Complex earthquake networks: hierarchical organization and assortative mixing.

Phys Rev E Stat Nonlin Soft Matter Phys

Institute of Physics, University of Tsukuba, Ibaraki 305-8571, Japan.

Published: August 2006


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

To characterize the dynamical features of seismicity as a complex phenomenon, the seismic data are mapped to a growing random graph, which is a small-world scale-free network. Here, hierarchical and mixing properties of such a network are studied. The clustering coefficient is found to exhibit asymptotic power-law decay with respect to connectivity, showing hierarchical organization. This structure is supported by not only main shocks but also small shocks, and may have its origin in the combined effect of vertex fitness and deactivation by stress release at faults. The nearest-neighbor average connectivity and the Pearson correlation coefficient are also calculated. It is found that the earthquake network has assortative mixing. This is a main difference of the earthquake network from the Internet with disassortative mixing. Physical implications of these results are discussed.

Download full-text PDF

Source
http://dx.doi.org/10.1103/PhysRevE.74.026113DOI Listing

Publication Analysis

Top Keywords

hierarchical organization
8
assortative mixing
8
earthquake network
8
complex earthquake
4
earthquake networks
4
networks hierarchical
4
organization assortative
4
mixing
4
mixing characterize
4
characterize dynamical
4

Similar Publications

The ESCRT machinery mediates membrane remodeling in fundamental cellular processes including cytokinesis, endosomal sorting, nuclear envelope reformation, and membrane repair. Membrane constriction and scission is driven by the filament-forming ESCRT-III complex and the AAA-ATPase VPS4. While ESCRT-III-driven membrane scission is generally established, the mechanisms governing the assembly and coordination of its twelve mammalian isoforms in cells remain poorly understood.

View Article and Find Full Text PDF

Background And Objectives: Older adults living with dementia are a heterogeneous group, which can make studying optimal medication management challenging. Unsupervised machine learning is a group of computing methods that rely on unlabeled data-that is, where the algorithm itself is discovering patterns without the need for researchers to label the data with a known outcome. These methods may help us to better understand complex prescribing patterns in this population.

View Article and Find Full Text PDF

The global prevalence of mental health disorders among youths aged 15 to 24 is a significant public health concern. This systematic review aimed to explore global strategies for promoting mental well-being and addressing mental health challenges within this demographic, as defined by the World Health Organization. A comprehensive search of electronic scientific databases was conducted on November 1, 2023, yielding 43 studies with a total of 29,581 participants published between 2008 and 2023 that examined mental health interventions targeting youth.

View Article and Find Full Text PDF

Background: Passenger rail drivers' physical behaviors contribute to individual, organizational and community risks. As work tasks are theorized to determine physical behaviors performed during work hours, there is a need to clarify how work tasks determine passenger rail drivers' physical behaviors to inform improved work design.

Aims: The aim of this study was to describe the physical behaviors of passenger train drivers across their work tasks and breaks, and explore what potential influences create variations in physical behaviors within tasks.

View Article and Find Full Text PDF

Defining breast epithelial cell types in the single-cell era.

Dev Cell

September 2025

Department of Pharmacology, University of Cambridge, Cambridge, UK; Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK. Electronic address:

Single-cell studies on breast tissue have contributed to a change in our understanding of breast epithelial diversity that has, in turn, precipitated a lack of consensus on breast cell types. The confusion surrounding this issue highlights a possible challenge for advancing breast atlas efforts. In this perspective, we present our consensus on the identities, properties, and naming conventions for breast epithelial cell types and propose goals for future atlas endeavors.

View Article and Find Full Text PDF