Results 101 to 110 of about 288,863 (259)

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Resilience and online learning emotional engagement among college students in the digital age: a perspective based on self-regulated learning theory

BMC Psychology
Background Self-efficacy perception and strategy use are two key processes for achieving self-regulated learning. Based on the perspective of self-regulated learning theory, this study explores the mediating mechanism of self-regulated learning efficacy,
Dandan Ge
doaj   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Conceptualising quality early childhood education: Learning from young children in Brazil and South Africa through creative and play‐based methods

British Educational Research Journal, EarlyView., 2023
Abstract Early childhood has increasingly been acknowledged as a vital time for all children. Inclusive and quality education is part of the United Nations Sustainable Development Goals, with the further specification that all children have access to quality pre‐primary education.
Laura H. V. Wright, Irene Rizzini, Malibongwe Gwele, Lynn McNair, Cristina Laclette Porto, Marsha Orgill, E. Kay M. Tisdall, Malcolm Bush, Linda Biersteker   +8 more
wiley   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Evaluating Three Foundation Potentials for Predicting Selected Properties of the Co–Ni–Ru Alloy System

Advanced Intelligent Discovery, EarlyView.
Distributions of intrinsic stacking fault energies (ISFE) among different slip planes in the face‐centered cubic Co2Ni2Ru alloy, predicted by three foundation potentials (DPA, Orb, and SevenNet) and density functional theory (DFT) calculations. This study evaluates the efficacy of three foundation potentials (FPs)—SevenNet, DPA, and Orb—in predicting ...
Subah Mubassira, Thu Nguyen, Anvesh Nathani, Shoutian Sun, Ming Hu, Yanqing Su, Bin Wang, Iman Ghamarian, Shuozhi Xu   +8 more
wiley   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Design, Control, and Clinical Applications of Magnetic Actuation Systems: Challenges and Opportunities

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo, Lidong Yang, Tiantian Xu, Dong Sun   +3 more
wiley   +1 more source

The effect of teacher self-efficacy, online pedagogical and content knowledge, and emotion regulation on teacher digital burnout: a mediation model

BMC Psychology
Background With the increasing prevalence of online teaching, understanding the dynamics that impact educators' well-being and effectiveness is paramount.
Xianbi Yang, Juan Du
doaj   +1 more source