VictorJuiz/thesis huggingface dataset:
(Sparse) Exchangeable Random Graphs
Keywords: Exchangeability
Machine learning
Network science
Random graphs
Sampling
Statistics

Many common statistical models for network valued datasets fall under the remit of the graphon (cf. dense exchangeable) framework. These models are defined by a multi-dimensional analogue to de Finetti style exchangeability that provides a natural formalization of the requirement that the labels of a random graph carry no information about its structure. This seemingly innocuous assumption implies that the corresponding networks are densely connected: a property that rarely holds for real-world networks of practical interest. This thesis develops the statistical theory for network valued data; in particular, generalizing the dense exchangeable models to the sparse graph regime. The key ingredient is a novel notion of exchangeability for graphs based on a point process representation of networks. The main results are: The construction of a new modeling framework through a de Finetti style representation theorem. The characterization of several important sampling distribution properties of the resulting random graphs. The introduction of a generic non-parametric estimator (analogous to the empirical measure) for these models. And, finally, the recasting of the core exchangeability concepts in the language of sampling, which leads to a clear articulation of the sampling design naturally associated with the models, as well as a unification with the theory of limits of large (sparse) graphs.
Investigating brittle rock failure and associated seismicity using laboratory experiments and numerical simulations
Keywords: Acoustic emission
Fault evolution
FDEM
micro-CT
Microseismicity
Rotary shear test

Rock failure process is a complex phenomenon that involves elastic and plastic deformation, microscopic cracking, macroscopic fracturing, and frictional slipping of fractures. Understanding this complex behaviour has been the focus of a significant amount of research. In this work, the combined finite-discrete element method (FDEM) was first employed to study (1) the influence of rock discontinuities on hydraulic fracturing and associated seismicity and (2) the influence of in-situ stress on seismic behaviour. Simulated seismic events were analyzed using post-processing tools including frequency-magnitude distribution (b-value), spatial fractal dimension (D-value), seismic rate, and fracture clustering. These simulations demonstrated that at the local scale, fractures tended to propagate following the rock mass discontinuities; while at reservoir scale, they developed in the direction parallel to the maximum in-situ stress. Moreover, seismic signature (i.e., b-value, D-value, and seismic rate) can help to distinguish different phases of the failure process. The FDEM modelling technique and developed analysis tools were then coupled with laboratory experiments to further investigate the different phases of the progressive rock failure process. Firstly, a uniaxial compression experiment, monitored using a time-lapse ultrasonic tomography method, was carried out and reproduced by the numerical model. Using this combination of technologies, the entire deformation and failure processes were studied at macroscopic and microscopic scales. The results not only illustrated the rock failure and seismic behaviours at different stress levels, but also suggested several precursory behaviours indicating the catastrophic failure of the rock. Secondly, rotary shear experiments were conducted using a newly developed rock physics experimental apparatus ERDÎź-T) that was paired with X-ray micro-computed tomography (ÎźCT). This combination of technologies has significant advantages over conventional rotary shear experiments since it allowed for the direct observation of how two rough surfaces interact and deform without perturbing the experimental conditions. Some intriguing observations were made pertaining to key areas of the study of fault evolution, making possible for a more comprehensive interpretation of the frictional sliding behaviour. Lastly, a carefully calibrated FDEM model that was built based on the rotary experiment was utilized to investigate facets that the experiment was not able to resolve, for example, the time-continuous stress condition and the seismic activity on the shear surface. The model reproduced the mechanical behaviour observed in the laboratory experiment, shedding light on the understanding of fault evolution.
Quantification of Belowground C Flow from Root Exudation of Peatland Sedges and Shrubs
Keywords: Radiative transfer modelling
Root depth distribution
Root exudation
Simulation model

