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Efficiency of The Carnot Cycle

Efficiency of The Carnot Cycle

The hypothetical Carnot cycle consists of an ideal gas subjected to two isothermal and two adiabatic processes. Since the internal energy of an ideal gas depends only on its temperature, which is the same before and after the completion of the Carnot cycle, there is no change in its internal energy. Hence, using the first law of thermodynamics, the total heat exchanged by the ideal gas equals the total work done. Thus, we can quantify the efficiency of the Carnot cycle via the heat exchanged...

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Related Experiment Video

Updated: Jul 18, 2025

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

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A Pilot Study Using Entropy for Optimizing Self-Pacing during a Marathon.

Florent Palacin^1,2, Luc Poinsard^1,2, Jean Renaud Pycke³

¹Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles Neuroscience Institut, 1070 Bruxelles, Belgium.

Entropy (Basel, Switzerland)

|August 26, 2023

Summary

This summary is machine-generated.

Marathon runners can improve performance by monitoring stride length entropy. A decrease in stride length information signals fatigue, helping runners self-pace effectively to avoid "hitting the wall".

Keywords:

Shannon entropy hitting the wall marathon running performance stride length

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Area of Science:

Sports Science
Human Physiology
Biomechanics

Background:

Marathon running involves self-pacing based on perceived exertion (RPE) rather than constant speed or heart rate.
Understanding how runners use physiological and mechanical signals for self-pacing remains unclear.

Purpose of the Study:

Investigate the relationship between information conveyed by running signals (Shannon Entropy), RPE, and marathon performance.
Hypothesize that reduced physiological or mechanical information impacts performance.

Main Methods:

Calculated Shannon Entropy for heart rate, speed, and stride length per kilometer.
Analyzed the association between stride length entropy, RPE, and performance outcomes.

Main Results:

Stride length exhibited the highest entropy among measured variables.
Reduced stride length entropy (below 50% of max, H=3.3) correlated significantly with "hard exertion" (RPE 15) between kilometers 22-40 and overall performance (p < 0.001).

Conclusions:

Stride length entropy is a key indicator of fatigue and performance in marathon runners.
Integrating stride length entropy feedback into devices like cardioGPS watches could enhance marathon performance.