VictorJuiz/thesis huggingface dataset:
Learning-based Path-tracking Control for Ground Robots with Discrete Changes in Dynamics

Control algorithms such as stochastic model predictive control (SMPC) choose control inputs that guide the robot towards its goal by minimising a cost function while limiting the risk of collision to an acceptable threshold. This ability to manage risk makes it appropriate for autonomous mobile robots to manage the potential for damage to the robot and its environment. A key ingredient in SMPC is a dynamics model that predicts the motion of the robot, including an estimate of uncertainty in that prediction. This thesis focuses on using data to improve this dynamics model in changing conditions with limited prior knowledge about those changes. Existing approaches focus on either a single model that can be adapted to slowly changing dynamics or a fixed number of models that are known ahead of time. In contrast, we focus on the case where the robot dynamics may be subjected to an unknown number of potentially large changes. First, we develop a method to model the robot dynamics as a Gaussian Process (GP), learning new models when new dynamics are encountered and leveraging existing models when possible. However, the GPs resulting from this method are too computationally expensive for use in closed-loop experiments. To reduce their computational cost, we switch to a repetitive path-following task and an experience-recommendation paradigm, whereby a single, local GP is constructed based on relevant data from previous traversals of the path. We then build on this framework using Bayesian Linear Regression (BLR) to model the robot dynamics which facilitates continuous adaptation to changing dynamics in addition to leveraging data from previous traversals. To make better use of data available apriori, we develop a method to learn basis functions for BLR from data rather than requiring that they be specified by hand. Finally, we develop a method to learn a correction to the cost function used in SMPC that automatically discourages the robot from entering states where the dynamics model does not accurately predict the cost associated with a sequence of control inputs. These approaches are validated through a series of experiments on ground robots.

Keywords: field robotics
machine learning
model predictive control
Advisor: Schoellig, Angela P
Strategies for Noisy Photonic Quantum Technologies: Quantum Computation to Quantum Key Distribution

This thesis focuses on photonic implementations of two quantum technologies: quantum computers and quantum key distribution (QKD). Part I concentrates on photonic quantum computation using a qubit encoding for continuous-variable (CV) systems such as photonic modes known as Gottesman-Kitaev-Preskill (GKP) states. GKP states would be an advantageous encoding for photonics due to their error-correcting properties in the CV space and due to the experimental accessibility of gate and measurement implementations. This thesis advances the prospect of photonic quantum computation with GKP states on three fronts: first, to address the outstanding issue of how to prepare these qubits in optics, we analyze a proposal for their generation using two experimentally-accessible resources, multimode squeezed states and photon-number resolving detectors. Next, to overcome the difficulty of simulating GKP states in the Fock basis, a phase space simulation technique is introduced to understand realistic noise on these qubits. Lastly, to determine the potential of GKP qubits for fault-tolerant photonic quantum computation, a measurement-based architecture with GKP states is analyzed to determine thresholds for the quality of state required. Part II shifts focus to QKD, and how security proofs can account for realistic device imperfections. We first examine entanglement-based QKD protocols that employ high-dimensional photonic degrees of freedom (e.g. time-frequency or electric field quadrature) to produce more bits of key per optical signal. While entanglement-based protocols circumvent security assumptions about the quantum state source, they come at the cost of having to trust one's detectors. This thesis analyzes a previously-identified detector loophole for these schemes, and provides a modified security proof that succeeds in establishing security when encoding in electric field quadrature, with limited success for time-frequency encoding. Luckily, an alternative protocol known as measurement-device-independent (MDI) QKD requires no security assumptions about detectors. Instead, MDI QKD requires trusted sources of quantum states, which are nonetheless subject to their own imperfections that can compromise security. In the remainder of the thesis, we advance security proofs for MDI QKD in the presence of two potential source flaws: noise that introduces mixedness to the quantum states, and side-channels that leak information about the encoding choices of states.

Keywords: bosonic qubits
MDI QKD
photonics
quantum computing
quantum key distribution
quantum optics
Advisor: Lo, Hoi-Kwong
Imagining the Actual

Suppose I ask you how many windows are on the outside of your house. A natural way to answer my question is to imagine the outside of your house from various angles, counting the number of windows in your mental image. Suppose now that I describe to you a car accident I witnessed on my way to work this morning. As I do so, it would be natural for you to imagine this event as I describe the various details. In cases like these, we exercise our ability to imagine the actual world, using mental imagery to put us in touch with the way things are in reality. Prior to reflecting on such examples, it’s intuitive to associate the imagination with our ability to mentally transcend reality: to daydream, fantasize, and conjure up fictional worlds. But this obscures the fact that uses of imagination to cognize actuality are a common, core part of everyday mental life. This dissertation investigates the nature and epistemic significance of such uses of the imagination, both in our individual explorations of the world and in how we learn from other people.

