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Cornell Theses and Dissertations

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The theses and dissertations of graduate students at Cornell University have been deposited in Cornell's institutional repository (eCommons) since about 2004. This collection also includes a few earlier Cornell theses.

Students retain ownership of the copyright of their work. Students also have the option of imposing a temporary embargo on access to the full text of their theses for limited amount of time (see eCommons access policy). If access to a thesis is restricted, the metadata record for the thesis is still visible, but the text "Access to Document Restricted" is displayed, and a field labeled "No Access Until," which indicates the date when the full text of the thesis will become accessible.

More information about finding Cornell theses and dissertations is available on this library guide, and the eCommons help page for finding content in specific collections, including theses and dissertations.

In general, older theses and dissertations from Cornell University are not currently available as digital files in eCommons. The Library is willing to digitize and make available older Cornell theses on a cost recovery basis. If you are interested in this service, please contact dcaps@cornell.edu.

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    CHEMICAL CONTROL OF SEMICONDUCTOR SURFACE: XPS AND STM
    Zhu, Qingyuan (2024-08)
    The chemical and physical control of semiconductor surfaces is crucial for various applications, including the performance enhancement of field-effect transistors, photocatalysts, and photocathodes. Despite significant advancements, there remains a need for in-depth research on various surface processes and characteristics of semiconductors. This thesis concentrates on the surface control of semiconductor photocatalysts and photocathodes, utilizing X-ray photoelectron spectroscopy and scanning tunneling microscopy.Investigation into the surface fluorination mechanism of rutile TiO2 (110) was performed. A mechanism akin to the Cabrera-Mott theory was proposed, where fluorination reduces surface charge density and induces an electric field. This field causes Ti cations to migrate to the surface, where they react with XeF2 and O2. Surface fluorination results in an atomically clean and non-stick surface, both before and after water rinsing. Additionally, this fluorination reaction is photo-switchable due to the photocatalyzed removal of the TiO2 surface carboxylate layer. Furthermore, the development of a method to protect photocathodes with atomically thin coatings, such as single-layer graphene and hexagonal boron nitride, was discussed. The feasibility of this method was proved by fabricating protected Mg photocathodes and detecting photoelectrons through the graphene layer. However, extending this approach to protect Cs3Sb photocathodes presented challenges, including the creation of clean substrates for photocathode growth and the nucleation of Cs3Sb on graphene and hexagonal boron nitride. These challenges require further investigation. Additionally, the surface chemistry of CsI-activated GaAs was investigated. Contrary to the conventional “yo-yo” activation method, the most stable oxide of Cs, Cs2O, was absent from the surface after annealing. Cs suboxides, such as Cs2O2 and CsO2, which possess lower work functions than Cs2O, were present in the activation layer. This hypothesis suggests a promising activation method for GaAs, potentially avoiding the formation of high work function Cs2O.
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    Optimizing Foundational System Building Blocks of Datacenter Applications
    Zhou, Zhuangzhuang (2024-08)
    Cloud computing has become the prevailing computing infrastructure for the majority of the world's computation. Computing platforms for cloud computing and large internet services are hosted in datacenters, and optimizing the performance of datacenter applications can result in significant cost savings. Given the diversity of datacenter workloads, optimizing a single application may not yield substantial improvements in the total system efficiency, as costs are spread across numerous independent workloads. In contrast, optimizing the foundational system building blocks of datacenter applications, including high-level system infrastructures to underlying system software libraries, can significantly improve the productivity of the datacenter fleet, since entire classes of datacenter applications can benefit from such optimizations. This dissertation proposes a series of optimizations in foundational system building blocks of datacenter applications. Applications running in datacenter are often built as collections of loosely coupled services that are deployed and executed through high-level system building blocks such as serverless workflow engines and microservice frameworks. First, we focus on optimizing such a system building block at the top of the computing stack, the serverless computing framework. Despite the benefits of ease of programming, fast elasticity, and fine-grained billing, serverless computing suffers from resource inefficiency. We designed Aquatope, a QoS-and-uncertainty-aware resource scheduler for end-to-end serverless workflows that takes into account the inherent uncertainty present in FaaS platforms, and improves performance predictability and resource efficiency. Aquatope uses a set of scalable and validated Bayesian models to create prewarmed containers ahead of function invocations, and to allocate appropriate resources at function granularity to meet a complex workflow’s end-to-end QoS, while minimizing resource cost. Aquatope demonstrates that a joint solution to cold start and resource management, taking into account uncertainty, can effectively improve the resource efficiency of serverless applications. However, serverless workflows still suffer from significant control plane and inter-function communication overheads, which make them unsuitable for latency-critical applications. We also designed Meteion, a fast and efficient serverless workflow engine for latency-critical interactive applications. Meteion decouples the control plane from the workflow execution, and leverages lightweight per-function engines to enable decentralized workflow orchestration and direct inter-function communication. Meteion's DAG scheduler utilizes the workflow's latency distribution and graph structure to provision containers promptly, ensuring that functions can execute seamlessly on worker servers without falling back to the control plane. Second, we delve into a foundational system library, the memory allocator. Datacenter applications typically share the usage of certain low-level software libraries, and memory allocation constitutes a substantial component of datacenter computation. Optimizing the memory allocator can improve application performance, leading to significant cost savings. We present the first comprehensive characterization of TCMalloc at warehouse scale. Our characterization reveals a profound diversity in the memory allocation patterns, allocated object sizes and lifetimes, for large-scale datacenter workloads, as well as in their performance on heterogeneous hardware platforms. Based on these insights, we optimize TCMalloc for warehouse-scale environments. Specifically, we propose optimizations for each level of its cache hierarchy that include usage-based dynamic sizing of allocator caches, leveraging hardware topology to mitigate inter-core communication overhead, and improving allocation packing algorithms based on statistical data. Evaluation results show that these optimizations significantly improve the productivity of the datacenter fleet.
