VictorJuiz/thesis huggingface dataset:
Transient Emission Phenomena in Millisecond Pulsars
Keywords: interstellar scintillation
neutron stars
pulsars
radio astronomy
radio bursts
signal processing

Millisecond pulsars are rapidly rotating neutron stars, with rotational periods on the order of milliseconds. The radio emission of millisecond pulsars exhibit a variety of interesting features such as bright transient bursts and rapid state changes which, when better understood, will improve our understanding of the pulsar magnetosphere. In this thesis, I study the transient emission phenomena of two millisecond pulsars. In observations of PSR B1957+20, I present the first ever detection of mode-changing behavior in a millisecond pulsar along with measurements of bright narrow bursts called "giant pulses". I find that the mode changes affect multiple emission components as well as the giant pulse emission, indicating that mode changing reflects a global reconfiguration of the pulsar's magnetosphere. Using observations of PSR B1937+21 which also emits giant pulses, I use a novel technique to directly measure the impulse response of the interstellar medium using the bright impulsive giant pulses. This method can be used to probe the structures in the interstellar medium and also to recover the intrinsic emission of the pulsar which was otherwise obscured by scattering and scintillation due to multi-path propagation. I present a detailed study of the intrinsic signals of giant pulses as well as the discovery of "giant micro-pulses" in the emission from PSR B1937+21. Studies of transient emission such as these can be used to place observational constraints on the radio emission mechanism of pulsars as well as improve our ability to use radio pulsars as probes of gravitational waves, the structure of the interstellar medium, and other astrophysical phenomena.
Security Proofs of Quantum Key Distribution with Imperfect Source Devices: From Practical Devices to Passive System
Keywords: Communication
continuous variable
discrete variable
Information theory
Quantum communication
Quantum key distribution

Quantum key distribution (QKD) is a method that enables two parties separated by distance to share a secret data string. QKD is based on the principles of quantum mechanics and offers information-theoretical security, making it a strong contender for the next generation of cryptography. However, the use of imperfect devices can lead to vulnerabilities and potential quantum hacking schemes. It is crucial to address these imperfections and restore the security of QKD, especially for individuals who use realistic devices for secure communication. QKD can be categorized into two types based on key encoding methods: discrete-variable (DV) QKD and continuous-variable (CV) QKD. It can also be classified based on the transmission medium: fiber-based QKD, free-space-based QKD, and chip-based QKD. This thesis focuses on chip-based DVQKD and fiber-based CVQKD. In the first part, we study the chip-based DVQKD system in the presence of phase-and polarization-dependent loss. We develop innovative methods to restore the security and improve the key rate. The solution is practical, requiring no hardware modifications, and has been adopted by other groups. The second part focuses on fiber-based CVQKD systems that use intensity fluctuating sources. We establish the security by incorporating the concept from DVQKD. Our proposed techniques are practical and do not require any hardware adjustments for existing CVQKD systems. Lastly, we present a general framework for passive CVQKD. Our proposed passive protocol offers a one-time solution to eliminate all potential side channels or imperfections in the source. Interestingly, we discover that the passive source is an excellent choice for the discrete-modulated CVQKD protocol, since the passive protocol offers the same key rate as its active counterpart, while removing all modulator side channels that have plagued the active ones. To sum up, this thesis introduces novel techniques and practical solutions to address imperfections in source devices in different QKD systems. We also propose a passive protocol that can handle all loopholes in source devices in a one-time process. We anticipate that this thesis will facilitate significant advancements in chip-based and fiber-based QKD implementations in the future.
COVID-19 Vaccination during Pregnancy and Infant Health Outcomes
Keywords: COVID-19
Infant health outcomes
Pregnancy
Vaccination

