VictorJuiz/thesis huggingface dataset:
On Love: Between Lacan and Badiou
Keywords: Alain Badiou
Jacques Lacan
Love
Philosophy
Psychoanalysis

This thesis considers love through the interlacing of psychoanalyst Jacques Lacan and philosopher Alain Badiou. Engaging with the problematic of love as an in-between (metaxú) in Western thought and intervening in the contemporary scholarship around Lacan and Badiou, this thesis examines love in the works of Lacan and Badiou and conceptualizes the consequences that remain implicit and unexplored in the two authors’ thoughts on love. Chapter 1 addresses love through mathematics. Noting that mathematics plays a pivotal role in Lacan’s and Badiou’s approaches to love, I discuss love through the sexuation formulas, numericity, modality, topology, and knot theory, elaborating the concept of amorous void. Chapter 2 addresses love through politics. Noting that politics resides where the interlacing of Lacan and Badiou reaches a peak, I examine the enigmatic knot between love and politics through the contemporary crisis of love, the reinvention of philia, community, and humanity, elaborating the concept of amorous unpower. Chapter 3 addresses love through antiphilosophy and philosophy. Referring to Japanese writer Murakami Haruki’s Tony Takitani as a facilitator for the dialogue between antiphilosophy and philosophy, I examine how love straddles both the psychoanalytic symptom and the philosophical truth, the analytic act and the philosophical operation. I conclude this chapter by elaborating the concepts of sinthomatic truth and archiamorous acts. Chapter 4 reads Letter to D by French philosopher André Gorz. Discussing Gorz and Dorine’s amorous itinerary from their first encounter to their joint suicide, I address how Gorz and Dorine weave both the Lacanian side and the Badiouian side through their “Bacanian” love. In Conclusion, I revisit love as an in-between in relation to intermediate daemons in Plato’s Epinomis, from which are drawn the interlacing of the analyst as a participant of pain and the philosopher as a discerner of truth. Developing the problematic implied in this interlacing, I argue that the subject of love comes between the enigma of love as the loveless that is indiscernible to love and the principle of love as the love that infinitely surpasses itself.
Mating costs and gametic barriers to reproduction
Keywords: Gametic isolation
Reproductive barriers
Sexual Selection
Speciation

Mating is essential to many organisms for their continued existence, and yet mating is costly. However, the fitness costs–which may immediately affect the individuals involved, or may affect their future reproductive output, are not often quantified. I assess costs that are acquired at different periods of the mating process–in search of a mate and gametic interactions after copulation. I first quantify the cost of mate searching of a monogynous spider measured by male longevity and I additionally examine how mate searching affects subsequent mating behaviours and performance. I find evidence for behavioural plasticity in males influenced by mate search duration to maximize female egg laying which may be mediated by male seminal fluids and/or female cryptic choice. I then use transparent organisms, Caenorhabditis nematodes, to identify a novel form of gametic isolation using 10 different species. This sperm mediated form of gametic isolation likely evolved from intra-species sperm competition, resulting in incompatibilities as a byproduct of competitive sperm in inter-species matings that caused early death, sterility, and invasive sperm. I further explored sperm-mediated gametic isolation in Caenorhabditis from the perspective of inter-species interactions by experimentally evolving populations with mixed species for six generations to show reproductive interference at the population level. Finally, I screened 25 genetic mutants and phenotyped 99 nearly isogenic lines of Caenorhabditis to identify genetic contributions to gametic isolation (i.e. speciation genes). I identified candidate genes that fall into two categories of phenotypic defects: ovulation defects increase the incidence of sperm invasion, whereas sperm signaling defects reduce the incidence of sperm invasion. These findings and novel methods add to our understanding of how costly mating can be, and how gametic interactions, in particular, contribute to reproductive isolation in Caenorhabditis.
Managing Software Evolution Through Semantic History Slicing
Keywords: Evolution management
Program analysis
Software changes
Version control

