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Title: Three Essays on the Internet Economy
Creator: Sun, Yidan
Date: 2024
Description: In an era of digital platforms, the integrity and visibility of consumer reviews, the dynamics of digital advertising markets, and the role of...
Show moreIn an era of digital platforms, the integrity and visibility of consumer reviews, the dynamics of digital advertising markets, and the role of software development kits (SDKs) emerge as pivotal elements shaping user experiences and platform economics. My research spans three distinct but interconnected domains: the impact of safety reviews on Airbnb, the effects of privacy protections on digital advertising markets, and the significance of SDK releases in the evolution of Apple's iOS app market. We find that critical reviews concerning the safety of an Airbnb listing's vicinity influence guest bookings negatively and, therefore, could boost platform revenues if such reviews were obscured, highlighting a misalignment between consumer interests and platform revenue objectives. This effect is more pronounced in low-income and minority neighborhoods, suggesting a nuanced impact on different community segments. In the digital advertising sector, we identify that data frictions disproportionately harm small publishers, especially when associated with smaller ad intermediaries, underscoring the vulnerability of niche players to market and regulatory changes. Lastly, our analysis of the iOS app market reveals the instrumental role of SDK releases in fostering the app ecosystem's growth, independent of the expanding iPhone user base. Together, these findings underscore the complex interplay between consumer feedback, technological advancements, and market dynamics in digital environments, urging a balanced approach that safeguards consumer interests while fostering innovation and equitable market practices.
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Title: Integrating Deep Learning And Innovative Feature Selection For Improved Short-Term Price Prediction In Futures Markets
Creator: Tian, Tian
Date: 2024
Description: This study presents a novel approach for predicting short-term price movements in futures markets using advanced deep-learning models, namely...
Show moreThis study presents a novel approach for predicting short-term price movements in futures markets using advanced deep-learning models, namely LSTM, CNN_LSTM, and GRU_LSTM. By incorporating cophenetic correlation in feature preparation, the study addresses the challenges posed by sudden fluctuations and price spikes while maintaining diversification and utilizing a limited number of variables derived from daily public data. However, the effectiveness of adding features relies on appropriate feature selection, even when employing powerful deep-learning models. To overcome this limitation, an innovative feature selection method is proposed, which combines cophenetic correlation-based hierarchical linkage clustering with the XGBoost importance listing function. This method efficiently identifies and integrates the most relevant features, significantly improving price prediction accuracy. The empirical findings contribute valuable insights into price prediction accuracy and the potential integration of algorithmic and intuitive approaches in futures markets. Moreover, the developed feature preparation method enhances the performance of all deep learning models, including LSTM, CNN_LSTM, and GRU_LSTM. This study contributes to the advancement of price prediction techniques by demonstrating the potential of integrating deep learning models with innovative feature selection methods. Traders and investors can leverage this approach to enhance their decision-making processes and optimize trading strategies in dynamic and complex futures markets.
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Title: The Voderettes: Gender, Labor, and Techno-Utopia at the 1939 New York World's Fair
Creator: Simon, Sara M. B.
Date: 2024
Description: This thesis explores the labor demands of the Voder, the electrical speech synthesis machine developed by Bell Labs to be a major component of...
Show moreThis thesis explores the labor demands of the Voder, the electrical speech synthesis machine developed by Bell Labs to be a major component of AT&T's 1939 New York World's Fair exhibit. With the United States emerging from the Great Depression, and with political tensions escalating across the globe, the paper situates the Voder's labor demands within the historical context of the fair. Specifically, I explore the decision to have young women operate the Voder, the intricacies of the machine cloaked by the warm presence of its highly-skilled female operator. Using archival records from Bell Labs engineers, the paper exposes the previously unacknowledged engineering contributions of Voder operators in the years before the fair. These young women not only influenced major decisions about the Voder's mechanics but also gave early credence to the notion that developing a performance with the machine could make for a thrilling fair exhibit. Moreover, the paper argues that at the fair itself, AT&T and Bell Labs executives used the Voder operators to normalize a new vision of a technological utopia that relied heavily and conspicuously on the infrastructural labor of women. Given the Voder's legacy, as a tool that laid critical groundwork for voice encryption technology, the paper adds important context to the historical record, highlighting the young women at the heart of the machine.
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Title: Design and Synthesis of New Sulfur Cathodes Containing Polysulfide Adsorbing Materials
Creator: Suzanowicz, Artur M
Date: 2023
Description: Lithium-sulfur battery (LSB) technology has tremendous prospects to substitute lithium-ion battery (LIB) technology due to its high...
