Results 81 to 90 of about 34,792 (262)
Arthritis Care &Research, EarlyView.Objective Orofacial manifestations are significantly impactful in patients with systemic sclerosis (SSc) yet remain understudied, with no dedicated clinical guidelines to inform their management. Methods An international online survey comprised38 questions addressing orofacial manifestations of SSc, including patients’ confidence in their treating ...
Eleni Deligianni +4 more
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What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Knowledge Graph Completion Algorithm with Multi-view Contrastive Learning [PDF]
Jisuanji kexue yu tansuoKnowledge graph completion is a process of reasoning new triples based on existing entities and relations in knowledge graph. The existing methods usually use the encoder-decoder framework.
QIAO Zifeng, QIN Hongchao, HU Jingjing, LI Ronghua, WANG Guoren
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Advanced Engineering Materials, EarlyView.In this review, the current state of light‐assisted 3D printing as it pertains to engineering musculoskeletal tissues including bone, cartilage, skeletal muscle, tendon, and ligaments is summarized. Common printing techniques, photoreactive materials, and study design choices are compiled and reviewed.
Meagan Morgan, Bin Zhang, Roger Narayan
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IEEE AccessThe completeness of knowledge graphs is critical to their effectiveness across various applications. However, existing knowledge graph completion methods face challenges such as difficulty in adapting to new entity information, parameter explosion, and ...
Ying Zhang +3 more
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Knowledge Graph Completion Method Fusing Entity Descriptions and Topological Structure [PDF]
Jisuanji kexueKnowledge graph completion aims to predict missing entities and relationships in given triplets to enhance the completeness and quality of the knowledge graph.Existing knowledge graph completion methods typically only consider the structural information ...
HAN Daojun, LI Yunsong, ZHANG Juntao, WANG Zemin
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Advanced Engineering Materials, EarlyView.This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
Few-Shot Knowledge Graph Completion Based on Selective Attention [PDF]
Jisuanji kexue yu tansuoMost few-shot knowledge graph completion models have some problems, such as low ability to learn relation representation and rarely attaching importance to the relative location and interaction between query entity pair when the relation between entities
LIN Sui, LU Chaohai, JIANG Wenchao, LIN Xiaoshan, ZHOU Weilin
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Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
A Brief Survey on Deep Learning-Based Temporal Knowledge Graph Completion
Applied SciencesTemporal knowledge graph completion (TKGC) is the task of inferring missing facts based on existing ones in a temporal knowledge graph. In recent years, various TKGC methods have emerged, among which deep learning-based methods have achieved state-of-the-
Ningning Jia, Cuiyou Yao
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