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Gaining Deeper Insights into Thin Profile Donors via Attributed Graph Contrastive Learning

Jiyeon Hong, Qing Liu, Wenjun Zhou
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<i>Cistanche deserticola</i>-derived exosome-like nanovesicles target the Microbiota-GABA signaling axis to ameliorate loperamide-induced constipation. [PDF]

Front Pharmacol
Zhang X, Yan K, Bao X, Yang D, Chen X, Xiao W, Zhou J, Cai Y, Wang H, Sun G, Lin A.   +10 more
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Simulation of personalized english learning path recommendation system based on knowledge graph and deep reinforcement learning. [PDF]

Sci Rep
Zhou LY, Wang YY.
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Design and performance of two stages square cut rectangular multiband microstrip fractal antenna. [PDF]

MethodsX
Kadam S, Desai KR, Kadam P, Pawar AP, Pawar S, Nigade PA.   +5 more
europepmc   +1 more source

Causal insights into gestational diabetes mellitus. [PDF]

Front Endocrinol (Lausanne)
Zahoor S, Constantinou AC, O'Halloran F, O'Mahony L, O'Riordan M, Kgosidialwa O, Culliney L, Said Alhajri M, Hasanuzzaman M.   +8 more
europepmc   +1 more source

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Relation between the inertia indices of a complex unit gain graph and those of its underlying graph

Linear and multilinear algebra, 2020
A -gain graph is a triple consisting of an underlying graph , the circle group and a gain function , such that . In this paper, we focus our attention on the relations between the inertia indices of -gain graph Φ and the inertia indices of its underlying
Shahid Zaman, Xiaocong He
semanticscholar   +1 more source

On the relation between the adjacency rank of a complex unit gain graph and the matching number of its underlying graph

Linear and multilinear algebra, 2020
Let be an n-vertex complex unit gain graph and let G be its underlying graph. The adjacency rank of , written as , is the rank of its adjacency matrix and denote by the matching number of the underlying graph G.
Shuchao Li, Ting Yang
semanticscholar   +1 more source

Graph Neural Networks: Foundation, Frontiers and Applications

Knowledge Discovery and Data Mining, 2022
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the recent years. Graph neural networks, also known as deep learning on graphs, graph representation learning, or geometric deep learning, have become one of the fastest-
Lingfei Wu, P. Cui, Jian Pei, Liang Zhao, Xiaojie Guo   +4 more
semanticscholar   +1 more source

Decentralized Circular Formation Control of Nonholonomic Mobile Robots Under a Directed Sensor Graph

IEEE Transactions on Automatic Control, 2023
This article investigates the circular formation control problem of multiple unicycle-type mobile robots under a directed sensor graph. The topology of the sensor graph among all robots is described by a directed graph containing a spanning tree, and the
Xiao Yu, R. Su
semanticscholar   +1 more source