Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Entropy Change in Reversible Processes

Entropy Change in Reversible Processes

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.

Network Covalent Solids

Network Covalent Solids

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...

Complexation Equilibria: The Chelate Effect

Complexation Equilibria: The Chelate Effect

In complexation reactions, metal atoms or cations interact with ligands to form donor-acceptor adducts called metal complexes. Ligands that bind through one donor site are monodentate, ligands with two donor sites are bidentate, and those with more than two donor sites are polydentate ligands. For example, ethylene diamine is a bidentate ligand that binds through two nitrogen donor atoms, forming a five-membered ring. EDTA is a polydentate ligand that binds through four oxygen and two nitrogen...

Protein Networks

Protein Networks

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,...

Distribution and Dispersion

Distribution and Dispersion

To understand intra-specific interactions in populations, scientists measure the spatial arrangement of species individuals. This geographic arrangement is known as the species distribution or dispersion. Highly territorial species exhibit a uniform distribution pattern, in which individuals are spaced at relatively equal distances from one another. Species that are highly tied to particular resources, such as food or shelter, tend to concentrate around those resources, and thus exhibit a...

Complexation Equilibria: Overview

Complexation Equilibria: Overview

Complexation reactions take place when dative or coordinate covalent bonds form between metal ions and ligands. The compounds formed in these reactions are called coordination compounds. The number of bonds formed between the metal ion and the ligands is called its coordination number. Generally, most metal ions in an aqueous solution are solvated by water molecules and thus exist as aqua complexes.
The equilibrium constant of the complexation reaction is represented as the formation constant...

You might also read

Related Articles

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

Sort by

Same author

Complex network topological and spectral determinants of extreme events.

Chaos (Woodbury, N.Y.)·2026

Same author

Ordinal pattern of brain electrical activity as a marker of stroke-induced alterations in motor imagery task.

Chaos (Woodbury, N.Y.)·2026

Same author

Ordinal patterns for characterization of transition to extreme events.

Chaos (Woodbury, N.Y.)·2026

Same author

Emergent dynamics in heterogeneous pulsatile swarmalators.

Chaos (Woodbury, N.Y.)·2026

Same author

Controlling extreme events in neuronal networks: A single driving signal approach.

Chaos (Woodbury, N.Y.)·2026

Same author

Imitation-based evolutionary dynamics of behavioral decisions between health-conscious and health-unconscious strategies.

Chaos (Woodbury, N.Y.)·2026

Search research articles

Related Experiment Video

Updated: Aug 15, 2025

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

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

Published on: December 7, 2021

Extreme events in a complex network: Interplay between degree distribution and repulsive interaction.

Arnob Ray¹, Timo Bröhl², Arindam Mishra³

¹Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108, India.

Chaos (Woodbury, N.Y.)

|January 1, 2023

Summary

Topological heterogeneity and repulsive interactions in networks drive extreme events. Node degree influences vulnerability, with high-degree nodes affected by weaker interactions and low-degree nodes by stronger ones.

More Related Videos

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Related Experiment Videos

Last Updated: Aug 15, 2025

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

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

Published on: December 7, 2021

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Author Spotlight: Evaluation of Protein-Condensate Dynamics in Live Human Cells

Published on: January 5, 2024

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

Area of Science:

Complex systems
Network science
Nonlinear dynamics

Background:

Understanding extreme events in complex networks is crucial.
Oscillator dynamics are influenced by network topology and interactions.
Topological heterogeneity can significantly impact system behavior.

Purpose of the Study:

Investigate the role of topological heterogeneity in generating extreme events.
Analyze the interplay between repulsive interactions and node degree.
Identify conditions leading to extreme events in network oscillators.

Main Methods:

Utilized a second-order phase model for oscillator dynamics.
Employed mean-field repulsive interactions.
Applied an annealed network approximation for model reduction.

Main Results:

Extreme events arise from the interplay of topological heterogeneity and repulsive coupling.
Node degree dictates vulnerability: high-degree nodes are sensitive to weaker repulsion, low-degree nodes to stronger repulsion.
The location of extreme events shifts from high- to low-degree nodes as repulsion strength increases.

Conclusions:

Repulsive interactions and node degree play a dual role in the origin of extreme events.
Extreme events occur near the rotation-libration transition boundary.
Network topology is a key factor in predicting and understanding extreme event dynamics.