Background: Pregnant women are considered a high-risk group for severe Coronavirus Disease of 2019 (COVID-19); maternal COVID-19 vaccination is recommended during pregnancy in Canada and many countries worldwide. There is limited comparative epidemiological evidence on infant outcomes following maternal COVID-19 vaccination during pregnancy. Objective: To evaluate newborn and early infant health outcomes associated with maternal mRNA COVID-19 vaccination during pregnancy. Methods: We used data on mother-infant dyads from multiple linked health administrative databases in Ontario. Study designs included test-negative, cohort, and exposure-discordant sibling-matched analysis. We adjusted for measured potential confounders using multivariable logistic regression and propensity score methods. We performed quantitative bias analyses to assess the sensitivity of results to residual confounding and selection bias. Results: Maternal COVID-19 vaccination with two doses during pregnancy was highly effective against delta and moderately effective against omicron infection or hospital admission in infants during the first six months of life. A third vaccine dose bolstered protection against omicron. Effectiveness for two doses against omicron was highest with vaccination in the third trimester, and effectiveness decreased in infants beyond eight weeks of age. Postpartum maternal vaccination was moderately effective against delta infection but conferred little protection against omicron in infants younger than six months of age. Compared with no maternal COVID-19 vaccination preconception or at any point during pregnancy, vaccination with at least one dose during pregnancy was associated with lower risks of severe neonatal morbidity, neonatal death, and neonatal intensive care unit admission and no increases in neonatal readmission and hospital admission up to six months of age. Maternal vaccination during the first trimester was not associated with major or most organ system congenital anomalies. There was a small increase in ankyloglossia (tongue-tie) in infants of mothers vaccinated in the first versus second or third trimesters; residual confounding might have contributed to this apparent association and type I error, due to multiple comparisons, cannot be ruled out. Conclusions: This research substantially contributes to the understanding of the effectiveness and safety of maternal COVID-19 vaccination during pregnancy for newborns and young infants and can inform clinical decisions and guidance on COVID-19 vaccination during pregnancy.
Near-Ultraviolet Instrumentation and Cosmology in the New Space Era
Keywords: Ballooning
Cosmology
dark energy
Dark matter
luvs
superbit

This thesis explores the development of low-cost space instruments that leverage the ”New Space” era, to address the increasing demand for high-resolution astronomical imaging that traditionally relies on expensive space-based observatories. I focus on visible (VIS) and near-ultraviolet (NUV) instruments, as they offer high scientific impact with minimal added complexity due to the maturity of commercial imaging sensors in these ranges. I discuss three missions: Gigapixel Balloon-borne Imaging Telescope (GigaBIT), Super-pressure Balloon-borne Imaging Telescope (SuperBIT), and Little Ultra-Violet Space telescope (LUVS). GigaBIT aims to provide space-quality imaging without the prohibitive costs and long development timescales of traditional space missions. It combines ”New Space” ecosystem technology with ”Old Space” infrastructure for its launch, aiming to revolutionize the accessibility of astronomy to a more diverse range of research groups and increase the field’s research output. SuperBIT, a pathfinder mission for GigaBIT, demonstrates the feasibility of high-resolution balloon-borne observatories. It has proven the ability to achieve space-quality imaging, and it launched in April 2023 to study galaxy clusters, as a probe for the nature of Dark Matter and Dark Energy. SuperBIT will contribute to the reconciliation of the tension between different cluster mass observables by providing cost effective weak lensing maps for as many as 100 galaxy clusters. LUVS is an innovative project that aims to develop world-class telescopes on small satellites at low costs and fast development timescales. It seeks to rapidly and accurately localize gravitational wave sources, testing scientific theories from fundamental particle physics to large-scale cosmology. The ability to locate the sources of these events will help us better understand the fundamental nature of the universe and the forces that govern it. In this thesis, I focus on the early development of LUVS as a case study in adapting lessons learned from balloon-borne projects for orbital use while keeping mission costs increase minimal, resulting in a fully ”New Space” mission. By exploring the development of these three missions, I demonstrate the potential of the ”New Space” era to revolutionize astronomical imaging and contribute significantly to our understanding of the universe’s greatest mysteries.
Beyond Consultocracy and Servants of Power: Exploring and Explaining the Role of Private Market Consultants in Public Policy Formulation
Keywords: New Public Management
Outsourcing
Policy Feedback
Policy Formulation
Privatization

Private market consultants participate in public policy formulation, yet we know little about the content of their work, and what explains their impact on public policy. Using interviews, analysis of public documents, contracts data, and additional sources, this dissertation develops and empirically evaluates and specifies a novel conceptualization of consultants’ policy formulation roles, through analysis of their routine activity in health policy subsystems in two jurisdictions: Victoria, Australia, and Ontario, Canada. It demonstrates that contrary to how they are currently conceptualized in policy literature, consultants do much more than merely inform policy formulation. In what this dissertation terms “core” formulation roles, consultants provide policy advice and develop policy proposals; and foster their adoption by promoting buy-in among stakeholders and providing symbolic capital. In more peripheral roles, termed here “linkage” roles, consultants connect the government to the broader policy subsystem: they provide interpretation and legibility of its complexities, and inform policymakers on policy preferences of various stakeholders. In these roles, consultants have various types of impact on policy formulation. The dissertation further explains the variation in these roles, specifically – between core and linkage policy formulation work. It demonstrates that in Victoria, Australia, consultants are institutionalized in core policy formulation roles; while in Ontario, Canada, they are primarily involved in linkage roles, with sporadic inclusion in core formulation work. The research considers the conditions under which consultants became included and institutionalized in core policy formulation roles (where their impact is greater). It analyzes the impact of the diverging implementation of New Public Management (NPM) reforms and argues that major and rapid changes in state policy capacity, as was the case in Victoria, can prompt the inclusion and institutionalization of consultants in core policy work; and that this inclusion is susceptible to path-dependency and lock-in processes, and can support the development of consultants’ institutional power. Where state policy capacity remained robust, as in Ontario, consultants’ entrance and institutionalization in core roles were mitigated and restricted.
Improving Our Understanding of Arctic Tropospheric Pollution Through Measurements and Models
Keywords: Arctic
Atmosphere
FTIR
Pollution
VOC
Wildfires

