Exposed singularity

Edkins, J., Exposed singularity, Journal for Cultural Research, Volume 9, Issue 4 October 2005 , pages 359 - 386 RAE2008

Asymptotic behaviour of the elastic solution near the tip of a crack situated at a nonideal interface

Mishuris, G; Kuhn, G., (2001) 'Asymptotic behaviour of the elastic solution near the tip of a crack situated at a nonideal interface', Zeitschrift f?r Angewandte Mathematik und Mechanik 81(12) pp.811-826 RAE2008

Komizm w teorii i praktyce antycznej powieści greckiej

The topic of the study entitled humour in the ancient greek novels: the theoretical conceptions and the lite- rary practice is significance of humour in ancient Greek novels. In the first part of this study the theoretical aspects are examined with reference to the conceptions of contemporary researchers of Greek novels. The influence of the humour on the character of the world presented in particular novels is considered in the second part of the article.

A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models

This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

A survey of fingerprint classification Part II: experimental analysis and ensemble proposal

In the first part of this paper we reviewed the fingerprint classification literature from two different perspectives: the feature extraction and the classifier learning. Aiming at answering the question of which among the reviewed methods would perform better in a real implementation we end up in a discussion which showed the difficulty in answering this question. No previous comparison exists in the literature and comparisons among papers are done with different experimental frameworks. Moreover, the difficulty in implementing published methods was stated due to the lack of details in their description, parameters and the fact that no source code is shared. For this reason, in this paper we will go through a deep experimental study following the proposed double perspective. In order to do so, we have carefully implemented some of the most relevant feature extraction methods according to the explanations found in the corresponding papers and we have tested their performance with different classifiers, including those specific proposals made by the authors. Our aim is to develop an objective experimental study in a common framework, which has not been done before and which can serve as a baseline for future works on the topic. This way, we will not only test their quality, but their reusability by other researchers and will be able to indicate which proposals could be considered for future developments. Furthermore, we will show that combining different feature extraction models in an ensemble can lead to a superior performance, significantly increasing the results obtained by individual models.

Base pairing interaction between 5′- and 3′-UTRs controls icaR mRNA translation in Staphylococcus aureus

UPNa. Instituto de Agrobiotecnología. Laboratorio de Biofilms Microbianos.

Estimation of long-run parameters in unbalanced cointegration

This paper analyses the asymptotic properties of nonlinear least squares estimators of the long run parameters in a bivariate unbalanced cointegration framework. Unbalanced cointegration refers to the situation where the integration orders of the observables are different, but their corresponding balanced versions (with equal integration orders after filtering) are cointegrated in the usual sense. Within this setting, the long run linkage between the observables is driven by both the cointegrating parameter and the difference between the integration orders of the observables, which we consider to be unknown. Our results reveal three noticeable features. First, superconsistent (faster than √ n-consistent) estimators of the difference between memory parameters are achievable. Next, the joint limiting distribution of the estimators of both parameters is singular, and, finally, a modified version of the ‘‘Type II’’ fractional Brownian motion arises in the limiting theory. A Monte Carlo experiment and the discussion of an economic example are included.

Some preliminary conjunctural thoughts on countercultures

The article is devoted to analysis of various countercultures aspects. The Author hypothesizes that the forms of contemporary politics are the result of two fundamentally interrelated strategic vectors. First is built upon a politics of ressentiment, setting “ordinary” folks against the socio‐cultural elite which constututed to the “new right” movement. Second vector is originated of counterculture of the 1960s. The author states that counterculture exists without a singular identity. It is a space of hybridity and heterogenity. On the other hand counterculture is related to the concept of contemporary ambivalence as well it transforms of affective experience of everyday life. Another feature of counterculture is connected with the conviction that counterculture stands against of dominant culture. Also the author puts counterculture movements against various aspects of new american modernity including reconstruction of the practice of the hegemony, as well as through popular culture and reconstruction of the „left” and „right” idelogy and practice.

Gestão do cooperativismo médico no Brasil

Tese apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Doutor em Ciências Empresariais, especialidade em Gestão

Uniformly convergent finite element and finite difference methods for singularly perturbed ordinary differential equations

This thesis is concerned with uniformly convergent finite element and finite difference methods for numerically solving singularly perturbed two-point boundary value problems. We examine the following four problems: (i) high order problem of reaction-diffusion type; (ii) high order problem of convection-diffusion type; (iii) second order interior turning point problem; (iv) semilinear reaction-diffusion problem. Firstly, we consider high order problems of reaction-diffusion type and convection-diffusion type. Under suitable hypotheses, the coercivity of the associated bilinear forms is proved and representation results for the solutions of such problems are given. It is shown that, on an equidistant mesh, polynomial schemes cannot achieve a high order of convergence which is uniform in the perturbation parameter. Piecewise polynomial Galerkin finite element methods are then constructed on a Shishkin mesh. High order convergence results, which are uniform in the perturbation parameter, are obtained in various norms. Secondly, we investigate linear second order problems with interior turning points. Piecewise linear Galerkin finite element methods are generated on various piecewise equidistant meshes designed for such problems. These methods are shown to be convergent, uniformly in the singular perturbation parameter, in a weighted energy norm and the usual L2 norm. Finally, we deal with a semilinear reaction-diffusion problem. Asymptotic properties of solutions to this problem are discussed and analysed. Two simple finite difference schemes on Shishkin meshes are applied to the problem. They are proved to be uniformly convergent of second order and fourth order respectively. Existence and uniqueness of a solution to both schemes are investigated. Numerical results for the above methods are presented.

