VictorJuiz/thesis huggingface dataset:
The Position of the Sammarinese Dialects in the Romagnol Linguistic Group
Keywords: Italian Dialectology
Romagnolo

Although Italo-Romance varieties continue to be documented, classified, and analyzed by dialectologists, many are at risk of not being recorded thoroughly and systematically before their imminent extinction. While considerable attention has been devoted to the phonetics, phonology, morphosyntax, and lexicon of the more archetypal Romagnol dialects spoken in the Po Valley, dialectologists have largely overlooked peripheral Romagnol varieties such as Sammarinese. The present dissertation begins to fill this lacuna in Italian dialectology by providing an historical and synchronic study of Sammarinese phonology and morphology based on the examination of old and modern texts as well as copious oral data. The main purpose of the thesis is to delineate diatopic variation within the tiny Republic through comparative analysis, while also addressing the need for a more complete and precise definition of Sammarinese‘s position in the Romagnol linguistic group. In addition to confirming Sammarinese‘s status as a Borderline Romagnol variety, the dissertation offers evidence that Sammarinese is divided geographically into two main dialectal groups: Northeastern and Southwestern. The secondary intent of the thesis is to provide systematic, comprehensive, and phonetically precise documentation of the phonology and morphology of a moribund language. iii The dissertation consists of five chapters. The Introduction includes a brief linguistic history which relates diatopic variation to geopolitical factors. The first chapter also contributes an assessment of the status of scholarship dedicated to Sammarinese dialectology. Chapter 2 examines diachronic phonetics, emphasizing the dichotomy between the traits which link Southwestern Sammarinese to Borderline Romagnol and those which join Northeastern Sammarinese with the Romagnol varieties of the Po Valley. Chapter 3 treats synchronic phonetics and proposes a generative phonology which aims to identify the diasystem underlying phonetic variation within the Republic. Chapter 4 analyzes historical declensional morphology, underscoring diatopic variation in internal flexion configurations as further evidence of the division between Northeastern and Southwestern Sammarinese. Chapter 5 examines diachronic verb morphology. The dissertation concludes with an assessment of linguistic aspects meriting further research and analysis.
Fabrication and Characterization of Waveguides in Potassium Gadolinium Tungstate
Keywords: Waveguides
Raman
Microreflectivity
crystals

This thesis describes the fabrication and characterization of waveguides in the nonlinear, Raman-active optical crystal potassium gadolinium tungstate (KGW). Ion implantation and femtosecond laser writing techniques are used for the first time to fabricate waveguides in this material. The light ion implanted waveguides using hydrogen ions showed unexpected refractive index increases in the damage regions of approximately 0.3% of the nominal refractive index values for three of the four polarization orientations, with only the highest refractive index polarization exhibiting a refractive index decrease of approximately 0.2%. Waveguides fabricated using high-energy carbon, oxygen and fluorine ion irradiations resulted in strongly confining waveguides with wide amorphous damage regions. Carbon ion irradiation of KGW showed the most promise, with sharp step-like waveguides with a maximum refractive index change of delta-n=0.2 with excellent preservation of the Raman properties in the waveguide core. Microreflectivity measurements on the carbon ion irradiated sample revealed unexpected intermittent refractive index changes in the core region, a feature not detected using standard characterization techniques found in the literature. The oxygen ion irradiation of KGW also generated strongly confining waveguides with a maximum refractive index change of delta-n=0.17, however the Raman performance was shown to be reduced to less than 50% in the waveguide cores. Fluorine ion irradiations of KGW resulted in amorphous regions fabricated in the surface regions, offering promise for masking techniques for creating two-dimensional structures. The waveguides written using femtosecond laser writing processes were used to write buried channel waveguides using compressive stresses to form the waveguide. These waveguides exhibited low-losses down to to 2.0 dB/cm in the telecommunications spectrum, with high coupling efficiency to SMF fiber, and excellent Raman properties in the waveguide core. These channel waveguides also successfully showed SRS generation into the 1.8-1.9 \mu m infrared region using a high power picosecond pump source in the telecommunications band. The use of the microreflectivity and micro-Raman spectroscopy measurement techniques were demonstrated to be valuable characterization tools for each of the fabrication methods.
Nonparametric Bayesian Methods for Extracting Structure from Data
Keywords: 0800

