VictorJuiz/thesis huggingface dataset:
Essays on International Trade and Development

This thesis contains three papers examining topics related to international trade, growth, and development. In chapter 1, I examine the role of buyer-seller relationships on the global platform for the transfer of knowledge across borders, wherein firms can learn about products produced by each other in a transaction. I find that an exogeneous increase in plants’ access to foreign downstream knowledge through exports increases the likelihood that they produce new downstream products. I then build a model of international trade, knowledge spillovers, and growth to analyze the general equilibrium effects of such firm-level innovation on aggregate economic outcomes and find that trade induces growth and a convergence of the technology gaps between countries. Further, firm level innovation activity reduces in response to this convergence reflecting the lower opportunities to learn from foreign firms.In chapter 2, which is based on joint work with Stephen Ayerst, Faisal Ibrahim, and Gaelan MacKenzie, we study the role of knowledge embodied in traded goods for knowledge diffusion. We use US patent citation data to first, construct a knowledge input-output structure, and second, to measure embodied knowledge in products that is useful for the production of innovative ideas in a sector. We find that countries that import more knowledge from the United States that is useful for knowledge production in a specific sector also have increased innovation activity (R, researchers), innovation outputs (patents, citations), and finally employment and output production in that sector. Further, these results are stronger in richer economies, suggesting that they are better able to utilize frontier knowledge to generate new innovations. In chapter 3, which is based on joint work with Marijn Bolhuis and Diego Restuccia, we study how distorted rental markets for agricultural land lead to low agricultural productivity in India. We first recognize that there is large variation in land market institutions across different states in India due to colonial institutional precedence and differences in state-level land reforms implemented post-independence. We find that states with more rental market activity feature less misallocation, and also reallocate land more efficiently over time. Based on this observation, we build a model of land rental markets and heterogeneous farms and estimate land market frictions by state. Land market distortions contribute to about one quarter of the differences in agricultural productivity across states. Without rental activity agricultural productivity falls by 22%, and reallocating land more efficiently can increase agricultural productivity by 29% on average.

Keywords: Growth
Input-Output Linkages
International trade
Knowledge Diffusion
Misallocation
Advisor: Trefler, Daniel
Client-centric Orchestration and Management of Distributed Applications in Multi-tier Clouds

The increasing ubiquity of IoT and “smart” devices in our everyday surroundings presents enormous opportunities to bring novel applications and services close to end-users. As these devices continue to become more powerful, we foresee scenarios where they serve as extensions of the traditional cloud, enabling time-sensitive operations to be directly performed on premises. For composite applications and services based on the microservice and NFV architectures, whose overall performance is highly dependent on the placement of their constituent microservices relative to one another, the mobility of such devices may adversely impact the application’s operational efficiency. These composite applications therefore require an orchestration system to actively manage and reconfigure the microservices so that they continue to meet operational goals and the needs of end-users. Such orchestrators must address the challenges that come with the expected scale, variety, and mobility of resources spread out over multiple tiers and geographical regions.This thesis presents our concept of client-centric orchestration, in which compute and network resources are jointly managed to ensure that clients are able to receive their service(s) at some pre-determined quality level. To this end, we present the design and implementation of a series of management plane components that can be leveraged by a client-centric orchestrator. We first develop a multi-layer telemetry system that is capable of monitoring the metrics of both applications and the underlying infrastructure. An implementation of a client-centric orchestrator is then presented that can dynamically scale and place service replicas to optimize the clients’ perceived network quality. To further augment the orchestrator, we develop SDN-based network control capabilities that it can use to install custom network flows directly into the underlying network and enforce QoS. Lastly, we consider the case where devices are cut off from central management components, and introduce a P2P-based solution that empowers the clients (whether they be end-users or microservices in a composite application) to independently discover nearby service replicas or request allocation of new replicas. Since this work contributes towards the extension of the SAVI multi-tier cloud, we will also share our operational insights, experiences, and lessons learned.