Advisor: Nagel, Jennifer
Affective Contours of Two College Microbiology Laboratories: Potentializing International Students' Be-longings with Science, Education and Canada

This dissertation explores affective politics of two college microbiology laboratory courses. Drawing from studies of affect, care and politics of aesthetics, I examine how bodies of science education and science education bodies are reproduced and transformed through particular affective attachments or be-longings. Accounting for student demographics in the two courses observed — International students from India — my analyses further situate those be-longings in relation to what it means to have ‘the good life’ in Canada. While one course (project 3) depicts affectivities of precarious living and being (for various participants involved), the other course (project 2) gestures to how a disciplining of the biotechnician body meets histories of subjugation that entangle nature (simplistically here, bacteria) and women. Pedagogies of the college microbiology laboratory (existing within larger networks) work affectively to coalesce epistemic privileges of science (as hard, objective, masculinist) with production of more-than-human subjects for capitalist markets (in this case, food and pharmaceutical industries). Seeking affect through its productive (and not merely reproductive) intensities in educational situations, I approach my contexts of study as already ripe with pedagogical openings for being, thinking and caring differently within science and science education. I further describe such openings in relation to a new pedagogical approach, ‘STEPWISE’ (Bencze, 2017), that creates some interruptions in this context, potentializing new be-longings. Particularly evident in project 3, STEPWISE turns into a ‘warm’ pedagogy that meets with friendship flows and possibilities for being in renewed relationships with science, knowledge, bacteria, education and the job market. This research contributes to studies of emotions/affect in science education from a political perspective. A proposed direction for future research seeking productive ways to engage with emotions/affect in science education may start by contaminating cultural analyses of science education with an affectivity lens that can open new horizons for be-longing with science education and research. For instance, what could be some pedagogical possibilities for a science education that departs from a main preoccupation with ‘critical thinking’ towards centering ‘critical care’?

Advisor: Bencze, John Lawrence L
CYP2D in the Brain Alters Response to Drugs and Neurotoxins

Cytochrome P450 2D (CYP2D) is a subfamily of enzymes that metabolize many centrally acting drugs and neurotoxins. In humans, CYP2D6 is genetically polymorphic, resulting in variable activity. CYP2D in the liver is regulated primarily by genetics, while CYP2D in the brain is affected by genetics and other factors, including xenobiotic induction and hormonal regulation. Thus, CYP2D in the brain is highly variable and may alter brain drug concentrations and drug response. This thesis investigated the impact of inhibiting CYP2D specifically in the brain, without affecting CYP2D in the liver, on brain drug metabolism and resulting responses. CYP2D in rat brain was inhibited using a twenty-hour intracerebroventricular pretreatment with an irreversible inhibitor of CYP2D. We found that inhibiting CYP2D in rat brain increased brain methamphetamine concentrations and decreased the methamphetamine p-hydroxylation metabolic ratio in the brain, enhanced striatal dopamine and serotonin release, exacerbated acute methamphetamine-induced rearing, and enhanced repeated methamphetamine-induced stereotypy sensitization. Next, to assess the role of human CYP2D6 in brain in vivo, humanized CYP2D6-expressing transgenic mice and wild-type mice were given intracerebroventricular pretreatments with a CYP2D inhibitor. A four-hour inhibitor pretreatment irreversibly inhibited human CYP2D6 in transgenic brain and competitively inhibited mouse CYP2D in transgenic and wild-type brain. This four-hour inhibitor pretreatment exacerbated harmine-induced hypothermia and tremor in transgenic mice and exacerbated only hypothermia in wild-type mice. A twenty-four-hour inhibitor pretreatment irreversibly inhibited human CYP2D6 in transgenic brain only and was thus used to test the specific contribution of human CYP2D6 in vivo in brain. The twenty-four-hour inhibitor pretreatment exacerbated harmine-induced hypothermia in transgenic mice, having no effect in wild-type mice. Confirming an impact of human CYP2D6 in brain, the twenty-four-hour inhibitor pretreatment also reduced haloperidol-induced catalepsy in transgenic mice. We demonstrated that CYP2D in rat brain alters brain methamphetamine concentrations and methamphetamine-induced neurotransmitter release and behavioral sensitization. Further, we demonstrated that human CYP2D6 is active in vivo in brain, and its activity is sufficient to alter haloperidol-induced adverse effects and harmine-induced neurotoxicity. In conclusion, the extensive variation in CYP2D6 in the human brain may contribute to interindividual differences in drug-induced neurochemical and behavioral responses, adverse effects, and neurotoxicity.

