VictorJuiz/thesis huggingface dataset:
The Role of Form-focused Instruction: Learner Investment in L2 Communication
Keywords: Instruction
Investment
Form-Focused Instruction
Discursive Practice
Language Socialization
Second Language Learning
Communication
Grammar
EFL in Japan
Identity

The purpose of this study is to examine the role of form-focused instruction in relation to learner investment in second language (L2) communication and learning. Although positive effects of form-focused instruction have been reported in the instructed second language acquisition literature, most of this research has been conducted from a cognitive-interactionist perspective. Little attention has been paid to the social and cultural factors of form-focused instruction, including learner investment— a desire to learn a second/foreign language taking into consideration learners’ socially constructed identities (Norton-Peirce, 1995). Drawing on second language socialization theory (Duff, 2007) and using discursive practices (Young, 2009) as an analytic framework, this study examines how form-focused instruction influences learner investment in L2 communication in the classroom setting. Twenty-four high school students in Japan participated in a study, where two Japanese teachers of English team-taught four 50-minute lessons. Each lesson contained a 30-minute treatment period, which consisted of a 15-minute exclusively meaning-focused (MF) activity and a 15-minute form-focused (FF) activity that included attention to both form and meaning. By counter-balancing effects of tasks, target grammar features, and teachers, the study examined whether and how the same learners invested in L2 communication in similar or different ways during the two different types of activities. Data were collected through classroom observations, video-recorded classroom interactions, stimulated recalls, interviews, questionnaires, and diaries. The interactional data were analyzed quantitatively by comparing the frequency of turns and language-related episodes during FF and MF activities. The same interactional data were also analyzed qualitatively in relation to discursive practices and self-reported data. The results showed that the FF activities created contexts for learners to establish their identities as L2 learners leading to more engagement in L2 communication than in the MF activities. This suggests that FF activities create a social context that enables learners to communicate in the L2 with greater investment than in MF activities.
Sequence Determinants of In Vivo and Intrinsic Nucleosome Occupancy
Keywords: nucleosomes
chromatin
gene regulation
transcription
transcription factors
genomics
computational biology

The genomes of all eukaryotic organisms are packaged into chromatin, the fundamental unit of which is the nucleosome. Since the proposal of the nucleosome as the primary repeating unit of chromatin structure in 1974, it has become clear that the biological roles of nucleosomes extend far beyond simple DNA packaging and include virtually all processes involving the genome. Despite the integral roles of nucleosomes in many fundamental biological processes, the relative contributions of the cellular cues and sequence features that directly govern their arrangement on genomic DNA remain unclear. In this Thesis, I characterise the sequence preferences of nucleosomes using data sets derived from genome-wide studies. I describe the analysis of data derived from the first genome-wide map of in vivo nucleosome occupancy across a eukaryotic genome (in this case, the budding yeast, Saccharomyces cerevisiae). Using these data, I construct a sequence-based linear model of nucleosome occupancy that takes into account structural features of DNA (which correlate with simple base composition) as well as transcription factor (TF) binding site information, which has significant ability to predict nucleosome occupancy in vivo. I go on to test particular aspects of this model and show that genetic perturbation of TFs that the in vivo model deems important (Abf1, Reb1, and Rsc3) have the expected effects, an increase in nucleosome occupancy over their cognate binding sites as well as a reduction in transcription from the corresponding genes, suggesting that these factors are required for promoter function and definition. I also confirm that in vitro nucleosome occupancy correlates highly with sequence features important for nucleosome occupancy in vivo and go on to develop a simple model for nucleosome occupancy based solely on histone-DNA interactions. This model suggests that base composition (G+C content) is a dominant feature in determining intrinsic nucleosome occupancy. Finally, I apply a model of intrinsic nucleosome occupancy to the human genome and show that there is a fundamental difference in intrinsic nucleosome occupancy at regulatory regions across species. This finding illustrates a potential functional consequence of variation in base composition in eukaryotic genomes.
Statistical Methods for Dating Collections of Historical Documents
Keywords: Kernel
Dating Documents
Shingle
Correspondence distance
Smoothing
Generalized linear models
Logistics regression
Local polynomial regression

