Search

This paper has investigated the predictability of the top ten 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 behaviour.

Green bonds are financial assets similar to classic debt securities used to finance sustainable investments. Given this, they are a long-term investment alternative that effectively contributes to the planet’s future by preserving the environment and encouraging sustainable development. This research encompasses a rich dataset of equity and bond sectors, general indices, and the S&P Green Bond Index. We estimate the permutation entropy [Formula: see text], an appropriate statistical complexity measure [Formula: see text], and Fisher Information measure [Formula: see text]. Therefore, we employ these complexity measures to construct two 2D maps, the complexity-entropy causality plane ([Formula: see text] ×[Formula: see text]) and the Shannon–Fisher causality plane ([Formula: see text] ×[Formula: see text]). Also, we use the information theory quantifiers to rank these indices’ efficiency analogous to the complexity hierarchy. From a mathematical point of view, the complexity-entropy causality plane (CECP) is a map that considers the global analysis, while the SFCP is a map that simultaneously feels the global and local analysis. Our findings reveal that both 2D maps indicated the most efficient (b_info_tech) and least efficient (b_energy) assets. There are peculiarities in the ranking performed considering the information theory quantifiers used to build each map due to the mathematical distinction that underlies the construction of each map. Moreover, we applied two clustering approaches ([Formula: see text]-means and Hierarchical cluster) that categorically converged in the indication of four distinct groups, which allowed us to verify that, in an overview, equities present a unique dynamic when compared to bonds and the Green bond index.

This paper performs the asymmetric multifractal cross-correlation analysis to examine the COVID-19 effects on three relevant high-frequency fiat currencies, namely euro (EUR), yen (YEN) and the Great Britain pound (GBP), and two cryptocurrencies with the highest market capitalization and traded volume (Bitcoin and Ethereum) considering two periods (Pre-COVID-19 and during COVID-19). For both periods, we find that all pairs of these financial assets are characterized by overall persistent cross-correlation behavior [Formula: see text]. Moreover, COVID-19 promoted an increase in the multifractal spectrum’s width, which implies an increase in the complexity for all pairs considered here. We also studied the Generalized Cross-correlation Exponent, which allows us to verify that there is no asymmetric behavior between Bitcoin and fiat currencies and between Ethereum and fiat currencies. We conclude that investing simultaneously in major fiat currencies and leading cryptocurrencies can reduce the portfolio risk, leading to improvement in the investment results.

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(α) 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 (α 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.

Independent of science branch, scientists have a consensus that peoples 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.

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.

Cryptocurrencies play a pivotal role in the financial market. Given this, we perform the asymmetric multifractal cross-correlation analysis to examine the weak form of the Efficient Market Hypotheses (EMH) considering two temporal scales. In the daily scale, we find that the pair Bitcoin–Litecoin displays the largest multifractal spectrum. While, in the hourly scale, the pair Bitcoin–Ethereum presents the largest multifractal spectrum. Our empirical evidence has rejected the weak form of the EMH and clearly suggests that the dynamics of the analyzed cryptocurrency pairs are in line with the Fractal Market Hypothesis (FMH). Cross-correlation asymmetries are more persistent for small fluctuations than for large fluctuations. The results are essential for investors, portfolio and risk managers, and policymakers.

The management of colorectal cancer liver metastasis (CRLM) has become complex because of the increasing availability of medical, radiological, and surgical treatment options applied either alone or in combination. However, resection remains the only evidence-based curative therapy. These Brazilian Society of Surgical Oncology surgical standards are intended to guide clinicians in the decision-making process for modern surgical management of CRLM within a multidisciplinary team in an evidence-based framework, focusing on resectable disease.

The Probabilistic Foam method (PFM) is a path planner that ensures a volumetric region for safe maneuverability called bubble. This method generates paths bounded by a set of overlapped bubbles, called rosary. In this paper, we present an approach to obtain safe and smooth collision-free paths from PFM for a lower limb active exoskeleton, which is based on two main processes: The rosary adjustment and the path smoothing. The first process keeps the size of the bubbles more regular, while the second process guarantees a smooth and short path, satisfying the safe constraints imposed by the rosary. To evaluate these proposed approaches, we presented a simulation of the exoskeleton leg performing the swing phase movement in three different scenarios: overcoming an obstacle, walking up and down a step. The resulting planned paths were evaluated and compared, considering the path length and the path smoothness.

