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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

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

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

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...

Radical Anti-Markovnikov Addition to Alkenes: Thermodynamics

Radical Anti-Markovnikov Addition to Alkenes: Thermodynamics

The anti-Markovnikov addition of hydrogen halides to an alkene is thermodynamically feasible only with HBr. The radical addition reaction with other hydrogen halides like HCl and HI is thermodynamically unfavorable.

Variables and Equations of State

Variables and Equations of State

The physical state of a pure substance can be defined by certain state variables such as volume (V), pressure (p), temperature (T), and amount of substance (n). When two gases are separated by a movable wall, the gas with the higher pressure naturally compresses the gas with the lower pressure. This causes the high-pressure gas to expand and the low-pressure gas to compress until both gases achieve mechanical equilibrium. At this point, their pressures equalize, and the movement of the wall...

Temperature Dependence on Reaction Rate

Temperature Dependence on Reaction Rate

The Collision Theory
Atoms, molecules, or ions must collide before they can react with each other. Atoms must be close together to form chemical bonds. This premise is the basis for a theory that explains many observations regarding chemical kinetics, including factors affecting reaction rates.
The collision theory is based on the postulates that (i) the reaction rate is proportional to the rate of reactant collisions, (ii) the reacting species collide in an orientation allowing contact between...

You might also read

Related Articles

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

Sort by

Same author

Theoretical analysis of the denoising autoencoder using Tweedie's formula.

Neural networks : the official journal of the International Neural Network Society·2026

Same author

The occurrence of a particular state is a predictor of successful travel consultation.

PloS one·2026

Same author

Herding as an emergent behaviour in harem groups of feral Garrano ponies.

Journal of the Royal Society, Interface·2026

Same author

Author Correction: Induction of functional tissue-engineered skeletal muscle constructs by defined electrical stimulation.

Scientific reports·2024

Same author

Time-series blood cytokine profiles correlate with treatment responses in triple-negative breast cancer patients.

British journal of cancer·2024

Same author

Bayesian traction force estimation using cell boundary-dependent force priors.

Biophysical journal·2023

Search research articles

Related Experiment Video

Updated: May 13, 2026

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

Adaptive Markov chain Monte Carlo for auxiliary variable method and its application to parallel tempering.

Takamitsu Araki¹, Kazushi Ikeda

¹Graduate School of Information Science, Nara Institute of Science and Technology, Japan. takamitsu-a@is.naist.jp

Neural Networks : the Official Journal of the International Neural Network Society

|March 19, 2013

Summary

This study introduces an adaptive algorithm for auxiliary variable methods like Parallel Tempering, improving parameter tuning during sampling. The adaptive Parallel Tempering enhances efficiency in complex distribution sampling.

Related Experiment Videos

Last Updated: May 13, 2026

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

Area of Science:

Computational statistics
Statistical modeling

Background:

Auxiliary variable methods, including Parallel Tempering and cluster Monte Carlo, are efficient for sampling complex distributions.
Standard Markov chain Monte Carlo methods are less efficient for such tasks.
Algorithm performance heavily relies on critical parameter selection.

Purpose of the Study:

To develop an adaptive algorithm for optimizing parameters in auxiliary variable methods during sample generation.
To prove the convergence of the proposed adaptive algorithm.
To enhance the efficiency and applicability of Parallel Tempering through on-the-fly parameter tuning.

Main Methods:

Proposed a novel algorithm for adaptive parameter tuning within auxiliary variable methods.
Developed an adaptive Parallel Tempering algorithm that adjusts parameters dynamically.
Proved the convergence theorem for the adaptive sampling algorithm.

Main Results:

The adaptive Parallel Tempering algorithm successfully tunes parameters during sampling.
Validation confirmed the effectiveness of the adaptive algorithm compared to conventional methods.
Generated samples accurately followed the target distribution with the adaptive approach.

Conclusions:

The proposed adaptive algorithm significantly improves parameter selection for auxiliary variable methods.
Adaptive Parallel Tempering offers a more efficient and robust approach for sampling complex distributions.
This work provides a theoretical guarantee (convergence theorem) and practical validation for adaptive sampling techniques.