The problem in this thesis was originally motivated by problems presented with documents of Early England Data Set (DEEDS). The central problem with these medieval documents is the lack of methods to assign accurate dates to those documents which bear no date. With the problems of the DEEDS documents in mind, we present two methods to impute missing features of texts. In the first method, we suggest a new class of metrics for measuring distances between texts. We then show how to combine the distances between the texts using statistical smoothing. This method can be adapted to settings where the features of the texts are ordered or unordered categoricals (as in the case of, for example, authorship assignment problems). In the second method, we estimate the probability of occurrences of words in texts using nonparametric regression techniques of local polynomial fitting with kernel weight to generalized linear models. We combine the estimated probability of occurrences of words of a text to estimate the probability of occurrence of a text as a function of its feature -- the feature in this case being the date in which the text is written. The application and results of our methods to the DEEDS documents are presented.
Researching Class Consciousness: The Transgression of a Radical Educator Across Three Continents
Keywords: radical education
working class consciousness
formative experience
revolutionary critical pedagogy
popular education
popular theatre
sociological auto/biography
critical human rights
arts based education
Ghana
Scotland
collective self
ontology/epistemology
anti-racism
critical consciousness
oral history
gender and class
communist/socialist parties
auto-ethnography
ideology of educator
mining communities and unionism
organic intellectuals

This study addresses the topic of class consciousness and the radical educator. Using the theory of revolutionary critical pedagogy and Marxist humanism I examine the impact of formative experience and class consciousness on my own radical praxis across three continents. The methodology of auto/biography is used to interrogate my own life history. I excavate my own formative experience in Scotland, Canada and my radical praxis as a human rights educator in Ghana West Africa. The study is particularly interested in the possibility of a radical educator transgressing across race, whiteness and gender while working in Ghana, West Africa. Chapter One begins by discussing the theory of revolutionary critical pedagogy, Marxist humanism and theories of the self. Chapter Two assesses the methodology of auto/biography,research methods and an introduction to formative experience. Chapter Three, Four and Five contain excavation sites from Scotland, Canada and Ghana with accompanying analysis. Chapter Six concludes with a summary of research findings.
Applications of Lexicographic Breadth-first Search to Modular Decomposition, Split Decomposition, and Circle Graphs
Keywords: Modular Decomposition
Split Decomposition
Circle Graphs
Lexicographic Breadth-First Search
LBFS
LexBFS
Charging argument
Amortized analysis
Aggregate analysis
Recognition
Graph Labelled Trees
GLT

This thesis presents the first sub-quadratic circle graph recognition algorithm, and develops improved algorithms for two important hierarchical decomposition schemes: modular decomposition and split decomposition. The modular decomposition algorithm results from unifying two different approaches previously employed to solve the problem: divide-and-conquer and factorizing permutations. It runs in linear-time, and is straightforward in its understanding, correctness, and implementation. It merely requires a collection of trees and simple traversals of these trees. The split-decomposition algorithm is similar in being straightforward in its understanding and correctness. An efficient implementation of the algorithm is described that uses the union-find data-structure. A novel charging argument is used to prove the running-time. The algorithm is the first to use the recent reformulation of split decomposition in terms of graph-labelled trees. This facilitates its extension to circle graph recognition. In particular, it allows us to efficiently apply a new lexicographic breadth-first search characterization of circle graphs developed in the thesis. Lexicographic breadth-first search is additionally responsible for the efficiency of the split decomposition algorithm, and contributes to the simplicity of the modular decomposition algorithm.
The Role of Teneurin C-terminal Associated Peptide (TCAP)-1 in the Regulation of Stress-related Behaviours
Keywords: Neuroscience
Behaviour
Endocrinology

The teneurin C-terminal associated peptides (TCAPs) are a newly-elucidated family of four bioactive peptides that were found during a screen for novel corticotropin-releasing factor (CRF)-like peptide families. The predicted peptide sequences have the characteristics of a bioactive peptide and are 40 or 41 amino acid residues long. One of the peptides in the family, TCAP-1, has numerous in vitro effects, where it modulates cAMP accumulation, neuronal proliferation, neurite outgrowth, brain-derived neurotrophic factor levels, and possesses neuroprotective effects under alkalotic or hypoxic conditions. However, little is known about TCAP-1’s in vivo effects. Given the structural similarity of TCAP-1 to the CRF family, it is expected that these peptide systems may interact in vivo. The aims of this research were to 1) investigate the role of TCAP-1 on CRF- and stress-induced behaviours in rats, and determine if intracerebral TCAP-1 could modulate stress-induced anxiety-like behaviours; 2) determine the areas of the brain where TCAP-1 is taken up and is active; and 3) investigate the role of TCAP-1’s cytoskeletal modulation on stress-sensitive areas of the brain so as to determine a mechanism for long-term behavioural changes in the brain. I have established that TCAP-1 modulates anxiety-like behaviour in exploratory tests of anxiety, and that TCAP-1 is particularly active in the limbic system, including the hippocampus, amygdala, septum, and medial prefrontal cortex, and that TCAP-1 increases the dendritic spine density in the hippocampus, a brain area important for anxiety, learning, and memory. These studies have confirmed that TCAP-1 indeed plays a role in stress-like behaviours and modulates stress-related processes in the brain.
Reliability and Maintenance of Medical Devices
Keywords: Reliability
Maintenance
Medical Devices
Periodic Inspection
Opportunistic Inspection
Prioritization
Trend Analysis

