Results 101 to 110 of about 84,208 (297)

Innate Immune Reprogramming Mediated by Endogenous Retroelement Dysregulation Drives Multiple Sclerosis Progression

Annals of Clinical and Translational Neurology, EarlyView.
Epigenetic reprogramming in hematopoietic stem and progenitor cells (HSPCs) and downstream myeloid cells, mediated by H3.3 downregulation and endogenous retroelement (ERE) overexpression, contributes to the progression of multiple sclerosis (MS). ABSTRACT Background Skewed myelopoiesis in the bone marrow has been identified as a key driver of multiple ...
Li‐Mei Xiao, Qiu‐Ping Zhao, Run‐Yun Li, Wei Chen, Huan‐Huan Song, Wan‐Jin Chen, Ying Fu   +6 more
wiley   +1 more source

Attention Graph Convolution Network for Image Segmentation in Big SAR Imagery Data

Remote Sensing, 2019
The recent emergence of high-resolution Synthetic Aperture Radar (SAR) images leads to massive amounts of data. In order to segment these big remotely sensed data in an acceptable time frame, more and more segmentation algorithms based on deep learning ...
Fei Ma, Fei Gao, Jinping Sun, Huiyu Zhou, Amir Hussain   +4 more
doaj   +1 more source

A Depolarizing Leak in Sodium Bicarbonate Cotransporter NBCe1 Causes Brain Edema

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives SLC4A4 encodes electrogenic sodium bicarbonate cotransporter NBCe1, prominently expressed in kidney and brain. Recessive loss‐of‐function variants in SLC4A4 cause proximal renal tubular acidosis, no brain edema. In the brain, NBCe1 is expressed by astrocytes, where it regulates pH and mediates astrocyte volume changes.
Quinty Bisseling, Mark D. Parker, Sven Kerst, Richard A. Pasternack, Jacob Tondreau, Marjolein Breur, Gemma M. van Rooijen‐van Leeuwen, Davide Tonduti, Ettore Salsano, Alejandra Darling, Joanna A. E. van Wijk, Susanna Törnroth‐Horsefield, Marianna Bugiani, Petra J. W. Pouwels, Quinten Waisfisz, Marjo S. van der Knaap, Rogier Min   +16 more
wiley   +1 more source

Text Summarization With Graph Attention Networks

CoRR
This study aimed to leverage graph information, particularly Rhetorical Structure Theory (RST) and Co-reference (Coref) graphs, to enhance the performance of our baseline summarization models. Specifically, we experimented with a Graph Attention Network architecture to incorporate graph information.
Mohammadreza Ardestani, Yllias Chali
openaire   +3 more sources

MEGAN: Multi-explanation Graph Attention Network

, 2023
We propose a multi-explanation graph attention network (MEGAN). Unlike existing graph explainability methods, our network can produce node and edge attributional explanations along multiple channels, the number of which is independent of task specifications.
Jonas Teufel, Luca Torresi, Patrick Reiser, Pascal Friederich   +3 more
openaire   +4 more sources

Accelerating Transistor Simulations With Self-Supervised Graph Attention Networks

IEEE Access
Technology CAD (TCAD) tools are pivotal for transistor modeling, enabling physics-based simulations with high accuracy essential for developing next-generation technology nodes. However, their high computational cost and low throughput severely constrain
Tarek Mohamed, Hussam Amrouch
doaj   +1 more source

Advancing Force Fields Parameterization: A Directed Graph Attention Networks Approach

Force Fields (FFs) are an established tool for simulating large and complex molecular systems. However, parametrizing FFs is a challenging and time-consuming task that relies on empirical heuristics, experimental data, and computational data.
Jean-Philip, Piquemal, Louis, Lagardère, Théo, Jaffrelot Inizan, Gong, Chen, Thomas, Plé, Yvon, Maday   +5 more
core   +1 more source

Adaptive Partitioning for Large-Scale Dynamic Graphs [PDF]

, 2013
—In the last years, large-scale graph processing has gained increasing attention, with most recent systems placing particular emphasis on latency. One possible technique to improve runtime performance in a distributed graph processing system is to reduce
Martella, Claudio, Martella, C, Dionysios Logothetis, Cuadrado, Félix, Logothetis, Dionysios, Felix Cuadrado, Cuadrado, F, Vaquero, Luis M., Logothetis, D, Luis Vaquero, Luis M. Vaquero, Claudio Martella, Vaquero, LM, IEEE   +13 more
core   +1 more source

Effectiveness of rTMS on Working Memory and Inhibitory Impairments in Patients With Post‐Stroke Executive Deficits

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Considerable efforts have been dedicated to developing effective treatments for post‐stroke executive impairment (PSEI), among which repetitive transcranial magnetic stimulation (rTMS) has shown great potential. This study aimed to investigate the therapeutic effects of high‐frequency rTMS on working memory (WM) and response ...
Mengting Lao, Rongwei Du, Zhujun Wang, Yang Gao, Meiling Cheng, Xianglong Wang, Wen Wu   +6 more
wiley   +1 more source

Graph Neural Networks With Lifting-Based Adaptive Graph Wavelets

Spectral-based graph neural networks (SGNNs) have been attracting increasing attention in graph representation learning. However, existing SGNNs are limited in implementing graph filters with rigid transforms and cannot adapt to signals residing on ...
Zou, Junni, Xu, Mingxing, Xiong, Hongkai, Dai, Wenrui, Frossard, Pascal, Li, Chenglin   +5 more
core   +1 more source