Results 41 to 50 of about 448 (209)
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
Pump-turbines are critical for maintaining power grid stability, but they frequently suffer from flow instabilities induced by cavitation due to frequent operating condition changes.
Yanhao Li, Lei Chen, Jianwen Xu, An Yu
doaj +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +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
The present paper demonstrates a proof-of-concept by introducing a variable guide vane system in the draft tube of a high-head Francis model turbine. The aim is to examine the hydraulic performance of the turbine while mitigating the pressure pulsations ...
Jesline Joy +2 more
doaj +1 more source
Formation of Rotating Vortex Rope in the Francis-99 Draft Tube
The aim of this research is to understand the mechanism(s) of RVR formation duringthe changes in operating condition from the Best Efficiency Point (BEP) to Part Load (PL).
N Sotoudeh, R Maddahian, M J Cervantes
openaire +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed +15 more
wiley +1 more source
A Metabolomic Signature Predicts Gout Flare Clinical Outcome Associated With Colchicine Prophylaxis
Objective This study investigated that serum metabolomics, before urate‐lowering therapy (ULT) initiation, could serve as a biomarker for responsiveness to colchicine prophylaxis in patients with gout commencing treat‐to‐target ULT. Methods We studied a multicenter prospective cohort (n = 409) initiating treat‐to‐target ULT plus colchicine prophylaxis.
Wenyan Sun +13 more
wiley +1 more source
Energy distribution and chaotic pressure pulsation analysis of vortex ropes in Francis-99
Francis turbines, essential for stability in diverse operating conditions and variable-speed scenarios, encounter efficiency-compromising vortex rope formations in the draft tube, leading to substantial pressure fluctuations.
Puxi Li +5 more
doaj +1 more source

