Results 151 to 160 of about 10,388,998 (324)

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

open access: yesAdvanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Conformationally Driven Dual Fluorescence Properties of Higher Heteroacenes With Periodically Incorporated Boron Atoms

open access: yesAngewandte Chemie, EarlyView.
We herein report the synthesis of a new heteroheptacene derivative with periodically incorporated six boron atoms. This compound exhibits dual fluorescence attributed to two interconvertible conformers that result from a delicate balance between the extended π‐system and the steric demand of bulky aryl groups attached to the boron centers.
Takeshi Yokochi   +6 more
wiley   +2 more sources

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

open access: yesAdvanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova   +4 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley   +1 more source

ALK1 controls hepatic vessel formation, angiodiversity, and angiocrine functions in hereditary hemorrhagic telangiectasia of the liver

open access: yesHepatology, EarlyView., 2022
Hepatic endothelial Alk1 signaling protects from development of vascular malformations while maintaining organ‐specific endothelial differentiation and angiocrine portmanteau of the names Wingless and Int‐1 signaling. Abstract Background and Aims In hereditary hemorrhagic telangiectasia (HHT), severe liver vascular malformations are associated with ...
Christian David Schmid   +20 more
wiley   +1 more source

Materials Informatics

open access: yesMaterials Today, 2005
openaire   +1 more source

ResearchConnect: An AI‐Powered Platform for Interdisciplinary Research Team Formation and Ideation Development

open access: yesAdvanced Intelligent Systems, EarlyView.
ResearchConnect is an AI‐powered platform that automates researcher profiling, interdisciplinary team formation, and early‐stage research ideation. By extracting keywords from papers and web sources, it quickly clusters researchers into coherent teams and generates collaborative ideas using large language models. Validation on NSF‐funded projects shows
Akshay Vilas Jadhav   +2 more
wiley   +1 more source

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