VictorJuiz/thesis huggingface dataset:
Robust Fluid Simulation over Complex Boundaries

Beautiful, realistic fluid simulations emerge from the interaction of a fluid with complex environments. However, the design of such environments that satisfy the preconditions of existing simulators can be a tedious or even infeasible task; thus there is a need to design new simulators that accurately respect complex environments with fewer restrictions. This thesis addresses both of these challenges by making advancements in both the construction of simulation domains and the representation of functions on those domains, which permits the resolution of constitutive models for fluids. The simulation domain is decomposed through the use of a novel cut-cell mesh generation algorithm that robustly captures arbitrarily small features at a fraction of the computational cost of tetrahedralization algorithms and without the homogenizing artifacts seen in voxelization like the loss of narrow features and stairstepping. Rather than developing shape functions for the general polyhedral elements constructed by our cut-cell mesher, we use polynomial bases that are incorporated in each cell with the Virtual Element Method. We further show show that the Virtual Element Method elegantly fits into the traditional Particle-in-Cell pipeline with a novel class of coefficient-sampling operators. The amalgamation of these advances is VEMPIC, which creates novel fluid simulations that embrace problematic boundary geometries.

Keywords: computer graphics
cut-cell meshing
fluid simulation
virtual element method
Advisor: Fiume, Eugene
Fiber-optic Communications Under Direct Detection: Capacity Bounds & Tukey Signalling

Because of its extremely simple implementation, intensity modulation with direct detection (IMDD) is widely employed in short-haul fiber-optic communication systems. However, since IMDD systems do not exploit phase information, they suffer from having a low spectral efficiency. Alternatively, being capable of measuring both the magnitude and the phase of the received complex-valued waveform, a coherent detector can provide high spectral efficiency, but at the price of having a complicated optical/optoelectronic receiver front-end. This high cost hinders the wide deployment of coherent detectors in short-haul applications. This thesis aims to introduce a new transceiver, compatible with short-haul fiber-optic communications, which has the simplicity of an IMDD receiver's optical front-end and the high spectral efficiency of a coherent detector. In this thesis, upper and lower bounds for the capacity of waveform channels under square-law detection of time-limited signals are derived. The upper bound is the capacity of the channel under phase-unlocked coherent detection. The lower bound is just one bit less, per dimension, than the upper bound. The lower bound suggests that the price in spectral efficiency of a simple direct-detection receiver is not as high as previously thought. To achieve the capacity lower bound, it is necessary both to modulate the magnitude and the phase of the transmitted waveform. However, it is not at all obvious how one may detect the magnitude and the phase of the transmitted complex-valued waveform only from intensity measurements of the received waveform. In this thesis, by introducing a new direct-detection-compatible signalling scheme, we address this question, as well. Extraction of phase information is made possible by the introduction of controlled inter-symbol interference, resulting in a scheme that achieves spectral efficiencies about one bit less, per second per hertz, than those of a coherent detector. The use of an integrate-and-dump detector in the proposed scheme makes precise waveform shaping unnecessary, thereby equipping the scheme with a high degree of robustness to nonlinear signal distortions introduced by practical modulators. Since maintaining linearity in the optical domain is expensive, this nonlinearity robustness is a main feature of the proposed scheme which makes it viable for short-haul applications.

Keywords: direct detection
fiber-optic communication
ISI
short-haul
Tukey window
Advisor: Kschischang, Frank R.
Characterizing the Impact of Penile-vaginal Sex on the Immune Correlates of HIV Susceptibility in the Female and Male Genital Tracts

Globally most HIV transmission occurs through penile-vaginal sex. Various factors in the genital tract of the uninfected partner increase the risk of HIV acquisition, including sexually transmitted infections (STIs) and the genital microbiome, with mucosal inflammation serving as the central pathway for enhanced risk. However, the clinical studies defining the mucosal immune correlates of HIV susceptibility collected genital samples remote from sexual activity, while HIV penetrates mucosal tissues within hours of sex. Therefore, it is critical to understand the impact of penile-vaginal sex itself on genital immunology. This was the primary objective of the Sex, Couples and Science study (SECS) project. Cervical cytobrush sampling is commonly used to study immune cell populations in the FGT, but the impact of sample collection itself on mucosal immunology has not been defined. Therefore, I first investigated the impact of cytobrush sampling on mucosal correlates of HIV susceptibility after 6 and 48 hours. Cytobrush sampling increased cervical HIV target cell numbers and pro-inflammatory cytokine levels at 6 hours, with most immune changes resolving by 48 hours. Cytobrush sampling did not alter the absolute abundance of key vaginal bacteria. Therefore, in designing the SECS protocol I ensured that there was a gap of at least 48 hours between consecutive cytobrush samples. I then recruited 40 established heterosexual couples to assess the impact of penile-vaginal sex, either condomless or condom-protected, on FGT and penile immunology. The level of penile and cervico-vaginal cytokines previously associated with HIV acquisition increased 1 hour after sex, regardless of condom use, and returned to baseline levels by 72 hours. Penile cytokine changes largely reflected exposure to cytokine-rich FGT secretions. The proportion of endocervical HIV target cells, specifically Th17 cells and activated/mature dendritic cells (DCs), increased transiently 1 hour after condomless sex, although this increase was only seen in the context of an uncircumcised male partner. In summary, penile-vaginal sex induced profound short-term immune changes that may enhance HIV susceptibility in women and men. This furthers our understanding of the biology of mucosal HIV acquisition and has implications for the design of clinical studies assessing mucosal immunology and HIV acquisition.

