VictorJuiz/thesis huggingface dataset:
Volatility, Atmosphere and Relation: A Multi-Modal Ethnography of Petrochemical VOCs in Toronto, Canada
Keywords: atmosphere
chemical sensitivity
feminist science and technology studies
multi-modal ethnography
petrochemicals
volatile organic compounds

This dissertation draws from feminist science and technology studies (STS) and sociocultural anthropological theory and methods to explore multiple sources of knowledge production about petrochemical derived gases known as volatile organic compounds (VOCs) in Toronto, Canada. A multi-modal dissertation, it brings 18 months of ethnographic fieldwork at two fieldsites, a publicly-funded environmental health clinic, and the neighbourhood of South Parkdale together with original archival research, filmic media art, photography produced during collaborative workshops with chronically ill and disabled women, and autobiographical prose. Framed throughout by the key concept of “volatility,” an understanding that petrochemical volatile organic compounds have socially, affective, and economically volatile effects beyond the material, I articulate the uneven intergenerational consequences that everyday, long-term atmospheric exposures to petrochemicals in everyday consumer products have, underscoring intersectional forms of identity and difference. Medical chart review (N=82) and interviews (N=70) reveal how chemical sensitivities in particular are not adequately addressed by the existing highly gendered and classed medical system and disability insurance providers. Drawing on my experiences in housing organizing contexts and navigating rental housing accessibility, I point to how uneven distributions of atmospheric exposures especially impact low-income tenants and are instrumentalized in processes of renoviction (eviction via renovation). Given these stakes, I highlight the crip-led possibilities of collective atmospheric access production. I conclude by suggesting that collective relations to volatility must center how VOCs are signatures of chemical violence in settler colonial Toronto, and thus be foregrounded in relation to the historical and material preconditions of their existence. This is supported by an immanent relationship to material ethics, and building alliances across crip, anticolonial, and antiracist movements.
Searches for Lepton Flavour Violating Higgs Boson Decays with the ATLAS Detector
Keywords: ATLAS
Experiment
Flavour
Higgs
Lepton
Search

Measurements of the lepton flavour violating Higgs boson decays to the final states $e\tau$ and $\mu\tau$ are presented in this thesis. These measurements use data from proton-proton collisions measured by the ATLAS detector at a centre-of-mass energy of $\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. No signicant excess above the Standard Model predictions is observed and upper limits on the lepton flavour violating branching ratios are set.
Identification and Systemic Investigation of Novel Chemical Seed Priming Agents and their Persistent Effect on Plant Phenotype and Metabolism
Keywords: Anthocyanin
Arabidopsis
Chemical genetics
Plant stress
Seed priming

Priming is a general term for a phenomenon in which exposure to an early environmental stimulus results in a more rapid or vigorous response when the plant is exposed to subsequent challenges. Various types of priming have been described: ‘systemic acquired resistance’ against biotic stimuli, ‘epigenetic stress memory’ induced by repeated abiotic stimuli, and ‘seed priming’ treatments which apply water and additional adjuncts to seeds to improve crop performance. Using a high-throughput chemical genomic approach, thousands of small molecules were screened to identify compounds capable of ‘chemical priming’, asking if these could serve as artificial environments to persistently induce altered response to later abiotic challenges when applied as seed treatments. Several novel structural categories of molecules were identified that had the ability to reduce total anthocyanin accumulation in 7-18-day old seedlings induced by later low temperature challenge, persisting days after the removal of the compounds. Application variables were explored with thought to future use of the priming compounds as functional treatments: a dose-dependent relationship was established, the necessary temporal window of treatment was explored and reduced, and duration of additional effects on growth and development were documented to ensure minimal detrimental side effects on the treated plants. Cross-testing of the priming treatments identified by low temperature screening for ability to reduce anthocyanin induction by alternative exogenous and endogenous conditions showed consistent attenuative effect and revealed that the effect of priming on this metabolic phenotype was not specific to low temperature response. Targeted transcriptional profiling of genes encoding flavonoid and anthocyanin biosynthetic enzymes and untargeted metabolomic profiling of total plant extracts were undertaken to characterize the detailed effect of these chemical seed priming treatments on this pathway. These revealed significant continued perturbations in the secondary metabolism of chemically-primed plants including but not limited to the expected changes in anthocyanins, and suggested a potential target site in upstream phenylpropanoid regulation for further analysis. The presented research represents a proof-of-concept for the functional potential of seed priming with novel compounds, and underscores the complexity of secondary metabolism as a component of plant stress response.
Instability of Gravitational and Electromagnetic Perturbations of Extremal Reissner--Nordstr\"om Spacetime
Keywords: Extremal Reissner--Nordstr\"om
Instability
Linear Stability
Teukolsky system

