Results 51 to 60 of about 8,049,750 (250)

Evaluating the effect of γ‐oryzanol on MASLD pathology using a medaka fish model

FEBS Open Bio, EarlyView.
This study explores a liver disease called MASLD, which is increasing worldwide and can lead to serious damage. Researchers used medaka fish instead of rodents to test a food compound, γ‐oryzanol. Fish fed this compound had less liver fat and healthier gut bacteria.
Yukako Ito, Haduki Asano, Ayano Ueki, Joe Sakamoto, Yasuhiro Kamei, Hayato Tokumoto, Ayaka Yazawa, Shigeki Kamitani   +7 more
wiley   +1 more source

Design and evaluation of FEBS Education and Training Academy module – Integrating generative artificial intelligence into life‐science education

FEBS Open Bio, EarlyView.
Life‐science educators from 14 countries redesigned their own course materials with generative AI in a three‐session, pedagogy‐first FEBS Education and Training Academy workshop built on PICRAT. Among 12 matched respondents, four more reported high confidence in each of five practical domains, and 10 of 13 reported implementing at least one idea ...
Zvonimir Mlinarić, Ali Burak Özkaya
wiley   +1 more source

Understanding the Burden of Orofacial Involvement and Patient Treatment Preferences in Systemic Sclerosis: Results From a Large International Survey

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, Lee Shapiro, Deana Gibbs, Zsuzsanna H. McMahan, Michael Hughes   +4 more
wiley   +1 more source

Knowledge Graph Embedding for Hyper-Relational Data

Tsinghua Science and Technology, 2017
Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper, we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs.
Chunhong Zhang, Miao Zhou, Xiao Han, Zheng Hu, Yang Ji   +4 more
doaj   +1 more source

Rule-based data augmentation for knowledge graph embedding

AI Open, 2021
Knowledge graph (KG) embedding models suffer from the incompleteness issue of observed facts. Different from existing solutions that incorporate additional information or employ expressive and complex embedding techniques, we propose to augment KGs by ...
Guangyao Li, Zequn Sun, Lei Qian, Qiang Guo, Wei Hu   +4 more
doaj   +1 more source

Mapping the Social Network Structure and Composition of Black Individuals With Rheumatic and Musculoskeletal Conditions

Arthritis Care &Research, EarlyView.
Objective Our objective was to describe the social networks of Black individuals with rheumatic and musculoskeletal conditions and understand the clustering of health‐related behaviors to inform future community‐based, peer‐led interventions. Methods We used an adapted Personal Network Survey for Clinical Research (PERSNET) to map the personal social ...
Taussia Boadi, Amar Dhand, Leah Santacroce, Neil Pillai, Komel Safdar, Mia T. Chandler, Ariel Childs, Monica Crespo‐Bosque, Gina Curry, Mary Dollear, Alice Eggleston, Daniel Erickson, Dieufort Fleurissaint, Denice Garrett, Gail Granville, Tyler Green, Magdalena Hamielec, Elena Losina, Karen Mancera‐Cuevas, Mary Ann Nelson, Chisa Nosamiefan, Bisola Ojikutu, Tonya S. Roberson, Mary Beth Son, Marie Jacques Toussaint, Michael York, Rosalind Ramsey‐Goldman, Candace H. Feldman   +27 more
wiley   +1 more source

Using Knowledge Graph Embedding for Fault Detection

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023
Automotive manufacturers are under stressful timelines as they shift their focus from internal combustion engines (ICE) to electric (EV) and hybrid-electric vehicles (HEV).
Ziad Kobti, Joseph El-Ghaname
doaj   +1 more source

Locally Adaptive Translation for Knowledge Graph Embedding

, 2016
Knowledge graph embedding aims to represent entities and relations in a large-scale knowledge graph as elements in a continuous vector space. Existing methods, e.g., TransE and TransH, learn embedding representation by defining a global margin-based loss
Wang, Yuanzhuo, Lin, Hailun, Jin, Xiaolong, Jia, Yantao, Cheng, Xueqi, Hailun Lin, Yantao Jia, Xueqi Cheng, Yuanzhuo Wang, Xiaolong Jin   +9 more
core   +1 more source

Bio‐Inspired Artificial Ionic Mechanoreceptor

Advanced Functional Materials, EarlyView.
A skin‐inspired artificial mechanoreceptor based on ionic interactions is presented for biomimetic tactile sensing. Pressure‐driven ionic redistribution within microfluidic channels generates a self‐powered electrical signal without external bias. The generated waveform exhibits mechanoreceptor‐like temporal features, including overshoot and undershoot,
Mohammad Akbari, Jeppe Don, Lasse A. N. Pedersen, John Noee, Rassoul Tabassian   +4 more
wiley   +1 more source

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source