Keywords: Client-centric orchestration
Cloud computing
Network function virtualization
Software-defined infrastructure
Software-defined networking
Telemetry
Advisor: Leon-Garcia, Alberto
Multivariate Prediction of Pain Relief Following Surgical Interventions for Trigeminal Neuralgia: Intersections Between Brain Imaging and Machine Learning

Trigeminal neuralgia (TN) is a chronic neuropathic facial pain disorder characterized by severe lancinating pain. While surgical treatments exist for TN, 20-30% of patients achieve minimal pain relief and require multiple, repeat interventions. Structural neuroimaging of TN has revealed widespread white and gray matter abnormalities in central nervous system and peripheral nervous system areas implicated in sensory and emotional processing of facial pain. While group-level associations have been shown between these abnormalities and TN surgical treatment response, whether these abnormalities are effective predictors of surgical treatment response remain unclear. The overarching goal of this dissertation is to combine structural neuroimaging and machine learning (ML) techniques to identify and understand individual-level predictors of TN surgical treatment response. The main aims are: 1) to investigate the role of pre-treatment trigeminal nerve microstructural diffusivity patterns as predictors of long-term response to surgical treatment for TN; 2) to characterize temporal patterns of trigeminal nerve microstructural diffusivities following surgical treatment for TN with respect to treatment response; 3) to investigate the role of pre-treatment regional brain gray matter morphology as predictors of long-term response to surgical treatment for TN; and 4) to investigate the potential of a ML-derived biomarker (brain age gap estimate; brain-AGE) as a pre-treatment predictor of long-term response to surgical treatment for TN. Study 1 demonstrated that pre-treatment diffusivity patterns within peripheral and brainstem portions of trigeminal nerves can predict long-term response to TN surgery. Study 2 revealed that post-treatment patterns of microstructural diffusivities within trigeminal nerves of TN patients are associated with response to TN surgery and that treatment response is associated with temporally delayed fractional anisotropy reduction within the treatment target. Study 3 identified pre-treatment regional brain gray matter morphology (surface area and cortical thickness) as effective predictors of long-term response to TN surgery. Study 4 demonstrated that brain-AGE was elevated in TN patients and can differentiate long-term responders from non-responders to TN surgery. In sum, this thesis identified novel collections of effective TN surgical treatment response predictors and provided several candidate ML models which may serve as sensible starting points toward personalized surgical treatment response prognostication paradigms in TN.

Keywords: Chronic pain
Machine learning
Magnetic resonance imaging
Pain imaging
Treatment response
Trigeminal neuralgia
Advisor: Hodaie, Mojgan
The Portfolio Diet and Cardiovascular Disease Risk Reduction: Insights from International Prospective Cohort Studies

The Portfolio Diet significantly lowered low-density lipoprotein cholesterol (LDL-C) and several other cardiovascular disease (CVD) risk factors in randomized controlled trials of patients with hyperlipidemia. However, it is not known if the diet lowers CVD risk in other populations. To examine the long-term health effects of the diet in broader populations, we developed a Portfolio Diet Score (PDS) using a food frequency questionnaire (FFQ). The PDS gives positive scores for foods and nutrients recommended in the diet (plant protein, viscous fibre, nuts, phytosterols, and monounsaturated fatty acids), and reverse scores for foods limited in the diet (those high in saturated fat and dietary cholesterol). This dissertation describes the development of and examines the validity of the PDS, and then evaluates the PDS’ associations with incident CVD outcomes and cardiometabolic risk factors in two prospective cohort studies. In chapter 1, we used data from the Toronto Healthy Diet Study to develop and examine the predictive and concurrent validity of the PDS. We found the PDS from the FFQ was associated with LDL-C in the expected direction. The PDS from the FFQ also had reasonable correlations and good agreement with a PDS determined from a 7-day diet record. In chapter 2, we examined associations of the PDS with incident CVD outcomes in the Women’s Health Initiative (WHI). We included ~120,000 postmenopausal women from 1993 through 2017 with a mean follow-up of 15.3 years. In the multivariable-adjusted analysis, the PDS was inversely associated with incident total CVD, coronary heart disease (CHD), and heart failure, but not stroke and atrial fibrillation. In chapter 3, we examined associations of the PDS with several cardiometabolic risk factors in PREDIMED-Plus, a cohort of ~6,000 older adults with metabolic syndrome. Over one year of follow-up, the PDS was inversely associated with markers of glycemic control and adiposity, and triglycerides, but not with LDL-C or other cardiometabolic risk factors. In conclusion, we found reasonable validity of the PDS as determined by an FFQ. The findings suggest that the Portfolio Diet is associated with lower risk of CVD and CHD, and several cardiometabolic risk factors, in different populations.

