VictorJuiz/thesis huggingface dataset:
Evaluation of Cost-Effectiveness for Lung Transplant and Ex-Vivo Lung Perfusion
Keywords: Economic Evaluation
Ex-Vivo Lung Perfusion
Health Economics
Health Technology Assessment
Lung Transplantation
Organ Preservation

Demand for lung transplantation exceeds the supply of suitable donor lungs. Ex-vivo lung perfusion (EVLP) is a technology that enables further objective evaluation of potentially-useable organs, as well as rehabilitation of “marginal-risk” donor lungs, outside the body prior to transplantation, which together may increase organ supply and overcome this bottleneck. However, the decision of whether to fund EVLP and integrate it into lung transplant programs must be supported by evidence that considers the clinical, economic, and humanistic consequences of the technology; for EVLP to justifiably receive healthcare resources, the costs, health outcomes, and incremental cost-utility of the technology must be determined. The goal of this thesis was to conduct an economic evaluation of lung transplantation with versus without EVLP at the largest lung transplant center in North America. Our first study determined the impact of EVLP on the cumulative and phase-specific hospital-perspective costs of lung transplantation in Ontario, Canada. This retrospective before-after cohort study presented a novel methodology for phase-based costing that uses multi-state survival regression to overcome the limitations of conventional costing methods. Study 2 evaluated the impact of EVLP on organ transplantation and patient outcomes, using linked health administrative data from the only adult lung transplantation centre in Ontario, Canada, and identified the health resource and clinical implications of having EVLP available. Study 3 involved a cost-utility analysis using an individual patient simulation. This study used input parameters from our antecedent studies to inform a decision-analytic model that estimates the number of transplants, cumulative lifetime costs, and projected health outcomes expressed as quality-adjusted life-years (QALYs). Results from our observational studies suggest that the implementation of EVLP in the Toronto Lung Transplant Program at the University Health Network has been associated with improved accessibility to transplantation, improvements in several clinical outcomes, but no significant difference in phase-specific or cumulative costs. We found that having EVLP available should be considered cost- effective across a range of commonly accepted cost-effectiveness thresholds. Collectively, this thesis synthesized evidence that EVLP was economically justifiable at our centre; these findings may be used by clinicians, administrators, and other institutional stakeholders involved in resource allocation and funding decisions.
Development of Multi-functional Electroactive Fibers for Electrophysiological Application
Keywords: Conductive Elastomers
Conductive Fiber
Dry Textile Electrode
ECG monitoring
PEDOT:PSS
Textile Computing

Recent advances in telemedicine and personalized healthcare have motivated a wave of new developments in wearable technologies targeting continuous monitoring of biosignals. The common limitations of wearables for continuous monitoring are the durability, flexibility and breathability of their biopotential electrodes interfacing the body. Our studies tackle these challenges by proposing flexible, breathable, and washable dry textile electrodes made of electroactive fibers. In this thesis, we developed conductive elastomeric filament (CEF) fibers through melt spinning. Using an industrial scale knitting machine, CEF fibers were directly knitted into dry textile electrodes. Underwear and headband garments with integrated textile electrodes were knitted and electrocardiograms (ECGs) were acquired using the underwear garment and electrooculograms (EOGs) were acquired using the headband. ECG and EOG recordings with textile electrodes were found to have comparable fidelity to that of the gold standard gel electrodes. CEF electrodes were continued to acquire high-fidelity ECGs and EOGs after 30 wash and dry cycles. Smart underwear garments were also used to perform continuous ECG measurements in 5 participants over 24-hour of unrestricted daily activities. Results demonstrated the success of these garments in performing high fidelity continuous ECG monitoring. We also developed novel multifunctional electroactive fibers with various cross-sectional geometries for electrophysiological applications. Different fiber materials with cross-sectional geometry of round, ribbon, and trilobal were coated using poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS) biocompatible conductive ink through a continuous roll-to-roll coating technique. Physico-chemical interactions between the fiber substrates and PEDOT:PSS ink were calculated based on the Owens, Wendt, Rabel and Kaelble (OWRK) method. Coated fibers were knitted into 3D textile electrodes using an industrial knitting machine. The electrochemical impedance spectroscopy, skin-electrode impedance, and ECG signals of the knitted electrodes after repetitive wash cycles were used as criteria to study the electrode’s performance for biomedical applications. The results showed that factors such as capillary force, cross-section of the filaments, and type of polymer materials affect the adhesion properties of the conductive ink to the fiber substrates. Collectively, the results of our studies present novel dry textile electrodes as a promising scalable solution to the challenges of wearable technologies for long-term continuous electrophysiological monitoring applications.
Sounding the Alarm: An Exploration of Professionalization within the Ontario Fire Service Focused on the Issues, Challenges, Pressures, and Opportunities for Transforming a Lauded Public Sector Institution
Keywords: Fire service
Firefighters
Institutionalism
Neoliberalism
Profession
Professionalization