Keywords: Genital tract
HIV susceptibility
Inflammation
Microbiome
Mucosal
Penile-vaginal sex
Advisor: Kaul, Rupert
On the Difficulty of Training Deep Neural Networks with Raw Encephalography Data

A call for deep neural networks (DNN) to permeate all classification problems has found its way to brain computer interface (BCI) applications. Despite this interest, the “depth” of DNNs in this field is a troublesome concept, and it appears uncon-vincing that the available data is being put to effective use. This dissertation centres around these questions by proposing ways to effectively treat the myriad recording contexts that are a necessary aspect of BCI applications. I argue that acknowledging these different contexts as domains of classification is an important step. Through doing so, I demonstrate that it is possible to develop deeper networks that make more effective use of available data as well as make use of the otherwise detrimental sensitivity DNNs exhibit to these domains. As a result of the latter, extensions are made into neuroscientific applications of DNNs. Finally, I argue for and propose an alternative path to pre-training extremely large DNNs inspired by language modelling rather than the extensions of successes in computer vision which have tended to be favoured. Finally, I describe the open source software library developed in support of this work, that enables similar work to continue in the future.

Keywords: Brain computer interfaces
Deep learning
Deep neural networks
Domain generalization
Open source
Self-supervised learning
Advisor: Rudzicz, Frank
Transcriptional and Multi-Omic Heterogeneity in Glioblastoma Stem Cells

Glioblastoma Multiforme (GBM) is a disease with terrible prognosis, having a median survival time of ~12-15 months for patients undergoing current treatment regimens, and a 5-year survival rate under 10%. There is strong evidence to suggest the existence of stem like cells, which we term glioma stem cells (GSCs), that are capable of repopulating the tumor after surgery and chemotherapy. Thus, any effective treatment for GBM will likely have to target this population. Evidence of functional heterogeneity of GSCs at the level of the transcriptome and drug response motivates a full characterization of GSCs’ biological variation. In this project, I use multiple -omic data types from both bulk and single cell resolution to explore how multiple biological processes such as transcription and epigenetic regulation play into GSC heterogeneity in therapeutic vulnerabilities. With single cell/nuclei RNA-sequencing, in collaboration with the Pugh and Dirks labs and others, I establish that transcriptional heterogeneity in GSCs and more generally GBM can be decomposed into two major axes of variation: a Developmental/Injury Response transcriptional axis present in both the stem fraction of GBM tumors as well as the tumors themselves, and a stem to astrocyte differentiation gradient present only in the tumor samples. Further functional characterization with CRISPR knockout data reveals that differential functional dependencies between Developmental and Injury Response GSCs largely match their differentially expressed genes, showing that this transcriptional axis of variation translates into functional consequences that could inform development of combination therapies. Following these results, I perform an integrated analysis of genomic, transcriptomic, epigenomic, and miRNA-seq data to obtain a more complete picture of both how this transcriptional axis is regulated as well as what other heterogeneity exists independent of transcription. Here, I find four major axes in multi -omics space: one corresponding to a hypermutation phenotype largely matching one previously characterized for GBM dependent on mismatch repair deficiency and temozolomide treatment, two others corresponding to apparent latent variation in regulation of inflammatory genes, and lastly a multi-omics axis corresponding to the coordinated regulation of the Developmental/Injury Response transcriptional axis by multiple biological layers. Collectively, the results presented in this thesis provide better mechanistic understanding of GSC heterogeneity and open the door to developing novel therapies.

