VictorJuiz/thesis huggingface dataset:
The Prevention and Control of Carbapenemase-Producing Enterobacterales (CPE) in Ontario, Canada

Carbapenemase-producing Enterobacterales (CPE) are an important threat to human health. CPE spread appears to occur primarily in healthcare facilities, and transmission is usually patient-to-patient but can sometimes be from contaminated hospital drains to patients. The extent to which community transmission occurs is unknown. This thesis aimed to inform CPE infection prevention and control (IPAC) measures in Ontario, Canada. First, we surveyed all acute care hospitals in Ontario to determine whether their CPE IPAC practices were in accordance with provincial guidelines. Only 60% of hospitals screened patients with prior healthcare abroad or high-risk travel on admission, despite guidelines recommending this. Even fewer hospitals (20%) screened patients with prior hospitalization in Canada on admission, possibly because guidelines do not recommend this despite recent evidence revealing considerable local CPE transmission. Second, we cultured all hospital drains previously exposed to inpatients with CPE at ten hospitals in Southern Ontario (N=1,209) and used whole-genome sequencing to determine whether drain CPE could be linked to patient exposure. Drain contamination was uncommon (53, 4%) but dispersed across 7 (70%) hospitals, and only 4 CPE-contaminated drains could be linked to prior patient exposure. This suggested contamination of drains by prior room occupants whose CPE was undetected, further highlighting insufficient patient screening practices. Finally, we examined risk of CPE household transmission. Of 177 household contacts, only 5 (3%) were detected as colonized due to confirmed or probable household transmission, suggesting little community transmission. Given that screening is cost-effective in low prevalence populations, household contacts of known CPE cases should be included in hospital admission screening programs. In summary, this thesis revealed an urgent need for methods to improve uptake of provincial guidelines for CPE prevention and control in Ontario hospitals, particularly with respect to admission screening. This thesis also shone a light on aspects of provincial guidelines that require updating, such as recommendations for admission screening to include patients with prior hospitalization in Canada and household contacts of known cases. We should continue to focus our IPAC efforts for CPE in healthcare facilities, where most transmission appears to occur, as opposed to the community.

Advisor: McGeer, Allison J
Targeting the Mitochondrial Peptidase Neurolysin in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) cells and stem cells have unique mitochondrial characteristics with an increased reliance on oxidative phosphorylation (OXPHOS). Through a genetic screen to find novel mitochondrial targets in AML, we identified the mitochondrial peptidase, neurolysin (NLN). NLN is a metallopeptidase whose mitochondrial function is not well understood and whose role in AML has not been reported. We analyzed the expression of NLN in AML cells and normal hematopoietic cells. NLN gene expression was enhanced in 41% of AML samples and overexpression was confirmed by immunoblotting. Next, we assessed the effects of knocking down NLN in AML cell lines. NLN knockdown reduced AML growth by up to 70%, clonogenic growth by up to 80%, and engraftment into mouse marrow by 90%. We next identified NLN’s mitochondrial interactors by BioID-MS. NLN interacted extensively with the respiratory chain and NLN knockdown reduced OXPHOS. Moreover, NLN knockdown impaired the formation of respiratory chain supercomplexes (RCS), which promote efficient oxidative metabolism. RCS have not been previously studied in leukemia. We found that RCS assembly was increased in a subset of AML patients compared to normal hematopoietic cells and positively correlated with NLN protein expression (R2 = 0.80, p

Keywords: AML
metabolism
NLN
respiratory chain supercomplexes
Advisor: Schimmer, Aaron D
Women in the House: The Impact of Elected Women on Parliamentary Debate and Policymaking in Canada

