Results 171 to 180 of about 13,074 (347)
Social Media and Online Brand Communities [PDF]
Madina Ansarin, Wilson Ozuem
openalex +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
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
Branding co-creation with members of online brand communities [PDF]
This article looks at the co-creation of value in the branding process with members of online communities. Three online communities in Iran are analyzed through 45 interviews with members along with three interviews with top managers of the three brands ...
Richard M +4 more
core
Emotionally Structured Interaction Networks and Consumer Perception of New Energy Vehicle Technology: A Behavioral Network Analysis of Online Brand Communities. [PDF]
Xu J, Liu C, Lu L.
europepmc +1 more source
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source
A multi-platform analysis of e-cigarette online marketing in China (2024-2025). [PDF]
Liu R +6 more
europepmc +1 more source
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
Research on the influencing factors and mechanism of AR e-commerce consumers' purchase intention. [PDF]
Zhang X, Yang P, Guo C, He P.
europepmc +1 more source
Analyzing Social Brand Communities VS. Online Brand Communities
null 김주란, null 이기훈
openaire +1 more source

