VictorJuiz/thesis huggingface dataset:
The States and Traits of EEG Variability

The States and Traits of EEG VariabilityErin Gibson Doctor of Philosophy Institute of Medical Science University of Toronto 2021 Neurons in the brain are seldom perfectly quiet. They continually receive input and generate output, resulting in noisy, highly variable patterns of ongoing activity. Yet the functional significance and behavioral consequences of this variability remains largely unknown. We hypothesize that brain signal variability is tightly coupled to the processing of task-relevant information and serves as an important indicator of cognitive function. To test this, we examine EEG activity in young, healthy adults as they perform a cognitive skill learning and resting state task. Several measures of EEG variability and signal strength are calculated at multiple timescales, or in overlapping time windows that span the trial interval. We perform a systematic examination of the factors that most strongly influence the variability and strength of EEG activity. Study 1 examines the relative sensitivity of each measure to trait-level variation across subjects and state-level variation across task blocks. We find that EEG variability is most sensitive to trait-level differences across individuals that remain relatively stable across blocks. Study 2 examines the sensitivity of each measure to different sources of state-level variation across task blocks. We find that key task-driven changes in EEG activity are better reflected in the strength, rather than the variability, of EEG activity. Study 3 examines trait-level variation in each measure and its relationship with behavior. We find that differences in learning speed and acquired skill across individuals are better reflected in relative changes in the variability, rather than the strength, of EEG activity. These results demonstrate that EEG variability is particularly sensitive to stable trait-level variation across individuals and relative changes in EEG variability around a particular level, rather than the level itself, are a strong indicator of behavioral performance in young, healthy adults.

Advisor: McIntosh, Randy
Path Following Control for Multiple Quadrotors Carrying A Rigid-body Slung Payload

Novel robust path-following flight controllers for quadrotors carrying a tethered payload are extensively studied from the perspective of dynamic modelling, control design, and experimental verification. By using multiple quadrotors to cooperatively carry a payload, their payload capacities can be significantly boosted. The number of vehicles can be adjusted according to the weight of the payload, resulting in a flexible and efficient use of drone resources. The presented model development starts from a single quadrotor with a point-mass payload to multiple quadrotors with a rigid-body payload. The payload is towed by quadrotors with cables. The systems are decomposed into the payload subsystem and the quadrotor attitude subsystem by assuming the cable is tethered at the center of mass of each quadrotor. The controller designs are then developed for a single quadrotor with a point-mass payload, followed by controller of multiple quadrotors with a rigid-body payload. Both controllers resemble a cascade form in structure. The outer loop offers a robust path-following controller that stabilizes the payload subsystem by assuming the lift vector of each quadrotor can point instantaneously to a given direction. An uncertainty and disturbance estimator is designed to estimate and eliminate the lumped disturbances caused by exogenous wind and parameter imperfection. The inner loop, on the other hand, is an attitude tracker implemented on each quadrotor to follow a reference attitude generated by the outer-loop controller. The overall stability of the complete system is proven using the Lyapunov method and the Reduction Theorem. Aside from the analytical control law, a model predictive controller (MPC) method is also studied and implemented on quadrotor for cooperative slung payload delivery. The MPC method utilizes the equivalent damping force from the previous controller as the baseline stabilizing inner loop. The linearized closed-loop model is then calculated. Finally, the optimum controller is calculated after a prediction horizon and a cost function are defined. The MPC scheme achieves better performance and requires less parameter tuning. Extensive simulations and experiments show that the controller designs are capable of stabilizing the payload under model imperfection and exogenous disturbances simultaneously.

Keywords: Multi-body dynamics
Nonlinear control
Quadrotor
Robust control
Advisor: Liu, Hugh H.T. Prof.
Therapy Roles in Family-centred Care: Negotiating Expectations between Parents and Service Providers Over Time

