Results 31 to 40 of about 16,728 (252)
Swamped with Too Many Articles? GraphRAG Makes Getting Started Easy
Background: Both early researchers, such as new graduate students, and experienced researchers face the challenge of sifting through vast amounts of literature to find their needle in a haystack.
Joëd Ngangmeni, Danda B. Rawat
doaj +1 more source
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling +15 more
wiley +1 more source
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
A dynamically actuated reconfigurable topographical surface (DARTS) integrates contact‐mediated bactericidal nanotopography with programmable mechanical actuation to actively disrupt bacterial biofilms. Dynamic surface reconfiguration enhances bacterial killing and suppresses implant‐associated infections in vivo, providing a new strategy for active ...
Mohammad Asadi Tokmedash +4 more
wiley +1 more source
Dynamic and Parametric Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) has become a foundational paradigm for equipping large language models (LLMs) with external knowledge, playing a critical role in information retrieval and knowledge-intensive applications. However, conventional RAG systems typically adopt a static retrieve-then-generate pipeline and rely on in-context knowledge ...
Weihang Su +4 more
openaire +4 more sources
Implementing Retrieval-Augmented Generation for Academic Libraries
This article details the technical development of a Retrieval-Augmented Generation (RAG) system designed to enhance discovery within an academic library's institutional repository.
Wei Xuan
doaj +1 more source
This study presents a magneto‐mechanical strategy that incorporates FP@MSCs into an aligned PCL/GelMA nerve guidance conduit. Magnetic stimulation increases membrane tension in FP@MSCs, triggering cytoskeletal remodeling, Schwann cell‐like differentiation, and TIMP1 secretion. TIMP1 activates ITGB1/CD63–FAK signaling in NE‐4C cells, increasing membrane
Xinyu Zhu +14 more
wiley +1 more source
Data Imputation Based on Retrieval-Augmented Generation
Modern organizations collect increasing volumes of data to drive decision-making, often stored in centralized repositories such as data lakes, which consist of diverse structured and unstructured datasets.
Xiaojun Shi +4 more
doaj +1 more source
A Survey on Retrieval-Augmented Text Generation
all authors contributed ...
Huayang Li +4 more
openaire +3 more sources
Schematic illustration of the proposed mechanism: PEG/RGD‐PSLs mimic apoptotic cells to engage PS receptors (notably CD300a), transducing an inhibitory signal that suppresses the MyD88/NF‐κB pathway, leading to global anti‐inflammatory and pro‐reparative effects.
Lele Wu +10 more
wiley +1 more source

