Power law and entropy analysis of catastrophic phenomena

Catastrophic events, such as wars and terrorist attacks, tornadoes and hurricanes, earthquakes, tsunamis, floods and landslides, are always accompanied by a large number of casualties. The size distribution of these casualties has separately been shown to follow approximate power law (PL) distributions. In this paper, we analyze the statistical distributions of the number of victims of catastrophic phenomena, in particular, terrorism, and find double PL behavior. This means that the data sets are better approximated by two PLs instead of a single one. We plot the PL parameters, corresponding to several events, and observe an interesting pattern in the charts, where the lines that connect each pair of points defining the double PLs are almost parallel to each other. A complementary data analysis is performed by means of the computation of the entropy. The results reveal relationships hidden in the data that may trigger a future comprehensive explanation of this type of phenomena.

Shannon entropy analysis of the genome code

This paper studies the chromosome information of twenty five species, namely, mammals, fishes, birds, insects, nematodes, fungus, and one plant. A quantifying scheme inspired in the state space representation of dynamical systems is formulated. Based on this algorithm, the information of each chromosome is converted into a bidimensional distribution. The plots are then analyzed and characterized by means of Shannon entropy. The large volume of information is integrated by averaging the lengths and entropy quantities of each species. The results can be easily visualized revealing quantitative global genomic information.

Entropy analysis of integer and fractional dynamical systems

This paper investigates the adoption of entropy for analyzing the dynamics of a multiple independent particles system. Several entropy definitions and types of particle dynamics with integer and fractional behavior are studied. The results reveal the adequacy of the entropy concept in the analysis of complex dynamical systems.

Effect of hole drilling at the overlap on the strength of single-lap joints

Bonded unions are gaining importance in many fields of manufacturing owing to a significant number of advantages to the traditional fastening, riveting, bolting and welding techniques. Between the available bonding configurations, the single-lap joint is the most commonly used and studied by the scientific community due to its simplicity, although it endures significant bending due to the non-collinear load path, which negatively affects its load bearing capabilities. The use of material or geometric changes in single-lap joints is widely documented in the literature to reduce this handicap, acting by reduction of peel and shear peak stresses at the damage initiation sites in structures or alterations of the failure mechanism emerging from local modifications. In this work, the effect of hole drilling at the overlap on the strength of single-lap joints was analyzed experimentally with two main purposes: (1) to check whether or not the anchorage effect of the adhesive within the holes is more preponderant than the stress concentrations near the holes, arising from the sharp edges, and modification of the joints straining behaviour (strength improvement or reduction, respectively) and (2) picturing a real scenario on which the components to be bonded are modified by some external factor (e.g. retrofitting of decaying/old-fashioned fastened unions). Tests were made with two adhesives (a brittle and a ductile one) varying the adherend thickness and the number, layout and diameter of the holes. Experimental testing showed that the joints strength never increases from the un-modified condition, showing a varying degree of weakening, depending on the selected adhesive and hole drilling configuration.

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.

The black box of health care expenditure growth determinants

In this paper, the determinants of growth of aggregate health expenditures are investigated. The study departs from previous literature in that it looks at differences across countries in growth (and not levels) of health care expenditures. Estimation is made for 24 OECD countries. Health system characteristics usually believed to influence health expenditures growth, like population ageing, the type of health system (public reimbursement, public contract or integrate) and existence of gatekeepers, are found to be non-significant. Nevertheless, there is evidence that health expenditures experienced a clear slower growth in the last decade. The explanation for this slowdown could not be found in the proposed model and should stimulate further research.

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.

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.

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

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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.