Advisor: Sievenpiper, John
The Contested Academy: African Canadian Women’s Experiences as Tenured, Tenure Stream and Non-tenured Faculty

This thesis explores the experiences of Black women who are in tenured, tenure-stream, and non-tenured faculty positions and presents how Black women negotiate their intersectional identities in the academy. The study documents their self-identifications and struggles with the academy in terms of power relations in their respective universities, including racial and sexual discrimination. In addition, the study explores the career paths of Black women faculty from contract faculty to full professor. Methodologically, the study uses Black Feminist theorizing along with autoethnography in order to explore the nature of the experiences of Black Canadian women faculty within the academy. I interviewed 13 self-identified Black women across Canadian universities, including myself as the fourteenth key informant. This study reveals a complex and rich text of how Black women see themselves in the university, their experiences with multiple and overlapping oppressions and how this affects their careers, and finally, their contributions to the academy and their visions of success.

Keywords: Black
Black Feminism
Faculty
Higher Education
Tenure
Women
Advisor: Muzzin, Linda
One-Dimensional MEMS Optical Phased Array Systems Based on Surface Micro-Machined Silicon Mirrors for Scanning LiDAR Applications

Optical phased array (OPA) systems are an emerging technology for lightweight and miniature LiDAR scanners due to their compact size and construction that eliminate the need for robust physical moving parts, leading to a fast response, high reliability, and low power requirements. MEMS based OPA systems generally demand narrow and tightly spaced suspended microstructures with high-aspect-ratios in the lateral dimensions, rendering some significant challenges in the system design, fabrication, and integration. This thesis presents the first MEMS based OPA system that is fabricated using a conventional surface micromachining process, leading to a simplified design for the OPA technology. The one-dimensional OPA device utilizes an array of piston-type micromirrors which act as optical phase shifters. Each metal coated polysilicon micromirror is suspended by a pair of serpentine springs and is individually actuated at low voltage by a separate electrostatic parallel plate actuator. The field of view obtained by the prototype is measured as 4.76°. The low-mass micromirrors have a response time of 6.5 µs and an out of plane actuation stroke of 0.16 µm at a dc bias voltage of 55 V which is equal to one-quarter of the laser wavelength (650 nm) used, translating into the desired optical phase shift of π radian. LiDAR scanners are usually required to generate hundreds to thousands of scan points along a far-field scan line which leads to a large number of active phase shifters in the arrays and high complexity in control. A novel one-dimensional OPA system based on a limited number of pitch tunable silicon micromirrors is presented for laser steering with high angular resolution. The in-plane pitch tuning of all the physically connected micromirrors is realized by a pair of lateral electrostatic comb-drive actuators which require only one conductive layer. The longitudinal motion of the actuators is linearly guided by a group of mirror-positioned flexures. During the fabrication steps, an optical path difference is realized by slightly elevating every other suspended micromirror along the array in order to form the required phase shift pattern. A pitch tuning of the prototype at 30 V results in an optical steering range of 0.04° with an angular resolution of 0.002°.

Keywords: Autonomous Vehicles
LiDAR Scanner
Micro Electromechanical Systems
Optical Phased Array
Silicon Micromirror
Surface Micromachining
Advisor: Ben Mrad, Ridha
He, Siyuan
Measurement of Higgs couplings to top quarks and τ leptons with the ATLAS detector

Since the discovery of the Higgs boson in 2012 during the first run of the Large Hadron Collider (LHC) at CERN, extensive measurements have been performed to characterize its properties. Its mass, spin, parity and couplings have been studied in detail with no significant deviations from the SM predictions observed. The second run of the LHC saw incredible progress with the addition of new measurements. This thesis highlights the measurements of Higgs couplings to third generation fermions, first with the observation of the ttH process and then through improved pp → H → ττ cross section measurements. The search for the ttH process is discussed in the context of the ttH → multilepton analysis, with an emphasis on final states with τhad-vis. A ttH cross section measurement, obtained in combination with results from tt(H → γγ), tt(H → ZZ* → 4ℓ) and tt(H → bb), is also presented. All results are found to be compatible with the Standard Model predictions. The study of Higgs decays involving τ leptons is expanded upon with the measurement of the pp → H → ττ cross section using the full Run 2 dataset, and a new method to estimate the largest background to this measurement is introduced. The improvement in the precision of pp → H → ττ measurements coupled with an increased sensitivity to broader regions of phase space allows for a deeper scrutiny of the Standard Model predictions, with the theory still providing an accurate description of the experimental results.

