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

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

85
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
85
Classification of Systems-I01:26

Classification of Systems-I

167
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
167
Feedback control systems01:26

Feedback control systems

273
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
273
Linear Circuits01:17

Linear Circuits

379
A linear circuit is characterized by its output having a direct proportionality to its input, adhering to the linearity property, which encompasses the principles of homogeneity (scaling) and additivity. Homogeneity dictates that when the input, also referred to as the excitation, is multiplied by a constant factor, the output, known as the response, is correspondingly scaled by the same constant factor. For instance, if the current is multiplied by a constant 'k,' the voltage likewise...
379
Linear time-invariant Systems01:23

Linear time-invariant Systems

208
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...
208
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

59
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
59

You might also read

Related Articles

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

Sort by
Same author

Reducing size bias in epidemic network modelling.

Journal of theoretical biology·2025
Same author

Critically appraising the cass report: methodological flaws and unsupported claims.

BMC medical research methodology·2025
Same author

Use and understanding of AI in the ART laboratory: an international survey.

Reproductive biomedicine online·2025
Same author

Graft ischemia post cell transplantation to the brain: Glucose deprivation as the primary driver of rapid cell death.

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics·2025
Same author

Modelling indoor airborne transmission combining architectural design and people movement using the VIRIS simulator and web app.

Scientific reports·2024
Same author

Gap junctions in Turing-type periodic feather pattern formation.

PLoS biology·2024
Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026
Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026
Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026
Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026
Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026
Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026
See all related articles

Related Experiment Video

Updated: May 27, 2025

Patterning via Optical Saturable Transitions - Fabrication and Characterization
08:19

Patterning via Optical Saturable Transitions - Fabrication and Characterization

Published on: December 11, 2014

6.8K

Linear coupling of patterning systems can have nonlinear effects.

N Mahashri1, Thomas E Woolley2, M Chandru1

  • 1Vellore Institute of Technology, Department of Mathematics, School of Advanced Sciences, Vellore 632014, India.

Physical Review. E
|February 20, 2025
PubMed
Summary
This summary is machine-generated.

This study analyzes interconnected reaction-diffusion systems, revealing that interlayer communication can surprisingly suppress or enhance pattern formation, despite linear coupling. This nonlinear behavior is crucial for understanding complex biological systems.

More Related Videos

Patterning of Microorganisms and Microparticles through Sequential Capillarity-assisted Assembly
10:17

Patterning of Microorganisms and Microparticles through Sequential Capillarity-assisted Assembly

Published on: November 4, 2021

3.1K
Control of Cell Geometry through Infrared Laser Assisted Micropatterning
11:04

Control of Cell Geometry through Infrared Laser Assisted Micropatterning

Published on: July 10, 2021

3.4K

Related Experiment Videos

Last Updated: May 27, 2025

Patterning via Optical Saturable Transitions - Fabrication and Characterization
08:19

Patterning via Optical Saturable Transitions - Fabrication and Characterization

Published on: December 11, 2014

6.8K
Patterning of Microorganisms and Microparticles through Sequential Capillarity-assisted Assembly
10:17

Patterning of Microorganisms and Microparticles through Sequential Capillarity-assisted Assembly

Published on: November 4, 2021

3.1K
Control of Cell Geometry through Infrared Laser Assisted Micropatterning
11:04

Control of Cell Geometry through Infrared Laser Assisted Micropatterning

Published on: July 10, 2021

3.4K

Area of Science:

  • Systems biology
  • Chemical kinetics
  • Mathematical modeling

Background:

  • Biological systems often involve interconnected components, unlike isolated patterning systems.
  • Interlayer communication is a key feature in complex biological structures like mammary organoids.

Purpose of the Study:

  • To theoretically and quantitatively analyze a bilayer system coupling two reaction-diffusion systems.
  • To investigate how interlayer communication affects pattern formation in systems with identical kinetics but different diffusion coefficients.

Main Methods:

  • Utilized a two-domain interconnected geometry (bilayer) with two-species reaction-diffusion systems.
  • Applied the Routh-Hurwitz stability criterion to analyze pattern formation in uncoupled, weakly coupled, and strongly coupled systems.
  • Employed numerical simulations to validate theoretical analysis and investigate system behavior.

Main Results:

  • Demonstrated that linear coupling between layers can lead to nonlinear pattern suppression or enhancement.
  • Showed that patterning wave modes in strongly coupled systems can be approximated by a quartic polynomial, simplifying analysis.
  • Identified complex pattern-forming capabilities arising from interlayer communication.

Conclusions:

  • Interlayer communication in bilayer systems can induce emergent nonlinear behaviors, significantly impacting pattern formation.
  • The study provides a framework for understanding pattern dynamics in interconnected biological systems.
  • Approximation of complex dispersion relations simplifies the analysis of pattern formation in coupled reaction-diffusion systems.