The fire service is highly regarded by the community and is routinely recognized as a highly trusted occupation. The demands placed on the fire service have grown substantially in recent years due to neoliberal pressures, growing fiscal costs, accountability pressures, an expanding emergency response mandate, and the acquisition of additional non-emergency roles. This thesis explores the extent to which these changes are resulting in the professionalization of the Ontario fire service. It employs historical and sociological institutionalism to examine the Ontario fire service as an institution to understand factors influencing its behaviour and shaping its change mechanisms. It uses related theoretical concepts of institutional agency, path dependence, endogenous and exogenous variables, rule makers versus rule takers, and institutional isomorphism to provide insight on how institutional change occurs or does not occur. This study comprised twenty-four interviews with leaders from Ontario and international fire services, the Ontario police and paramedic services, senior municipal officials, labour relations experts and higher education professors. The findings of this study suggest that the Ontario fire service may be approaching a critical juncture whereby it is forced to adapt to neoliberal pressures and pressures for occupational change to remain effective and become more professionalized, despite its entrenched nature as a long-standing hierarchically structured but non-professionalized institution. These pressures combined with growing calls for change are challenging the ingrained status quo. This study contributes to the literature on institutionalism and the professions through its exploration of an understudied institution. While the focus is the Ontario fire service, the findings may have implications for other fire services and similar institutions. It finds tensions between pressures for professionalization on the one hand, and neoliberal fiscal pressures on the other. These complexities contribute to firefighters embodying a quasi-professional status that gains legitimacy from the ‘heroic work’ it undertakes rather than by qualifications or credentials. Furthermore, the post-pandemic workplace and a newer generation of workers are producing institutional pressures that can potentially shift the entrenched fire service. This research sheds light on the Ontario fire service through an academic lens and reveals a complex institution facing a challenging trajectory.
Sequential Decision-Making in Networking Algorithms using Deep Reinforcement Learning
Keywords: Adaptive Bitrate Selection
Congestion Control
Machine Learning
Network Adaptive Coding
Reinforcement Learning

Networking algorithms perform sequential decision-making on the Internet, where they take decisions, e.g., on when to transmit a packet. Traditional networking algorithms use fixed mappings between network-level events and control responses, which may result in inefficient usage of network resources in some network environments. The main issue with existing networking algorithms is the lack of generalization to diverse network environments. This results in poor performance in a wide variety of network environments. This dissertation proposes new techniques in reinforcement learning (RL) to solve the lack of generalization issue. We propose new RL techniques and study them in congestion control, network adaptive coding, and adaptive bitrate selection. First, we present Pareto, a congestion control algorithm fueled by deep reinforcement learning (DRL). Different from existing RL-based congestion control algorithms, Pareto uses expert demonstrations, a new staged training process, multi-agent RL fairness training framework, and online adaptation to new environments. All of these techniques enable Pareto to perform well in a wide variety of environments in terms of high throughput, low latency, low loss rate and fairness to competing flows. In network adaptive coding, we propose Ivory, a new DRL-based network adaptive coding algorithm that utilizes an existing low-latency forward error correction (FEC) scheme. Ivory chooses better coding parameters to ensure a low loss rate and latency while having lower coding overhead compared to the state-of-the-art. Lower coding overhead makes Ivory a better fit for limited bandwidth networks. Since interactions with the environment are costly in online RL, we propose Lethe, a new online RL approach to quickly acquire new knowledge by biasing against old interfering knowledge. In Lethe, we solve issues resulting from interference between knowledge acquired in different time slots. On a different note, in federated learning (FL), interference occurs when the server simultaneously accumulates models from clients with interfering objectives. To avoid inter-client interference, we propose Cascade, a curriculum-federated RL framework. Cascade is tested by training an adaptive bitrate selection algorithm, and it achieves a better asymptotic behavior with fairer knowledge accumulation as compared to other FL algorithms. This results in a better performance over diverse network environments.
Where is Communication Breaking Down? Narrative Tensions in Obesity-in-Pregnancy Clinical Encounters
Keywords: Clinical Encounters
Narrative
Obesity
Obstetrics
Pregnancy
Qualitative