A large range of labile organic compounds are secreted by roots into the soil, which inevitably leads to changes in nutrient availability and C cycling. Little is known about root exudation variability among species, or at the individual root level, hampering estimates of total C deposition. Environmental controls are believed to influence root exudation at the single root scale, yet are rarely accounted for. Quantifying exudation heterogeneities within the root system permits more accurate upscaling to the whole plant and landscape level, provided the sites of exudation and belowground biomass are well quantified. Root exudate composition was characterized in two model organisms - Eriophorum vaginatum and Rhododendron groenlandicum utilizing localized sampling of root segments. E. vaginatum roots were distinguished into three classes by age, and R. groenlandicum into four classes by fine root abundance and root diameter. Considerable variations in the total efflux, as well as the composition of exudates, was documented at both the species and root class level, confirming that exudation is not homogenous within the root system. Existing root biomass data has little correlation with the vertical gradients of exudation. Whole plant root systems were excavated and digitally mapped at sufficient detail to explicitly distinguish the depth distribution of the roots associated with exudation. Measurements of the normalized root length fraction per depth interval were tested against a variety of density distribution models to infer a suitable function to represent roots for upscaling a single root to the landscape scale. The abundance of key species such E. vaginatum that deposit C directly into the anoxic zone are poorly mapped in peatlands. A new detection methodology, based on phenological timing and the spectral contrast of decomposing litter, was investigated utilizing an expanded version of PROSAIL. Close range imagery indicated the calibrated model was capable of quantifying decaying monocot litter as a unique class, which bodes well for detection at the landscape scale. The studies presented in this thesis document root exudation rates and root distribution data necessary to conduct a simple upscaling from the single root to the landscape level. Collectively, they permit the C flow via the exudation pathway to be estimated, with consideration for vertical gradients that partition exudation into the oxic and anoxic zone.
Diagnosing and Treating Infectious Diseases and Antimicrobial Resistance Using Gold Nanoparticles
Keywords: Antimicrobial resistance
Clinical Diagnosis
Gold nanoparticles
MNAzyme
Nucleic acid detection
Photothermal therapy

The continued emergence of infectious diseases and the development of antimicrobial resistance represent a major global health challenge in the 21st century. Rapid and accurate diagnosis of infectious pathogens is vital for both the treatment and prevention of new forms of antimicrobial resistance. The current advances in nanotechnology have afforded the development of new simple and rapid diagnostic assays as well as novel therapeutic technologies. This thesis presents new and original work that exploits the physical and chemical properties of gold nanoparticles to diagnose and treat infectious diseases. The contributions to the field are two-folds. Earlier work was aimed at developing a rapid, sensitive and simple platform for the detection of infectious diseases and antimicrobial resistance, where signal readout could be observed with the naked eye. Second, the photo-thermal characteristics of gold nanoparticles were used to create a novel plasmonic thermogel that disinfected antimicrobial resistant bacteria in surgical wounds, preventing the use of a broad-spectrum antibiotic. It is anticipated that the contribution of this thesis will continue to advance the implementation of gold nanoparticles for the development of commercial diagnostics and therapeutics. Collectively, this work should improve the mitigation of infectious diseases and reduce the risk of the development of further antimicrobial resistance.
Statistics, Formation and Stability of Exoplanetary Systems
Keywords: Exoplanets
Machine Learning
Numerical Methods
Physics
Planetary Science
Statistics

Over the past two decades scientists have detected thousands of exoplanets, and their collective properties are now emerging. This thesis contributes to the exoplanet field by analyzing the statistics, formation and stability of exoplanetary systems. The first part of this thesis conducts a statistical reconstruction of the radius and period distributions of Kepler planets. Accounting for observation and detection biases, as well as measurement errors, we calculate the occurrence of planetary systems, including the prevalence of Earth-like planets. This calculation is compared to related works, finding both similarities and differences. Second, the formation of Kepler planets near mean motion resonance (MMR) is investigated. In particular, 27 Kepler systems near 2:1 MMR are analyzed to determine whether tides are a viable mechanism for transporting Kepler planets from MMR. We find that tides alone cannot transport near-resonant planets from exact 2:1 MMR to their observed locations, and other mechanisms must be invoked to explain their formation. Third, a new hybrid integrator HERMES is presented, which is capable of simulating N-bodies undergoing close encounters. HERMES is specifically designed for planets embedded in planetesimal disks, and includes an adaptive routine for optimizing the close encounter boundary to help maintain accuracy. We find the performance of HERMES comparable to other popular hybrid integrators. Fourth, the longterm stability of planetary systems is investigated using machine learning techniques. Typical studies of longterm stability require thousands of realizations to acquire statistically rigorous results, which can take weeks or months to perform. Here we find that a trained machine is capable of quickly and accurately classifying longterm planet stability. Finally, the planetary system HD155358, consisting of two Jovian-sized planets near 2:1 MMR, is investigated using previously collected radial velocity data. New orbital parameters are derived using a Bayesian framework, and we find a high likelihood that the planets are in MMR. In addition, formation and stability constraints are placed on the HD155358 system.
CNS hormonal and nutritional regulation of glucose and energy homeostasis
Keywords: Diabetes
Dorsal Vagal Complex
Glucose Homeostasis
Hypothalamus
Metabolism
Obesity

