Multidimensional Scaling Visualization using Parametric Similarity Indices

In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of ‘points’. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of “shapes”. This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

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.

Molecular analysis of the dengue virus type 1 and 2 in Brazil based on sequences of the genomic envelope-nonstructural protein 1 junction region

The genomic sequences of the Envelope-Non-Structural protein 1 junction region (E/NS1) of 84 DEN-1 and 22 DEN-2 isolates from Brazil were determined. Most of these strains were isolated in the period from 1995 to 2001 in endemic and regions of recent dengue transmission in São Paulo State. Sequence data for DEN-1 and DEN-2 utilized in phylogenetic and split decomposition analyses also include sequences deposited in GenBank from different regions of Brazil and of the world. Phylogenetic analyses were done using both maximum likelihood and Bayesian approaches. Results for both DEN-1 and DEN-2 data are ambiguous, and support for most tree bipartitions are generally poor, suggesting that E/NS1 region does not contain enough information for recovering phylogenetic relationships among DEN-1 and DEN-2 sequences used in this study. The network graph generated in the split decomposition analysis of DEN-1 does not show evidence of grouping sequences according to country, region and clades. While the network for DEN-2 also shows ambiguities among DEN-2 sequences, it suggests that Brazilian sequences may belong to distinct subtypes of genotype III.

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.

Separating sequential equilibrium in a Bayesian international duopoly

We consider two Cournot firms, one located in the home country and the other in the foreign country, producing substitute goods for consumption in a third country. We suppose that neither the home government nor the foreign firm know the costs of the home firm, while the foreign firm cost is common knowledge. We determine the separating sequential equilibrium outputs.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Maximum likelihood detection for OFDM signals with strong nonlinear distortion effects

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

A bayesian approach for NDT data fusion: The Saint Torcato Church case study

This paper presents a methodology based on the Bayesian data fusion techniques applied to non-destructive and destructive tests for the structural assessment of historical constructions. The aim of the methodology is to reduce the uncertainties of the parameter estimation. The Young's modulus of granite stones was chosen as an example for the present paper. The methodology considers several levels of uncertainty since the parameters of interest are considered random variables with random moments. A new concept of Trust Factor was introduced to affect the uncertainty related to each test results, translated by their standard deviation, depending on the higher or lower reliability of each test to predict a certain parameter.

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.

Response of blood pressure to maximum exercise in hypertensive patients under different therapeutic programs

OBJECTIVE: To evaluate the behavior of blood pressure during exercise in patients with hypertension controlled by frontline antihypertension drugs. METHODS: From 979ergometric tests we retrospectively selected 49 hipertensive patients (19 males). The age was 53±12 years old and normal range rest arterial pressure (<=140/90 mmHg) all on pharmacological monotherapy. There were 12 on beta blockers; 14 on calcium antagonists, 13 on diuretics and 10 on angiotensin converting enzyme inhibitor. Abnormal exercise behhavior of blood pressure was diagnosed if anyone of the following criteria was detected: peak systolic pressure above 220 mmHg, raising of systolic pressure > or = 10 mmHg/MET; or increase of diastolic pressure greater than 15 mmHg. RESULTS: Physiologic response of arterial blood pressure occurred in 50% of patients on beta blockers, the best one (p<0.05), in 36% and 31% on calcium antagonists and on diuretics, respectively, and in 20% on angiotensin converting enzyme inhibitor, the later the leastr one (p<0.05). CONCLUSION: Beta-blockers were more effective than calcium antagonists, diuretics and angiotensin-converting enzyme inhibitors in controlling blood pressure during exercise, and angiotensin converting enzyme inhibitors the least effective drugs.

Relative information entropy in cosmology: The problem of information entanglement

The necessary information to distinguish a local inhomogeneous mass density field from its spatial average on a compact domain of the universe can be measured by relative information entropy. The Kullback-Leibler (KL) formula arises very naturally in this context, however, it provides a very complicated way to compute the mutual information between spatially separated but causally connected regions of the universe in a realistic, inhomogeneous model. To circumvent this issue, by considering a parametric extension of the KL measure, we develop a simple model to describe the mutual information which is entangled via the gravitational field equations. We show that the Tsallis relative entropy can be a good approximation in the case of small inhomogeneities, and for measuring the independent relative information inside the domain, we propose the R\'enyi relative entropy formula.

Variabilidad paleoambiental desde el Último Máximo Glacial en la región Centro-Sur de Argentina: Paleocirculación atmosférica, variabilidad hidroclimática y dimensión humana. Palaeoenvironmental variability from the Last Glacial Maximum in the Central-Southern region of Argentina: Atmospheric Palaeocirculation, Hydroclimatic Variability and Human Dimension.

