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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

438
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
438
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

359
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
359
Generalized Hooke's Law01:22

Generalized Hooke's Law

3.2K
The generalized Hooke's Law is a broadened version of Hooke's Law, which extends to all types of stress and in every direction. Consider an isotropic material shaped into a cube subjected to multiaxial loading. In this scenario, normal stresses are exerted along the three coordinate axes. As a result of these stresses, the cubic shape deforms into a rectangular parallelepiped. Despite this deformation, the new shape maintains equal sides, and there is a normal strain in the direction of the...
3.2K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.5K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.5K
Equation of the Elastic Curve01:23

Equation of the Elastic Curve

1.2K
The concept of curvature in plane curves, crucial in structural engineering, defines how sharply a beam bends under load. This curvature is determined using the curve's first and second derivatives.
Consider a cantilever beam with a point load at its free end (for instance, a diving board). When analyzing beam deflection with small slopes, the shape of the beam's elastic curve becomes key. The governing equation for this analysis involves the bending moment and the beam's flexural rigidity,...
1.2K
Elastic Curve from the Load Distribution01:16

Elastic Curve from the Load Distribution

588
The structural behavior of beams under distributed loads is critical for engineering analysis, which focuses on predicting how beams bend and react under such conditions. Different types of beams (e.g., cantilever, supported, or overhanging) behave differently under distributed load conditions.
For all beams, the analysis of the beam's reaction to distributed loads begins by understanding the relationship between a beam's load and the resulting shear forces and bending moments. Initially, this...
588

You might also read

Related Articles

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

Sort by
Same author

Internal protein motion in a rough model potential.

The Journal of chemical physics·2025
Same author

How to simulate Lévy flights in a steep potential: An explicit splitting numerical scheme.

Chaos (Woodbury, N.Y.)·2025
Same author

Bernoulli trial under subsystem restarts: Two competing searchers looking for a target.

Chaos (Woodbury, N.Y.)·2025
Same author

Relation between generalized diffusion equations and subordination schemes.

Physical review. E·2021
Same author

Random Search with Resetting: A Unified Renewal Approach.

Physical review letters·2018
Same author

Scale-invariant puddles in graphene: Geometric properties of electron-hole distribution at the Dirac point.

Physical review. E·2017

Related Experiment Video

Updated: May 3, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

2.9K

Numerical approach to unbiased and driven generalized elastic model.

M Ghasemi Nezhadhaghighi1, A Chechkin2, R Metzler2

  • 1Department of Physics, Sharif University of Technology, Tehran, P.O.Box: 11365-9161, Iran.

The Journal of Chemical Physics
|January 21, 2014
PubMed
Summary

This study investigates the generalized elastic model (GEM), revealing no intermittent behavior in interface fluctuations. It also analyzes the driven GEM dynamics under perturbation, providing insights into its ergodic properties.

Related Experiment Videos

Last Updated: May 3, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

2.9K

Area of Science:

  • Physics
  • Soft Matter Physics
  • Statistical Mechanics

Background:

  • The generalized elastic model (GEM) is a versatile framework for describing diverse physical systems, including polymers, membranes, and rough interfaces.
  • Understanding the dynamic properties and scaling behavior of GEM is crucial for various scientific disciplines.

Purpose of the Study:

  • To investigate the properties of the generalized elastic model (GEM) using scaling arguments and numerical simulations.
  • To compare analytical and numerical results for the subdiffusion exponent and scaling properties of moments.
  • To analyze the ergodic properties and the behavior of the driven GEM under perturbation.

Main Methods:

  • Scaling arguments and numerical simulations were employed to analyze the GEM.
  • The subdiffusion exponent (β) was characterized by the growth of mean squared displacement.
  • Scaling properties of qth order moments and ergodic properties were investigated.
  • Numerical simulations were performed for the driven GEM with a localized perturbation.

Main Results:

  • Interface fluctuations within the GEM exhibit no intermittent behavior.
  • The subdiffusion exponent (β) and scaling of moments were determined and compared analytically and numerically.
  • Ergodic properties, including ergodicity breaking and time-averaged mean squared displacement distribution, were analyzed.
  • Characteristics of average drift for a tagged probe in the driven GEM were extracted.

Conclusions:

  • The generalized elastic model (GEM) demonstrates non-intermittent interface fluctuations.
  • The study provides a comprehensive analysis of GEM dynamics, including subdiffusion, scaling, and ergodic properties.
  • The driven GEM exhibits distinct characteristics under localized perturbation, offering insights into its response to external forces.