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Related Concept Videos

Entropy02:39

Entropy

Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression results...
Uncertainty: Overview00:59

Uncertainty: Overview

In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
Entropy Change in Reversible Processes01:10

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.
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
Entropy and the Second Law of Thermodynamics01:26

Entropy and the Second Law of Thermodynamics

Consider an isolated system in which a hot object is placed in contact with a cold one. This is an irreversible process that eventually leads both objects to reach the same equilibrium temperature. It is crucial to note that the constituents of any substance exhibit increased disorder at higher temperatures. As a cold substance absorbs heat, its constituents become more disordered. The energy transfer from a hotter object to a cooler one increases the system's disorder or randomness. This...

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Related Experiment Video

Updated: May 14, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

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Published on: August 30, 2013

Fractal fluctuations and complexity: current debates and future challenges.

Didier Delignieres1, Vivien Marmelat

  • 1EA 2991 Movement to Health, Euromov, University Montpellier 1, France. didier.delignieres@univ-montp1.fr

Critical Reviews in Biomedical Engineering
|January 30, 2013
PubMed
Summary
This summary is machine-generated.

This review explores the link between system complexity and 1/f fluctuations. Understanding fractal fluctuations offers new insights into emergent macroscopic functions and theories of motor control.

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Area of Science:

  • Complexity science
  • Nonlinear dynamics
  • Systems theory

Background:

  • Complexity remains poorly understood, even in science.
  • Advances link system complexity to 1/f fluctuations in macroscopic behavior.
  • This connection opens new avenues for fundamental and applied research.

Purpose of the Study:

  • To review the theoretical debate on the origins of 1/f fluctuations.
  • To highlight hypotheses connecting complexity and fractal fluctuations.
  • To clarify conceptual oppositions and discuss implications for motor control and psychological processes.

Main Methods:

  • Literature review of theoretical and experimental advances.
  • Focus on recent hypotheses linking complexity and fractal fluctuations.
  • Analysis of conceptual frameworks (idiosyncratic vs. nomothetic, global vs. componential).

Main Results:

  • 1/f fluctuations are a key indicator of system complexity.
  • Fractal fluctuations provide a framework for understanding emergent functions.
  • The complexity-fluctuation link challenges existing theories.

Conclusions:

  • The relationship between complexity and 1/f fluctuations offers a novel perspective on emergent phenomena.
  • This approach has significant implications for understanding motor control and psychological processes.
  • Future developments are anticipated in physical medicine and rehabilitation.