Software change histories are results of incremental updates made by developers. As a byproduct of the software development process, change history is surprisingly useful for understanding, maintaining and reusing software. However, traditional commit-based sequential organization of version histories lacks semantic structure and thus is insufficient for many development tasks that require high-level, semantic understanding of program functionality. In this dissertation, we propose a new semantics-based view of software version histories, where a set of related changes satisfying a common high level property (also known as slicing criteria) is recognized as a semantic history slice. As one concrete instantiation, test cases exercising a software functionality can be used as slicing criteria to identify changes implementing the particular functionality. Specifically, we present a family of automated techniques which analyze the semantics of historical changes and assist developers in many practical software evolution tasks. First, we introduce CSlicer, an efficient static history slicing algorithm which requires only a one-time effort for compilation and test execution. It mostly relies on static analysis of dependencies between change sets and is therefore inexpensive in terms of running time but can be imprecise. Second, we present Definer, a dynamic history slicing algorithm based on delta refinement. It executes tests multiple times and observes the test results while attempting to shorten the history slices iteratively. The semantic slices found by the dynamic approach are guaranteed to be minimal, but the running time can be much longer. Finally, we describe the design and implementation of a Web-based semantic slicing framework CSlicerCloud which aims to find balance between performance and precision, unifies different history slicing algorithms and provides software developers a flexible and ready-to-use environment for various evolution management tasks. We have successfully applied the history slicing techniques in many development tasks including creating focused pull requests, back-porting bug fixes, locating feature implementations and building feature models to assist evolution understanding. For validation, we evaluate our approaches on a benchmark of developer-annotated version history instances obtained from real-world open-source software projects from GitHub.
Conceptualization, Measurement, and Association of Underemployment to Mental Health Inequities between Immigrant and Canadian-born Labour Force Participants
Keywords: discrimination
immigrants
mental health
refugees
social determinants
underemployment

This thesis aims to increase understanding of the association of underemployment (unemployment or overqualification) to mental health inequities between immigrant and Canadian-born labour force participants. The first paper provides a theoretical framework to guide design, analyses and interpretation of findings for this thesis, and future research on social determinants of mental health inequities. The second paper uses the Canadian Community Health Survey (CCHS) Cycle 1.2 to assess the construct validity of self-rated mental health (SRMH) for the overall population, and sub-groups by immigrant status and sex. Positive associations between SRMH and a comprehensive array of mental morbidity measures were large and consistent, but a sizeable percentage of respondents with mental morbidity did not rate their mental health as fair/poor. SRMH is useful for assessing social determinants of inequities in general mental health, but not specific mental health morbidities. The third paper uses CCHS Cycle 2.1 (2003) to examine the association of underemployment to fair/poor self-rated mental health (SRMH) in: 1. labour force participants (18-64yrs) in Canada, and 2. between a. immigrants vs. Canadian-born labour force participants, and b. recent immigrant (
Exploring Functional Neuroplasticity and the Associations with Outcomes of Advanced Gross Motor Interventions for Children with Cerebral Palsy
Keywords: cerebral palsy
fMRI
functional neuroplasticity
gross motor

