VictorJuiz/thesis huggingface dataset:
Decoding and Reconstructing Orthographic Information from Visual Perception and Mental Imagery Using EEG and fMRI

Vision plays a crucial role in reading by supporting the processing of visual-orthographic representations, which are essential for social interactions and daily activities. In recent years, there has been a lot of interest in investigating such processes across multiple methodological domains, including electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). For instance, studies have shown the importance of the visual word form area (vWFA) in reading, but its exact role remains unclear. On the other hand, mental imagery is a unique form of visual experience where, in contrast to perception, no external stimuli are present. The current thesis aims to investigate the neural representational structure of visual-orthographic information in both visual perception and mental imagery by considering both EEG and fMRI signals during word recognition and by applying state-of-the-art pattern analysis techniques to such signals. Specifically, Chapter 2 established the feasibility of decoding and reconstructing whole-word images from EEG data. The examination of the time course of decoding provided insight into the temporal dynamics of early word processing, identifying critical time points for word recognition. Chapter 3 examined the relative contribution of different time points from different EEG channels, revealing time and frequency features that underlie decoding for words and faces. Chapter 4 investigated the neural representational structure of words in mental imagery using fMRI and successfully decoded and reconstructed whole words from activity patterns in both vWFA and early visual cortex. These findings provide a deeper understanding of the neural mechanisms underlying visual perception and mental imagery of orthographic information. They demonstrate the feasibility of retrieving fine-grained visual features from neural signals that support the distinction of within-category exemplars, which offers considerable potential benefits for the development of new communication methods for individuals with communication impairments.

Keywords: Decoding
EEG
fMRI
Reconstruction
Visual recognition
Advisor: Nestor, Adrian
Lee, Andy C.H.
Statistics of the Synchrosqueezing Transform

We investigate the synchrosqueezing transform applied to complex gaussian white noise, as well as signals consisting of a single harmonic component contaminated with complex gaussian white noise. First, this involves analyzing the reassignment rule, which is built from a quotient of improper, correlated complex gaussians. We provide a new formula for the general density of said quotient and use this to carefully clarify the decay rate of the covariance of the reassignment rule. Next, for a fixed time $t$, we analyze the synchrosqueezing integrand $Y_{\alpha,\eta}$ at different frequencies $\eta$ and resolutions $\alpha$. A detailed asymptotic analysis of the covariance between $Y_{\alpha,\eta}$ and $Y_{\alpha,\eta'}$ is provided. By appealing to an $M$-dependent approximation argument, we obtain a central-limit theorem for the synchrosqueezing transform at time $t=0$ and fixed frequency $\xi$ and give an interpretation within the context of kernel regression. Finally, we provide a number of open problems whose resolution may lend themselves to further results in the vein of this work.

Keywords: complex gaussian noise
synchrosqueezing
time-frequency analsis
Advisor: Pugh, Mary
Wu, Hau-Tieng
Crossroads in Digital Gaming: Metaplay, Communication, Interaction

This dissertation conducts a qualitative study in a region in Canada, anonymized as “the District”, which sits outside of a major city, focusing on adult players of the main series of Pokémon games. The District encompasses different geographic areas, characterized by suburban growth in a rural context with limited urban areas, with a significant industrial sector that comes with a working class demographic. By interviewing players who began playing Pokémon at different points in time, ranging from the first generation of players in 1998 to those who played their first Pokémon games in the mid-to-late 2000s, the dissertation captures a snapshot of changing play practices that came alongside the deployment of high-speed and more accessible Internet in the mid 2000s. Since the debut of Pokémon in North America in 1998, Pokémon play is now significantly more complex owing to an intricate network of gaming practices and communication, contextualized by play practice developments over time, changes in hardware, and information communication technology (ICT) infrastructure in local communities. This dissertation argues the best means of engaging digital play today is the framework of metaplay, derived from Bateson’s theories of meta-action and meta-communication (1956), supported by the components of metagame (Donaldson, 2016), paratexts, and gaming capital (Consalvo, 2007). Through this framework, the study reveals inequities in Pokémon play in the District, demonstrating the impact of infrastructure and perceptions of play for adult players in regions like the District, while also demonstrating a desire for local play cultures and how ICTs impact the complicated relationship local players have with global play cultures and practices.

