Results 91 to 100 of about 121,408 (279)
ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang +10 more
wiley +1 more source
ABSTRACT Objective To explore how cerebral hypoxia and Normal‐Appearing White Matter (NAWM) integrity affect MS lesion burden and clinical course. Methods Seventy‐nine MS patients, including 13 clinically isolated syndrome (CIS) patients and 66 relapsing–remitting multiple sclerosis (RRMS) patients, and 44 healthy controls (HCs) were recruited from ...
Xinli Wang +8 more
wiley +1 more source
The Maximum Order of Adjacency Matrices With a Given Rank [PDF]
AMS Subject Classification: 05B20, 05C50.Graph;Adjacency ...
Haemers, W.H., Peeters, M.J.P.
core +1 more source
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 +6 more
wiley +1 more source
γ-Inverse graph of some mixed graphs
Let GG be a graph. Then, the inverse graph G−1{G}^{-1} of GG is defined to be a graph that has adjacency matrix similar to the inverse of the adjacency matrix of GG, where the similarity matrix is ±1\pm 1 diagonal matrix. In this article, we introduced a
Boulahmar Wafa +2 more
doaj +1 more source
The adjacency spectrum of two new operations of graphs
Let be a graph and be its adjacency matrix. The eigenvalues of are the eigenvalues of and form the adjacency spectrum, denoted by . In this paper, we introduce two new operations and , and describe the adjacency spectra of and of regular graphs , and ...
Dijian Wang, Yaoping Hou, Zikai Tang
doaj +1 more source
Enhanced Adjacency Matrix-Based Lightweight Graph Convolution Network for Action Recognition. [PDF]
Zhang D, Deng H, Zhi Y.
europepmc +1 more source
Evaluating adjacency matrix for network visualization
Adjacency Matrix (AM) is one of the commonly used techniques to visualize networks. While an AM provides a clean and compact representation for dense networks, several studies have shown that it is not suitable for path-related tasks. Several visualization techniques have been proposed to address this limitation.
openaire +2 more sources
ABSTRACT Background Central nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin‐4 antibody–positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody–associated disease (MOGAD), occasionally overlap.
Bade Gulec +6 more
wiley +1 more source
Dynamic Correlation Adjacency-Matrix-Based Graph Neural Networks for Traffic Flow Prediction. [PDF]
Gu J, Jia Z, Cai T, Song X, Mahmood A.
europepmc +1 more source

