Results 161 to 170 of about 6,691 (300)
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source
Manufacturing of 8 million Q-factor micro hemispherical resonator gyroscopes via patterned coating technology. [PDF]
Zhu F +8 more
europepmc +1 more source
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Reexamination of Grain-Boundary Sliding by Diffusion
identifier:oai:t2r2.star.titech.ac.jp ...
openaire +1 more source
High-Temperature Formability and Friction Regulation Mechanism of TA17 Titanium Alloy with Typical Microstructures. [PDF]
Yan B, Zhang G, Liu X, Yang Y.
europepmc +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Effect of Heat Treatment on the Corrosion and Wear Behavior of Hastelloy C276 Alloy Fabricated via Laser Powder Bed Fusion. [PDF]
Fang X +11 more
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Wear Behavior of Austenitic Stainless Steel 308L Fabricated by Wire Arc Additive Manufacturing. [PDF]
Alzughaibi S +6 more
europepmc +1 more source
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula +10 more
wiley +1 more source