Keywords: Canada Suburban play
Gaming capital
Metagame
Metaplay
Paratexts
Pokemon
Advisor: Grimes, Sara M
Enhanced Beneficiation of Ultramafic Nickel Ores Using Novel Reagents

Due to its outstanding physical and chemical properties, nickel (Ni) is used in the manufacture of stainless steel, batteries, catalysts etc. However, high Ni demand has rapidly depleted high-grade sulfide deposits, leading the mining industry to seek alternative Ni sources such as low-grade ultramafic Ni ores. Processing of these ores is difficult due to their high content of the gangue mineral, serpentine, which slime coats the Ni-bearing mineral, pentlandite, and increases slurry viscosity. In response to stringent environmental regulations, process water is recycled, introducing significant amounts of Ca2+ and Mg2+ into flotation unit operations, which exacerbates the slime coating phenomenon. Additionally, the mining industry is under pressure to decarbonize its operations: it currently accounts for 4–7% of global greenhouse gas emissions. To overcome these challenges, the first part of this thesis focuses on decarbonizing mineral processing operations by utilizing carbon dioxide (CO2) in unit operations such as flotation and rheology modification. CO2 conditioning prior to flotation prevented slime coating and mitigated the detrimental impacts of divalent cations by permanently storing CO2 as metal carbonates. Zeta potential measurements and theoretical calculations indicated adsorption of metal carbonates onto the serpentine surface and microflotation experiments demonstrated increased Ni recovery. The second part of the thesis focuses on using sustainable flotation reagents for separation of pentlandite from ultramafic Ni ore. Citrate and Oxalate were shown to chelate with divalent cations to form metal-citrate or metal-oxalate chelates, which desorb from the pentlandite surface and adsorb onto the serpentine surface. Removal of chelates restored the charge and hydrophobicity of pentlandite whereas it reversed the charge of serpentine. The induced electrostatic dispersion among the mineral particles enhanced selective separation of pentlandite. The third part of the thesis explored the use of citrate and oxalate as rheology modifiers during slurry transport operations. Both reagents prevented bridging between serpentine particles and were selectively adsorbed onto the brucite plane of serpentine. Theoretical calculations and AFM measurements showed repulsive/weakened interactions between the brucite plane and silica/edge plane, which broke the mineral microstructure. Rheology investigations confirmed weakened interparticle interactions, manifested as significant decreases in slurry viscosity, yield stress, and storage modulus.

Keywords: Chelating Agents
Decarbonization
Flotation
Nickel
Rheology
Ultramafic Ores
Advisor: Bobicki, Erin
Leveraging Preclinical Pharmacogenomics Studies to Discover Translatable Expression Biomarkers of Drug Response

Precision oncology trials have demonstrated that matching cancer patients to treatment based on the molecular characteristics of their tumour leads to better response to therapy. Recent evidence suggests that transcriptomic profiling is particularly informative for matching patients to treatments. However, in many clinical studies, the majority of patients could not be matched to a genomically or transcriptomically selected therapy, highlighting a need for more biomarkers predictive of drug response. Preclinical pharmacogenomic studies combine molecular profiling of cancer models with drug sensitivity screening with the goal of discovering novel predictive markers. However, inconsistencies between experiments done in different laboratories raised concerns about the reliability of biomarkers discovered from these datasets. In this thesis, I address three challenges to using such studies for the discovery of transcriptomic biomarkers predictive of drug response. To address differences in data pre-processing and inconsistent nomenclature, I present PharmacoDB, a unified database of preclinical pharmacogenomic studies. I then investigate which statistical approaches are best suited to correlating noisy drug response measurements, both in simulation and real datasets. I propose and investigate the rCI statistic, a semi-parametric extension of the concordance index designed to reduce the impact of noisy drug response measurements. The rCI is shown to be more powerful at detecting correlations than the concordance index or Spearman correlation coefficient, however, it remains less powered than the Pearson correlation in the application to drug response data. Finally, I present a framework using statistical meta-analysis models to resolve technical and biological differences across datasets. I apply this framework to the seven largest preclinical pharmacogenomic studies released to date, discovering 4338 putative robust trancriptomic biomarkers. Using clinical validation data, I demonstrate a novel biomarker, expression of ODC1, is predictive of paclitaxel response for treatment of Breast Carcinoma a neo-adjuvant setting. Together, these contributions provide novel tools and propose novel approaches for analysing preclinical pharmacogenomic screens, as well as initiate the translation of discoveries made in these studies to clinically actionable biomarkers.

Keywords: Cancer
Pharmacogenomics
Transcriptomics
Advisor: Haibe-Kains, Benjamin
Pugh, Trevor J
The Same River, Together: Theorizing and Assessing Shared Rule in Treaty Federalism

