This thesis examined the evidence, policy decision-making, and implementation of HPV vaccination in Canada as a case study to explore normalization versus individualized decision making in public health programs. Mixed methods were used: a systematic review, content analyses and policy document analysis. Overall, the scientific evidence supported an effect of vaccination against HPV infection and precancerous cervical lesions, but evidence regarding cervical cancer incidence or mortality is lacking. Scientific and medical communities appeared optimistic about the vaccine, but cautious about its readiness for routine implementation. Policy decision-making was initially cautious, but shifted towards active program implementation, possibly related to the availability of federal funding. The educational materials and media coverage both sent clearly normalizing messages about HPV vaccination. The discussion suggests that HPV vaccination might be more suited to an individualized than population approach, but many factors coincided to promote its implementation, in Canada, within a traditional public health model.

Nanostring technology provides a new method to measure gene expressions. It's more sensitive than microarrays and able to do more gene measurements than RT-PCR with similar sensitivity. This system produces counts for each target gene and tabulates them. Counts can be normalized by using an Excel macro or nSolver before analysis. Both methods rely on data normalization prior to statistical analysis to identify differentially expressed genes. Alternatively, we propose to model gene expressions as a function of positive controls and reference gene measurements. Simulations and examples are used to compare this model with Nanostring normalization methods. The results show that our model is more stable, efficient, and able to control false positive proportions. In addition, we also derive asymptotic properties of a normalized test of control versus treatment.

Cancer of the prostate (CaP) is the most common malignancy diagnosed in men in the Western society. During the last years, prostate specific antigen (PSA) has been used as a biomarker for CaP, although a high PSA value is not specific for CaP. Thus, there is an urgent need for new and improved diagnostic markers for CaP. In this thesis, the aim was to find a miRNA signature for diagnosis of CaP and to elucidate if differences in behavior between transition zone and peripheral zone tumors are reflected in miRNA expression. One of the major findings is anexpression signature based on nine miRNAs that with high accuracy (85%) could classify normal and malignant tissues from the transition zone of the prostate. The results furthermore show that the major differences in miRNA expression are found between normal and malignant tissues, rather than between the different zones. In addition, tumors arising in the peripheral zone have fewer changes in miRNA expression compared to tumors in the transition zone, indicating that the peripheral zone is more prone to tumor development compared to the transition zone of the prostate. A crucial step in pre-processing of expression data, in order to differentiate true biological changes, is the normalization step. Therefore, an additional aim of this thesis was to compare different normalization methods for qPCR array data in miRNA expression experiments. The results show that data-driven methods based on quantile normalization performs the best. The results also show that in smaller miRNA expression studies, only investigating a few miRNAs, RNU24 is the most suitable endogenous control gene for normalization. Taken together, the results in this thesis show the importance of miRNAs and the possibility of their future use as biomarkers in the field of prostate cancer.

Submitted thesis The Portrayal of Czech Society in Petr Schulhoff's Film Comedies of the Normalization Era analyses the cinematography of the Czechoslovak Republic in the seventies and the eighties through the topic of social a ideological values which they present. Its primary concern is the question what are selected movies saying about Czechoslovak social reality of that time and which instruments of semiotic mediations are used for this purpose. The main assumption of the work is that also escapist entertainment described the era, setting and characters according to norms dictated by the communist government and thus help to stabilize the system.

In this thesis, we address two major problems in Generative Adversarial Networks (GAN), an important sub-field in deep learning. The first problem that we address is the instability in the training process that happens in many real-world problems and the second problem that we address is the lack of a good evaluation metric for the performance of GAN algorithms. To understand and address the first problem, three approaches are developed. Namely, we introduce randomness to the training process; we investigate various normalization methods; most importantly we develop a better parameter initialization strategy to help stabilize training. In the randomness techniques part of the thesis, we developed two randomness approaches, namely the addition of gradient noise and the batch random flipping of the results from the discrimination section of a GAN. In the normalization part of the thesis, we compared the performances of the z-score transform, the min-max normalization, affine transformations and batch normalization. In the most novel and important part of this thesis, we developed techniques to initialize the GAN generator section with parameters that can produce a uniform distribution on the range of the training data. As far as we are aware, this seemingly simple idea has not yet appeared in the extant literature, and the empirical results we obtain on 2-dimensional synthetic data show marked improvement. As to better evaluation metrics, we demonstrate a simple yet effective way to evaluate the effectiveness of the generator using a novel "overlap loss".