Clinical encounters in the context of obesity in pregnancy can be complex to navigate. The biomedical literature on obesity in pregnancy focuses on numerous adverse outcomes that these patients are at an increased risk of, and the associated procedural difficulties. In contrast, the literature on patients’ lived experiences characterizes obesity in pregnancy as challenging due to stigma, and feel weight is overemphasized. To date, studies lack an exploration of stories of both patients and healthcare providers (HCPs) in tandem, as they relate to these clinical encounters. The objective of the study was to understand the communication challenges within obesity-in-pregnancy clinical encounters. I conducted in-depth, semi-structured narrative interviews with 16 patients and 19 HCPs. Stigma theory informed this work, along with Goffman’s dramaturgical approach, which allowed for an exploration of how participants portrayed their identities when describing these encounters and communication. In my analysis of their accounts, I identified five narrative tensions that contributed to communication challenges. The first three tensions related to obesity: 1) obesity is only seen as a detriment to health versus acceptance of obesity; 2) obesity is a result of personal choice versus a result of uncontrollable circumstances; and 3) a regular pregnancy versus a high-risk diagnosis. The fourth and fifth tensions related to characterizations of the obesity-in-pregnancy clinical encounter and the communication therein: 4) a typical and problem-free clinical encounter versus a tremendously difficult clinical encounter; and 5) talking openly about BMI and related co-morbidities versus sidestepping the topic. How participants positioned themselves relative to prevailing societal discourse regarding obesity and being a ‘good’ HCP/patient influenced these tensions. These narrative tensions revealed specific areas where communication is vulnerable to breaking down. They also illuminated the experiences of both HCPs and patients (and the meaning they ascribe), as well as the complexities in this interactive space. This research has important implications for improving clinical practice and education. Beyond the implications in the realm of obesity in pregnancy, this approach and these findings may be applicable to other obesity contexts, to improve clinical encounters for people of larger body sizes.
A Quantitative Study of Occupational Stress in Animal Shelter Workers
Keywords: Animal
Care Worker
Occupational
Shelter
Stress

Animal shelter workers are a unique cohort of care workers who have been shown to have high levels of burnout, compassion fatigue, and occupational stress. The full extent of the burden of this type of work is still being discovered. We deployed an online survey (n = 113) which included a novel occupational stress questionnaire and established mental health measures to evaluate levels of compassion fatigue, potential for moral injury, anxiety, and depression in animal shelter workers. Specific variables of interest were type of worker (full/part- time/volunteer), reason for euthanasia (medical vs. non-medical), and level of training. Results reveal only a small percentage of shelters did not practice any form of euthanasia (9%). Overall, respondents exceeded normative levels of burnout, compassion fatigue/secondary trauma, depression, and anxiety. Shelter work was shown to place respondents at a higher-than-average risk of moral injury, which was found to be significantly correlated with depression, anxiety, and compassion fatigue, and inversely related to optimism. Moral injury was higher for shelter workers whose work included euthanasia for non-medical reasons. Euthanasia for non-medical reasons and having formal animal care training, however, were not associated with significant increases in depression, compassion fatigue, or optimism. Full-time workers were found to have significantly higher levels of anxiety, depression, and risk of moral injury than part-time workers and volunteers. A factor analysis of the 43 workplace stressors included in the novel occupational stressor questionnaire revealed four distinct dimensions: 1) involvement in policy and decision-making, 2) public perceptions and stigma, 3) staff and the environment, and 4) job rigidity and social support. Of these scales, job rigidity and social support were found to have the greatest impact on burnout, depression, anxiety, optimism, and compassion fatigue/secondary trauma. Involvement in policy and decision-making had the greatest impact on moral injury. It is clear from our findings that the mental health burden of caring for shelter animals is great. Our findings add four distinct areas of focus that policy and decision-makers may consider to improve the wellbeing of animal shelter workers.
A Geometric Approach for Generating Feasible Configurations of Robotic Manipulators
Keywords: Distance geometry
Kinematics
Manipulability
Manipulation
Riemannian geometry