Starting from a query regarding the place of pre-Confederation treaties in the reconciliatory intentions of the contemporary Canadian political order, the primary objective of my dissertation is to consider one possible answer to this challenge by asking whether and how Indigenous peoples’ aspirations for both self-rule and shared rule might be achieved, and what role – if any – the Canadian federal state might play in those aspirations. The theory of treaty federalism, which takes the pre-Confederation treaties as the foundation of a federal relationship between Indigenous peoples and Canada’s colonial authorities, presents one vision for achieving such aspirations. The general aim of this dissertation is to consider both the theoretical basis for a theory of shared rule in treaty federalism as well as its implications for assessing the merit of various institutional models operationalizing shared rule. However, the theory of treaty federalism has been criticized for its under-theorization of the element of shared rule. This dissertation fills the shared rule gap in the theory of treaty federalism by elaborating what I have termed a “sharing protocol” that could feasibly underpin treaty relations in the Canadian federal order. If a functioning, treaty-centered nation-to-nation relationship is ever to be within reach, a coherent and comprehensive theory of shared rule is imperative. The sharing protocol rests on three core principles, derived from historical and contemporary treaty processes and traditions: enacting self-determination, commitment to co-responsibility and reciprocal prosperity. To test the viability of these principles in operationalizing a treaty federal order, the dissertation assesses the core models of political representation employed in service of increasing Indigenous political presence in settler state legislative bodies around the globe. Ultimately, the dissertation finds that both operational and proposed models of Indigenous political representation offer only limited enactments of shared rule from the perspective of a theory of treaty federalism, most often constrained by a lack of affirmation for Indigenous self-determination and the imposition of state-centric and hierarchical, rather than nation-to-nation, relations.

Keywords: federalism
reconciliation
self-determination
shared rule
treaties
treaty federalism
Advisor: Kuokkanen, Rauna
Schertzer, Robert
A Systematic Pipeline to Identify Bypass Suppressors of Essential Genes and Gene Pairs in S. cerevisiae

Genetic suppression occurs when a phenotype associated with a mutation in one gene is rescued by a secondary, extragenic mutation. Dramatic examples of genetic suppression include bypass of the lethal phenotype associated with mutation in an essential gene, or of phenotypes associated with severe Mendelian disease mutations in humans. Previous efforts to map bypass suppressors of essential genes have involved screening for chemically induced or spontaneous mutations, followed by next generation sequencing which, although biologically informative, can be laborious and time-consuming. Here, I developed a systematic method for identifying bypass suppressors using Synthetic Genetic Array (SGA) (Suppressor-SGA; Sup-SGA) technology to introduce defined loss-of-function mutations from yeast mutant arrays into strains carrying deletion mutations in essential query genes or gene pairs. Because the identity of the suppressor gene on the mutant array is known, this method enables rapid and exhaustive tests for suppressor relationships involving all genes in the genome. Analysis of bypass suppressors identified known suppressors and uncovered novel genetic factors that contribute to conditional essentiality. For example, analysis of bypass suppressors of NAT2 deletion revealed previously unappreciated roles in viral attenuation and mitochondrial function. I also adapted Sup-SGA to identify bypass suppressors of synthetic lethal gene pairs; that is, genes which when deleted alone do not cause a dramatic growth defect but cause lethality when combined as double mutants. I show that the suppressors of different bni1 synthetic lethal gene pairs are distinct and likely act through different mechanisms. In another screen, I identified three independent alleles of the essential cyclin-dependent kinase CDC28 at a semi-permissive temperature that cause G1-delay as suppressors of the synthetic lethal gene pair rpn4∆ ire1∆. Further experiments showed that the suppression occurs due to a bypass of the UPR pathway, likely alleviating the downstream consequences of ER stress. Intriguingly, rpn4∆ ire1∆ mutants were chemically rescued by the presence of low concentrations of α-factor which, like the mutation of CDC28, also causes G1-delay. This result illustrates the potential of small molecules to phenocopy genetic suppression. Altogether, I demonstrate the utility of Sup-SGA to elucidate the mechanisms of gene essentiality, to illuminate cell biology that governs synthetic lethality and to explore the basis of chemical suppression.

Keywords: suppression
systems biology
Advisor: Andrews, Brenda
Boone, Charles
Deep Transfer Learning Models for Prediction from Ultrasound

Deep learning models are powerful tools for prediction but can fail when data is insufficient or shifts between training and deployment. These failure modes are expected in models built for ultrasound imaging, as small data sets for imaging of specific conditions and variability between sonographers, machines, institutions, and patient populations make prediction in this data challenging. Ultrasound is by far one of the most accessible and non-invasive medical imaging technologies available so the benefit of stable, effective models in this technology is very high. Therefore, a key to improved deep learning modeling of ultrasound data (and achieving this benefit) is identifying methods which enable effective small sample model development and model transfer to new populations. Many methods and classes of methods have been proposed to enable deep learning model transfer, including pretraining with a related or unrelated data set and task, domain adaptation, and qualitative interviews. I adapt and apply these methods in 3 ultrasound use-cases: paediatric hydronephrosis (HN) renal ultrasound, paediatric echocardiography (ECHO), and first-trimester prenatal ultrasound. Domain adaptation is explored for its potential to bridge covariate shifts of different sizes, with more or less data, conditioned on the label or not. This work shows that if the covariate shift assumption can be satisfied, domain adaptation is extremely effective at improving target performance even with very few labeled samples. This makes domain adaptation a preferable choice when (multi-)source data is available and the assumptions of the model are met. Finally, the context of model transfer is examined with a qualitative analysis of deep renal ultrasound model transfer to South Africa. This work finds major demand for tools which guide and improve ultrasound interpretation as well as a demand for greater ultrasound access and training at point-of-care. Creating models for ultrasound-informed precision care that transfers stably between these sources is an essential precursor to deep learning-enabled precision care with ultrasound modeling. This work shows how effective each model transfer method is, even with very little training data for a target task. In addition, the compendium of these studies can guide model development and decision-making around data collection, labeling, and sharing.

