Results 181 to 190 of about 18,691 (261)

A Power‐Efficient Monte Carlo Framework for Nonlinear Light–Matter Interactions: In Silico Modeling of Spontaneous and Stimulated Raman Scattering in Turbid Media

Journal of Raman Spectroscopy, EarlyView.
Power‐efficient Monte Carlo modeling of nonlinear light–matter interactions in turbid media is demonstrated using Apple Silicon–accelerated photon transport. The Metal‐base framework enables accurate simulation of spontaneous and stimulated Raman scattering, revealing detection‐dependent SRS efficiency while providing a scalable, energy‐efficient ...
Ilya Vladyko, Vladislav Yakovlev, Alexander Doronin   +2 more
wiley   +1 more source

Alzheimer's clinical research data via R packages: The alzverse. [PDF]

Alzheimers Dement
Donohue MC, Hussen K, Langford O, Gallardo R, Jimenez-Maggiora G, Aisen PS, Alzheimer's Disease Neuroimaging Initiative.   +6 more
europepmc   +1 more source

Optimising Human–AI Decision Performance: A Trust and Capability Framework for Knowledge Management

Knowledge and Process Management, EarlyView.
ABSTRACT Organisations struggle to optimise human–AI collaboration in knowledge‐intensive decision‐making. This paper proposes the Trust–Complementarity Model of Collective Intelligence (TCM‐CI), explaining how calibrated trust and complementary capability utilisation drive superior organisational performance.
Eduardo Carlos Dittmar, Martin Sposato
wiley   +1 more source

Inherent instability of simple DNA repeats shapes an evolutionarily stable distribution of repeat lengths. [PDF]

Nat Commun
McGinty RJ, Balick DJ, Mirkin SM, Sunyaev SR.   +3 more
europepmc   +1 more source

Structure‐Aware Machine Learning for Polymers: A Hierarchical Graph Network for Predicting Properties From Statistical Ensembles

Macromolecular Rapid Communications, EarlyView.
This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig, Yannik Köster, Timo Koswig, Punith Raviswamy, Subhash V. S. Ganti, Stefan Zechel, Christopher Kuenneth, Ulrich S. Schubert   +7 more
wiley   +1 more source

Generalized Additive Modeling of Ecological Data With mgcv: New Adequacy Assessment Tools. [PDF]

Ecol Evol
Mainguy J, McInerney R, Millar RB, Valiquette E, Bélanger M, Moral RA.   +5 more
europepmc   +1 more source

Local Field Aperiodic Spectral Power Modulated by Deep Brain Stimulation in Parkinson's Disease

Movement Disorders, EarlyView.
Abstract Background Aperiodic spectral broadband power has been described recently as reflecting Parkinson's disease (PD) severity. It has therefore become an increasing focus of research interest in the context of the new adaptive deep brain stimulation (DBS) approach.
Martin Lamoš, Aneta Žáčková, David Ulčák, Benjamin Gurka, Daniel Brzuchanski, Lucia Šmahovská, Martina Bočková   +6 more
wiley   +1 more source

Landmark matching and B-spline implicit neural representations for diffusion-weighted imaging distortion correction. [PDF]

Phys Med Biol
Li Y, Liao YP, Dai Y, Deng J, Zhang Y.
europepmc   +1 more source

New Opportunities For the Integration of Artificial Intelligence With Materials Science: From Large Language Models to Embodied Large Models

Materials Genome Engineering Advances, EarlyView.
This review first introduces the diversified applications of large language models in materials discovery. Subsequently, the evolution of autonomous experimentation platforms empowered by large language models is analyzed. Finally, four key future research interests are proposed to develop embodied large models for driving autonomous experimentation ...
Zhen Song, Yishuai Cai, Yadong Yu, Pan Xiang, Minglong Li, Zhe Liu, Mengyan Dai   +6 more
wiley   +1 more source

Generative models of cell dynamics: from Neural ODEs to flow matching. [PDF]

Commun Biol
Richter T, Wang W, Palma A, Theis FJ.
europepmc   +1 more source