VictorJuiz/thesis huggingface dataset:
Comprehensive Head Motion Correction For Functional Magnetic Resonance Imaging

Head motion artifacts are major confounds that limit use of functional magnetic resonance imaging (fMRI) in neuroscience research and clinical settings. Prospective motion correction is a promising candidate solution for head motion in fMRI that ideally allows the image plane to remain fixed with respect to the moving head (i.e., in the moving reference frame). Prospective motion correction has been shown to correct successfully for rigid body movement artifacts, but residual geometric distortion due to dynamic magnetic field nonuniformities and dynamic changes in receiver coil sensitivity profiles in the moving reference frame still remain a problem. This thesis focuses on three objectives. First, I investigated and corrected for the influence of respiratory effects on the performance of dynamic geometric correction using Phase Labeling for Additional Coordinate Encoding (PLACE). It was demonstrated that PLACE combined with the dynamic off-resonance in k-space (DORK) method, and temporal averaging substantially improved fMRI data quality in comparison to the results obtained by standard processing and static geometric distortion correction. Second, I verified that appreciable signal artifacts occur due to coil sensitivity changes in fMRI maps in presence of overt head motion with prospective motion correction using Prospective Acquisition CorrEction (PACE) technique [1]. Sensitivity map compensations were shown to suppress these artifacts and provide improved fMRI results Third, I studied signal artifacts resulted from the head motion between the coil sensitivity map measurement (i.e., the calibration step) and data acquisition for fMRI with parallel-imaging reconstruction methods using two parallel imaging schemes: sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA) with acceleration factors 2 and 4. Coil sensitivity map compensations were shown to improve fMRI results obtained with PACE in the presence of overt head motion compared to those obtained with no overt head motion. Overall, prospective motion correction, integrated dynamic geometric distortion correction, and coil sensitivity map correction present an appealing compound approach for suppressing rigid and non-rigid motion artifacts during fMRI. This thesis has developed robust and comprehensive head motion correction strategies that ultimately will expand the patient populations for which fMRI can be performed robustly

Advisor: Graham, Simon J
Statistical Methods for Marker Discovery and Disease Risk Prediction Amid Unobserved Genetic Interactions

Many human traits, including Mendelian disorders, are now recognized to have complex genetic architecture, and demand innovative statistical approaches to identify the contributing genetic factors. Genetic interaction effects are widely believed to play an important role in the pathophysiology of such complex traits; however, many of these interactions remain undiscovered due to a lack of knowledge or collection of the relevant exposures, or feasibility in examining enormous numbers of interaction combinations. In this thesis, I explore two important consequences to statistical analysis amid unobserved genetic interactions. (1) Artificially induced variance heterogeneity across genotype groups for quantitative traits and (2) increased prediction bias at the extremes of risk for survival models. For both cases, I develop statistical methodology to address the corresponding limitations. For (1), I propose a joint location-scale testing (JLS) framework that simultaneously tests the null hypothesis of equal mean and equal variance between genotype groups, by aggregating association evidence from the individual location-only and scale-only tests, focusing on Fishers method of combining information (JLS-Fisher). I also extend Levene's test for variance heterogeneity and the JLS framework to analyze more complex data structures involving genotype/group uncertainty and dependent observations. For (2), I propose a new calibration test for Cox models that leverages additional power from biased risk estimates at the tails of risk distribution. The test aggregates martingale residuals for subjects from extreme high and low risk groups with a test statistic maximum chosen by varying which risk groups are included in the extremes. The methods developed in this thesis are evaluated alongside existing approaches through simulation studies. Data sets involving patients with cystic fibrosis and patients with type 1 diabetes are used to demonstrate that additional power can be gained from methods that account for potential missing interactions over conventional methods.