Keywords: Cancer Stem Cells
Glioblastoma
Advisor: Bader, Gary D
Using Neurorestorative Approaches for the Rehabilitation of Individuals living with Spinal Cord Injury or Disease

In recent years, rehabilitation for individuals living with spinal cord injury or disease (SCI/D) has shifted from a focus on compensatory approaches to address loss of function to a focus on neurorestorative approaches. My central thesis aim was to understand the use of neurorestorative approaches in physical rehabilitation for individuals with SCI/D. Regarding the central thesis aim, I identified barriers and facilitators to the use of these approaches. Also, I described the current state of translation and implementation of these neurorestorative approaches as part of Canadian SCI/D rehabilitation. Data were gathered from four main studies of neurorestorative approaches to SCI/D rehabilitation in Canada. Study 1 was a scoping review that investigated the effect of epidural stimulation on different functions for individuals with SCI/D. Study 2 and Study 3 investigated the perspectives of occupational therapists (OTs) and physical therapists (PTs) on activity-based therapy (ABT) using conventional content analysis. Study 2 focused on the inpatient/outpatient hospital setting, while Study 3 looked at the acute care setting. For Study 4, I interviewed OTs and PTs about their use of brain-computer interface-triggered functional electrical stimulation therapy (BCI-FEST). My research identified therapists’ need for increased knowledge and education about neurorestorative approaches to SCI/D rehabilitation using mentorship and large support groups. Implementation of these neurorestorative approaches should occur across the continuum of care yet take into consideration differences between settings and nuances between sites. Across studies, I noted that perspectives from therapists working in rural and remote (i.e., non-specialized SCI/D centres) were not included. Future research should target the perspectives of these individuals as we work towards implementation.

Keywords: activity-based therapy
brain-computer interface
functional electrical stimulation
qualitative methods
spinal cord injury
technology
Advisor: Musselman, Kristin E
Marquez-Chin, Cesar
Collective Dynamics of Interacting Cell Types

Recent experimental advances have opened up entirely new ways to study and conceptualize biological systems. This shift is particularly pronounced in the context of complex multicellular organisms, where single-cell technologies allow us to dissect tissue heterogeneity at the level of individual cells. For the theoretical sciences, this wealth of data provides a unique opportunity to synthesize general principles that unify the variability observed across diverse organisms. This thesis focuses on questions that are inspired by the concept of “cell type”, which is fundamental to our understanding of multicellular development and homeostasis, yet remains poorly defined. Motivated by the ongoing data revolution, cell types are defined here as subsets of gene expression space that are invariant to the dynamics of gene regulation. In particular, I investigate physics-inspired dynamical systems that encode cell types as fixed point attractors. In the process, I derive a formal correspondence between Hopfield networks and restricted Boltzmann machines – two classical architectures at the interface of statistical physics and machine learning. I then show that in the presence of gene regulatory noise alone, Hopfield networks encoding mammalian cell types can recapitulate in vivo differentiation patterns. The statistics of noise-induced cell type transitions reflect their transcriptional proximity, suggesting organizing principles for cell lineage trees. Next, by coupling the transcriptional states of multistable single cells, I develop a general model of multicellular gene regulation that formalizes emerging notions of cell type “plasticity” and establishes a framework to study the self-assembly of compositionally diverse tissues from identical subunits. I then analyze the population dynamics of interacting cell types in the context of cancer development, identifying qualitatively distinct collective states and quantifying their roles in cancer initiation. The results of this thesis not only suggest general principles involved in multicellular development and homeostasis, they also point towards new theoretical approaches inspired by multicellular systems.

Advisor: Zilman, Anton
Fc Gamma Receptors and Phagocytosis in Immune Thrombocytopenia

Immune thrombocytopenia (ITP) is an autoimmune disease characterized by a low platelet count in the absence of secondary or other explanations of thrombocytopenia. Platelet destruction in ITP is thought to be caused predominantly by pathogenic factors present in circulation. In particular, platelets are understood to be targets of immunoglobulin G (IgG) anti-platelet autoantibodies, which may then engage Fc gamma receptors (FcγRs) on macrophages in the spleen, triggering clearance of platelets by phagocytosis. However, direct demonstrations of splenic macrophage phagocytosis of autoantibody opsonized platelets are lacking. In addition, it is unclear which specific FcγRs are utilized in the phagocytosis of platelets. There is also the potential of other humoral factors to mediate or augment macrophage phagocytosis of platelets which remains insufficiently characterized. In this thesis, I focus on the mechanisms of macrophage phagocytosis of IgG opsonized platelets, the utilization of FcγRs in phagocytosis, and potential strategies to prevent this process in ITP. In the first study, I characterize the mechanism of anti-CD44 antibodies, a potential ITP therapeutic able to ameliorate passive IgG-mediated ITP in mice. I demonstrate that anti-CD44 inhibits macrophage FcγRs through an apparent blockade-type mechanism via the Fc region of the anti-CD44 antibody, preventing macrophage phagocytosis of platelets and explaining amelioration of passive IgG-mediated murine ITP. In the second study, I demonstrate that splenic macrophages from ITP patients utilize FcγRI and FcγRIII in the phagocytosis of platelets opsonized with ITP serum positive for IgG anti-platelet autoantibodies. I suggest that the individual or combined blockade of FcγRI and FcγRIII may be an effective therapeutic strategy for ITP. In the third study, I evaluate the ability of serum from ITP patients as a source of ITP humoral thrombocytopenic factors to mediate macrophage phagocytosis of platelets. I demonstrate that 40% of ITP sera mediated phagocytosis greater than the normal human serum mean plus two standard deviations, while an additional 35% mediated phagocytosis greater than one standard deviation. I further characterized ITP sera for IgG anti-platelet autoantibodies and serum pentraxins to evaluate their contribution to macrophage phagocytosis.

