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In this paper, we adopt multifractal detrended fluctuation analysis (MF-DFA) to explore relationships between the Russia–Ukraine conflict and defense stock markets. Specifically, we analyze the behaviors of 20 U.S. defense stock markets confronting with the Russia–Ukraine conflict. By using the stock price charts, combined with multifractal spectra and singularity exponents calculated by MF-DFA, we explore how the conflict affects the defense stock markets in perspectives of closing price, market efficiency and stability. In addition, the obtained results reveal high level of consistency while each type shows distinct features. According to singularity exponents, we observe that all 20 stocks can be divided into three types which we note as T y p e s  A, B and C. We infer from the singularity spectra that the T y p e  A stock price will experience plummet after the conflict, instead, stock price of T y p e  A increases based on stock price charts, while stock price of T y p e s  B and C rises as predicted. For T y p e  A stocks, their market efficiency and stability show increments where we draw completely opposite conclusion for T y p e  B stocks. Furthermore, we also note that T y p e  C stocks include two defense stocks having a special phenomenon, and their multifractal spectra indicate the increase in stock price which behave like T y p e  B stocks. However, their singularity exponents reduce during the conflict, meaning the slump in their market efficiency, which share the same characteristic as T y p e  A stocks. Hence, we treat T y p e  C stocks as a unique type. To mitigate the influence of stochastic elements in the experimental process, three comparative analyses are undertaken. We humbly believe that the induced implications are aroused by the Russia–Ukraine conflict. [ABSTRACT FROM AUTHOR]

Important nodes can determine the internal structure of complex networks and reveal the internal relationships of real-world systems, and identifying key nodes in complex networks is one of the important research areas of complex network science. As the king of commodities, changes in the price of gold significantly impact the economic development of various countries. Especially in the early stages of the outbreak of war between Russia and Ukraine, the price of gold futures has been greatly impacted, and the systemic risks are gradually spreading. In this paper, a gold future price series is mapped into a visibility graph (VG), the characteristics of the gold price time series and key points-in-time, have been explored from the perspective of complex network. First, according to the data structure characteristics of gold futures, this paper converts the closing prices of gold futures of the New York Mercantile Exchange into a complex network through the VG model. Then, by using the complex network model to further delve into the price of gold futures, it is found that the degree distribution of the gold futures network follows a power-law distribution, and has obvious scale-free characteristics. Finally, this paper uses the visual network node shrinking algorithm and the technique for order preference by similarity to ideal solution (TOPSIS) analysis method to identify the key nodes of the gold futures visual map to find the key time nodes in the timeline of gold futures market. Analysis of the key time nodes of this market by four methods reveals that the repetition rate of the key time nodes in the methods' top 10 ranking is as high as 82.5%, indicating that the results obtained in this paper are robust. This study introduces a new model to describe the characteristics of gold futures price series, one which can find key time nodes in gold futures prices and provide potential help for predicting gold futures prices. [ABSTRACT FROM AUTHOR]

Information on the 2nd International Moscow Conference on Computational Molecular Biology which was held in Moscow, Russia from July 18-21, 2005 is presented. Topics discussed during the conference include comparative genomics and proteomics, genome annotation, gene recognition and alternative splicing, systems biology, and molecular evolution.

This paper has investigated the predictability of the top 10 cryptocurrencies' price dynamics, ranked by their daily market capitalization and trade volume, via the information theory quantifiers. Our analysis considers the Complexity-entropy causality plane to study the temporal evolution of the price of these cryptocurrencies and their respective locations along this 2D map, bearing in mind after and during the Russia–Ukraine war. Moreover, we apply the permutation entropy and the Jensen–Shannon statistical complexity measure to rank these cryptocurrencies similarly to a complexity hierarchy. Our findings reflect that the Russian–Ukraine war affects the informational efficiency of cryptocurrency dynamics. Specifically, the cryptocurrencies notably showed a decrease in informational inefficiency (USD-coin, Binance-USD, BNB, Dogecoin, and XRP). At the same time, the cryptocurrencies with more expressiveness for the financial market, considering the volume traded and the capitalized market, were strongly impacted, presenting an increase in informational inefficiency (Tether, Cardano, Ethereum, and Bitcoin). It clarifies the potential of cryptocurrencies to mitigate exogenous shocks and their capability to use with portfolio selection, risk diversification and herding behavior. [ABSTRACT FROM AUTHOR]

