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 Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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 squares (OLS)...
Reaction Mechanisms03:06

Reaction Mechanisms

Chemical reactions often occur in a stepwise fashion, involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs.
For instance, the decomposition of ozone appears to follow a mechanism with two steps:
Multi-Step Reactions02:31

Multi-Step Reactions

Chemical reactions often occur in a stepwise fashion involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs. Each of the steps in a reaction mechanism is called an elementary reaction. These...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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...
Reaction Mechanisms: The Steady-State Approximation01:26

Reaction Mechanisms: The Steady-State Approximation

The steady-state approximation, also referred to as the quasi-steady-state approximation to differentiate it from a true steady state, is a widely used method for simplifying calculations in complex reaction mechanisms. This approach is particularly useful when dealing with multi-step reactions that involve reverse reactions or several steps, which can significantly increase mathematical complexity and make the reactions nearly unsolvable analytically.The steady-state approximation operates on...
Evolutionary Processes in Microbes01:26

Evolutionary Processes in Microbes

Microbial evolution occurs rapidly due to short generation times and a variety of genetic processes, including horizontal gene transfer, mutation, recombination, and genetic drift. These mechanisms collectively enable microbes to adapt swiftly to changing environments.Horizontal gene transfer (HGT) allows genes to move between different species and occurs through three main mechanisms: conjugation, transformation, and transduction. Conjugation involves direct cell-to-cell contact for DNA...

You might also read

Related Articles

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

Sort by
Same author

Cultural evolution in the laboratory: evolution of cooperative altruistic punishing.

Evolutionary human sciences·2025
Same author

Explaining Performance on Interval and Ratio Schedules with a Molar View of Behavior.

Perspectives on behavior science·2025
Same author

Understanding resurgence and other emergent activity with the laws of allocation, induction, and covariance.

Journal of the experimental analysis of behavior·2024
Same author

A molar view of goal direction and habit.

Journal of the experimental analysis of behavior·2024
Same author

Rate matching, probability matching, and optimization in concurrent ratio schedules.

Journal of the experimental analysis of behavior·2022
Same author

Covariance, feedback, and discounting in ratio schedules.

Journal of the experimental analysis of behavior·2022
Same journal

A Mediational Theory of Verbal Relations.

Perspectives on behavior science·2026
Same journal

It is Time to Retire "Noncontingent Reinforcement".

Perspectives on behavior science·2026
Same journal

Using Wearable Technology to Predict the Occurrence of Severe Behavior Problems among Neurodiverse Individuals: A Systematic Review.

Perspectives on behavior science·2026
Same journal

Toward a Modern View of Pavlovian Conditioning in Applied Behavior Analysis.

Perspectives on behavior science·2026
Same journal

Citing the Literature.

Perspectives on behavior science·2026
Same journal

Extending a Matching-Law Based Account of Extinction Bursts to Humans.

Perspectives on behavior science·2026
See all related articles

Related Experiment Video

Updated: Jun 6, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

Behavior, Process, and Evolution in the Multiscale Molar Paradigm.

William M Baum1,2

  • 1Department of Environmental Science and Policy, University of California, Davis, CA USA.

Perspectives on Behavior Science
|June 5, 2026
PubMed
Summary
This summary is machine-generated.

The Multiscale Molar View integrates evolutionary and General Process Theory, defining behavior as extended activities within behavior-environment relations. This framework offers a unified understanding of behavior for research and clinical applications.

Keywords:
AllocationCovarianceFeedback systemInductionMolar view

More Related Videos

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

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

Published on: September 17, 2021

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

Related Experiment Videos

Last Updated: Jun 6, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

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

Published on: September 17, 2021

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

Area of Science:

  • Behavioral Science
  • Ontology
  • Evolutionary Theory

Background:

  • Traditional views often treat behavior as discrete events.
  • General Process Theory posits a world of processes, not static entities.
  • Evolutionary theory views species and individuals as processes focused on survival and reproduction.

Purpose of the Study:

  • To present the Multiscale Molar View of behavior.
  • To establish a monistic ontological basis for understanding behavior.
  • To integrate General Process Theory and evolutionary theory for behavioral analysis.

Main Methods:

  • Conceptual analysis integrating General Process Theory and evolutionary theory.
  • Applying process ontology to understand behavior-environment relations.
  • Examining the role of induction in behavioral processes.

Main Results:

  • Behavior is conceptualized as extended activities controlled by extended behavior-environment relations.
  • A unified framework is provided for understanding behavior in laboratory and real-world settings.
  • The integration supports more flexible clinical applications.

Conclusions:

  • The Multiscale Molar View offers a robust, process-based framework for behavior analysis.
  • This approach aligns with evolutionary principles and provides a monistic ontology.
  • It enhances understanding and application of behavioral phenomena across diverse contexts.