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.