This study examines the impact of elected women in Canada on patterns and processes of parliamentary debate and policymaking from 1968 to 2015. It argues that women’s presence in parliament matters for the substantive representation of women, particularly under conditions of threat to women’s equality. The study refines core concepts in the literature on women’s political representation to explain how the substantive representation of women occurs in Canadian parliamentary institutions. It disaggregates the concept of substantive representation and expands the scope of the critical actors framework to include actions that defend women’s equality against regressive policy initiatives. Building on these refinements, the study argues that gender is a key factor in determining whether an MP will represent women in parliamentary debate, but the institutional role MPs occupy and the political context in which they operate influence the mechanisms they use to advocate for women’s equality in policymaking and their chances of success. Through an automated analysis of the content of nearly 50 years of parliamentary debate, the study finds that women MPs, regardless of party affiliation, are consistently more likely than their male colleagues to make representative claims about women. Using supervised and unsupervised machine learning to analyse the content of these representative claims, the study finds that parliamentary speeches about women focus almost entirely on issues relating to women’s equality and autonomy. The analysis of parliamentary debate shows that the number of speeches about women spiked during parliaments when governments initiated policies that threatened women’s equality. Qualitative case studies examine these two instances of policymaking, focusing on the actors involved, the processes through which they advocated for women, and the impact of their actions. The study finds that women MPs led the charge against hostile government policy initiatives but their varying ability to influence policy outcomes was shaped by their institutional positions and the political conditions under which they operated. The study concludes by suggesting the presence of women in Canadian politics matters as a tool for guarding against policies that would roll back previous equality gains. Efforts to increase women’s presence in electoral politics in Canada therefore remain important.

Advisor: Bashevkin, Sylvia
Quantum Homomorphic Encryption: Implementation and Applications

As the field of quantum information as a whole continues to see sustained and rapid progress, two sub- disciplines distinguish themselves as having had particularly noteworthy recent developments: quantum cryptography and quantum metrology. Of late, quantum cryptography has had a renaissance of sorts as techniques in classical post-quantum cryptography (i.e. classical schemes believed to be robust against attacks by a quantum computer) mature, making it possible to construct more elaborate and flexible quantum+classical schemes. A particularly interesting offshoot is the construction of quantum homomorphic encryption (QHE) which allows anyone in possession of a ciphertext to perform an arbitrary computation directly without having to decrypt beforehand. We describe the construction and experimental implementation of a QHE scheme which, unlike previous schemes that have focused on the use-case of delegating computation to an untrusted party, is flexible enough to serve as a primitive for much wider gamut of cryptographic applications. In quantum metrology, the gradual but continued adoption of rigorous analyses and bounds borrowed from classical statistics increasingly puts claims of quantum metrological advantage on more solid footing. Recently, an exciting insight stemming from these systematic analyses is that the Rayleigh criterion, long seen as a fundamental resolution limit in imaging with finite-sized optics, is not so fundamental after all. Leveraging this realization, in this thesis we describe the construction and implementation of a set of measurements (nicknamed “SPLICE”) that outperforms traditional imaging in its ability to resolve two arbitrary point sources separated along a known axis.

Keywords: Cryptography
Homomorphic Encryption
Metrology
Super-resolution imaging
Advisor: Steinberg, Aephraim M
Using Transcranial Direct Current Stimulation to Improve Cognitive Function in Mild Cognitive Impairment and Dementia

