When tomato Craigella is infected with Verticillium dahliae Dvd-E6 (Dvd-E6), a tolerant state is induced with substantial pathogen load, but few symptoms. Unexpectedly, these plants are more robust and taller with Dvd-E6 behaving as an endophyte. Some endophytes can protect plants from virulent pathogens. This research was undertaken to improve understanding of the cellular and molecular nature of Verticillium tolerance in tomato, especially whether infection by Dvd-E6 can protect Craigella from virulent V. dahliae, race 1 (Vd1). To permit mixed infection experiments a restriction fragment length polymorphism (RFLP)-based assay was developed and used for differentiating Dvd-E6 from Vd1, when present in mixed infections. The results suggested that protection involves molecular interplay between Dvd-E6 and Vd1 in susceptible Craigella (CS) tomatoes, resulting in restricted Vd1 colonization. Further studies showed a dramatic reduction of Vd1 spores and mycelia. To examine genetic changes that account for these biological changes, a customized DNA chip (TVR) was used to analyze defense gene mRNA levels. The defense gene response was categorized into four groups. Group 1 was characterized by strong induction of defense genes followed by suppression. However, Vd1-induced gene suppression was blocked by Dvd-E6 in mixed infections. These genes included some transcription factors and PR proteins such as class IV chitinases and beta glucanases which are known to target fungal spores and mycelia. Experiments also were repeated with a Craigella resistant (CR) isoline containing a fully active Ve locus (Ve1+ and Ve2+). The biological results showed that the presence of the Ve1+ allele resulted in restricted Vd1 colonization and, in a mixed infection with Dvd-E6, Vd1 was completely eliminated from the plant stem. Surprisingly, there was no significant increase in defense gene mRNAs. Rather, elevated basal levels of defense gene products appeared sufficient to combat pathogen attack. To investigate functional effects of the genetic changes observed, an inducible RNAi knockdown vector for a defense gene (TUS15G8) with unknown function (pMW4-TUS15G8) as well as the Ve2 resistance gene (pMW-Ve2) was prepared as a initial step for future transformation analyses. Taken together the results reveal intriguing but complex biological and molecular changes in mixed infections, which remain a basis for future experiments and potential agricultural benefits. / Canadian Commonwealth Scholarship and Fellowship Plan

This research investigates how the speech community living in Maputo city uses language in relation to HIV/AIDS and studies related stigmas which impede women's access to HIV/AIDS counselling services. My hypothesis is that frequent use of gender stereotypes in AIDS discourse aims at stigmatising women as AIDS propagators, while minimizing male sexual transgressions in the AIDS crisis. Interpretation of primary data collected via focus group discussions and interviews is done with five different approaches that study respectively: social meanings and representations of AIDS embedded in context, the stigmatising process correlating gender stereotypes and discrimination against women, stereotypical speech attitudes and speech mechanism as well as the functions and effects of stereotyping. My conclusion is that deeply rooted gender barriers are to be removed in order to combat the social plague of AIDS and that ethnography of communication offers interesting models for development projects that can initiate behavioural changes through speech. / Linguistics and Modern Languages / M.A. (Sociolinguistics)

The present diploma thesis is focused on the definition of differences resulting from the comparison of two chosen forms of doing business of a foreign person in the Czech Republic. It specifies differences from the viewpoint of the commercial law and the obligations as an accounting unit. Foremost, the thesis includes a detailed analysis from a tax point of view. The thesis involves a model example to define the precise amount of tax obligation incumbent on the both forms of business of a foreign person in the Czech Republic. This model example constitutes a basis for the final evaluation and to draw relevant conclusions. Suggestions and recommendations mentioned in this work can serve as an overview of the approach to the taxation of cross-border income and at the same time as a tool for the elimination of errors and discrepancies in connection with the chosen form of business of a foreign person in the Czech Republic.

