Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.

Non-stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil

This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of Sao Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of Sao Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

Univariate and bivariate distribution of growth traits in beef buffaloes from Brazil

The aim of this study was to analyze the weight at birth (BW) and adjusted at 205 (W205), 365 (W365) and 550 (W55O) days in beef buffaloes from Brazil, using two approaches: parametric, by normal distribution, and non-parametric, by kernel function, and thus estimating the genetic, environmental and phenotypic correlation among traits. Information of 5,169 animals at birth (BW), 3,792 at 205 days (W205), 3.883 at 365 days (W365) and 1,524 at 550 days of age (W550) were used. The birth weight distribution presented an evident discrepancy in relation to the normal distribution. However, W205, W365 and W550 presented normal distributions. The birth weight presented weak genetic, environmental, and phenotypic associations with the other weight measurements. on the other hand, the weight traits at 205, 365, 550 days of age showed a high genetic correlation.

Non-stationary frequency analysis of extreme daily rainfall in São Paulo, Brazil

This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of São Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of São Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

Absence motivated by illness: A non-concurrent prospective study of physical education teachers in the municipal education system of the city of Campinas, São Paulo, Brazil

The object of this investigation was to identify and analize aspects of the health status related to absenteism in physical education teachers in the municipal education system of the city of Campinas, Brazil, as related to the medical leave program. The non-concurrent prospective study was accomplished by means of a comparison with teachers who work only in the classroom, refering to a three year period. In the variables of greatest interest, the Pearson non-parametric chi-square (X2) statistical test was adopted. Calculations of relative risk and level of confidence were made using the Epi-info computer program. Significant differences were observed in the following diagnostic groups favoring the not exposed group: i) Supplementary Classification of factors that exercise influence over the health status and access to health services and ii) Digestive system illness; while the physical education teachers showed a significant difference in: i) diseases of the musculoskeletal and connective tissue system and ii) Injuries and poisoing. Possible explications for some of the adverse effects as well as the protective ones that were observed include physical activity as a way of life along with being a physical education teacher and on the other side, peculiar behavior of epidemiological descriptive characteristics, like sex and age, within the socio-economic context of the country. © Copyright Moreira Jr. Editora.

Home ranges of Guiana dolphins (Sotalia guianensis) (Cetacea: Delphinidae) in the Cananeia estuary, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluating different methods of microarray data normalization

Abstract Background With the development of DNA hybridization microarray technologies, nowadays it is possible to simultaneously assess the expression levels of thousands to tens of thousands of genes. Quantitative comparison of microarrays uncovers distinct patterns of gene expression, which define different cellular phenotypes or cellular responses to drugs. Due to technical biases, normalization of the intensity levels is a pre-requisite to performing further statistical analyses. Therefore, choosing a suitable approach for normalization can be critical, deserving judicious consideration. Results Here, we considered three commonly used normalization approaches, namely: Loess, Splines and Wavelets, and two non-parametric regression methods, which have yet to be used for normalization, namely, the Kernel smoothing and Support Vector Regression. The results obtained were compared using artificial microarray data and benchmark studies. The results indicate that the Support Vector Regression is the most robust to outliers and that Kernel is the worst normalization technique, while no practical differences were observed between Loess, Splines and Wavelets. Conclusion In face of our results, the Support Vector Regression is favored for microarray normalization due to its superiority when compared to the other methods for its robustness in estimating the normalization curve.