In this thesis, we address two major problems in Generative Adversarial Networks (GAN), an important sub-field in deep learning. The first problem that we address is the instability in the training process that happens in many real-world problems and the second problem that we address is the lack of a good evaluation metric for the performance of GAN algorithms. To understand and address the first problem, three approaches are developed. Namely, we introduce randomness to the training process; we investigate various normalization methods; most importantly we develop a better parameter initialization strategy to help stabilize training. In the randomness techniques part of the thesis, we developed two randomness approaches, namely the addition of gradient noise and the batch random flipping of the results from the discrimination section of a GAN. In the normalization part of the thesis, we compared the performances of the z-score transform, the min-max normalization, affine transformations and batch normalization. In the most novel and important part of this thesis, we developed techniques to initialize the GAN generator section with parameters that can produce a uniform distribution on the range of the training data. As far as we are aware, this seemingly simple idea has not yet appeared in the extant literature, and the empirical results we obtain on 2-dimensional synthetic data show marked improvement. As to better evaluation metrics, we demonstrate a simple yet effective way to evaluate the effectiveness of the generator using a novel "overlap loss".

Statistical inference in time series analysis has been an important subject in various fields including climate science, economics, finance and industrial engineering among others. Numerous problems of research interest include statistical inference about unknown quantities, assessing structural stability and forecasting. These problems have been widely studied in the literature, but mainly for independent data, while in many applications involving time series data dependence is not unusual and in fact quite common. In this thesis, we incorporate serial dependence into the analysis by involving self-normalization in time series analysis. We start with the problem of testing whether there are change-points in a given time series. The method we propose does not require the number of change-points to be predefined, and thus is unsupervised. It does not require any tuning parameters and can be applied to a wide class to quantities of interest. The asymptotic distribution of the test statistic is studied and an approximation scheme is proposed to reduce testing procedure complexity. We then consider the problem of construction of confidence intervals, for which the conventional self-normalizer exhibits certain degrees of asymmetry when applied to quantities other than the mean. The method we propose provides a time-symmetric generalization to the conventional self-normalizer and leads to improved finite sample performance for quantities other than the mean.

A pesquisa apresenta a teoria marcuseana do poder como perspectiva crítica no debate contemporâneo acerca do conceito foucaultiano de biopolítica. À primeira vista, tal relação parece controversa, ao reconhecer que Foucault desenvolve seu conceito paralelamente à crítica contra Marcuse. Ora, o conceito foucaultiano de biopolítica descreve jogos de poder como administração dos corpos e também como um modo de cálculo da vida da população. Tal concepção contraria diretamente a hipótese marcuseana do poder repressivo, um modelo crítico que tem em vista uma camada verdadeira e subjacente de poder, recalcada nas formações sociais e subjetivas estabelecidas. Com esse quadro, como reunir os dois autores na crítica do poder, assumindo a biopolítica como premissa da teoria do poder? De fato, a aproximação seria impossível ao partir da aposta marcuseana em uma civilização nãorepressiva, presente em Eros e Civilização. Contudo, com a análise do avanço da racionalidade instrumental no pós-Guerra em O Homem Unidimensional, Marcuse avalia a possibilidade de um poder não-repressiva. Afinal, na nova ordem social não se apresenta mais um controle repressivo dos corpos, mas sim uma excitação da vida e dos corpos em movimento. Seria este um sinal de concordância entre os autores? E ainda, dada esta nova correspondência, é possível aproveitar a crítica foucaultiana à biopolítica para redimensionar não apenas as reflexões de Marcuse sobre o poder, como também as passagens contemporâneas entre a teoria crítica e a genealogia do poder? / This research presents Marcuses theory of power as an essential perspective for the contemporary debate on the Foucaultian concept of biopolitics. This would seem a rather controversial choice at a first glance, as, admittedly, the development of Foucaults concept occurred alongside that of his critique of Marcuse. Indeed, Foucaults conception of biopolitics describes games of power that include the administration of the bodies and the calculated management of the life of a given population a notion entirely adverse to Marcuses repressive hypothesis of power, a critical model that assumes a real, subjacent layer of power that is repressed in established social and subjective formations. Given these differences, as well as an adoption of biopolitics as a fundamental premise for a theory of power, how are the two authors to be brought together for a critique of power? Such an approximation would certainly be impossible in light of Marcuses arguments, in Eros and Civilization, for the possibility of a non-repressive civilization. Still, through the analysis of the advancement of instrumental rationality in the postwar period conducted in One- Dimensional Man, Marcuse will revise his former perspective on non-repressive power; after all, the new social order no longer features a repressive control of bodies, but rather an excitation of life, and of bodies to motion. Could that be understood as a sign of agreement between the authors? Furthermore, given this new correspondence, would it be possible to employ Foucaults critique to add dimensions not only to Marcuses reflections on power, but to contemporary mediations between critical theory and the genealogy of power?

