Results 101 to 110 of about 287,840 (285)

Cumulative Social Disadvantage and Disease Activity in Juvenile Idiopathic Arthritis: A Childhood Arthritis and Rheumatology Research Alliance Registry Study

open access: yesArthritis Care &Research, EarlyView.
Objective Social determinants of health (SDOH) contribute to juvenile idiopathic arthritis (JIA) disparities, but most studies have assessed SDOH independently rather than cumulatively across individual, family, and neighborhood levels. Using a socioecological framework, we investigated the relationship among cumulative social disadvantage ...
William Daniel Soulsby   +448 more
wiley   +1 more source

QLite: Lightweight Knowledge Graph Embedding Framework With Query Processing

open access: yesIEEE Access
A vast number of studies on knowledge graph embedding have been conducted. However, most knowledge graph embedding models have high dimensional embedding vectors.
Chun-Hee Lee, Dong-Oh Kang
doaj   +1 more source

Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai   +2 more
wiley   +1 more source

Neural-based inexact graph de-anonymization

open access: yesHigh-Confidence Computing
Graph de-anonymization is a technique used to reveal connections between entities in anonymized graphs, which is crucial in detecting malicious activities, network analysis, social network analysis, and more.
Guangxi Lu   +5 more
doaj   +1 more source

A Novel Time Constraint-Based Approach for Knowledge Graph Conflict Resolution

open access: yesApplied Sciences, 2019
Knowledge graph conflict resolution is a method to solve the knowledge conflict problem in constructing knowledge graphs. The existing methods ignore the time attributes of facts and the dynamic changes of the relationships between entities in knowledge ...
Yanjun Wang   +7 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

open access: yesAdvanced 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

Network community detection via neural embeddings

open access: yesNature Communications
Recent advances in machine learning research have produced powerful neural graph embedding methods, which learn useful, low-dimensional vector representations of network data. These neural methods for graph embedding excel in graph machine learning tasks
Sadamori Kojaku   +3 more
doaj   +1 more source

Anomalous behavior detection based on optimized graph embedding representation in social networks

open access: yesJournal of King Saud University: Computer and Information Sciences
Anomalous behaviors in social networks can lead to privacy leaks and the spread of false information. In this paper, we propose an anomalous behavior detection method based on optimized graph embedding representation. Specifically, the user behavior logs
Ling Xing   +5 more
doaj   +1 more source

Thermophysical Properties of the Desulphurization Slags With Various CaS and CaO/Al2O3 Ratio

open access: yesAdvanced Engineering Materials, EarlyView.
This article investigates how CaS content and the CaO/Al2O3 ratio influence the thermophysical properties of desulphurization slags. Using experimental measurements and thermodynamic simulations, this study reveals complex effects on viscosity, surface tension, and density, providing new insight into slag structure and phase behavior under ...
Eldar Salpagarov   +4 more
wiley   +1 more source

TorusE: Knowledge Graph Embedding on a Lie Group

open access: yes, 2017
Knowledge graphs are useful for many artificial intelligence (AI) tasks. However, knowledge graphs often have missing facts. To populate the graphs, knowledge graph embedding models have been developed.
Ebisu, Takuma, Ichise, Ryutaro
core   +1 more source

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