VictorJuiz/thesis huggingface dataset:
Bilateral Pulmonary Artery Banding ± Ductal Stenting (Hybrid Palliation) for Infants with Critical Left Heart Obstruction: A Multi-Institutional Outcomes Analysis

Bilateral pulmonary artery banding ± ductal stenting (hybrid palliation) is an established initial management option for infants with critical left heart obstruction. We determined patient/procedural characteristics, subsequent outcomes, and associated factors for 214 infants who underwent hybrid palliation from 2005-2019 across 24 institutions. Parametric multivariable hazard modeling with competing risk methodology was performed to determine risk and factors associated with the various endpoints. At 5 years, 9% had biventricular repair, 36% had Fontan, 12% had transplantation, 35% died, and 8% were alive without an endpoint. High-risk patient characteristics and anatomic factors relevant to critical left heart obstruction were associated with mortality and/or achieved surgical pathway. Procedural and interstage mortality are high after initial hybrid palliation. Nonetheless, hybrid palliation may be used as a strategy both to facilitate biventricular repair for some infants, and for others, as stabilization for intended functional univentricular palliation or primary transplantation.

Keywords: congenital heart disease
Fontan
hypoplastic left heart syndrome
pulmonary artery banding
Advisor: McCrindle, Brian W
Barron, David J
Extended Proximal Primal-Dual Online Feedback Controller

This thesis studies the convergence rate of the primal-dual method for convex equality-constrained optimization problems. Three different approaches are used to determine the convergence rate, and the rates guaranteed are compared. Further, an online feedback-based optimization controller for a non-linear plant is developed. The control algorithm uses an extension of the primal-dual algorithm, the extended proximal primal-dual algorithm, to drive the system toward a critical point of a cost function. The cost function is able to consider differentiable and non-differentiable costs on the inputs and outputs of the system. Finally, the algorithm is applied to a simulated distribution feeder system. The controller is able to successfully optimize the power inputs while satisfying the physical constraints of the system.

Keywords: extended lagrangian
Online Feedback Controller
Optimization
Primal-dual
Advisor: Simpson-Porco, John W
Increasing the Speed of Colloidal Quantum Dot Based Photodetectors

Solution-processed colloidal quantum dots (CQDs) are promising materials for photodetectors operating in the short-wavelength infrared (SWIR) region. I herein explore routes to improve the temporal response in CQD photodetectors through modifications to the hole transport layer (HTL) and active layer (AL), aided by simulations and implemented experimentally. Herein, I find that these HTL materials exhibit low carrier mobility, limiting the photodiode response speed. We develop instead inverted (p-i-n) SWIR photodetectors operating at 1370 nm, employing NiOx as the HTL, ultimately enabling 4x shorter fall times in photodiodes (~800 ns for EDT and ~200 ns for NiOx). Optoelectronic simulations reveal that the high carrier mobility of NiOx enhances the electric field in the active layer, decreasing the overall transport time and increasing photodetector response time. This work broadens the understanding of CQD based photodetector speed and provides recommendations for a path to meet the industrial demand of fast IR sensing.

Keywords: Material Science
Photodetectors
Quantum Dots
Speed
Advisor: Sargent, Edward
Using Height-age as a Child linear Growth Outcome Measure in Randomized Controlled Trials in Low- and Middle-income Countries

Small-quantity lipid-based nutrient supplements (SQ-LNS) are a promising intervention to improve child growth in low- and middle-income countries, yet the effect of SQ-LNS on growth has been considered modest when randomized controlled trial (RCT) results were expressed using length-for-age z-scores (LAZ). We investigated height-age (HA) as an alternative to LAZ to assess the extent which SQ-LNS achieves children’s optimal linear growth potential using the novel ‘proportion of maximal benefit’ (PMB) metric. Published results from 15 RCTs of SQ- LNS were re-expressed using HA and the PMB, and pooled using an inverse variance fixed effect model. On average, SQ-LNS increased mean HA by 12 days, corresponding to a 0.15 increase in mean LAZ. Use of HA conveyed new information that SQ-LNS achieves, on average, 11% of children’s optimal growth potential (95% CI: 9.0, 12; n=19946). Future studies are needed to determine the broader acceptability and interpretability of HA-based methods to assess RCTs.

