Investigating Dynamical Complexity and Fractal Characteristics of Bitcoin/US Dollar and Euro/US Dollar Exchange Rates around the COVID-19 Outbreak.

This article investigates the dynamical complexity and fractal characteristics changes of the Bitcoin/US dollar (BTC/USD) and Euro/US dollar (EUR/USD) returns in the period before and after the outbreak of the COVID-19 pandemic. More specifically, we applied the asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) method to investigate the temporal evolution of the asymmetric multifractal spectrum parameters. In addition, we examined the temporal evolution of Fuzzy entropy, non-extensive Tsallis entropy, Shannon entropy, and Fisher information. Our research was motivated to contribute to the comprehension of the pandemic's impact and the possible changes it caused in two currencies that play a key role in the modern financial system. Our results revealed that for the overall trend both before and after the outbreak of the pandemic, the BTC/USD returns exhibited persistent behavior while the EUR/USD returns exhibited anti-persistent behavior. Additionally, after the outbreak of COVID-19, there was an increase in the degree of multifractality, a dominance of large fluctuations, as well as a sharp decrease of the complexity (i.e., increase of the order and information content and decrease of randomness) of both BTC/USD and EUR/USD returns. The World Health Organization (WHO) announcement, in which COVID-19 was declared a global pandemic, appears to have had a significant impact on the sudden change in complexity. Our findings can help both investors and risk managers, as well as policymakers, to formulate a comprehensive response to the occurrence of such external events.

The Impact of COVID-19 on Weak-Form Efficiency in Cryptocurrency and Forex Markets.

The COVID-19 pandemic has had an unprecedented impact on the global economy and financial markets. In this article, we explore the impact of the pandemic on the weak-form efficiency of the cryptocurrency and forex markets by conducting a comprehensive comparative analysis of the two markets. To estimate the weak-form of market efficiency, we utilize the asymmetric market deficiency measure (MDM) derived using the asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) approach, along with fuzzy entropy, Tsallis entropy, and Fisher information. Initially, we analyze the temporal evolution of these four measures using overlapping sliding windows. Subsequently, we assess both the mean value and variance of the distribution for each measure and currency in two distinct time periods: before and during the pandemic. Our findings reveal distinct shifts in efficiency before and during the COVID-19 pandemic. Specifically, there was a clear increase in the weak-form inefficiency of traditional currencies during the pandemic. Among cryptocurrencies, BTC stands out for its behavior, which resembles that of traditional currencies. Moreover, our results underscore the significant impact of COVID-19 on weak-form market efficiency during both upward and downward market movements. These findings could be useful for investors, portfolio managers, and policy makers.

Retention of higher fertility depending on ovarian follicle reserve in cystine-glutamate transporter gene-deficient mice.

The cystine-glutamate transporter (xCT) is responsible for the transport of cystine into cells. We recently found that xCT-deficient (xCTKO) aged mice maintained a higher rate of ovulation and ovarian weight compared with wild-type (WT) mice. It has been reported that a xCT deficiency in cultured cells induces autophagy through the suppression of mTOR survival pathways. We have previously reported that starvation in neonatal mice increases the number of primordial follicles with concomitant autophagy activation. Therefore, we investigated age-related changes in follicle reserve and fertility in xCTKO mice and clarified whether the PI3K/AKT/mTOR signaling pathway contributes to this. The numbers of offspring in the xCTKO mice aged 10 and 12 months were significantly higher than those in the WT mice. The primordial follicle numbers in xCTKO neonatal mice tended to be higher than WT mice during all times evaluated. In contrast, the primary follicle number was significantly lower in the xCTKO mice at 60 h after birth. The expression of p-AKT, which promotes follicle development, was significantly lower in xCTKO mice than that in WT mice, whereas the expression ratios of LC3-II/LC3-I were significantly higher. The xCTKO mice had significantly more primordial follicles than WT mice at 2 months of age and showed a similar trend at 13-15 months of age. These results suggest that the maintenance of fertility in aged xCTKO mice can be attributed to high follicle reserve after puberty by suppression of follicle activation during the neonatal period.

Chaotic synchronization of mutually coupled systems-arbitrary proportional linear relations.