Introduction: Cognitive deficits are key clinical features of Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD). Current first-line pharmacotherapies demonstrate only modest efficacy in AD and lack efficacy in MCI. Transcranial direct current stimulation (tDCS), a non-invasive neuromodulatory technique, has been used to improve cognitive functions with positive results, but with wide variability in response. This research aims to optimize tDCS for cognition by evaluating the effects of electrode placement, the efficacy of exercise primed tDCS, and examining mechanistic correlates of tDCS response in MCI and mild AD patients. Methods and Results: Study 1. To evaluate the effects of electrode placement on cognition, MCI and mild AD participants (n=17) received a single session (2mA, 20 minutes) of bifrontal (F3/F4), bitemporal (T3/T4), and sham stimulations. There was a significant effect of stimulation condition on working memory (F(2,28)=5.28, p=0.01, ηp=0.27), with greater improvements following bitemporal tDCS compared to bifrontal and sham stimulations. Study 2. To investigate the efficacy of exercise primed tDCS on cognition, MCI and mild AD participants (n=19) were randomized to either exercise primed tDCS, exercise primed sham tDCS, or treatment as usual (exercise education only) with tDCS. Ten sessions of bitemporal (T3/T4, 2mA, 20 minutes) or sham tDCS were applied following personalized moderate-intensity aerobic exercise (30 minutes). The trial is ongoing and to maintain blindness, the treatment groups are named as Group A, B, and C. There was a significant effect of time (F(1,14)=11.40, p=0.005), but no group by time interaction on recognition memory (F(2,14)=1.00, p=0.38). However, post hoc analysis revealed significantly greater improvements on recognition memory over time within Group A only (t(5)=-3.70, p=0.02). Study 3. To examine mechanistic correlates of tDCS response, serum vascular endothelial growth factor (VEGF) and endostatin concentrations were analyzed from participants who completed Study 2 (n=18). After controlling for diagnosis, lower VEGF concentrations at screening predicted greater improvement in recognition memory following tDCS treatment with or without exercise priming (b[SE]=-0.66[0.004], p=0.03). Conclusion: Single-session and repeated-session exercise primed bitemporal tDCS may be effective at improving specific cognitive domains in MCI and mild AD patients. Angiogenic mechanisms may underlie tDCS-induced cognitive improvements in these patients.

Advisor: Lanctot, Krista
Management Going Concern Disclosure

An entity’s ability to continue as a going concern (GC), or the ability to fulfill obligations when they become due, is one of the key concerns of businesses, investors, and policymakers. My dissertation provides a comprehensive study of management GC disclosures and generates insights that are timely and highly policy-relevant. Chapter one examines management GC disclosures after the implementation of ASU 2014-15, a new accounting standard issued by the FASB requiring management to evaluate GC uncertainties quarterly and to provide disclosures in the notes to the financial statements. I first show that the market reacts negatively to such disclosures overall. More importantly, by employing highly detailed textual analysis to extract and categorize mitigation-plan discussions, I find that certain types of management mitigation plans are interpreted positively by investors, thereby alleviating the negative market reactions. These plans include selling assets, increasing liquidity through debt, equity, and grants, and revenue-enhancing strategies. Further, I demonstrate that management GC disclosures are associated with corporate failures and that mitigation-plan discussions can indicate firms’ future viability. Chapter two focuses on management strategic behavior related to avoiding GC disclosures. Managers contemplate potential consequences to decide whether to disclose GC uncertainties. Chapter two explores how to separate “strategic firms” - companies with substantial doubt in GC but whose managers do not provide adequate disclosures - from “truthful firms.” Employing a linguistic model built based on textual features extracted from the Q sections of conference calls for distressed firms, I demonstrate that the strategic executives talk longer and in a less negative tone. The strategic executives are more likely to use deceptive language and to mention non-GAAP measures and macroeconomic information and are less likely to discuss litigation and liquidity matters. I further extend the linguistic model to the non-distressed sample and predict the strategic scores indicating whether firms have GC uncertainties but withhold such disclosures. I find that the strategic firms are less likely to mention the word “going concern” in the financial reports and tend to increase their leverage after a new GC standard - ASU 2014-15 - was issued by the FASB.

Keywords: Accounting Standards
Corporate Failure
Going Concern
Management Disclosure
Textual Analysis
Advisor: Hope, Ole-Kristian
The Function and Evolution of C2H2 Zinc Finger Proteins and Transposons