Keywords: ATLAS detector
Higgs boson
tau lepton
Advisor: Savard, Pierre
Cross-species Modeling of Replication Repair Deficient Cancers

Replication repair deficiency (RRD) is a leading cause of cancer hypermutation. RRD cancers are found across tissue types, often resistant to chemo-radiation therapy, and therefore universally lethal. Among children, germline deficiencies in either replication repair mechanism—DNA polymerase proofreading or the mismatch repair (MMR) system—result in early-onset cancers which were considered incurable. Despite recent success of immune checkpoint inhibition (ICI) in treating RRD cancers, most tumors remain refractory or unresponsive. Novel treatments and robust models to study RRD cancers are lacking.Using a multi-omics approach, we found that RRD hypermutant cancers are enriched for RAS/MAPK mutations, exhibited increased RAS/MAPK pathway activity, and responded to MEK inhibition. Treatment of patients with RRD gliomas revealed durable responses to MEK inhibition, suggesting these tumors are addicted to oncogenic pathways resulting in favorable response to targeted therapies. To better study hypermutant cancers in vivo, we established mouse models harboring cancer-associated POLE mutations P286R and S459F, which caused rapid yet distinct time to cancer initiation, enabled stratification of POLE mutations into 3 groups based on clinical phenotype and mutagenicity, and mirrored human cancer ultrahypermutation and mutational signatures. These animals primarily developed lymphomas which could not be prevented, and were likely exacerbated by ICI, as observed in humans. We then used the Pole models to study combined RRD (MMRD+Pole mutations), which commonly occur in childhood hypermutant cancers. We developed novel brain and gastrointestinal-specific RRD mouse models. Both models resulted in highly penetrant, rapid onset cancers that genomically mimicked human RRD cancers. We observed that increased RRD likely contributes to mutational loads not sustainable for normal cell function as manifested by maldevelopment and malfunction of colon and brain from MMRD+Pole mutant homozygous mice. Moreover, serial passaging of RRD brain tumors revealed differences in mutation accumulation between intracranially and subcutaneously transplanted tumors in immunocompromised and immunocompetent animals, likely due to differences in immune surveillance within and outside the brain. Collectively, our observations provide insights into the carcinogenesis of POLE-driven tumors, information for genetic counselling, surveillance, and immunotherapy for patients. Finally, this work provides insight on immune editing, and platforms to further study RRD cancers in vivo.

Advisor: Tabori, Uri
Proportionate Sentencing within the Criminal Records Act

This paper analyzes the negative impact that Canada’s criminal records regime has on sentencing judges’ ability to proportionately sentence. The advent of the criminal record check as a risk-management tool in the private sector has increased the burden of the modern criminal record. Although the current legislative push for making record suspensions more accessible is welcome, it is best analogized as a push to reduce the mandatory minimum sentences that currently apply to criminal records. The regime continues to fall short of affording sentencing judges the flexibility to craft sentences that impose punishment that is proportionate to the circumstances of an offence and the characteristics of the offender. In response to this shortcoming, this paper proposes a modified record suspension regime that provides for judicial discretion in the longevity of Canadian criminal records.

Keywords: Criminal Law
Criminal Records
Proportionality
Sentencing Law
Advisor: Stewart, Hamish
Emergent Phenomena in Correlated Materials with Strong Spin-orbit Coupling

Correlated materials have a long history in the research of the condensed matter community, and in the past couple of decades effects of spin-orbit coupling have been recognized for emergent unconventional phenomena in quantum materials. A series of transition metal compounds have been proposed to exhibit exotic states of mater. Among them, quantum spin liquids are highly entangled states of matter where strongly interacting magnetic moments do not show long range magnetic order. In general, strong spin-orbit coupling entangles spin and orbital degrees of freedom into an effective pseudospin moment. For d^5 materials like Sr_2IrO_4, beta-Li_2IrO_3, and alpha-RuCl_3, unconventional bond-dependent exchange interactions among jeff=1/2 pseudospins are expected. Although stabilization of exotic states is possible within these bond-dependent interactions, usually a unconventional magnetic order may set in due to other small interactions. Beyond the pseudospin moment jeff=1/2 picture, a bond-dependent interaction may exist among higher spin moments, but it is unclear how such an interaction arise in transition metal systems. Understanding the microscopics of how these interactions arise and how to manipulate them is important in characterizing the nature of a phase, tuning the systems into different regimes, and identifying new candidate materials. In this thesis, we provide the microscopic theories for a certain set of pseudospin systems, and their implications. In the first part, the unconventional counter-rotating magnetic order in beta-Li_2IrO_3 is addressed from the perspective of a hidden symmetry of a minimal jeff=1/2 model. Later, a microscopic mechanism for a higher spin S model with bond-dependent interactions is proposed, where S=1 and S=3/2 cases are addressed explicitly. In the last part, we present ab initio results that allow us to estimate and characterize the spin interactions of related materials. Finally comments on open questions and directions for future studies are summarized.

Advisor: Kee, Hae-Young