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

Protein Networks02:26

Protein Networks

4.6K
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,...
4.6K
Static Equilibrium - I01:05

Static Equilibrium - I

18.9K
A rigid body is said to be in dynamic equilibrium when both its linear and angular acceleration are zero, relative to an inertial frame of reference. This means that a body in equilibrium can be moving, but only when its linear and angular velocities are constant. A rigid body is said to be in static equilibrium when it is at rest in the selected frame of reference. The distinction between static equilibrium (e.g., a state of rest) and dynamic equilibrium (e.g, a state of uniform motion) is...
18.9K
Static Equilibrium - II01:07

Static Equilibrium - II

10.0K
Static equilibrium is a special case in mechanics that is very important in everyday life. It occurs when the net force and the net torque on an object or system are both zero. This means that both the linear and angular accelerations are zero. Thus, the object is at rest, or its center of mass is moving at a constant velocity. However, this does not mean that no forces are acting on the object within the system. In fact, there are very few scenarios on Earth in which no forces are acting upon...
10.0K
Static Friction01:18

Static Friction

1.4K
Static friction is a force that opposes the relative motion or tendency of motion between two surfaces in contact. It plays a crucial role in our daily lives, from walking on the ground to driving a car.
For example, consider a scenario where a truck is connected to a car by a rope, ready to tow it along a road. When no external force is applied by the truck, the car remains stationary and is said to be in static equilibrium. In this case, the forces acting on the car, such as gravity and the...
1.4K
Ogive Graph01:07

Ogive Graph

6.8K
An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
6.8K
Graphing Antiderivatives01:30

Graphing Antiderivatives

75
The concept of an antiderivative is fundamental in calculus, describing how a function's values accumulate over time. This process is closely related to physical motion, such as the movement of a rolling ball. As the ball progresses, its position changes in response to variations in velocity, just as an antiderivative graph reflects the cumulative effect of the original function's values.Graphing an antiderivative requires interpreting how a function's values influence the shape of its...
75

You might also read

Related Articles

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

Sort by
Same author

Strengthening military preparedness and public safety through research and collaboration on infectious disease transmission epidemiological systems.

BMJ military health·2026
Same author

Human mobility in the metaverse mirrors patterns in the physical world.

Scientific reports·2026
Same author

Differences in Shared T Cell receptor α Repertoire Associated with Recognition of Viral Antigens.

Immunological investigations·2026
Same author

Homophily within and across groups.

Nature communications·2025
Same author

Initialisation and network effects in decentralised federated learning.

Applied network science·2025
Same author

Social inequalities in vaccine coverage and their effects on epidemic spreading.

PLoS computational biology·2025

Related Experiment Video

Updated: Feb 6, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.5K

Mapping temporal-network percolation to weighted, static event graphs.

Mikko Kivelä1, Jordan Cambe1,2, Jari Saramäki1

  • 1Department of Computer Science, Aalto University School of Science, FI-00076, Aalto, Finland.

Scientific Reports
|August 19, 2018
PubMed
Summary
This summary is machine-generated.

Temporal network correlations impact diffusion processes with limited agent lifetimes. Weighted event graphs reveal this temporal percolation is analogous to directed percolation.

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

1.6K
Generation of Shear Adhesion Map Using SynVivo Synthetic Microvascular Networks
09:52

Generation of Shear Adhesion Map Using SynVivo Synthetic Microvascular Networks

Published on: May 25, 2014

9.3K

Related Experiment Videos

Last Updated: Feb 6, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

18.5K
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

1.6K
Generation of Shear Adhesion Map Using SynVivo Synthetic Microvascular Networks
09:52

Generation of Shear Adhesion Map Using SynVivo Synthetic Microvascular Networks

Published on: May 25, 2014

9.3K

Area of Science:

  • Complex systems
  • Network science
  • Statistical physics

Background:

  • Diffusion processes on networks are crucial for understanding phenomena like disease spread and information dissemination.
  • Temporal network structures, characterized by time-varying connections, significantly alter diffusion dynamics.
  • The limited lifetime of spreading agents (e.g., recovery time, information decay) introduces complex constraints on temporal network processes.

Purpose of the Study:

  • To introduce a novel framework, weighted event graphs, for analyzing connectivity in temporal networks with time-respecting paths and waiting time limits.
  • To investigate the phenomenon of temporal network percolation under these constraints.
  • To establish an analogy between temporal network percolation and directed percolation.

Main Methods:

  • Development and application of the weighted event graph framework.
  • Simulation and analysis of percolation on both weighted event graphs and underlying temporal networks.
  • Comparison of temporal network percolation with directed percolation models.

Main Results:

  • Weighted event graphs provide an efficient method for studying time-limited connectivity.
  • Temporal network percolation exhibits characteristics analogous to directed percolation.
  • The study identifies multiple order parameters to characterize this temporal percolation phenomenon.

Conclusions:

  • Weighted event graphs are a powerful tool for analyzing temporal network dynamics with time constraints.
  • Temporal network percolation shares fundamental properties with directed percolation, offering new theoretical insights.
  • The findings advance the understanding of diffusion processes on dynamic networks with agent lifetime limitations.