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

Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

949
Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
949
Second Order systems II01:18

Second Order systems II

488
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
488
Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

1.1K
In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
1.1K
Second Order systems I01:20

Second Order systems I

732
A servo system exemplifies a second-order system, featuring a proportional controller and load elements that ensure the output position aligns with the input position. The relationship between these components is described by a second-order differential equation. Applying the Laplace transform under zero initial conditions yields the transfer function, showing how inputs are converted to outputs in the system.
By reinterpreting the system, one can derive the closed-loop transfer function, which...
732
Pole and System Stability01:24

Pole and System Stability

1.3K
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
1.3K
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

1.2K
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
1.2K

You might also read

Related Articles

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

Sort by
Same author

A voter-model representation of the multi-allelic Moran process: Exact stationary distributions and diversity thresholds from well-mixed populations to complex networks.

Journal of theoretical biology·2026
Same author

Desegregation of neuronal predictive processing.

Nature communications·2026
Same author

Synchronization of identical oscillators on a sphere: Exact results with external forces and higher-order interactions.

Physical review. E·2025
Same author

Increased Osteocyte Lacunae Size and Organic Matrix Pyridinoline Content in Transiliac Bone from Patients with Axial Spondyloarthritis (axSpA).

Calcified tissue international·2025
Same author

Suppressing Sensation during Action across Species and Sensory Modalities: Predictive and Nonpredictive Mechanisms of Sensory Modulation.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2025
Same author

Probability of achieving bone mineral density treatment targets with abaloparatide and teriparatide.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research·2025
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

Related Experiment Video

Updated: Mar 30, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K

Binary dynamics on star networks under external perturbations.

Carolina A Moreira1, David M Schneider1, Marcus A M de Aguiar1

  • 1Instituto de Física 'Gleb Wataghin', Universidade Estadual de Campinas, Unicamp 13083-970, Campinas, São Paulo, Brazil.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|November 14, 2015
PubMed
Summary
This summary is machine-generated.

This study models opinion dynamics with external influences on different network structures. Star networks show unique behavior compared to fully connected networks, with distinct equilibrium states influenced by central nodes.

More Related Videos

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

688
Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy
06:37

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

4.3K

Related Experiment Videos

Last Updated: Mar 30, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K
Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

688
Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy
06:37

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

4.3K

Area of Science:

  • Complex systems
  • Statistical physics
  • Social network analysis

Background:

  • The voter model simulates opinion dynamics in social networks.
  • Opinion makers introduce external influence on network states.
  • Network topology significantly impacts dynamic processes.

Purpose of the Study:

  • To investigate a binary dynamical process on star and fully connected networks.
  • To analyze the influence of opinion makers on opinion formation.
  • To compare equilibrium states and dynamics across different network topologies.

Main Methods:

  • Modeling a voter model with opinion makers on star and fully connected networks.
  • Calculating the probability of nodes in state 1 over time.
  • Deriving approximate analytical solutions for equilibrium distributions.
  • Comparing results with simulations on scale-free networks.

Main Results:

  • A transition from disordered to ordered states is observed in both network types as external influence decreases.
  • Fully connected networks exhibit a uniform probability distribution at the critical point.
  • Star networks show a bimodal equilibrium distribution, reflecting the central node's state.
  • Network topology affects the speed of dynamic oscillations, with star networks being faster.

Conclusions:

  • The central node plays a crucial role in the opinion dynamics of star networks.
  • Network topology is a key determinant of opinion formation and equilibrium states.
  • The study provides insights into opinion dynamics in systems with hubs and external influences.