Show moreLithium-sulfur battery (LSB) technology has tremendous prospects to substitute lithium-ion battery (LIB) technology due to its high theoretical specific capacity and energy density. However, escaping polysulfide intermediates (produced during the redox reaction process) from the cathode structure is the primary reason for rapid capacity fading. Suppressing the polysulfide shuttle (PSS) is a viable solution for this technology to move closer to commercialization and supersede the established LIB technology. In this dissertation, I have analyzed the challenges faced by LSBs and selected methods and materials to address these problems. I have concluded that in order to further pioneer LSBs, it is necessary to address these essential features of the sulfur cathode: superior electrical conductivity to ensure faster redox reaction kinetics and high discharge capacity, high pore volume of the cathode host to maximize sulfur loading/utilization, and polar polysulfide-resistive materials to anchor and suppress the migration of lithium polysulfides.Furthermore, a versatile, low-cost, and practical scalable synthesis method is essential for translating bench-level development to large-scale production. This dissertation covers designing and synthesizing new scalable cathode structures for lithium-sulfur batteries that are inexpensive and highly functional. The rationally chosen cathode components accommodate sulfur, suppress the migration of polysulfide intermediates via chemical interactions, enhance redox kinetics, and provide electrical conductivity to sulfur, rendering excellent electrochemical performance in terms of high initial specific capacity and good long-term cycling performance. TiO2, Ni12P5, and g-C3N4 as polysulfide adsorbing materials (PAMs) have been fully studied in this thesis along with three distinct types of host structures for lithium-sulfur batteries: Polymer, Carbon Cloth, and Reduced Graphene Oxide. I have created adaptable bulk synthesis techniques that are inexpensive, easily scalable, and suitable for bench-level research as well as large-scale manufacturing. The exceptional performance and scalability of these materials make my cathodes attractive options for the commercialization of lithium-sulfur batteries.
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Title: In situ EXAFS studies of novel Palladium-based anode catalysts for direct ethanol and formic acid fuel cells
Creator: Su, Ning
Date: 2024
Description: In this work we made nanoscale uniform deposition of Pd based anode catalyst on the transition metal Au (with atomic ratio Pd:Au=1:10) support...
Show moreIn this work we made nanoscale uniform deposition of Pd based anode catalyst on the transition metal Au (with atomic ratio Pd:Au=1:10) support of direct liquid ethanol fuel cells (DLEFCs) and direct liquid formic acid fuel cells (DLFAFCs). Synthesizing with uniform dispersion and catalyst nanoparticle dimensions understand the role of Pd reaction on its support in the direct EOR (ethanol oxidation reaction) and FOR (formic acid reaction) pathways, we performed in situ Pd K-edge X-ray absorption spectroscopy measurements as a function of potential using a custom-designed flow cell with the catalyst deposited on the glassy carbon window. We did in-situ EXAFS to better understand the reaction mechanism of Pd1@Au10 anode catalyst with EOR and AOR in nanoscale. Compared EOR with FOR electrochemical performance showed Pd@Au&C played better in ethanol than HCOOH and more stable which the the current density can reach up to 1216.25 mA·mg-1 Pd of EOR with Pd1@Au10&C in 1M KOH+1M EtOH (CH3CH2OH) on the ethanol fuel cells (DLEFCs), and 3.56 times higher of the EOR current compared with commercial Pd@C
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Title: Agency and Pathway Thinking as Mediators of The Relationship Between Caregiver Burden And Life Satisfaction Among Family Caregivers Of People With Parkinson’s Disease: An Application Of Snyder’s Hope Theory
Creator: Springer, Jessica Gabrielle
Date: 2024
Description: In the United States, there are 47.9 million caregivers providing care to family members with disabilities. Those providing care to someone...
Show moreIn the United States, there are 47.9 million caregivers providing care to family members with disabilities. Those providing care to someone who has Parkinson’s Disease (PD), a complex degenerative movement disorder, may have a unique caregiving experience, given that disease-related factors (e.g. motor and non-motor symptoms) can contribute to worsening caregiver burden and life satisfactions (LS). PD has an increasing incidence of 90,000 new cases per year, likely resulting in an increased need for caregivers. Caregiving research frequently focuses on the mediators between caregiver burden and LS including social support, coping skills, and appraisals. Research that has specifically focused on caregivers of people with PD (Pw/PD) is significantly limited. Hope is a “positive motivational characteristic comprised of agency and pathways thinking that can help facilitate drive towards one’s goal while also serving as a buffer against negative events” (Snyder et al.,1991). The goal of this study is to understand Snyder’s hope theory as it relates to caregiver burden and LS for caregivers of Pw/PD. Specifically, we hypothesized that (a) caregiver burden will be negatively correlated with agency thinking, pathways thinking, and LS among caregivers of Pw/PD. In addition, pathways thinking, and agency thinking will be positively associated with LS, and (b) agency thinking, and pathways thinking will mediate the relationship between caregiver burden and LS among caregivers of Pw/PD. The study sample consisted of 249 caregivers of Pw/PD who completed an online anonymous questionnaire. Correlations between agency and pathways thinking, LS, caregiver burden, and sociodemographic factors were evaluated. A parallel mediation analysis was run to evaluate the mediating roles of pathways and agency thinking in the relationship between caregiver burden and LS. Results indicated that LS was significantly and negatively correlated with caregiver burden. LS was significantly and positively correlated with both pathways and agency thinking. Pathways thinking had no indirect effect on the relationship of caregiver burden on LS. Agency thinking had a negative, indirect effect on the relationship suggesting that agency thinking partially mediated the relationship between caregiver burden and LS. Clinical implications and future directions are discussed.
