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Entropy
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Stability and Flexibility in Dynamic Systems: Novel Research Pathways
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Stability and Flexibility in Dynamic Systems: Novel Research Pathways

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

Deadline for manuscript submissions: 15 September 2024 | Viewed by 2219

Special Issue Editors

Dr. Giulio de Felice

E-Mail Website
Guest Editor
1. Faculty of Psychology, University of Chichester, Xenophon College, Chichester PO19 6PE, UK
2. Faculty of Literature and Philosophy, Sapienza University of Rome, 00185 Roma, Italy
Interests: psychotherapy; psychopathology; change processes; mind–body interaction; dynamic systems
Dr. Riccardo Pernice

E-Mail Website
Guest Editor
Department of Engineering, University of Palermo, 90128 Palermo, Italy
Interests: portable/wearable monitoring systems; electrocardiographic (ECG) and photoplethysmographic (PPG) acquisition sensors and systems; biomedical signal processing; autonomic nervous system; heart rate variability (HRV) analysis; brain–heart interactions
Special Issues, Collections and Topics in MDPI journals
Dr. Yuri Antonacci

E-Mail Website
Guest Editor
Department of Engineering, University of Palermo, 90128 Palermo, Italy
Interests: time series analysis; complex systems; network physiology; EEG

Special Issue Information

Dear Colleagues,

Complexity tackles a broad set of phenomena with a unifying approach when they occur in systems consisting of several subunits. Until recently, the predominant idea was that the collective behaviour of a complex system could be understood and predicted by studying the dynamics of all the subunits, considering each one in isolation. However, this approach of analysis proved to be insufficient when studying emergent behaviours, i.e., all the properties of the system that arise from the interaction among different components of the system at hand. Emergent properties reflect the existence of different levels of description following their specific laws expressed in terms of appropriately defined variables. Once these latest are identified, the literature highlights the importance of investigating two main dimensions of the system at hand: stability and flexibility, that is, correlation and variance (for a review: Gorban, A. N., Tyukina, T. A., Pokidysheva, L. I., & Smirnova, E. V. 2021. Dynamic and thermodynamic models of adaptation. Physics of life reviews, 37, 17-64).

For example,

-In biology and chemistry, the monitoring of increases in flexibility in gene expression of a cancer cell demonstrated the possibility of identifying the precursors of its phenotype change (Zimatore, G., Tsuchiya, M., Hashimoto, M., Kasperski, A., & Giuliani, A. 2021. Self-organization of whole-gene expression through coordinated chromatin structural transition. Biophysics Reviews, 2, 3);

-In medicine, correlations and variance of physiological parameters have been used to predict myocardial infarction (Strygina, S. O., Dement’ev, S. N., Uskov, V. M., & Chernyshova, G. I. 2000. Dynamics of the system of correlations between physiological parameters in patients after myocardial infarction. In Mathematics, Computer, Education, Proceedings of Conference No. 7, pp. 685-689);

-In psychotherapy, the stability and flexibility of psychotherapy processes have been used to predict the final outcome of the treatment (de Felice, G., Giuliani, A., Pincus, D., Scozzari, A., Berardi, V., Kratzer, L., ... & Schiepek, G. 2022. Stability and flexibility in psychotherapy process predict outcome. Acta Psychologica, 227, 103604);

-In geopolitics, the stability and flexibility of different regions of the world have been used to predict potential international crises (de Felice, G., Tutal, N., & Sciaraffa, N. (2023). Geopolitical aspects of COVID-19 vaccines distribution. EUR J ENV PUBLIC HLT. 2023; 7 (3): em0132; Rybnikov, S. R., Rybnikova, N. A., & Portnov, B. A. (2017). Public fears in Ukrainian society: Are crises predictable?. Psychology and Developing Societies, 29(1), 98-123);

-In finance, the stability and flexibility of the stock market have been used to predict financial crises (Gorban AN, Smirnova EV, Tyukina TA. Correlations, risk and crisis: from physiology to finance. Physica A 2010;389, 16:3193–217).

Therefore, this Special Issue aims to collect original articles, opinions and review papers focusing on novel research pathways concerning stability and flexibility in dynamic systems. Interdisciplinary contributions are welcomed:

  • Ranging from methodological to applicative perspectives;
  • Based on a dynamic system approach;
  • Promoting research advancements regarding the interaction among stability and flexibility in a dynamic system.

Potential topics include, but are not limited to:

  • Novel methodological approaches aimed at improving existing quantifiers of stability and flexibility of a dynamic system;
  • Applications of complexity-based measures in physiological or clinical settings;
  • Detection and monitoring of phase transitions;
  • Novel machine learning methods for classification using complexity-based features;
  • Assessment of stability and flexibility of networks;
  • Changes in stability and flexibility during phase transitions.