The ideal principles of family-centred care models underlying paediatric rehabilitation generate expectations that therapy sessions involve clients choosing their level of involvement, family members being treated with respect, and everyone having their needs considered. However, expectations are often unmet or overlooked in practice. Expectations associated with professional- or system-centred care models persist. Allowing expectations to remain implicit may create assumptions that unnecessarily constrain views about what therapy roles and responsibilities between parents and service providers are ideal. Expectations are future-oriented beliefs about what will and should happen during therapy. This dissertation explored the meaning, development, and change of parents’ and service providers’ expectations for therapy spanning their years of experience in paediatric rehabilitation. I conducted one study to analyze expectations from three perspectives. First, what meanings of expectations for therapy were expressed directly and indirectly? Second, how did power affect the negotiation process to develop expectations for therapy? Third, how and why did expectations for therapy change over time? Five parents and nine service providers took part in qualitative interviews. Data were transformed into a collection of stories using narrative analysis. I worked within the constructivism paradigm. Parents and service providers experienced expectations for therapy as a paradoxical construct with multiple contradictory meanings, including positive/negative, heavy/light, and definite/indefinite. Next, their experiences negotiating expectations for therapy were shaped through a range of in-session processes affecting the level of power differences in partnerships. Finally, their expectations changed after experiencing disillusioning events that challenged them to re-think their personal stories. This research created knowledge and tools that parents and service providers can use to make the process of talking about and adapting expectations for therapy more jointly accessible. Findings revealed how becoming aware of and responding to ‘incongruent’ expectations for therapy are essential to personalizing the ideal principles of family-centred care to individual cases. Additionally, a master narrative of ‘betrayal induced belief changes,’ a sequence of experiences involving parents and service providers replacing initially desired narratives with experienced and informed narratives, can serve as a template of expected experiences readying parents and service providers to develop informed, sustainable, and meaningful expectations for therapy.

Advisor: King, Gillian
On the Generation of Theta Rhythms in the Hippocampus

A prevalent local field potential (LFP) rhythm in the CA1 hippocampus associated with memory processing and spatial navigation is the (3-12 Hz) theta oscillation. Theta rhythms emerge intrinsically in an in vitro whole hippocampus preparation. This system makes it possible to assess the contribution of different cell types, a problem that remains unresolved, in the absence of state-dependent confounding factors typically encountered in vivo. To decipher the theta generation mechanism we leverage insights from minimal models in application to biologically detailed ones. We extract a piece of a previously published full CA1 model, the segment model, on which we test minimal model hypotheses. We distinguish the pyramidal (PYR) cells as the theta rhythm initiators whose activity is regularized by inhibitory cells supporting an ‘inhibition-based tuning’ mechanism. We find a strong correlation between the PYR cell input currents and the resulting theta frequency, establishing that the intrinsic PYR cell properties underpin frequency characteristics. We analyze contributions of external drives and find that strongest theta responses are generated by the hippocampus CA3 while weakest responses are induced by inputs from the CA1. Subsequently we turn our attention to the full CA1 model and explain the theta activities it produces according to our gathered insights. We demonstrate that the termination of PYR cell theta bursts relies on sequential activation of distinct inhibitory cell classes. Two main types of inhibitory cells have been considered particularly important for the generation of theta rhythms, the parvalbumin-positive (PV+) and the somatostatin positive (SOM+) cells. Having demonstrated the importance of PV+ cells in theta generation, we turn to the SOM+ oriens lacunosum-moleculare (OLM) cells, a heavily studied cell class whose role is still unclear. We find that OLM cells regulate the robustness of the LFP laminar polarity profile without affecting average power, a robust response that depends on co-activation of distal inhibition and basal excitation. Finally, we estimate the spatial extent of the theta LFP, and predict that about 22,000 PYR cells participate in intrinsic theta generation. The work presented in this thesis provides a cellular-based foundation from which in vivo theta activities can be explored.

Keywords: biophysical modelling
computational neuroscience
hippocampus
inhibitory classes
local field potentials
theta rhythms
Advisor: Skinner, Frances K
The Essential Internet: Locating Internet Contingent Practices Activities at the Toronto Community Housing Corporation

This doctoral dissertation examines household internet use amongst residents of the Toronto Community Housing Corporation (TCHC), North America’s second largest social housing undertaking, comprised of 60,000 residential units that provide housing for more than 100,000 low-income individuals. Primary data was collected from rent-geared-to-income residents at three facilities characterized by elderly, single, and family occupancy. The research methodology utilizes a Social Systems Theory framework which situates household internet service as a technical resource employed by residents in the course of their basic needs undertakings. Five basic needs activity areas were investigated in order to ascertain the extent to which internet services facilitate and support household routines: education, health, childcare, nutrition, and finances. The results of the study suggest that household internet services can elevate the productivity of residents by multiplying the volume of tasks they are able to perform, and with greater efficiencies across interconnected basic needs activity areas. As internet use becomes normalized within the household, basic needs activities and routines that are arranged around household internet services can become contingent on access to the technology, and are consequently at risk of being destabilized during periods of long-term internet service disruption. This precarity is heightened by the experience of fixed and limited income resources liminal to the poverty threshold in TCHC households. The data collected in this study suggests that traditional policy approaches to remediating digital exclusion, such as retail market incentives and investment in community intermediaries, are insufficient to support the internet needs of the TCHC households who participated in the study. First, income to expense ratios in family households further tension the affordability constraints associated with maintaining their retail internet services. Second, the temporary access facilitated by community intermediaries, such as public schools and public libraries, is insufficient in supporting household routines which have been patterned on household internet services, and should not be situated as proxies for fixed at-home internet services. The results of this study broaden the scope of scholarship concerned with issues of digital exclusion, as well as public policy interested in ameliorating digital divides and fostering digital inclusion.

