Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Effect of aging on network structure.

Han Zhu1, Xinran Wang, Jian-Yang Zhu

  • 1Department of Physics, Nanjing University, Nanjing 210093, China.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 20, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

DAQplugin: Deep Learning based Real-time Model Evaluation Plugin for ChimeraX.

bioRxiv : the preprint server for biology·2026
Same author

Interfacial Redox Decoupling via Amphiphilic Carbon Dots for Highly Efficient Biphasic Photocatalytic H<sub>2</sub>O<sub>2</sub> Production and Selective Benzyl Alcohol Oxidation.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

Beta-Adrenergic Stimulation and <i>MYH7</i> G256E Mutant Gene Dosage Drive Hypertrophic Cardiomyopathy Phenotype Penetrance.

bioRxiv : the preprint server for biology·2026
Same author

Stress-Driven Accelerated Evolution and Ecological Network Reconfiguration in Extremophilic Microbial Communities.

Biology·2026
Same author

Workload-induced changes to cell state contribute to β-cell failure in diabetes.

bioRxiv : the preprint server for biology·2026
Same author

A nomogram estimates postoperative urinary tract infection risk after upper urinary tract stone surgery with double-J stents.

Scientific reports·2026
Same journal

Tension on dsDNA bound to ssDNA-RecA filaments may play an important role in driving efficient and accurate homology recognition and strand exchange.

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Amplitude-phase coupling drives chimera states in globally coupled laser networks [Phys. Rev. E 91, 040901(R) (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Shapes of sedimenting soft elastic capsules in a viscous fluid [Phys. Rev. E 92, 033003 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Erratum: Attenuation of excitation decay rate due to collective effect [Phys. Rev. E 90, 022142 (2014)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Role of connectivity and fluctuations in the nucleation of calcium waves in cardiac cells [Phys. Rev. E 92, 052715 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
Same journal

Publisher's Note: Lattice Boltzmann approach for complex nonequilibrium flows [Phys. Rev. E 92, 043308 (2015)].

Physical review. E, Statistical, nonlinear, and soft matter physics·2016
See all related articles

Aging significantly impacts network evolution across various domains. Introducing aging factors, like exponential or power-law decay, transforms network structure, affecting clustering, hierarchy, and node distances in models like Barabasi-Albert.

Area of Science:

  • Network Science
  • Complex Systems
  • Statistical Physics

Background:

  • Aging is a universal phenomenon affecting evolving networks, including scientific collaboration, movie actor, and the Internet.
  • Nodes in networks, such as scientists or devices, have finite active periods or become obsolete.
  • Understanding aging's impact is crucial for analyzing dynamic network structures.

Purpose of the Study:

  • To investigate the effect of aging on network evolution, specifically within citation networks.
  • To model aging using exponential and power-law decay factors and compare their impact.
  • To analyze the transformation of the Barabasi-Albert scale-free model when incorporating aging.

Main Methods:

  • Representing node aging with an exponential decay factor, e(-betatau), where tau is node age.

Related Experiment Videos

  • Comparing exponential decay with other aging types, such as power-law decay.
  • Introducing aging factors into the Barabasi-Albert scale-free model to observe network transformations.

    • Main Results:

    • Aging introduces significant transformations to the Barabasi-Albert model, leading to clustering even in infinitely large networks.
    • The clustering coefficient's behavior depends on the aging intensity: linear increase for small beta, exponential decay for large beta.
    • Aging can induce hierarchical structures, disassortative degree-degree correlations, and alter average node distances based on the decay type.

    Conclusions:

    • The type of decay factor (exponential vs. power-law) significantly influences network properties like clustering and average node distance.
    • Exponential decay leads to a one-dimensional chain-like structure, while power-law decay shows a transformation from small-world to hypercubic lattice to a chain.
    • These findings have implications for interpreting empirical data and understanding network dynamics in real-world systems.