Advisor: Roth, Daniel
Emerging Adults' Experience of Caring for Parents with Advanced Disease

Emerging adults (EAs; 18-29 years) are increasingly assuming caregiving roles. Caring for a parent during this critical developmental stage may be a disruptive and non-normative experience. Despite the growing prevalence of EA caregivers and their distinct challenges, there remains limited research. This study explored the experiences of EAs caring for parents living with advanced disease. Interviews with 12 participants were analyzed using constructivist grounded theory. The core category was identified as negotiating accelerated adulthood, which emerged as a dynamic interplay between the dominant experience of feeling more of an adult than before and feeling confined, and not where I should be. The model included participants assuming their caregiving role. Availability of support also influenced the process of negotiating accelerated adulthood. Findings highlight the uniqueness and developmental impact of this experience. Results also suggest an interplay of different factors with how the role is assumed, appraised, and experienced by EAs.

Keywords: advanced disease
caregiving
emerging adulthood
qualitative research
Advisor: Goldstein, Abby L
Knowledge of Molar Incisor Hypomineralization among Physicians and Dentists

Objectives: To assess the knowledge of physicians and dentists on Molar Incisor Hypomineralization (MIH) and its association with antibiotic exposure during early childhood. Methods: A cross-sectional survey design was utilized. The study was electronically advertised through professional organizations with a hyperlink provided to the questionnaire. Chi-square test was used to compare differences in levels of knowledge between the study groups. Results: There were 335 participants in the study; general physicians (n=79), pediatricians (n=98) and dentists (n=158). A significantly lower proportion of general physicians (19%) and pediatricians (18%) had knowledge of molar incisor hypomineralization compared to dentists (82%, P<0.001). There was no statistically significant difference between the groups regarding the association between antibiotics prescribed during the first years of life and MIH development (P=0.07). Conclusions: Physicians lacked knowledge about the MIH dental condition. Most study respondents did not know the potential association between MIH and frequent antibiotic intake during early childhood.

Keywords: Antibiotics
Dentists
Early childhood
Knowledge
Molar incisor hypomineralization
Physicians
Advisor: Kulkarni, Gajanan
Towards a Human-Centered Approach to Data Science in Healthcare: An Exploration of Methods

Data science has become pervasive in healthcare, where it has both the potential to improve health outcomes and the risk of leaving some people on the sidelines. In this thesis, we adopt human-centered data science as a theoretical lens to explore how context and granularity in data can be leveraged in healthcare research. Through three exploratory studies, we demonstrate how categorization methods can add a nuanced layer to results and interpretations, thereby advancing our understanding of complex healthcare issues. Specifically, we use demographic segmentation, persona development and unsupervised clustering to nuance pre-existing assumptions, with the objective of supporting personalization of care. This thesis contributes to human-centered data science methodology and its application in healthcare, presenting significant opportunities for future work.

Keywords: Healthcare
Human-centered data science
Machine learning
Advisor: Guha, Shion
Characterizing Long COVID Patients for Enhanced Clinical Pathways: An Application of Clustering and Topic Modeling to Electronic Health Records

Managing long COVID presents significant challenges due to the diverse range and varying severity of symptoms experienced by patients, as well as the absence of well-defined subtypes. This thesis proposes a data-driven approach to characterize long COVID patients by utilizing cluster analysis, topic modeling, and thematic analysis on structured data and patient narratives extracted from electronic health records (EHRs). This study identifies nine distinct clusters of long COVID patients, providing more granularity towards the phenotypes and emphasizing the need for a multidisciplinary team approach in their treatment. The analysis of patient narratives offers a unique perspective on the impact of long COVID on quality of life and the difficulties patients face in navigating the healthcare system, which is invaluable in developing targeted intervention strategies. Overall, this study holds important clinical implications as it offers healthcare professionals a promising pathway to enhance care delivery and improve outcomes for long COVID patients.