Keywords: Brain
Cytochrome P450
Drug metabolism
Haloperidol
Harmine
Methamphetamine
Advisor: Tyndale, Rachel F
Practice Patterns and Long-term Health Outcomes of Bilateral Salpingo-Oophorectomy at Benign Hysterectomy

Background: Bilateral salpingo-oophorectomy (BSO) is offered at the time of benign hysterectomy to prevent ovarian cancer later in life. However, BSO results in the cessation of ovarian hormone production and may be harmful to long-term health. If BSO is associated with adverse outcomes, then understanding variation in surgeon practice will help identify targets for knowledge translation and quality improvement. Methods: We performed three population-based observational studies of women undergoing benign hysterectomy in Ontario, Canada, using linked administrative databases held at ICES. We used mixed logistic regression modelling to describe between-surgeon variation in BSO; overlap propensity score weighted survival modelling to determine whether BSO was associated with all-cause and cause-specific death; and inverse probability of treatment weighted survival modelling to quantify the risk reduction in ovarian cancer associated with BSO. Results: Rates of BSO at benign hysterectomy varied markedly between surgeons even after adjusting for patient case-mix, and the surgeon providing care was one of the strongest factors influencing whether patients underwent BSO (median odds ratio 2.10, 2.49, 2.84, 2.00 in women

Keywords: Gynecology
Health services research
Hysterectomy
Mortality
Oncology
Oophorectomy
Advisor: Baxter, Nancy N
Three Priority Queuing Models Motivated by Healthcare Management

In this thesis, we study three priority queueing models in healthcare management. In the first chapter, we analyze the impact of incentive misalignment between ED and physicians. We analyze two scheduling rules: physician self-schedule and centralized schedule. For the first scheduling rule, we show, using Markov decision process, that the physician's optimal policy has a time-dependent pattern. More specifically, near the beginning of the shift, the physician is more willing to see new patients, while near the end of the shift, the physician is more willing to see reentrant patients. Using a fluid model, we demonstrate that the time-dependent behaviour increases the variance of the system, and thus raises the 90th percentile of time to physician initial assessment (TPIA). For the second scheduling rule, we show, using the fluid model, that the centralized scheduling rule decreases the 90th percentile of TPIA. In the second chapter, we analyze the practice of capacity rationing under the setting of a non-preemptive priority queueing model with c servers. In the model, an arriving low priority customer enters service without waiting only when the number of idle servers exceeds the capacity rationing level. When the service rates for high and low priority customers are equal, we demonstrate, using diffusion approximation, that the non-degenerative rationing level is at most O(√c). When the service rates for two classes are different, we develop an algorithm, using queueing and Markov chain decomposition method, that calculates the performance measures of interest. In the third chapter, we study an M/G/1 preemptive priority queue with transition delays, which happen when high priority customers preempt low priority customers. Recent literature empirically shows the existence of transition delay. We build a queueing model to incorporate the transition delay into performance analysis. For queueing systems with two priority classes, we find the analytical solution of the expected waiting time of both classes. For systems with more than two priority classes, we summarize our preliminary results, and discuss the difficulty of extending the result of the two class model to multiple classes.

Keywords: healthcare
priority queue
queueing theory
service operations management
Advisor: Baron, Opher OB
Krass, Dmitry DK
Jewish Geographies: Spatial Narratives of Orthodox Jewish Leavetakers in Toronto

Through interviews with twenty self-described leavetakers from a wide range of Orthodox Jewish lifestyles in Toronto, Canada, this dissertation argues that leavetaking from normative Orthodox Judaism does not mean exiting Judaism or even stopping observance completely. Study data illustrates how leavetakers instead embark on individual journeys towards what they perceive as greater personal Jewish authenticity. They do so by restructuring their Jewishness from a perspective coloured anew by their leavetaking trajectories. Their experiences living in their old normatively Orthodox community, leaving these communities, and returning to Jewish Toronto post-disaffiliation to maintain contact with their families of origin all contribute to their new Jewish identities. Using a framework highlighting the effects of spatial and social Jewish Geography on disaffiliation and identity change, I adapt sociologist Wayne Brekhus’ typologies of gay identity disclosure in my investigation of Orthodox leavetaking trajectories. In addition, by expanding inclusion criteria to include both Haredi and other observant leavetakers towards a broader “Orthodox” participant sample, this research addresses a wider discourse on permeable religious boundaries than existing scholarship on leaving Judaism typically offers. My analysis uncovers a variety of local models for changing religiosity, from firm rejection of normative observance to break-taking and eventual return to an amended Orthodoxy and beyond. Leavetakers seek out and develop for themselves an adjacent “other Jewishness” sometimes still within observant Judaism but distinctly different from normative Orthodoxy, finding that established denominational categories do not correspond with their reconstituted Judaism. These narratives offer profound insights into what post-leavetaking Judaism looks like for disaffiliates who find themselves in indeterminate spaces still within Judaism—not outside of it.