Phylogeny and historical biogeography of the Australian Camphorosmeae (Chenopodiaceae)

Diese Studie befasst sich mit der Phylogenie und Biogeographie der australischen Camphorosmeae, die ein wichtiges Element der Flora arider Gebiete Australiens sind. Die molekularen Phylogenien wurden mit Hilfe Bayes’scher Statistik und „maximum likelihood”berechnet. Um das Alter der Gruppe und interner Linien abzuschätzen, wurden die Methoden „Nonparametric rate smoothing” und “penalized likelihood” benutzt. Morphologische Merkmale wurden nach Kriterien der Parsimonie auf den molekularen Baum aufgetragen. „Brooks parsimony analysis”, „cladistic analysis of distributions and endemism”, „dispersal-vicariance analysis”,„ancestral area analysis” und „weighted ancestral area analysis” wurden angewandt, um Abfolge und Richtungen der Ausbreitung der Gruppe in Australien zu analysieren.Von sieben getesteten Markern hatten nur die nukleären ETS und ITS genügend Variation für die phylogenetische Analyse der Camphorosmeae. Die plastidären Marker trnL-trnF spacer,trnP-psaJ spacer, rpS16 intron, rpL16 intron und trnS-trnG spacer zeigten kein ausreichendes phylogenetisches Signal. Die gefundenen phylogenetischen Hypothesen widersprechen der jetzigen Taxonomie der Gruppe. Neobassia, Threlkeldia, Osteocarpum und Enchylaena sollten den Gattungen Sclerolaena bzw. Maireana zugeordnet werden. Die kladistische Analyse der Fruchtanhängsel unterstützt die taxonomischen Ergebnisse der auf DNA basierenden Phylogenie. Allerdings hat die Behaarung, die bei anderen Gruppen der Chenopodiaceae als wichtiges taxonomisches Merkmal herangezogen wird, die Phylogenie nicht unterstützt. Vorfahren der heutigen Camphorosmeen sind im Miozän, vor ca. 8-14 Millionen Jahren, durch Fernausbreitung vermutlich aus Asien in Australien eingewandert. Anfängliche Diversifizierung fand während des späten Miozäns bis in das frühe Pliozän vor ca. 4-7 Millionen Jahren statt. Am Ende des Pliozäns existierten schon 45% - 72% der Abstammungslinien der jetzigen Camphorosmeen. Dies weist auf eine schnelle Ausbreitung hin. Das Alter stimmt mit dem Einsetzen der Aridisierung Australiens überein, und deutet darauf hin, dass die Ausbreitung der ariden Gebiete eine große Rolle bei der Diversifizierung der Gruppe spielte. Die Vorfahren der australischen Camphorosmeae scheinen die Südküste Australiens zuerst besiedeln zu haben. Dies geschah vor dem Einsetzen der Aridisierung des Kontinents. Die anschließende Ausbreitung erfolgte in verschiedene Richtungen und folgte der fortschreitenden Austrocknung im späten Tertiär und im ganzen Quartär. Durch ihre Anpassung an Trockenheit ist der Erfolg der Camphorosmeae in den ariden Gebieten zu erklären.Die Abwesenheit von klaren phylogenetischen und artspezifischen Signalen zwischen Arten der australischen Camphorosmeae ist auf das junge Alter und die schnelle Diversifizierung der Gruppe zurückzuführen, welche die Häufung von Mutationen und eine starke morphologische Differenzierung nicht zugelassen haben.

Mechanical non-surgical treatment of peri-implantitis: a single-blinded randomized longitudinal clinical study. II. Microbiological results

BACKGROUND: Peri-implantitis is common in patients with dental implants. We performed a single-blinded longitudinal randomized study to assess the effects of mechanical debridement on the peri-implant microbiota in peri-implantitis lesions. MATERIALS AND METHODS: An expanded checkerboard DNA-DNA hybridization assay encompassing 79 different microorganisms was used to study bacterial counts before and during 6 months following mechanical treatment of peri-implantitis in 17 cases treated with curettes and 14 cases treated with an ultrasonic device. Statistics included non-parametric tests and GLM multivariate analysis with p<0001 indicating significance and 80% power. RESULTS: At selected implant test sites, the most prevalent bacteria were: Fusobacterium nucleatum sp., Staphylococci sp., Aggregatibacter actinomycetemcomitans, Helicobacter pylori, and Tannerella forsythia. 30 min. after treatment with curettes, A. actinomycetemcomitans (serotype a), Lactobacillus acidophilus, Streptococcus anginosus, and Veillonella parvula were found at lower counts (p<0.001). No such differences were found for implants treated with the ultrasonic device. Inconsistent changes occurred following the first week. No microbiological differences between baseline and 6-month samples were found for any species or between treatment study methods in peri-implantitis. CONCLUSIONS: Both methods failed to eliminate or reduce bacterial counts in peri-implantitis. No group differences were found in the ability to reduce the microbiota in peri-implantitis.

