Results 81 to 90 of about 69,930 (266)
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
As the scale and complexity of modern industrial equipment continue to grow, there is an increasing demand for efficient and reliable fault detection technologies.
Jianhua Lyu, Liangzhen Zhu, Baili Zhang
doaj +1 more source
Towards Temporal Knowledge Graph Alignment in the Wild
Temporal Knowledge Graph Alignment (TKGA) seeks to identify equivalent entities across heterogeneous temporal knowledge graphs (TKGs) for fusion to improve their completeness. Although some approaches have been proposed to tackle this task, most assume unified temporal element standards and simplified temporal structures across different TKGs.
Runhao Zhao +5 more
openaire +2 more sources
Our study reveals the protective role of GPR124 in maintaining BBB integrity and promoting neurological recovery following TBI. It makes a significant contribution by uncovering a novel molecular interaction between GPR124 and FGFBP1 and linking this to activation of the Wnt/β‐catenin signaling pathway in vascular repair mechanisms.
Chen Wang +13 more
wiley +1 more source
Liu et al. define a systems‐level interactome of fibroadipogenic progenitor (FAP)‐mediated signaling in skeletal muscle by integrating single‐cell transcriptomics with FAP depletion‐based perturbation analysis. Functional interrogation using a conditioned media bioassay links predicted signaling to multicellular outcomes, establishing a framework to ...
Xingyu Liu +13 more
wiley +1 more source
Enhancing Temporal Knowledge Graph for Future Event Prediction with Long-Term Dense Graph
Temporal knowledge graph (TKG) reasoning has emerged as a pivotal approach in event prediction. An important yet challenging task in TKG reasoning is to predict future events by extrapolating from historical events and their correlations.
Bin Chen +4 more
doaj +1 more source
Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu +7 more
wiley +1 more source
A multimodal intravital imaging platform enables longitudinal tracking of human cortical organoids transplanted into chronic stroke lesions. By combining surgical microscopy, MRI, bioluminescence imaging, and two‐photon fluorescence microscopy, the platform captures graft placement, viability dynamics, and cellular‐scale morphology in vivo, offering a ...
Jinghui Wang +12 more
wiley +1 more source
This study investigates how the internal structure of fiber‐reinforced ceramic composites affects their resistance to damage. By combining 3D X‐ray imaging with acoustic emission monitoring during mechanical testing, it reveals how silicon distribution influences crack formation.
Yang Chen +7 more
wiley +1 more source
Dissecting the Ecological Structure of Health and Disease in the Global Gut Microbiome
We introduce Wiredancer, a framework that identifies three continuous ecological factors of the gut microbiota. These factors exhibit distinct patterns across health and disease, jointly capturing disrupted ecological stability and offering a new perspective for precision diagnostics and therapeutic strategies.
Baoyuan Zhu +19 more
wiley +1 more source