Keywords: Calibration
Cystic Fibrosis
Genetic Interaction
Joint Location and Scale
Levene's Test
Statistical Genetics
Advisor: Sun, Lei
Strug, Lisa J
Acting Out(side) the Canadian Multicultural "Script" in Toronto's Ethno-cultural Festivals

This thesis articulates the promising disruptions of the Canadian multicultural “script” that a Brechtian dramaturgy of ethno-cultural festivals critically practices, and also draws attention to the fissures in scholarship and in the official record through which these festivals often tumble into either obscurity or reductive characterisations. Within the framework of performance studies, this thesis adapts Bertolt Brecht’s dramaturgical approach to interrogate the ways in which Toronto’s largest ethno-cultural festivals—in particular, Toronto Caribbean Carnival Festival (1967-present), Toronto International Festival Caravan (1969-2002/2003), and the Taste of the Danforth (1994-present)—produce, perform, and negotiate the plurality of contrasting and contested meanings of the Canadian multicultural “script.” Enshrining the values of multiculturalism as part of the performance of Canadian identity, this “script” was developed in stages by the Canadian Government after the Second World War, and was institutionalised in the Charter of Rights and Freedoms (1982) and the Canadian Multiculturalism Act (1988). I employ Brecht’s Verfremdungseffekt, gestus, and historicisation to denaturalise and make visible the often unnoticed discourses of power, that shape the presentation of ethno-cultural identities at festivals, for further examination and questioning. In doing so, I illustrate that the ways in which they operate are not just fixed within understandings of the official multicultural “script,” but rather can, and do, change over time. Organised around three meditations of performativity, this thesis examines how material objects like food, physical and metaphoric spaces, and performing bodies at festivals create, perform, and present multicultural identities that play into normative understandings of the multicultural “script” as well as opening the possibility of their resistance through performance. In addition to the existing critiques of commoditisation at ethno-cultural festivals, my work on the performativity of food opens up a dialogue about the other ways that the multicultural “script” contributes to the management of diversity in the nation. Foregrounding the discursive practices of space at ethno-cultural festivals, my study illustrates the ways in which access to, or displacement or exclusion from, space is a performance of power. The performing body in ethno-cultural festivals has counter-hegemonic potential that can interfere and disrupt the safe representation and consumption of the multicultural “script” that discursively reinforce unequal power relations.

Keywords: Dramaturgy
Ethno-cultural Festival
Multiculturalism
Performance
Performativity
Toronto
Advisor: Budde, Antje
Convergence and Efficiency of Adaptive MCMC

Adaptive Markov Chain Monte Carlo (MCMC) algorithms attempt to ‘learn’ from the results of past iterations so the Markov chain can converge quicker. Unfortunately, adaptive MCMC algorithms are no longer Markovian, so their convergence is difficult to guarantee. The first part of this thesis approaches the problem via finite adaption. We develop new diagnostics to determine whether the adaption is still improving the convergence. We present an algorithm which automatically stops adapting once it determines further adaption will not increase the convergence speed. Our algorithm allows the computer to tune a ‘good’ Markov chain through multiple phases of adaption, and then run conventional non-adaptive MCMC. In this way, the efficiency gains of adaptive MCMC can be obtained while still ensuring convergence to the target distribution. The second part of the thesis proves convergence to stationarity of adaptive MCMC algorithms, assuming only simple easily-verifiable upper and lower bounds on transition densities. In particular, the transition and proposal densities are not required to be continuous, thus improving on the previous ergodicity results of Craiu et al. (2015). The third part of the thesis develops an adaptive algorithm which can locally adjust to an irregularly-shaped target distribution. When the target distribution of a Markov chain is irregularly shaped, a ‘good’ proposal distribution for one part of the state space might be a ‘poor’ one for another part of the state space. We consider a component-wise multiple-try Metropolis (CMTM) algorithm that can automatically choose a better proposal out of a set of proposals from different distributions. The computational efficiency is increased using an adaption rule for the CMTM algorithm that dynamically builds a better set of proposal distributions as the Markov chain runs. We also demonstrated theoretically the ergodicity of the adaptive chain.

