Results 131 to 140 of about 25,782,438 (282)
Benchmarking criteria to determine latent linear dimensionality in neural data
Dimensionality reduction is widely used in modern Neuroscience to process massive neural recordings data. Despite the development of complex non-linear techniques, linear algorithms, in particular principal component analysis (PCA), are still the gold ...
Francesco Edoardo Vaccari +6 more
doaj +1 more source
Potential PCA interpretation problems for volatility smile dynamics [PDF]
Principal Component Analysis (PCA) is a common procedure for the analysis of financial market data, such as implied volatility smiles or interest rate curves.
Reiswich, Dimitri, Tompkins, Robert
core
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
Pancreatic adenocarcinoma (PAAD) remains highly lethal with limited treatment options. This study demonstrates that coixenolide, a bioactive compound from Coix lacryma‐jobi L. and a key component of the clinically approved Kanglaite injection, exhibits enhanced antitumor efficacy in high‐fat diet (HFD)‐induced obese mice bearing PAAD tumors compared to
Kaidi Chen +20 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
This study uncovers hierarchical coordination between K11 lactylation and S199 phosphorylation of CKB in cerebral ischemia‐reperfusion injury. Such dual modifications potentiate CKB enzymatic function, remodel energy metabolism, alleviate oxidative stress and neuronal damage, and represent a viable therapeutic target for stroke treatment.
Chao Duan +17 more
wiley +1 more source
Machine Learning for Green Solvents: Assessment, Selection and Substitution
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta +4 more
wiley +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
An Object-Oriented Framework for Robust Multivariate Analysis [PDF]
Taking advantage of the S4 class system of the programming environment R, which facilitates the creation and maintenance of reusable and modular components, an object-oriented framework for robust multivariate analysis was developed.
Valentin Todorov, Peter Filzmoser
core
Modulation of miR‐23b Wnt/β‐catenin Axis Strengthens Endothelial Barrier Properties
Early blood‐brain barrier (BBB) disruption contributes to stroke and CNS disease pathology. miR‐23b was identified as a regulator of BBB integrity in brain endothelial cells. Inhibition of miR‐23b enhanced barrier‐associated properties, promoted repair‐related signaling, and reduced BBB leakage in experimental stroke models, supporting further ...
Victor Anthony Martinez +16 more
wiley +1 more source

