This paper performs a systematic investigation into the temporal evolution of daily death cases of COVID-19 worldwide lethality considering 90 countries. We apply the information theory quantifiers, more specifically the Permutation entropy [Formula: see text] and Fisher information measure [Formula: see text] to construct the Shannon-Fisher causality plane (SFCP), which allows us to quantify the disorder and evaluate randomness present in the time series of daily death cases related to COVID-19 in each country. Moreover, we employ [Formula: see text] and [Formula: see text] to rank the COVID-19 lethality in these countries based on the complexity hierarchy. Our findings reveal that the countries that are located farther from the random ideal position ([Formula: see text], [Formula: see text]) in the SFCP such as Taiwan, Vietnam, New Zealand, Singapore, Monaco, Iceland, Thailand, Bahamas, Cyprus, Australia, and Norway are characterized by a less entropy and low disorder, which leads to high predictability of the COVID-19 lethality. Otherwise, the countries that are located near to the random ideal position ([Formula: see text], [Formula: see text]) in the SFCP such as Ecuador, Czechia, Iraq, Colombia, Belgium, Italy, Philippines, Iran, Peru, and Japan are characterized by high entropy and high disorder, which implies low predictability of the COVID-19 lethality. We also employ two cluster techniques to analyze the similarity considering the temporal evolution of COVID-19 worldwide lethality for the countries investigated. Based on the values of [Formula: see text], [Formula: see text] and our cluster analysis, we suggest that this health crisis will only be adequately combated through global adherence to scientific exchange and technology sharing to homogenize the actions to combat the COVID-19.

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We examine the price disorder and market efficiency of five cryptocurrencies (Bitcoin, BNB, Cardano, Ethereum, and XRP) before and during COVID-19 pandemic period. Using permutation entropy and Fisher information measure (FIM), we construct the Shannon-Fisher causality plane (SFCP) to map these cryptocurrencies and their respective locations in a two-dimensional plane and then apply sliding time window approach to study the temporal evolution of efficiency. All cryptocurrencies exhibit high but slightly varying informational efficiency during both periods. Cardano is the most efficient. These results might point to the increasing maturity and lower potential for price predictability, which matter to cryptocurrencies usage for liquidity risk diversification strategy.

This research explores the predictability of the Brazilian inflation monthly price indexes time series by information theory quantifiers. Given this, we apply the Bandt and Pompe method to estimate the information theory quantifiers, specifically the Permutation entropy ([Formula: see text]) and the Fisher information measure ([Formula: see text]). Based on the values of both complexity measures, we construct the 2D plane called the Shannon-Fisher causality plane, which allows us to explore the disorder and quantify the randomness inherent to the temporal evolution of the significant Brazilian inflation indexes. Also, we apply [Formula: see text] and [Formula: see text] to rank the Brazilian inflation indexes based on the complexity hierarchy. An overview shows that the Brazilian inflation indexes display lower entropy which implies in higher predictability. The sliding window approach reveals that Brazilian inflation indexes (IPA, IPCA, IGP, IPC, and INPC) present decrease related to efficiency. The only exception is the INCC, which shows an increase in efficiency.

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Independent of science branch, scientists have a consensus that people’s lives are highly susceptible to risk, and effectively quantifying risk is a big challenge. This paper assesses the Multifractal Cross-Correlation Measure (MRCC) among West Texas Intermediate (WTI), seven fiat currencies and three foreign exchange rates. Therefore, we use the Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) to examine the volatility dynamics considering the pairs of these financial records. We discover that all these volatility time series pairs [Formula: see text] are characterized by overall persistent behavior based on the values of [Formula: see text]. The MRCC values exhibit that the pairs WTI versus MXN [Formula: see text], WTI versus JPY [Formula: see text] and WTI versus NOK [Formula: see text] are more complex and persistent than the other pairs. Otherwise, the pairs WTI versus AUD [Formula: see text], WTI versus CAD [Formula: see text] and WTI versus EMK [Formula: see text] are less complex and persistent. Thus, our empirical findings shed light on the problem of quantification risk based on a multifractal perspective.

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Poucos são os estudos que destacam o efeito de diferentes regimes hídricos sobre o crescimento de plantas da Caatinga; ao passo que modelos matemáticos empíricos são utilizados em larga escala na modelagem de crescimento de plantas, mas também tem sido pouco aplicados para espécies desse bioma. Objetivou-se avaliar o crescimento inicial e o desempenho de modelos matemáticos no ajuste de dados biométricos e de biomassa de espécies ocorrentes na caatinga sob diferentes regimes hídricos. Um experimento foi conduzido, em condições de viveiro, no município de Serra Talhada, PE, com as espécies Caesalpinia pyramidallis Tul. (catingueira) e Prosopis juliflora Sw (DC.) (algaroba) submetidas a regimes hídricos com base na evapotranspiração de referência (ETo) (50%.ETo, 75%.ETo, 100%.ETo e 125%.ETo). Ao longo do tempo foram feitas medições biométricas e de biomassa nas plantas. Foram testados os modelos de Gompertz, Sigmoidal, Logístico, Chapman e Gaussiano, usando como variáveis independentes, os dias após a semeadura e graus dias acumulados. Os quatro regimes hídricos não exerceram influência na matéria seca da raiz, e não se observou diferenças para o acúmulo de matéria seca das folhas e da planta nas lâminas superiores a 75% de ETo. P. juliflora apresentou maior emissão de folíolos, porém não se diferenciou em área foliar da C pyramidalis. As variáveis biométricas da catingueira e da algaroba foram melhores ajustadas pelo modelo de Gompertz, enquanto os de Chapman e Gaussiano foram os que mais explicaram a variação dos dados de biomassa nos distintos regimes hídricos, utilizando como variável independente os graus dias acumulados. Palavras-chave: algaroba, biometria, biomassa, catingueira, graus dias, modelagem, regressão não linear. Species Caesalpinia pyramidalis Tul. and Prosopis juliflora Sw (DC.) on different water regimes: growth and mathematical models fitting A B S T R A C T Few are the studies that highlight the effect of different water regimes on the plants growth of the Caatinga; while empirical mathematical models are used in a large scale in the modelling of plants growth, but it also has been applied to species of this biome. Objective to evaluate the initial growth and performance of mathematical models in the adjustment of biometric and biomass data of species occurring in the caatinga under different water regimes. An experiment was conducted under conditions of viveiro, in the municipality of Serra Talhada, State of Pernmabuco, with the species Caesalpinia pyramidallis Tul. (catingueira) and Prosopis juliflora Sw (DC.) (algaroba) submitted to water regimes based on the reference evapotranspiration (ETo) (50%.ETo, 75%.ETo, 100%.ETo and 125%.ETo). Over time biometric and biomass measurements in plants were made. The Gompertz, Logistic, Sigmoid, Chapman and Gaussian models were tested, using as independent variables, the days after sowing and degrees days accumulated. The four water regimes do not exerted influence on root dry matter, and was not observed differences for dry matter accumulation of leave...