Analysis of the Czech Intraday Electricity Market During COVID-19 Pandemic from the Multifractal Perspective

This paper investigates a progress of the maturity of the Czech intraday electricity market during the COVID-19 pandemic by employing the multifractal analysis. Our results indicate that since intraday electricity returns display multifractal property originating both from long-range correlations and fat-tailed distribution, a sole use of the Hurst exponent is not sufficient, and multifractality characteristics should be used. The quantities describing a multifractal behavior indicate in some periods higher stage of market development operating on short temporal scales compared to the larger temporal scales, especially the MLM index. In some periods, they are in close agreement with the Hurst approach (e.g., July 2020). Moreover, the ADL models indicate a positive association of the Hurst exponent on short temporal scales with its lagged values and new cases of the COVID-19. On short temporal scales, the rate of new COVID-19 cases was positively related to the strength of multifractality, i.e., smaller degree of maturity, both by singularity spectrum width and MLM index. We found a nonlinear relationship between the government stringent policy and the Hurst exponent on long temporal scales, singularity spectrum width and the MLM index on short temporal scales, indicating that the loose anti-COVID policies are associated with more mature market and vice versa. On the contrary, on its long counterpart, the relationships are weaker and opposite in signs.

Characterization of Genetic Mutations Using DNA Walks and Multifractal Detrended Fluctuation Analysis

Monitoring genetic mutations in DNA sequences and their subsequent characterisation provide the possibility for rapid development of diagnostics and therapeutic tools. Here, it is shown that the "DNA walk" (DNAW) representation together with multifractal detrended fluctuation analysis (MFDFA), i.e. DNAW/MFDFA, form a reliable characterization method for studying local and global properties of similar DNA sequences. The DNAW/MFDFA approach allows to study the stochastic properties of genetic sequences by constructing a one-to-one map of the sequence onto a walk, and is able to uncover the self-similarity properties of DNA walks. These features are illustrated on a set of similar DNA sequences of SARS-CoV-2 virus, in which the differences in nucleotide bases arise due to genetic mutations. The results show that DNAW/MFDFA can be used to extract long-range correlation information and type and degree of fractal complexity.

Fast and Accurate Deep Learning Framework for Secure Fault Diagnosis in the Industrial Internet of Things

This article introduced a new deep learning framework for fault diagnosis in electrical power systems. The framework integrates the convolution neural network and different regression models to visually identify which faults have occurred in electric power systems. The approach includes three main steps: 1) data preparation;2) object detection;and 3) hyperparameter optimization. Inspired by deep learning and evolutionary computation (EC) techniques, different strategies have been proposed in each step of the process. In addition, we propose a new hyperparameters optimization model based on EC that can be used to tune parameters of our deep learning framework. In the validation of the framework's usefulness, experimental evaluation is executed using the well known and challenging VOC 2012, the COCO data sets, and the large NESTA 162-bus system. The results show that our proposed approach significantly outperforms most of the existing solutions in terms of runtime and accuracy.

The impacts of demand and supply shocks in the dry bulk shipping market

The freight rate is a representative variable in the shipping market and is characterized by a cyclical re-lationship. Even though downturns in the shipping market, such as the shipping industry recession in the 1980s, the global financial crisis in 2008 and COVID-19 crisis in 2020, recur, few studies have analyzed the dynamic relationship between supply and demand in terms of its effect on freight rates. Thus, this study classifies the factors affecting fluctuations in dry cargo freight rates into demand, supply, and freight rate specific demand factors, which play the most important role in managing risk in the shipping market. Based on the recursive structural vector autoregressive (recursive SVAR) model, we analyze the historical con-tributions of the effects of each factor across different time periods. Two main findings are summarized as follows: first, we identify the dynamic relationship between factors affecting BDI in the shipping market, and reveal that the magnitude and direction of factors are different. Second, we verify that in an extreme situation in which freight rates exceed the normal range, the market is overheated, and freight rates are therefore determined by the freight rate specific demand of market participants rather than by the actual supply and demand.(c) 2023 The Authors. Production and hosting by Elsevier B.V. on behalf of The Korean Association of Shipping and Logistics, Inc. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).

