Three Risky Decades: A Time for Econophysics?

Our Special Issue we publish at a turning point, which we have not dealt with since World War II. The interconnected long-term global shocks such as the coronavirus pandemic, the war in Ukraine, and catastrophic climate change have imposed significant humanitary, socio-economic, political, and environmental restrictions on the globalization process and all aspects of economic and social life including the existence of individual people. The planet is trapped—the current situation seems to be the prelude to an apocalypse whose long-term effects we will have for decades. Therefore, it urgently requires a concept of the planet's survival to be built—only on this basis can the conditions for its development be created. The Special Issue gives evidence of the state of econophysics before the current situation. Therefore, it can provide excellent econophysics or an inter-and cross-disciplinary starting point of a rational approach to a new era

Екофізика криптовалютних крахів: систематичний огляд

Cryptocurrencies refer to a type of digital asset that uses distributed ledger, or blockchain technology to enable a secure transaction. Like other financial assets, they show signs of complex systems built from a large number of nonlinearly interacting constituents, which exhibits collective behavior and, due to an exchange of energy or information with the environment, can easily modify its internal structure and patterns of activity. We review the econophysics analysis methods and models adopted in or invented for financial time series and their subtle properties, which are applicable to time series in other disciplines. Quantitative measures of complexity have been proposed, classified, and adapted to the cryptocurrency market. Their behavior in the face of critical events and known cryptocurrency market crashes has been analyzed. It has been shown that most of these measures behave characteristically in the periods preceding the critical event. Therefore, it is possible to build indicators-precursors of crisis phenomena in the cryptocurrency market.Криптовалюти відносяться до типу цифрових активів, які використовують технологію розподіленого реєстру, або блокчейн, для забезпечення безпечного проведення транзакцій. Як і інші фінансові активи, вони мають ознаки складних систем, побудованих з великої кількості нелінійно взаємодіючих складових, які демонструють колективну поведінку і завдяки обміну енергією або інформацією з навколишнім середовищем можуть легко змінювати свою внутрішню структуру і моделі діяльності. Ми розглядаємо методи та моделі еконофізичного аналізу, прийняті або винайдені для фінансових часових рядів, а також їх тонкі властивості, які можна застосувати до часових рядів в інших дисциплінах. Запропоновано, класифіковано та адаптовано до ринку криптовалют кількісні міри складності. Проаналізовано їх поведінку в умовах критичних подій та відомих обвалів криптовалютного ринку. Показано, що більшість з цих показників характерно поводять себе в періоди, що передують критичній події. Тому є можливість побудови індикаторів-передвісників кризових явищ на ринку криптовалют

Еконофізика крахів криптовалюти: огляд

Cryptocurrencies refer to a type of digital asset that uses distributed ledger, or blockchain technology to enable a secure transaction. Like other financial assets, they show signs of complex systems built from a large number of nonlinearly interacting constituents, which exhibits collective behavior and, due to an exchange of energy or information with the environment, can easily modify its internal structure and patterns of activity. We review the econophysics analysis methods and models adopted in or invented for financial time series and their subtle properties, which are applicable to time series in other disciplines. Quantitative measures of complexity have been proposed, classified, and adapted to the cryptocurrency market. Their behavior in the face of critical events and known cryptocurrency market crashes has been analyzed. It has been shown that most of these measures behave characteristically in the periods preceding the critical event. Therefore, it is possible to build indicators-precursors of crisis phenomena in the cryptocurrency market.Криптовалюти - це тип цифрового активу, який використовує розподілену книгу або технологію блокчейна для забезпечення безпечної транзакції. Як і інші фінансові активи, вони мають ознаки складної системи, побудованої з великої кількості нелінійно взаємодіючих складових, яка демонструє колективну поведінку і завдяки обміну енергією чи інформацією з навколишнім середовищем може легко змінювати свою внутрішню структуру та моделі діяльності. Ми оглядаємо методи та моделі еконофізичного аналізу, прийняті у фінансових часових рядах або винайдені для них, та їхні тонкі властивості, які застосовні до часових рядів в інших дисциплінах. Кількісні показники складності були запропоновані, класифіковані та адаптовані до ринку криптовалют. Було проаналізовано їх поведінку перед критичними подіями та відомими кризами на ринку криптовалют. Було показано, що більшість цих заходів поводяться характерно в періоди, що передують критичній події. Тому на ринку криптовалют можна будувати індикатори-попередники кризових явищ