The mediobasal hypothalamus (MBH) and the dorsal vagal complex (DVC) regions contain a leaky blood-brain barrier and therefore act as critical sites of action for circulating hormones and nutrients on glucose and energy homeostasis. For example, hormones such as insulin, leptin and glucagon and nutrients such as lipids, glucose and amino acids act in the MBH and DVC to regulate hepatic glucose production, glucose tolerance, food intake and body weight, but the underlying CNS sensory mechanisms in rodents and humans remain elusive. The current dissertation unveils novel mechanisms for glucagon action in the MBH and glycine sensing in the DVC in rats and mice that maintain glucose and energy homeostasis. In Study 1, we discovered that KATP channel is necessary for MBH glucagon action to exert glucose control. In Study 2, we found that pharmacological and molecular manipulation of glycine transporter 1 in the DVC enhances glycine sensing and potently regulates glucose and energy homeostasis. In conclusion, I have discovered novel mechanisms for glucagon and glycine sensing in the brain that regulate glucose and energy homeostasis, and have unveiled CNS therapeutic targets for diabetes and obesity.
Self-Assembled Carbon-Polyoxometalate Composites for Electrochemical Capacitors
Keywords: biochar
carbon
energy storage
polyoxometalates
supercapacitors
surface-modification

The development of high performance yet cost effective energy storage devices is critical for enabling the growth of important emerging sectors from the internet of things to grid integration of renewable energy. Material costs are by far the largest contributor to the overall cost of energy storage devices and thus research into cost effective energy storage materials will play an important role in developing technology to meet real world storage demands. In this thesis, low cost high performance composite electrode materials for supercapacitors (SCs) have been developed through the surface modification of electrochemically double layer capacitive (EDLC) carbon substrates with pseudocapacitive Polyoxometalates (POMs). Significant fundamental contributions have been made to the understanding of all components of the composite electrode including the POM active layer, cation linker, and carbon substrate. The interaction of different POM chemistries in solution has been studied to elucidate the novel ways in which these molecules combine and the mechanism underlying this combination. A more thorough understanding regarding the cation linkerâ s role in electrode fabrication has been developed through examining the linker properties which most strongly affect electrode performance. The development of porosity in biomass derived carbon materials has also been examined leading to important insights regarding the effect of substrate porosity on POM modification and electrochemical properties. These fundamental contributions enabled the design and performance optimization of POM-carbon composite SC electrodes. Understanding how POMs combine in solution, allowed for the development of mixed POM molecular coatings with tunable electrochemical properties. These molecular coatings were used to modify low cost biomass derived carbon substrates that had been structurally optimized to accommodate POM molecules. The resulting electrode composites utilizing low cost materials fabricated through simple scalable techniques demonstrated (i) high capacitance (361 F g-1), (ii) close to ideal pseudocapacitive behavior, (iii) stable cycling, and (iv) good rate performance.
Multiplexed Microfluidics for the Study of Photosynthetic Microorganisms
Keywords: Algae
Microfluidics
Photosynthesis

The ability of large datasets of simple metrics (i.e. growth rate, lipid accumulation) to contribute to the understanding of microalgal photosynthesis is explored in this thesis. Specifically, three tools were developed, (i) a microfluidic multiplexed irradiance assay, which was composed of a microfluidic chip and a liquid crystal display; (ii) a second order mathematical model which can predict the growth under fluctuating light for periods ranging from a day to one under second and; (iii) a combinatorial assay for studying the mixed effect of light and nitrogen on growth and lipid accumulation. The multiplexed microfluidic irradiance assay (Microalgae on display) was capable of producing a large number of independent light treatments (200+), while avoiding the self-shading typical of flask-scale experiments. A set of linear ordinary differential equations were capable of capturing a second order behavior of photosynthetic growth, specifically a penalty at intermediate frequencies. This behavior lies outside the prevailing understanding of a high and low frequency limit. Lastly, the interplay between irradiance intensity and ammonium was resolved, showing that ammonium concentration plays a role at high light intensities only.
Oral Glucocorticoids: Fracture Risk and Benefit of Osteoporosis Pharmacotherapy
Keywords: Drug effectiveness
Fracture risk
Glucocorticoid-induced osteoporosis
Meta-analytic methods
Pharmacoepidemiology