The walking experience in environments with obstacles is a challenge for patients with lower limb pathology. A transparent exoskeleton is an interesting solution since it guarantees the performance of autonomous motion. In this paper, we present a new method to detect and model steps using point cloud data to find a feasible path for the exoskeleton to perform. We use a RGB-D sensor to obtain depth information and perform a scene segmentation strategy. Next, we classify the different detected elements either as a floor, step or obstacle and then use a path planning method to find a collision-free path. Experiments show that the system accomplished satisfactory results for the presented scenarios.

Este trabalho apresenta uma arquitetura baseada em redes definidas por software (Software-Defined Network - SDN), intitulada SD-FANET, para gerenciar um sistema de múltiplos VANTs (Veículos Aéreos Não Tripulados) utilizado na varredura de área de impacto de foguetes suborbitais. Tal aplicação está contida no projeto SPACEVANT, o qual está em andamento. Para idealização da arquitetura SD-FANET, além dos requisitos da aplicação de varredura de área e do projeto, foram tomadas como referência outras soluções disponíveis na literatura. Nesse sentido é feita uma comparação entre arquiteturas conforme características importantes para esse tipo de aplicação. Como resultado é apresentado o design da arquitetura, o qual é composto por um controlador SDN hierárquico distribuído capaz de implementar funções de gerenciamento de monitoramento, mobilidade, topologia, roteamento, QoS e eleição. As funções de todos os componentes são descritas, assim como todo o fluxo de mensagens.

This paper presents an approach to simplify the path planning for an active orthosis through the application of the Probabilistic Foam Method. In this method, a structure called probabilistic foam was formed by a set of bubbles that propagates through the free space starting from an initial configuration to a goal configuration. Thus, it is possible to extract an obstacle-free path. Bubbles ensure safe region, meeting the safety requirements in maneuvering. In this paper, the method uses workspace metrics instead of configuration space metrics, enabling its application on robotics problems defined in high-dimensional spaces. Preliminary results show that the method was able to plan the safe movement to be performed by an active orthosis, transposing obstacles and performing safe movements in the proposed scenario

This paper presents the development of a computer vision algorithm that uses planar regions obtained images captures through a stereo camera in order to provide essential information about the environment allied with low computational cost. The proposed algorithm is used to detect obstacles in the field of view of a stereo camera embedded in an active orthosis for lower limbs, developed for assistive walking applications. The main objective is to collect data from the surroundings of the orthosis in order to construct a local map, based on dense planar SLAM, that will be used to detect obstacles and other ground irregularities, providing the orthosis with adequate information for planning autonomous movements during walking. The paper presents the mechanical exoskeleton developed to implement the orthosis, the proposed strategy adopted for creating local maps from planar regions, and some preliminary results.

Este trabalho apresenta uma proposta para um sistema multi-VANT(Véıculo Aéreo Não Tripulado) para monitoramento deárea de proteção ambiental. Para tal é feita uma especificação de uma arquitetura de comunicação para os componentes de rede, escolha de uma tecnologia para troca de dados e uma breve apresentação do sistema de visão computacional. Como resultado preliminar foi realizada uma comparação entre os módulos XBee S1 e S3 para definir qual será embarcado nas aeronaves.

This paper presents an improved variation of Probabilistic Foam Method (PFM) for robot path planning. In PFM, a structure named probabilistic foam, formed by bubbles propagate through the free space from initial configuration to goal as a breadth-first search, obtaining a collision-free path. Although the method is able to obtain a navigable path, it is computationally expensive. We propose a new foam propagation approach inspired on random tree growth from RRT. Results from simulation experiments using 2D and 3D map show benefits with the new method.

