciences (HSS) scholars whose research is anchored in local contexts yet must adhere to international (Western) standards. Under this circumstance, the study aims to examine how the cultural self-awareness of non-Western HSS scholars is manifested in research through a Chinese lens. Based on previous theoretical perspectives and Fei Xiaotong’s theory of cultural self-awareness, the study first constructs two analytical dimensions: academic self-reflexivity and cultural appreciation attitudes. It then performs a qualitative investigation including 28 Mainland Chinese HSS scholars through interviews and literature analyses. The findings highlight key principles for academic self-reflexivity, namely reflecting on intellectual extraversion, dichotomous thinking, and the reemphasis on Chinese culture and knowledge. The cultural appreciation attitudes are also elaborated, which are embodied in the recognition and revaluation of traditional Chinese knowledge, the continued appreciation of modern Western knowledge, and the synthesis of different cultures and knowledge in research. These findings develop Fei’s cultural self-awareness theory and add new discourses to address global knowledge imbalances, promoting a more diverse and inclusive global higher education landscape.
Low-light image enhancement (LLIE) aims to improve visibility and signal-to-noise ratio in images captured under poor lighting conditions. Despite impressive improvement, deep learning-based LLIE approaches require extensive training data, which is often difficult and costly to obtain. In this paper, we propose a zero-shot LLIE framework leveraging pre-trained latent diffusion models for the first time, which act as powerful priors to recover latent images from low-light inputs. Our approach introduces several components to alleviate the inherent challenges in utilizing pre-trained latent diffusion models, modeling the degradation process in an image-adaptive manner, penalizing the latent outside the manifold of natural images, and balancing the strengths of the guidance from the given low-light image during the denoising process. Experimental results demonstrate that our framework outperforms existing methods, achieving superior performance across various datasets.