In this thesis, ground-based Fourier transform infrared (FTIR) measurements from the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut are used to retrieve total columns of CO, C2H2, C2H4, C2H6, CH3OH, HCOOH, H2CO, and PAN over the period of 2006--2020. The retrievals of C2H4 and PAN were developed as part of this thesis, and are the first long-term ground-based FTIR measurements of these gases in the high Arctic. A global inter-comparison of the TROPOMI and ACE-FTS CO satellite datasets shows strong correlations but a latitudinal dependence of the biases, with positive biases in high-latitude regions and negative biases near the equator. At Eureka, the TROPOMI CO total columns were highly correlated with the ground-based FTIR measurements but with a mean bias of 14.7 +- 0.16%. ACE-FTS and the FTIR CO partial columns show good correlations and a mean bias of 7.89 +- 0.21%. All mean TROPOMI biases fall within the TROPOMI mission accuracy requirement. FTIR measurements of CO, C2H4, CH3OH, HCOOH, and PAN at Eureka were strongly enhanced in August 2017 due to wildfires in British Columbia and the Northwest Territories. For CO, C2H4, HCOOH, and PAN, these were the largest observed enhancements at Eureka. The emissions of these fires were estimated using FTIR and IASI measurements at Eureka, and for C2H4 and HCOOH they were found to be higher than previously reported. The fires were also simulated using the GEOS-Chem model, and the impact of the modeled biomass burning injection height and secondary VOC production was investigated. The inter- and intra-annual variability of the eight trace gases were derived from FTIR measurements at Eureka, Nunavut (2006--2020) and Thule, Greenland (1999--2022). Consistent seasonal cycles were observed at both sites. Decreasing trends were observed for CO, C2H2, and CH3OH at both sites, and for HCOOH at Eureka. Increasing trends were detected for C2H6 and H2CO at both sites, and for PAN at Eureka. A GEOS-Chem simulation for 2003--2021 was performed. The model reproduced the seasonality of all gases, but showed large negative biases for some species. The modeled trends broadly agreed with observations for all species except C2H6, H2CO, and PAN.
Queering the In-between: Liminality and Environmental Gentrification in Toronto
Keywords: affective geographies
environmental gentrification
more-than-human city
queer geographies

This dissertation examines environmental gentrification through the lens of queer affect, looking at two parks-led redevelopment projects in downtown Toronto, Canada: Reimagine Galleria and the Green Line. In it I argue that place-specific affective dynamics and politics shape and drive environmental gentrification processes. I also argue that environmental gentrification shapes people's emotional relationships with the places they live, while altering the more-than-human relations that constitute those places. Using queer affect as a prism through which to examine environmental gentrification as a process, I detail life-altering changes and losses that are happening on the ground as Reimagine Galleria and the Green Line proceed as redevelopment initiatives, as well as how these projects are experienced by people who feel both worried about their survival and place in the world and attached to a world that is slipping away as another one takes shape. A queer approach to examining the feeling of environmental gentrification renders visible a range of complex emotional dynamics and more-than-human relations that shape belonging, exclusion, life, and death in gentrifying space. At the centre of this dissertation is an exploration of how feelings are political, of what kinds of communities they bring together, and of what kinds of solidarities they make possible in the face of gentrification.
Automatic Compiler-based Optimizations for Deep Neural Networks
Keywords: Compilers
Deep Neural Networks
GPUs
Machine Learning Systems
Memory Optimizations
Performance Optimizations