ENLIGHTENMENT OF INTERNATIONAL CARBON EMISSION TRADING PRACTICE TO CHINA

In the era of "Post-epidemic" and "Dual-carbon targets", the focus of research on China's carbon trading market has changed from basic framework design to problem solving and development paths in the process of practice. Foreign carbon trading markets have developed for many years, and have experienced the financial crisis and the impact of the coronavirus epidemic. By analyzing the important problems and countermeasures encountered in the process of carbon trading market by representative organizations such as EU, USA, New Zealand, Korea and Japan, the valuable experience and reference significance of foreign carbon trading practice were summarized. At the same time, comparing the similarities and differences between Chinese and foreign carbon trading national conditions, and taking into account the current development of China's carbon trading market, this paper put forward some carbon trading strategies with Chinese characteristics and absorbing foreign advanced experience, such as choosing appropriate emission caps, balancing regulation, formulating price stabilization mechanism, and leaving interfaces for international cooperation. © 2023 Research Institute of Petroleum Processing, SINOPEC. All rights reserved.

Analysis of the relationship between bitcoin, oil prices, and the Dow Jones Industrial Average using a wavelet-based approach

This paper analyzes the correlation between bitcoin, oil price fluctuations and the DOW Jones Industrial Index in the time-frequency framework. Coherent wavelet method applied to recent daily data in the United States (1863 in total). Our research has several implications and supports for policy makers and asset managers. We find that oil prices lead the U.S. market at both low and high frequencies throughout the observation period. This result suggests that sanctions against Russia by a number of countries, including the U.S., are influencing oil prices, while oil remains a major source of systemic risk to the U.S. economy and economic uncertainty between the international level is exacerbated by tensions between Russia and Ukraine. © COPYRIGHT SPIE.

Output and Energy Prices Fluctuations in Response to Market Shocks: System Dynamic Modeling

Regardless of the fact, whether governments of particular country implemented the strong lockdown measures to prevent the spread of COVID-19 or not, the economies of each country all over the word have been suffered considerably due to the shocks caused by the pandemic. We observed slowdown of economic activity, macroeconomic instability and shifts in consumption preferences supplemented by rising unemployment as well as significant fluctuation of demand and production capability. The research problem addressed in this paper focuses on dynamic properties of output and inflation fluctuations that occur in response to economic shocks different magnitudes and types. We use a system dynamic approach and constructs two system dynamic models to examine the dynamics of output, prices, wage and inflation. The paper indicates ranges of relevant parameters' values that correspond with sensitivity of output to demand and production capability changes related to possibility of reaching new equilibrium point. To explore the variety of prices and wage behavior in response to shocks we evaluate distinguish possible phase diagrams associated with stable node, stable focus, circle, unstable focus and unstable node. The results is a contribution to discussion of the policy issues related to mitigation of recession caused by unpredictable and strong shocks.

Dynamic impacts of online investor sentiment on international crude oil prices

In recent years, international crude oil prices have been subject to unusually high fluctuations due to the ravages of the COVID-19 epidemic. Under such extreme market conditions, online investor sentiment can strengthen the correlation between oil price changes and external events. We use a (rolling-window) structural vector autoregression method to investigate the dynamic impact of online investor sentiment on WTI crude oil prices before and after the COVID-19 pandemic across multiple topics of price, supply, demand, and so on, which aims to explore the fluctuation mechanism driven by sentiment and the price changes triggered by public health events. The proposed aspect-level sentiment analysis approach can effectively distinguish and measure sentiment scores of different aspects of the oil market. Our results show that the constructed oil price prosperity index contributes 49.84% to the long-term fluctuations of WTI oil price, ranking first among the influencing factors considered. In addition, the peak value of impulse shocks to WTI oil prices rose from 6.47% to 8.40% during the period of dramatic price volatility caused by the epidemic. The results sketch the mechanisms by which investor sentiment can affect crude oil prices, which help policymakers and investors protect against extreme risks in the oil market. © 2023 Elsevier Ltd

ENLIGHTENMENT OF INTERNATIONAL CARBON EMISSION TRADING PRACTICE TO CHINA

In the era of "Post-epidemic" and "Dual-carbon targets", the focus of research on China's carbon trading market has changed from basic framework design to problem solving and development paths in the process of practice. Foreign carbon trading markets have developed for many years, and have experienced the financial crisis and the impact of the coronavirus epidemic. By analyzing the important problems and countermeasures encountered in the process of carbon trading market by representative organizations such as EU, USA, New Zealand, Korea and Japan, the valuable experience and reference significance of foreign carbon trading practice were summarized. At the same time, comparing the similarities and differences between Chinese and foreign carbon trading national conditions, and taking into account the current development of China's carbon trading market, this paper put forward some carbon trading strategies with Chinese characteristics and absorbing foreign advanced experience, such as choosing appropriate emission caps, balancing regulation, formulating price stabilization mechanism, and leaving interfaces for international cooperation. © 2023 Research Institute of Petroleum Processing, SINOPEC. All rights reserved.