Advisor: Rosenthal, Jeffrey S
Craiu, Radu V
Exploiting Linguistic Knowledge in Lexical and Compositional Semantic Models

A fundamental principle in distributional semantic models is to use similarity in linguistic environment as a proxy for similarity in meaning. Known as the distributional hypothesis, the principle has been successfully applied to many areas in natural language processing. As a proxy, however, it also suffers from critical limitations and exceptions, many of which are the result of the overly simplistic definitions of the linguistic environment. In this thesis, I hypothesize that the quality of distributional models can be improved by carefully incorporating linguistic knowledge into the definition of linguistic environment. The hypothesis is validated in the context of three closely related semantic relations, namely near-synonymy, lexical similarity, and polysemy. On the lexical level, the definition of linguistic environment is examined under three different distributional frameworks including lexical co-occurrence, syntactic and lexicographic dependency, and taxonomic structures. Firstly, combining kernel methods and lexical level co-occurrence with matrix factorization is shown to be highly effective in capturing the fine-grained nuances among near-synonyms. Secondly, syntactic and lexicographic information is shown to result in notable improvement in lexical embedding learning when evaluated in lexical similarity benchmarks. Thirdly, for taxonomy-based measures of lexical similarity, the intuitions for using structural features such as depth and density are examined and challenged, and the refined definitions are shown to improve correlation between the features and human judgements of similarity as well as performances of similarity measures using these features. On the compositional level, distributional models of multi-word contexts are also shown to benefit from incorporating syntactic and lexicographic knowledge. Analytically, the use of syntactic teacher-forcing is motivated by derivations of full gradients in long short-term memory units in recurrent neural networks. Empirically, syntactic knowledge helps achieve statistically significant improvement in language modelling and state-of-the-art accuracy in near-synonym lexical choice. Finally, a compositional similarity function is developed to measure the similarity between two sets of random events. Application in polysemy with lexicographic knowledge produces state-of-the-art performance in unsupervised word sense disambiguation.

Keywords: Artificial Intelligence
Compositional Semantics
Computational Linguistics
Distributional Semantics
Lexical Semantics
Advisor: Hirst, Graeme
An Ecogeographic Study of Body Proportion Development in the Sadlermiut Inuit of Southampton Island, Nunavut

This thesis explores growth status and body proportion development in past North American Arctic populations. Living in one of the most extreme environments on the planet, Arctic foragers provide an opportunity to explore how human morphological variation is shaped by growth and climate. The study focuses on the Sadlermiut Inuit, who lived on Southampton Island in Hudson Bay, Nunavut. This main sample is comprised of 111 juveniles and 160 adults (62 F, 52 M, 46 und). Comparative samples are derived from Northwest Hudson Bay, Point Hope (Alaska), and Greenland, and are comprised of 106 juveniles and 151 adults (76 F, 75 M). Growth status in four long bones is assessed by comparing the samples' tempo of growth to normative values from a modern North American sample. Body proportion development is assessed by calculating brachial index, crural index, and limb length relative to skeletal trunk height. Plots of index values versus dental age are assessed visually, and compared to results from the literature. Sadlermiut individuals who died as juveniles show a predominant pattern of growth faltering as compared to the North American tempo of growth. Most Sadlermiut juveniles who died in infancy either began life lagging in proportional growth, or fell behind quickly after birth. Most Sadlermiut juveniles who died later in childhood/adolescence had continued to falter in growth, indicating either insufficient, or a lack of, catch-up growth. This contrasts with Point Hope, which showed a broad range of growth outcomes: individuals with growth in line with the North American tempo, as well as individuals with lagging and accelerated growth. The analysis of body proportion development demonstrates that Sadlermiut infants exhibit a wide range of index values, and adult-type body proportions appear by early- to mid-childhood. Adult proportionality is achieved by most older Sadlermiut juveniles, despite a lag in linear growth. This demonstrates that linear growth is more environmentally labile, while body shape is more conserved. Moreover, the timing of body proportion development is consistent across samples from this study and the literature, suggesting a consistent pattern of growth with regard to body proportionality, regardless of latitude/climate and ultimate adult proportionality.

