VictorJuiz/thesis huggingface dataset:
Correlates and Prediction of Generalized Anxiety Disorder from Acoustic and Linguistic Features of Impromptu Speech

The diagnosis and tracking of Generalized Anxiety Disorder (GAD) require frequent interaction with mental health professionals, but there are not enough professionals to serve the demand. The ability to automatically detect anxiety disorders through samples of speech could be a valuable complement to conventional treatment and provide greater access to it. In this work, we explore acoustic and linguistic features of speech that correlate with anxiety and use those to predict above or below the screening threshold of GAD. A large number of participants (N = 2, 000) participated in a single online study session where they completed the Generalized Anxiety Disorder-7 (GAD-7) assessment and provided an impromptu speech sample in response to a modified version of the Trier Social Stress Test (TSST). Acoustic and linguistic speech features were a-priori selected based on the existing speech and anxiety literature, together with related features. Associations between speech features and anxiety levels were assessed using sex, age, and personal income included as covariates. The amount of speech had the most significant correlation with GAD-7 (r = −0.12; P < .001), indicating that participants with higher anxiety scores spoke less. Linguistic features acquired using Linguistic Inquiry and Word Count (LIWC) were also significantly (P < .05) associated with anxiety. Using these acoustic and LIWC features to predict above or below a screening threshold of 10 for GAD, a logistic regression model achieved a mean AUROC = 0.57, SD = 0.03. The mean AUROC increased to 0.62 (SD = 0.03) when demographic information (age, sex, and income) was included indicating the importance of demographics when screening for anxiety disorders. The LIWC linguistic features are based on single-word counts and do not account for the surrounding word context. We attempted the same prediction based on greater context using a transformer-based neural-network model (pre-trained on large textual corpora) and fine-tuned on the speech transcripts. This model, which only uses the textual input, achieved an AUROC value of 0.64. When acoustic, LIWC, and the predicted output of the fine-tuned transformer-based model are combined into one model, the AUROC increased to 0.67 and further increased to 0.68 when demographic information was included. The results suggest that there is a signal of anxiety within such impromptu speech that may be useful as part of a system to screen for anxiety, detect relapse, or monitor treatment.

Keywords: Anxiety Prediction
Digital Health
Generalized Anxiety Disorder
Machine Learning
Mental Health
Natural Language Processing
Advisor: Rose, Jonathan S
A Network Approach to Cultural Interaction and Maritime Connectivity on Crete during the Late Bronze Age – Late Minoan II – IIIB2

Approaches to trade and exchange in the Late Bronze Age (LBA) have generally centred on one class of artifacts: those identified as long-distance imports or exotica. This has served to limit the discussion of trade and exchange in the LBA to one scale of analysis: the international and long-distance. This emphasis on the long-distance has, however, disregarded the movement of goods at a range of other scales. This thesis takes an empirical approach to LBA connectivity and interaction in the eastern Mediterranean by focusing on Crete during the Late Minoan II to Late Minoan IIIB period. I argue that making sense of large-scale patterns of interaction visible in the archaeological record of the LBA also requires a consideration of connectivity at a much smaller scale: locally, between people and the objects they used; regionally, between various settlements; and trans-regionally, between larger regional centres on the island. I utilize a collected dataset of 13,737 ceramic entries from published assemblages at the sites of Chania, Knossos, Kommos, Mochlos, and Palaikastro. With this data, I explore interaction and maritime mobility from a nested, diachronic perspective and argue that connections between these local and regional communities form the backbone of larger social and economic networks. I then highlight the range of possible interactions at this smaller, local scale, through an in-depth case study of the consumption of imports in local assemblages from one building at Kommos. I explore access and mobility between these settlements on Crete by applying new methods and models adapted from network science and GIS for modelling interaction. Lastly, I discuss the results of the modelling in tandem with the collected ceramic data to highlight the advantages of an interdisciplinary, multiscalar approach in exploring LBA interaction.