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Title: Three-Dimensional Co-Culture Systems for Vascularization of Cardiac Tissue
Creator: Rodriguez Arias, Jessica A.
Date: 2023
Description: Myocardial Infarction (MI) is the partial or complete blockage of blood flow to the myocardial tissue resulting in damage and therefore loss...
Show moreMyocardial Infarction (MI) is the partial or complete blockage of blood flow to the myocardial tissue resulting in damage and therefore loss of heart function. In the U.S. every 40 seconds, someone will suffer from MI and the only available treatment is medication to treat the symptoms of heart function loss, but do not treat the underlying cause. Some attempts to treat the underlying cause have arisen in the last decades including cell-based therapies or tissue engineering therapies such as spheroid-based cardiac patches that have shown to be promising. Improvement in the mechanical properties to create suturable engineered tissues remain to be improved for ease of implantation purposes. Cell-laden hydrogel scaffolds can provide improved mechanical properties compared to biomaterial free cell-based therapies but need to allow for vascularization of the engineered tissue. Thus, the goal of this thesis is to provide preliminary studies for the use of a cell adhesive, proteolytically degradable PEG hydrogel scaffold that eventually would be used as an invitro model to evaluate engineered tissue vascularization for cardiac tissue engineering. To construct this model, important cell spheroid parameters on vascular invasion in 3D culture were investigated including the total number of cells/spheroid, the supporting cell for endothelial cells. In order to scale-up scaffolds to size of clinically relevant dimensions, a multilayered hydrogel construct visible light free-radical polymerization approach encapsulating vascular spheroids in multiple layers was also investigated. Results indicate that a total cell number of 5000 cells/spheroid aggregate were feasible due to cell sourcing. In addition, co-cultures of endothelial and mesenchymal stem cells led to maximized vascular invasion of the spheroids compared to fibroblast/endothelial co-culture and endothelial monoculture of spheroids in the hydrogel. Finally, the extent of vascularization of spheroids in each layer of the multilayered hydrogel constructs varied due to the observed differences in mechanical properties and swelling ratio of each layer due to incomplete polymerization of layers. This study demonstrated the importance of support cells and hydrogel mechanical properties in promoting vascularization of spheroid which serves as basis for building cell-laden hydrogel scaffolds for vascularization for cardiac tissues.
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Title: Financialization in the Structured Products Market
Creator: Zhu, Lizi
Date: 2023
Description: This dissertation aims to study financialization in the structured products market. The structured products market has been undergoing a major...
Show moreThis dissertation aims to study financialization in the structured products market. The structured products market has been undergoing a major transformation in recent years. The market used to mainly serve institutional investors. However, as a few trading platforms powered by fintech companies emerged on the horizon, more and more banks are starting to compete in this market. The average trade size has also been declining significantly, thereby making the market increasingly accessible to retail investors. What are the factors that facilitate the development of this market? What are the economic incentives of issuers and investors? How do issuers compete? What does the future hold for this market? The main finding of this dissertation is that structured products provide utility to retail investors; As the level of risk aversion increases, an investor increasingly prefers structured products to other traditional asset classes; issuers develop three sources of competitive advantage to be a satisficer; the rise of fintech and improvement of financial education are the key to opening this market to retail investors.
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Title: Multimodal Learning and Generation Toward a Multisensory and Creative AI System
Creator: Zhu, Ye
Date: 2023
Description: We are perceiving and communicating with the world in a multisensory manner, where different information sources are sophisticatedly processed...
Show moreWe are perceiving and communicating with the world in a multisensory manner, where different information sources are sophisticatedly processed and interpreted by separate parts of the human brain to constitute a complex, yet harmonious and unified intelligent system. To endow the machines with true intelligence, multimodal machine learning that incorporates data from various modalities including vision, audio, and text, has become an increasingly popular research area with emerging technical advances in recent years. Under the context of multimodal learning, the creativity to generate and synthesize novel and meaningful data is a critical criterion to assess machine intelligence.As a step towards a multisensory and creative AI system, we study the problem of multimodal generation in this thesis by exploring the field from multiple perspectives. Firstly, we analyze different data modalities in a comprehensive manner by comparing the data natures, the semantics, and their corresponding mainstream technical designs. We then propose to investigate three multimodal generation application scenarios, namely text generation from visual data, audio generation from visual data, and visual generation from textual data, with diverse approaches to give an overview of the field. For the direction of text generation from visual data, we study a novel multimodal task in which the model is expected to summarize a given video with textual descriptions, under a challenging condition where the video can only be partially seen. We propose to supplement the missing visual information via a dialogue interaction and introduce QA-Cooperative network with a dynamic dialogue history update learning mechanism to tackle the challenge. For the direction of audio generation from visual data, we present a new multimodal task that aims to generate music for a given silent dance video clip. Unlike most existing conditional music generation works that generate specific types of mono-instrumental sounds using symbolic audio representations (e.g., MIDI), and that heavily rely on pre-defined musical synthesizers, we generate dance music in complex styles (e.g., pop, breaking, etc.) by employing a Vector-Quantized (VQ) audio representation via our proposed Dance2Music-GAN (D2M-GAN) framework. For the direction of visual generation from textual data, we tackle a key desideratum in conditional synthesis, which is to achieve high correspondence between the conditioning input and generated output using the state-of-the-art generative model -- Diffusion Probabilistic Model. While most existing methods learn such relationships implicitly, by incorporating the prior into the variational lower bound in model training. In this work, we take a different route by explicitly enhancing input-output connections by maximizing their mutual information, which is achieved by our proposed Conditional Discrete Contrastive Diffusion (CDCD) framework. For each direction, we conduct extensive experiments on multiple multimodal datasets and demonstrate that all of our proposed frameworks are able to effectively and substantially improve task performance in their corresponding contexts.
