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Entropy
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Entropy and Organization in Natural and Social Systems
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Entropy and Organization in Natural and Social Systems

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (30 July 2023) | Viewed by 15683

Special Issue Editor

Dr. Ashwin Vaidya

E-Mail Website
Guest Editor
Department of Mathematics, Montclair State University, Montclair, NJ 07043, USA
Interests: mathematical fluid mechanics; non-linear partial differential equations; hydrodynamic stability; non-Newtonian fluid mechanics; fluid–structure interaction; experimental fluid mechanics; philosophy of science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

This issue is devoted to themes of organization and emergence, which are inherent traits of any complex system out of equilibrium. Complexity and self-organization are observed across systems or scales, be they physical, biological, economic, or sociological resulting in a quest for a fundamental unifying explanation that bridges the divide between living and non-living systems. The “immutable laws of thermodynamics”, as Sir Arthur Eddington put it, have proved to be robust and expansive in their explanatory power, as several articles in this very journal will indicate. The associated ideas of energy, entropy, equilibrium, complexity, etc. are now part of the lexicon of more than the natural sciences; they have invaded fields such as economics, education, psychology, sociology, sustainability, and political science, among others. The works of Nicolas Georgescu-Rogen in economics, Kenneth Bailey in sociology, Stephen Coleman in political science, Rudolf Arnheim in art, and William Doll in education are some classic examples of diffusion of thermodynamics beyond its birth-home in physics. This Special Issue is focused on understanding the diverse ways in which we recognize, define and discuss structures, patterns, and dynamics in different systems and their connection to thermodynamic principles by bringing together scholarship from different fields (natural and social sciences) to help to foster an interdisciplinary dialogue. We invite contributions from researchers in any discipline working on topics related to these topics. Theoretical, experimental, field data-driven, philosophical or even historical articles are welcome, provided they are relevant, novel, and abide by the journal requirements. Since the issue aims to bridge the disciplinary divide, we ask that authors clearly define terms and the approaches taken in a manner comprehensible to scholars from other fields. All papers will undergo rigorous peer-review.

Dr. Ashwin Vaidya
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • entropy
  • organization
  • emergence
  • systems theory
  • steady state
  • pattern formation
  • social entropy
  • out of equilibrium

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Related Special Issue

Published Papers (6 papers)