First trimester markers for pre-eclampsia: placental vs. non-placental protein serum levels

BACKGROUND/AIM: Parallel investigation, in a matched case-control study, of the association of different first-trimester markers with the risk of subsequent pre-eclampsia (PE). METHOD: The levels of different first trimester serum markers and fetal nuchal translucency thickness were compared between 52 cases of PE and 104 control women by non-parametric two-group comparisons and by calculating matched odds ratios. RESULTS: In univariable analysis increased concentrations of inhibin A and activin A were associated with subsequent PE (p < 0.02). Multivariable conditional logistic regression models revealed an association between increased risk of PE and increased inhibin A and translucency thickness and respectively reduced pregnancy-associated plasma protein A (PAPP-A) and placental lactogen . However, these associations varied with the gestational age at sample collection. For blood samples taken in pregnancy weeks 12 and 13 only, increased levels of activin A, inhibin A and nuchal translucency thickness, and lower levels of placenta growth factor and PAPP-A were associated with an increased risk of PE. CONCLUSIONS: Members of the inhibin family and to some extent PAPP-A and placental growth factor are superior to other serum markers, and the predictive value of these depends on the gestational age at blood sampling. The availability of a single, early pregnancy 'miracle' serum marker for PE risk assessment seems unlikely in the near future.

Comparison of two non-bronchoscopic methods for evaluating inflammation in patients with acute hypoxaemic respiratory failure

INTRODUCTION: The simple bedside method for sampling undiluted distal pulmonary edema fluid through a normal suction catheter (s-Cath) has been experimentally and clinically validated. However, there are no data comparing non-bronchoscopic bronchoalveolar lavage (mini-BAL) and s-Cath for assessing lung inflammation in acute hypoxaemic respiratory failure. We designed a prospective study in two groups of patients, those with acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) and those with acute cardiogenic lung edema (ACLE), designed to investigate the clinical feasibility of these techniques and to evaluate inflammation in both groups using undiluted sampling obtained by s-Cath. To test the interchangeability of the two methods in the same patient for studying the inflammation response, we further compared mini-BAL and s-Cath for agreement of protein concentration and percentage of polymorphonuclear cells (PMNs). METHODS: Mini-BAL and s-Cath sampling was assessed in 30 mechanically ventilated patients, 21 with ALI/ARDS and 9 with ACLE. To analyse agreement between the two sampling techniques, we considered only simultaneously collected mini-BAL and s-Cath paired samples. The protein concentration and polymorphonuclear cell (PMN) count comparisons were performed using undiluted sampling. Bland-Altman plots were used for assessing the mean bias and the limits of agreement between the two sampling techniques; comparison between groups was performed by using the non-parametric Mann-Whitney-U test; continuous variables were compared by using the Student t-test, Wilcoxon signed rank test, analysis of variance or Student-Newman-Keuls test; and categorical variables were compared by using chi-square analysis or Fisher exact test. RESULTS: Using protein content and PMN percentage as parameters, we identified substantial variations between the two sampling techniques. When the protein concentration in the lung was high, the s-Cath was a more sensitive method; by contrast, as inflammation increased, both methods provided similar estimates of neutrophil percentages in the lung. The patients with ACLE showed an increased PMN count, suggesting that hydrostatic lung edema can be associated with a concomitant inflammatory process. CONCLUSIONS: There are significant differences between the s-Cath and mini-BAL sampling techniques, indicating that these procedures cannot be used interchangeably for studying the lung inflammatory response in patients with acute hypoxaemic lung injury.

