Announcements

We are pleased to announce the launch of a project entitled "Editor's Choice Articles" in Entropy (ISSN: 1099-4300). The list of high-quality and interesting papers that were specifically recommended by our Editorial Board Members can be found at the following link: https://www.mdpi.com/journal/entropy/editors_choice. We have selected 16 of these papers to display here. The paper list is as follows:

• “High-Entropy Alloys for Advanced Nuclear Applications”
  Ed J. Pickering, Alexander W. Carruthers, Paul J. Barron, Simon C. Middleburgh, David E. J. Armstrong and Amy S. Gandy
  Available online: https://www.mdpi.com/1099-4300/23/1/98

• “Applications of Distributed-Order Fractional Operators: A Review”
  Wei Ding, Sansit Patnaik, Sai Sidhardh and Fabio Semperlotti
  Available online: https://www.mdpi.com/1099-4300/23/1/110

• “The Entropy Universe”
  Maria Ribeiro, Teresa Henriques, Luísa Castro, André Souto, Luís Antunes, Cristina Costa-Santos and Andreia Teixeira
  Available online: https://www.mdpi.com/1099-4300/23/2/222

• “Deep Task-Based Quantization”
  Nir Shlezinger and Yonina C. Eldar
  Available online: https://www.mdpi.com/1099-4300/23/1/104

• “Global Sensitivity Analysis Based on Entropy: From Differential Entropy to Alternative Measures”
  Zdeněk Kala
  Available online: https://www.mdpi.com/1099-4300/23/6/778

• “Information Theory for Agents in Artificial Intelligence, Psychology, and Economics”
  Michael S. Harré
  Available online: https://www.mdpi.com/1099-4300/23/3/310

• “Mechanism Integrated Information”
  Leonardo S. Barbosa, William Marshall, Larissa Albantakis and Giulio Tononi
  Available online: https://www.mdpi.com/1099-4300/23/3/362

• “Information Geometric Theory in the Prediction of Abrupt Changes in System Dynamics”
  Adrian-Josue Guel-Cortez and Eun-jin Kim
  Available online: https://www.mdpi.com/1099-4300/23/6/694

• “The Principle of Covariance and the Hamiltonian Formulation of General Relativity”
  Massimo Tessarotto and Claudio Cremaschini
  Available online: https://www.mdpi.com/1099-4300/23/2/215

• “Information Structures for Causally Explainable Decisions”
  Louis Anthony Cox, Jr.
  Available online: https://www.mdpi.com/1099-4300/23/5/601

• “Ordinal Pattern Dependence in the Context of Long-Range Dependence”
  Ines Nüßgen and Alexander Schnurr
  Available online: https://www.mdpi.com/1099-4300/23/6/670

• “Information and Self-Organization II: Steady State and Phase Transition”
  Hermann Haken and Juval Portugali
  Available online: https://www.mdpi.com/1099-4300/23/6/707

• “Causality and Information Transfer Between the Solar Wind and the Magnetosphere–Ionosphere System”
  Pouya Manshour, Georgios Balasis, Giuseppe Consolini, Constantinos Papadimitriou and Milan Paluš
  Available online: https://www.mdpi.com/1099-4300/23/4/390

• “Why Do Big Data and Machine Learning Entail the Fractional Dynamics?”
  Haoyu Niu, YangQuan Chen and Bruce J. West
  Available online: https://www.mdpi.com/1099-4300/23/3/297

• “Beyond Causal Explanation: Einstein’s Principle Not Reichenbach’s”
  Michael Silberstein, William Mark Stuckey and Timothy McDevitt
  Available online: https://www.mdpi.com/1099-4300/23/1/114

• “Coupling between Blood Pressure and Subarachnoid Space Width Oscillations during Slow Breathing”
  Agnieszka Gruszecka, Magdalena K. Nuckowska, Monika Waskow, Jacek Kot, Pawel J. Winklewski, Wojciech Guminski, Andrzej F. Frydrychowski, Jerzy Wtorek, Adam Bujnowski, Piotr Lass, Tomislav Stankovski and Marcin Gruszecki
  Available online: https://www.mdpi.com/1099-4300/23/1/113

We would like to take this opportunity to thank all the research groups that submitted these exceptional papers for their contributions to Entropy. We would appreciate it if you would circulate this document among your colleagues or through your network.

