Results 121 to 130 of about 7,114 (212)
Fan communities are a socio-political resource capable of mobilizing public initiatives and movements, especially on the regional scale. Research interest in sports fan communities is steadily growing because the fan movement has established itself as a ...
Evgeny V. Golovatsky, Pavel B. Gvozdilov
doaj +1 more source
ABSTRACT Strategic positioning becomes increasingly important as markets mature, particularly in consumer‐facing industries that offer similar products, experiential cues, and values‐based messages. This study offers a conceptual model to examine the strategic positioning factors that motivate consumers to visit one local business over another before ...
Aaron J. Staples +2 more
wiley +1 more source
In this multicenter prospective study of 158 working‐age patients undergoing curative‐intent surgery for gastric or esophageal cancer, 78.5% were working at 18 months. Postoperative appetite loss, financial difficulties, and ≥ 10% weight loss at 6 months were associated with non‐working status.
Kentaro Goto +18 more
wiley +1 more source
GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs
Abstract Piping and Instrumentation Diagrams (P&IDs) are central to process engineering workflows, yet extracting information from them remains a tedious and time‐consuming task. This work introduces ChatP&ID, a framework enabling natural‐language interaction with smart P&IDs through Graph Retrieval‐Augmented Generation (GraphRAG), to our knowledge ...
Achmad Anggawirya Alimin +1 more
wiley +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 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
Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
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
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
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 +3 more
wiley +1 more source

