GA-UNet: A Lightweight Ghost and Attention U-Net for Medical Image Segmentation.

U-Net has demonstrated strong performance in the field of medical image segmentation and has been adapted into various variants to cater to a wide range of applications. However, these variants primarily focus on enhancing the model's feature extraction capabilities, often resulting in increased parameters and floating point operations (Flops). In this paper, we propose GA-UNet (Ghost and Attention U-Net), a lightweight U-Net for medical image segmentation.

Protein-Inspired Self-Healable TiC MXenes/Rubber-Based Supramolecular Elastomer for Intelligent Sensing.

Progress toward the integration of electronic sensors with a signal processing system is important for artificial intelligent and smart robotics. It demands mechanically robust, highly sensitive, and self-healable sensing materials which could generate discernible electric variations responding to external stimuli. Here, inspired by the supramolecular interactions of amino acid residues in proteins, we report a self-healable nanostructured TiCMXenes/rubber-based supramolecular elastomer (NMSE) for intelligent sensing.

Multiple Hydrogen Bonding Enables the Self-Healing of Sensors for Human-Machine Interactions.

Despite its widespread use in signal collection, flexible sensors have been rarely used in human-machine interactions owing to its indistinguishable signal, poor reliability, and poor stability when inflicted with unavoidable scratches and/or mechanical cuts. A highly sensitive and self-healing sensor enabled by multiple hydrogen bonding network and nanostructured conductive network is demonstrated. The nanostructured supramolecular sensor displays extremely fast (ca.