Speculation and clarification announcements on stock price fluctuations: Why are rumours plausible and hard to clarify?

During the COVID-19 pandemic, stock markets were fragile and sensitive to downside news regardless of whether the news was true. In China, stock rumours are increasingly rampant, affecting the sound development of the capital market. By manually gathering a sample of rumours about Chinese A-share firms, this paper studies the effects of stock market rumours and the corresponding rumour clarifications on stock returns. The study suggests that rumours rely on the information environment to persuade the market through the media effect. In terms of information disclosure, for firms that previously disclosed "negative news”, stock prices would experience abnormal drops when negative rumours appear. In terms of the media effect, rumours released by leading media cause even more significant abnormal fluctuations in stock prices. Further study shows that positive rumours significantly cause an abnormal rise in state-owned enterprises' stock prices, while negative rumours significantly cause an abnormal decline in small and medium enterprise board (SME) and growth enterprise market board (GEM) stock prices. From the perspective of the effect of clarification announcements in restraining stock price fluctuations, clear and timely clarifications are recommended. © 2023 Elsevier Inc.

Screening and identification of potential MERS-CoV papain-like protease (PLpro) inhibitors; Steady-state kinetic and Molecular dynamic studies.

MERS-CoV belongs to the coronavirus group. Recent years have seen a rash of coronavirus epidemics. In June 2012, MERS-CoV was discovered in the Kingdom of Saudi Arabia, with 2,591 MERSA cases confirmed by lab tests by the end of August 2022 and 894 deaths at a case-fatality ratio (CFR) of 34.5% documented worldwide. Saudi Arabia reported the majority of these cases, with 2,184 cases and 813 deaths (CFR: 37.2%), necessitating a thorough understanding of the molecular machinery of MERS-CoV. To develop antiviral medicines, illustrative investigation of the protein in coronavirus subunits are required to increase our understanding of the subject. In this study, recombinant expression and purification of MERS-CoV (PLpro), a primary goal for the development of 22 new inhibitors, were completed using a high throughput screening methodology that employed fragment-based libraries in conjunction with structure-based virtual screening. Compounds 2, 7, and 20, showed significant biological activity. Moreover, a docking analysis revealed that the three compounds had favorable binding mood and binding free energy. Molecular dynamic simulation demonstrated the stability of compound 2 (2-((Benzimidazol-2-yl) thio)-1-arylethan-1-ones) the strongest inhibitory activity against the PLpro enzyme. In addition, disubstitutions at the meta and para locations are the only substitutions that may boost the inhibitory action against PLpro. Compound 2 was chosen as a MERS-CoV PLpro inhibitor after passing absorption, distribution, metabolism, and excretion studies; however, further investigations are required.

Speculation and clarification announcements on stock price fluctuations: Why are rumours plausible and hard to clarify?

During the COVID-19 pandemic, stock markets were fragile and sensitive to downside news regardless of whether the news was true. In China, stock rumours are increasingly rampant, affecting the sound development of the capital market. By manually gathering a sample of rumours about Chinese A-share firms, this paper studies the effects of stock market rumours and the corresponding rumour clarifications on stock returns. The study suggests that rumours rely on the information environment to persuade the market through the media effect. In terms of information disclosure, for firms that previously disclosed "negative news”, stock prices would experience abnormal drops when negative rumours appear. In terms of the media effect, rumours released by leading media cause even more significant abnormal fluctuations in stock prices. Further study shows that positive rumours significantly cause an abnormal rise in state-owned enterprises' stock prices, while negative rumours significantly cause an abnormal decline in small and medium enterprise board (SME) and growth enterprise market board (GEM) stock prices. From the perspective of the effect of clarification announcements in restraining stock price fluctuations, clear and timely clarifications are recommended.

The Rupee-Dollar Ratio Fluctuations: Challenges and Impact on the Economy

Indian witnessed its record lowest ever currency fall in a matter of few days. The Rupee loss meant that it's a gain for the US Dollar. There have been numerous reasons which paved way to the diminishing value of Indian rupee. Within a timeframe of just 75 years a sharp rise to 79INR/1USD could be witnessed in the year 2022. The value of Rupees has diminished by about seventeen times during this time frame. There has been numerous reasons for the fall in the vale of Rupee such as the Russia-Ukraine war, inflation rate, crude oil price change etc. the fall in Rupee value has put the Indian economy in great stress and challenge creating an impact on the economy. This paper attempts to make a Rupee-Dollar comparison since 2016 to 2022 using data collected from reliable sources and using SPSS software to evaluate the results obtained. Copyright © 2022, Anka Publishers. All rights reserved.