Keywords: Clustering analysis
COVID-19
Long COVID
Machine learning
Topic modeling
Advisor: Guha, Shion
Preschool Diet and Child Health Outcomes: The CHILD Cohort Study

Obesity and asthma are on the rise and have origins in childhood, with overlapping risk factors. Asthma is one of the most common childhood diseases and one of the leading causes of pediatric hospitalization. Obesity and asthma can lead to increased risk for long-term health issues and resulting burden of cost to the healthcare system in Canada. These outcomes may be minimized by understanding important modifiable risk factors, such as diet in early life. This thesis aims to understand the association between dietary patterns and obesity and asthma in preschool-aged children, and the impact of sex on these outcomes, drawing data from the Canadian CHILD Cohort Study. The results of this thesis may spark further research directions, which may improve dietary recommendations for preschool aged children and improve long term health and disease prevention.

Advisor: Subbarao, Padmaja
Towards Human-Centered Models in Healthcare: Development of Practical Applications for Surgical Wards

Data science solutions in healthcare are becoming increasingly prevalent, with clinicians becoming more aware of their potential across several departments in hospital facilities. Often, streamlining technical solutions is prioritized over the specific needs of stakeholders, leaving patients at a disadvantage and further vulnerable to potential bias. This work investigates past data science implementations in the healthcare field and employs a human-centered motivation towards the development of decision-making models across a healthcare facility’s surgical wards. The need for contextual information is emphasized, with strategies for human-centered models in healthcare explored, using these projects as case studies. This thesis outlines the process of implementing a human-centered design through model development, comparing results of these models to those previously seen in the literature. Important factors to consider are reviewed alongside the specific models that allow these factors to be implemented.

Keywords: healthcare
human-centered data science
surgical wards
Advisor: Guha, Shion
Light Control of β-lapachone Activity Using Photoremovable Protecting Groups

β-lapachone is an ortho-naphthoquinone natural product with significant antiproliferative activity but suffers from adverse systemic toxicity. With such in mind, photoremovable protecting groups (“photocages”) can serve as an attractive prodrug approach to limit toxicity by covalently inactivating a substrate, then, upon light activation, release the substrate with high spatial and temporal resolution. However, visible light activatable photocages are nearly exclusively linked to nucleophilic functional sites of substrates such as alcohols, amines, thiols, and phosphates. Extension to instead mask electrophilic moieties such as the quinone group is an immense challenge in the development and use of photocages. This thesis describes the design strategy to inactivate β-lapachone with a photocage that under light activation, recovers β-lapachone and its bioactivity evaluated in vitro and in cellulo. The design employed encompasses investigations into the first report of a visible light-induced Csp3-Csp3 photocage cleavage, expanding the chemical toolbox of photocages.

Advisor: Beharry, Andrew
The Role of the Estrous Cycle on Human CYP2D6-mediated Harmine Response in CYP2D6-transgenic Mice

CYP2D is a drug metabolising enzyme found in the brain and the liver, whose activity in brain is influenced by both genetics and environment. Our aim was to investigate whether drug metabolism by CYP2D6 in brain could be altered by the estrous cycle. Using a previously established method, CYP2D6-transgenic and wild type female mice were given an intracerebroventricular injection of an inhibitor. After 24 hours, there may be irreversible inhibition of human CYP2D6 in transgenic brain, but not liver, and no irreversible inhibition of mouse CYP2D in either brain or liver. Harmine-induced hypothermia was increased in transgenic females in estrus but not diestrus, suggesting more CYP2D6 in brain in estrus. There was no effect of this inhibitor pre-treatment on harmine response in wild type females, or on peripheral drug concentrations. These data provide support that the menstrual cycle may impact CYP2D6 in human brain sufficiently to change drug response.

Keywords: brain
CYP2D6
drug metabolism
transgenic mice
Advisor: Tyndale, Rachel F
Peptide Aerogel Composites for the Capture and Electrochemical Reduction of CO2

Global warming and rapid climate change caused by excessive CO2 released due to fossil fuel combustion is of serious concern. Removal and re-utilization of these high CO2 amounts remains a key challenge in today’s world. Electrochemical reduction of CO2 is an efficient method to mitigate rising CO2 levels by capturing and converting CO2 to value added chemicals. Nobel metals are known to play a crucial role as catalysts for CO2 reduction. Here we report a myristic acid-Phe-Phe (MA-FF) peptide aerogel with graphene oxide (Gox) and Ag to capture and reduce CO2 to CO. These co-gels have been optimized by modulating Gox/Ag ratio for optimal CO2RR. The MA-FF + Ag aerogel exhibits a faradaic efficiency of 46% at a high overpotential of -0.8 V vs RHE. Incorporation of Gox in the aerogel enhances this faradaic efficiency to 88% in MA-FF + Gox+ Ag (2:1) aerogels at a low overpotential of -0.7 V vs RHE. Using peptide aerogels with Gox in addition to metal active center provides an enhanced and new method for CO2 capture and conversion using low environmental impact bio-based aerogels.

