Results 151 to 160 of about 1,903,201 (339)

Graph Neural Network for Metal Organic Framework Potential Energy Approximation

, 2020
Shehtab Zaman, Christopher Owen, Kenneth Chiu, Michael J. Lawler   +3 more
openalex   +2 more sources

Customizable Fabrication of 2D and Conformal Multielectrode Arrays for 3D Printed Organotypic Bioelectronic Interfaces

Advanced Healthcare Materials, EarlyView.
Aerosol jet printing enables rapid, customizable fabrication of flexible, fully gold multi‐electrode arrays (MEAs) for organotypic bioelectronic interfaces. The printed MEAs exhibit stable electrochemical performance, cytocompatibility, and functionality in recording and stimulation, including integration with 3D‐printed constructs.
Ernest Cheah, Xinchao Gao, Wei Qi Jaw, Guo Liang Goh, Jia Min Lee, Chongquan Huang, Sing Yian Chew, Wai Yee Yeong   +7 more
wiley   +1 more source

A binary-domain recurrent-like architecture-based dynamic graph neural network

Autonomous Intelligent Systems
The integration of Dynamic Graph Neural Networks (DGNNs) with Smart Manufacturing is crucial as it enables real-time, adaptive analysis of complex data, leading to enhanced predictive accuracy and operational efficiency in industrial environments.
Zi-chao Chen, Sui Lin
doaj   +1 more source

Smart Catheters for Diagnosis, Monitoring, and Therapy

Advanced Healthcare Materials, EarlyView.
This study presents a comprehensive review of smart catheters, an emerging class of medical devices that integrate embedded sensors, robotics, and communication systems, offering increased functionality and complexity to enable real‐time health monitoring, diagnostics, and treatment. Abstract This review explores smart catheters as an emerging class of
Azra Yaprak Tarman, Samiha Ahmed, Majed Othman Althumayri, Megan Guy, Darlenne Chavez Lugo, Frances S. Ligler, George T. Ligler, Rahmi Oklu, Hiroshi Kawahira, Michael J. McShane, Jun Kameoka, Jonathan Bova, Hatice Ceylan Koydemir   +12 more
wiley   +1 more source

Rethinking graph data placement for graph neural network training on multiple GPUs [PDF]

, 2022
Shihui Song, Peng Jiang
openalex   +1 more source

Redefining Therapies for Drug‐Resistant Tuberculosis: Synergistic Effects of Antimicrobial Peptides, Nanotechnology, and Computational Design

Advanced Healthcare Materials, EarlyView.
Antimicrobial peptide (AMP)‐loaded nanocarriers provide a multifunctional strategy to combat drug‐resistant Mycobacterium tuberculosis. By enhancing intracellular delivery, bypassing efflux pumps, and disrupting bacterial membranes, this platform restores phagolysosome fusion and macrophage function.
Christian S. Carnero Canales, Jessica Ingrid Marquez Cazorla, Renzo Marianito Marquez Cazorla, Aline Martins dos Santos, Jonatas Lobato Duarte, Letícia Oliveira Catarin Nunes, Túlio Custódio Reis, Lara Cerazi Salvador, Norival Alves Santos‐Filho, Rafael Miguel Sábio, Hélder A. Santos, Fernando Rogério Pavan   +11 more
wiley   +1 more source

Thermodynamics-Informed Graph Neural Networks

IEEE Transactions on Artificial Intelligence
In this paper we present a deep learning method to predict the temporal evolution of dissipative dynamic systems. We propose using both geometric and thermodynamic inductive biases to improve accuracy and generalization of the resulting integration scheme. The first is achieved with Graph Neural Networks, which induces a non-Euclidean geometrical prior
Quercus Hernández, Alberto Badías, Francisco Chinesta, Elías Cueto   +3 more
openaire   +2 more sources

Self‐Assembling Peptide Hydrogels Support Stromal Vascular Fraction Viability to Promote In Vivo Nerve Regeneration

Advanced Healthcare Materials, EarlyView.
Stromal vascular fraction (SVF) may enhance nerve repair, especially when delivered in a self‐assembling peptide hydrogel (SAPH). In vitro, softer SAPH increased neuronal explant outgrowth and supported greater SVF viability and proliferation. In a rat sciatic defect, SVF in an optimized SAPH produced motor and sensory recovery equivalent to autograft ...
Liam A. McMorrow, Steffan Llewellyn, Jared McSweeney, Alessandro Faroni, Aline F. Miller, Alberto Saiani, Adam J. Reid   +6 more
wiley   +1 more source

Getting NBA Shots in Context: Analysing Basketball Shots with Graph Embeddings

International Journal of Computer Science in Sport
Evaluating the quality of shots in basketball is crucial and requires considering the context in which they are taken. We introduce a graph neural network to process a graph based on player and ball tracking data to compute expected shot quality.
Schmid Marc, Schöpf Moritz, Kolbinger Otto   +2 more
doaj   +1 more source

Development of a scoring model for the Sharp/van der Heijde score using convolutional neural networks and its clinical application in predicting radiographic progression using a graph convolutional network [PDF]

, 2022
Suguru Honda, Koichiro Yano, Eiichi Tanaka, Katsunori Ikari, Masayoshi Harigai   +4 more
openalex   +1 more source