Mechanical non-surgical treatment of peri-implantitis: a double-blind randomized longitudinal clinical study. I: clinical results

BACKGROUND: Peri-implantitis is a frequent finding in patients with dental implants. The present study compared two non-surgical mechanical debridement methods of peri-implantitis. MATERIAL AND METHODS: Thirty-seven subjects (mean age 61.5; S.D+/-12.4), with one implant each, demonstrating peri-implantitis were randomized, and those treated either with titanium hand-instruments or with an ultrasonic device were enrolled. Data were obtained before treatment, and at 1, 3, and 6 months. Parametric and non-parametric statistics were used. RESULTS: Thirty-one subjects completed the study. The mean bone loss at implants in both groups was 1.5 mm (SD +/-1.2 mm). No group differences for plaque or gingival indices were found at any time point. Baseline and 6-month mean probing pocket depths (PPD) at implants were 5.1 and 4.9 mm (p=0.30) in both groups. Plaque scores at treated implants decreased from 73% to 53% (p<0.01). Bleeding scores also decreased (p<0.01), with no group differences. No differences in the total bacterial counts were found over time. Higher total bacterial counts were found immediately after treatment (p<0.01) and at 1 week for ultrasonic-treated implants (p<0.05). CONCLUSIONS: No group differences were found in the treatment outcomes. While plaque and bleeding scores improved, no effects on PPD were identified.

Regularization for sparsity in statistical analysis and machine learning

Pragmatism is the leading motivation of regularization. We can understand regularization as a modification of the maximum-likelihood estimator so that a reasonable answer could be given in an unstable or ill-posed situation. To mention some typical examples, this happens when fitting parametric or non-parametric models with more parameters than data or when estimating large covariance matrices. Regularization is usually used, in addition, to improve the bias-variance tradeoff of an estimation. Then, the definition of regularization is quite general, and, although the introduction of a penalty is probably the most popular type, it is just one out of multiple forms of regularization. In this dissertation, we focus on the applications of regularization for obtaining sparse or parsimonious representations, where only a subset of the inputs is used. A particular form of regularization, L1-regularization, plays a key role for reaching sparsity. Most of the contributions presented here revolve around L1-regularization, although other forms of regularization are explored (also pursuing sparsity in some sense). In addition to present a compact review of L1-regularization and its applications in statistical and machine learning, we devise methodology for regression, supervised classification and structure induction of graphical models. Within the regression paradigm, we focus on kernel smoothing learning, proposing techniques for kernel design that are suitable for high dimensional settings and sparse regression functions. We also present an application of regularized regression techniques for modeling the response of biological neurons. Supervised classification advances deal, on the one hand, with the application of regularization for obtaining a na¨ıve Bayes classifier and, on the other hand, with a novel algorithm for brain-computer interface design that uses group regularization in an efficient manner. Finally, we present a heuristic for inducing structures of Gaussian Bayesian networks using L1-regularization as a filter. El pragmatismo es la principal motivación de la regularización. Podemos entender la regularización como una modificación del estimador de máxima verosimilitud, de tal manera que se pueda dar una respuesta cuando la configuración del problema es inestable. A modo de ejemplo, podemos mencionar el ajuste de modelos paramétricos o no paramétricos cuando hay más parámetros que casos en el conjunto de datos, o la estimación de grandes matrices de covarianzas. Se suele recurrir a la regularización, además, para mejorar el compromiso sesgo-varianza en una estimación. Por tanto, la definición de regularización es muy general y, aunque la introducción de una función de penalización es probablemente el método más popular, éste es sólo uno de entre varias posibilidades. En esta tesis se ha trabajado en aplicaciones de regularización para obtener representaciones dispersas, donde sólo se usa un subconjunto de las entradas. En particular, la regularización L1 juega un papel clave en la búsqueda de dicha dispersión. La mayor parte de las contribuciones presentadas en la tesis giran alrededor de la regularización L1, aunque también se exploran otras formas de regularización (que igualmente persiguen un modelo disperso). Además de presentar una revisión de la regularización L1 y sus aplicaciones en estadística y aprendizaje de máquina, se ha desarrollado metodología para regresión, clasificación supervisada y aprendizaje de estructura en modelos gráficos. Dentro de la regresión, se ha trabajado principalmente en métodos de regresión local, proponiendo técnicas de diseño del kernel que sean adecuadas a configuraciones de alta dimensionalidad y funciones de regresión dispersas. También se presenta una aplicación de las técnicas de regresión regularizada para modelar la respuesta de neuronas reales. Los avances en clasificación supervisada tratan, por una parte, con el uso de regularización para obtener un clasificador naive Bayes y, por otra parte, con el desarrollo de un algoritmo que usa regularización por grupos de una manera eficiente y que se ha aplicado al diseño de interfaces cerebromáquina. Finalmente, se presenta una heurística para inducir la estructura de redes Bayesianas Gaussianas usando regularización L1 a modo de filtro.