Keywords: Aerogels
Capture
CO2
Electrocatalyst
Reduction
Advisor: Kraatz, Heinz-Bernhard
Development of a General Strategy to Access Bisubstrate Inhibitors of Acetyltransferase Enzymes In Vivo

The growing antibiotic resistance crisis makes the development of new antibiotic drugs crucial. Bisubstrate enzymes are key components of many biosynthetic pathways. Covalently linking the two substrates can generate a potent inhibitor, but they are incapable of crossing cell membranes. This project set out to develop a strategy to generate bisubstrate inhibitors for acetyltransferases in vivo. The enzyme targeted was M. tuberculosis GlmU which uses GlcN-1P and AcCoA to make the key metabolite UDP-GlcNAc. The goal of this project was to assess whether GlmU could catalyze the formation of its own potent bisubstrate inhibitor from a GlcNAc-1-phosphate electrophile and CoA. GlcN bearing acryloyl and chloroacetamide functional groups were synthesized and assessed in vitro with GlmU. Unfortunately, no evidence of bisubstrate formation catalyzed by GlmU was obtained for either substrate. The synthesis of a third substrate based on a thioester was explored and further work is necessary to complete this synthesis.

Advisor: Nitz, Mark
Ontogenetic Shifts in Sex Ratios and the Evolution of Temperature-dependent Sex Determination

Temperature-dependent sex determination (TSD) exists in all major reptile clades, occurring when incubation temperature determines sex. Theory suggests TSD evolves when incubation temperature differentially influences male versus female fitness. However, TSD’s evolution remains unknown, with difficulty in assessing temperature-by-sex fitness interactions and reconciling confounding TSD types, phylogeny, and life history effects. Based on classical theory, I suggest that since incubation temperature affects condition, TSD evolved so males are produced in high-quality environments. I therefore expect that females suffer greater mortality than males and predict female-biased sex ratios at hatching as compensation, so populations reach even Fisherian sex ratios by adulthood. I test these predictions by examining ontogenetic shifts in sex ratios using a novel dataset in phylogenetically-controlled Bayesian models. I show multiple mechanisms are involved in TSD evolution, with crocodilians and testudines matching my predictions and short-lived reptiles exhibiting the opposite pattern – providing unparalleled insights into the evolution of TSD.

Keywords: life history
reptiles
sex determining mechanisms
sex ratio
sexual selection
temperature-dependent sex determination
Advisor: Rollinson, Njal
On-device 3D Foot Reconstruction for Digital Sizing

3D surface reconstruction for the extraction of anthropometric data is a proven methodology that often relies on depth sensing cameras and has produced results of high accuracy. We develop a similar reconstruction pipeline that allows the extraction of foot measurements using a portable smartphone device. Our solution uses a single monocular camera and relies on augmented reality depth sensing available on smartphone devices to scan and reconstruct a foot. We use a machine learning model for filtering our data that is lightweight enough to be run on a mobile device and has an accuracy of 81.4%. The final proposed solution runs on a Google Pixel 3 device. It has a scanning time of 10 seconds and a reconstruction time of 15 seconds. The methods employed have shown that it is possible to get foot length and width dimensions with an error as small as 0.2 cm.