Transcription factors (TFs) confer specificity to transcriptional regulation by binding specific DNA sequences and ultimately affecting the ability of RNA polymerase to transcribe a locus. The C2H2 zinc finger proteins (C2H2 ZFPs) are a TF class with the unique ability to diversify their DNA-binding specificities in a short evolutionary time. C2H2 ZFPs comprise the largest class of TFs in Mammalian genomes, including nearly half of all Human TFs (747/1,639). Positive selection on the DNA-binding specificities of C2H2 ZFPs is explained by an evolutionary arms race with endogenous retroelements (EREs; copy-and-paste transposable elements), where the C2H2 ZFPs containing a KRAB repressor domain (KZFPs; 344/747 Human C2H2 ZFPs) are thought to diversify to bind new EREs and repress deleterious transposition events. However, evidence of the gain and loss of KZFP binding sites on the ERE sequence is sparse due to poor resolution of ERE sequence evolution, despite the recent publication of binding preferences for 242/344 Human KZFPs. The goal of my doctoral work has been to characterize the Human C2H2 ZFPs, with specific interest in their evolutionary history, functional diversity, and coevolution with LINE EREs. I contributed to the expert curation of the full complement of 1,639 Human TFs and used the results to quantitatively compare their evolutionary history and tissue specificities to all other Human TFs. I analyzed protein-protein interaction (PPI) data for 118 DNA-binding C2H2 ZFPs and found extremely diverse interactions with nuclear factors despite paradoxically few dedicated PPI domains, revealing a new and unexplained dimension of functional diversity in addition to DNA-binding specificity diversity. Finally, I pioneered a computational technique to reconstruct extinct LINE L1 sequences and showed that they can be used to anchor the integration of KZFP genomic binding data and binding specificities for a complete picture of dynamic KZFP-ERE sequence specificity relationships. Together, my results paint a detailed picture of the diverse functionality and rapid evolution of Human C2H2 ZFPs, contribute to ongoing theorization on KZFP-ERE coevolution, and provide parallel datasets to power future investigations.

Keywords: Ancestral sequence reconstruction
Computational biology
Genomics
Proteomics
Transcription factors
Transposons
Advisor: Hughes, Timothy R
Unacknowledged Permissivism

Permissivism is the view that a single body of evidence can sometimes rationalize incompatible doxastic attitudes – for example, suspension of judgment and belief – toward some hypothesis. Impermissivism, by contrast, is the view that there is at most one rational doxastic response to the evidence. This dissertation argues that rationality is permissive, but in an unexpected way: cases in which a body of evidence rationalizes multiple, incompatible responses are possible, but subjects who are in such a case can never rationally believe that they are. This view has sometimes been referred to as unacknowledged permissivism. Unacknowledged permissivism is often said to be implausible. The orthodox view is that it is an unmotivated view, in part because it is said to break ties with the core motivation for defending permissivism in the first place – namely, our intuitions about cases describing disagreement between peers. I challenge the dominant view, arguing that, contrary to what has been assumed, our intuitions about these cases are compatible with unacknowledged permissivism. I also provide a positive argument for unacknowledged permissivism. I argue for a requirement of rationality that prohibits a subject from believing some proposition P while also believing that an incompatible attitude toward P is rational, given his or her evidence. A subject who believes such a conjunction is committed to a kind of intrapersonal incoherence that, in other cases, is obviously rationally problematic. If this is correct, there is a compelling case for the conclusion that believing one is in a permissive case is rationally prohibited. This, combined with the theoretical implausibility of impermissivism, constitutes a strong case for unacknowledged permissivism.

Keywords: belief
disagreement
evidence
permissivism
rational
rationality
Advisor: Nagel, Jennifer
Ecology of Vector-borne Diseases at the Interface of Theory and Data

Infectious diseases continue to impact human lives. However, surprisingly little is known about the fundamental biology of disease-causing organisms and their interactions with the host. This thesis focuses on vector-borne diseases which account for 17% of all known human infections and put more than half of the global population at risk of infection. An overarching focus of the work presented is heterogeneity within species, which is ubiquitous and fundamental to biology, yet has often been neglected outside of evolutionary biology. In infectious disease biology, a better understanding of individual heterogeneity is needed across scales. At the within-host level, infection dynamics and health outcomes are highly variable between hosts. Therefore, a single clinical intervention strategy will likely not achieve the desired cure in all individuals infected with the same parasite. At the between-host level, it is important to map the consequences of heterogeneity because a small fraction of the host population contributes disproportionately to disease transmission and determines the fate of an epidemic. By combining mathematical modelling and empirical data, this thesis develops conceptual and methodological frameworks that are rooted in ecology, but shift away from the strict focus on the average often found in biological sciences, dubbed the “tyranny of the golden mean”. This thesis uncovers within-host origins, and explores the between-host consequences, of heterogeneities in vector-borne diseases. In the first half, I outline how differences in within-host ecological processes generate variation in parasite population dynamics and health outcomes of malaria infection across inoculum sizes and host genetic backgrounds. In the latter half, I present host population-level consequences of variation generated by tri-trophic interactions be- tween parasites, hosts, and arthropod disease vectors, and of temperature-dependent heterogeneity in within-vector processes that govern the timing of infectivity. Overall, this thesis showcases the synergistic benefit of combining mathematical and computational modelling with empirical data to achieve better understanding and management of infectious diseases.