An Initial Framework Assessing the Safety of Complex Systems

Trabajo presentado en la Conference on Complex Systems, celebrada online del 7 al 11 de diciembre de 2020.Atmospheric blocking events, that is large-scale nearly stationary atmospheric pressure patterns, are often associated with extreme weather in the mid-latitudes, such as heat waves and cold spells which have significant consequences on ecosystems, human health and economy. The high impact of blocking events has motivated numerous studies. However, there is not yet a comprehensive theory explaining their onset, maintenance and decay and their numerical prediction remains a challenge. In recent years, a number of studies have successfully employed complex network descriptions of fluid transport to characterize dynamical patterns in geophysical flows. The aim of the current work is to investigate the potential of so called Lagrangian flow networks for the detection and perhaps forecasting of atmospheric blocking events. The network is constructed by associating nodes to regions of the atmosphere and establishing links based on the flux of material between these nodes during a given time interval. One can then use effective tools and metrics developed in the context of graph theory to explore the atmospheric flow properties. In particular, Ser-Giacomi et al. [1] showed how optimal paths in a Lagrangian flow network highlight distinctive circulation patterns associated with atmospheric blocking events. We extend these results by studying the behavior of selected network measures (such as degree, entropy and harmonic closeness centrality)at the onset of and during blocking situations, demonstrating their ability to trace the spatio-temporal characteristics of these events.This research was conducted as part of the CAFE (Climate Advanced Forecasting of sub-seasonal Extremes) Innovative Training Network which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813844

On Collective Computation

Postprint (published version

Збірник наукових праць 9-ї Міжнародної конференції з моніторингу, моделювання та управління емерджентною економікою (M3E2-MLPEED 2021). Одеса, Україна, 26-28 травня 2021 р.

Збірник наукових праць 9-ї Міжнародної конференції з моніторингу, моделювання та управління емерджентною економікою (M3E2-MLPEED 2021). Одеса, Україна, 26-28 травня 2021 р.Proceedings of the Selected and Revised Papers of 9th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2-MLPEED 2021). Odessa, Ukraine, May 26-28, 2021

What Makes Hollywood Run? Capitalist Power, Risk and the Control of Social Creativity

This dissertation combines an interest in political economy, political theory and cinema to offer an answer about the pace of the Hollywood film business and its general modes of behaviour. More specifically, this dissertation seeks to find out how the largest Hollywood firms attempt to control social creativity such that the art of filmmaking and its related social relations under capitalism do not become financial risks in the pursuit of profit. Controlling the ways people make or watch films, the thesis argues, is an institutional facet of capitalist power. Capitalist powerthe ability to control, modify and, sometimes, limit social creation through the rights of ownershipis the foundation of capital accumulation. For the Hollywood film business, capitalist power is about the ability of business concerns to set the terms that mould the future of cinema. The overall objective of Part I is to outline and rectify some of the methodological problems that obscure our understanding of how capital is accumulated from culture. Marxism stands as the theoretical foil for this argument. Because Marxism defines capital such that only economic activity can create value, it needs to clearly distinguish between economics and politicsyet this is a distinction it is ultimately unable to make. With this backdrop in mind, Part I introduces the capital-as-power approach and uses it as a foundation to an alternative political economic theory of capitalism. The capital-as-power approach views capital not as an economic category, but as a category of power. Consequently, this approach reframes the accumulation of capital as a power process. Part II focuses on the Hollywood film business. It investigates how and to what extent major filmed entertainment attempts to accumulate capital by lowering its risk. The process of lowering risk has characterized Hollywoods orientation toward the social-historical character of cinema and mass culture. This push to lower risk has been most apparent since the 1980s. In recent decades, major filmed entertainment has used its oligopolistic control of distribution to institute an order of cinema based on several key strategies: saturation booking, blockbuster cinema and high-concept filmmaking