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Title: UTILIZING BACTERIAL INTERACTIONS TO CONTROL PATHOGENIC BIOFILM FORMATION
Creator: Fang, Kuili
Date: 2020
Description: Many chronic infections involve bacterial biofilms, which are difficult to eliminate using conventional antibiotic treatments. Biofilm...
Show moreMany chronic infections involve bacterial biofilms, which are difficult to eliminate using conventional antibiotic treatments. Biofilm formation is a result of dynamic intra- or inter-species interactions. However, the nature of molecular interactions between bacteria in multi-species biofilms are not well understood compared to those in mono-species biofilms. The first project (Chapter 3) investigated the ability of probiotic Escherichia coli Nissle 1917 (EcN) to outcompete the biofilm formation of pathogens including enterohemorrhagic E. coli (EHEC), Pseudomonas aeruginosa, Staphylococcus aureus, and S. epidermidis. When dual-species biofilms were formed, EcN inhibited the EHEC biofilm population by 14-fold compared to EHEC mono-species biofilms. This figure was 1,100-fold for S. aureus and 8,300-fold for S. epidermidis; however, EcN did not inhibit P. aeruginosa biofilms. In contrast, commensal E. coli did not exhibit any inhibitory effect toward other bacterial biofilms. We identified that EcN secretes DegP, a bifunctional (protease and chaperone) periplasmic protein, outside the cells and controls other biofilms. Although three E. coli strains tested in this study expressed degP, only the EcN strain secreted DegP outside the cells. The deletion of degP disabled the activity of EcN in inhibiting EHEC biofilms, and purified DegP directly repressed EHEC biofilm formation. Hence, probiotic E. coli outcompetes pathogenic biofilms via extracellular DegP activity during dual-species biofilm formation. Enterohemorrhagic Escherichia coli O157:H7 (EHEC) is a pathogen causing the outbreaks of hemorrhagic colitis. Conventional antibiotics treatment is not recommended for EHEC infection as antibiotics trigger Shiga toxin production of EHEC and aggravate hemolytic-uremic syndrome. EHEC biofilm formation is closely associated with its virulence expression. Previously, we identified that probiotic E. coli Nissle 1917 (EcN) secretes DegP resulting in the inhibition of EHEC biofilm formation in a dual culture. DegP is a serine protease exhibiting both proteolytic and chaperone functions and binds to outer membrane proteins (OMPs) of target cells. However, the extracellular function of DegP is not clear. We hypothesized that binding of DegP to OMPs of EHEC might inhibit EHEC biofilm formation by affecting the adhesion ability or changing biofilm-related gene regulations of EHEC. We constructed EHEC mutants lacking ompA, ompC, or ompF individually and in combination and assessed their biofilm formation in the presence of DegP-secreting EcN in the co-culture or by adding purified DegP. It was found that both ompA and ompC double deletion decreased EHEC single species biofilm, and also caused that DegP inhibited more EHEC biofilm (about 25 fold inhibition) than DegP inhibited EHEC wt biofilm (about 10 fold), indicating that OmpA and OmpC are more related to EHEC biofilm than OmpF, and OmpA and OmpC might deplete DegP inhibitory functions. On the other hand, DegP S210A, a DegP mutant lacking protease function, inhibited EHEC wt biofilm, indicating that DegP’s biofilm inhibition function is not from its protease activity. Additionally, EHEC transcription profiles in the presence of DegP showed that DegP up-regulated expressions of cellulose production related genes (csgD and bcsA) and motility related genes (flhD, qseB), which were all involved in EHEC biofilm inhibition, and down-regulated Shiga toxin 2 virulence gene (stx2). Besdies, DegP promoted EHEC cellulose production and motility, which is consistent with transcription profile, and Shiga toxin 2 production will be further tested. This study reveals a new function of DegP secreted by EcN in controlling biofilms and leads us to develop an alternative strategy to control biofilm-related infections. Foodborne pathogen Listeria monocytogenes biofilm formation renders these cells highly resistant to current sanitation methods, and probiotics may be a promising approach to the efficient inhibition of Listeria biofilms. In the Chapter 5 study, three Leuconostoc mesenteroides strains of lactic acid bacteria isolated from kimchi were shown to be effective probiotics for inhibiting Listeria biofilm formation. Biofilms of two L. monocytogenes serotypes, 1/2a (ATCC15313) and 4b (ATCC19115), in dual-species culture with each probiotic strain were decreased by more than 40-fold as compared with single-species Listeria biofilms; for instance, a reduction from 5.4 times 10^6 CFU/cm2 L. monocytogenes ATCC19115 in single-species biofilms to 1.1 times 10^5 CFU/cm2 in dual-species biofilms. Most likely, one of the Leuconostoc strains, L. mesenteroides W51, led to the highest Listeria biofilm inhibition without affecting the growth of L. monocytogenes. The cell-free supernatant from the L. mesenteroides W51 culture containing large protein molecules (> 30 kDa) also inhibited Listeria biofilms. These data indicate that Leuconostoc probiotics can be used to repress L. monocytogenes biofilm contamination on surfaces at food processing facilities.