Keywords: Judaism
leavetaking
off the derech (OTD)
Orthodoxy
spatiality
Toronto
Advisor: Coleman, Simon
A Computational Study of the Role of Neurogenesis in Learning and Memory

Neurogenesis persists throughout life in the dentate gyrus of the mammalian hippocampus. There is a large body of evidence that neurogenesis may impact cognition, particularly concerning learning and memory, though it is unclear what mechanisms underlie these processes. Computational models have established that the addition of neurons degrades existing memories (i.e., produces forgetting). These predictions are supported by empirical observations in rodents, where post-training increases in neurogenesis also promote forgetting of hippocampus-dependent memories. However, in these models that use 10-1,000 neurons to represent the dentate gyrus, forgetting is only observed at new neuron addition rates that greatly exceed adult neurogenesis rates observed in vivo. To address this, we generated an artificial neural network that incorporated more realistic features of the hippocampus – including increased network size, sparse activity, and sparse connectivity and explored how these properties modulate the impact of using biologically relevant rates of neurogenesis in a pattern categorization task. Our model captures several mnemonic phenomena associated with neurogenesis, including forgetting and enhanced reversal learning. These effects were sensitive to changes in increased output connectivity and excitability of new neurons. Crucially, forgetting was observed at lower rates of neurogenesis in larger networks, with the addition of as little as 0.1% of the total DG population sufficient to induce forgetting. We also propose a role for neurogenesis in the generalization of memories using traditional deep learning architectures. At rates of 3% turnover, we found that neurogenesis alone improved generalization on unseen data in two commonly used categorization tasks, the MNIST and CIFAR-10 datasets. Together, we suggest not only that low rates of neurogenesis can have an impact on cognition, but that we can use biologically-inspired and artificial neural networks to investigate the computational functions of neurogenesis that may mirror those occurring in vivo as well.

Keywords: computational
learning
memory
neurogenesis
Advisor: Frankland, Paul W.
Evidence to Inform Policy Options for the Elimination of Hepatitis C Virus in First Nations Populations in Ontario

In Canada, an estimated 220,000-246,000 people currently live with chronic hepatitis C viral (HCV) infection. To achieve the goals set by the World Health Organization (WHO) strategy to eliminate HCV infection by 2030, a mandate for action in the form of the Blueprint to Inform Hepatitis C Elimination Efforts in Canada was released. The Blueprint outlines what is necessary to achieve HCV elimination in Canada, emphasizing the need to inform specific knowledge gaps and calling on provinces/territories to develop action plans to meet the WHO targets for viral elimination. As a part of Canada’s commitment to the WHO strategy and the Blueprint, Canada has made First Nations-led approaches and First Nations populations a priority focus for national and provincial/territorial HCV strategies. Therefore, the purpose of this thesis is to generate evidence that can inform policy options for HCV elimination efforts in First Nations populations in Ontario. In Ontario, recent negotiations have allowed for partnerships between academic researchers and First Nations organizations to perform First Nations-directed research using administrative health data. In partnership with the Ontario First Nations HIV/AIDS Education Circle (OFNHAEC), we examined the health and economic impacts of HCV on Status First Nations populations in Ontario. The first study explored trends in the epidemiology and testing for HCV among a cohort of Status First Nations individuals across Ontario. The second study estimated the provincial publicly-funded healthcare costs associated with HCV among a cohort of Status First Nations individuals in Ontario. The third study uses the example of HCV screening within the emergency department setting to demonstrate how existing research can be used to perform economic evaluations of novel HCV case-finding approaches. With future work and using the evidence generated from this thesis, a similar approach can be used to evaluate First Nations-specific HCV interventions. Collectively, these studies inform research gaps necessary to reach the WHO goals for viral elimination and serve as reference in beginning to understand the impact of infection among First Nations individuals in Ontario. The data presented by this dissertation provides decision-makers with evidence that can inform the creation of HCV policy, prevention, and treatment efforts.

Keywords: First Nations Health
Health Economics
Health Services Research
Hepatitis C
Indigenous Health
Advisor: Krahn, Murray
Isaranuwatchai, Wanrudee