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Localization behaviors of Laplacian eigenvectors of complex networks furnish an explanation to various dynamical phenomena of the corresponding complex systems. We numerically examine roles of higher-order and pairwise links in driving eigenvector localization of hypergraphs Laplacians. We find that pairwise interactions can engender localization of eigenvectors corresponding to small eigenvalues for some cases, whereas higher-order interactions, even being much much less than the pairwise links, keep steering localization of the eigenvectors corresponding to larger eigenvalues for all the cases considered here. These results will be advantageous to comprehend dynamical phenomena, such as diffusion, and random walks on a range of real-world complex systems having higher-order interactions in better manner.
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http://dx.doi.org/10.1103/PhysRevE.107.034311 | DOI Listing |
Neuroimage Rep
September 2025
Department of Endocrinology, Amsterdam University Medical Centers, location VUMC, Amsterdam, the Netherlands.
People with obesity tend to have altered functional connectivity of reward-related areas in the brain, contributing to overeating and weight gain. The gut-brain axis may function as a mediating factor, with gut-derived short-chain fatty acids (SCFAs) as possible intermediates in the relationship between microbiota and functional connectivity. We investigated the influence of SCFA turnover on resting state functional connectivity in healthy individuals with extremely high and extremely low levels of intestinal SCFA turnover.
View Article and Find Full Text PDFComput Methods Programs Biomed
November 2025
Background: Understanding spinal biomechanics is essential for exploring the functions of the spine and the pathogenesis of related diseases. Traditional numerical methods for biomechanical analysis are computationally expensive, while Physics-Informed Neural Network (PINN) struggles with complex solid geometries. This study develops an Enhanced Physics-Informed Neural Network that integrates Geometric Features (EPINN-GF) to address these limitations in predicting stress distribution for the complex spinal geometries.
View Article and Find Full Text PDFImaging Neurosci (Camb)
August 2024
Institute of Biological and Medical Psychology, University of Bergen, Bergen, Norway.
Music's role in modulating brain structure, particularly in neurodegenerative contexts such as Alzheimer's Disease (AD), has been increasingly recognized. While previous studies have hinted at the potential neuroplastic benefits of musical engagement and training, the mechanisms through which music impacts structural connectivity in neurodegenerative pathways remain underexplored. We aimed to examine the impact of music perception skills, active musical engagement, and musical training on structural connectivity in areas relating to memory, emotion, and learning in individuals with worsening memory impairment, investigating the potential neuroplastic effects of music.
View Article and Find Full Text PDFClinics (Sao Paulo)
July 2025
Instituto do Câncer do Estado de São Paulo (ICESP), Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil; Comprehensive Center for Precision Oncology, Universidade de São Paulo, São Paulo, SP, Brazil.
Objective: In a prospective, randomized phase II study, exploratory data analysis was conducted to evaluate angiogenesis-associated plasma protein levels in patients with locally advanced cervical cancer METHODS: Participants were divided into two groups: Group A received neoadjuvant cisplatin and gemcitabine treatment (NAC) followed by chemoradiation with cisplatin and brachytherapy (CRT), while Group B received only CRT. Plasma samples were collected from patients in Group A at three time points: baseline, after NAC, and after CRT. Group B patients had samples taken at two time points: baseline and after CRT.
View Article and Find Full Text PDFSci Rep
July 2025
College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin, 132000, Jilin, China.
This paper proposes a novel metaheuristic algorithm-the Power Method Algorithm (PMA), which is inspired by the power iteration method to solve complex optimization problems. PMA simulates the process of computing dominant eigenvalues and eigenvectors, incorporating strategies such as stochastic angle generation and adjustment factors, effectively addressing eigenvalue problems in large sparse matrices. The algorithm is rigorously evaluated on 49 benchmark functions from the CEC 2017 and CEC 2022 test suites.
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