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Title: A MICROFLUIDIC INTESTINAL-MICROBIOTA PLATFORM TO STUDY DRUG METABOLISM
Creator: Wang, Chengyao
Date: 2020
Description: The intestine is the main site that orally administered drugs are primarily metabolized, absorbed, and distributed. The trillions of bacteria...
Show moreThe intestine is the main site that orally administered drugs are primarily metabolized, absorbed, and distributed. The trillions of bacteria that inhabit the intestine influence health and regulate important biochemical factors, such as the activity of enzymes pertinent to drug metabolism. However, this has not been systematically studied partly due to the challenges of recapitulating the unique and complex intestinal microenvironment that includes (1) the presence of mammalian and microbial cells and (2) a unique partitioned oxygenation proﬁle across the lumen to the subepithelial mucosa from anaerobic to the richly vascularized oxygenated. This thesis reports the development of a microfluidic device in which is integrated a membrane synthesized from a key element of mucosal basal lamina, collagen, and precisely controlled partitioned oxygen environment. The device enabled excellent cell viability and long-term function. More importantly, it enabled the coculture of intestinal epithelial cells and aerobic and anaerobic bacteria in the partitioned oxygen environment. These experiments on one hand allowed the measurement of cellular oxygen consumption rate under perfusion, which could be used to study microbial regulation of oxidative metabolism in epithelial cells. On the other hand, the device allowed a systematic examination of the role of different gut bacteria strains on the regulation of factors that are important in drug metabolism, namely, transporters and phase I enzymes. Our studies highlighted the importance of direct communication between the intestinal cells and the gut bacteria with major findings being that species-specific differences exist in the regulation of drug metabolism. This work will be useful for (1) the discovery of novel regulators of drug metabolizing enzymes, (2) developing new pharmacokinetic models, and (3) advancing precision medicine models for patients.
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Title: Population Dynamics of Listeria monocytogenes in Nut, Seed and Legume Butters
Creator: Zhang, Xinyuan
Date: 2020
Description: Nut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that...
Show moreNut, seed, and legume butters are low water activity foods and do not support the growth of foodborne pathogens. Research has determined that some pathogens, such as Listeria monocytogenes, can survive for long periods of time in butters, such as almond butter. However, information on the persistence of L. monocytogenes in butters is lacking. The purpose of this study was to determine the population dynamics of L. monocytogenes in butters stored at 5 and 25°C. Nut (almond, hazelnut, pecan), seed (pumpkin, sesame, sunflower), legume (peanut and soy) and butters containing chocolate (hazelnut and peanut) were inoculated with a 4-strain cocktail of rifampicin-resistant L. monocytogenes at 4 (high inoculation) or 1 log CFU/g (low inoculation). High inoculation butters were mixed by hand for 15 min and 100-g portions were weighed into deli-style containers with lids and stored at 5 or 25°C for 12 mo (370 d). Low inoculation butters were stored in 25- g portions in stomacher bags at 25°C for 6 mo (180 d). During storage, 25 g from the 100- g high inoculation portion or 25 g from the low inoculation samples, in triplicate, were homogenized with 225 mL BPB (or BLEB for FDA BAM enrichments when necessary) and serial dilutions of the homogenate were plated onto BHIA with rifampicin for enumeration of L. monocytogenes. Data were statistically analyzed using Student’s t-test (α=0.05). The average initial population of L. monocytogenes in the butters was 3.58±0.25 log CFU/g for the high inoculation butters; L. monocytogenes was detected through enrichments for all low inoculation butters. After 12 mo storage at 5°C, the population of L. monocytogenes decreased by 1.34, 1.27, 1.72, 2.04 and 0.93 log CFU/g in almond, hazelnut, peanut with chocolate, hazelnut with chocolate and pecan butter, respectively, when inoculated at the higher level. Significantly less population reduction was observed in pumpkin, sesame, soy, peanut and sunflower butters (1.08, 0.61, 0.84, 0.05 and 0.40 log CFU/g, respectively). After 12 mo storage at 25°C, the L. monocytogenes population in all butters, with the exception of sunflower butter, decreased to below the limit of enumeration (1.67 log CFU/g), but the pathogen was still present via enrichment. For low inoculation butters, L. monocytogenes was present as determined by enrichment in all butters in at least one of two trials after 6 mo. The results of this study provide information on the survival of L. monocytogenes in different butter types when stored at different temperatures.