Compressed sensing has been proposed as a computationally efficient method to estimate the finite-dimensional signals. The idea is to develop an undersampling operator that can sample the large but finite-dimensional sparse signals with a rate much below the required Nyquist rate. In other words, considering the sparsity level of the signal, the compressed sensing samples the signal with a rate proportional to the amount of information hidden in the signal. In this dissertation, first, we employ compressed sensing for physical layer signal processing of directional millimeter-wave communication. Second, we go through the theoretical aspect of compressed sensing by running a comprehensive theoretical analysis of compressed sensing to address two main unsolved problems, (1) continuous-extension compressed sensing in locally convex space and (2) computing the optimum subspace and its dimension using the idea of equivalent topologies using Köthe sequence. In the first part of this thesis, we employ compressed sensing to address various problems in directional millimeter-wave communication. In particular, we are focusing on stochastic characteristics of the underlying channel to characterize, detect, estimate, and track angular parameters of doubly directional millimeter-wave communication. For this purpose, we employ compressed sensing in combination with other stochastic methods such as Correlation Matrix Distance (CMD), spectral overlap, autoregressive process, and Fuzzy entropy to (1) study the (non) stationary behavior of the channel and (2) estimate and track channel parameters. This class of applications is finite-dimensional signals. Compressed sensing demonstrates great capability in sampling finite-dimensional signals. Nevertheless, it does not show the same performance sampling the semi-infinite and infinite-dimensional signals. The second part of the thesis is more theoretical works on compressed sensing toward application. In chapter 4, we leverage the group Fourier theory and the stochastical nature of the directional communication to introduce families of the linear and quadratic family of displacement operators that track the join-distribution signals by mapping the old coordinates to the predicted new coordinates. We have shown that the continuous linear time-variant millimeter-wave channel can be represented as the product of channel Wigner distribution and doubly directional channel. We notice that the localization operators in the given model are non-associative structures. The structure of the linear and quadratic localization operator considering group and quasi-group are studied thoroughly. In the last two chapters, we propose continuous compressed sensing to address infinite-dimensional signals and apply the developed methods to a variety of applications. In chapter 5, we extend Hilbert-Schmidt integral operator to the Compressed Sensing Hilbert-Schmidt integral operator through the Kolmogorov conditional extension theorem. Two solutions for the Compressed Sensing Hilbert Schmidt integral operator have been proposed, (1) through Mercer's theorem and (2) through Green's theorem. We call the solution space the Compressed Sensing Karhunen-Loéve Expansion (CS-KLE) because of its deep relation to the conventional Karhunen-Loéve Expansion (KLE). The closed relation between CS-KLE and KLE is studied in the Hilbert space, with some additional structures inherited from the Banach space. We examine CS-KLE through a variety of finite-dimensional and infinite-dimensional compressible vector spaces. Chapter 6 proposes a theoretical framework to study the uniform convergence of a compressible vector space by formulating the compressed sensing in locally convex Hausdorff space, also known as Fréchet space. We examine the existence of an optimum subspace comprehensively and propose a method to compute the optimum subspace of both finite-dimensional and infinite-dimensional compressible topological vector spaces. To the author's best knowledge, we are the first group that proposes continuous compressed sensing that does not require any information about the local infinite-dimensional fluctuations of the signal.

