Results 11 to 20 of about 7,875 (197)

Aα-Spectral Characterizations of Some Joins

open access: yesJournal of Mathematics, 2020
Let G be a graph with n vertices. For every real α∈0,1, write AαG for the matrix AαG=αDG+1−αAG, where AG and DG denote the adjacency matrix and the degree matrix of G, respectively.
Tingzeng Wu, Tian Zhou
doaj   +1 more source

On the Aα-Eigenvalues of Signed Graphs

open access: yesMathematics, 2021
For α∈[0,1], let Aα(Gσ)=αD(G)+(1−α)A(Gσ), where G is a simple undirected graph, D(G) is the diagonal matrix of its vertex degrees and A(Gσ) is the adjacency matrix of the signed graph Gσ whose underlying graph is G.
Germain Pastén, Oscar Rojo, Luis Medina
doaj   +1 more source

Graphs Whose Aα -Spectral Radius Does Not Exceed 2

open access: yesDiscussiones Mathematicae Graph Theory, 2020
Let A(G) and D(G) be the adjacency matrix and the degree matrix of a graph G, respectively. For any real α ∈ [0, 1], we consider Aα (G) = αD(G) + (1 − α)A(G) as a graph matrix, whose largest eigenvalue is called the Aα -spectral radius of G.
Wang Jian Feng   +3 more
doaj   +1 more source

Directed random geometric graphs: structural and spectral properties

open access: yesJournal of Physics: Complexity, 2022
In this work we analyze structural and spectral properties of a model of directed random geometric graphs: given n vertices uniformly and independently distributed on the unit square, a directed edge is set between two vertices if their distance is ...
Kevin Peralta-Martinez   +1 more
doaj   +1 more source

On the Aα-Spectral Radii of Cactus Graphs

open access: yesMathematics, 2020
Let A ( G ) be the adjacent matrix and D ( G ) the diagonal matrix of the degrees of a graph G, respectively. For 0 ≤ α ≤ 1 , the A α -matrix is the general adjacency and signless Laplacian spectral matrix having the form of
Chunxiang Wang   +3 more
doaj   +1 more source

Graphs with Clusters Perturbed by Regular Graphs—Aα-Spectrum and Applications

open access: yesDiscussiones Mathematicae Graph Theory, 2020
Given a graph G, its adjacency matrix A(G) and its diagonal matrix of vertex degrees D(G), consider the matrix Aα (G) = αD(G) + (1 − α)A(G), where α ∈ [0, 1).
Cardoso Domingos M.   +2 more
doaj   +1 more source

图的Aα-特征多项式系数的一个注记(A note on the coefficients of the Aα-characteristic polynomial of a graph)

open access: yesZhejiang Daxue xuebao. Lixue ban, 2019
Let G be a graph on n vertices, and let A( G ) and D ( G ) denote the adjacency matrix and the degree matrix of G, respectively. Define Aα ( G )= αD ( G )+( 1 - α ) A( G ) for any real α ∈ [ 0,1 ].
LIUShunyi,(柳顺义)   +1 more
doaj   +1 more source

On the Number of α-Labeled Graphs

open access: yesDiscussiones Mathematicae Graph Theory, 2018
When a graceful labeling of a bipartite graph places the smaller labels in one of the stable sets of the graph, it becomes an α-labeling. This is the most restrictive type of difference-vertex labeling and it is located at the very core of this research ...
Barrientos Christian, Minion Sarah
doaj   +1 more source

Perturbation of the α-spectral radius of complete multipartite graphs

open access: yes上海师范大学学报. 自然科学版
Let G be a graph and α∈[0, 1), Nikiforov merged the adjacency matrix and the signless Laplacian matrix to Aα(G)=αD(G)+(1-α)A(G), where D(G), A(G) are the degree diagonal matrix and the adjacency matrix of G, respectively.
WU Yuhao   +3 more
doaj   +1 more source

Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation

open access: yesFEBS Letters, EarlyView.
Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang   +2 more
wiley   +1 more source

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