Bionic Multimodal Augmented Somatosensory Receptor Enabled by Thermogalvanic Hydrogel
A skin‐inspired self‐powered multimodal fingertip receptor that integrates thermogalvanic hydrogels as active mechanoreceptors and thermoreceptors is proposed. By exploiting dynamic‐static thermovoltage of the hydrogel to visualize the unsteady interfacial heat conduction, different materials can be determined in 80 ms.
Ning Li+6 more
wiley +1 more source
Real-Time Detection of Meningiomas by Image Segmentation: A Very Deep Transfer Learning Convolutional Neural Network Approach. [PDF]
Das D, Sarkar C, Das B.
europepmc +1 more source
SGCD presents a novel approach for tissue spatial domain identification by employing interpolation to estimate inter‐spot gene expression and deconvolution to resolve cell‐type composition in both sampled and interstitial regions. By integrating gene expression, cell type, and spatial coordinates within a graph contrastive learning framework, SGCD ...
Tianjiao Zhang+7 more
wiley +1 more source
Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels. [PDF]
Yang Z, Cheng Z, Wu D.
europepmc +1 more source
Soft robotics, featuring intrinsic compliance and biomimetic adaptability, emerges as transformative in next‐generation intelligent systems. This review outlines how advancements in four foundational domains—actuation, materials, manufacturing, and control—drive the evolution of bioinspired intelligent soft robotics, poised to redefine the boundaries ...
Xiaopeng Wang+7 more
wiley +1 more source
Automatic melanoma and non-melanoma skin cancer diagnosis using advanced adaptive fine-tuned convolution neural networks. [PDF]
Khan MA+6 more
europepmc +1 more source
Human Activity Recognition Using a Single Wrist IMU Sensor via Deep Learning Convolutional and Recurrent Neural Nets [PDF]
Edwin Valarezo Añazco+7 more
openalex +1 more source
Predicting unseen drug‐target interactions is challenging. BioBridge presents an Inductive‐Associative pipeline inspired by scientists' workflow. It combines transferable binding principles, learned via multi‐level encoders and adversarial training, with insights from weakly related references through meta‐learning.
Xiaoqing Lian+11 more
wiley +1 more source
Application of Spectral Approach Combined with U-NETs for Quantitative Microwave Breast Imaging. [PDF]
Diès A, Roussel H, Joachimowicz N.
europepmc +1 more source
MGPT: A Multi‐task Graph Prompt Learning Framework for Drug Discovery
MGPT is a unified multi‐task graph prompt learning model providing generalizable and robust graph representations for few‐shot drug association prediction. MGPT demonstrates the ability of seamless task switching and outperforms competitive approaches in few‐shot scenarios.
Yang Li+4 more
wiley +1 more source