We study the linear stability problem to gravitational and electromagnetic perturbations of the \textit{extremal}, $ |Q |=M, $ Reissner--Nordstr\"om spacetime, as a solution to the Einstein-Maxwell equations. Our work uses and extends the framework \cite{giorgi2019boundedness,giorgie2020boundedness} of Giorgi, and contrary to the subextremal case we prove that instability results hold, similar to those of Aretakis, for a set of gauge invariant quantities along the event horizon $ \mathcal{H}^+ $. In particular, for associated quantities shown to satisfy generalized Regge--Wheeler equations we prove decay, non-decay, and polynomial blow-up estimates asymptotically along $ \mathcal{H}^+ $, the exact behavior depending on the number of translation invariant derivatives that we take. As a consequence, we show that for generic initial data, solutions to the generalized Teukolsky system of positive and negative spin satisfy both stability and instability results. It is worth mentioning that the negative spin solutions are significantly more unstable, with the extreme curvature component $ \underline{\alpha} $ not decaying asymptotically along the event horizon $ \mathcal{H}^+, $ a result previously unknown in the literature.
The Dynamic Network Connectivity of Music Listening
Keywords: Aging
Computational neuroscience
Music
Network dynamics

Music listening is a sophisticated behaviour that employs numerous networks of brain regions. Because music remains enjoyable later in life, it is often used in clinical settings with those with neurodegeneration. However, much is still unknown about how music listening adapts to reconfigurations in brain network dynamics related to healthy aging. This dissertation examines dynamic brain network activity during music listening in healthy adults. Network measures were analyzed with behavioural and stimulus data across three studies using a combination of hidden Markov modelling and partial least squares. The first study presents age- and preference-related differences in music listening in healthy younger and older adults using fMRI. Both age groups showed higher occupancy (the proportion of time a network was active) in a temporal-mesolimbic network while listening to self-selected music. Activity in this network was strongly positively correlated with liking and familiarity ratings in younger adults, but was more ambiguously correlated in older adults. Additionally, older adults showed a higher degree of correlation between liking and familiarity ratings consistent with past behavioural work on age-related dedifferentiation. The second study presents effects in a subset of the older adult group from the first study following an 8-week music listening intervention. Results showed higher occupancy in the temporal-mesolimbic network following the intervention suggesting that network activity can change in response to music-based interventions. The third study presents task differences in a music listening task in healthy young adults using EEG. In this study, participants listened to music while continuously rating either perceptual features in the musical signal, or emotional states induced by the music. Network activity in medial frontoparietal, pericentral, anterior frontal, and bilateral temporal networks was most strongly positively correlated with rudimentary features in the musical signal during the perceptual listening task. In the emotional task, transitions between networks were more positively correlated with low-arousal low-valence emotional states in anterior cingulate, frontal, and occipital networks. I discuss the implications of modelling music at different spatiotemporal scales with a particular focus on these findings’ applicability for clinical research.
Essays in Computational Econometrics
Keywords: Computation
Econometrics