For decades, reliability engineering techniques have been successfully applied in many industries to improve the performance of equipment maintenance management. Numerous inspection and optimization models are developed and widely used to achieve maintenance excellence, i.e. the balance of performance, risk, resources and cost to reach to an optimal solution. However, the application of all these techniques and models to medical devices is new. Hospitals, due to possessing a large number of difference devices, can benefit significantly if the optimization techniques are used properly in the equipment management processes. Most research in the area of reliability engineering for medical equipment mainly considers the devices in their design or manufacturing stage and suggests some techniques to improve the reliability. To this point, best maintenance strategies for medical equipment in their operating context have not been considered. We aim to address this gap and propose methods to improve current maintenance strategies in the healthcare industry. More specifically, we first identify or propose the criteria which are important to assess the criticality of medical devices, and propose a model for the prioritization of medical equipment for maintenance decisions. The model is a novel application of multi-criteria decision making methodology to prioritize medical devices in a hospital according to their criticality. The devices with high level of criticality should be included in the hospital’s maintenance management program. Then, we propose a method to statistically analyze maintenance data for complex medical devices with censoring and missing information. We present a classification of failure types and establish policies for analyzing data at different levels of the device. Moreover, a new method for trend analysis of censored failure data is proposed. A novel feature of this work is that it considers dependent failure histories which are censored by inspection intervals. Trend analysis of this type of data has not been discussed in the literature. Finally, we introduce some assumptions based on the results of the analysis, and develop several new models to find the optimal inspection interval for a system subject to hard and soft failures. Hard failures are instantaneously revealed and fixed. Soft failures are only rectified at inspections. They do not halt the system, although they reduce its performance or productivity. The models are constructed for two main cases with the assumption of periodic inspections, and periodic and opportunistic inspections, respectively. All numerical examples and case studies presented in the dissertation are adapted from the maintenance data received from a Canadian hospital.
High Multi-vitamin Intake During Pregnancy in Wistar Rats and the Metabolic Syndrome in the Offspring
Keywords: maternal nutrition
multi-vitamin supplementation
fetal programming
obesity
hyperphagia
metabolic syndrome

Vitamins are readily available in the modern diet due to liberalized fortification and supplementation policies. This research tested the hypothesis that high multi-vitamin intake by Wistar rats during pregnancy leads to the development of obesity and characteristics of the metabolic syndrome in the offspring. Pregnant Wistar rats were fed the AIN-93G diet containing either the recommended (RV) or 10-fold increase (HV) in vitamin content. Pups were weaned to the RV diet (Study 1), an obesogenic liquid diet (Ob, Study 2), low vitamin diets (1/3RV or 1/6RV, Study 3), or a nutrient selection paradigm (NSP) with 10% and 60% casein diets (Study 4). Body weight (BW), food intake (FI), glucose and insulin responses, appetite hormones, abdominal fat pad mass (FPM) and systolic blood pressure (SBP) was measured. Expressions of mRNA for hypothalamic serotonin (5-HT) receptors and proopiomelanocortin (POMC) were measured in Study 4. Males, but not females, born to HV dams had higher post-weaning BW and FI when weaned to the RV or 1/3RV diet, and exhibited components of metabolic syndrome, including higher FPM, hyperglycemia, insulin resistance and elevated SBP compared with those born to RV dams. The Ob diet led to exaggerated weight gain and expressions of components of metabolic syndrome in both sexes born to dams fed the HV diet. Female pups on the 1/6RV diet from HV dams had two-fold higher glucose response and lower insulin response, but no difference in post-weaning BW and daily FI compared to those from RV dams. In contrast to the pups born to HV dams and fed a single diet, those from the HV dams and on the NSP gained less weight and ate less, and had lower hypothalamic mRNA expressions of 5-HT receptors and POMC. In conclusion, high multi-vitamin intake during pregnancy may lead to obesity, and result in a higher risk of developing characteristics of metabolic syndrome in the offspring. However, sex, weaning diet composition, and the presence of diet choice alter the outcomes.
Interpreting Faces with Neurally Inspired Generative Models
Keywords: facial expressions
neural network
deep belief net
restricted boltzmann machine