Advisor: Knappett, Carl
Feasibility of Skull Base Neuronavigation Using Optical Topographic Imaging Toward Guidance of Human and Robotic Drill Operators

Mastoidectomy is a surgical procedure that allows access to critical portions of the skull base in order to treat a broad range of conditions. Mastoidectomy requires enormous precision and focus in order to avoid critical structures such as veins or nerves, and often occurs at the beginning of long, complex skull base operations, leading to cognitive and physical fatigue before some of the most crucial portions of a surgery have occurred. Neuronavigation, the technique of using preoperative imaging and patient anatomy to generate a surgical roadmap, is often used to facilitate safe mastoidectomy in current clinical practice. Optical topographical imaging (OTI) is a form of neuronavigation that uses structured light projected onto the operative surface to facilitate co-registration of 3D space with preoperative imaging. This thesis endeavored to explore whether OTI-assisted neuronavigation could be combined with multi-parameter, realtime data collection of the mechanical parameters of mastoidectomy, with the ultimate goal of developing a platform to be used in the future for robotic mastoidectomy. First, a comprehensive review of the current body of literature surrounding robotic mastoidectomy revealed that previous investigators had not yet quantified the mechanical parameters of mastoidectomy. Our next step was to compare both OTI-assisted and free-hand mastoidectomy, which revealed that OTI-assistance led to shorter procedure times. This set of experiments also demonstrated that OTI navigation was accurate in the skull base, while highlighting room for improvement of the accuracy of OTI navigation. Following this, we used an iterative design approach to develop a platform for multi-parameter, real-time data collection during the drilling. This platform allows for the collection of data ranging from drill tip movement to force magnitude in all three dimensions throughout mastoidectomy. Ultimately, this body of work serves to advance the goal of robotic OTI-assisted mastoidectomy by demonstrating the feasibility of OTI-assisted neuronavigation in the lateral skull base and developing a platform which can be used to create a reference database of the mechanical parameters of mastoidectomy, effectively serving to quantify a previously qualitative process. Future projects may use this database, in combination with patient-specific preoperative imaging, to train roboticalgorithms to perform mastoidectomy.

Keywords: Mastoidectomy
Neuronavigation
Optical topographic imaging
Skull base
Target registration error
Temporal bone
Advisor: Yang, Victor
The Ecological Consequences of Hummingbird Pollination for Plant Mating Systems

Plant-pollinator interactions are an essential component of the ecology and evolution of natural and agricultural ecosystems, as they drive the ecological process of pollination and determine the outcomes of plant mating. My PhD thesis capitalized on plant-pollinator interactions in Heliconia tortuosa Griggs (Heliconiaceae) to understand the role of the ecological process of pollination as a driver of the outcomes of plant mating. The ecological process of pollination in H. tortuosa is exclusively mediated by territorial and trapline foraging hummingbirds. My PhD thesis combined a landscape-scale observational field survey, a variety of techniques of molecular biology, and a breadth of methods in statistical analysis to evaluate the interplay of ecology and evolution through the process of pollination. In Chapter 2, I found that patterns of pollen-mediated gene flow in H. tortuosa are characterized by a signature that is consistent with the behaviour of trapline foraging pollinators. I demonstrated that patterns of pollen-mediated gene flow can provide information to infer the foraging behaviour of pollinators. In Chapter 3, I found that deforestation altered the composition of the pollinator community through the decline of trapline foraging pollinators. This impact reduced the quality of pollen received by H. tortuosa individuals, as it reduced the genetic diversity of progeny and enhanced inbreeding. Given this perspective, I identified important implications for the conservation of plant-pollinator interactions. In Chapter 4, I found novel consequences of the foraging behaviour of pollinators for patterns of cross-fertilization and multiple paternity in H. tortuosa, with particular attention to the impact of trapline foraging. I demonstrated that variation in the foraging behaviour of pollinators can have divergent implications for the outcomes of plant mating. My PhD thesis demonstrated that disparities in the pollen transport mechanism can have profound implications for the ecology and evolution of plant mating. In particular, my PhD thesis revealed that the foraging behaviour of pollinators and the composition of the pollinator community are fundamental factors that determine patterns of pollen-mediated gene flow, self-fertilization, cross-fertilization, and multiple paternity in plants. Collectively, my PhD thesis contributed to a rich literature that has established a dialogue of ecology and evolution in the study of plant-pollinator interactions.