This thesis consists of three chapters, each in the form of a self-contained essay. In contemporary econometric research, computational limitations are often binding. This can be true in theoretical work, where restrictive assumptions are imposed to maintain computational tractability, or in empirical work, where large real-world datasets present computational challenges. Each essay in this thesis presents methods that relate to computational problems arising in econometric theory or applications. In the first essay, an improved Bayesian method for probabilistic record linkage in large matching problems, with an accompanying implementation in R/C++, is presented. The method refines the modelling of comparison data relative to previous methods, allowing the distribution of disagreement among non-matched pairs to be record-specific, leading to dramatic performance improvements in a large application, with accompanying computational improvements. The second essay considers partial identification of counterfactuals in a broad class of models with discrete outcomes and covariates and develops a procedure for computing the identified interval using several new computational tools, including a new algorithm for enumerating the cells induced by hyperplane arrangements. The third essay examines the problem of inference on the value function of a linear program where the right-hand side parameters are random. A tractable method for developing confidence intervals is presented that has asymptotically exact coverage and shows good performance in finite samples.
Developing Fluorescent Chemosensors and Activatable Photosensitizers for Cancer Biology
Keywords: Cytochrome P450
DNA Methyltransferases
Fluorescence Chemosensors
O6-Methylguanine DNA Methyltransferase
Photodynamic Therapy

Aberrant enzyme activity is a hallmark of cancer. Fluorescent chemosensors can directly measure enzyme activity to diagnose cancer, predict resistance to anti-cancer drugs, and to facilitate the discovery of novel anticancer drugs. Moreover, activatable photosensitizers (PS) further exploit aberrant enzyme activity in cancer by activating only in the presence of a cancer over-expressed enzyme. This allows activatable PS to enhance the cancer selectivity of photodynamic therapy (PDT), compared to non-activatable PS. In this work, fluorescent chemosensors and activatable PS were developed for three cancer-relevant enzymes. The first is O6-methylguanine methyltransferase (MGMT), for which fluorescent chemosensors were developed. MGMT activity is a predictor of resistance towards anticancer alkylating agents, making the development of MGMT fluorescent chemosensors highly warranted. We designed, synthesized, and evaluated an array of MGMT fluorescent chemosensors, using synthetic scaffolds based on AA-CW236, a covalent MGMT inhibitor. The chemosensors could measure MGMT activity in-vitro, however, further work needs to be done to improve selectivity for MGMT. Activatable PS for Cytochrome P4501A1 (CYP1A1) were also developed in this work since CYP1A1 is overexpressed in several cancer (including lung, breast, and ovarian). Our approach was to alkylate xanthene PSs at one xanthene hydroxyl, quenching fluorescence and photosensitization. We show that CYP1A1 can reverse this alkylation, thus activating the PSs in the presence of CYP1A1. However, lack of selectivity for CYP1A1 resulted in PDT that had poor selectivity for cells over-expressing CYP1A1. The third enzyme target explored in this work is DNA methyltransferase enzymes (MTases). MTases are responsible for epigenetic regulation, which is highly aberrant in cancer, therefore MTase chemosensors valuable tools to diagnose cancer. We attempted to synthesize aziridine analogues of s-adenosyl-l-methionine (SAM) to transfer a fluorophore to DNA labelled with a good FRET pair. Upon transfer of the SAM analogue to DNA, the resulting FRET signal should correlate with MTase activity. However, the aziridine SAM analogue scaffold proved too reactive, and we could not observe transfer of the SAM analogues to DNA. Therefore, the less reactive “double activated” SAM analogues should be explored in the future.
In Vivo Effects of Stereotactic Body Radiation Therapy on the Pancreatic Tumor Microenvironment
Keywords: Intravital microscopy
Mouse model
Pancreatic cancer
Stereotactic body radiation therapy
Tumor hypoxia
Tumor microenvironment

