Rotation invariant iris feature extraction using Gaussian Markov random fields with non-separable wavelet

Rotation invariance is important for an iris recognition system since changes of head orientation and binocular vergence may cause eye rotation. The conventional methods of iris recognition cannot achieve true rotation invariance. They only achieve approximate rotation invariance by rotating the feature vector before matching or unwrapping the iris ring at different initial angles. In these methods, the complexity of the method is increased, and when the rotation scale is beyond the certain scope, the error rates of these methods may substantially increase. In order to solve this problem, a new rotation invariant approach for iris feature extraction based on the non-separable wavelet is proposed in this paper. Firstly, a bank of non-separable orthogonal wavelet filters is used to capture characteristics of the iris. Secondly, a method of Markov random fields is used to capture rotation invariant iris feature. Finally, two-class kernel Fisher classifiers are adopted for classification. Experimental results on public iris databases show that the proposed approach has a low error rate and achieves true rotation invariance. © 2010.

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

Exploring Relationships Between Vector-Borne Diseases and Landscape Architecture: Aedes aegypti, Aedes albopictus and Landscape Architecture

Thesis (Master's)--University of Washington, 2016-06

A new method for conditioning stochastic groundwater flow models in fractured media

Many geological formations consist of crystalline rocks that have very low matrix permeability but allow flow through an interconnected network of fractures. Understanding the flow of groundwater through such rocks is important in considering disposal of radioactive waste in underground repositories. A specific area of interest is the conditioning of fracture transmissivities on measured values of pressure in these formations. This is the process where the values of fracture transmissivities in a model are adjusted to obtain a good fit of the calculated pressures to measured pressure values. While there are existing methods to condition transmissivity fields on transmissivity, pressure and flow measurements for a continuous porous medium there is little literature on conditioning fracture networks. Conditioning fracture transmissivities on pressure or flow values is a complex problem because the measurements are not linearly related to the fracture transmissivities and they are also dependent on all the fracture transmissivities in the network. We present a new method for conditioning fracture transmissivities on measured pressure values based on the calculation of certain basis vectors; each basis vector represents the change to the log transmissivity of the fractures in the network that results in a unit increase in the pressure at one measurement point whilst keeping the pressure at the remaining measurement points constant. The fracture transmissivities are updated by adding a linear combination of basis vectors and coefficients, where the coefficients are obtained by minimizing an error function. A mathematical summary of the method is given. This algorithm is implemented in the existing finite element code ConnectFlow developed and marketed by Serco Technical Services, which models groundwater flow in a fracture network. Results of the conditioning are shown for a number of simple test problems as well as for a realistic large scale test case.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Motor Unit Spike Trains Recontruction from sEMG Signals for Gesture Classification on a Low-Power Processing Platform

Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.

Development And Characterization Of A Cationic Lipid Nanocarrier As Non-viral Vector For Gene Therapy.

The aim of the present work was to produce a cationic solid lipid nanoparticle (SLN) as non-viral vector for protein delivery. Cationic SLN were produced by double emulsion method, composed of softisan(®) 100, cetyltrimethylammonium bromide (CTAB), Tween(®) 80, Span(®) 80, glycerol and lipoid(®) S75 loading insulin as model protein. The formulation was characterized in terms of mean hydrodynamic diameter (z-ave), polydispersity index (PI), zeta potential (ZP), stability during storage time, stability after lyophilization, effect of toxicity and transfection ability in HeLa cells, in vitro release profile and morphology. SLN were stable for 30days and showed minimal changes in their physicochemical properties after lyophilization. The particles exhibited a relatively slow release, spherical morphology and were able to transfect HeLa cells, but toxicity remained an obstacle. Results suggest that SLN are nevertheless promising for delivery of proteins or nucleic acids for gene therapy.

O futebol e os jogos/brincadeiras de bola com os pes

Universidade Estadual de Campinas. Faculdade de Educação Física

Influence of light-curing unit systems on shear bond strength and marginal microleakage of composite resin restorations

The aim of the present study was to evaluate the influence of different photopolymerization (halogen, halogen soft-start and LED) systems on shear bond strength (SBS) and marginal microleakage of composite resin restorations. Forty Class V cavities (enamel and dentin margins) were prepared for microleakage assessment, and 160 enamel and dentin fragments were prepared for the SBS test, and divided into 4 groups. Kruskal-Wallis and Wilcoxon tests showed statistically significant difference in microleakage between the margins (p < 0.01) with incisal margins presenting the lowest values. Among the groups, it was observed that, only at the cervical margin, halogen soft-start photo polymerization presented statistically significant higher microleakage values. For SBS test, ANOVA showed no statistical difference (p > 0.05) neither between substrates nor among groups. It was concluded that Soft-Start technique with high intensity end-light influenced negatively the cervical marginal sealing, but the light-curing systems did not influence adhesion.

Fatal adenoviral necrotizing bronchiolitis case in a post-cardiac surgery intensive care unit

We report a case of a 67 year-old-male patient admitted to the intensive care unit in the post-coronary bypass surgery period who presented cardiogenic shock, acute renal failure and three episodes of sepsis, the latter with pulmonary distress at the 30th post-operative day. The patient expired within five days in spite of treatment with vancomycin, imipenem, colistimethate and amphotericin B. At autopsy severe adenovirus pneumonia was found. Viral pulmonary infections following cardiovascular surgery are uncommon. We highlight the importance of etiological diagnosis to a correct treatment approach.

