Search research articles

Related Concept Videos

Intracellular Signaling Cascades

Intracellular Signaling Cascades

Once a ligand binds to a receptor, the signal is transmitted through the membrane and into the cytoplasm. The continuation of a signal in this manner is called signal transduction. Signal transduction only occurs with cell-surface receptors, which cannot interact with most components of the cell, such as DNA. Only internal receptors can interact directly with DNA in the nucleus to initiate protein synthesis. When a ligand binds to its receptor, conformational changes occur that affect the...

Rab Cascades

Rab Cascades

Rab GTPases act in a regulated cascade during membrane fusion, helping the lipid bilayers mix. The Rab family of proteins are active when bound to GTP, and inactive when bound to GDP. Hence, they act as guanine nucleotide-dependent molecular switches. Rab-GTP recognizes and binds to long or short-range tethering proteins to capture the target vesicle. These tethers coordinate with SNAREs on the vesicle and the target membrane to assemble the trans SNARE complex that locks the mixing bilayers.

Cascaded Op Amps

Cascaded Op Amps

Operational amplifiers (op-amps) are versatile electronic components that can be interconnected in a cascade - one after another in a linear sequence. This cascading is possible due to their infinite input resistance and zero output resistance, allowing them to maintain their input-output relationships even when connected in series.
In a cascaded system, each op-amp is referred to as a stage. The output of one stage drives the input of the subsequent stage. As the input signal passes through...

Amplifying Signals via Enzymatic Cascade

Amplifying Signals via Enzymatic Cascade

When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...

Design Example: Creating a Hydraulic Model of a Dam Spillway

Design Example: Creating a Hydraulic Model of a Dam Spillway

Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.

Collisions in Multiple Dimensions: Introduction

Collisions in Multiple Dimensions: Introduction

It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...

You might also read

Related Articles

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

Sort by

Same author

Network-driven discovery of repurposable drugs targeting hallmarks of aging.

Nature aging·2026

Same author

Design of robust networks via reinforcement learning prompts the emergence of multi-backbones.

Nature communications·2026

Same author

Slower searching yields higher efficiency: A case study of taxi drivers.

Proceedings of the National Academy of Sciences of the United States of America·2025

Same author

Evaluating in-vivo spontaneous firing rate in the brain based on neuronal noise modeling.

Communications biology·2025

Same author

Network dismantling by physical damage.

Communications physics·2025

Same author

The random cascading origin of abrupt transitions in interdependent systems.

Nature communications·2025

Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026

Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026

Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026

Same journal

State estimation in spatiotemporal chaos via low-rank StatFEM.

Chaos (Woodbury, N.Y.)·2026

Same journal

Universal response functions in driven dissipative tunneling dynamics.

Chaos (Woodbury, N.Y.)·2026

Same journal

A network-based approach to characterize the dynamics of the coupling field of thermoacoustic oscillators in annular geometry.

Chaos (Woodbury, N.Y.)·2026

See all related 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

Search research articles

Related Experiment Video

Updated: Jul 13, 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

Dynamics of cascades in spatial interdependent networks.

Bnaya Gross¹, Ivan Bonamassa², Shlomo Havlin¹

¹Department of Physics, Bar-Ilan University, 52900 Ramat-Gan, Israel.

Chaos (Woodbury, N.Y.)

|October 13, 2023

Summary

This summary is machine-generated.

Cascading failures in interdependent networks change with dependency range, showing diverse phase transitions and cascade dynamics. This research reveals mechanisms for known transitions and predicts a new type.

More Related Videos

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Published on: August 1, 2011

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

Related Experiment Videos

Last Updated: Jul 13, 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

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Multi-electrode Array Recordings of Neuronal Avalanches in Organotypic Cultures

Published on: August 1, 2011

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

Area of Science:

Complex Systems Science
Network Science
Condensed Matter Physics

Background:

Cascading failures in spatial interdependent networks are influenced by the range of dependency couplings between network layers.
Understanding these dynamics is crucial for predicting system-wide failures and designing robust networks.

Purpose of the Study:

To investigate how the interaction range of dependency couplings affects cascading failure dynamics in spatial interdependent networks.
To characterize different types of phase transitions and cascade kinetics associated with varying dependency ranges.
To explore the potential for experimental observation of these phenomena in physical systems.

Main Methods:

Analysis of cascading failure dynamics in spatial interdependent networks with varying dependency coupling ranges.
Identification and characterization of different phase transition types (mixed-order, first-order, second-order) and their associated cascade kinetics.
Examination of cascade dynamics during mixed-order resistive transitions in interdependent superconductors.

Main Results:

Increasing dependency coupling range leads to diverse phase transitions and cascade kinetics, including critical branching, nucleation cascades, and weak cascades.
Cascade dynamics at the mixed-order resistive transition in interdependent superconductors exhibit similarities to percolation in abstract networks.
A novel fourth type of phase transition, triggered by microscopic intervention, is predicted.

Conclusions:

The interaction range of dependency couplings is a critical factor governing cascading failures and phase transitions in interdependent networks.
The study elucidates mechanisms for known phase transitions and proposes a new type, offering insights into network robustness.
Findings provide a framework for experimental studies of phase transitions and cascade kinetics in physical interdependent systems.