Oral glucocorticoids are potent anti-inflammatory and immunosuppressant agents used to treat and control several conditions. However, oral glucocorticoid exposure leads to an osteoporotic state characterized by increased bone loss and fracture risk. Bone loss is rapid upon oral glucocorticoid exposure, particularly in the vertebra. Osteoporosis treatment are often recommended for patients receiving oral glucocorticoids to prevent fracture. However, osteoporosis drug benefit in randomized controlled trials and observational studies is not yet established among oral glucocorticoid users. This research aimed to estimate fracture rates among new and ongoing oral glucocorticoid users and assess the benefit of osteoporosis drugs. First, meta-analytic methods were leveraged to pool fracture data from randomized clinical trials and examine fracture rates by oral glucocorticoid exposure history. Second, network meta-analysis was used to estimate the relative efficacy of osteoporosis drugs among oral glucocorticoid users. Third, using Ontario administrative healthcare data, three cohort analyses were conducted to assess the effectiveness of alendronate, etidronate, and risedronate in reducing fracture risk among chronic oral glucocorticoid users. Results of the meta-analytic analyses (study 1) showed that vertebral and non-vertebral fracture rates are higher among patients starting a new oral glucocorticoid treatment course than patients with ongoing use. These findings are consistent with higher bone loss among glucocorticoid initiators than ongoing users. The network meta-analysis (study 2) showed etidronate, risedronate, and teriparatide as efficacious in preventing vertebral fracture; teriparatide was identified as the most efficacious treatment followed by risedronate. No treatment was associated with a reduction in hip fracture risk, yet the data were limited to small pooled samples of heterogeneous patients in clinical trials. Results of the large population-based observational research (study 3) support the effectiveness of alendronate and risedronate to reduce hip fracture risk, and all three oral bisphosphonates to reduce vertebral fracture risk. The findings of this dissertation draw attention to the high fracture risk among new oral glucocorticoid users and provide evidence of the benefit of osteoporosis drugs early upon oral glucocorticoid exposure to reduce fracture risk. Further research is required to examine fracture risk by different glucocorticoid exposure patterns and estimate the comparative effectiveness between osteoporosis drugs.
A Learning Based Robot Interaction System for Multi-User Activities
Keywords: Human-Robot Interaction
Learning from Demonstration
Socially Assistive Robotics

The population of the world is rapidly aging and there is presently an increasing demand for residential care facilities to provide care for older adults. Understimulation can be a major concern in such facilities due to high resident-to-staff ratios and a decreasing number of healthcare staff to facilitate cognitive, social, and physical activities for older adults. Currently, socially assistive robots are being developed to assist in providing such stimulation. However, the existing robots are limited to only facilitating a set of activities that have been pre-programmed on the robot and cannot be customized to the needs of a facility. Furthermore, the majority consider only one-on-one activities, rather than providing stimulation to groups of users at the same time. This thesis focused on developing a learning based interaction system for socially assistive robots to: 1) autonomously facilitate multi-user activities while providing individualized assistance; 2) learn new customized activities from caregivers; and 3) personalize robot assistive behaviours to obtain user compliance. Numerous human-robot interaction experiments were conducted with the system integrated into the socially assistive robot Tangy for the multi-user activity of Bingo. The participants for the experiments consisting of caregivers and older adults. The results showed that: 1) participants had positive attitudes towards interacting with the robot and found it easy to use, 2) older adults were engaged during the activity and complied with the robotâ s behaviours, and 3) caregivers were able to successfully teach a new activity to the robot with moderately low perceived workload.
Essays in the Economics of Violence and Conflict
Keywords: Applied Microeconomics
Development Economics
Political Economy

Chapter 1 studies the impact of the arrival of displaced individuals on the wages of residents at receiving locations. To do this, the study employs an enclave IV strategy, which exploits both social distance between origin and destination locations and forced migration. I compare the effects on four different subgroups of the population, partitioned by skill (low-skilled versus high-skilled) and by gender. The analysis suggests that a conflict-induced increase in population leads to a short-run negative impact on wages, but that subsequent out-migration from receiving municipalities helps to mitigate these effects. Chapter 2 studies the relationship between political violence and congressional decision-making. I examine how politicians and their constituents respond to attacks by FARC, Colombia's largest rebel group, using data from politicians' Twitter accounts and roll-call voting records, and employing both an event study and a difference-in-differences research design. The analysis finds that tweets from incumbent politicians and tweets which exhibit "right-wing" language receive higher user engagement (a proxy for popular support) following rebel attacks. In congress, politicians were more likely to align their legislative votes with the right-leaning ruling party following an attack, before the government started negotiations with the rebels in 2012. However, this relationship breaks down after the start of the peace process. The empirical results are consistent with a political economy model of legislative behaviour in which events that shift median voter preferences, and the presence of rally 'round the flag effects, elicit different politician responses depending on the policy position of the ruling party. Chapter 3, joint work with Gustavo Bobonis and Roberto Castro, provides evidence of the long-term relationship between male-to-female spousal violence and the Oportunidades conditional cash transfer program in rural Mexico. It uses data from three nationally representative surveys that include detailed information on the prevalence of spousal abuse and threats of violence against women. Constructing comparable groups of beneficiary and nonbeneficiary households within each village to minimize potential selection biases, the analysis finds that, in contrast to short-run estimates, physical and emotional abuse rates over the long term do not differ significantly between existing beneficiary and nonbeneficiary couples.