Keywords: Plant mating systems
Plant-pollinator interactions
Pollination ecology
Advisor: Wagner, Helene H
Influence of Chronic Disease and Comorbidity on Colorectal Cancer Screening and Diagnostic Testing

Colorectal cancer (CRC) is a leading cause of morbidity and mortality. Population-based CRC screening has been recommended by in Canada since 2001 and organized screening programs, which involve coordinated activities from screening through diagnosis, have been implemented in most Canadian jurisdictions. Those who have chronic comorbidities may be less likely to participate in all steps of the cancer preventive pathway due to the competing demands of chronic disease management. As some major chronic conditions are also associated with increased cancer morbidity and mortality, understanding the use of cancer preventive services in these populations is necessary to improve the effectiveness of screening programs.This dissertation aimed to determine whether major chronic medical and mental health comorbidities are associated with lower use CRC screening and follow-up diagnostic testing, focusing on the province of Ontario, Canada. The first study was a systematic review and meta-analysis examining the effect of one “model” chronic condition – diabetes – on screening for CRC and other common cancers for which universal screening has been recommended (breast and cervical cancer). The second and third studies were longitudinal population-based cohorts using Ontario health administrative data, with the second study investigating the influence of diabetes, heart disease, renal failure, chronic obstructive pulmonary disease, and mental health conditions on periodic CRC screening test uptake, and the third study considering the effects of these conditions on follow-up diagnostic testing receipt. The first study found that diabetes was associated with lower likelihood of breast and cervical cancer screening, while the results for CRC screening were mixed. There were significant methodological limitations in the evidence base, including the focus on one-time screening in opportunistic settings and the use of cross-sectional designs and self-report data. The second and third studies found that major chronic conditions were associated with lower rates of periodically becoming up-to-date with CRC screening and with receiving follow-up testing. Having multiple medical conditions or comorbid medical and mental health conditions exacerbated these relationships. The findings of this thesis highlight that organized screening programs may need to consider additional strategies to reduce breakdowns in the cancer preventive pathway and improve appropriateness of screening for people with comorbidities.

Keywords: Cancer prevention
Cancer screening
Chronic disease
Comorbidity
Multimorbidity
Advisor: Lipscombe, Lorraine L.
The Impact of Indoor Air Quality and Exposure to Indoor Air Pollutants on Cognitive Function

In addition to the well-recognized comfort and health impacts, indoor air quality has been linked with cognitive function and further with work productivity and learning performance. Such cognitive impact has significant economic consequences and may serve as an additional incentive for IAQ improvement. However, our current understanding of this link is limited, with the causal agents not identified and the mechanisms not understood. This thesis explores the cognitive impact of IAQ through firstly synthesizing existing experimental investigations of the role of CO2 and ventilation in affecting cognitive function and identifying the causes of discrepancies in the literature and then conducting human exposure experiments to assess cognitive responses to exposures to emissions from a strong source. The results of the review suggest a strong link between ventilation rates and cognitive function but mixed and sometimes contradictory effects of CO2 on cognitive performance even after controlling for inconsistency in experimental designs. The exposure experiments saw a few significant changes but mostly trends in decision-making patterns towards more impulsive behaviour with subjects exposed to emissions from an essential oil diffuser using scented lemon oil or non-scented grapeseed oil. Further, methods were developed for characterizing emissions sources and monitoring long-term air change rate and pollutant removal rates to facilitate future research on IAQ and cognitive performance. Findings in this thesis suggest a clear correlation between overall IAQ and cognitive performance and a less definitive link between specific pollutants, such as CO2, PM, and VOCs, and distinctive brain functions including executive functioning, memory, and response inhibition. Despite the complexity of controlling airborne exposure and assessing cognitive function, understanding the cognitive impact of IAQ is crucial for the health and performance of building occupants and the development of the building industry.

Keywords: carbon dioxide
essential oil
IAQ
machine learning
ventilation
work performance
Advisor: Siegel, Jeffrey A
Customized Approaches for Inhibition and Degradation of Drug Targets

Diseases are often caused by increase or decrease of specific proteins, and changes in the level of their activities in cell. Many cancers have already been directly or indirectly linked to such changes, for example. This necessitates development of therapeutics for diseases caused by such imbalances and dysregulations. Therefore, the dysregulated proteins are attractive drug targets, and small molecules are needed to modulate their function or antagonize their interactions with partner proteins. However, some protein targets may not be druggable, and finding small molecule modulators of their function may not be practical. Alternative approach would be to selectively target these proteins for degradation. This approach utilizes protein degradation pathway to specifically ubiquitinate the protein of interest by E3 ligases and mark it for degradation. My research takes advantage of all available options for modulating the level of activities of drug targets. Major step in the discovery of small molecule modulators of drug targets is to characterize their function and develop high throughput methods for screening. In the first chapter of my thesis, I focused on better understanding of the mechanism of function of protein arginine methyltransferase (PRMT) 1 in nucleosome setting by investigating its crosstalk with other methyltransferases. This study resulted in discovery of the activating effect of monomethylation of H4K20 on nucleosome by SETD8 on H4R3 methylation by PRMT1. In the second chapter, I focused on discovery of ligands for DDB1 Cul4-associated factor 1 (DCAF1) to employ the protein degradation approach. This project resulted in discovery of a potent antagonist of DCAF1 with a Kd value of 38 nM, a great step in the development for a chemical probe or PROTAC. Utilizing the two different approaches in targeting proteins of interest, will result in new opportunities that can facilitate early-stage drug discovery.