Keywords: Autoantibody
Fc gamma receptor
Immune thrombocytopenia
Macrophage
Phagocytosis
Platelet
Advisor: Lazarus, Alan H.
Efficient Aircraft Flutter Analysis using Model Order Reduction with Error Estimation

Fast and accurate aircraft flutter analysis in the transonic regime remains an open problem due to the high computational cost of accurately modelling transient aerodynamic forces. In this thesis, a methodology for flutter prediction with the application of model order reduction with error estimation is presented to reduce computational cost while achieving user desired accuracy. The methodology is shown to be computationally efficient, minimize the requirement for user knowledge, and provide user-prescribed accuracy for flutter prediction relative to the high-dimensional aeroelastic model. The Euler equations are used to model the aerodynamics, which are linearized about a nonlinear steady-state solution and reduced using a projection-based model order reduction approach. The resulting aerodynamic ROM is coupled to a structural model to form the primal aeroelastic ROM. The aeroelastic ROM is of low order, allowing for a computationally efficient parameter sweep of the aeroelastic eigenproblem to determine the flutter point. A dual-weighted residual-based error estimator is presented which approximates the error in the eigenvalues obtained from the primal aeroelastic ROM relative to the true eigenvalues from the high-dimensional aeroelastic model. This error estimator makes use of a dual aeroelastic ROM to approximate the dual solution. A second error estimator is presented which approximates the error in the predicted flutter point relative to the true flutter point from the high-dimensional model. By combining the aforementioned algorithmic elements, a ROM-based flutter methodology with error estimation is developed. The proposed method provides the user with approximate aeroelastic eigenvalues, an approximate flutter point, and an estimate of the error in both these quantities. Flutter analyses are presented for several test cases. Both the eigenvalue and flutter point error estimators are shown to have good agreement with the true error. For the test cases presented, the cost of computing the flutter point at a given Mach number is equivalent to the cost of approximately 4 to 15 steady nonlinear flow evaluations of the high-dimensional Euler equations. When compared to a POD-based ROM approach, the proposed method achieves comparable or faster computational times for similar levels of error while additionally providing error estimates for flutter analysis.

Keywords: Computational Fluid Dynamics
Dual-Weighted Residual
Dynamic Aeroelasticity
Error Estimation
Flutter Analysis
Reduced Order Modeling
Advisor: Zingg, David W
Essays on the Long-term Effects of Childhood Chronic Conditions

This dissertation is concerned with understanding the long-term implications of childhood chronic conditions (e.g., physical, mental/developmental) on health and socioeconomic outcomes in young adulthood. Across three studies, I address issues pertaining to underlying mechanisms, sources of heterogeneity, and comparatively examine the effects of different conditions. I draw on survey and administrative tax data from the US and Canada, which I analyze using a range of statistical tools.The first study examines distributional differences in earnings and mental health scores in young adulthood between individuals who suffered from a chronic condition in childhood, compared to those who did not, using non-parametric distributional methods applied to the Panel Study of Income Dynamics (US). I find that young adults who reported a mental/developmental disorder in childhood cluster in the lower percentiles of both distributions of interest, relative to those who did not. Covariate decompositions suggest educational attainment represents an indirect pathway. The second study investigates long-term implications of childhood chronic conditions in Canada using individual-level linked survey and tax data (National Longitudinal Survey of Children and Youth, T1 Family File). I find that childhood mental/developmental disorders negatively affect all adult outcomes of interest (e.g., income) in baseline and fixed effects specifications, while physical ailments only affect health-related work absences and social assistance take-up. Covariate decompositions point to cognitive skills in adolescence as an indirect pathway. The final study examines the effect of childhood chronic conditions on parental investment behaviours (e.g., affective time, discipline). Using the National Longitudinal Survey of Children and Youth, I find that child mental/developmental disorders and behavioural problems lead parents to reduce investments across investment domains, and that parental socioeconomic characteristics moderate investment responses. I find modest contributions from parental investments in tempering the effects between child health conditions and short-run cognitive skills. Results suggest that childhood chronic conditions affect future outcomes, though processes involved are somewhat complicated. The findings underscore the potential for large returns of investments in childhood health in the form of enhanced long-term outcomes across many domains. Findings encourage further empirical work on mental/developmental health conditions and recommend inter-sectoral policy investments in childhood (e.g., health, education).

Advisor: Laporte, Audrey