The paper presents a discussion on an opinion about the stability margin towards an emergency in local climate dynamics from the bifurcation analysis viewpoint. With this purpose we propose to attract the practice-oriented bifurcation analysis, where the conflict-of-units between notions used to understand natural evolution processes and notions used to describe desirable artificial regimes is resolved by integrating analytics on the basis of modified bifurcation diagrams. The discussion focuses on the phenomenon of interannual temperature variability, where local annual maximums and minimums are analyzed with daily details in both time and temperature coordinates. This phenomenon is considered via the probable, periodical and regulator conceptions. Advantages of the regulator conception are verified by results of processing the data of temperature meteorological observations on daily means over the last 135 years. This conception is based on the HDS-hypothesis, in accordance to which local climate dynamics is determined by the natural competition between the amplitude quantization (restricted by the temperature Hysteresis) and time quantization (caused by the Double Synchronization). Thus an alternation between three elementary processes with the same period (year) and different patterns of annual warming–cooling cycles is supposed as a typical behavior for local climate systems, and the idea on high-dynamic local climate ensembles is developed instead of the conventional opinion on quasi-static local climate norms. Mechanisms of temperature changes due to abrupt shifts (so-called change-points) of the HDS-regulator parameters are distinguished from mechanisms of temperature changes due to bifurcations. The notion of a stability margin is used as a distance to an emergency and is visualized in the parametrical space. So, in spite of the mechanisms of temperature changes with/without bifurcations are different, their conflict-free sewing becomes conceptually possible in the context of the stability margin towards emergencies determined relatively bifurcation boundaries in the parametrical space. Since the discussed dynamics is not supposed to exist in terms of the traditional estimations concerning the observed local climate changes, then we believe that the paper would be interesting for scientists in the field of bifurcation analysis as well as for scientists and specialists, activity areas of which relate to the contemporary challenges connected with climate changes. [ABSTRACT FROM AUTHOR]

Since the bifurcation analysis remains the basic tool to inquire into nonlinear system dynamics, then, theoretically, the bifurcation analysis should be widely used to estimate the evolution of the climate dynamics at a certain geographic point over the last centenary. But it does not occur in practice. A viewpoint how to estimate such evolution is proposed and discussed in the paper. The viewpoint can be briefly formulated as the following: the extra-short timescale, plus the novel conceptual model, plus the modified bifurcation diagrams. So, first, only the data of instrumental measurements (hereafter observations) are used to build the bifurcation diagram, correspondingly, the timescale is restricted by the maximal duration of the reliable observations. In particular, 130-years time series of the land surface air temperature in Russia are analyzed in the paper. Second, the conceptual model (HDS-model) to describe the annual warming-cooling cycle dynamics similar to the dynamics of the hysteresis regulator with double synchronization (HDS-regulator) is introduced. Correspondingly, the local climate dynamics is considered as the dynamics of the system with a variable structure. The main advantage of HDS-model is the possibility to describe quite simply the rich variety of the observable temperature evolution based on the known nonlinear phenomena by the combinations of C-bifurcations (or, in other words, border-collision bifurcations) between three conjugate periodical processes with the same period but different orders of structural changes. Then HDS-hypothesis on the climate dynamics is proposed, where the local temperature evolution is considered under the competition between both amplitude and time quantizations within the Sun-Earth-Moon system. Processing the observations follows the SUC-logic conceptions on the experimental bifurcation analysis that allows to untangle the intricate nonlinear nonstationary behavior of a local climate system by using both special sections (S) and units (U) in a certain consequence (C). As a result, the modified bifurcation diagrams to show the temperature evolution in local climate systems are built under the variation of several bifurcation parameters. The diagrams exhibit intermittency phenomena of high activity in the European part of Russia at least. Generally speaking, HDS-hypothesis gives the good approximation to answer the question whether the observable changes in the local climate dynamics are qualitative and, if yes, in what meaning? [ABSTRACT FROM AUTHOR]

This paper is devoted to the development of the experimental bifurcation analysis in the research of local climate dynamics. In particular, we consider the dynamics of the land surface air temperature in the centennial timescale. The experimental bifurcation analysis supposes the choice of a conceptual model to demonstrate how the observable kinds of dynamical processes can be realized on the whole. We worked on the conceptual model with a variable structure (HDS-model), where the dynamics is determined by the competition between the amplitude quantization and the time quantization. The model originates from the hysteresis regulator with double synchronization (HDS-regulator) proposed in 1970's to achieve the extreme combination of both efficiency and reliability of energy conversion processes. The HDS-model allows to consider the interplay between several periodical processes instead of chaos and quasi-periodicity in order to excuse the variety of the behaviors observed in the local climate dynamics. In particular, the intermittency seems to be the typical behavior of a local climate system from such viewpoint. Here we continue to verify the HDS-model and continue to develop the idea of the modified bifurcation diagrams to reveal the regularities within the intermittency. In particular, we first build the spatial diagram to summarize the results of the bifurcation analysis of the local climate dynamics in the centennial timescale. We assume that each effect of the regional temperature oscillations (RTO-effect) appears as a certain combination of several effects of the local temperature oscillations (LTO-effects), where each LTO-effect can be revealed by the bifurcation analysis. The possibility to build the modified bifurcation diagrams is provided by the SUC-logic aimed for the synthesis of experimental bifurcation analysis, symbolical analysis, and multidimensional data visualization under the assumption that an annual warming-cooling cycle is the unit to analyze. Since only the historical data of the temperature observations are used, then the results approach as close as possible to the real events. We believe that our research seems to be interesting to estimate the theoretically possible latent abilities and evolution of the local climate dynamics. [ABSTRACT FROM AUTHOR]