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Title: Intraoperative Assessment of Surgical Margins in Head And Neck Cancer Resection Using Time-Domain Fluorescence Imaging
Creator: Cleary, Brandon M.
Date: 2023
Description: Rapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to...
Show moreRapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to over- or under-resection of cancerous tissues and follow-up treatments such as ‘call-back’ surgery and chemotherapy. Current techniques utilizing direct measurement of tumor margins in frozen section pathology are slow, which can prevent surgeons from acting on information before a patient is sent home. Other fluorescence techniques require the measurement of margins via captured images that are overlayed with fluorescent data. This method is flawed, as measuring depth from captured images loses spatial information. Intensity-based fluorescence techniques utilizing tumor-to-background ratios do not decouple the effects of concentration from the depth information acquired. Thus, it is necessary to perform an objective measurement to determine depths of surgical margins. This thesis focuses on the theory, device design, simulation development, and overall viability of time-domain fluorescence imaging as an alternative method of determining surgical margin depths. Characteristic regressions were generated using a thresholding method on acquired time-domain fluorescence signals, which were used to convert time-domain data to a depth value. These were applied to an image space to generate a depth map of a modelled tissue sample. All modeling was performed on homogeneous media using Monte Carlo simulations, providing high accuracy at the cost of increased computational time. In practice, the imaging process should be completed within a span of under 20 minutes for a full tissue sample, rather than 20 minutes for a single slice of the sample. This thesis also explores the effects of different thresholding levels on the accuracy of depth determination, as well as the precautions to be taken regarding hardware limitations and signal noise.
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Title: Investigation in the Uncertainty of Chassis Dynamometer Testing for the Energy Characterization of Conventional, Electric and Automated Vehicles
Creator: Di Russo, Miriam
Date: 2023
Description: For conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their...
Show moreFor conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their energy performance exist. However, the regulations do not include requirements on the confidence value to associate with the results. As vehicles become more and more efficient to meet the stricter regulations mandates on emissions, fuel and energy consumption, traditional testing methods may become insufficient to validate these improvements, and may need revision. Without information about the accuracy associated with the results of those procedures however, adjustments and improvements are not possible, since no frame of reference exists. For connected and automated vehicles, there are no standard testing procedures, and researchers are still in the process of determining if current evaluation methods can be extended to test intelligent technologies and which metrics best represent their performance. For these vehicles is even more important to determine the uncertainty associated with these experimental methods and how they propagate to the final results. The work presented in this dissertation focuses on the development of a systematic framework for the evaluation of the uncertainty associated with the energy performance of conventional, electric and automated vehicles. The framework is based on a known statistical method, to determine the uncertainty associated with the different stages and processes involved in the experimental testing, and to evaluate how the accuracy of each parameter involved impacts the final results. The results demonstrate that the framework can be successfully applied to existing testing methods and provides a trustworthy value of accuracy to associate with the energy performance results, and can be easily extended to connected-automated vehicle testing to evaluate how novel experimental methods impact the accuracy and the confidence of the outputs. The framework can be easily be implemented into an existing laboratory environment to incorporate the uncertainty evaluation among the current results analyzed at the end of each test, and provide a reference for researchers to evaluate the actual benefits of new algorithms and optimization methods and understand margins for improvements, and by regulators to assess which parameters to enforce to ensure compliance and ensure projected benefits.
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Title: Using Niobium surface encapsulation and Rhenium to enhance the coherence of superconducting devices
Creator: Crisa, Francesco
Date: 2024
Description: In recent decades, the scientific community has grappled with escalating complexity, necessitating a more advanced tool capable of tackling...
Show moreIn recent decades, the scientific community has grappled with escalating complexity, necessitating a more advanced tool capable of tackling increasingly intricate simulations beyond the capabilities of classical computers. This tool, known as a quantum computer, features processors composed of individual units termed qubits. While various methods exist for constructing qubits, superconducting circuits have emerged as a leading approach, owing to their parallels with semiconductor technology.In recent years, significant strides have been made in optimizing the geometry and design of qubits. However, the current bottleneck in the performance of superconducting qubits lies in the presence of defects and impurities within the materials used. Niobium, owing to its desirable properties, such as high critical temperature and low kinetic inductance, stands out as the most prevalent superconducting material. Nonetheless, it is encumbered by a relatively thick oxide layer (approximately 5 nm) exhibiting three distinct oxidation states: NbO, NbO$_2$, and Nb$_2$O$_5$. The primary challenge with niobium lies in the multitude of defects localized within the highly disordered Nb$_2$O$_5$ layer and at the interfaces between the different oxides. In this study, I present an encapsulation strategy aimed at restraining surface oxide growth by depositing a thin layer (5 to 10 nm) of another material in vacuum atop the Nb thin film. This approach exploits the superconducting proximity effect, and it was successfully employed in the development of Josephson junction devices on Nb during the 1980s.In the past two years, tantalum and titanium nitride have emerged as promising alternative materials, with breakthrough qubit publications showcasing coherence times five to ten times superior to those achieved in Nb. The focus will be on the fabrication and RF testing of Nb-based qubits with Ta and Au capping layers. With Ta capping, we have achieved the best T1 (not average) decay time of nearly 600 us, which is more than a factor of 10 improvements over the bare Nb. This establishes the unique capping layer approach as a significant new direction for the development of superconducting qubits.Concurrently with the exploration of materials for encapsulation strategies, identifying materials conducive to enhancing the performance of superconducting qubits is imperative. Ideal candidates should exhibit a thin, low-loss surface oxide and establish a clean interface with the substrate, thereby minimizing defects and potential sources of losses. Rhenium, characterized by an extremely thin surface oxide (less than 1 nm) and nearly perfect crystal structure alignment with commonly used substrates such as sapphire, emerges as a promising material platform poised to elevate the performance of superconducting qubits.
