Jove
Visualize
Contact Us

Related Concept Videos

The Sense of Self: Reflected Self-Appraisal and Social Comparison02:57

The Sense of Self: Reflected Self-Appraisal and Social Comparison

56.1K
According to Charles Cooley, we base our image on what we think other people see (Cooley 1902). We imagine how we must appear to others, then react to this speculation. We don certain clothes, prepare our hair in a particular manner, wear makeup, use cologne, and the like—all with the notion that our presentation of ourselves is going to affect how others perceive us. We expect a certain reaction, and, if lucky, we get the one we desire and feel good about it. But more than that, Cooley...
56.1K
What is Energy?04:10

What is Energy?

59.2K
The universe is composed of matter in different forms, and all forms of matter contain energy.  The different forms of energy on Earth originate from the Sun — the ultimate energy source. Plants capture light energy from the Sun, and, via the process of photosynthesis, convert it into chemical energy. This stored energy from plants can be harnessed in many ways. For example, eating plant products as food provides energy for our body to function, and burning wood or coal (fossilized...
59.2K
Free Energy01:21

Free Energy

52.2K
Free energy—abbreviated as G for the scientist Gibbs who discovered it—is a measurement of useful energy that can be extracted from a reaction to do work. It is the energy in a chemical reaction that is available after entropy is accounted for. Reactions that take in energy are considered endergonic and reactions that release energy are exergonic. Plants carry out endergonic reactions by taking in sunlight and carbon dioxide to produce glucose and oxygen. Animals, in turn, break...
52.2K
Cell Potential and Free Energy02:58

Cell Potential and Free Energy

46.6K
Thermodynamics of a Redox Reaction
Thermodynamics is the branch of physics dealing with the relationship between heat and other forms of energy. In an electrochemical cell, chemical energy is converted into electrical energy.
Thus, a link can be predicted between cell potential, free energy change, and the equilibrium constant for the reaction. Cell potential can also be measured as the oxidant or the reducing strength, and similar acid-base strength measures are reflected in equilibrium...
46.6K
Internal Energy02:00

Internal Energy

36.8K
The total of all possible kinds of energy present in a substance is called the internal energy (U), sometimes symbolized as E. Suppose a system with initial internal energy, Uinitial, undergoes a change in energy (transfer of work or heat), and the final internal energy of the system is Ufinal. Change in internal energy equals the difference between Ufinal and Uinitial.
36.8K
Energy Basics02:27

Energy Basics

47.8K
Chemical reactions, such as those that occur when you light a match, involve changes in energy as well as matter.
47.8K

You might also read

Related Articles

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

Sort by
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
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 Experiment Video

Updated: Feb 8, 2026

Processing of Primary Brain Tumor Tissue for Stem Cell Assays and Flow Sorting
08:14

Processing of Primary Brain Tumor Tissue for Stem Cell Assays and Flow Sorting

Published on: September 25, 2012

18.6K

Sorting processes with energy-constrained comparisons.

Barbara Geissmann1, Paolo Penna1

  • 1Department of Computer Science, ETH Zurich, Zurich, Switzerland.

Physical Review. E
|June 17, 2018
PubMed
Summary
This summary is machine-generated.

Simple sorting algorithms using probabilistic comparisons show adjacent swaps can outperform random swaps. This study analyzes Markov chains to understand sorting efficiency under comparison errors.

More Related Videos

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

15.2K
Fluorescence Activated Cell Sorting of Plant Protoplasts
13:35

Fluorescence Activated Cell Sorting of Plant Protoplasts

Published on: February 18, 2010

25.5K

Related Experiment Videos

Last Updated: Feb 8, 2026

Processing of Primary Brain Tumor Tissue for Stem Cell Assays and Flow Sorting
08:14

Processing of Primary Brain Tumor Tissue for Stem Cell Assays and Flow Sorting

Published on: September 25, 2012

18.6K
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

15.2K
Fluorescence Activated Cell Sorting of Plant Protoplasts
13:35

Fluorescence Activated Cell Sorting of Plant Protoplasts

Published on: February 18, 2010

25.5K

Area of Science:

  • Computer Science
  • Algorithm Analysis
  • Probability Theory

Background:

  • Sorting algorithms are fundamental in computer science.
  • Probabilistic comparator models introduce realism by accounting for comparison errors.
  • Markovian processes model the behavior of these randomized sorting algorithms.

Purpose of the Study:

  • To analyze simple sorting algorithms based on a probabilistic comparator model.
  • To investigate the efficiency of algorithms that compare adjacent elements versus arbitrary elements.
  • To understand the underlying Markov chains and their properties, including stationary distributions and mixing times.

Main Methods:

  • Development of a probabilistic comparator model where errors depend on comparison effort and element difference.
  • Modeling sorting algorithms as Markovian processes.
  • Analysis of Markov chains, including nonreversible chains, to determine stationary distributions and mixing times.

Main Results:

  • The algorithm repeatedly comparing adjacent elements often outperforms the one making arbitrary comparisons.
  • The adjacent-comparison algorithm produces better-sorted sequences in the long run.
  • Bounds on stationary distributions and mixing times were provided for restricted cases, despite challenges with nonreversible chains.

Conclusions:

  • Simple sorting algorithms with probabilistic comparisons exhibit complex behaviors.
  • Prioritizing adjacent comparisons can be a more efficient strategy than arbitrary comparisons in certain scenarios.
  • Further analysis of nonreversible Markov chains is needed for a complete understanding of these sorting processes.