We are pleased to announce the two winners of the Best ECR Presentation Awards sponsored by Entropy (ISSN: 1099-4300) for the CNS*2021 Online Workshop on Methods of Information Theory in Computational Neuroscience held on 6 and 7 July 2021. Congratulations to the winners, Dr. Fleur Zeldenrust and Mr. Lucas Rudelt.

“Estimating Information Transfer In Vitro: Results from Barrel Cortex” by Fleur Zeldenrust

Understanding the relation between (sensory) stimuli and the activity of neurons (i.e., ‘the neural code’) lies at the heart of understanding the computational properties of the brain. However, quantifying the information between a stimulus and a spike train has proven to be challenging due to the limited life span of a cell in an in vitro setup. In 2017, in this workshop, I presented a new in vitro method to measure how much information a single neuron transfers from the input it receives to its output spike train. This method has the advantage that it is fast (~10 minutes) compared with traditional methods. This decrease in recording time is obtained by generating an input by an artificial neural network that responds to a randomly appearing and disappearing ‘sensory stimulus’: the hidden state. The low entropy of this hidden state allows for a fast estimate of transferred information. Using this method, we have now recorded over 850 trials in almost 300 inhibitory and excitatory neurons of the barrel cortex, using different pharmacological modulations (including dopamine, acetylcholine, and serotonin receptor agonists). Here, I presented the first conclusions of this large database of recordings and showed how this method can be extended to dynamic clamp and the effects this has on modeled neurons.

"Embedding Optimization Reveals Long-Lasting History Dependence in Neural Spiking Activity" by Lucas Rudelt

Information processing can leave distinct footprints on the statistics of neural spiking. For example, efficient coding minimizes statistical dependencies on spiking history, while temporal integration of information may require the maintenance of information over various timescales. To investigate these footprints, I presented an approach that quantifies history dependence within the spiking of a single neuron, using mutual information between the entire past and current spiking. Applying this approach to extracellular spike recordings, we found that both the strength and the timescale of history dependence showed striking differences between different neural systems. In conjunction with recent highly parallel spike recording techniques, this approach could yield valuable insights into how information processing is organized in the brain.

We are pleased to announce the winners of the 2022 Best Paper Award, which was sponsored by MDPI and Entropy (ISSN: 1099-4300). Each winner (corresponding author) will receive CHF 500 and the opportunity to publish a paper free of charge in Entropy in 2022.

The winners, comprising one review article and four research articles, are:

Review article:

• “Thermodynamics in Ecology—An Introductory Review”
  by Søren Nors Nielsen, Felix Müller, Joao Carlos Marques, Simone Bastianoni and Sven Erik Jørgensen
  Entropy 2020, 22(8), 820; https://doi.org/10.3390/e22080820

Research articles:

• “The Role of Entropy in the Development of Economics”
  by Aleksander Jakimowicz
  Entropy 2020, 22(4), 452; https://doi.org/10.3390/e22040452

• “Large Deviations for Continuous Time Random Walks”
  by Wanli Wang, Eli Barkai and Stanislav Burov
  Entropy 2020, 22(6), 697; https://doi.org/10.3390/e22060697

• “Thermodynamics at Very Long Time and Space Scales”
  by Bjarne Andresen and Christopher Essex
  Entropy 2020, 22(10), 1090; https://doi.org/10.3390/e22101090

• “Geometric Optimisation of Quantum Thermodynamic Processes”
  by Paolo Abiuso, Harry J. D. Miller, Martí Perarnau-Llobet and Matteo Scandi
  Entropy 2020, 22(10), 1076; https://doi.org/10.3390/e22101076

We congratulate the winners on their accomplishments, and we would also like to take this opportunity to thank the research groups of the above papers for their contributions to Entropy, as well as the Award Committee for their efforts in the evaluation process.

We are pleased to announce the launch of a new initiative, the Special Issue Mentor Program.

This program intends to provide an opportunity for early-career scientists to enhance their editing, networking, and organizational skills and to work closely with our journal to gain more editorial experience.

Early-career scientists are being asked to propose ideas for new Entropy Special Issues. Early-career scientists would act as Guest Editors under the mentorship of an experienced scientist. This mentor could be a member of the Editorial Board of Entropy, or from other well-established research institutes or laboratories.