Despite decades of improvements in cancer therapies, the current standard of care for locally advanced pancreatic cancer (LAPC) provides, on average, only a few months of survival benefit. Stereotactic Body Radiation Therapy (SBRT), a technique that accurately delivers high doses of radiation to tumors, has emerged as a promising therapy to improve local control of LAPC; however, its effects on the tumor microenvironment and hypoxia remain poorly understood. Our group and others have shown that high-dose radiotherapy can cause significant damage to tumor blood vessels. Thus, we hypothesized that SBRT would result in vascular damage that may further lead to tumor hypoxia, potentially generating a more aggressive tumor phenotype. To explore this hypothesis, orthotopic pancreatic tumors in mice were treated with SBRT in 5 daily fractions (8 Gy/fraction, or ‘5×8Gy’) to simulate a typical SBRT dose regimen for LAPC patients. A small animal micro-irradiator with integrated three-dimensional bioluminescence imaging provided accurate spatial targeting for pancreatic tumors in the orthotopic setting. A novel experimental platform using intravital fluorescence microscopy was also developed to enable the longitudinal study of the pancreatic tumor microenvironment in vivo, including real-time quantification of pancreatic tumor cell hypoxia, blood vessels, and collagen structures, at cellular resolution. Contrary to our hypothesis, this platform demonstrated a persistent decrease in pancreatic tumor hypoxia as early as one day after SBRT, with no evidence of vascular damage. This coincided with significant tumor cell death and growth arrest from treatment, indicating that a decrease in the demand for oxygen within the pancreatic tumor microenvironment significantly contributed to its reoxygenation. Overall, the unique combination of a small animal irradiator with the orthotopic intravital imaging platform presented in this thesis provides a novel methodology to investigate the effects of SBRT on the pancreatic tumor microenvironment in vivo. The findings from this work allow us to better understand the mechanisms that influence the tumor response to SBRT and may help to inform clinical practice, potentially guiding the design of future SBRT-based clinical trials.
Role of the Anterior and Mediodorsal Thalamic Nuclei in Cognitive Processes
Keywords: Anterior Thalamus
Cognition
Executive
fMRI
Mediodorsal Thalamus
Memory

Our lab encountered a patient with developmental amnesia due to stroke damage to two subcortical regions: the anterior thalamus (AT) and mediodorsal thalamus (MD). To see cognitive deficits after damage to these subcortical regions was somewhat surprising as most research into amnesia historically focused on the hippocampus or prefrontal cortex. The present dissertation thus sought to explore the involvement of these subcortical regions in cognition. In chapter 1 I used functional magnetic resonance imaging to examine activations of the AT and MD of healthy adults during different phases of an associative memory task. I found that the AT showed a greater deactivation during successful memory encoding but that activations of the MD did not show any relation with task accuracy. In chapter 2 I took a different approach in order to address theories that suggest that the MD is important for other forms of cognition such as executive function. I examined recall, recognition, working memory, executive function, and language performance in a group of 22 patients with stroke damage to the thalamus. All cognitive processes were impaired in the thalamic stroke group but there was not a detectable link between which parts of the thalamus were damaged and specific deficits in cognition. Next, I sought to relate these cognitive functions to brain activity patterns in the cortex of these same thalamic stroke patients. Existing theories suggest that the thalamus, particularly the MD, modulates the way cortical regions communicate with each other. In chapter 3 I explored this theory in humans. I examined how patterns of communication between cortical regions as measured by “resting state” functional connectivity were different in thalamic stroke patients and controls. This analysis did not reveal any indication that MD damage disrupts cortico-cortical modulation. It is possible that the MD plays a more prominent role only during specific tasks or at smaller scales. Overall, the results suggest that the AT is involved in associative forms of memory but the role of the MD is less clear. However, a critical first step was made towards understanding the limitations of MD involvement in modulation of cortico-cortical communication.
Design Methods for “Effectively Engaging” Digital Health Behaviour Change Interventions
Keywords: behavioural science
co-design
design methods
design thinking
digital health
theories and frameworks