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Research

12 pages, 256 KiB  
Article
Informational Resilience in the Human Cognitive Ecology
by Rasmus Gahrn-Andersen
Entropy 2023, 25(9), 1247; https://doi.org/10.3390/e25091247 - 22 Aug 2023
Cited by 1 | Viewed by 1191
Abstract
Resilience is a basic trait of cognitive systems and fundamentally connected to their autopoietic organization. It plays a vital role in maintaining the identity of cognitive systems in the face of external threats and perturbances. However, when examining resilience in the context of [...] Read more.
Resilience is a basic trait of cognitive systems and fundamentally connected to their autopoietic organization. It plays a vital role in maintaining the identity of cognitive systems in the face of external threats and perturbances. However, when examining resilience in the context of autopoiesis, an overlooked issue arises: the autopoietic theory formulated by Maturana and Varela (1980) renders traditional Shannon information obsolete, highlighting that information should not be ascribed a role in cognitive systems in a general sense. This paper examines the current situation and suggests a possible way forward by exploring an affordance-based view on information, derived from radical cognitive science, which is exempted from Maturana and Varela’s critique. Specifically, it argues that the impact of social influence on affordance use is crucial when considering how resilience can manifest in informational relations pertaining to the human cognitive ecology. Full article
(This article belongs to the Special Issue Entropy and Organization in Natural and Social Systems)
24 pages, 9960 KiB  
Communication
Geometric Insights into the Multivariate Gaussian Distribution and Its Entropy and Mutual Information
by Dah-Jing Jwo, Ta-Shun Cho and Amita Biswal
Entropy 2023, 25(8), 1177; https://doi.org/10.3390/e25081177 - 7 Aug 2023
Cited by 5 | Viewed by 2924
Abstract
In this paper, we provide geometric insights with visualization into the multivariate Gaussian distribution and its entropy and mutual information. In order to develop the multivariate Gaussian distribution with entropy and mutual information, several significant methodologies are presented through the discussion, supported by [...] Read more.
In this paper, we provide geometric insights with visualization into the multivariate Gaussian distribution and its entropy and mutual information. In order to develop the multivariate Gaussian distribution with entropy and mutual information, several significant methodologies are presented through the discussion, supported by illustrations, both technically and statistically. The paper examines broad measurements of structure for the Gaussian distributions, which show that they can be described in terms of the information theory between the given covariance matrix and correlated random variables (in terms of relative entropy). The content obtained allows readers to better perceive concepts, comprehend techniques, and properly execute software programs for future study on the topic’s science and implementations. It also helps readers grasp the themes’ fundamental concepts to study the application of multivariate sets of data in Gaussian distribution. The simulation results also convey the behavior of different elliptical interpretations based on the multivariate Gaussian distribution with entropy for real-world applications in our daily lives, including information coding, nonlinear signal detection, etc. Involving the relative entropy and mutual information as well as the potential correlated covariance analysis, a wide range of information is addressed, including basic application concerns as well as clinical diagnostics to detect the multi-disease effects. Full article
(This article belongs to the Special Issue Entropy and Organization in Natural and Social Systems)
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24 pages, 5958 KiB  
Article
Foraging Dynamics and Entropy Production in a Simulated Proto-Cell
by Benjamin De Bari, Dilip K. Kondepudi and James A. Dixon
Entropy 2022, 24(12), 1793; https://doi.org/10.3390/e24121793 - 8 Dec 2022
Cited by 1 | Viewed by 1514
Abstract
All organisms depend on a supply of energetic resources to power behavior and the irreversible entropy-producing processes that sustain them. Dissipative structure theory has often been a source of inspiration for better understanding the thermodynamics of biology, yet real organisms are inordinately more [...] Read more.
All organisms depend on a supply of energetic resources to power behavior and the irreversible entropy-producing processes that sustain them. Dissipative structure theory has often been a source of inspiration for better understanding the thermodynamics of biology, yet real organisms are inordinately more complex than most laboratory systems. Here we report on a simulated chemical dissipative structure that operates as a proto cell. The simulated swimmer moves through a 1D environment collecting resources that drive a nonlinear reaction network interior to the swimmer. The model minimally represents properties of a simple organism including rudimentary foraging and chemotaxis and an analog of a metabolism in the nonlinear reaction network. We evaluated how dynamical stability of the foraging dynamics (i.e., swimming and chemotaxis) relates to the rate of entropy production. Results suggested a relationship between dynamical steady states and entropy production that was tuned by the relative coordination of foraging and metabolic processes. Results include evidence in support of and contradicting one formulation of a maximum entropy production principle. We discuss the status of this principle and its relevance to biology. Full article
(This article belongs to the Special Issue Entropy and Organization in Natural and Social Systems)
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25 pages, 3408 KiB  