Improvement of advanced gross motor skills is a key rehabilitation goal of children with cerebral palsy (CP), given their underlying brain injury, motor impairments, and physical activity participation possibilities. Evidence for potential functional neuroplastic change following gross motor training is lacking, and may provide important indicators that could advance intervention design to target children’s goals. This research focused on independently ambulatory children with hemiplegic CP (HCP) (i.e., those with unilateral motor involvement), and with diplegic CP (DCP) (i.e., those with both legs involved). In the first study, an ankle dorsiflexion functional magnetic resonance imaging (fMRI) paradigm was refined and optimized to calculate the ratio of hemispheric activity in the primary motor cortex (M1) and overall M1 activation volume. This fMRI paradigm was then used in two linked studies that explored relationships between changes in M1 activation and changes in advanced motor skills following goal-directed gross motor interventions for children with HCP and DCP. Lower limb M1 functional connectivity was also probed using resting state fMRI. Individual changes in fMRI outcomes were observed, with no significant group change. Three patterns of change in the laterality of M1 activation were identified: maintenance of principally contralateral activation (i.e. typical motor control), increased contralateral activation, or increased ipsilateral activation. Relationships were observed between motor skill gains and M1 activation during ankle dorsiflexion on the more affected/non-dominant side. For children with DCP, increased ipsilateral activity was associated with motor skill improvements. In both HCP and DCP, a smaller cortical activation volume was a predictor of motor skill gains. These exploratory findings suggest that M1 activation may be related to motor skill change. This investigation of lower limb functional neuroplasticity is an important step towards developing evidence of the underlying neural mechanisms of advanced gross motor skill improvement following interventions for children with CP.
Delineating the Cardio-Myogenic Hierarchy during Mouse Embryonic Development
Keywords: cardiac progenitor cells
cell surface capture
Frizzled 4
mass spectrometry
mouse pluripotent stem cells

The identification of cell surface proteins on stem cells or stem cell derivatives is a key strategy for the functional characterization, isolation, and understanding of stem cell population dynamics. We have turned to cell surface mass spectrometry to increase the candidate pool of membrane proteins on cardiac progenitor cells (CPCs). Specifically, we examined the expression of surface markers on CPCs using an integrated mass spectrometry and microarray-based approach. We analyzed the genome and surface proteome of cardiac progenitors generated from the stage-specific differentiation of mouse (m) and human (h) pluripotent stem cells (PSCs). We have identified and characterized Frizzled 4 (FZD4) as a new marker for lateral plate mesoderm (LPM). We also utilized FZD4 as a marker, in conjunction with fetal liver kinase 1 (FLK1) and platelet derived growth factor alpha (PDGFRA) and demonstrated an increase in CPC purity and a subsequent increase in cardiomyocyte (CM) enrichment. Additionally, we have found FZD4 is also expressed in the hPSC system and results in a similar enrichment in CM. Furthermore, we showed that NORRIN can be presented to the FZD4 receptor to induce Wingless-related integration site (WNT) signaling-mediated proliferation, resulting in an increase in CM output from CPCs. This demonstrates the value in knowing the set of surface markers present on a cell at a specific stage of development and the potential to leverage that knowledge into more efficient cell differentiation protocols. Further validation of the function of FZD4 is also being established in a preliminary in vivo study. The identified surface markers also have the potential to isolate cell types not only within the CPC stage, but within the PSC, epiblast, and primitive streak stages as well. These markers have been compiled into a preliminary cell-cell communication network model overlaid with an initial alternative slicing analysis to determine potential mechanisms that impact cell signaling during early CPC development. In summary, the application of a systems biology approach as demonstrated in this thesis, greatly expanded the number of surface markers available and upon further characterization and validation, can improve our understanding of cardiac biology.
A Design Methodology for Porous Stents to Control Hemodynamics Inside Abdominal Aortic Aneurysms
Keywords: flow control
optimization
porous stents