Keywords: Community informatics
Internet policy
Social technology studies
Technology inclusion
Telecommunications policy
Universal broadband
Advisor: Shade, Leslie
Instructor’s Emotional Responses during Online Asynchronous Teaching

Online instruction is becoming a more dominant method of instruction; over 69% of higher education institutions now say that online learning is a critical part of their long-term strategy (Allen and Seaman, 2017). The expansion of online education can create multiple challenges for educators due to a lack of resources, time, training, and experience. Faculty are faced with learning curves around course content and delivery while simultaneously adapting to new technologies (Keengwe Kidd, 2010; Rehfuss, Kirk-Jenkins, Milliken, 2015). Therefore, online instructors' emotions are of central importance, as the well-being and general demeanour of instructors, even behind the computer, can impact their relationships with their students. Students and instructors in online learning should develop a reciprocal relationship where both understand and communicate effectively to prevent negative emotions, such as frustration and contempt. However, little is known about instructor emotional experiences in online learning, and most studies on teacher and instructor emotions are done through self-report. Survey results showed a high level of well-being and positive emotions across all instructors. Open-ended responses on the emotional profile were coded into four themes, technical and organizational, communication, instructor experiences and attention and engagement. Instructors expressed that their online learning emotions were largely dependent on student attention and engagement, with achievement specifically being the prime influence in their emotions while completing instructional activities. Further investigation of four instructors in IMotions, all of which chose to complete student feedback activities as their filmed task, highlighted the use of comments on student assignments as a means of communication between instructor and student and a method of understanding student profiles. This task proved to be a highly emotional experience, with frustration and contempt being the two most consistently reported emotions in IMotions throughout each recorded task.. Therefore, this study highlights the importance of capturing instructor emotions in real-time and through self-report. Each method captures a specific point of the instructional experience and instructors' expressed emotions during instructional tasks and their emotional state while completing these tasks.

Keywords: Case study
Emotions
Higher Education
IMotions
Online Instruction
Advisor: Woodruff, Earl
Consequences of Sex Differences in Selection and Sex-specific Genetic Architecture of Fitness

The sexes exhibit dramatic phenotypic differences. Ultimately, these differences are thought to be the result of sex differences in selection. My thesis takes a variety of approaches to investigate the consequences of these differences from an evolutionary genetics perspective. In Chapter 2 I surveyed the literature for estimates of sex-specific phenotypic selection in the wild and performed meta-analysis to understand the strength of sex-specific selection. Results of this study suggest that selection is often male-biased in magnitude and consistent with sexual selection theory, male-biased selection is driven by components of fitness related to mating success. In Chapter 3, I explored two potentially contradictory consequences of increased variance in fitness among males: stronger selection but also increased genetic drift. I used a mathematical model to explore how increased condition-dependency of male fitness relates to the efficacy of selection. Next, I estimated sex-specific fitness in a laboratory population of Drosophila melanogaster in environmental contexts intended to alter sex-specific variance. I show that increased variance in male fitness can facilitate stronger selection without a concomitant increase in the strength of genetic drift when a substantial amount of the variance in fitness is due to stochastic processes such as random juvenile mortality. In Chapter 4 I investigated the sex-specific genetic architecture of fitness using inbred lines of D. melanogaster. I used three approaches – quantitative genetics, genome wide association and a mutation load approach – each providing a unique perspective into the genetic underpinnings of male and female fitness. Finally, in Chapter 5 I used RNA-seq data to investigate the coincidence of two forms of sexually dimorphic gene regulation: sex-bias in gene expression (SBGE) and sexually dimorphic isoform usage (SDIU) in D. melanogaster. Results of this study suggest that both forms of gene regulation are widespread and tissue specific. Population genomic patterns of these genes are consistent with the idea that both SBGE and SDIU evolve to resolve sexual conflict but that they may represent alternative routes to resolution. Overall, my thesis reinforces a view that the sexes represent very different selective environments and provides novel insights into the causes and consequences of these sex differences.