Keywords: body proportions
ecogeography
growth
Inuit
Advisor: Pfeiffer, Susan
A Comprehensive Piezoelectric Bending-Beam Model Inspired by Microaerial Vehicle Applications

Microaerial vehicles are an up-and-coming area of robotics which is fuelled by modern understanding of the unsteady aerodynamics of insect flight and the development of new actuation technologies. In the past two decades computer simulations have aided in uncovering the lift mechanisms which flying insects use to stay aloft. Using these details, roboticists had begun using lightweight structures and high power density actuators to mimic the physical parameters and flapping kinematics of flying insects with the intent to recreate the dynamics of insect flight. One of the most important aspects of flapping-wing microaerial vehicles is the actuation method. Piezoelectric bending-beam actuators have been scaled up from MEMS technology for use in microaerial vehicle applications owing to their high power density and performance at low mass. The initial development toward the UTIAS Robotic Dragonfly, a microaerial vehicle platform using a piezoelectric-based actuator, is outlined. The components are fabricated from lightweight materials such as a carbon fibre frame, polymide film joints, and polyester film wings while the actuator is a piezoelectric bending-beam which was designed using existing mathematical models. The design and fabrication of the wings, actuator, transmission, and power supply are detailed. The prototypes are measured for lift generation using custom lift sensors which had undergone static and dynamic calibration for low-force, high-bandwidth measurement. Although the resulting lift curves qualitatively correspond with the literature, it was determined that more power was needed for lift-off to be achieved and existing piezoelectric models do not fully account for maximizing the force-deflection relationship. An extension to the existing Ballas model of piezoelectric bending-beam devices is derived. This modified Ballas model incorporates devices beyond constant width. Actuator performance limitations highlighted the need for a more comprehensive piezoelectric bending-beam model. The final contribution is a derivation of a new bending-beam model to permit multiple layers, any continuous width profile, and independent layer excitation. An energy-based approach using the extended Hamilton's principle was used to incorporate the generalities desired in the new piezoelectric bending-beam model. Examples of the new model are compared to both simulation and experiment for verification as well as to showcase its versatility.

Keywords: Actuators
Dragonfly
Flapping Wing
Microaerial Vehicles
Piezoelectric
Sensors
Advisor: D'Eleuterio, Gabriele M.T.
Attention and Inhibitory Control in Children with Traumatic Brain Injury: Outcomes and Prediction Using Biomarkers

Children with traumatic brain injury (TBI) have a range of cognitive problems, notably in the domain of executive functioning and attention. Previous studies have attempted to relate performance on measures of executive function and attention in groups of children with TBI to pre-injury variables and measures of TBI severity, to predict outcome, but clear relations have not emerged. This is likely due to variability in both patient and injury characteristics. Prior studies also have not found consistent results as to why these cognitive difficulties are so frequently seen as sequelae to TBI in children. This thesis evaluated a variety of patient variables, along with serum biomarkers (proposed objective measures of brain injury), as predictors of long-term (one to six years) attention and executive function outcome in children following TBI. A secondary aim of this thesis was to investigate performance monitoring through the use of the stop signal task (SST) in children following TBI compared to age-matched controls. Significant relations were found between serum biomarkers (such as neuron specific enolase [NSE] and soluble neuron cell adhesion molecule [sNCAM]), pre-injury functioning, and persistent attention and executive function difficulties at long-term follow-up time points. Other standard clinical measures (Glasgow Coma Scale, age) were not reliable predictors. During performance monitoring, children with TBI did not show the expected slowing in reaction time following an error on the SST that was observed in an age-matched healthy control group, but the group differences were not significant. When validated in future research studies, the findings of the predictive value of certain serum biomarkers and pre-injury measures could contribute to acute clinical and long-term rehabilitation decisions, with the expectation of improving the quality of life in survivors of paediatric TBI.