Digital health interventions are increasingly being designed to support health behaviour changes. Despite the promise of digital health behaviour change interventions to improve health outcomes, there is mixed evidence on whether they are effective in doing so. One key concern is that digital health behaviour change interventions are not “effectively engaging” patient and public users. “Effective engagement” with a digital health behaviour change intervention necessitates that users “micro-engage” with the digital intervention itself (e.g., log-in and use app features) and “macro- engage” with the behaviours the intervention aims to support (e.g., complete physiotherapy exercises). This thesis explored the research question: how can design methods be optimized to support the development of digital health behaviour change interventions that aim to “effectively engage” patients and the public? Paper 1 scoped the literature to examine how digital health design teams can integrate insights from behavioural science and design thinking to develop more “effectively engaging” digital health behaviour change interventions. This paper found that design teams can follow an interdisciplinary, amalgamated approach, referred to as “Behavioural Design Thinking.” Paper 2 used qualitative interviews with digital health design leaders and patient- public partners to explore how to maximize the value of patient-public co-design in the digital health behaviour change design process. This paper found that the value of patient-public co-design extends far beyond product design improvement; patient-public co-design also adds value by ensuring more appropriate implementation planning and more empowering, sustainable partnership building. Paper 3 used qualitative interviews with digital health design leaders to explore how design leaders select and use behavioural science theories, models, and frameworks (TMFs) to guide digital health behaviour change design. This paper found that there is no “magic bullet” behavioural science TMF. The selection of TMFs in digital health behaviour change design is highly nuanced and clearer guidance is needed to help design teams select and use TMFs more meticulously. Overall, this thesis provided a starting point to open the “black box” of digital health behaviour change design methods optimization. Future work is needed to create design methodological guidance that will help ensure digital health interventions are purposefully designed to support “effective engagement.”
Multimodal Neuroimaging as a Means to Explore, Refine, and Personalize Neuropsychiatric Deep Brain Stimulation Therapy
Keywords: Deep brain stimulation
Depression
Magnetic resonance imaging
Neuroimaging
Psychiatry
Subcallosal cingulate area

Deep brain stimulation (DBS), a neurosurgical intervention in which implanted electrodes are used to modulate dysregulated neural circuits, is a safe and effective therapy for a variety of neurological conditions. Over the last two decades, considerable clinical research has investigated subcallosal cingulate area DBS (SCC-DBS) as a tool for managing severe treatment-resistant depression. This work has produced promising results, with approximately half of treated patients experiencing meaningful clinical improvement (i.e., ‘response’) in open-label trials. Despite this, the ‘failure’ of the largest randomized controlled trial to date and the general difficulty in predicting and optimizing clinical response to SCC-DBS indicate the need for a deeper understanding of this therapy’s mechanism of action and the identification of biomarkers that could guide treatment decisions and improve therapeutic outcomes. This thesis focused on the use of multimodal neuroimaging to characterize the impact of SCC-DBS on brain circuits and to explore factors that explain variance in antidepressant outcome. Our work involved four major components: i) exploring the relationship between stimulation location and clinical outcome using volume of tissue activated modelling and probabilistic stimulation mapping; ii) mapping connectivity patterns associated with efficacious stimulation using normative diffusion-weighted MRI data; iii) investigating potential differences in pre- and post-operative glucose metabolism and brain volume between responders and non-responders; iv) studying acute stimulation-linked changes in brain activity using functional MRI scans acquired under varying DBS conditions. Our results indicated that the precise locus of stimulation within the target region and the engagement of specific white matter tracts are important – albeit incomplete – predictors of clinical outcome. They revealed robust pre-operative differences in brain metabolism and structure between eventual responders and non-responders, suggesting response to SCC-DBS is influenced in part by intrinsic characteristics, and identified how these features changed over months-to-years of chronic stimulation. Finally, they evinced rapid, fMRI-detectable brain activity changes associated with active stimulation that related to long-term outcome and distinguished optimal and suboptimal stimulation settings. Overall, these findings enrich our understanding of the network-level mechanisms of SCC-DBS and proffer candidate biomarkers that might help refine and personalize this therapy through improved patient selection, electrode placement, and stimulation parameter programming.