This thesis presents a methodology to control blood flow conditions inside aneurysm sacs by means of multilayer porous stents. These devices are an alternative for patients with complex endovascular morphologies, specifically, in Abdominal Aortic Aneurysms (AAAs) with short infrarenal necks that are not eligible for Endovascular Aneurysm Repair (EVAR) with traditional devices. Whereas traditional stents isolate the blood flow from the wall, porous stents aim to regulate the flow conditions inside the aneurysm to reduce the risk of rupture, promoting the formation of an Intraluminal Thrombus (ILT) to mechanically protect the wall from flow-induced forces. However, a clear definition of the optimal ILT size, location, attachment type and thickness that lead to the reduction of AAA wall rupture risk is still not well understood. In the event that one of these factors contribute to the increase of AAA rupture risk, porous devices should be designed or customized according to a patient's geometry to prevent undesirable configurations by controlling the hemodynamics inside the AAA sac. Based on this, we conducted our research with the aim of developing a methodology to design porous stents that can induce appropriate blood flow conditions within AAAs. Before developing this methodology, a study focused on the mechanical behavior of the aneurysm wall under different AAA-ILT configurations is performed. This is done to confirm that the presence of the thrombus could lower the forces on the aneurysm wall, and to characterize the effect of partial ILT attachment on these forces. After performing the AAA-ILT mechanical behavior study, we develop a relatively accurate and computationally inexpensive method to model the flow behavior in the AAA when porous stents are used. Given that there are multiple length scales involved (micrometer size pores in a centimeter size artery), a multi-level approach is proposed as a modelling methodology for capturing the hydrodynamic changes across the stent pores without requiring a large number of mesh cells. The detailed simulations through stent pores are carried out to capture the hydrodynamic effects, specifically to study the pressure drop across the stent under different angles of incidence and stent porosity values for a range of physiological velocities typically found in AAAs. Once the flow behavior across the stent is characterized with detailed pore-level simulations, its effect on the flow is modelled as a porous region with known porosity and pressure-velocity curves. This allows us to reduce the computational cost of the simulation by bridging information across multiple length scales. Then, a methodology is proposed to effectively design porous stents that control the blood flow inside the sac within a suitable hemodynamic range defined \textit{a priori}. The method proposed could improve the current decision-making, planning, and outcomes of interventions for any AAA geometry.
Investigation of Genetic Profiles in Chromosome 5p15.33 and Telomere Length in Lung Cancer Risk and Clinical Outcomes
Keywords: chromosome 5p15
lung cancer
telomere length

Lung cancer remains the most common cancer in the world and the leading cause of cancer mortality. This dissertation investigates two complementary hypotheses regarding the role of chromosome 5p15.33 and telomere length, in lung cancer etiology and clinical outcomes. This research uses data from the Toronto Mount Sinai Hospital-Princess Margaret Hospital case-control study, and pooled datasets within the International Lung Cancer Consortium. Chromosome 5p15.33 is an established lung cancer susceptibility locus. TERT is the main 5p15.33 candidate gene, which encodes the catalytic subunit of the telomerase enzyme, critical for maintaining telomere length (TL). Telomeres are highly conserved 5′-TTAGGG-3′ repeats at chromosome ends, which promote genome stability. TL has been implicated in lung cancer risk, although the epidemiologic evidence has been inconsistent. TL alterations are also established characteristics of solid tumours. Despite its importance, the underlying genetic and biological mechanisms in chromosome 5p.15.33 have not been elucidated. The fine-mapping analysis in Manuscript 1 identifies novel lung cancer susceptibility loci, using data from 5164 cases and 5716 controls. This study advances previous research by investigating a large number of novel, rare variants, discovered in a separate deep- sequencing study. The findings of Manuscript 2, based on the largest Mendelian Randomization analysis of lung cancer (16396 cases, 13013 controls), support the causal role TL. Methodological contributions of this work include the development of a new 5p15.33 instrument for TL, and a novel approach to mediation analysis. Manuscript 3 summarizes the published evidence for the clinical utility of TL and 5p15.33 variants. Manuscript 4 demonstrates the prognostic potential of TL in two independent lung cancer populations. A survival analysis of 4672 lung cancer cases suggests that telomere- independent genetic mechanisms in 5p15.33 may have prognostic relevance. In summary, this dissertation provides further insight into genetic and molecular determinants of lung cancer risk and progression.
Computation of Loss Distribution Based on the Structural Model for Credit Portfolios
Keywords: convolution
credit risk
expected shortfall
FFT
risk management
value-at-risk