Carotid artery intimal medial thickness, brachial artery flow-mediated vasodilation and cardiovascular risk factors in diabetic and non-diabetic indigenous Australians

Background: Indigenous Australians are at high risk for cardiovascular disease and type 2 diabetes. Carotid artery intimal medial thickness (CIMT) and brachial artery flow-mediated vasodilation (FMD) are ultrasound imaging based surrogate markers of cardiovascular risk. This study examines the relative contributions of traditional cardiovascular risk factors on CIMT and FMD in adult Indigenous Australians with and without type 2 diabetes mellitus. Method: One hundred and nineteen Indigenous Australians were recruited. Physical and biochemical markers of cardiovascular risk, together with CIMT and FMD were meausred for all subjects. Results: Fifty-three Indigenous Australians subjects (45%) had type 2 diabetes mellitus. There was a significantly greater mean CIMT in diabetic versus non-diabetic subjects (p = 0.049). In the non-diabetic group with non-parametric analyses, there were significant correlations between CIMT and: age (r = 0.64, p < 0.001), systolic blood pressure (r = 0.47, p < 0.001) and non-smokers (r = -0.30, p = 0.018). In the diabetic group, non-parametric analysis showed correlations between CIMT, age (r = 0.36, p = 0.009) and duration of diabetes (r = 0.30, p = 0.035) only. Adjusting forage, sex, smoking and history of cardiovascular disease, Hb(A1c) became the sole significant correlate of CIMT (r = 0.35,p = 0.01) in the diabetic group. In non-parametric analysis, age was the sole significant correlate of FMD (r = -0.31,p = 0.013), and only in non-diabetic subjects. Linear regression analysis showed significant associations between CIMT and age (t = 4.6,p < 0.001), systolic blood pressure (t = 2.6, p = 0.010) and Hb(A1c) (t = 2.6, p = 0.012), smoking (t = 2.1, p = 0.04) and fasting LDL-cholesterol (t = 2.1, p = 0.04). There were no significant associations between FMD and examined cardiovascular risk factors with linear regression analysis Conclusions: CIMT appears to be a useful surrogate marker of cardiovascular risk in this sample of Indigenous Australian subjects, correlating better than FMD with established cardiovascular risk factors. A lifestyle intervention programme may alleviate the burden of cardiovascular disease in Indigenous Australians by reducing central obesity, lowering blood pressure, correcting dyslipidaemia and improving glycaemic control. CIMT may prove to be a useful tool to assess efficacy of such an intervention programme. (c) 2004 Elsevier Ireland Ltd. All rights reserved.

Discriminating antigen and non-antigen using proteome dissimilarity:bacterial antigens

It has been postulated that immunogenicity results from the overall dissimilarity of pathogenic proteins versus the host proteome. We have sought to use this concept to discriminate between antigens and non-antigens of bacterial origin. Sets of 100 known antigenic and nonantigenic peptide sequences from bacteria were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we were unable to determine a threshold able to separate meaningfully antigen from non-antigen. Thus, antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to the human genome.