Becoming a face expert takes years of learning and development. Many research programs are devoted to studying face perception, particularly given its prerequisite role in social interaction, yet its fundamental neural operations are poorly understood. One reason is that there are many possible explanations for a change in facial appearance, such as lighting, expression, or identity. Despite general agreement that the brain extracts multiple layers of feature detectors arranged into hierarchies to interpret causes of sensory information, very little work has been done to develop computational models of these processes, especially for complex stimuli like faces. The studies presented in this thesis used nonlinear generative models developed within machine learning to solve several face perception problems. Applying a deep hierarchical neural network, we showed that it is possible to learn representations capable of perceiving facial actions, expressions, and identities, better than similar non-hierarchical architectures. We then demonstrated that a generative architecture can be used to interpret high-level neural activity by synthesizing images in a top-down pass. Using this approach we showed that deep layers of a network can be activated to generate faces corresponding to particular categories. To facilitate training models to learn rich and varied facial features, we introduced a new expression database with the largest number of labeled faces collected to date. We found that a model trained on these images learned to recognize expressions comparably to human observers. Next we considered models trained on pairs of images, making it possible to learn how faces change appearance to take on different expressions. Modeling higher-order associations between images allowed us to efficiently match images of the same type according to a learned pairwise similarity measure. These models performed well on several tasks, including matching expressions and identities, and demonstrated performance superior to competing models. In sum, these studies showed that neural networks that extract highly nonlinear features from images using architectures inspired by the brain can solve difficult face perception tasks with minimal guidance by human experts.
Chemical Modification of Cellulose Fibers and their Orientation in Magnetic Field
Keywords: Magnetic Cellulose
Cellulose Complex
Biofiber Orientation
Cellulose Biocomposite
Biodegradable Composite

Studies that involve natural fiber orientation in a matrix were mostly based on regulating shear forces during mixing of fiber and matrix. This study attempts to propose a novel technique for orientating natural fibers like cellulose in a viscous polymer matrix such as polylactic acid (PLA) by applying the concepts of magnetism. Orientation of cellulose fibers in a PLA was achieved by modifying the cellulose fibers with a ferromagnetic entity and subjecting to a magnetic field. Chemically modified cellulose fibers (CLF) were oriented in dilute polylactic acid by subjecting the fiber and matrix to a magnetic field of ≈ 4T (Tesla). CLF and Microcrystalline cellulose (MCC) were oxidized with Hydrogen peroxide and further reacted with activated Ferrous sulphate heptahydrate (FeSO4.7H2O) in order to form Cellulose-Fe complexes. Chemically modified CLF was characterized by spectroscopic, thermal and morphological methods. The results from X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR spectroscopy) agree that coordination bonds were formed between deprotonated and/or oxidized hydroxyl groups of cellulose and Fe2+ ions. Powder X-ray diffraction (PXRD) was used to compare the crystallinity of unmodified and modified samples of CLF. Thermal properties of modified cellulose were studied using thermogravimetric analysis (TGA) and a differential scanning calorimeter (DSC). Scanning electron microscopy (SEM) results showed that there was minimal morphological change occurred to cellulose after treatment. It was also observed that the electrical conductivity of cellulose modified with Fe 2+ was higher than that of unmodified samples. The modified CLF was then mixed with polylactic acid diluted with dichloromethane and the fibers in the matrix suspension were subjected to a magnetic field of ≈ 4T. The suspension was allowed to solvent cast inside a glass vial in the magnetic field. Morphological examination of the fiber matrix composites using confocal microscopy showed that CLF were successfully oriented along the flux direction of the magnetic field.
Membership Change: A Network Perspective
Keywords: Teams
Membership Change
Social Networks

This dissertation theorizes about why a team’s network structure might affect team performance immediately and over time when membership changes. I propose that the low substitutability of a central team member immediately disrupts the structure of interactions between remaining members and leaves the team without an important resource that is relied upon to facilitate team process. This performance loss is expected to decay as time elapses because the saliency of the event creates the focus and urgency required for the team to implement widespread systemic change. Dense interaction and task redundancy among core members in a centralized structure is expected to help offset this performance loss both immediately and over time. I examine the effect of network structure on initial team performance (performance immediately following member exit and entry) and performance over time (the rate of performance change following exit and entry) in professional hockey teams experiencing membership change due to player injury. Results show that the departure of a central player has a significant and negative effect on a team’s immediate performance, but the centrality of the absent member has a curvilinear effect on team performance over time. Teams that lost a central player experienced a drop in performance immediately after that player’s exit; but subsequently demonstrated an improvement in performance over time. Teams that lost a peripheral player experienced a more positive performance trajectory over time when compared with their performance before the exit, while the performance of teams that lost a mid-central player remains constant over time. While team centralization had no influence on initial team performance, over time it dramatically altered team outcomes such that, regardless of the departing player’s network position, teams with a centralized structure improved over time, whereas decentralized teams performed more poorly over time.