Advisor: Agrawal, Aneil F
Galaxy Cluster Pressure Profiles and The Next Generation of South Pole Telescope Science and Instrumentation

The sensitivity of ground-based Cosmic Microwave Background telescopes has exploded over the past decade. Multichroic pixel design and improved wide-field optics have allowed for huge increases to the number of background limited detectors that can be installed into a single focal plane array. Such telescopes are on the cusp of detecting the elusive primordial gravitational waves predicted by models of cosmic inflation. They will also map vast numbers of galaxy clusters out to high redshifts, providing a powerful probe of evolving structure within the largest gravitationally bound objects in our Universe. This thesis covers several active areas of research relating to the instrumentation, observations, and scientific analysis for one of the worlds leading Cosmic Microwave Background telescopes, the South Pole Telescope. We begin by covering the design, operation, and performance of the third-generation South Pole Telescope camera, SPT3G. The SPT-3G camera contains over 14,000 operable transition edge sensor detectors, and is on track to map a 1500 deg2 patch of the Cosmic Microwave Background to a depth of ∼ 2 µK-arcmin at 150 GHz. We follow this with a description of the cryogenic testbed environment that was developed for characterizing the SPT-3G detectors and readout in a laboratory environment. The dark testing results of transition edge sensor properties were used to fine-tune the fabrication process towards the desired detector performance, as well as informing future research and development efforts. This thesis concluded with an analysis of galaxy cluster pressure profiles using the cluster catalogue and data from the 2500 deg2 SPT-SZ survey. Projected temperature profiles are computed using a multi-band least-squares fit and then fit to parametric pressure profile models. We find that the the average pressure at high radii is low compared to previous works, with the discrepancy driven by a population of clusters that display strongly peaked profiles with little extended signal. Morphologically different cluster subsamples are explored which show a measurably different pressure profile structure between relaxed and disturbed clusters. We also explore deviations from self similar scaling across the mass and redshift range of the SPT-SZ catalogue, finding that the measured evolution is driven by variations in the underlying cluster morphology.

Keywords: Cosmology
Galaxy Clusters
Instrumentation
Advisor: Vanderlinde, Keith
Optimization Methods based on Decision Diagrams for Constraint Programming, AI Planning, and Mathematical Programming

Decision diagrams (DDs) are graphical structures that can be used to solve discrete optimization problems by representing the set of feasible solutions as paths in a graph. This graphical encoding of the feasibility set can represent complex combinatorial structures and is the foundation of several novel optimization techniques. Due to their flexibility, DDs have become an attractive optimization tool for researchers in different fields, including operations research and computer science. This dissertation investigates new techniques to use DDs in conjunction with existing discrete optimization approaches based on constraint programming (CP), artificial intelligence (AI), and integer programming (IP). The central thesis of this dissertation is that DDs are effective tools to capture complex combinatorial structures of discrete optimization problems that are not fully exploited by general-purpose solvers. Thus, combinations of DDs with existing technologies can achieve state-of-the-art performance on challenging optimization problems. Throughout this work, we address this thesis by developing novel DD procedures that leverage methodologies from different optimization fields to solve discrete optimization problems. Our first project employs Lagrangian duality to strengthen DD bounds for pickup-and-delivery problems. The second project explores new ways to generate admissible heuristics for AI planning tasks by combining DD relaxations with AI planning techniques. This work also studies the relationship between DD heuristics and existing admissible heuristics in the community. Lastly, we propose a novel combinatorial lifting procedure and two cutting plane approaches based on DDs for general-form binary optimization problems. We show theoretical guarantees for our lifting procedure (e.g., conditions to obtain facet-defining inequalities) and provide a thorough theoretical analysis of our two cutting plane procedures. We apply our DD techniques to different problems, extending the usability of DDs in the field. Our first work extends the literature of DDs for sequencing problems by considering capacity constraints and proposing a DD construction procedure based on this restriction. We also present two DD encodings for delete-free AI planning and analyze the properties of both representations. Our last project introduces a new DD network flow formulation and proposes a novel DD encoding for second-order cone inequalities.

Keywords: Artificial Intelligence
Constraint Programming
Decision Diagrams
Discrete Optimization
Mathematical Programming
Advisor: Beck, J Christopher
Cire, Andre A