Approximate entropy normalized measures for analyzing social neurobiological systems

When considering time series data of variables describing agent interactions in social neurobiological systems, measures of regularity can provide a global understanding of such system behaviors. Approximate entropy (ApEn) was introduced as a nonlinear measure to assess the complexity of a system behavior by quantifying the regularity of the generated time series. However, ApEn is not reliable when assessing and comparing the regularity of data series with short or inconsistent lengths, which often occur in studies of social neurobiological systems, particularly in dyadic human movement systems. Here, the authors present two normalized, nonmodified measures of regularity derived from the original ApEn, which are less dependent on time series length. The validity of the suggested measures was tested in well-established series (random and sine) prior to their empirical application, describing the dyadic behavior of athletes in team games. The authors consider one of the ApEn normalized measures to generate the 95th percentile envelopes that can be used to test whether a particular social neurobiological system is highly complex (i.e., generates highly unpredictable time series). Results demonstrated that suggested measures may be considered as valid instruments for measuring and comparing complexity in systems that produce time series with inconsistent lengths.

Topological entropy of catalytic sets: Hypercycles revisited

The dynamics of catalytic networks have been widely studied over the last decades because of their implications in several fields like prebiotic evolution, virology, neural networks, immunology or ecology. One of the most studied mathematical bodies for catalytic networks was initially formulated in the context of prebiotic evolution, by means of the hypercycle theory. The hypercycle is a set of self-replicating species able to catalyze other replicator species within a cyclic architecture. Hypercyclic organization might arise from a quasispecies as a way to increase the informational containt surpassing the so-called error threshold. The catalytic coupling between replicators makes all the species to behave like a single and coherent evolutionary multimolecular unit. The inherent nonlinearities of catalytic interactions are responsible for the emergence of several types of dynamics, among them, chaos. In this article we begin with a brief review of the hypercycle theory focusing on its evolutionary implications as well as on different dynamics associated to different types of small catalytic networks. Then we study the properties of chaotic hypercycles with error-prone replication with symbolic dynamics theory, characterizing, by means of the theory of topological Markov chains, the topological entropy and the periods of the orbits of unimodal-like iterated maps obtained from the strange attractor. We will focus our study on some key parameters responsible for the structure of the catalytic network: mutation rates, autocatalytic and cross-catalytic interactions.

Human and climatic change impact modelling on the habitat suitability for the chimpanzee (Pan troglodytes ellioti) – Case study: The proposed Mount Cameroon National Park

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Fly by data link: feasibility of a relative navigation solution for aviation relying on a future L-band data link

Trabalho final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Fractional Order Generalized Information

This paper formulates a novel expression for entropy inspired in the properties of Fractional Calculus. The characteristics of the generalized fractional entropy are tested both in standard probability distributions and real world data series. The results reveal that tuning the fractional order allow an high sensitivity to the signal evolution, which is useful in describing the dynamics of complex systems. The concepts are also extended to relative distances and tested with several sets of data, confirming the goodness of the generalization.

Nonautonomous Graphs and Topological Entropy of Nonautonomous Lorenz Systems

In this work, we associate a p-periodic nonautonomous graph to each p-periodic nonautonomous Lorenz system with finite critical orbits. We develop Perron-Frobenius theory for nonautonomous graphs and use it to calculate their entropy. Finally, we prove that the topological entropy of a p-periodic nonautonomous Lorenz system is equal to the entropy of its associated nonautonomous graph.

Relative abelian kernels of some classes of transformation monoids

Bulletin of the Australian Mathematical Society, nº 73 (2006), p. 375-404

Relative Frequency of Nosocomial Microorganisms at Unicamp University Hospital from 1987 to 1994

The frequency of microorganisms identified in nosocomial infections at Unicamp University Hospital from 1987 to 1994 was analysed. The most common microorganism was S. aureus (20.9%), which was found in surgical wound, bloodstream and arterial-venous infections. In urinary tract infections (UTI), gram-negative rods (56.5%) and yeasts (9%) predominated. A. baumannii isolates were observed to have increased in the last three years. There was a gradual increase in the frequency of coagulase-negative staphylococci and A. baumannii in bloodstream infections but there wasn’t any change in Candida sp

Quantificação da complexidade do ritmo cardíaco usando o método da Multiscale Entropy

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Fractional Order Generalized Information

This paper formulates a novel expression for entropy inspired in the properties of Fractional Calculus. The characteristics of the generalized fractional entropy are tested both in standard probability distributions and real world data series. The results reveal that tuning the fractional order allow an high sensitivity to the signal evolution, which is useful in describing the dynamics of complex systems. The concepts are also extended to relative distances and tested with several sets of data, confirming the goodness of the generalization.

Integer and Fractional Order Entropy Analysis of Earthquake Data-series

This paper studies the statistical distributions of worldwide earthquakes from year 1963 up to year 2012. A Cartesian grid, dividing Earth into geographic regions, is considered. Entropy and the Jensen–Shannon divergence are used to analyze and compare real-world data. Hierarchical clustering and multi-dimensional scaling techniques are adopted for data visualization. Entropy-based indices have the advantage of leading to a single parameter expressing the relationships between the seismic data. Classical and generalized (fractional) entropy and Jensen–Shannon divergence are tested. The generalized measures lead to a clear identification of patterns embedded in the data and contribute to better understand earthquake distributions.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Forecasts of relative performance in tournaments: Evidence from the field

This paper uses a field experiment to investigate the quality of individuals’ forecasts of relative performance in tournaments. We ask players in luck-based (poker) and skill-based (chess) tournaments to make point forecasts of rank. The main finding of the paper is that players’ forecasts in both types of tournaments are biased towards overestimation of relative performance. However, the size of the biases found is not as large as the ones often reported in the psychology literature. We also find support for the “unskilled and unaware hypothesis” in chess: high skilled chess players make better forecasts than low skilled chess players. Finally, we find that chess players’ forecasts of relative performance are not efficient.

Polyethylene glycol 8000+ citrate salts aqueous two-phase systems: Relative hydrophobicity of the equilibrium phases

The Gibbs free energy of transfer of a methylene group, G*(CH2), is reported as a measure of the relative hydrophobicity of the equilibrium phases. Furthermore, G*(CH2) is a characteristic parameter of each tie-line, and for that reason can be used for comparing different tie-lines of a given aqueous two-phase system (ATPS) or even to establish comparisons among different ATPSs. In this work, the partition coefficients of a series of four dinitrophenylated-amino acids were experimentally determined, at 23 °C, in five different tie-lines of PEG8000(sodium or potassium) citrate ATPSs. G*(CH2) values were calculated from the partition coefficients and used to evaluate the relative hydrophobicity of the equilibrium phases. PEG8000potassium citrate ATPSs presented larger relative hydrophobicity than PEG8000sodium citrate ATPSs. Furthermore, the results obtained indicated that the PEG-rich phase (top phase) has higher affinity to participate in hydrophobic hydration interactions than the salt-rich phase (bottom phase).

Rényi entropy and the thermodynamic stability of black holes

Thermodynamic stability of black holes, described by the Rényi formula as equilibrium compatible entropy function, is investigated. It is shown that within this approach, asymptotically flat, Schwarzschild black holes can be in stable equilibrium with thermal radiation at a fixed temperature. This implies that the canonical ensemble exists just like in anti-de Sitter space, and nonextensive effects can stabilize the black holes in a very similar way as it is done by the gravitational potential of an anti-de Sitter space. Furthermore, it is also shown that a Hawking–Page-like black hole phase transition occurs at a critical temperature which depends on the q-parameter of the Rényi formula.