Keywords: 3D scanning
Computer Vision
Mobile
Advisor: Kundur, Deepa
Harnessing the Power of the Evanescent Wave in Optical Fibers for Photocatalytic Remediation

Photocatalytic optical fibers can act both as light carriers for energy transfer and as substrates for catalyst immobilization, showcasing their potential to create solar-powered, energy-efficient and low-cost systems for contaminated water treatment. However, despite a half-century of promising research, more efficient photon transfer and utilization remains a necessary precursor prior to the upscaling of this technology. To this end, this research investigates a quantum mechanism termed frustrated total internal reflection (FTIR) which addresses these issues by means of harnessing the evanescent wave. A novel FTIR-promoting fiber achieved a 35% and a 67% increase in degradation capability and quantum efficiency, respectively, as compared to the baseline. These improvements were attributed to reduced recombination of electron-hole pairs and more uniform distribution of light intensity along the fiber. This work outlines a simple method with wide applicability to various waveguide photocatalytic systems, presenting a mechanism that may bring this technology closer to industrialization.

Keywords: Evanescent Wave
Frustrated Total Internal Reflection
Optical Fiber
Photocatalysis
Photonics
Titanium Dioxide
Advisor: Gu, Frank
Detecting Groups of Co-occurring Single Nucleotide Polymorphisms in Preeclampsia using Networks

Preeclampsia is a pregnancy disorder contributing to maternal and neonatal health complications. Current research aims to develop preventative treatments and risk prediction models. Both aims could benefit from understanding the genetics of preeclampsia. However, for polygenic disorders like preeclampsia, individual single nucleotide polymorphisms (SNPs) have small effects and are difficult to detect. In this thesis, I have developed a method for identifying groups of SNPs that co-occur in disease and applied the method to preeclampsia. First, I conducted simulations with artificial genomes (SNPs) mimicking polygenic disease to develop and test the proposed method. Secondly, I applied the method to real genetic data from a preeclampsia cohort. I used pathway analysis to assess SNPs highlighted by the co-occurrence method. These results indicated angiogenesis, endoplasmic reticular stress, and the immune system have roles in preeclampsia, as anticipated. This provides evidence that known pathophysiological mechanisms of preeclampsia have genetic underpinnings.

Keywords: Genetics
Hypertension
Interactions
Networks
Pathway enrichment
Preeclampsia
Advisor: Cox, Brian J
Skeleton-based Human Activity and Orientation Recognition with Feature and Template Matching

In this thesis, we propose a multi-person pose and orientation recognition method. We first extract the human body skeleton by using Regional Multi-person Pose Estimation (RMPE) algorithm and then apply a pose tracking algorithm (Pose Flow). For dynamic poses, we exploit velocity parameters that are obtained from the flow vector between consecutive frames. For stationary poses, we propose two different approaches: POse Estimation with Matching (POEM) and POse Estimation with Templates (POET).We evaluate our methods by conducting experiments using custom dataset and using the Le2i Fall Detection dataset, then compare the proposed method with other techniques in the literature. Then, we test the orientation estimation performance of the proposed method by using UCF-ARG Dataset. We also extend our classes with bending and raising hand to test the flexibility of POET. In the last part, we compare our method with recent papers by using the KTH dataset.

Keywords: human activity recognition
machine learning
orientation estimation
skeleton-based
Advisor: Shahrokh, Valaee prof
Organic Polar Crystals and Heteroadamantanes: Synthesis and Characterization

This thesis describes the synthesis and characterization of heteroadamantane structures, specifically halogenated and metalated derivatives of 1,3,5-triazaadamantane, wherein the halogen or metal bonds at the 7-position. This work demonstrates that 7-chloro-1,3,5-triazaadamantane and 7-bromo-1,3,5-triazaadamantane represent a new class of organic, polar crystals based on a diamondoid-type structural motif. These compounds were shown to produce isostructural crystals, which were analyzed and compared for the attributes typical of compounds within the polar space group R3m. This work also explored the utility of the halo-triazaadamantane molecules by investigating metal substitutions of the halogen. This began with computational data to determine if the materials have potential applications as semi-conductors. This was followed by the synthesis of these metalated derivatives with the objective of crystallizing them as 3-dimensional extended structures. Synthesis of 7-lithio-1,3,5-triazaadamantane was successfully achieved. This thesis explores several new classes of diamondoid materials, with significant potential for future smart material applications.

Keywords: Non-linear optics
Noncentrosymmetric
Piezoelectricity
Polar Crystals
Second harmonic generation
Advisor: Fekl, Ulrich W