Renova black toilet paper: The creation of a glocal market space

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Hole cleaning performance monitoring during the drilling of directional wells

During drilling operation, cuttings are produced downhole and must be removed to avoid issues which can lead to Non Productive Time (NPT). Most of stuck pipe and then Bottom-Hole Assembly (BHA) lost events are hole cleaned related. There are many parameters which help determine hole cleaning conditions, but a proper selection of the key parameters will facilitate monitoring hole cleaning conditions and interventions. The aim of Hole Cleaning Monitoring is to keep track of borehole conditions including hole cleaning efficiency and wellbore stability issues during drilling operations. Adequate hole cleaning is the one of the main concerns in the underbalanced drilling operations especially for directional and horizontal wells. This dissertation addresses some hole cleaning fundamentals which will act as the basis for recommendation practice during drilling operations. Understand how parameters such as Flowrate, Rotation per Minute (RPM), Rate of Penetration (ROP) and Mud Weight are useful to improve the hole cleaning performance and how Equivalent Circulate Density (ECD), Torque & Drag (T&D) and Cuttings Volumes coming from downhole help to indicate how clean and stable the well is. For case study, hole cleaning performance or cuttings volume removal monitoring, will be based on real-time measurements of the cuttings volume removal from downhole at certain time, taking into account Flowrate, RPM, ROP and Drilling fluid or Mud properties, and then will be plotted and compared to the volume being drilled expected. ECD monitoring will dictate hole stability conditions and T&D and Cuttings Volume coming from downhole monitoring will dictate how clean the well is. T&D Modeling Software provide theoretical calculated T&D trends which will be plotted and compared to the real-time measurements. It will use the measured hookloads to perform a back-calculation of friction factors along the wellbore.

Observation of initial clinical manifestations and repercussions from the treatment of 314 human injuries caused by black sea urchins (Echinometra lucunter) on the southeastern Brazilian coast

INTRODUCTION: Injuries caused by sea urchins are the most common caused by marine animals in humans in Brazil, with the black sea urchin (Echinometra lucunter) causing the most injuries to bathers. METHODS: This study observed 314 human wounds with emphasis on the early observation of clinical signs and symptoms and their implications on the recommended treatment. RESULTS: All the injuries were caused by black sea urchins and were observed in bathers. The lesions and the pain were associated with penetration of the spines; there was no early inflammation or pain without pressure on the wounded places. Complications arising from this kind on injury, including infections and foreign body granulomas, are associated with the permanence of the spines in the wounds. CONCLUSIONS: The study confirmed that this kind of injury is the most common accident caused by aquatic animals in Brazil. The main therapeutical recommendation is early removal of the spines to prevent late complications, such as infections and the formation of foreign body granulomas.

Prevalence of enterotoxin-encoding genes and antimicrobial resistance in coagulase-negative and coagulase-positive Staphylococcus isolates from black pudding

INTRODUCTION: Staphylococcal species are pathogens that are responsible for outbreaks of foodborne diseases. The aim of this study was to investigate the prevalence of enterotoxin-genes and the antimicrobial resistance profile in staphylococcus coagulase-negative (CoNS) and coagulasepositive (CoPS) isolates from black pudding in southern Brazil. METHODS: Two hundred typical and atypical colonies from Baird-Parker agar were inoculated on mannitol salt agar. Eighty-two mannitol-positive staphylococci were submitted to conventional biochemical tests and antimicrobial susceptibility profiling. The presence of coagulase (coa) and enterotoxin (se) genes was investigated by polymerase chain reaction. RESULTS: The isolates were divided into 2 groups: 75.6% (62/82) were CoNS and 24.4% (20/82) were CoPS. The biochemical tests identified 9 species, of which Staphylococcus saprophyticus (37.8%) and Staphylococcus carnosus (15.9%) were the most prevalent. Antimicrobial susceptibility tests showed resistance phenotypes to antibiotics widely administered in humans, such as gentamicin, tetracycline, chloramphenicol, and erythromycin. The coa gene was detected in 19.5% (16/82) of the strains and 4 polymorphic DNA fragments were observed. Five CoNS isolates carrying the coa gene were submitted for 16S rRNA sequencing and 3 showed similarity with CoNS. Forty strains were positive for at least 1 enterotoxin-encoding gene, the genes most frequently detected were sea (28.6%) and seb (27.5%). CONCLUSIONS: The presence of antimicrobial resistant and enterotoxin-encoding genes in staphylococci isolates from black pudding indicated that this fermented food may represent a potential health risk, since staphylococci present in food could cause foodborne diseases or be a possible route for the transfer of antimicrobial resistance to humans.