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

Entropy02:39

Entropy

35.0K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
35.0K
Entropy01:18

Entropy

3.5K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
3.5K
Lewis Symbols and the Octet Rule02:36

Lewis Symbols and the Octet Rule

80.3K
Chemical bonds are complex interactions between two or more atoms or ions, which reduce the potential energy of the molecule. Gilbert N. Lewis developed a model called the Lewis model that simplified the depiction of chemical bond formation and provided straightforward explanations for the chemical bonds seen in most common compounds.
80.3K
Elements: Chemical Symbols and Isotopes02:31

Elements: Chemical Symbols and Isotopes

125.3K
A chemical symbol is an abbreviation used to indicate an element or an atom of an element. For example, the symbol for mercury is Hg. The same symbol is used to indicate one atom of mercury (microscopic domain) or to label a container of many atoms of the element mercury (macroscopic domain).
Some symbols are derived from the common English name of the element; others are abbreviations of the name in another language — Latin, Greek or German. For example, the symbol for aluminum (common name)...
125.3K
Standard Entropy Change for a Reaction03:00

Standard Entropy Change for a Reaction

24.1K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
24.1K
Chemical Symbols01:09

Chemical Symbols

10.5K
A chemical symbol is an abbreviation that is used to indicate an element or an atom of an element. For example, the symbol for mercury is Hg. We use the same symbol to indicate one atom of mercury (microscopic domain) or to label a container of many atoms of the element mercury (macroscopic domain).
Some symbols are derived from the common name of the element; others are abbreviations of the name in another language. Most symbols have one or two letters, but three-letter symbols have been used...
10.5K

You might also read

Related Articles

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

Sort by
Same author

The detection matrix as a model-agnostic tool to estimate the number of degrees of freedom in mechanical systems and engineering structures.

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

How adherence to public health measures shapes epidemic spreading: A temporal network model.

Chaos (Woodbury, N.Y.)·2021
Same author

Improving on transfer entropy-based network reconstruction using time-delays: Approach and validation.

Chaos (Woodbury, N.Y.)·2020
Same author

Application of symbolic recurrence to experimental data, from firearm prevalence to fish swimming.

Chaos (Woodbury, N.Y.)·2019
Same author

Detecting switching leadership in collective motion.

Chaos (Woodbury, N.Y.)·2019
Same author

Inference of time-varying networks through transfer entropy, the case of a Boolean network model.

Chaos (Woodbury, N.Y.)·2018

Related Experiment Video

Updated: Jan 22, 2026

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides
09:41

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Published on: May 29, 2018

10.0K

Transfer entropy on symbolic recurrences.

Maurizio Porfiri1, Manuel Ruiz Marín2

  • 1Department of Mechanical and Aerospace Engineering and Department of Biomedical Engineering, New York University, Tandon School of Engineering, Brooklyn, New York 11201, USA.

Chaos (Woodbury, N.Y.)
|July 4, 2019
PubMed
Summary

This study introduces transfer entropy on symbolic recurrence plots to uncover causal links in complex dynamical systems. This novel approach effectively quantifies interactions within time series data.

More Related Videos

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.4K
Identification and Protection of the Recurrent Laryngeal Nerve during Transoral Robotic Thyroidectomy
05:25

Identification and Protection of the Recurrent Laryngeal Nerve during Transoral Robotic Thyroidectomy

Published on: October 24, 2025

429

Related Experiment Videos

Last Updated: Jan 22, 2026

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides
09:41

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Published on: May 29, 2018

10.0K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.4K
Identification and Protection of the Recurrent Laryngeal Nerve during Transoral Robotic Thyroidectomy
05:25

Identification and Protection of the Recurrent Laryngeal Nerve during Transoral Robotic Thyroidectomy

Published on: October 24, 2025

429

Area of Science:

  • Complex Systems Science
  • Information Theory
  • Dynamical Systems Analysis

Background:

  • Recurrence quantification analysis (RQA) is a key method for studying complex dynamical systems.
  • Existing methods for multivariate RQA lack robust information-theoretic tools for causal link discovery.
  • Symbolic recurrence plots offer advantages over traditional methods, providing richer data representation.

Purpose of the Study:

  • To develop information-theoretic tools for causal inference using symbolic recurrence plots.
  • To introduce transfer entropy applied to symbolic recurrences for quantifying system interactions.
  • To enable reliable discovery of causal links in multivariate time series data.

Main Methods:

  • Establishment of a probability space for information encoding within symbolic recurrences.
  • Application of transfer entropy to symbolic recurrence plots for interaction analysis.
  • Validation using synthetic and experimental time series data.

Main Results:

  • Demonstrated statistically reliable discovery of causal links between dynamical systems.
  • Successfully inferred the strength and direction of interactions using the proposed method.
  • The approach is effective with as few as two time series or larger datasets.

Conclusions:

  • The integration of recurrence plots, information theory, and symbolic dynamics provides a powerful new framework.
  • This method enhances the visualization and quantification of interactions in complex systems.
  • Researchers and practitioners gain effective tools for analyzing dynamical system behaviors.