Keywords: Computational biology
Dengue
Disease ecology
Malaria
Vector-borne disease
Advisor: Mideo, Nicole
Machine Learning in Algorithmic Trading leading to Reinforced Deep Kalman Filters

In this thesis, we develop machine learning frameworks that are suitable for algorithmic trading, where environments are volatile, heteroscedastic, and driven by latent factors. The thesis contains two main parts increasing in the complexity of the frameworks we develop. In the first part, we model the dynamics of ask-bid prices using and Hidden Markov Models (HMM) and compare its performance against First Order Markov Models (MM). A supervised learning method is developed for making binary (buy or sell) market order predictions using Restricted Boltzmann Machines (RBMs). The RBMs are adapted to Gaussian-Bernoulli (GB-RBM), and later to discriminative GB-RBMs (DGB-RBM). The algorithm's performance is compared to predictions made using the industry standard of naive bid-ask depth imbalances. We demonstrate that the DGB-RBM outperforms the industry standard by up to 18% increment in the area under the receiver operating characteristic curve (AUC). In the second part, we use traditional reinforcement learning (RL) algorithms to solve an optimal execution problem – where an agent seeks to optimally sell stocks to simultaneously mitigate the risk of price movements and price impact in a stochastic environment. We develop optimal policies using variants of Q-Learning, DynaQ-ARIMA and DynaQ-LSTM algorithms, which are used as benchmarks. The analysis shows that idiosyncrasies of the optimal execution problem require delicate treatment of data inefficiency and model bias issues, which we address next. We propose a model-based RL approach, coined Reinforced Deep Kalman Filter (RDKF), designed to integrate desirable properties of a reinforcement learning algorithm acting as an automatic trading system. The network architecture allows for the possibility that market dynamics are partially visible and are modified by the agent's actions. The RDKF filters incomplete and noisy data to create better-behaved input data for RL planning. The policy search optimisation also properly accounts for state uncertainty. We perform ablation studies to understand the contributions of individual components of the RDKF. The experiments show that the RDKF is data-efficient and provides financial gains compared to the benchmarks in the optimal execution problem using real data sets from the limit order book of Facebook, Intel, Vodafone and Microsoft.

Keywords: Algorithmic Trading
Artificial Inteligence
Finance
Machine Learning
Reinforcement Learning
Statistics
Advisor: Jaimungal, Sebastian
The Law Society of Ontario’s Assessment of Capacity in Relation to Mental Illness: A Critical Analysis

Over the past 20 years, a number of studies across the globe have found that mental health issues—including substance abuse, depression, anxiety, and other forms of psychopathology—are especially acute in the legal profession. The Law Society of Ontario (“Law Society”), the regulator of the legal professions in the province, has a role to play in addressing these issues, particularly due to its statutory jurisdiction over the capacity of lawyers and paralegals (“licensees”). In this paper, I review in depth the Law Society’s current approach to licensee capacity concerns in its applications before the Law Society Tribunal. My critical examination of the current coercive processes is informed by their impacts on the autonomy interests of licensees. Ultimately, I argue that in light of these impacts, the Law Society’s authority with respect to licensee capacity must be strictly and narrowly interpreted, to the greatest benefit of the individuals at issue.

Keywords: Capacity
Illness
Licensee
Mental
Regulatory
Society
Advisor: Lemmens, Trudo
Lessard, Michaël