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

Entropy Change in Reversible Processes

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.

Standard Entropy Change for a Reaction

Standard Entropy Change for a Reaction

Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.

Free Energy Changes for Nonstandard States

Free Energy Changes for Nonstandard States

The free energy change for a process taking place with reactants and products present under nonstandard conditions (pressures other than 1 bar; concentrations other than 1 M) is related to the standard free energy change according to this equation:

Molecular Kinetic Energy

Molecular Kinetic Energy

The word "gas" comes from the Flemish word meaning "chaos," first used to describe vapors by the chemist J. B. van Helmont. Consider a container filled with gas, with a continuous and random motion of molecules. During collisions, the velocity component parallel to the wall is unchanged, and the component perpendicular to the wall reverses direction but does not change in magnitude. If the molecule’s velocity changes in the x-direction, then its momentum is changed. During the short time of the...

Potential-Energy Criterion for Equilibrium

Potential-Energy Criterion for Equilibrium

Potential energy or potential function plays an essential role in determining the stability of a mechanical system. If a system is subjected to both gravitational and elastic forces, the potential function of the system can be expressed as the algebraic sum of gravitational and elastic potential energy. If the system is in equilibrium and is displaced by a small amount, then the work done on the system equals the negative of the change in the system's potential energy from the initial to the...

Propagation of Uncertainty from Random Error

Propagation of Uncertainty from Random Error

An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...

You might also read

Related Articles

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

Sort by

Same author

Rarely categorical, highly separable representations along the cortical hierarchy.

Nature·2026

Same author

Sparse component analysis: A method that uncovers separable computations within neural population activity.

Neuron·2026

Same author

Beast3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting.

ArXiv·2026

Same author

Limited Benefits of Oyster Aquaculture on Water Clarity in Two Rhode Island Salt Ponds.

Coasts (Basel, Switzerland)·2026

Same author

Lightning Pose 3D: an uncertainty-aware framework for data-efficient multi-view animal pose estimation.

bioRxiv : the preprint server for biology·2026

Same author

Computational optimization of two-photon holographic stimulation sites<i>in vivo</i>.

Journal of neural engineering·2026

Search research articles

Related Experiment Video

Updated: Jun 24, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Maximally reliable Markov chains under energy constraints.

Sean Escola¹, Michael Eisele, Kenneth Miller

¹Center for Theoretical Neuroscience and M.D./Ph.D. Program, Columbia University, New York, NY 10032, U.S.A. gse3@columbia.edu

Neural Computation

|March 19, 2009

Summary

Biological systems enhance signal reliability using multistep processing. Optimal signal generation occurs in irreversible linear chains, with reliability limited by energy costs, suggesting a trade-off between signal fidelity and energetic demands.

Related Experiment Videos

Last Updated: Jun 24, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Systems biology
Theoretical physics
Information theory

Background:

Biological systems often require highly reliable signal generation.
High variability in signal output can degrade signal-to-noise ratios.
Multistep processing is observed in biological signaling pathways.

Purpose of the Study:

To mathematically determine the optimal structure for reliable signal generation in multistate systems.
To investigate the influence of energy constraints on signal reliability.
To understand the design principles behind biological signaling cascades.

Main Methods:

Mathematical modeling of multistate systems using Markov chains.
Proof of reliability maximization under specific topological and transition rate conditions.
Numerical optimization of system topology considering energy cost functions.

Main Results:

Signal reliability is maximized in irreversible linear chains where each state generates an equal signal fraction.
Increasing the number of states can arbitrarily increase theoretical reliability.
Energy constraints impose practical limits on the number of states, favoring linear architectures.

Conclusions:

Biological systems likely employ linear architectures for signal processing to balance reliability and energy efficiency.
The number of processing steps in biological systems is constrained by available energy.
Irreversible linear chains represent a fundamental design principle for reliable signal generation in physical and biological systems.