Feasibility of combined wind-wave energy platforms

The European Union has set out an ambitious 20% target for renewable energy use by 2020. It is expected that this will be met mainly by wind energy. Looking towards 2050, reductions in greenhouse gas emissions of 80-95% are to be sought. Given the issues securing this target in the transport and agriculture sectors, it may only be possible to achieve this target if the power sector is carbon neutral well in advance of 2050. This has permitted the vast expansion of offshore renewables, wind, wave and tidal energy. Offshore wind has undergone rapid development in recent years however faces significant challenges up to 2020 to ensure commercial viability without the need for government subsidies. Wave energy is still in the very early stages of development so as yet there has been no commercial roll out. As both of these technologies are to face similar challenges in ensuring they are a viable alternative power generation method to fossil fuels, capitalising on the synergies is potentially a significant cost saving initiative. The advent of hybrid solutions in a variety of configurations is the subject of this thesis. A singular wind-wave energy platform embodies all the attributes of a hybrid system, including sharing space, transmission infrastructure, O&M activities and a platform/foundation. This configuration is the subject of this thesis, and it is found that an OWC Array platform with multi-MegaWatt wind turbines is a technically feasible, and potentially an economically feasible solution in the long term. Methods of design and analysis adopted in this thesis include numerical and physical modelling of power performance, structural analysis, fabrication cost modelling, simplified project economic modelling and time domain reliability modelling of a 210MW hybrid farm. The application of these design and analysis methods has resulted in a hybrid solution capable of producing energy at a cost between €0.22/kWh and €0.31/kWh depending on the source of funding for the project. Further optimisation through detailed design is expected to lower this further. This thesis develops new and existing methods of design and analysis of wind and wave energy devices. This streamlines the process of early stage development, while adhering to the widely adopted Concept Development Protocol, to develop a technically and economically feasible, combined wind-wave energy hybrid solution.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Summer Sprite for Orchestra

Summer Sprite for Orchestra was completed in December, 2004. The piece originated from a singular encounter with little angels at Chang-Kyung Palace, which is the oldest and the most beautiful palace in Korea, and where the kings of the Chosun Dynasty (1393-1897) lived. This encounter was in the summer of 2002. I certainly could not prove that those angels I met were real. Possibly they were the reflection of drops of water after a sudden shower on that summer day. However, I definitely remember that short, unforgettable, and mysterious moment and the angels' beautiful dance-like celebration. Summer Sprite is based on these special memories and the encounter with the little angels that summer. Summer Sprite consists of 3 movements: "Greeting," "Encounter," and "Celebration." These follow the course of my encounter with the little angels. In Summer Sprite, I wished to describe the image of the angels as well as the progression of greeting, encounter, and celebration with them. The moods that follow in Summer Sprite are by turns lyrical, poetic, fantastic, mysterious, and dream-like. In each movement, I describe the meeting of angels and composer through the use of the soloists -- violin (sometimes viola) and cello. As suggested by the subtitle of the first movement, "Greeting" portrays the moment when a surprised I met the angels. It begins with tam-tam, marimba, harp, and piano and sets a mysterious and dark mood. The second movement, "Encounter," is shorter than the first movement. This movement provides a more tranquil mood as well as more unique timbres resulting from the use of mutes and special instruments (English horn, harp, crotales, suspended cymbal, and celesta). The delicate expression of the percussion is particularly important in establishing the static mood of this movement . The last movement, °?Celebration,°± is bright and energetic. It is also the longest. Here, I require the most delicate changes of dynamics and tempo, the most vigorous harmonies, and the fastest rhythmic figures, as well as the most independent, lyrical, and poetic melodies. For bright orchestral tone color, I used various kinds of percussion such as timpani, xylophone, marimba, vibraphone, cymbals, side drum, tambourine, triangle, and bass drum. This last movement is divided rondo-like into five sections: The first (mm.1-3), second (mm.4 - rehearsal number 1), third (rehearsal numbers 2-4), fourth (rehearsal numbers 5-7), and fifth, (rehearsal numbers 8 -18). To sum up, Summer Sprite describes an unforgettable and mysterious moment in a my life. My intention was to portray this through a concerto-like framework. A model for this would be Brahms°Ø °?Double Concerto°± in A minor, op.102, in which the solo cello stands for my angel and the solo violin (sometimes solo viola) for me.

Intensification of summer rainfall variability in the southeastern United States during recent decades

The variability of summer precipitation in the southeastern United States is examined in this study using 60-yr (1948-2007) rainfall data. The Southeast summer rainfalls exhibited higher interannual variability with more intense summer droughts and anomalous wetness in the recent 30 years (1978-2007) than in the prior 30 years (1948-77). Such intensification of summer rainfall variability was consistent with a decrease of light (0.1-1 mm day-1) and medium (1-10 mm day-1) rainfall events during extremely dry summers and an increase of heavy (.10 mm day-1) rainfall events in extremely wet summers. Changes in rainfall variability were also accompanied by a southward shift of the region of maximum zonal wind variability at the jet stream level in the latter period. The covariability between the Southeast summer precipitation and sea surface temperatures (SSTs) is also analyzed using the singular value decomposition (SVD) method. It is shown that the increase of Southeast summer precipitation variability is primarily associated with a higher SST variability across the equatorial Atlantic and also SST warming in the Atlantic. © 2010 American Meteorological Society.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.