Calculating hippocampal volume from Magnetic Resonance (MR) images is an essential task in many studies of neurocognition in healthy and diseased populations. The `gold standard' method involves hand tracing, which is accurate but laborious, requiring expertly trained researchers and significant amounts of time. As such, segmenting large datasets with the standard method is impractical. Current automated pipelines are inaccurate at hippocampal demarcation and volumetry. We developed a semi-automated hippocampal segmentation pipeline based on the Advanced Normalization Tools (ANTs) suite of programs to segment the hippocampus. We applied the semi-automated segmentation pipeline to 70 participant scans (26 female) from groups that included participants diagnosed with autism spectrum disorder, healthy older adults (mean age 74) and healthy younger controls. We found that hippocampal segmentations obtained with the semi-automated pipeline more closely matched the segmentations of an expert rater than those obtained using FreeSurfer or the segmentations of novice raters. Further, we found that the pipeline performed best when including manually- placed landmarks and when using a template generated from a heterogeneous sample (that included the full variability of group assignments) than a template generated from more homogeneous samples (using only individuals within a given age or with a specific neuropsychiatric diagnosis). Additionally, the semi-automated pipeline required much less time (5 minutes per brain) than manual segmentation (30-60 minutes per brain) or FreeSurfer (8 hours per brain).

Diffusion tensor imaging provides the ability to study white matter connectivity and integrity noninvasively. The information contained in the diffusion tensors is very complex. Therefore a simple way of dealing with tensors is to compute rotationally invariant scalar quantities. These scalar indices have been used to perform population studies between controls and patients with neurological and psychiatric disorders. Implementing the scalar values may reduce the information contained in the whole tensor. A group analysis using the full tensors may give better estimate of white matter changes that occur in the diseased subjects. For spatial normalization of diffusion tensors, it is necessary to interpolate the tensor representation as well as rotate the diffusion tensors after transformation to keep the tensors consistent with the tissue reorientation. Existing reorientation methods cannot be directly used for higher order diffusion models (e.g. q-ball imaging). A novel technique called gradient rotation is introduced where the rotation is directly applied to the diffusion sensitizing gradients providing a voxel by voxel estimate of the diffusion gradients instead of a volume of by volume estimate. The technique is validated by comparing it with an existing method where the transformation is applied to the resulting diffusion tensors. For better matching of diffusion tensors a novel multichannel registration method is proposed based on a non-parametric diffeomorphic demons algorithm. The channels used for the registration include T1-weighted volume and tensor components. A fractional anisotropy (FA) channel is used for defining the contribution of each channel. Including the anatomical data together with the tensors, allows the registration to accurately match the global brain shape and the underlying white matter architecture simultaneously. Using this multichannel registration framework, 10 healthy controls and 9 patients of schizophrenia were spatially normalized. For the group analysis, the tensors were transformed to log-euclidean space. Linear regression analysis was performed on the transformed tensors. Results show that there is a significant difference in the anisotropy between patients and controls especially in the anterior regions that include genu of the corpus callosum and anterior and superior corona radiata, forceps minor and anterior limb on the internal capsule.