Results 181 to 190 of about 1,486,932 (305)
Fast and interpretable quantification of biological shape heterogeneity via stratified Wasserstein kernel. [PDF]
Zhao W, Sutherland DJ, Dao Duc K.
europepmc +1 more source
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali +5 more
wiley +1 more source
Element-Free Galerkin Method for Analyzing Size-Dependent Thermally Induced Free Vibration Characteristics of Functionally Graded Magneto-Electro-Elastic Doubly Curved Microscale Shells. [PDF]
Wu CP, Liu MJ.
europepmc +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Identifying stochastic dynamics from non-sequential data (DyNoSeD). [PDF]
Lu Z, Kuśmierz Ł, Mihalas S.
europepmc +1 more source
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
Mean and variance heterogeneity loci impact kernel compositional traits in maize. [PDF]
Ismail YMA +5 more
europepmc +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
How competition can drive allochronic divergence: A case study in the Marine Midge, Clunio marinus. [PDF]
Jacobsen AGG, Kaiser TS, Gokhale CS.
europepmc +1 more source

