The diploma thesis is concerned with the portrayal of the Windrush generation, the first wave of immigrants coming to Britain from its former colonies, in Andrea Levy's Small Island (2004) and Samuel Selvon's The Lonely Londoners (1956). The theoretical part of the thesis outlines the socio-historical and cultural overview of the rising immigration to Britain after the Second World War, which according to the selected secondary sources contributed to the increase of racism and discrimination, namely against people of Caribbean origin. The thesis further presents principal concepts of postcolonial and Anglophone Caribbean literature and examines both authors' personal experience with immigration as well as the idiosyncratic features of their writing. These are essential for understanding the literary works of the selected authors and the subsequent interpretation of their literary depiction of the immigrant experience. The practical part of the thesis relies on the theoretical part and focuses on the comparison of the two novels, their presentation and view of the so-called Windrush generation with specific attention paid to their form and content. Simultaneously, the work examines how the literary depictions of the immigrant experience correspond to the theory presented. Moreover, the thesis...

<div>Biological dynamics have been studied by many methods. Fluorescence dynamic microscopy and optical coherence tomography provided fundamental understandings of biological systems. However, their high NA optics only represent local characteristics. Biodynamic imaging (BDI) technique implements a low NA optics and acquires the statistical average of Doppler shifts that occurred by dynamic light scattering with biological dynamic subsystems provided globally averaged dynamic characteristics. </div><div>BDI is used for this study to investigate biomedical applications. The chemotherapy efficacy measurement by BDI demonstrated a good agreement between the Doppler spectral phenotypes and the preclinical outcomes. Also, dynamic responses of microbiomes by chemical stimuli demonstrated featured Doppler characteristics. The bacterial infection of epithelial spheroids showed consistent spectral responses and antibiotic-resistant E. coli infection treatment with a sensitive and resistive antibiotic showed a dramatic contrast. Furthermore, the phase-sensitive characteristics of BDI provided a clue to understanding the characteristics of the random process of biological systems. Levy-like heavy-tailed probability density functions are demonstrated and </div><div>the shape changed by infection will be discussed. </div>

Bedienstete Internationaler Organisationen stehen in einem speziellen Rechtsverhältnis zu ihrem Arbeitgeber, das ihnen ermöglicht, belastende Maßnahmen von speziell für Personalrechtsangelegenheiten errichteten internationalen Verwaltungsgerichten (Administrative Tribunals) überprüfen zu lassen. Anläßlich einer konkreten Streitigkeit (ESA) um Gehaltskürzungen befaßt sich der Beitrag sowohl mit prozeduralen als auch mit materiell-rechtlichen Fragenstellungen und erörtert, wie weit hier bereits allgemeine Rechtsgrundsätze existieren.

Title: Options under Stable Laws. Author: Andrea Karlová Department: Department of Probability and Mathematical Statistics Supervisor: Doc. Petr Volf, CSc. Abstract: Stable laws play a central role in the convergence problems of sums of independent random variables. In general, densities of stable laws are represented by special functions, and expressions via elementary functions are known only for a very few special cases. The convenient tool for investigating the properties of stable laws is provided by integral transformations. In particular, the Fourier transform and Mellin transform are greatly useful methods. We first discuss the Fourier transform and we give overview on the known results. Next we consider the Mellin transform and its applicability on the problem of the product of two independent random variables. We establish the density of the product of two independent stable random variables, discuss the properties of this product den- sity and give its representation in terms of power series and Fox's H-functions. The fourth chapter of this thesis is focused on the application of stable laws into option pricing. In particular, we generalize the model introduced by Louise Bachelier into stable laws. We establish the option pricing formulas under this model, which we refer to as the Lévy Flight...

Efficiently pricing multi-asset options is a challenging problem in computational finance. Although classical Fourier methods are extremely fast in pricing single asset options, maintaining the tractability of Fourier techniques for multi-asset option pricing is still an area of active research. Fourier methods rely on explicit knowledge of the characteristic function of the suitably stochastic price process, allowing for calculation of the option price by evaluation of multidimensional integral in the Fourier domain. The high smoothness of the integrand in the Fourier space motivates the exploration of deterministic quadrature methods that are highly efficient under certain regularity assumptions, such as, adaptive sparse grids quadrature (ASGQ), and Randomized Quasi-Monte Carlo (RQMC). However, when designing a numerical quadrature method for most of the existing Fourier pricing approaches, two key factors affecting the complexity should be carefully controlled, (i) the choice of the vector of damping parameters that ensure the Fourier-integrability and control the regularity class of the integrand, (ii) the high-dimensionality of the integration problem. To address these challenges, in the first part of this thesis we propose a rule for choosing the damping parameters, resulting in smoother integrands. Moreover, we explore the effect of sparsification and dimension-adaptivity in alleviating the curse of dimensionality. Despite the efficiency of ASGQ, the error estimates are very hard to compute. In cases where error quantification is of high priority, in the second part of this thesis, we design an RQMC-based method for the (inverse) Fourier integral computation. RQMC integration is known to be highly efficient for high-dimensional integration problems of sufficiently regular integrands, and it further allows for computation of probabilistic estimates. Nonetheless, using RQMC requires an appropriate domain transformation of the unbounded integration domain to the hypercube, which may originate in a transformed integrand with singularities at the boundaries, and consequently deteriorate the rate of convergence. To preserve the nice properties of the transformed integrand,we propose a model-dependent domain transformation to avoid these corner singularities and retain the optimal efficiency of RQMC. The effectiveness of the proposed optimal damping rule, the designed domain transformation procedure, and their combination with ASGQ and RQMC are demonstrated via several numerical experiments and computational comparisons to the MC approach and the COS method.

The Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem.

Made available in DSpace on 2016-04-04T18:36:31Z (GMT). No. of bitstreams: 1 Ednea Zandonadi Brambila.pdf: 1153153 bytes, checksum: 70abed7b1525cb983c387ff3947fec64 (MD5) Previous issue date: 2006-02-13 / The origin of the Science of the Information as interdisciplinary science, enrolled in the Post-modern context, it considers information a product integrated to the social cycle that it foresees its circulation and use. In this sense, the Public Library, as institution that collect culture should contemplate the development of collections compromised with the local community's culture, making available a space in the society where the individual can exercise its creativity and the exaltation of his/her citizenship, contributing like this to the elaboration and preservation of the local cultural identity. To identify the way for which fellow creature process if it renders, it is made a historical rising of the appearance of the Public Libraries in Brazil, being drawn a parallel one among BP idealized by M?rio of Andrade and the characterization of the performance of first BP of Esp?rito Santo State. Finally, through empiric study, it tries to develop possibilities of effective viabilization of the access to the culture through BP. / A origem da Ci?ncia da Informa??o como ci?ncia interdisciplinar, inscrita no contexto P?s-Moderno, considera informa??o um produto integrado ao ciclo social que prev? sua circula??o e uso. Neste sentido, a Biblioteca P?blica, como institui??o coletora de cultura deve contemplar o desenvolvimento de cole??es compromissadas com a cultura da comunidade local, disponibilizando um espa?o na sociedade onde o indiv?duo possa exercer sua criatividade e o enaltecimento de sua cidadania, contribuindo assim para a elabora??o e preserva??o da identidade cultural local. Para identificar o modo pelo qual semelhante processo se concretiza, faz-se um levantamento hist?rico do surgimento das Bibliotecas P?blicas no Brasil, tra?ando-se um paralelo entre a BP idealizada por M?rio de Andrade e a caracteriza??o da atua??o da primeira BP do Estado do Esp?rito Santo. Finalmente, atrav?s de estudo emp?rico, procura-se desenvolver possibilidades de efetiva viabiliza??o do acesso ? cultura via BP.

The Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem.

The Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem.

本篇論文主要探討1880至1930年代英國女性作家所再現的性別化空間。女性逐漸在十九世紀末倫敦的公共空間嶄露頭角，扮演各種不同的重要角色，舉凡上班族、消費者、俱樂部會員、電影迷、行善者及觀光客等都是當時女性公共形象的最佳例證。然而這些跨越公/私領域界限的女性漫遊者迄今都未獲得學界足夠的重視。女性漫遊者在世紀末文學研究中長期遭受忽視主要肇因於早期學者對於十九世紀男主外、女主內的公/私領域劃分大致認同，未能加以批判。透過檢視艾蜜‧列薇 (Amy Levy)、桃樂斯‧理察森 (Dorothy Richardson) 以及維吉尼亞‧吳爾夫 (Virginia Woolf) 等三位女作家的跨文類書寫，本篇論文指出世紀末的中產階級女性已逐漸掙脫傳統私領域以及家庭意識形態的束縛，開始在城市空間行走與觀看。在十九世紀末許多新興的大城市例如倫敦，如此的女性公共行走則又更加顯著並且和日益蓬勃發展的商品文化、大眾消費/享樂以及公共空間皆有極密切的關聯。流動 (mobility) 與觀察 (spectatorship) 因此成為中產階級女性在城市空間行走與觀看時的重要經驗，前者來自於女性在日益開放的公共領域遂行的空間探索，後者則是來自女性觀察者對於城市景觀例如商品展示、來往的人潮以及繁忙的街景所做的視覺凝視。經由書寫世紀末的女性城市漫遊，上述三位女作家明確地指出這些表面看似被動的中產階級女性其實早已跨越傳統空間限制，不斷挪用與創造新的城市公共空間。 / This study has examined the numerous roles played by women entering the public spaces of London in the half century from the 1880s to the 1930s as workers, shoppers, diners, clubbers, cinema-goers, philanthropists, and tourists, a wide spectrum of active female social actors that until recently have not attracted enough attention from scholars of late-Victorian and Edwardian literature. The neglect of these newly pubic women in the fin de siècle period, who are distinct from their home-bound Victorian predecessors, is largely ascribed to an uncritical acceptance of or surrender to the long-held, dominant assumption of separate spheres in the nineteenth century. Through examining the writings of Amy Levy, Dorothy Richardson, and Virginia Woolf, who portray the multifarious pictures of women rambling the streets of modern London, this study has demonstrated that female public visibility and mobility have at least since the fin de siècle period been commonly practiced by a conglomerate of middle-class women. Mobility and spectatorship are thus two significant tropes applicable to women’s spatial and visual explorations of the fin de siècle city, the former underscoring their meandering footsteps threading through the increasingly egalitarian public space while the latter their roving eyes casting glances at those enticing urban spectacles which are already a phantasmagoria of commodity display, jostling crowd, and bustling streetscapes. Through writing about fin de siècle female streetwalking, the three women writers have demonstrated that those seemingly passive women of the middle-class may indeed be capable, through their public presence and their incessant footsteps, of pushing at the established boundaries.