Early career scientists would have the following responsibilities:

• Providing a CV, including a list of publications;
• Proposing a Special Issue title and a short introduction;
• Writing a brief promotion plan for the Special Issue;
• Writing an editorial for the online Special Issue;
• Reviewing and making decisions for submissions under the mentorship of our Editorial Board Members.

Mentor’s Responsibilities:

• Conducting a final check before the Special Issue is published online;
• Co-editing the Special Issue with younger scholars and performing quality control of the publications in the SI;
• Providing suggestions to younger scholars if they have doubts or concerns regarding submissions;
• Organizing video calls with young scholars and the office regularly to discuss problems and improvement suggestions for the Special Issue.

Certificates and Awards:

When the Special Issue is closed, the Editorial Office will provide official certificates for all the mentors. Younger scholars will be prioritized as candidates for Entropy Young Investigator Awards in future editions.

If you are interested in this opportunity, please send your Special Issue proposal to the Entropy Editorial Office (entropy@mdpi.com), and we will discuss the process (i.e., mentor collaboration, Special Issue topic feasibility analysis, etc.) in further detail.

In addition to the new Special Issue Mentor Program, Entropy continues to welcome all Special Issue proposals based on hot research topics as usual.

Entropy Editorial Office

We are pleased to announce the winners of the 2021 Outstanding Reviewer Awards, sponsored by MDPI and Entropy (ISSN: 1099-4300). The awards have been granted to five outstanding scholars in recognition of their excellent contributions to their reviewer process. These scholars have been awarded a prize of CHF 500 as well as a 50% discount towards the publication fee of one paper in 2022.

The award winners are:

Name: Jim W. Kay
Affiliation: School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QQ, UK

Name: Christophe Chesneau
Affiliation: Department of Mathematics, University of Caen, 14000 Caen, France

Name: Esteban Tlelo-Cuautle
Affiliation: Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla 72840, México

Name: Dr. Dennis Dieks
Affiliation: Freudenthal Instituut History and Philosophy of Science, Utrecht University, 3584 CC Utrecht, Netherlands

Name: Claudio Cremaschini
Affiliation: Research Center for Theoretical Physics and Astrophysics, Institute of Physics, Silesian University in Opava, Bezrucovo nám.13, CZ-74601 Opava, Czech Republic

The selection process was incredibly difficult due to the high number of exceptional candidates. We appreciate every reviewer’s work in facilitating the review process and controlling the quality of manuscripts.

For more information about the Entropy awards, please see the following link: https://www.mdpi.com/journal/entropy/awards.

It is our great honor to congratulate the Editorial Board Members and Editors in MDPI's journals who have been distinguished as 2021 Highly Cited Researchers by Clarivate, according to Web of Science data. We herewith express our gratitude for the immense impact the named researchers continue to make on scientific progress and on our journals' development.

Clarivate's annual list of Highly Cited Researchers^TM identifies the most highly cited scientists for the past decade. Their impactful papers are among the top 1 per cent in the citation distribution of one or more of 22 fields analyzed in the "Essential Science Indicators", distinguishing them as hugely influential among their peers.

The full list of 2021 Highly Cited Researchers  can be accessed at the following webpage in the Web of Science^TM https://recognition.webofscience.com/awards/highly-cited/2021/.

--- Highly Cited Researchers (HCR) is a Clarivate product.

We are pleased to announce that the Best Paper Award, sponsored by Entropy (ISSN 1099-4300; website: https://www.mdpi.com/journal/entropy), for the 1st International Conference on Novelties in Intelligent Digital Systems (NIDS2021) was granted to the work by Anton Anikin, Oleg Sychev, and Mikhail Denisov (Volgograd State Technical University, Volgograd, Russia). Congratulations!

Title: “Ontology Reasoning for Explanatory Feedback Generation to Teach how Algorithms Work”