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Title: The Double-edged Sword of Executive Pay: How the CEO-TMT Pay Gap Influences Firm Performance
Creator: Haddadian Nekah, Pouya
Date: 2024
Description: This study examines the relationship between the chief executive officer (CEO) and top management team (TMT) pay gap and consequent firm...
Show moreThis study examines the relationship between the chief executive officer (CEO) and top management team (TMT) pay gap and consequent firm performance. Drawing on tournament theory and equity theory, I argue that the effect of the CEO-TMT pay gap on consequent firm performance is non-monotonic. Using data from 1995 to 2022 from S&P 1500 US firms, I explicate an inverted U-shaped relationship, such that an increase in the pay gap leads to an increase in firm performance up to a certain point, after which it declines. Additionally, multilevel analyses reveal that this curvilinear relationship is moderated by attributes of the TMT, and the industry in which the firm competes. My findings show that firms with higher TMT gender diversity suffer lower performance loss due to wider pay gaps. Furthermore, when firm executives are paid more compared to the industry norms, or when the firm has a long-tenured CEO, firm performance becomes less sensitive to larger CEO-TMT pay gaps. Lastly, when the firm competes in a masculine industry, firm performance is more negatively affected by larger CEO-TMT pay gaps. Contrary to my expectations, firm gender-diversity friendly policies failed to influence the CEO-TMT pay gap-firm performance relationship.
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Title: Improving Niobium Superconducting Radio-Frequency Cavities by Studying Tantalum
Creator: Helfrich, Halle
Date: 2023
Description: Niobium superconducting radio-frequency (SRF) cavities are widely used accelerating structures. Improvements in both quality factor, Q0, and...
Show moreNiobium superconducting radio-frequency (SRF) cavities are widely used accelerating structures. Improvements in both quality factor, Q0, and maximum accelerating gradient, Eacc, have been made to SRF cavities by introducing new processing techniques. These breakthroughs include processes such as nitrogen doping(N-Doping) and infusion, electrochemical polishing (EP) and High Pressure Rinsing (HPR). [1] There is still abundant opportunity to improve the cavities or, rather, the material they’re primarily composed of: niobium. A focus here is the role the native oxide of Nb plays in SRF cavity performance. The values of interest in a given cavity are its quality factor Q0, maximum accelerating gradient Eacc and surface resistance Rs . This work characterizes Nb and Ta foils prepared under identical conditions using X-ray photoelectron spectroscopy (XPS) to compare surface oxides and better understand RF loss mechanisms in Nb SRF cavities and qubits. It is well established that Ta qubits experience much longer coherence times than Nb qubits, which is probably due to the larger RF losses in Nb oxide. By studying Tantalum, an element similar to Niobium, the mechanisms of the losses that originate in the oxide and suboxide layers present on the surface of Nb cavities might finally be unlocked. We find noticeable differences in the oxides of Nb and Ta formed by air exposure of clean foils. In particular, Ta does not display the TaO2 suboxide in XPS, while Nb commonly shows NbO2. This suggests that suboxides are an additional contributor of RF losses. We also suggest that thin Ta film coatings of Nb SRF cavities may be a way of increasing Q0. It is in the interest of the accelerator community to fully understand the surface impurities present in Nb SRF cavities so that strategies for mitigating the effects can be proposed.
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Title: Improving Localization Safety for Landmark-Based LiDAR Localization System
Creator: Chen, Yihe
Date: 2024
Description: Autonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem...