Considering a system combining two generalized Boolean transformations, we found that depending on the parameters, we can generate generalized synchronization such that the two chaotic orbits have arbitrary proportional linear relations. We rigorously determined its synchronization conditions by the explicit computing conditional Lyapunov exponent using the ergodic property and stable property of the Cauchy distribution. We found that a phenomenon similar to chaotic synchronization occurs even when the synchronization conditions are not strictly satisfied, which exhibits some degree of structural stability of chaotic synchronization. Our model can be further extended to systems with more degrees of freedom and, in the future, can be applied to reservoir computing.

The impact of oocyte death on mouse primordial follicle formation and ovarian reserve.

Background: Ovaries, the source of oocytes, maintain the numbers of primordial follicles, develop oocytes for fertilization and embryonic development. Although it is well known that about two-thirds of oocytes are lost during the formation of primordial follicles through cyst fragmentation and the aggregation of oocytes within the cyst, the mechanism responsible for this remains unclear. Methods: We provide an overview of cell death that is associated with the oocyte cyst breakdown and primordial follicle assembly along with our recent findings for mice that had been treated with a TNFα ligand inhibitor. Main Findings: It is generally accepted that apoptosis is the major mechanism responsible for the depletion of germ cells. In fact, a gene deficiency or the overexpression of apoptosis regulators can have a great effect on follicle numbers and/or fertility. Apoptosis, however, may not be the only cause of the large-scale oocyte attrition during oocyte cyst breakdown, and other mechanisms, such as aggregation, may also be involved in this process. Conclusion: The continued study of oocyte death during primordial follicle formation could lead to the development of novel strategies for manipulating the primordial follicle pool, leading to improved fertility by enhancing the ovarian reserve.

Infinite ergodicity that preserves the Lebesgue measure.

In this study, we prove that a countably infinite number of one-parameterized one-dimensional dynamical systems preserve the Lebesgue measure and are ergodic for the measure. The systems we consider connect the parameter region in which dynamical systems are exact and the one in which almost all orbits diverge to infinity and correspond to the critical points of the parameter in which weak chaos tends to occur (the Lyapunov exponent converging to zero). These results are a generalization of the work by Adler and Weiss. Using numerical simulation, we show that the distributions of the normalized Lyapunov exponent for these systems obey the Mittag-Leffler distribution of order 1/2.

Flexible two-point selection approach for characteristic function-based parameter estimation of stable laws.

Stable distribution is one of the attractive models that well describes fat-tail behaviors and scaling phenomena in various scientific fields. The approach based upon the method of moments yields a simple procedure for estimating stable law parameters with the requirement of using momental points for the characteristic function, but the selection of points is only poorly explained and has not been elaborated. We propose a new characteristic function-based approach by introducing a technique of selecting plausible points, which could bring the method of moments available for practical use. Our method outperforms other state-of-art methods that exhibit a closed-form expression of all four parameters of stable laws. Finally, the applicability of the method is illustrated by using several data of financial assets. Numerical results reveal that our approach is advantageous when modeling empirical data with stable distributions.

Average booking curves draw exponential functions.

The booking curve time series in perishable asset industries, including hotels, has been studied to manage a demand-supply condition or revenue management (RM). However, due to changing times, e.g., economy and technology, many RM practitioners have put their efforts into catching on to peoples' booking pattern shifts, representing macroscopic changes in booking curves. We investigate macroscopic aspects of booking curves with actual sales data across six properties in the hotel and car-rental industries for two years, considering the difference in the economic environment characterized before and during the COVID-19 epidemic. We explain a new cross-industry and cross-economic-environment universal statistical law: average booking curves draw exponential functions (the ABCDEF law). We provide a basis for the ABCDEF law from three perspectives; data validation, modeling in the statistical physics framework, and empirical justification for the causality of the model. The ABCDEF law derives informative statistics to quantitatively measure peoples' buying behavior even in time or society changes, which is expected to contribute to management in various industries.

Blind source separation of chaotic laser signals by independent component analysis.

We experimentally demonstrate blind source separation of chaos generated in Nd:YVO(4) microchip solid-state lasers by using independent component analysis. Two chaotic source signals are linearly mixed with randomly selected mixing ratio and independent component analysis is applied for the mixed signals to extract the source signals. We investigate blind source separation of many chaotic laser signals and succeed 100-signal separation of chaotic temporal waveforms. Longer temporal waveforms are required with increase of the number of mixed signals.