Multi-ligand molecular docking, simulation, free energy calculations and wavelet analysis of the synergistic effects between natural compounds baicalein and cubebin for the inhibition of the main protease of SARS-CoV-2.

Combination drugs have been used for several diseases for many years since they produce better therapeutic effects. However, it is still a challenge to discover candidates to form a combination drug. This study aimed to investigate whether using a comprehensive in silico approach to identify novel combination drugs from a Chinese herbal formula is an appropriate and creative strategy. We, therefore, used Toujie Quwen Granules for the main protease (Mpro) of SARS-CoV-2 as an example. We first used molecular docking to identify molecular components of the formula which may inhibit Mpro. Baicalein (HQA004) is the most favorable inhibitory ligand. We also identified a ligand from the other component, cubebin (CHA008), which may act to support the proposed HQA004 inhibitor. Molecular dynamics simulations were then performed to further elucidate the possible mechanism of inhibition by HQA004 and synergistic bioactivity conferred by CHA008. HQA004 bound strongly at the active site and that CHA008 enhanced the contacts between HQA004 and Mpro. However, CHA008 also dynamically interacted at multiple sites, and continued to enhance the stability of HQA004 despite diffusion to a distant site. We proposed that HQA004 acted as a possible inhibitor, and CHA008 served to enhance its effects via allosteric effects at two sites. Additionally, our novel wavelet analysis showed that as a result of CHA008 binding, the dynamics and structure of Mpro were observed to have more subtle changes, demonstrating that the inter-residue contacts within Mpro were disrupted by the synergistic ligand. This work highlighted the molecular mechanism of synergistic effects between different herbs as a result of allosteric crosstalk between two ligands at a protein target, as well as revealed that using the multi-ligand molecular docking, simulation, free energy calculations and wavelet analysis to discover novel combination drugs from a Chinese herbal remedy is an innovative pathway.

Anti-persistent adherence dynamic of the COVID-19 vaccines

This research explores the multifractal dynamics of time series of the daily number of vaccinees for COVID-19, considering six European countries (Belgium, Denmark, France, Germany, Greece and Italy) using the Multifractal Detrended Fluctuations Analysis (MF-DFA). We calculate the multifractal spectrum f(alpha) and apply a fourth-degree polynomial regression fit to estimate the complexity parameters that describe the degree of multifractality of the underlying process. We found that the multifractal dynamics of all these countries are characterized by strongly anti-persistent behavior (alpha (0) < 0.5) a lower degree of multifractality, and small fluctuations are dominant in the multifractal spectrum. From an immunization perspective, it means that a panorama that encompasses the population's behaviour is marked by the dynamics of anti-persistent adherence to COVID-19 vaccines. Our findings confirm that the period of immunization of the population that adhered to the vaccination campaigns is short and that the application of new doses of vaccines must obey this phenomenology to keep people safe. In addition, we used the multifractal efficiency coefficient to rank countries that are most proactive in developing campaigns that promote greater adherence and loyalty to COVID-19 vaccines. Our findings indicate that Germany, Belgium and France were more efficient than Greece, Denmark and Italy.

Characterization of Genetic Mutations Using DNA Walks and Multifractal Detrended Fluctuation Analysis

Monitoring genetic mutations in DNA sequences and their subsequent characterisation provide the possibility for rapid development of diagnostics and therapeutic tools. Here, it is shown that the "DNA walk" (DNAW) representation together with multifractal detrended fluctuation analysis (MFDFA), i.e. DNAW/MFDFA, form a reliable characterization method for studying local and global properties of similar DNA sequences. The DNAW/MFDFA approach allows to study the stochastic properties of genetic sequences by constructing a one-to-one map of the sequence onto a walk, and is able to uncover the self-similarity properties of DNA walks. These features are illustrated on a set of similar DNA sequences of SARS-CoV-2 virus, in which the differences in nucleotide bases arise due to genetic mutations. The results show that DNAW/MFDFA can be used to extract long-range correlation information and type and degree of fractal complexity.

Can the nucleic acid Ct value of discharged patients infected with SARS-CoV-2 Omicron variant be 35?--A retrospective study on fluctuation of nucleic acid Ct values in SNIEC mobile cabin hospital.