Credit risk analysis and management at the portfolio level is a challenging issue for financial institutions due to their portfolios’ large size, heterogeneity and complex correlation structure. In this thesis, we propose several new asymptotic methods and exact methods to compute the distribution and VaR of a loan portfolio’s loss in the CreditMatrics framework. For asymptotic methods, we give an approximation based on the Central Limit Theorem (CLT), which gives more accurate approximations to the conditional portfolio loss probabilities compared with existing approximations. For exact methods, we improve the efficiency by exploiting the sparsity that often arises in the obligors’ conditional losses. A sparse convolution method and a sparse FFT method are proposed, which enjoy significant speedups compared with the straightforward convolution method. We also construct truncated versions of the sparse convolution method and the sparse FFT method to further improve their efficiency. To control the aliasing errors and roundoff errors incurred in the truncated sparse FFT method, an optimal exponential windowing approach is developed as well. For lumpy portfolios, we introduce hybrid methods which combine an asymptotic approximation with Monte Carlo simulation or one of exact methods to achieve a good balance between efficiency and accuracy.
Unsupervised Representation Learning with Autoencoders
Keywords: Deep Learning
Machine Learning
Unsupervised Learning

Despite the recent progress in machine learning and deep learning, unsupervised learning still remains a largely unsolved problem. It is widely recognized that unsupervised learning algorithms that can learn useful representations are needed for solving problems with limited label information. In this thesis, we study the problem of learning unsupervised representations using autoencoders, and propose regularization techniques that enable autoencoders to learn useful representations of data in unsupervised and semi-supervised settings. First, we exploit sparsity as a generic prior on the representations of autoencoders and propose sparse autoencoders that can learn sparse representations with very fast inference processes, making them well-suited to large problem sizes where conventional sparse coding algorithms cannot be applied. Next, we study autoencoders from a probabilistic perspective and propose generative autoencoders that use a generative adversarial network (GAN) to match the distribution of the latent code of the autoencoder with a pre-defined prior. We show that these generative autoencoders can learn posterior approximations that are more expressive than tractable densities often used in variational inference. We demonstrate the performance of developed methods of this thesis on real world image datasets and show their applications in generative modeling, clustering, semi-supervised classification and dimensionality reduction.
A Passive Air Sampler for Precise, Spatially Distributed Atmospheric Gaseous Mercury Monitoring and Source Characterization
Keywords: Atmospheric mercury
Background monitoring
Emissions estimates
passive air sampling
Source characterization

This thesis describes the design, testing and implementation of a novel, inexpensive, high precision passive air sampler (PAS) for gaseous mercury (Hg) monitoring. The PAS uses a sulfur-impregnated activated carbon as a sorbent, a commercially available, radial diffusive barrier (Radiello®), and a protective shield that doubles as a storage and transport container. The diffusive barrier and protective shield also help reduce variability in uptake kinetics that can be caused by wind and precipitation. An initial outdoor calibration in Toronto revealed highly linear uptake over a one-year period and unprecedented precision. Small, but predictable effects on uptake kinetics caused by temperature and wind speed were determined in laboratory experiments. The diffusive barrier was also deemed reusable after cleaning. A study evaluating the accuracy of the PAS against industry standard active instrument at 20 global sites determined (i) the recommended sampling rate (volume of air stripped of gaseous Hg per unit time; 0.135 ± 0.013 m3 day-1) that can be adjusted for the measured temperature and wind speed during each deployment, (ii) the excellent precision based uncertainty (4 ± 3 %), and (iii) the average overall uncertainty is at most (9 ± 6 %); a conservative measure due to inherent active instrument uncertainties. The analytical method (thermal decomposition, amalgamation, and atomic absorption spectrometry) was improved by the addition of sodium-carbonate to samples, which prolongs the life of the analytical instrument’s catalyst. Two source characterization studies (at a former Hg mine and across the Greater Toronto Area) demonstrate the PAS’s ability to successfully monitor concentration gradients and to estimate emissions. The results produced in this thesis are indicative of the PAS’s ability to measure at both background and high concentration sites with exceptional accuracy and precision, and its potential to improve atmospheric Hg science globally.