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 Concept Videos

Symmetry01:26

Symmetry

222
The equation of an ellipse centered at the origin defines all points whose distances from the center maintain a constant ratio between the horizontal and vertical axes. This equation results in a smooth, closed curve that extends further along the x-axis than the y-axis, giving it a horizontal orientation. Such an ellipse demonstrates three kinds of symmetry: across the x-axis, across the y-axis, and about the origin. These symmetries are essential in understanding the graph's structure and...
222
Gauss's Law: Planar Symmetry01:27

Gauss's Law: Planar Symmetry

9.6K
A planar symmetry of charge density is obtained when charges are uniformly spread over a large flat surface. In planar symmetry, all points in a plane parallel to the plane of charge are identical with respect to the charges. Suppose the plane of the charge distribution is the xy-plane, and the electric field at a space point P with coordinates (x, y, z) is to be determined. Since the charge density is the same at all (x, y) - coordinates in the z = 0 plane, by symmetry, the electric field at P...
9.6K
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Symmetry in Maxwell's Equations01:28

Symmetry in Maxwell's Equations

4.2K
Once the fields have been calculated using Maxwell's four equations, the Lorentz force equation gives the force that the fields exert on a charged particle moving with a certain velocity. The Lorentz force equation combines the force of the electric field and of the magnetic field on the moving charge. Maxwell's equations and the Lorentz force law together encompass all the laws of electricity and magnetism. The symmetry that Maxwell introduced into his mathematical framework may not be...
4.2K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K
Cluster Sampling Method01:20

Cluster Sampling Method

14.8K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
14.8K

You might also read

Related Articles

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

Sort by
Same author

Ozone-driven degradation of sex pheromone in Plutella xylostella: Implications for reproductive communication and mating success.

Insect science·2026
Same author

Green synthesis of cubic CuO nanoparticles for biomedical applications and the photodegradation of methylene blue: RSM-BBD optimization of the reaction parameters and stability studies.

Nanoscale advances·2026
Same author

Vitamin D deficiency in chronic hepatitis B across the disease spectrum: association with viral activity rather than hepatocellular carcinoma.

BMC gastroenterology·2026
Same author

Medical facemask waste alters detritus decomposition and fungal communities in a freshwater pond.

Scientific reports·2026
Same author

Olive (Olea europaea) phenolics for the control of psoriasis via targeting SMYD2 and IL-17A protein-protein interaction networks.

Journal of natural medicines·2026
Same author

Comparative Transcriptome Profiling of <i>Nicotiana benthamiana</i> Plants Infected with Potato Mop-Top Virus and Its Mutant Lacking a Gene for the 8K Protein Underlines the Role of Chloroplasts During Infection.

Molecular plant-microbe interactions : MPMI·2026
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
See all related articles

Related Experiment Video

Updated: Feb 10, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.7K

Symmetry- and input-cluster synchronization in networks.

Abu Bakar Siddique1, Louis Pecora2, Joseph D Hart3

  • 1Department of Mechanical Engineering, University of New Mexico, Albuquerque, New Mexico 87131, USA.

Physical Review. E
|May 16, 2018
PubMed
Summary
This summary is machine-generated.

We found that network cluster synchronization stability relies on a few Lyapunov exponents. This method applies to symmetry-cluster and input-cluster synchronization, verified in optoelectronic oscillators.

More Related Videos

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.9K
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.5K

Related Experiment Videos

Last Updated: Feb 10, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

3.7K
CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
10:40

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis

Published on: April 25, 2022

2.9K
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.5K

Area of Science:

  • Complex networks
  • Nonlinear dynamics
  • Synchronization phenomena

Background:

  • Cluster synchronization is a key phenomenon in complex networks, where nodes form synchronized groups.
  • Understanding the stability of these clusters is crucial for predicting network behavior.
  • Existing methods may not cover all types of cluster synchronization patterns.

Purpose of the Study:

  • To develop a unified approach for analyzing the stability of diverse cluster synchronization patterns in networks.
  • To identify the key factors determining the stability of symmetry-cluster and input-cluster synchronization.
  • To experimentally validate the theoretical findings.

Main Methods:

  • Analysis of network stability using a reduced set of Lyapunov exponents.
  • Application of the method to orbital partitions (symmetry-cluster synchronization).
  • Application of the method to equitable partitions (input-cluster synchronization).

Main Results:

  • The stability of all analyzed cluster synchronization patterns is determined by a small, consistent set of Lyapunov exponents.
  • The proposed method effectively characterizes both symmetry-cluster and input-cluster synchronization stability.
  • Experimental verification in coupled optoelectronic oscillator networks confirmed the theoretical predictions.

Conclusions:

  • A novel, unified method for assessing cluster synchronization stability in complex networks has been established.
  • Lyapunov exponents provide a powerful tool for understanding the robustness of synchronized states in networks.
  • The findings have implications for designing and controlling synchronized behavior in various network systems.