Keywords: crosstalk
degradation
drug discovery
epigenetics
histone modifiers
inhibition
Advisor: Vedadi, Masoud
Designing Algorithms for Quantum Computers of the Near Future

Variational quantum algorithms (VQAs) have emerged as the leading strategy for using these noisy devices to achieve an advantage over their classical counterparts.VQAs use a hybrid quantum-classical framework, in which one employs the quantum computer to prepare a parameterized quantum state and outsource the optimization to a classical subroutine. VQAs have been proposed for applications in various fields, including physics, quantum chemistry, machine learning, and optimization. Nevertheless, many challenges must be addressed before we can use them for practical tasks. In this dissertation, we propose strategies to overcome some challenges in implementing VQAs. We first look at the issue of trainability for VQAs and propose three methods for optimizing them.The first method is based on natural evolutionary strategies (NES) and can alleviate the issue of vanishing gradients for randomly initialized parameterized quantum circuits (PQCs). The second method is based on the notion of information flow in PQCs and uses a mutual information-based distance metric to define paths for stochastic optimization of VQAs. Finally, we develop gradient evaluation procedures for optimizing objectives with the unitary coupled-cluster ansatz. Next, we study the issue of expressibility of PQCs used in variational algorithms.First, using the theory of quantum optimal control we define a notion of reachability of general ans\"atze used in VQAs. Next, using a variational autoencoder (VAE) coupled with a regression model, we try to gain a better understanding of the parameterization of PQCs. Finally, we attempt to remedy the inefficient usage of quantum resources for storing quantum data using evolutionary strategies to design quantum circuits for compressing quantum data. We present numerical evidence that the work presented here can increase trainability, efficiency, and understanding of VQAs.We believe our work is of interest to the quantum computing community as we continue to push the limits of NISQ devices for solving practical problems.

Advisor: Aspuru-Guzik, Alán
Informal Caregiving: Health System Cost Implications and Caregiver Outcomes

Care provided by unpaid caregivers, is often seen as a lower cost substitute to care provided by health care providers (formal care), and hence the prevailing assumption is that caregivers’ contributions reduce healthcare costs. One unintended consequence of caregiving is a deterioration in caregiver’s health which could a) impact caregivers’ ability to provide care affecting care-recipients’ use of formal healthcare services; and b) result in a potential increase in healthcare utilization for caregivers themselves. Changes in healthcare resource use due to caregiving health consequences are direct costs to the healthcare system which have been largely omitted in healthcare policy and research. The overarching objective of this thesis is to provide a more accurate estimation of costs and consequences associated with caregiving. This is done by investigating patterns of: 1) healthcare use among caregivers; 2) healthcare use among care-recipients due to the consequences of caregiving; and 3) developing and validating a comprehensive tool that could facilitate routine measurement of caregiving and systematic inclusion of caregiving consequences in the policy making process. The first study was a difference-in-differences cohort study examining the impact of caregiving on caregivers’ use of healthcare services, before and after caregiving in comparison to non-caregivers using administrative databases. Results showed that adjusted total healthcare costs for caregivers were 10% lower than non-caregivers two years into caregiving. The second study was a longitudinal study examining the impact of caregiver distress on care-recipient’s use of healthcare services using administrative databases. The study found that caregiver distress was associated with a 4% increase in care-recipient’s total healthcare costs every six months. The third study reported on the development and validation of a caregiving survey. The survey was co-designed with caregivers providing a simultaneous measurement of caregivers’ health, experience of care, and costs. The analysis of the survey revealed four scales relating to care burden, care partner, caregiver assessment, and care integration. This thesis used novel data and methods to estimate the cost and consequences of caregiving and identifies issues that should be considered in healthcare policy making and in the design and evaluation of healthcare services.

Keywords: Caregiving experience
Family caregiving
formal and informal care
Healthcare expenditure
Healthcare utilization
Advisor: Wodchis, Walter