Spatial pattern detection modeling of thrips (Thrips tabaci) on onion fields

Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.

Intervenção com pais de crianças deficientes auditivas: elaboração e avaliação de um programa de orientação não presencial

As orientações aos pais favorecem a aceitação da deficiência auditiva e esclarecem possibilidades e condutas que viabilizam o desenvolvimento da criança. Devem ser cuidadosas, a fim de evitar insegurança, ansiedade, expectativas irreais ou reações inadequadas dos pais. Essas orientações são oferecidas no diagnóstico e no acompanhamento, mas as restrições de tempo e financeiras são dificuldades dos pais para o comparecimento freqüente a programas que forneçam um suporte contínuo. A proposta deste trabalho foi elaborar e avaliar um programa de orientação não presencial para pais de crianças com deficiência auditiva severa e profunda, de dois a seis anos de idade. O programa, estruturado em quatro unidades, foi aplicado a 30 pais atendidos no Hospital de Reabilitação de Anomalias Craniofaciais da USP, em Bauru/SP. As unidades foram formuladas com base nas orientações que os especialistas de diferentes áreas transmitem durante o diagnóstico da deficiência auditiva e nas dificuldades e interesses dos pais, identificando-se o conhecimento sobre as avaliações e acompanhamentos, opiniões sobre desempenho e necessidades da criança, deles próprios e das famílias. Para avaliação do programa foram analisadas as respostas dos pais aos questionários das unidades e às entrevistas finais. As análises revelaram que o programa forneceu aos pais, como eles desejavam, informações claras e sugestões de atividades que pudessem ser adequadas ao contexto familiar e colaborassem para o desenvolvimento da criança. Alguns pais encontraram dificuldade em se expressar por escrito e realizar algumas atividades, mas nas entrevistas, foi verificado que tal fato não inviabilizou o entendimento e a participação no programa.

Habitat suitability of Anopheles vector species and association with human malaria in the Atlantic Forest in south-eastern Brazil

Every year, autochthonous cases of Plasmodium vivax malaria occur in low-endemicity areas of Vale do Ribeira in the south-eastern part of the Atlantic Forest, state of São Paulo, where Anopheles cruzii and Anopheles bellator are considered the primary vectors. However, other species in the subgenus Nyssorhynchus of Anopheles (e.g., Anopheles marajoara) are abundant and may participate in the dynamics of malarial transmission in that region. The objectives of the present study were to assess the spatial distribution of An. cruzii, An. bellator and An. marajoara and to associate the presence of these species with malaria cases in the municipalities of the Vale do Ribeira. Potential habitat suitability modelling was applied to determine both the spatial distribution of An. cruzii, An. bellator and An. marajoara and to establish the density of each species. Poisson regression was utilized to associate malaria cases with estimated vector densities. As a result, An. cruzii was correlated with the forested slopes of the Serra do Mar, An. bellator with the coastal plain and An. marajoara with the deforested areas. Moreover, both An. marajoara and An. cruzii were positively associated with malaria cases. Considering that An. marajoara was demonstrated to be a primary vector of human Plasmodium in the rural areas of the state of Amapá, more attention should be given to the species in the deforested areas of the Atlantic Forest, where it might be a secondary vector.

Magnetic fields and acute lymphoblastic leukemia in children: a systematic review of case-control studies

Leukemia incidence in children has increased worldwide in recent decades, particularly due to the rise in acute lymphoblastic leukemia. Studies have associated exposure to non-ionizing radiation generated by low frequency magnetic fields with childhood leukemia. The current article reviews the case-control studies published on this subject. Of 152 articles tracked in different databases, ten studies from North America, Asia, and Europe met the defined selection criteria, with patients diagnosed from 1960 to 2004. Methodological limitations were observed in these articles, including difficulties with the procedures for assessing exposure. An association may exist between exposure to low frequency magnetic fields and acute lymphoblastic leukemia in children, but this association is weak, preventing the observation of consistency in the findings. Future studies from a wider range of geographic regions should focus on the analysis of acute lymphoblastic leukemia, which is the subtype with the greatest impact on the increasing overall incidence of childhood leukemia.

Quasinormal modes of black holes in anti-de Sitter space: A numerical study of the eikonal limit

Using series solutions and time-domain evolutions, we probe the eikonal limit of the gravitational and scalar-field quasinormal modes of large black holes and black branes in anti-de Sitter backgrounds. These results are particularly relevant for the AdS/CFT correspondence, since the eikonal regime is characterized by the existence of long-lived modes which (presumably) dominate the decay time scale of the perturbations. We confirm all the main qualitative features of these slowly damped modes as predicted by Festuccia and Liu [G. Festuccia and H. Liu, arXiv:0811.1033.] for the scalar-field (tensor-type gravitational) fluctuations. However, quantitatively we find dimensional-dependent correction factors. We also investigate the dependence of the quasinormal mode frequencies on the horizon radius of the black hole (brane) and the angular momentum (wave number) of vector- and scalar-type gravitational perturbations.