Results 51 to 60 of about 230,605 (276)
Statistical Properties of Quantum Graph Spectra
, 2006 A general analytical approach to the statistical description of quantum graph spectra based on the exact periodic orbit expansions of quantum levels is discussed.
Dabaghian, Yu.
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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 +6 more
wiley +1 more source
Clustering graph data: the roadmap to spectral techniques
Discover Artificial IntelligenceGraph data models enable efficient storage, visualization, and analysis of highly interlinked data, by providing the benefits of horizontal scalability and high query performance.
Rahul Mondal +5 more
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Arthritis Care &Research, Accepted Article.Objective Knee osteoarthritis (OA) commonly affects individuals with Type 2 diabetes (T2DM) and is associated with increased risk of diabetes‐related complications. To better understand potential mechanisms, we examined the association between symptomatic knee OA and glycemic control in individuals with T2DM.
Lauren K. King +10 more
wiley +1 more source
Lattice fermions as spectral graphs
Journal of High Energy Physics, 2022 We study lattice fermions from the viewpoint of spectral graph theory (SGT). We find that a fermion defined on a certain lattice is identified as a spectral graph. SGT helps us investigate the number of zero eigenvalues of lattice Dirac operators even on
Jun Yumoto, Tatsuhiro Misumi
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Hyperspectral Image Classification with Localized Graph Convolutional Filtering
Remote Sensing, 2021 The nascent graph representation learning has shown superiority for resolving graph data. Compared to conventional convolutional neural networks, graph-based deep learning has the advantages of illustrating class boundaries and modeling feature ...
Shengliang Pu +3 more
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Source localization on graphs via ℓ1 recovery and spectral graph theory [PDF]
2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2016 We cast the problem of source localization on graphs as the simultaneous problem of sparse recovery and diffusion kernel learning. An l1 regularization term enforces the sparsity constraint while we recover the sources of diffusion from a single snapshot of the diffusion process.
Pena, Rodrigo +2 more
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Universal spectral statistics in quantum graphs
, 2004 We prove that the spectrum of an individual chaotic quantum graph shows universal spectral correlations, as predicted by random--matrix theory. The stability of these correlations with regard to non--universal corrections is analyzed in terms of the ...
Alexander Altland +4 more
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Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials
Advanced Engineering Materials, EarlyView.Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai +2 more
wiley +1 more source
A novel algebraic technique for adjacency matrices of some derived graphs
Mathematical and Computer Modelling of Dynamical SystemsGraph energy has been the main concern of spectral graph theory in the last five decades. The classical graph energy is the sum of the absolute values of the eigenvalues of the adjacency matrix. In many research papers, different versions of graph energy
Hacer Ozden Ayna +5 more
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