VictorJuiz/thesis huggingface dataset:
Visualizing The Vulnerability of Face Processing Across The Lifespan: An Image Reconstruction Approach
Keywords: Emotion recognition
Face perception
Image reconstruction
Individual difference
Memory

Human faces convey a wealth of information, including identity and emotional expression, both of which are crucial for social interactions. Consequently, difficulties in face processing can cause severe problems and impact a person’s well-being and quality of life. Extensive research has demonstrated that face perception can be disrupted by a variety of factors, such as aging, brain lesions, and mental disorders. However, the nature and the extent to which these factors have upon face representations remain unclear. In this thesis, I addressed these issues by employing a behavioural-based image reconstruction approach to uncover the pictorial content of face representations across a diverse sample of individuals. Specifically, Chapter 2 showed that visual representations of facial shape and surface information diagnostic to facial identity was compromised in older adults. Yet, the age-related effects were less pronounced than those associated with individual variabilities in discriminating conjunctions of facial features. Further, Chapter 3 revealed that the ability to distinguish between facial identities was impaired by damage to the medial temporal lobe areas, particularly the dentate gyrus. Lastly, Chapter 4 found that the severity of self-related personality dysfunction and levels of affective state, both of which are core features of personality disorder, impacted not only the accuracy of the visual content represented in perception and memory of facial expression but also their visual characteristics, such as expressiveness and positivity/negativity. Together, the findings across these three studies shed light on the impact of various conditions on the fine-grained visual content underlying face perception and memory, and advance our understanding of the vulnerability of face processing across the lifespan. Practically, the present thesis also demonstrates the applicability and utility of the image reconstruction approach across a broader population and provides a methodological framework for future research.
Exploring the Glaciodynamic Significance and Origin of Drumlins and Mega-scale Glacial Lineations from High-resolution Topographic Imagery
Keywords: Drumlins
Geospatial Analysis
Glaciology
Ice streams
Machine Learning
Mega-scale glacial lineations

The study of modern and ancient ice streams is one of the most rapidly growing fields in the study of glacial geomorphology following the discovery that ancient ice sheets contained corridors of fast flow (possibly as much as 10 km yr-1) called ice streams which discharge large volumes of ice (and sediment) and dictate deglaciation behaviour. This new paradigm is based on the recognition of the paleo-glaciological significance of km-long, narrow streamlined ridges called ‘mega-scale glacial lineations’ (MSGLs) which are now recognized as the hallmark of fast flowing ice. Present research activity is focussed on their origin(s) however current models are incapable of accounting for the variability of glacially streamlined landforms. Many hypotheses are based off low resolution data resulting in an underestimation of the number and extent of paleo-ice streams. This thesis uses over 150,000 km2 of high-resolution digital elevation model data from the eastern Great Lakes sector of the former Laurentide Ice Sheet in North America to address this data gap. The use of the newly developed Curvature-Based Relief Separation method for mapping subglacially lineated bedforms shows that at least 10 paleo-ice streams were previously undiscovered in the study area. Unsupervised machine learning and hierarchical-based clustering also shows that MSGLs are part of a landform ‘continuum’ and are transitional to drumlins with statistically validated ‘intermediate’ bedforms which record the dissection of parent drumlins to form MSGLs. This suggests a fundamental ice velocity control on their formation which is explored by using Median Absolute Differences to calculate the frictional profiles of paleo ice sheet surfaces showing that the evolution of this landform continuum is associated with the development of lower drag ice bed morphologies. Such observations are consistent with an erosional origin for drumlins and MSGLs, likely as the result of deforming subglacial debris being swept across the bed suggesting a basic commonality of forms produced by abrasion of ‘wear debris’ as one surface moves over another. The wider paleoglaciological and geomorphological significance of these findings are explored, representing a fundamental contribution to our understanding of fast ice flow in former ice sheets and the field of glacial geomorphology.
Digital Histopathology with Second-harmonic Generation Microscopy
Keywords: cancer
collagen
digital pathology
microscopy
nonlinear optics
polarimetry

Histopathology has been one of the most important techniques in medical diagnostics, which often involves investigation of thin tissue sections, stained with dyes such as hematoxylin and eosin (H&E) for improved visual contrast under a white light microscope. Although white light histopathology has been instrumental in revolutionizing medicine, clearing and staining processes introduce non-native molecules in the tissue and may alter the structure of the sample. Second-Harmonic Generation (SHG) is a label-free and non-invasive imaging modality which relies on endogenous biomarkers in the tissue to provide the required contrast for visualization. SHG microscopy is a well-established nonlinear modality which allows for visualization of noncentrosymmetric molecules such as collagen in the tissue. Moreover, polarimetric second-harmonic generation (P-SHG) microscopy is often used to characterize the composition, organization, and polarity of collagen fibers in tissue in the form of second-order nonlinear optical susceptibilities. In this work, scanning P-SHG was utilized to reveal unipolar arrangement of collagen fibers in the human cardiac conduction system, which may consequently aid in effective transduction of the electrical signal through the heart. Moreover, a novel widefield P-SHG microscope was designed and constructed to increase imaging speed and field of view, while reducing the effects of photobleaching and photodamage. The widefield P-SHG microscope was used to demonstrate high-throughput whole-slide imaging of a breast tissue microarray. The microscope yielded in a series of polarimetric and texture parameters which were used in tandem with supervised machine learning to differentiate tumor tissue from normal with 94.2% accuracy and F1-score, and 6.3% false discovery rate. Furthermore, a large section of tissue spanning from normal to non-small cell lung carcinoma was imaged with the widefield P-SHG microscope to map the structural variations of the ECM across the sample. The resulting parameters were analyzed with principal components analysis and unsupervised K-means clustering to identify normal- and tumor-like tissue, and to further highlight the tumor margin surrounding the tumor mass. All in all, we showed that widefield P-SHG microscopy revealed collagen ultrastructure over large tissue regions and can be utilized as a sensitive biomarker for cancer diagnostics and prognostics studies.
Robust Fluid Simulation over Complex Boundaries
Keywords: computer graphics
cut-cell meshing
fluid simulation
virtual element method

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.
Fiber-optic Communications Under Direct Detection: Capacity Bounds & Tukey Signalling
Keywords: direct detection
fiber-optic communication
ISI
short-haul
Tukey window

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.
Characterizing the Impact of Penile-vaginal Sex on the Immune Correlates of HIV Susceptibility in the Female and Male Genital Tracts
Keywords: Genital tract
HIV susceptibility
Inflammation
Microbiome
Mucosal
Penile-vaginal sex

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.
On the Difficulty of Training Deep Neural Networks with Raw Encephalography Data
Keywords: Brain computer interfaces
Deep learning
Deep neural networks
Domain generalization
Open source
Self-supervised learning

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.
Transcriptional and Multi-Omic Heterogeneity in Glioblastoma Stem Cells
Keywords: Cancer Stem Cells
Glioblastoma

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.
Using Neurorestorative Approaches for the Rehabilitation of Individuals living with Spinal Cord Injury or Disease
Keywords: activity-based therapy
brain-computer interface
functional electrical stimulation
qualitative methods
spinal cord injury
technology

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.
Fc Gamma Receptors and Phagocytosis in Immune Thrombocytopenia
Keywords: Autoantibody
Fc gamma receptor
Immune thrombocytopenia
Macrophage
Phagocytosis
Platelet

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.