Results 141 to 150 of about 175,760 (266)

The Dropout

Journal of American History, 2022
openaire   +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

The Role of Parental Monitoring in the Relationships Among Academic Motivation, School Engagement, and Dropout Intention: A Two-Wave Study of Italian Adolescents. [PDF]

Behav Sci (Basel)
Affuso G, Picone N, Pace U, Pannone M, Zannone A, Alù AGM, Troncone A, Caldarelli G, Cella S, Abronzino D, Vozza A, Angelini S, De Matteis A, Murgia S, Vicale M, Passanisi A, Di Martino L, Bacchini D.   +17 more
europepmc   +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

Effect of Meibomian Gland Expression on Meibomian Gland Regeneration and Function: A Randomized Controlled Trial. [PDF]

Clin Ophthalmol
Le NVA, Chotikkakamthorn P, Kasetsuwan N, Luu H, Reinprayoon U.   +4 more
europepmc   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

A statistical physics framework for optimal learning. [PDF]

PNAS Nexus
Mignacco F, Mori F.
europepmc   +1 more source

Data‐Driven High‐Throughput Volume Fraction Estimation From X‐Ray Diffraction Patterns

Advanced Intelligent Discovery, EarlyView.
Long exposure times and the need for manual evaluation limit the use of X‐ray diffraction in high‐throughput applications. This study presents a data‐driven approach addressing both issues. HiVE (a method for High‐throughput Volume fraction Estimation) performs composition estimation for high‐noise XRD patterns produced using polychromatic emission ...
Hawo H. Höfer, André Orth, Robert Wang, Ben Breitung, Simon Schweidler, Jasmin Aghassi‐Hagmann, Markus Reischl   +6 more
wiley   +1 more source

Factors Associated with Dropout Intention in Engineering Education: A Learning Interpretable Modeling Approach. [PDF]

Behav Sci (Basel)
Pedraja-Rejas L, Ocaranza N, Ocaranza Paz P, Perez L.   +3 more
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced 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