One desirable property of machine learning algorithms is the ability to balance the number of parameters in a model in accordance with the amount of available data. Incorporating nonparametric Bayesian priors into models is one approach of automatically adjusting model capacity to the amount of available data: with small datasets, models are less complex (require storing fewer parameters in memory), whereas with larger datasets, models are implicitly more complex (require storing more parameters in memory). Thus, nonparametric Bayesian priors satisfy frequentist intuitions about model complexity within a fully Bayesian framework. This thesis presents several novel machine learning models and applications that use nonparametric Bayesian priors. We introduce two novel models that use flat, Dirichlet process priors. The first is an infinite mixture of experts model, which builds a fully generative, joint density model of the input and output space. The second is a Bayesian biclustering model, which simultaneously organizes a data matrix into block-constant biclusters. The model capable of efficiently processing very large, sparse matrices, enabling cluster analysis on incomplete data matrices. We introduce binary matrix factorization, a novel matrix factorization model that, in contrast to classic factorization methods, such as singular value decomposition, decomposes a matrix using latent binary matrices. We describe two nonparametric Bayesian priors over tree structures. The first is an infinitely exchangeable generalization of the nested Chinese restaurant process that generates data-vectors at a single node in the tree. The second is a novel, finitely exchangeable prior generates trees by first partitioning data indices into groups and then by randomly assigning groups to a tree. We present two applications of the tree priors: the first automatically learns probabilistic stick-figure models of motion-capture data that recover plausible structure and are robust to missing marker data. The second learns hierarchical allocation models based on the latent Dirichlet allocation topic model for document corpora, where nodes in a topic-tree are latent ``super-topics", and nodes in a document-tree are latent categories. The thesis concludes with a summary of contributions, a discussion of the models and their limitations, and a brief outline of potential future research directions.
Above and Below Ground Fungal Diversity in a Hemlock-dominated Forest Plot in Southern Ontario and the Phylogenetic Placement of a New Ascomycota Subphylum
Keywords: mycology
fungi
basidiomycota
ascomycota
soil
phylogenetics

The objective of this thesis was to assess the diversity and community structure of fungi in a forest plot in Ontario using a variety of field sampling and analytical methods. Three broad questions were addressed: 1) How do different measures affect the resulting view of fungal diversity? 2) Do fruiting bodies and soil rDNA sampling detect the same phylogenetic and ecological groups of Agaricomycotina? 3) Will additional rDNA sampling resolve the phylogenetic position of unclassified fungal sequences recovered from environmental sampling? Generally, richness, abundance, and phylogenetic diversity (PD) correspond and identify the same dominant fungal groups in the study site, although in different proportions. Clades with longer branch lengths tend to comprise a larger proportion of diversity when assessed using PD. Three phylogenetic-based comparisons were found to be variable in their ability to detect significant differences. Generally, the Unifrac significance measure (Lozupone et al., 2006) is the most conservative, followed by the P-test (Martin, 2002), and Libshuff library comparison (Singleton et al., 2001) with our dataset. Fruiting body collections and rDNA sampling recover largely different assemblages of fungi at the species level; however, both methods identify the same taxonomic groups at the genus-order level as well as ectomycorrhizal fungi as the dominant functional type of Agaricomycotina. This work also shows that the Soil Clone Group I (SCGI) clade is widespread in soils of diverse origins and represents a novel subphylum of Ascomycota.
Acute Care Nurse Practitioners', Physicians' and Staff Nurses' Relationships with Patients: A Descriptive, Comparative Study
Keywords: Interpersonal Relations
Professional-Patient Relationships
Nurse Practitioners
Advanced Nursing Practice
Acute Care Nurse Practitioners

Acute care nurse practitioners (ACNPs) are a new addition to the Canadian health care system, having been introduced in the Canadian health care system in the late 1980s. While some authors have suggested that nurse practitioners offer “something special” to patient care, no evidence to date has substantiated this claim. The findings of this grounded theory study offer a theory (Acute Care Health Professional-Patient Relationship (ACHPPR) Theory) to describe how three types of health care professionals establish relationships with patients in acute care settings (Figure 7). This qualitative study explored relationships that ACNPs, physicians and staff nurses establish with patients in a large urban multi-site university-affiliated hospital. Six quartets (patient, ACNP, physician, staff nurse) were recruited and interviews, using a semi-structured guide were audio-taped and subsequently transcribed verbatim. Each type of relationship was found to have a unique focus; ACNPs focus on making connections with patients, physicians focus on managing patients’ diseases and staff nurses focus on meeting patients’ needs. In order to establish relationships with patients, readiness conditions must be met. Health professionals use strategies to influence the achievement of readiness conditions as well as to move forward with relationship development. Each type of relationship varies in the range of potential intensity that can be achieved, which is influenced by various dimensions. Relational intensity ranges from the uncommon clinical relationship, which focuses on the patient’s disease, through the more typical professional relationship characterized by a comfortable rapport and then finally to the most relationally intense, but rare, personal relationship. If a relationship reaches professional or personal levels of relational intensity, relational products become evident. When comparing these three health professional-patient relationships, similarities and differences have been identified. Analysis of patient interviews yielded themes that substantiate the ACHPPR theory. The ACHPPR theory offers a beginning understanding of the complementary nature of three types of health professional-patient relationships in the acute care setting and has the potential to influence practice, education, theory development and future research related to ACNP-patient relationships.
Missing Data Problems in Machine Learning
Keywords: Computer Science
Artificial Intelligence
Machine Learning
Missing Data

