Results 171 to 180 of about 11,164 (213)

From diagnostics to prediction: development and validation of a multi-domain power-duration model. [PDF]

Eur J Appl Physiol
Wahl P, Ji S.
europepmc   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

Multi-model forecasting of [Formula: see text] and [Formula: see text] in Abu Dhabi: benefits of correlation-based feature augmentation. [PDF]

Sci Rep
Abuouelezz W, Ali N, Aung Z, Altunaiji A, Shah SB, Alkatheeri M.   +5 more
europepmc   +1 more source

A new drag and lift correlation for spherocylinders from fully resolved Immersed Boundary Method

AIChE Journal, EarlyView.
Abstract Many industrial processes deal with non‐spherical particles, e.g., mineral mining and biomass conversion. It is crucial to understand the particles' hydrodynamics to control and optimize these processes. To extend the current state‐of‐the‐art from arrays of spherical particles to spherocylindrical particles, we performed extensive particle ...
A. H. Huijgen, Y. Sterkenburgh, Y. Tang, N. G. Deen, M. W. Baltussen   +4 more
wiley   +1 more source

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

AIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

EMP: Enhanced Multi-modal Prediction for fashion sales using Fourier Mapping and ERP-based contrastive learning. [PDF]

PLoS One
Park S, Park B, Lee S, Shin S, Kim W.
europepmc   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

Advanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al‐Fahdi, Lingyu Kong, Victor Fung, Ming Hu   +5 more
wiley   +1 more source

Predicting Surfactant Oil-Water Interfacial Tension Using Gated Message-Passing Graph Neural Networks. [PDF]

ACS Omega
Liu S, Cui Y, Wang J, Xu H, Jiang H.
europepmc   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

A machine learning approach to using ultrasound for body composition and nutritional status assessment in newborns: a pilot study protocol. [PDF]

Pilot Feasibility Stud
Ranger BJ, Albert M, Kim JI, Cho H, Hohenberg J, He K, Wei D, Berhane M, Girma T, Estroff J, Bell KA, Park J.   +11 more
europepmc   +1 more source