Anomalous statistical properties and fluctuations on multiple timescales

How can fluctuations in one-dimensional time series data be characterized and how can detected effects be decomposed into their dynamical origins or causes? In the context of these questions, a variety of problems are discussed and solutions are introduced. The first issue concerns the causes of anomalous diffusion. A previously proposed framework decomposes the Hurst exponent into the Joseph, Noah, and Moses effects. They represent violations of the three premises of the central limit theorem. Here the framework is applied to an intermittent deterministic system, which exhibits a rich combination of all three effects. Nevertheless, the results provide an intuitive interpretation of the dynamics. In addition, the framework is theoretically discussed and connected to a calculation that proves its validity for a large class of systems. Once the type of anomalous statistical behavior is classified, one might ask what the dynamical origin of the effects is. Especially the property of long range temporal correlations (the Joseph effect) is discussed in detail. In measurements, they might arise from different dynamical origins or can be explained as an emerging phenomenon. A collection of different routes to the observed behavior is established here. A popular tool for detecting long range correlations is detrended fluctuation analysis. Its advantages over traditional methods are stability and smoothness for timescales up to one fourth of the measurement time and the ability to neglect the slow dynamics and trends. Recently, a theory for an analytical understanding of this method was introduced. In this thesis, the method is further analyzed and developed. An approach is presented that enables scientists to use this method for short range correlated data, even if the dynamics is very complex. Fluctuations can be decomposed into a superposition of linear models that explain its features. Therefore, on the one hand, this thesis is about understanding the effects of anomalous diffusion. On the other hand, it is about widening the applicability of one of its detection methods such that it becomes useful for understanding normal or complex statistical behavior. A good example of a complex system, where the proposed stochastic methods are useful, is the atmosphere. Here it is shown how detrended fluctuation analysis can be used to uncover oscillatory modes and determine their periods. One of them is the El Ni\~no southern oscillation. A less well known and more challenging application is a 7--8 year mode in European temperature fluctuations. A power grid is a very different type of complex system. However, using the new method, it is possible to generate a data model that incorporates the important features of the grid frequency

Cognitive Decay And Memory Recall During Long Duration Spaceflight

This dissertation aims to advance the efficacy of Long-Duration Space Flight (LDSF) pre-flight and in-flight training programs, acknowledging existing knowledge gaps in NASA\u27s methodologies. The research\u27s objective is to optimize the cognitive workload of LDSF crew members, enhance their neurocognitive functionality, and provide more meaningful work experiences, particularly for Mars missions.The study addresses identified shortcomings in current training and learning strategies and simulation-based training systems, focusing on areas requiring quantitative measures for astronaut proficiency and training effectiveness assessment. The project centers on understanding cognitive decay and memory loss under LDSF-related stressors, seeking to establish when such cognitive decline exceeds acceptable performance levels throughout mission phases. The research acknowledges the limitations of creating a near-orbit environment due to resource constraints and the need to develop engaging tasks for test subjects. Nevertheless, it underscores the potential impact on future space mission training and other high-risk professions. The study further explores astronaut training complexities, the challenges encountered in LDSF missions, and the cognitive processes involved in such demanding environments. The research employs various cognitive and memory testing events, integrating neuroimaging techniques to understand cognition\u27s neural mechanisms and memory. It also explores Rasmussen\u27s S-R-K behaviors and Brain Network Theory’s (BNT) potential for measuring forgetting, cognition, and predicting training needs. The multidisciplinary approach of the study reinforces the importance of integrating insights from cognitive psychology, behavior analysis, and brain connectivity research. Research experiments were conducted at the University of North Dakota\u27s Integrated Lunar Mars Analog Habitat (ILMAH), gathering data from selected subjects via cognitive neuroscience tools and Electroencephalography (EEG) recordings to evaluate neurocognitive performance. The data analysis aimed to assess brain network activations during mentally demanding activities and compare EEG power spectra across various frequencies, latencies, and scalp locations. Despite facing certain challenges, including inadequacies of the current adapter boards leading to analysis failure, the study provides crucial lessons for future research endeavors. It highlights the need for swift adaptation, continual process refinement, and innovative solutions, like the redesign of adapter boards for high radio frequency noise environments, for the collection of high-quality EEG data. In conclusion, while the research did not reveal statistically significant differences between the experimental and control groups, it furnished valuable insights and underscored the need to optimize astronaut performance, well-being, and mission success. The study contributes to the ongoing evolution of training methodologies, with implications for future space exploration endeavors

Aerospace Medicine and Biology: A cumulative index to the 1982 issues

This publication is a cumulative index to the abstracts contained in the Supplements 229 through 240 of Aerospace Medicine and Biology: A continuing Bibliography. It includes three indexes: subject, personal author, and corporate source