Objective: To explore the meaning of cycle threshold (Ct) value fluctuation and the appropriateness of setting the discharge Ct value to 35, which is the current standard in Chinese guidelines. Method: A retrospective study was conducted on 95 patients with Ct value fluctuation (Ct value below 35 on day 3; group A) and 97 patients with a normal discharge process (control; group B). Their clinical characteristics and follow-up data were collected. Results: (1) There was no significant difference between the groups in age, gender distribution, number of vaccinations, initial ORF-Ct value, and initial N-Ct value. The proportion of patients complicated with chronic internal disorders, respiratory symptoms, and abnormal chest radiology in group A was significantly higher than that in group B. (2) Between the two groups, there was no significant difference in the ORF-Ct or N-Ct value on day 1, but the ORF-Ct and N-Ct values of group B on days 2 to 4 were significantly higher than those of group A. (3) There was no significant difference between the groups in the ORF-Ct value at discharge, but there was a significant difference in the N-Ct value at discharge. Seven days after discharge, almost 100% of the patients had been cured. The mean negative conversion interval of nucleic acid of the patients in group A was 14.5 ± 4.6 days, which was longer than that of the patients in group B (11.8 ± 4 days). (4) Logistic regression analysis showed that the ORF-Ct value on day 2 was the key factor influencing the Ct value fluctuation. Conclusion: The fluctuation of Ct value is only a normal phenomenon in the recovery period of the disease, and there is no need for excessive intervention. It is reasonable to set the Ct value of the discharge standard to 35 and retest the nucleic acid on the 10th day after discharge for patients with underlying diseases or symptoms.

Emergency Distribution Network Design & Analysis for Consecrated COVID 19 Hospital Zone

A power distribution network is always a key topic in a grid system because of more complexity. Rapidly or sudden load increasing to a particular one or two feeders can arise uncertainty and unbalance conditions in the system. Voltage fluctuations, Deviations, THD (total harmonic distortion), Reactive power imbalances can seriously unstable the grid for load increasing situations. In recent days due to COVID 19 condition, dedicated hospitals are connected to the distribution network. Because of its urgency and usefulness, a new type of distribution network called loop plus parallel has been presented in this paper. Finally, the simulation studies show better performance when comparing the traditional types of networks. New distribution network shows promising values in THD, Voltage deviation and also for reactive power imbalance. © 2022 Authors. All rights reserved.

SNIF-DFA: A Signal Processing and Information Fusion Method for Smart Gua Sha Device

Due to the COVID-19 global pandemic, there are more needs for remote patient care especially in rehabilitation requiring direct contact. However, traditional Chinese rehabilitation technologies, such as gua sha, often need to be implemented by well-trained professionals. To automate and professionalize gua sha, it is necessary to record the nursing and rehabilitation process and reproduce the process in developing smart gua sha equipment. This paper proposes a new signal processing and sensor fusion method for developing a piece of smart gua sha equipment. A novel stabilized numerical integration method based on information fusion and detrended fluctuation analysis (SNIF-DFA) is performed to obtain the velocity and displacement information during gua sha operation. The experimental results show that the proposed method outperforms the traditional numerical integration method with respect to information accuracy and realizes accurate position calculations. This is of great significance in developing robots or automated machines that reproduce the nursing and rehabilitation operations of medical professionals. IEEE

Glycyrrhizin as a promising kryptonite against SARS-CoV-2: Clinical, experimental, and theoretical evidences.

COVID-19 is the most devastating disease in recent times affecting most people globally. The higher rate of transmissibility and mutations of SARS-CoV-2 along with the lack of potential therapeutics has made it a global crisis. Potential molecules from natural sources could be a fruitful remedy to combat COVID-19. This systematic review highlights the detailed therapeutic implication of naturally occurring glycyrrhizin and its related derivatives against COVID-19. Glycyrrhizin has already been established for blocking different biomolecular targets related to the SARS-CoV-2 replication cycle. In this article, several experimental and theoretical evidences of glycyrrhizin and related derivatives have been discussed in detail to evaluate their potential as a promising therapeutic strategy against COVID-19. Moreover, the implication of glycyrrhizin in traditional Chinese medicines for alleviating the symptoms of COVID-19 has been reviewed. The potential role of glycyrrhizin and related compounds in affecting various stages of the SARS-CoV-2 life cycle has also been discussed in detail. Derivatization of glycyrrhizin for designing potential lead compounds along with combination therapy with other anti-SARS-CoV-2 agents followed by extensive evaluation may assist in the formulation of novel anti-coronaviral therapy for better treatment to combat COVID-19.