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 and the Second Law of Thermodynamics

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

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 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.

Review and Preview

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...

Entropy and Solvation

Entropy and Solvation

The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...

The Second Law of Thermodynamics

The Second Law of Thermodynamics

In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...

You might also read

Related Articles

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

Sort by

Same author

Experimental investigation of Fe<sub>3</sub>O<sub>4</sub> nano-oil and outdoor temperature effects on a 5-ton R22 vapor compression chiller performance.

Scientific reports·2025

Same author

AI-based human whole-body posture-prediction in continuous load reaching/leaving activities.

Journal of biomechanics·2025

Same author

A toolbox for calculating quantitative image properties in aesthetics research.

Behavior research methods·2025

Same author

MicroRNA frontiers: Illuminating early detection paths in multiple sclerosis.

Multiple sclerosis and related disorders·2025

Same author

A Descriptive Study on "Renal Biopsy" Samples of Patients Admitted to Shahid Labbafinezhad Hospital (2019-2022).

Iranian journal of kidney diseases·2024

Same author

MicroRNAs regulating autophagy: opportunities in treating neurodegenerative diseases.

Frontiers in neuroscience·2024

Search research articles

Related Experiment Video

Updated: Aug 5, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Comparative Analysis of Preference in Contemporary and Earlier Texts Using Entropy Measures.

Mahdi Mohseni^1,2, Christoph Redies², Volker Gast¹

¹Department of English and American Studies, University of Jena, 07743 Jena, Germany.

Entropy (Basel, Switzerland)

|March 29, 2023

Summary

This summary is machine-generated.

Preferred texts, both historical and contemporary, exhibit higher unpredictability. However, sales figures for modern books correlate with global unpredictability, while historical canonization shows broader patterns.

Keywords:

Approximate Entropy POS tags Shannon Entropy bestseller books canonical texts contemporary texts fictional texts non-canonical texts non-fictional texts text classification

More Related Videos

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

A Two-interval Forced-choice Task for Multisensory Comparisons

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

Related Experiment Videos

Last Updated: Aug 5, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

A Two-interval Forced-choice Task for Multisensory Comparisons

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

Area of Science:

Computational linguistics
Literary studies
Textual aesthetics

Background:

Computational textual aesthetics research identifies textual features linked to reader preference in prose.
Previous studies suggest potential textual correlates of preference exist, but their temporal stability is unclear.

Purpose of the Study:

To investigate if textual correlates of preference differ between contemporary and historical (19th/early 20th century) texts.
To examine the relationship between text unpredictability and preference, operationalized as canonization (historical) and sales (contemporary).

Main Methods:

Analysis of parts of speech and sentence length distributions in prose texts from different eras.
Calculation of Shannon Entropy (global unpredictability) and Approximate Entropy (local surprise) as measures of textual unpredictability.
Comparison of entropy measures between canonical historical texts and contemporary bestsellers.

Main Results:

Preferred texts (canonical and bestsellers) across both periods demonstrate higher degrees of unpredictability.
Contemporary sales figures correlate with global unpredictability (Shannon Entropy) but not local surprise (Approximate Entropy).
Historical canonization shows a broader correlation with unpredictability compared to contemporary sales figures.

Conclusions:

Textual unpredictability is a time-invariant correlate of literary preference.
Period-specific factors influence how textual unpredictability relates to preference, with contemporary sales reflecting global text properties.
Findings highlight both enduring and time-dependent textual features associated with reader preference.