Deep neural networks (DNNs) are the current state-of-the-art machine learning algorithms in various application domains. Due to their importance, it is crucial that we guarantee their efficient executions on hardware platforms such as GPUs. In this thesis, we optimize the runtime performance and the device memory consumption of DNNs running on modern GPUs. To make our optimizations generic, automatic, and transparent to the frontend machine learning practitioners, we use compiler-based approaches that achieve the optimization objective by carefully analyzing DNNs’ graph representations, tensor expressions, and the hardware platforms on which they run. Compared with manual implementations that require a significant amount of engineering effort, our thesis work, which is made up of three key contributions, requires minimal changes to frontend applications’ source code and can be applied generically to various state-of-the-art DNN models. Our first contribution, Grape, is a new graph compiler on graph-based executions for dynamic DNNs on GPUs. Grape addresses the practicability and efficiency challenges of graph-based executions using three key components: an alias predictor, a metadata compressor, and a predication rewriter. It improves the runtime performance of state-of-the-art text generation and speech recognition workloads by up to 2.99× compared with the machine learning framework baseline, and can optimize workloads that are not practical for prior works on graph-based executions, achieving up to 1.82×speedup over the baseline. Our second contribution, DietCode, is a new tensor program auto-scheduler that efficiently supports dynamic-shape workloads. DietCode addresses the compilation time challenge of auto-scheduling dynamic-shape tensor programs using a shape-generic search space and a micro-kernel cost model. Not only can DietCode reduce the compilation time by up to 5.88× on the state-of-the-art language modeling workload compared with the existing tensor program auto-scheduler, but it also improves the runtime performance by up to 1.70×. Our third contribution, Echo, is a new compiler-based optimization scheme that reduces GPU memory footprint for training state-of-the-art DNNs. We show that by carefully estimating the recomputation's effect on the memory footprint and the runtime overheads, we can significantly reduce the GPU memory footprint by up to 3.13× with only 1% runtime performance overhead, resulting in up to 1.28× faster convergence to the same validation quality. In addition to the system optimization, in Echo, we also build GPU memory profiling tools that accurately pinpoint the GPU memory consumption bottlenecks of DNNs and are integrated into the state-of-the-art machine learning framework.
The Coordination of Aging in Place in Ontario: How Health System Design Impedes the Ability to Remain Living at Home
Keywords: Aging
Frailty
Institutional Ethnography
Listening Guide
Policy
System Design

This is a study of the experiences of older adults of advanced age living with complex health conditions, or frailty, and their caregivers as they carry out their everyday activities and work to remain living at home. Methods used combine an Institutional Ethnography (IE) inspired approach, an IE informed adaptation of the Listening Guide, a voice-centred relational approach, and qualitative interviewing with older adults and their caregivers (n=11). This investigation specifically examines how it happens that older people who intended to live out their lives at home may be unable to do so because of coordinating texts, including procedures, processes, policy, programs, legislation and regulation, activated by various actors, and implicated in an Ontario health system that is not designed for a major cohort of its population. Through qualitative data collection, empirical tracing, an extensive examination of aging in place literature, and a review of more than 160 coordinating texts currently activated in Ontario, this study models analytic techniques that can enable the inclusion of accounts from older adults in system design. Findings suggest the need for new skills for today’s health system leaders and demonstrate the need for an integrated healthcare system, systematic planning and better coordination to make aging in place for all older adults a reality.
Investigation of the Expression and Function of Numb Isoforms in Cancer
Keywords: bioinformatics
cancer
endocytosis
integrin
isoform
metastasis

The asymmetrically segregated cell fate determinant Numb was initially identified as an antagonist of the Notch pathway. It was subsequently shown to influence the trafficking of membrane proteins involved in numerous developmental pathways and has been characterized as a tumor suppressor. However, the differing expression patterns of the four protein isoforms of Numb in mammalian systems, and their emerging distinct roles in regulating trafficking of key signaling molecules, greatly confounds our understanding of the tumorigenic role of Numb. Specifically, the expression of exon9 included (Ex9+) Numb isoforms in various tissue types from mouse models is downregulated during development, but is upregulated in multiple cancer types, suggesting that in cancer, modified exon9 splicing could be oncogenic. Here, we generate a NUMB exon9 deletion in human breast cancer cells and show that the loss of NUMB exon9 leads to a significant decrease of spontaneous lung metastasis in an orthotopic xenograft model as well as slower cell growth in vitro. Quantitative mass spectrometry analysis reveals downregulated expression of proteins involved in EMT and ECM organization in cells lacking the Ex9+ Numb isoforms. Furthermore, exon9 deletion reduces surface levels of integrin β5, and downstream signaling to ERK and SRC, consistent with the enhanced lysosomal targeting mediated by the remaining Exon9 skipping Numb isoforms. Pan-tissue analysis on exon usage data from VastDB and GTEx databases supports earlier observations that the exon9 inclusion level of NUMB is higher in stem cells and high turnover tissues. Additionally, significantly greater NUMB exon9 inclusion in a variety of tumor types is observed when compared to tissue matched normal samples using TCGA and GTEx datasets. Greater exon9 inclusion is correlated with a worse progression free survival, but changes in total Numb expression are not associated with progression free survival. Strikingly, in multiple cancer types, greater exon9 inclusion also correlates with lower immune cell infiltration and immune cytolytic activity in the bulk tumor based on transcriptomic expression analysis. These findings indicate that exon9 inclusion, which is switched off during normal development, is turned back on in cancer, and that higher exon9 inclusion may lead to increased metastasis and worse patient outcome.