Results 221 to 230 of about 622,196 (281)
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han +10 more
wiley +1 more source
Transfer learning and knowledge graph enhanced VR animation resource recommendation with creativity prediction. [PDF]
Yan C, Mohamed HB.
europepmc +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Construction and application of knowledge graph for seed quality standard documents. [PDF]
Yang Z, He Q, Zhang J.
europepmc +1 more source
Large language model-driven knowledge graph reasoning for enhanced semantic segmentation. [PDF]
Su J +6 more
europepmc +1 more source
A short text entity disambiguation method based on BERT model and shortest path algorithm. [PDF]
Liu X +8 more
europepmc +1 more source
A Review of Fault Diagnosis Methods: From Traditional Machine Learning to Large Language Model Fusion Paradigm. [PDF]
Nie Q, Geng J, Liu C.
europepmc +1 more source
Robot End-Effectors Adaptive Design Method Based on Embedding Domain Knowledge into Reinforcement Learning. [PDF]
Zhu Y, Zhang T, Lu Y, Yao L.
europepmc +1 more source