Learning, inference, and prediction in the presence of missing data are pervasive problems in machine learning and statistical data analysis. This thesis focuses on the problems of collaborative prediction with non-random missing data and classification with missing features. We begin by presenting and elaborating on the theory of missing data due to Little and Rubin. We place a particular emphasis on the missing at random assumption in the multivariate setting with arbitrary patterns of missing data. We derive inference and prediction methods in the presence of random missing data for a variety of probabilistic models including finite mixture models, Dirichlet process mixture models, and factor analysis. Based on this foundation, we develop several novel models and inference procedures for both the collaborative prediction problem and the problem of classification with missing features. We develop models and methods for collaborative prediction with non-random missing data by combining standard models for complete data with models of the missing data process. Using a novel recommender system data set and experimental protocol, we show that each proposed method achieves a substantial increase in rating prediction performance compared to models that assume missing ratings are missing at random. We describe several strategies for classification with missing features including the use of generative classifiers, and the combination of standard discriminative classifiers with single imputation, multiple imputation, classification in subspaces, and an approach based on modifying the classifier input representation to include response indicators. Results on real and synthetic data sets show that in some cases performance gains over baseline methods can be achieved by methods that do not learn a detailed model of the feature space.
TCDD Disrupts Gene Expression in the Developing Mouse Kidney
Keywords: TCDD
Dioxin

Dioxins such as the potent 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) are persistent environmental contaminants, exposure to which results in a number of toxic effects in several species. In mice, TCDD-induced hydronephrosis of the kidney is among the most sensitive of developmental abnormalities. It is widely accepted that the toxic effects of dioxins such as TCDD are mediated by the aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor expressed in virtually all tissues. Though it is known that activation of the AHR during development is likely the first step in TCDD-induced hydronephrosis, genetic events occurring downstream of AHR activation remain to be elucidated. To this end, we investigated the effect of TCDD on gene expression during development of the mouse kidney through use of expression arrays. Our analysis indicates that TCDD alters the expression of genes involved in the developmentally-critical Wnt signaling pathway and genes involved in cell cycle and cell proliferation. Further investigation of the effect of TCDD on Wnt pathway gene expression using an mRNA expression time course and in situ hybridization to characterize localized mRNA changes suggests that TCDD inhibits canonical Wnt signaling in the developing kidney. Consistent with our expression array finding that TCDD downregulates genes involved in cell proliferation, we also report a decrease in cell proliferation that coincides with regions of the kidney where inhibitors of canonical Wnt signaling are induced in response to TCDD. TCDD-induced disruption of Wnt pathway gene expression is not limited to the kidney, and alteration of Wnt gene expression is tissue-specific with varying effects observed in the heart, lung, liver, skin, and brain. Preliminary evidence also indicates that exposure to TCDD during development can alter the expression of microRNAs predicted to target Wnt pathway genes, suggesting a new mechanism for TCDD-induced disruption of gene expression. Taken together, our findings suggest that TCDD may disrupt an important pathway that is critical to the normal development of several organs in numerous species.
Combinatorial Auctions for Truckload Transportation Procurement
Keywords: Combinatorial auctions
Truckload transportation
Procurement

The goal of this dissertation is to understand the market-based mechanisms that enable shippers to allocate lanes in an efficient way for truckload (TL) transportation procurement despite the self-interest of carriers. To understand the market-based mechanisms, we focus on proposing some novel models and mechanisms to enhance the use of combinatorial auction for TL transportation procurement. In this dissertation, our approach to gaining the understanding consists of three parts: 1. We develop a carrier optimal bid generation model for carriers (bidders) to discover the best sets of lanes to bid for at a given round. The optimal bid generation model simultaneously generates alternative tours and selects the most profitable package bid for the carrier under a myopic strategy, which has never been considered before. The simultaneous tour generation and selection significantly lessen the computational complexities of a carrier's optimization problem since it is unnecessary for the carrier to calculate the values for all possible packages. 2. We present an iterative combinatorial auction design that integrates the optimization problems for both the shipper and the bidders where the approximate dual prices derived from the result of a winner determination solution are used by the bidders in identifying profitable lanes. The auctions also allow the bidders to submit exclusive-OR (XOR) bids and are able to deal with some common business considerations. The extension of the concept of active bids enables this mechanism to effectively mitigate the exposure problem, the threshold problem, and the free-riding problem. Furthermore, both the shippers and the carriers are better off compared to multi-round auctions that do not integrate the shippers' and carriers' optimizations. 3. We extend a deterministic winner determination model to a two-stage stochastic winner determination model for TL transportation procurement under shipment volume uncertainty. We demonstrate that the value of the stochastic solution is always at least as good as one obtained by a deterministic model based on using expected shipment volumes. The sWDP model is to the best of our knowledge the first winner determination formulation of any kind that explicitly incorporates demand uncertainty.
Age Differences in Recollection: The Roles of Support and Demand
Keywords: human memory
aging
controlled processes
context