Article
Lexicons of Key Terms in Scholarly Texts and Their Disciplinary Differences: From Quantum Semantics Construction to Relative-Entropy-Based Comparisons
by Ismo Koponen and Ilona Södervik
Entropy 2022, 24(8), 1058; https://doi.org/10.3390/e24081058 - 31 Jul 2022
Cited by 1 | Viewed by 1958
Abstract
Complex networks are often used to analyze written text and reports by rendering texts in the form of a semantic network, forming a lexicon of words or key terms. Many existing methods to construct lexicons are based on counting word co-occurrences, having the [...] Read more.
Complex networks are often used to analyze written text and reports by rendering texts in the form of a semantic network, forming a lexicon of words or key terms. Many existing methods to construct lexicons are based on counting word co-occurrences, having the advantage of simplicity and ease of applicability. Here, we use a quantum semantics approach to generalize such methods, allowing us to model the entanglement of terms and words. We show how quantum semantics can be applied to reveal disciplinary differences in the use of key terms by analyzing 12 scholarly texts that represent the different positions of various disciplinary schools (of conceptual change research) on the same topic (conceptual change). In addition, attention is paid to how closely the lexicons corresponding to different positions can be brought into agreement by suitable tuning of the entanglement factors. In comparing the lexicons, we invoke complex network-based analysis based on exponential matrix transformation and use information theoretic relative entropy (Jensen–Shannon divergence) as the operationalization of differences between lexicons. The results suggest that quantum semantics is a viable way to model the disciplinary differences of lexicons and how they can be tuned for a better agreement. Full article
(This article belongs to the Special Issue Entropy and Organization in Natural and Social Systems)
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25 pages, 2247 KiB  
Article
Entropy-Based Behavioural Efficiency of the Financial Market
by Emil Dinga, Camelia Oprean-Stan, Cristina-Roxana Tănăsescu, Vasile Brătian and Gabriela-Mariana Ionescu
Entropy 2021, 23(11), 1396; https://doi.org/10.3390/e23111396 - 24 Oct 2021
Cited by 6 | Viewed by 2350
Abstract
The most known and used abstract model of the financial market is based on the concept of the informational efficiency (EMH) of that market. The paper proposes an alternative which could be named the behavioural efficiency of the financial market, which is based [...] Read more.
The most known and used abstract model of the financial market is based on the concept of the informational efficiency (EMH) of that market. The paper proposes an alternative which could be named the behavioural efficiency of the financial market, which is based on the behavioural entropy instead of the informational entropy. More specifically, the paper supports the idea that, in the financial market, the only measure (if any) of the entropy is the available behaviours indicated by the implicit information. Therefore, the behavioural entropy is linked to the concept of behavioural efficiency. The paper argues that, in fact, in the financial markets, there is not a (real) informational efficiency, but there exists a behavioural efficiency instead. The proposal is based both on a new typology of information in the financial market (which provides the concept of implicit information—that is, that information ”translated” by the economic agents from observing the actual behaviours) and on a non-linear (more exactly, a logistic) curve linking the behavioural entropy to the behavioural efficiency of the financial markets. Finally, the paper proposes a synergic overcoming of both EMH and AMH based on the new concept of behavioural entropy in the financial market. Full article
(This article belongs to the Special Issue Entropy and Organization in Natural and Social Systems)
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26 pages, 2784 KiB  
Article
A Network Theory Approach to Curriculum Design
by John O’Meara and Ashwin Vaidya
Entropy 2021, 23(10), 1346; https://doi.org/10.3390/e23101346 - 15 Oct 2021
Cited by 7 | Viewed by 3801
Abstract
In this paper we hypothesize that education, especially at the scale of curriculum, should be treated as a complex system composed of different ideas and concepts which are inherently connected. Therefore, the task of a good teacher lies in elucidating these connections and [...] Read more.
In this paper we hypothesize that education, especially at the scale of curriculum, should be treated as a complex system composed of different ideas and concepts which are inherently connected. Therefore, the task of a good teacher lies in elucidating these connections and helping students make their own connections. Such a pedagogy allows students to personalize learning and strive to be ‘creative’ and make meaning out of old ideas. The novel contribution of this work lies in the mathematical approach we undertake to verify our hypothesis. We take the example of a precalculus course curriculum to make our case. We treat textbooks as exemplars of a specific pedagogy and map several texts into networks of isolated (nodes) and interconnected concepts (edges) thereby permitting computations of metrics which have much relevance to the education theorists, teachers and all others involved in the field of education. We contend that network metrics such as average path length, clustering coefficient and degree distribution provide valuable insights to teachers and students about the kind of pedagogy which encourages good teaching and learning. Full article
(This article belongs to the Special Issue Entropy and Organization in Natural and Social Systems)
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