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

Rapidly Varying Flow01:24

Rapidly Varying Flow

718
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
718
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

134
Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression...
134
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

548
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
548
Linear time-invariant Systems01:23

Linear time-invariant Systems

1.1K
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
1.1K
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

3.1K
The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
3.1K
Current Growth And Decay In RL Circuits01:30

Current Growth And Decay In RL Circuits

5.0K
The current growth and decay in RL circuits can be understood by considering a series RL circuit consisting of a resistor, an inductor, a constant source of emf, and two switches. When the first switch is closed, the circuit is equivalent to a single-loop circuit consisting of a resistor and an inductor connected to a source of emf. In this case, the source of emf produces a current in the circuit. If there were no self-inductance in the circuit, the current would rise immediately to a steady...
5.0K

You might also read

Related Articles

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

Sort by
Same author

Random telegraph processes with nonlocal memory.

Physical review. E·2024
Same author

Empathy at school project: Effects of didactics of emotions® on emotional competence, cortisol secretion and inflammatory profile in primary school children. A controlled longitudinal psychobiological study.

Comprehensive psychoneuroendocrinology·2023
Same author

Hypomimia in Parkinson's disease: an axial sign responsive to levodopa.

European journal of neurology·2020
Same author

Relating size and functionality in human social networks through complexity.

Proceedings of the National Academy of Sciences of the United States of America·2020
Same author

Is there evidence of bradykinesia in essential tremor?

European journal of neurology·2020
Same author

Corticobasal syndrome: neuroimaging and neurophysiological advances.

European journal of neurology·2019
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: Apr 17, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

10.6K

Critical slowing down in networks generating temporal complexity.

M T Beig1, A Svenkeson2, M Bologna3

  • 1Center for Nonlinear Science, University of North Texas, Denton, Texas 76203, USA.

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

Complex network dynamics reveal critical slowing down and aging effects in the mean field variable X(t) when initialized far from equilibrium. Initializing at X(0)=0 shows aging in the fluctuating variable η(t) due to origin re-crossings.

More Related Videos

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.7K
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

Related Experiment Videos

Last Updated: Apr 17, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

10.6K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.7K
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

Area of Science:

  • Statistical Physics
  • Complex Systems
  • Network Science

Background:

  • Studying critical phenomena in finite-size complex networks is crucial for understanding emergent behaviors.
  • Nonlinear Langevin equations model dynamic variables like the mean field (order parameter) in these systems.
  • Autocorrelation functions are key indicators of system dynamics and criticality.

Purpose of the Study:

  • To investigate the conditions under which the autocorrelation function of a mean field variable (X(t)) in a complex network exhibits criticality.
  • To analyze the influence of initial conditions on critical slowing down and aging effects.
  • To understand the dynamics of the fluctuating variable η(t) and its relation to aging.

Main Methods:

  • Analysis of a nonlinear Langevin equation for the dynamic variable X(t).
  • Examination of autocorrelation functions under different initial conditions (X(0)=1 and X(0)=0).
  • Application of stochastic linearization to evaluate time scales and explain equilibrium autocorrelation behavior.

Main Results:

  • When initialized far from equilibrium (X(0)=1), X(t) shows clear signs of critical slowing down and aging.
  • Initialization at X(0)=0 does not reveal evident criticality in X(t), but the fluctuating variable η(t) exhibits significant aging.
  • Aging in η(t) is linked to origin re-crossing events, which are crucial for its dynamics.

Conclusions:

  • Initial conditions critically influence the manifestation of criticality and aging in complex network dynamics.
  • Aging effects can be present in derived variables (like η(t)) even when not apparent in the primary order parameter (X(t)).
  • Stochastic linearization provides a method to understand temporal complexity, aging, and ergodicity breakdown in such systems.