No planejamento de movimentos para uma ortese ativa para membros inferiores, e necessario considerar que se trata de uma tecnologia assistiva, ou seja, exige um certo grau de seguranca e contabilidade nos movimentos gerados. Alem disso, e um problema robotico de alta dimensao, repetindo no custo computacional. Nesse contexto, este artigo apresenta uma abordagem para simplificar o planejamento de movimentos para uma ortese ativa atraves da aplicacao do metodo Espuma Probabilistica (Probabilistic Foam Method - PFM). No PFM, uma estrutura chamada Espuma Probabilistica, formada por um conjunto de bolhas, se propaga pelo espaco livre partindo de uma configuracao inicial ate uma configuracao Final, sendo possivel extrair um caminho livre de obstaculos. As bolhas da espuma garantem regioes seguras de manobrabilidade, atendendo aos requisitos de seguranca na manobra. Dessa forma, o PFM foi aplicado no planejamento da ultrapassagem de um obstaculo por uma ortese ativa para os membros inferiores. Apesar de serem apresentados resultados preliminares, o metodo foi capaz de planejar o movimento seguro a ser realizado pelo robo no cenario proposto.

Este trabalho apresenta uma proposta para um sistema multi-VANT (Veiculo Aereo nao Tripulado) para monitoramento de _area de protecao ambiental. APAs sao regioes limitadas que visam a conservacao dos recursos naturais e ecossistemas. Entretanto, controlar acoes antropicas ilegais e um problema, dessa forma, faz-se necessario acoes de monitoramento. Para tal e apresentada a especificacao de uma arquitetura de comunicacao entre VANTs dentro de uma rede por meio de modulos XBee. E proposto tambem uma estrategia para elaboracao de um sistema de visao computacional com intuito de detectar carros em areas de dunas com acesso restrito, nesse sentido e feito uma breve descricao com informacoes iniciais para sua construcao. Como resultados foram apresentadas as possiveis formas de configuracao do sistema de comunicacao e o comportamento do link de comunicacao em diferentes modelos de propagacao. Constatou-se que o modulo XBee S3 permite uma distância entre os pontos de comunicacao de ate 6 km sem comprometer o desempenho do sistema.

Power companies usually answer the increase in power demand by building new generation facilities. Nevertheless, an efficient use of energy could reduce and delay the costs of investment in new power plants. This paper shows a software system to manage transformers and evaluate losses when they work with zero loads. This system contributes to reduce the waste of energy with some simple actions such as shutting off an unused transformer or reconnecting disabled equipment based on the customer’s demand. It uses real time measurements collected from Intelligent Electronic Devices as a base for software decisions. It also measures and reports the total power saving. Las compañías eléctricas por lo general responden al aumento de la demanda de energía mediante la construcción de nuevas instalaciones de generación. Sin embargo, un uso eficiente de la energía podría reducir y retrasar los gastos de inversión en nuevas centrales eléctricas. En este trabajo se muestra el sistema de software para gestionar transformadores y evaluar las pérdidas cuando trabajan con cero cargas. Este sistema ayuda a reducir la pérdida de energía con acciones simples como: Desenergizar un transformador no utilizado o volver a conectar el equipo con base en la demanda del cliente. Utiliza las mediciones en tiempo real obtenidas de la base de Intelligent Electronic Devices para el software de Decisiones. También mide e informa el ahorro total de energía.

SUMMARY The present study is a review of data available in Brazil on bacterial diseases transmitted through the consumption of seafood and related products. Data are presented regarding outbreaks and cases of disease and laboratory findings associated with pathogens in seafood and related products, and methods for prevention and control are described. RESUMO Esta revisão apresenta dados qualitativos e quantitativos sobre doenças bacterianas e achados laboratoriais associados ao consumo de pescado e derivados no Brasil de 1983 a 2011. Os resultados mostram uma séria lacuna de dados epidemiológicos relacionados a surtos causados por pescado. Os poucos dados disponíveis indicam que em contraste com outros surtos alimentares transmitidos por carne, aves, laticínios e vegetais, as bactérias patogênicas teriam um menor destaque na transmissão destas doenças pelo consumo de pescado e derivados. Vibrio parahaemolyticus parece ser a causa mais frequente das doenças causadas pelo consumo de pescado e derivados, bem como a bactéria patogênica mais comumente presente nesses produtos nas investigações laboratoriais.

Este artigo visa comprovar a eficiência da ação bactericida do Cloridrato de Polihexametileno Biguanida (PHMB), na desinfecção de indústrias cervejeiras bem como verificar seu custo benefício. Para tal, utilizou-se o produto Biguatin 400 (que contém 4% do princípio ativo) em diferentes concentrações nos tanques de fermentação de uma planta piloto de cervejaria, seguido de análise microbiológica. Ao final disto, avaliaram-se os resultados que mostraram o grau de eficiência do princípio ativo.