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

Restarting Stalled Replication Forks02:37

Restarting Stalled Replication Forks

6.1K
DNA replication is initiated at sites containing predefined DNA sequences known as origins of replication. DNA is unwound at these sites by the minichromosome maintenance (MCM) helicase and other factors such as Cdc45 and the associated GINS complex.The unwound single strands are protected by replication protein A (RPA) until DNA polymerase starts synthesizing DNA at the 5’ end of the strand in the same direction as the replication fork. To prevent the replication fork from falling apart,...
6.1K
Restarting Stalled Replication Forks02:37

Restarting Stalled Replication Forks

2.2K
2.2K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.0K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.0K
Cluster Sampling Method01:20

Cluster Sampling Method

13.7K
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...
13.7K
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

922
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
922
The Spindle Assembly Checkpoint02:19

The Spindle Assembly Checkpoint

3.5K
The spindle assembly checkpoint is a molecular surveillance mechanism ensuring the fidelity of chromosome segregation during anaphase. The checkpoint monitors the completion of all the prerequisite steps before chromosome segregation to determine whether the segregation process should proceed or be delayed.
Many proteins function together to control the spindle assembly checkpoint. Mutations affecting these proteins may allow cells to proceed into anaphase prematurely, resulting in the...
3.5K

You might also read

Related Articles

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

Sort by
Same author

Synchronizing chaos using reservoir computing.

Chaos (Woodbury, N.Y.)·2023
Same author

Reservoir computing with noise.

Chaos (Woodbury, N.Y.)·2023
Same author

Matryoshka and disjoint cluster synchronization of networks.

Chaos (Woodbury, N.Y.)·2022
Same author

Looking beyond community structure leads to the discovery of dynamical communities in weighted networks.

Scientific reports·2022
Same author

Reservoir computing with random and optimized time-shifts.

Chaos (Woodbury, N.Y.)·2022
Same author

Cluster synchronization of networks via a canonical transformation for simultaneous block diagonalization of matrices.

Chaos (Woodbury, N.Y.)·2021

Related Experiment Video

Updated: Nov 23, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.7K

Delays induced cluster synchronization in chaotic networks.

Chad Nathe1, Ke Huang1, Matteo Lodi2

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

Chaos (Woodbury, N.Y.)
|December 31, 2020
PubMed
Summary

Coupling delays in networks of coupled oscillators significantly influence cluster synchronization patterns. Researchers found that specific delay arrangements can stabilize various synchronization patterns in experimental and theoretical models.

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

947
Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

3.0K

Related Experiment Videos

Last Updated: Nov 23, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.7K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

947
Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

3.0K

Area of Science:

  • Complex Systems
  • Nonlinear Dynamics
  • Network Science

Background:

  • Synchronization is a fundamental phenomenon in coupled oscillator networks.
  • Coupling delays can drastically alter network dynamics and emergent behaviors.
  • Understanding delay effects is crucial for designing and controlling complex systems.

Purpose of the Study:

  • To investigate the impact of coupling delays on cluster synchronization patterns.
  • To analyze the stability of different cluster synchronization patterns.
  • To validate theoretical predictions with experimental observations.

Main Methods:

  • Theoretical analysis of coupled identical oscillators in a ring network.
  • Stability analysis of emergent cluster synchronization patterns.
  • Experimental realization using Colpitts oscillators with RF cable delays.
  • Verification on a larger, fully connected network with probabilistic delays.

Main Results:

  • Eight distinct cluster synchronization patterns emerge in a six-oscillator ring network based on delay assignments.
  • All identified patterns can be stabilized for sufficient coupling strength and specific delay values.
  • Experimental results closely match theoretical predictions for cluster synchronization.
  • Theory validated on a 50-node network with random delay distribution.

Conclusions:

  • Coupling delays are critical determinants of cluster synchronization in oscillator networks.
  • The precise arrangement of delays dictates emergent synchronization patterns.
  • Experimental validation confirms the theoretical framework for delay-coupled oscillator networks.