Keywords: attention
executive function
pediatric
serum biomarkers
traumatic brain injury
Advisor: Taylor, Margot J
Compact Object Binaries With Spinning Neutron Stars In Numerical Relativity

The inspiral and merger of binary neutron stars (BNS) is one of the most promising potential sources of gravitational waves for ground-based detectors like Advanced LIGO. BNS mergers are also likely a source of counterpart electromagnetic radiation. It is important to perform simulations of BNS to better understand and model their gravitational wave emission as well as their electromagnetic emission. The parameter space of BNS binaries is quite large, and one aspect that has not been well studied in neutron star spin. In this thesis, we focus on investigating spinning neutron stars in compact object binaries. Using the SpEC code, developed by the SXS collaboration, we begin by presenting a new code to create initial data for binary neutron stars with arbitrary spins. We introduce a novel method of measuring neutron star spin, and show that it is accurate and robust. We evolve several spinning binary configurations and show that their properties agree remarkably well with Post-Newtonian predictions. We also show that we are able to control the eccentricity of the binaries to ~0.1%. Thereafter, we proceed to extend our code to black hole--neutron star (BHNS) binaries. We create many data sets across the BHNS parameter space, varying neutron star spin magnitude, spin direction, compactness, and black hole mass, spin and spin direction. We are able to create initial data sets with neutron star spins near the mass-shedding limit, and nearly extremal black hole spins. Finally, we investigate spurious gravitational radiation in binary black hole systems. We study its parameter space dependence, by introducing three diagnostics, investigating them as a function of black hole spin and black hole separation, and comparing two different methods of constructing initial data.

Keywords: Black Holes
Gravitation
Gravitational Waves
Neutron Stars
Numerical Relativity
Simulation
Advisor: Pfeiffer, Harald P
Exploring the Role of Inflammatory Cytokines in the Pathophysiology, Cognitive Dysfunction and Treatment of Bipolar Disorder: Integrative Evidence Provided by a Proof-of-Concept Study with Adjunctive Minocycline

Background: Bipolar disorder (BD) is associated with increased levels of inflammatory cytokines, which may contribute to cognitive dysfunction. Anti-inflammatory intervention with minocycline is hypothesized to exert antidepressant and pro-cognitive effects in BD. The aims of the investigations were: 1) to identify inflammatory cytokine abnormalities in BD; 2) to identify inflammatory cytokines associated with cognitive dysfunction in BD; 3) to evaluate the efficacy of adjunctive minocycline for symptoms of bipolar depression and cognitive dysfunction. Method: The first two study aims were evaluated with cross-sectional exploratory methods, comparing 29 depressed (HAMD-17 ≥ 20) and 46 euthymic (4 week verification) adults with DSM-IV-TR-defined BD as well as of 31 healthy controls (HCs). Plasma cytokine levels were measured with a 30 V-PLEX immunoassay. Evaluated cognitive domains were verbal memory, executive function and psychomotor speed. The efficacy of adjunctive minocycline (100 mg b.i.d.) was evaluated in an overlapping sample of depressed individuals (intent-to-treat: n=27) using an 8-week, open-label study. The primary efficacy measure was the MADRS, while, cognitive composites and plasma cytokines were secondary outcome measures. Results: Results from multinomial logistic regression analyses indicate that IL-6 levels were increased in depressed and euthymic individuals with BD when compared to HCs, while, levels of CCL3, IL-15, and IL-17A were reduced below levels of HCs in euthymic individuals (Pseudo R2=.648, p

Keywords: bipolar disorder
cognition
Cytokines
Inflammation
minocycline
mood disorders
Advisor: Kennedy, Sidney K
McIntyre, Roger S