Six experiments were conducted to examine the factors modulating the size of age differences in recollection. The research presented in the current thesis was guided by the notions of self-initiated processing and environmental support. Older and younger adults’ performance in recollection was measured by Jacoby’s (1990) process dissociation procedure (PDP); the age differences as a function of self-initiated processing demands of the task and the amount of support provided to the participants were assessed by manipulating the encoding (Experiments 2.1, 2.2, and 2.3) and retrieval (Experiments 3.1, 3.2, and 3.3) contexts. Experiments 2.1, 2.2, and 2.3 examined interactions of aging and encoding contexts. Recollection under baseline conditions (i.e. visually presented words) was contrasted with recollection of items encoded under contexts that are assumed to enhance memory. The results showed differential age-related patterns of benefits from encoding conditions: Presenting pictures with words benefited older adults more than younger adults; word generation benefited both groups equally; and presenting sound effects with visual words benefited younger more than older adults. Experiments 3.1, 3.2, and 3.3 investigated age-related changes in retrieval processes and their interactions with retrieval contexts. In each of the three experiments, some of the test lists were constructed so that participants had to recollect specific aspects of the encoding event to differentiate between the to-be-included and to-be-excluded items, whereas other test lists were constructed so that they only had to recollect general aspects. Older adults showed reduced levels of recollection than younger adults for the high-specificity test lists only (Experiment 3.1). Encoding manipulations improved (Experiment 3.2) or reduced (Experiment 3.3) recollection performance but the effects did not interact with test, whereas DA at retrieval (Experiment 3.3) in younger adults partly mimicked aging. In summary, the six experiments showed that older adults have greater difficulties in spontaneously carrying out distinctive and integrative processes at encoding, and in accessing specific information at retrieval compared to their younger counterparts. These age-related changes further interact with the processing demanded or afforded by the encoding and retrieval conditions.
Identification of Host and Parasite Factors Mediating the Pathogenesis of Severe and Cerebral Malaria
Keywords: cerebral malaria
microarray
plasmodium falciparum
plasmodium berghei ANKA
severe malaria
acute lung injury

Severe manifestations of malaria, including cerebral malaria (CM) and respiratory distress, result in approximately three million deaths annually worldwide. Currently, relatively little is known about severe disease pathogenesis. The development and outcome of severe malaria is determined by host-pathogen interactions, a complex interface of genetics and immune responses. Hypothetically, a spectrum of genetic susceptibility and resistance to severe disease exists within the host population, and malaria infection results in diverse host and parasite responses that impact disease outcome. The aim of this study was to identify differential host and parasite responses in a murine model of severe malaria, Plasmodium berghei ANKA (PbA), in CM-susceptible and CM-resistant mice; and to analyze host genetics in patients with severe disease due to Plasmodium falciparum. In vivo, expression microarray analysis showed that, in malaria target organs, differential responses were related to immune response – primarily interferon and complement pathways – and apoptosis. Histopathological examination of the brain confirmed an increased prevalence of apoptosis in CM-susceptible mice. Further examination of the role of complement in CM-susceptibility determined that early complement 5 (C5) activation conferred susceptibility to CM, and that C5 deficiency conferred resistance, which could be recapitulated by antibody blockade of activated C5 or its receptor in susceptible mice. Additionally, single nucleotide polymorphism (SNP) studies identified that complement receptor 1 SNPs were associated with disease severity in patients with P. falciparum malaria. PbA parasites displayed a unique transcriptional signature in each tissue examined (brain, liver, spleen and lung), showed differential gene expression between CM-resistant and susceptible hosts, and were most prominent in lung tissue. Closer examination of lung involvement in PbA infection revealed that PbA-infected C57BL/6 mice develop acute lung injury (ALI), defined by disruption of the alveolar-capillary membrane barrier. ALI susceptibility did not correlate with CM susceptibility, but was influenced by peripheral parasite burden and CD36-mediated parasite sequestration in the lung. PbA provides a clinically relevant experimental model for CM and ALI, through which important disease mechanisms can be identified and modulated. Ideally, the use of such models aids in the discovery of disease biomarkers and novel therapeutic strategies, which may be applied to human severe and cerebral malaria.