Summary: Intelligent tutoring systems are becoming increasingly common in assisting students but are often aimed at isolated subject domain tasks without creating a scaffolding system from lower- to higher-level cognitive skills, with low-level skills often neglected. We designed and developed an intelligent tutoring system, CompPrehension, aimed at the comprehension level of Bloom's taxonomy. The system features plug-in-based architecture, adding new subject domains and learning strategies. It uses formal models and software reasoners to solve the problems, judge the answers, and generate explanatory feedback for the broken domain rules and follow-up questions to stimulate the students' thinking. We developed two subject domain models: an Expressions domain for teaching the expression order of evaluation and a Control Flow Statements domain for code-tracing tasks. Developing algorithms using control structures and understanding their building blocks are essential skills in mastering programming, while ontologies and software reasoning offers a promising method for developing intelligent tutoring systems in well-defined domains (such as programming languages and algorithms). It can also be used for many kinds of teaching tasks. In this work, we used a formal model consisting of production rules for Apache Jena reasoner as a basis for developing a constraint-based tutor for introductory programming domain. The tutor can determine fault reasons for any incorrect answer that a student can enter. The problem the student should solve is building an execution trace for the given algorithm. The problem is a closed-ended question that requires arranging given actions in the (unique) correct order; some actions can be used several times, while others can be omitted. Using formal reasoning to check domain constraints allowed us to provide explanatory feedback for all kinds of errors subject-domain tasks that students can make.

We are pleased to announce that the Best Presentation Award of the XLVII Congress of Polish Physicists 2021, sponsored by Entropy (ISSN: 1099-4300), has been granted to Dr. David Ziemkiewicz from Bydgoszcz University of Science and Technology. Congratulations!

Title: “Chaotic Dynamics of the Clock Mechanism”

For centuries, the mechanical pendulum clock has been one of the primary means of measuring time. Its central part is a damped pendulum, kept in motion by the exciting force, the nature of which depends on the type of clock mechanism. The mechanism supplies energy to the pendulum and is simultaneously regulated by it; it is a special case of a self-excited oscillator, and the current feedback makes the dynamics of the system non-linear and often chaotic, with a fractal attractor. In the history of clock development, most attempts to improve the precision of timing have been based on reducing the influence of non-linear effects by minimizing the interaction between the pendulum and the mechanism—so that it is a good approximation of a mathematical free pendulum. A completely different approach was proposed in 1722 by John Harrison. In its construction, the pendulum is in constant contact with the mechanism and vibrates with a very large amplitude. Thanks to modern numerical methods, it is possible to perform a detailed analysis of this type of system (D. Ziemkiewicz, Phys. Rev. E 2021, 103, 062208). It can be shown that under appropriate conditions (correctly identified by Harrison), one can obtain an error of indications at the level of a few seconds per year, which is an unattainable value for other types of mechanical clocks.

Academic editors play a crucial role in leading our journals and ensuring that each article undergoes a robust and timely peer-review. With the launch of Topics this year and addition of Topic Editors to our family of academic editors, we decided it would be a good time to restructure our academic boards, thus providing more clarity and support for each role. MDPI is pleased to announce the launch of a new position—Topical Advisory Panel Member, that will replace the previous position of Topics Board Member. The Topical Advisory Panel will be comprised of early career researchers eager to gain experience in editorial work.

The main responsibility of the new members of the Topical Advisory Panel is to regularly provide support to Guest Editors, Topic Editors, and Section Board Members. The responsibilities of the Topical Advisory Panel are available here: https://www.mdpi.com/editors.

Each year, the members’ performances are evaluated, and outstanding members are promoted to the Editorial Board by the Editor-in-Chief.

To qualify as a Topical Advisory Panel Member, applicants must:

• Have expertise and experience in the field related to the journal;
• Have received a Ph.D. in the last 10 years, approximately;
• Have at least 6-8 published papers in the last 5 years as first author or corresponding author;
• Currently hold an independent research position in academia or a government institute.

If you are interested in this role, please contact the editorial office by email.

We look forward to hearing from you soon.

We are pleased to announce that the Young Scientist Award, sponsored by Entropy for CCS2021-Satellite on Econophysics 2021, was granted to Dr. Jeremy D. Turiel, from University College London. Congratulations!

“Self-Organised Criticality in High-Frequency Finance: The Case of Flash Crashes”

With the rise of computing and artificial intelligence, advanced modeling and forecasting has been applied to High-Frequency markets. A crucial element of solid production modeling though relies on the investigation of data distributions and how they relate to modeling assumptions. In this work, we investigate volume distributions during anomalous price events and show how their tail exponents <2 indicate a diverging second moment of the distribution, i.e., variance. We then tie the dynamics of flash crashes to self-organised criticality. The findings are of great relevance for regulators and market makers as they advocate for rigorous heavy-tailed modeling of risks and changes in regulation to avoid simultaneous liquidity withdrawals and hard risk constraints which lead to synchronisation and critical events.