Dr. Giulio de Felice
Dr. Riccardo Pernice
Dr. Yuri Antonacci
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 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

  • complexity
  • network analysis
  • phase transitions
  • stability
  • flexibility
  • linear and nonlinear prediction
  • biomedical signal processing
  • machine/deep learning
  • dynamic systems

Published Papers (2 papers)

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Research

28 pages, 553 KiB  
Article
Almost Surely Exponential Convergence Analysis of Time Delayed Uncertain Cellular Neural Networks Driven by Liu Process via Lyapunov–Krasovskii Functional Approach
by Chengqiang Wang, Zhifu Jia, Yulin Zhang and Xiangqing Zhao
Entropy 2023, 25(11), 1482; https://doi.org/10.3390/e25111482 - 26 Oct 2023
Cited by 1 | Viewed by 783
Abstract
As with probability theory, uncertainty theory has been developed, in recent years, to portray indeterminacy phenomena in various application scenarios. We are concerned, in this paper, with the convergence property of state trajectories to equilibrium states (or fixed points) of time delayed uncertain [...] Read more.
As with probability theory, uncertainty theory has been developed, in recent years, to portray indeterminacy phenomena in various application scenarios. We are concerned, in this paper, with the convergence property of state trajectories to equilibrium states (or fixed points) of time delayed uncertain cellular neural networks driven by the Liu process. By applying the classical Banach’s fixed-point theorem, we prove, under certain conditions, that the delayed uncertain cellular neural networks, concerned in this paper, have unique equilibrium states (or fixed points). By carefully designing a certain Lyapunov–Krasovskii functional, we provide a convergence criterion, for state trajectories of our concerned uncertain cellular neural networks, based on our developed Lyapunov–Krasovskii functional. We demonstrate under our proposed convergence criterion that the existing equilibrium states (or fixed points) are exponentially stable almost surely, or equivalently that state trajectories converge exponentially to equilibrium states (or fixed points) almost surely. We also provide an example to illustrate graphically and numerically that our theoretical results are all valid. There seem to be rare results concerning the stability of equilibrium states (or fixed points) of neural networks driven by uncertain processes, and our study in this paper would provide some new research clues in this direction. The conservatism of the main criterion obtained in this paper is reduced by introducing quite general positive definite matrices in our designed Lyapunov–Krasovskii functional. Full article
(This article belongs to the Special Issue Stability and Flexibility in Dynamic Systems: Novel Research Pathways)
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22 pages, 3335 KiB  
Article
Features of Self-Organization during the Process of Mindfulness-Based Stress Reduction: A Single Case Study
by Günter Schiepek, Tatjana Marinell, Wolfgang Aichhorn, Helmut Schöller and Michael E. Harrer
Entropy 2023, 25(10), 1403; https://doi.org/10.3390/e25101403 - 30 Sep 2023
Viewed by 1013
Abstract
Compared to the extensive evidence of the effectiveness of mindfulness-based interventions, there is only a limited understanding of their mechanisms of change. The three aims of this study are (1) to identify features of self-organization during the process (e.g., pattern transitions), (2) to [...] Read more.
Compared to the extensive evidence of the effectiveness of mindfulness-based interventions, there is only a limited understanding of their mechanisms of change. The three aims of this study are (1) to identify features of self-organization during the process (e.g., pattern transitions), (2) to obtain an impression of the effects of continuous self-assessments and feedback sessions on mindfulness-related stress reduction, and (3) to test the feasibility of high-frequency process monitoring and process feedback. Concerning aim (1), the specific hypothesis is that change will occur as a cascade of discontinuous pattern transitions emerging spontaneously in the sense of not being a reaction to external input. This single case study describes changing patterns of multiple time series that were produced by app-based daily self-assessments during and after an 8-week mindfulness-based stress reduction program. After this MBSR program, the participant (a female nurse) continued the self-assessment and the mindfulness practice for a further 10 months. The results confirm findings on the positive effects of mindfulness programs for healthcare professionals, especially on coping with work-related stress. The analysis of the time series data supports the hypothesis of self-organization as a possible mechanism of change manifesting as a cascade of phase transitions in the dynamics of a biopsychosocial system. At the end of the year, the participant reported a beneficial impact of daily monitoring and systematic feedback on the change process. The results underline the feasibility and usefulness of continuous high-frequency monitoring during and after mindfulness interventions. Full article
(This article belongs to the Special Issue Stability and Flexibility in Dynamic Systems: Novel Research Pathways)
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