Most robotic manipulators, and especially those designed with autonomous operation in mind, consist of a series of joints that rotate about a single axis, also known as revolute joints. These mechanisms give robotic manipulators the degrees of freedom and versatility similar to that of the human arm, which they are designed to outperform. However, this results in a geometry of motion or kinematics that makes all aspects of robotic manipulation challenging from a computational perspective. A major part of this challenge lies in the fact that computing joint configurations adhering to a specific set of constraints (i.e., gripper pose) is a non-trivial problem. The procedure of finding feasible joint configurations and the mathematical problem associated with it are known as inverse kinematics - a core part of motion planning, trajectory optimization, calibration and other important challenges in successfully performing robotic manipulation. In recent years, the overall decrease of computation time required to perceive and process environmental and proprioceptive information has helped realize the potential of robotic manipulation in dynamic environments. Concurrently, a new standard in manipulator design has emerged, where additional degrees of freedom are added in order to increase their overall dexterity and capacity for motion. These two developments have vastly increased the requirements for inverse kinematics algorithms, which are now expected to deal with infinite solution spaces and difficult, nonlinear constraints. On the other hand, the addition of degrees of freedom in recent robot designs has enabled algorithms to search for locally optimal configurations with respect to some performance criteria in an infinitely large solution space. This property has motivated approaches that leverage non-Euclidean geometries to replace conventional constraints and optimization criteria, thereby overcoming computational bottlenecks and common failure modes. The contributions presented in this thesis propose three such approaches, that aim to develop new ways of looking at the problems associated with inverse kinematics through the use of geometric representations that are not widely utilized in robotic manipulation.
Improving Reliability and Performance of Storage Stacks on next generation Solid State Drives
Keywords: Computational Storage Drives
Performance
Reliability
Solid State Drives
Write Once Memory Codes

Solid State Drives (SSDs) are increasingly replacing HDDs as the primary source of persistent storage medium in both data centers and personal storage devices. SSDs offer higher performance and consume less power. They also bring two challenges in the storage space: First, SSDs have different reliability characteristics than HDDs. However, the impact of various SSD-based errors on the overlying software stack is not well known. Furthermore, as the demand for high-capacity SSDs increases, more bits are stored within the same voltage range of the underlying SSD medium. Second, with the end of Moore’s law, there is increased emphasis on disaggregated computing where data-intensive computation takes place on a processor within the device. Applications can offload computation from the host to the device, save host CPU cycles, lower host-to-device latency, and reduce bandwidth utilization. However, such devices are expensive, hard to program, and may not be suitable for all application computation offloads. We address these reliability and performance challenges for SSDs as follows: First, we evaluate file system reliability in the presence of SSD errors. We notice that real-world file systems often make performance assumptions for SSDs that impact their reliability. We find that real-world file systems incur severe failures, such as unmountable drives in 16% of our extensive test suite emulating 7000 SSD-based errors. Second, we invent a novel voltage-based Write Once Memory (WOM-v) coding scheme that reduces the number of erase operations that take place on every overwrite to the SSD. We show that for QLC SSD, the number of erase operations can be reduced from 4.4x to 11.1x for real-world workloads. Third, we build Nescafe, a computational storage framework to evaluate performance gains of offloading computational tasks to an emulated near storage device. We show that real-world, compute-intensive applications like zlib compression, jbd2 checksum computation, and LSM Tree compaction are easy to offload to a computational device using our framework. We show that Nescafe is generic and simple to extend to different types of block, stream, and application-based workloads.
Integrative Genomics of Human Cerebellar Development and Group 3/4 Medulloblastoma
Keywords: CBFA2T2
CBFA2T3
Group 3
Group 4
Medulloblastoma
Pediatric

Medulloblastoma (MB) comprises a group of heterogeneous pediatric neuronal neoplasms of the hindbrain with strong links to early development of the hindbrain. While Sonic Hedgehog MB arises in the upper rhombic lip (RL) granule cell lineage due to mutations that activate Shh signaling, and WNT MB arises in the lower RL due to mutations activating WNT signaling, little is known about the more common Group 4 (G4) MB, thought to arise in the unipolar brush cell (UBC) lineage. We demonstrate that somatic mutations in G4 MB converge on the Core Binding Factor Alpha (CBFA) complex, observing mutually exclusive alterations affecting CBFA2T2, CBFA2T3, PRDM6, KDM6A, and OTX2. CBFA2T2 is expressed early in the progenitor cells of the Homo sapiens cerebellar RL subventricular zone (RLSVZ), and G4 MB transcriptionally resemble these RLSVZ progenitors but are stalled in developmental time. Knockdown of OTX2 in model systems relieves this differentiation blockade, allowing MB cells to spontaneously proceed along normal developmental differentiation trajectories. The unique nature of the split human RL, destined to generate the majority of the neurons in the human brain, with its high level of susceptible EOMES+ KI67+ UBC progenitor cells, likely predisposes our species to the development of G4 MB.