This biomedical engineering thesis explores the opportunities and challenges of 2D+t contrast echocardiography for left ventricle functional analysis, both clinically and within a computer vision atlas-based deformable template model framework. A database was created for the experiments in this thesis, with 21 studies of contrast Dobutamine Stress Echo, in all 4 principal planes. The database includes clinical variables, human expert hand-traced myocardial contours and visual scoring. First the problem is studied from a clinical perspective. Quantification of endocardial global and local function using standard measures shows expected values and agreement with human expert visual scoring, but the results are less reliable for myocardial thickening. Next, the problem of segmenting the endocardium with a computer is posed in a standard landmark and atlas-based deformable template model framework. The underlying assumption is that these models can emulate human experts in terms of integrating previous knowledge about the anatomy and physiology with three sources of information from the image: texture, geometry and kinetics. Probabilistic atlases of contrast echocardiography are computed, while noting from histograms at selected anatomical locations that modelling texture with just mean intensity values may be too naive. Intensity analysis together with the clinical results above suggest that lack of external boundary definition may preclude this imaging technique for appropriate measuring of myocardial thickening, while endocardial boundary definition is appropriate for evaluation of wall motion. Geometry is presented in a Principal Component Analysis (PCA) context, highlighting issues about Gaussianity, the correlation and covariance matrices with respect to physiology, and analysing different measures of dimensionality. A popular extension of deformable models ---Active Appearance Models (AAMs)--- is then studied in depth. Contrary to common wisdom, it is contended that using a PCA texture space instead of a fixed atlas is detrimental to segmentation, and that PCA models are not convenient for texture modelling. To integrate kinetics, a novel spatio-temporal model of cardiac contours is proposed. The new explicit model does not require frame interpolation, and it is compared to previous implicit models in terms of approximation error when the shape vector changes from frame to frame or remains constant throughout the cardiac cycle. Finally, the 2D+t atlas-based deformable model segmentation problem is formulated and solved with a gradient descent approach. Experiments using the similarity transformation suggest that segmentation of the whole cardiac volume outperforms segmentation of individual frames. A relatively new approach ---the inverse compositional algorithm--- is shown to decrease running times of the classic Lucas-Kanade algorithm by a factor of 20 to 25, to values that are within real-time processing reach.

In this thesis I hope to provide a clear and concise introduction to Feigenbaum scaling accessible to undergraduate students. This is accompanied by a description of how to obtain numerical results by various means. A more intricate approach drawing from renormalization theory as well as a short consideration of some of the topological properties will also be presented. I was furthermore trying to put great emphasis on diagrams throughout the text to make the contents more comprehensible and intuitive.

Indiana University-Purdue University Indianapolis (IUPUI) / Magnetic resonance (MR) spectroscopy is a neuroimaging technique. It is widely used to quantify the concentration of important metabolites in a brain tissue. Imbalance in concentration of brain metabolites has been found to be associated with development of neurological impairment. There has been increasing trend of using MR spectroscopy as a diagnosis tool for neurological disorders. We established statistical methodology to analyze data obtained from the MR spectroscopy in the context of the HIV associated neurological disorder. First, we have developed novel methodology to study the association of marker of neurological disorder with MR spectrum from brain and how this association evolves with time. The entire problem fits into the framework of scalar-on-function regression model with individual spectrum being the functional predictor. We have extended one of the existing cross-sectional scalar-on-function regression techniques to longitudinal set-up. Advantage of proposed method includes: 1) ability to model flexible time-varying association between response and functional predictor and (2) ability to incorporate prior information. Second part of research attempts to study the influence of the clinical and demographic factors on the progression of brain metabolites over time. In order to understand the influence of these factors in fully non-parametric way, we proposed LongCART algorithm to construct regression tree with longitudinal data. Such a regression tree helps to identify smaller subpopulations (characterized by baseline factors) with differential longitudinal profile and hence helps us to identify influence of baseline factors. Advantage of LongCART algorithm includes: (1) it maintains of type-I error in determining best split, (2) substantially reduces computation time and (2) applicable even observations are taken at subject-specific time-points. Finally, we carried out an in-depth analysis of longitudinal changes in the brain metabolite concentrations in three brain regions, namely, white matter, gray matter and basal ganglia in chronically infected HIV patients enrolled in HIV Neuroimaging Consortium study. We studied the influence of important baseline factors (clinical and demographic) on these longitudinal profiles of brain metabolites using LongCART algorithm in order to identify subgroup of patients at higher risk of neurological impairment. / Partial research support was provided by the National Institutes of Health grants U01-MH083545, R01-CA126205 and U01-CA086368

No description available.