Neuromorphic vision hardware, embedded with multiple functions, has emerged as a potent platform for reducing redundant data shuffling and implementing processing tasks. Scientists in China have designed optoelectronic memory, which combines sensing, integration, and memory. Thanks to the unique underlying mechanism, optoelectronic memory exhibits a record photomemory speed and broadband application range. With no motion blur, the technique is expected to enable precise moving target tracking and recognition, underscoring its superiority in intelligent perception.

The NJUST research group of Prof. Qian Chen and Prof. Chao Zuo have reported a novel learning-based ultrafast three dimensions (3D) imaging technique, termed single-shot super-resolved fringe projection profilometry (SSSR-FPP), which enables ultrafast 3D imaging at 100,000 Hz. SSSR-FPP exploits the significant speed gain achieved by reducing the imaging window of conventional high-speed cameras while "regenerating" the lost spatial resolution with deep learning, resulting in a boost in 3D frame rate up to more than one order of magnitude without compromising spatial resolution.

Chiral transport has significant potential applications in optical systems and holds promise in fields like optical communications and sensing. However, current on-chip chiral transport devices are static, which limits their practical use. This work introduces a polarization-controlled chiral transport method, experimentally demonstrating that different polarizations can produce controllable mode outputs. This provides new insights for developing on-chip reconfigurable and high-capacity chiral transport devices.

This study shows that there is a complex and close interaction between plants and the root microbiota in nutrient utilization. Environmental nutrient conditions and plant nutrient-related genes jointly regulate the composition and assembly of the root microbiota, while the root microbiota significantly affects the plant's nutrient utilization efficiency by improving nutrient availability and regulating plant hormones.

This study introduces a Semantic Structure-Aware model to enhance Class Activation Mapping for image classification, achieving state-of-the-art performance in weakly-supervised tasks without extra training.

A groundbreaking study has uncovered a fascinating connection between the circadian rhythms of tea plants and the microbial communities in their rhizosphere, providing new insights into nutrient cycling. 

In a new study published in Engineering, researchers from Huazhong University of Science and Technology and the Technical University of Munich have developed an improved proximal policy optimization (IPPO) method. This method is designed to solve the distributed heterogeneous hybrid blocking flow-shop scheduling problem (DHHBFSP), aiming to minimize total tardiness and total energy consumption. The research offers a practical approach for manufacturing scheduling, and its experimental results show better performance compared with other methods.