Show moreAutonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem reliability, control algorithm stability, path planning, and localization. This thesis specifically delves into the localizer, a critical component responsible for determining the vehicle’s state (e.g., position and orientation), assessing compliance with localization safety requirements, and proposing methods for enhancing localization safety.Within the robotics domain, diverse localizers are utilized, such as scan-matching techniques like normal distribution transformations (NDT), the iterative closest point (ICP) algorithm,probabilistic maps method, and semantic map-based localization.Notably, NDT stands out as a widely adopted standalone laser localization method, prevalent in autonomous driving software such as Autoware and Apollo platforms.In addition to the mentioned localizers, common state estimators include variants of Kalman Filter, particle filter-based, and factor graph-based estimators. The evaluation of localization performance typically involves quantifying the estimated state variance for these state estimators.While various localizer options exist, this study focuses on those utilizing extended Kalman filters and factor graph methods. Unlike methods like NDT and ICP algorithms, extended Kalman filters and factor graph based approaches guarantee bounding of estimated state uncertainty and have been extensively researched for integrity monitoring.Common variance analysis, employed for sensor readings and state estimators, has limitations, primarily focusing on non-faulted scenarios under nominal conditions. This approach proves impractical for real-world scenarios and falls short for safety-critical applications like autonomous vehicles (AVs).To overcome these limitations, this thesis utilizes a dedicated safety metric: integrity risk. Integrity risk assesses the reliability of a robot’s sensory readings and localization algorithm performance under both faulted and non-faulted conditions. With a proven track record in aviation, integrity risk has recently been applied to robotics applications, particularly for evaluating the safety of lidar localization.Despite the significance of improving localization integrity risk through laser landmark manipulation, this remains an under explored territory. Existing research on robot integrity risk primarily focuses on the vehicles themselves. To comprehensively understand the integrity risk of a lidar-based localization system, as addressed in this thesis, an exploration of lidar measurement faults’ modes is essential, a topic covered in this thesis.The primary contributions of this thesis include: A realistic error estimation method for state estimators in autonomous vehicles navigating using pole-shape lidar landmark maps, along with a compensatory method; A method for quantifying the risk associated with unmapped associations in urban environments, enhancing the realism of values provided by the integrity risk estimator; a novel approach to improve the localization integrity of autonomous vehicles equipped with lidar feature extractors in urban environments through minimal environmental modifications, mitigating the impact of unmapped association faults. Simulation results and experimental results are presented and discussed to illustrate the impact of each method, providing further insights into their contributions to localization safety.
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Title: Independence and Graphical Models for Fitting Real Data
Creator: Cho, Jason Y.
Date: 2023
Description: Given some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m)...
Show moreGiven some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m) contingency table with nonzero rows or nonzero columns, we will be testing the goodness-of-fit of various independence models to the dataset using a variation of Metropolis-Hastings that uses Markov bases as a tool to get a Monte Carlo estimate of the p-value. This variation of Metropolis-Hastings can be found in Algorithm 3.1.1. Next we will consider the problem: ``out of all possible undirected graphical models each associated to some graph with m vertices that we test to fit on our dataset, which one best fits the dataset?" Here, the m attributes are labeled as vertices for the graph. We would have to conduct 2^(mC2) goodness-of-fit tests since there are 2^(mC2) possible undirected graphs on m vertices. Instead, we consider a backwards selection method likelihood-ratio test algorithm. We first start with the complete graph G = K(m), and call the corresponding undirected graphical model ℳ(G) as the parent model. Then for each edge e in E(G), we repeatedly apply the likelihood-ratio test to test the relative fit of the model ℳ(G-e), the child model, vs. ℳ(G), the parent model, where ℳ(G-e) ⊆ℳ(G). More details on this iterative process can be found in Algorithm 4.1.3. For our dataset, we will be using the alcohol dataset found in https://www.kaggle.com/datasets/sooyoungher/smoking-drinking-dataset, where the four attributes of the dataset we will use are ``Gender" (male, female), ``Age", ``Total cholesterol (mg/dL)", and ``Drinks alcohol or not?". After testing the goodness-of-fit of three independence models corresponding to the independence statements ``Gender vs Drink or not?", ``Age vs Drink or not?", and "Total cholesterol vs Drink or not?", we found that the data came from a distribution from the two independence models corresponding to``Age vs Drink or not?" and "Total cholesterol vs Drink or not?" And after applying the backwards selection likelihood-ratio method on the alcohol dataset, we found that the data came from a distribution from the undirected graphical model associated to the complete graph minus the edge {``Total cholesterol”, ``Drink or not?”}.
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Title: Development of a Model To Investigate Inflammation Using Peripheral Blood Mononucleated Cells
Creator: Geevarghese Alex, Peter
Date: 2023
Description: Our modern culture in our society is facing one of the biggest risks in health which is high-calorie diet-related postprandial inflammation....
Show moreOur modern culture in our society is facing one of the biggest risks in health which is high-calorie diet-related postprandial inflammation. Chronic diseases may be caused if the energy-dense food is the choice meaning if it is uncontrolled, clinical studies have demonstrated this with the body's post-meal inflammatory response. We aimed to find the causes of postprandial inflammation in response to various dietary treatments and provide a model to demonstrate. We aimed to make use of in vivo and in vitro techniques and statistics to create a model. The created model would help us to design specific treatments to minimize inflammation with response to dietary. In addition to figuring out vital dietary additives, the model additionally facilitates the layout of individualized interventions to reduce inflammation, thereby improving long-time period health outcomes. We aim to understand the clinical observations of diet-induced postprandial inflammation on the molecular level. We desire to make contributions to reduce the impact of chronic inflammatory disorders that is associated with postprandial inflammation.
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