Special Issue "Back to the Origin: Addressing Physical Phenomena with Information-Theoretic Tools"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: 20 December 2022 | Viewed by 701

Special Issue Editors

Prof. Dr. Leonardo Ricci
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Guest Editor
Department of Physics, University of Trento, Trento, Italy
Interests: nonlinear dynamics; time series analysis; information dynamics; digital signal processing
Prof. Dr. Luca Faes
E-Mail Website
Guest Editor
Department of Energy, Information engineering and Mathematical models (DEIM), University of Palermo, 90128 Palermo, Italy
Interests: time series analysis; information dynamics; network physiology; cardiovascular neuroscience; brain connectivity
Special Issues, Collections and Topics in MDPI journals
Dr. Ludovico Minati
E-Mail Website
Guest Editor
Center for Mind/Brain Sciences (CIMeC), University of Trento, 38123 Trento, Italy
Interests: nonlinear dynamics; time series analysis; information dynamics; digital signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Entropy was first formulated in the deeply physical context of thermodynamics. Thereupon, the seminal works by Boltzmann, Shannon and others disclosed the awesome link of the “physical” entropy with statistics and information, thus triggering the field of information theory and its application to a wide spectrum of “less physical” fields, from physiology and neuroscience to economy and social sciences.

The urge of tackling issues in these fields has then stimulated the elaboration of information measures like approximate entropy, sample entropy, transfer entropy, permutation entropy and higher-order multivariate measures, along with theoretical works aiming at providing a sound mathematical background to these tools. This process is far from being definitely established, thus making information theory still a thriving research field.

In an apparent contradiction, a more limited, though increasing, number of works are being devoted to addressing purely physical problems with information-theoretical methods, thus providing a complementary approach to more conventional and established analytical techniques.

This Special Issue is especially devoted to contributions addressing applications of information theory in physical systems and problems. Nevertheless, contributions concerning new methods as well as works addressing complexity and stemming from other research fields, from biomedical engineering and neuroscience to geophysics and climatology, in which both the physical aspect and the information-theoretical one are apparent, are also welcome.

Prof. Dr. Leonardo Ricci
Prof. Dr. Luca Faes
Dr. Ludovico Minati
Guest Editors

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 1800 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
  • relative entropy
  • mutual information
  • information dynamics
  • multivariate information
  • empirical estimators

Published Papers (1 paper)

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Research

Article
Information Dynamics of Electric Field Intensity before and during the COVID-19 Pandemic
Entropy 2022, 24(5), 726; https://doi.org/10.3390/e24050726 - 20 May 2022
Viewed by 535
Abstract
This work investigates the temporal statistical structure of time series of electric field (EF) intensity recorded with the aim of exploring the dynamical patterns associated with periods with different human activity in urban areas. The analyzed time series were obtained from a sensor [...] Read more.
This work investigates the temporal statistical structure of time series of electric field (EF) intensity recorded with the aim of exploring the dynamical patterns associated with periods with different human activity in urban areas. The analyzed time series were obtained from a sensor of the EMF RATEL monitoring system installed in the campus area of the University of Novi Sad, Serbia. The sensor performs wideband cumulative EF intensity monitoring of all active commercial EF sources, thus including those linked to human utilization of wireless communication systems. Monitoring was performed continuously during the years 2019 and 2020, allowing us to investigate the effects on the patterns of EF intensity of varying conditions of human mobility, including regular teaching and exam activity within the campus, as well as limitations to mobility related to the COVID-19 pandemic. Time series analysis was performed using both simple statistics (mean and variance) and combining the information-theoretic measure of information storage (IS) with the method of surrogate data to quantify the regularity of EF dynamic patterns and detect the presence of nonlinear dynamics. Moreover, to assess the possible coexistence of dynamic behaviors across multiple temporal scales, IS analysis was performed over consecutive observation windows lasting one day, week, month, and year, respectively coarse grained at time scales of 6 min, 30 min, 2 h, and 1 day. Our results document that the EF intensity patterns of variability are modulated by the movement of people at daily, weekly, and monthly scales, and are blunted during periods of restricted mobility related to the COVID-19 pandemic. Mobility restrictions also affected significantly the regularity of the EF intensity time series, resulting in lower values of IS observed simultaneously with a loss of nonlinear dynamics. Thus, our analysis can be useful to investigate changes in the global patterns of human mobility both during pandemics or other types of events, and from this perspective may serve to implement strategies for safety assessment and for optimizing the design of networks of EF sensors. Full article
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