El proyecto tiene como propósito caracterizar la variabilidad de la paleocirculación atmosférica en las latitudes medias de Sudamérica, su efecto sobre la fluctuación hidroclimática regional y la vulnerabilidad humana frente a los cambios ocurridos desde el Ultimo Máximo Glacial/Holoceno. El enfoque inter y multidisciplinaro aquí planteado para analizar la varibiliad hidroclimática pasada, sus causas y consecuencias, es inédito para esta región del país. El mismo contempla: a) análisis de archivos climáticos sedimentarios con una aproximación de multi-indicadores (sedimentología, geoquímica, isótopos estables y radiogénicos, mineralogía, ostrácodos y moluscos); b) determinación de la dinámica actual y pasada del polvo atmosférico (PA) combinando mediciones in situ y en registros sedimentarios y c) análisis de restos óseos humanos y malacológicos en sitios arqueológicos.Se contempla: a) Efectuar análisis de multi-indicadores de registros climáticos naturales almacenados en sistemas lacustres de la región Pampeana (S. Ambargasta, Mar Chiquita, Pocho, Melincué, Lagunas Encadenadas del Oeste de Buenos Aires) y en secuencias loessicas para inferir la variabilidad de la circulación atmosférica desde el UMG; b) Ampliar la resolución temporal de las reconstrucciones climáticas para ventanas de tiempo seleccionadas; c) Analizar la señal geoquímica del registro sedimentario de fases climáticas contrastantes; d) Identificar la variabilidad temporal de la procedencia y de los procesos actuantes mediante análisis mineralógicos y geoquímicos; e) Analizar el ambiente actual para calibrar indicadores ambientales o proxies (isótopos, flujo de sedimentos, geoquímica, moluscos y ostrácodos) con el escenario climático contemporáneo; f) Analizar en conjunto los archivos climáticos para inferir patrones de paleocirculación atmosférica regional y g) Dilucidar estrategias adaptativas y la historia biológica de poblaciones humanas en la región central de Argentina durante fases climáticas diversas.Este proyecto aborda uno de los aspectos menos conocidos de las reconstrucciones paleoambientales, que está relacionado con rol del material eólico derivado del Hemisferio Sur y el impacto que genera sobre el ciclo regional del Carbono. A pesar que el sur de Sudamérica es una de las áreas claves para entender este aspecto, no se conoce de forma acabada la incidencia de los cambios ambientales sobre el flujo de PA o el efecto de futuros cambios climáticos y/o uso de la tierra.La actividad planteada tiene implicancias directas sobre múltiples disciplinas como las ciencias atmosféricas, geoquímica, sedimentología, paleoclimatologia y bioarqueología. Nuestros resultados permitirán mejorar el entendimiento del cambio climático regional, la dinámica del polvo y su rol como forzante del sistema climático, la variabilidad hidrológica presente y pasada y la respuesta por parte de las poblaciones humanas. Profundizar el estudio de los cambios paleoclimáticos y bioarqueológicos en la región permitirá analizar la variabilidad hidroclimática y determinar su relación con las situaciones de crisis y vulnerabilidad del pobamiento humano. Asimismo, la inferencia de cambios para períodos con mínima o sin influencia humana es una herramienta clave para mejorar el conocimiento de las fluctuaciones climáticas del área extratropical Sudamericana. Estos resultados permitirán analizar no sólo los mecanismos operados en el sistema climático pasado sino también aquellos factores que explicarían el gran cambio hidroclimático registrado desde 1970 cuyos efectos han impactado claramente sobre las actividades socio-económicos en la región central Argentina.

Sex-Specific Equations to Estimate Maximum Oxygen Uptake in Cycle Ergometry

AbstractBackground:Aerobic fitness, assessed by measuring VO2max in maximum cardiopulmonary exercise testing (CPX) or by estimating VO2max through the use of equations in exercise testing, is a predictor of mortality. However, the error resulting from this estimate in a given individual can be high, affecting clinical decisions.Objective:To determine the error of estimate of VO2max in cycle ergometry in a population attending clinical exercise testing laboratories, and to propose sex-specific equations to minimize that error.Methods:This study assessed 1715 adults (18 to 91 years, 68% men) undertaking maximum CPX in a lower limbs cycle ergometer (LLCE) with ramp protocol. The percentage error (E%) between measured VO2max and that estimated from the modified ACSM equation (Lang et al. MSSE, 1992) was calculated. Then, estimation equations were developed: 1) for all the population tested (C-GENERAL); and 2) separately by sex (C-MEN and C-WOMEN).Results:Measured VO2max was higher in men than in WOMEN: -29.4 ± 10.5 and 24.2 ± 9.2 mL.(kg.min)-1 (p < 0.01). The equations for estimating VO2max [in mL.(kg.min)-1] were: C-GENERAL = [final workload (W)/body weight (kg)] x 10.483 + 7; C-MEN = [final workload (W)/body weight (kg)] x 10.791 + 7; and C-WOMEN = [final workload (W)/body weight (kg)] x 9.820 + 7. The E% for MEN was: -3.4 ± 13.4% (modified ACSM); 1.2 ± 13.2% (C-GENERAL); and -0.9 ± 13.4% (C-MEN) (p < 0.01). For WOMEN: -14.7 ± 17.4% (modified ACSM); -6.3 ± 16.5% (C-GENERAL); and -1.7 ± 16.2% (C-WOMEN) (p < 0.01).Conclusion:The error of estimate of VO2max by use of sex-specific equations was reduced, but not eliminated, in exercise tests on LLCE.