Advisor: Goldenberg, Anna
The Development and Miniaturization of In-Vivo Nuclear Magnetic Resonance Spectroscopy Towards Mass-Limited Environmental Samples

The continual release of environmental contaminants is a global concern that impacts human and environmental health. To monitor and characterize the risk of contaminants, it is critical to determine their toxic mode of action. Unfortunately, our understanding of toxicity pathways is limited, in large part due to a lack of analytical methods capable of monitoring living organisms at the molecular level. Current methods often rely on apical endpoints; however, metabolomics focuses on characterizing biochemical changes in response to external stimuli. Recently, in-vivo Nuclear Magnetic Resonance (NMR) spectroscopy has demonstrated a distinguished ability to monitor living organisms in real-time with the potential to decipher complex interconnected response pathways. Unfortunately, environmentally crucial specimens, such as aquatic eggs, are challenging to study using in-vivo NMR due to their small size and the low sensitivity of NMR. This dissertation will address this challenge through miniaturization of in-vivo NMR. After an introduction to environmental metabolomics and NMR in Chapter 1, Chapter 2 focuses on optimizing in-vivo NMR using existing technology. This chapter examined NMR probes and experiments to establish that the optimal protocol to monitor 13C enriched living organisms was an inverse 2D experiment and an inverse cryoprobe. In the next chapter, NMR was first miniaturized here using microcoils. Chapter 3 compares two main microcoil designs (surface and 3D volume coils) for their ability to perform complex experiments on intact biological samples, concluding a 3D coil is most beneficial for in-vivo studies. In Chapter 4, a microlitre probe is modified with a separate lock and used to significantly reduce sample size requirements for the analysis of D. magna hemolymph and eggs. Additionally, a L volume flow system is introduced for an in-vivo stress study of neonates at the microcoil level. Lastly, Chapter 5 miniaturizes NMR using a novel Lenz lens design while integrating sensitivity enhancements from cryoprobes. The detection system created here leads to massive reductions in sample requirements and substantial increases in sensitivity for mass-limited samples. This dissertation miniaturizes in-vivo NMR techniques and positions it as an important approach to help improve the fundamental understanding of biochemical processes and for future environmental risk assessments.

Keywords: Cryoprobes
Daphnia magna
In-Vivo
Metabolomics
Microcoils
Nuclear Magnetic Resonance Spectroscopy
Advisor: Simpson, Andre J
Toward a Compact Two-photon Optical Clock based on Calcium

This thesis presents details on the design, construction, and characterization of a novel compact optical clock based on a two-photon transition in calcium. Optical atomic clocks have reached unprecedented accuracy and precision and have the potential to revolutionize metrology. However, many of the applications of optical clocks, such as the detection of dark matter and gravitational waves, deep space navigation, measurements of variations in fundamental constants, and precision geodetic measurements, require compact portable clocks. Building optical atomic clocks on a scale suitable for most field applications is an ongoing challenge in the precision metrology community. This work describes a clock that can be made smaller and simpler than most existing optical clocks, while still operating with state-of-the-art precision. The basis for these improvements is using a two-photon transition, which eliminates the need for sub-Doppler cooling and tight confinement of the atoms. The design for the calcium two-photon clock is given, and the construction of the clock components is described. Experimental results are presented for the search for the clock transition frequency, which has never before been precisely determined. A detailed uncertainty budget is given, showing that this clock should be able to achieve a fractional frequency uncertainty of $\sim 10^{-17}$. In addition, a novel technique of ``magic polarization'' is presented which can be implemented to mitigate probe laser light shifts, long thought to be a serious impediment to precision two-photon clocks. An experiment in which a two-photon clock based on rubidium was launched and operated on a stratospheric balloon and subsequently recovered is also described. This work represents an advancement in the development of compact portable optical clocks which will further push the boundaries of precision measurement and our understanding of the universe.

Keywords: optical clock
precision measurement
quantum optics
Advisor: Vutha, Amar C