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    Gerrymandering in the United States: Evolution, Measurement, and Political Consequences
    Zhu, Zhiyang (2024-08)
    This dissertation investigates the multifaceted issue of gerrymandering in the United States through three interconnected studies. The first study reviews the historical evolution of gerrymandering, assessing its origins, development, and the contemporary political and legal efforts to mitigate its impact. The second study evaluates quantitative measures like the efficiency gap and mean-median difference, highlighting significant flaws and limitations in their current implementations. The third study explores the relationship between gerrymandering and the rise of safe partisan congressional seats, attributing this phenomenon primarily to changes in political geography and voter behavior rather than gerrymandering itself. Together, these studies provide a comprehensive analysis of gerrymandering's historical context, methodological challenges, and contemporary implications, contributing to the discourse on electoral fairness and redistricting reforms.
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    Functional characterization of the human genome
    Zhang, Junke (2024-08)
    In this dissertation, I present my studies on functionally characterizing the human genome through a comprehensive evaluation of massively parallel reporter assays (MPRAs) for identifying human enhancers and prioritizing oncogenic gene fusions using a gene-based permutation test.Enhancers play crucial roles in regulating gene expression, and emerging evidence has revealed the association between genetic variants in enhancers and complex traits and diseases. This highlights the significance of identifying and characterizing enhancers for comprehending disease pathogenesis and developing new therapeutic approaches. The advances in high-throughput sequencing technologies have enabled the quantification of regulatory activities of millions of sequences simultaneously using MPRAs and self-transcribing active regulatory region sequencing (STARR-seq). Through comprehensive evaluation of MPRA/STARR-seq assays, I demonstrate factors affecting assay consistencies. By developing a uniform processing pipeline that addresses those factors, I identify more reliable enhancer regions and improve assay consistencies. The study provides valuable insights into areas for improvement in future applications of MPRA/STARR-seq to better characterize human enhancers. Gene fusions are potential products resulting from structural variants and have been recognized as an important class of somatic alterations in cancer. Previous experimental studies discovered and functionally characterized several oncogenic gene fusions, leading to the development of several drugs targeting gene fusion products. Recent advances in sequencing technologies and bioinformatics have enabled the detection of thousands of gene fusion events in cancer. I conduct a computational study to prioritize potential oncogenic fusions and provide functional characterization in the context of protein interactome networks. I identify a list of candidate driver fusions and map retained and lost protein-protein interactions through gene fusions. This serves as a valuable resource for future studies to understand how protein-interactome network rewiring by fusions can contribute to their oncogenic roles in cancer.
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    PHASE RETRIEVAL WITH 4D-STEM: LIMITS ON SENSITIVITY, RESOLUTION, AND SPEED
    Zhang, Xiyue (2024-08)
    Moore’s Law predicts that the number of transistors in an integrated circuit (IC) doubles approximately every two years, leading to a continuous reduction in the size of individual circuits. As features on ICs shrink to nanometer or even Ångstrom scales, conducting microscopic local studies poses significant challenges, demanding improved resolution of imaging methods. Scanning transmission electron microscopy (STEM) emerges as a standout solution for its unparalleled resolution in material characterization. Recent advances in segmented and pixelated detectors have driven the development of 4D-STEM. This approach captures a full diffraction pattern at each scanning position, offering a significant enhancement in phase retrieval applications such as magnetic imaging and super-resolution ptychography. This thesis explores how to optimize sensitivity, resolution, and/or speed as a function of the number of detector pixels in 4D-STEM. One application is successfully disentangling nanoscale magnetic contrast from grain contrast in a polycrystalline chiral magnetic thin film using a pixelated detector. Another outcome is a high-throughput super-resolution imaging method for 2D materials. By implementing upsampled electron ptychography with just a 4-pixel segmented detector, we achieved a 40% improvement in resolution compared to dark field and integrated differential phase contrast imaging on the same detectors. This extends the super-resolution imaging technique to segmented detectors and reveals opportunities to implement ptychography for in-situ temporal imaging with acquisition times down to the millisecond scale.
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    FROM CELLULAR AND MOLECULAR MECHANISMS TO PHYSIOLOGY: NEW INSIGHTS INTO THE ROLE OF TRANSCRIPTION FACTORS AND VASCULARIZATION IN OVULATION AND OVARIAN FOLLICLE MATURATION
    Zhang, Hanxue (2024-08)
    Ovarian follicle development involves complex cellular and molecular processes that ultimately lead to either follicle atresia or ovulation. Despite extensive research, the mechanisms underlying these processes remain incompletely understood. This dissertation investigates the roles of vascularization and transcription factors in mouse ovarian functions.The Semaphorin 3E (Sema3E)-Plexin-D1 pathway has been well-studied in other tissue for its role in regulating vascularization. However, its expression and function in the ovary remain unknow. In Chapter 2, I explored the role of this pathway in the ovary during the preovulatory stage. Sema3e and Plxnd1 are regulated by transcription factor CCAAT/enhancer-binding protein α and β (C/EBPα/β) through alterations in chromatin accessibility in ovarian granulosa cells. The Semaphorin 3E-Plexin-D1 pathway is shown to regulate granulosa cell luteinization, ovarian vascularization and inflammation, thereby influencing ovulation and subsequent corpus luteum formation. C/EBPα/β are regulated by the luteinizing hormone (LH) surge in the ovary and are indispensable for ovulation and granulosa cell luteinization. Evidence suggests that follicle-stimulating hormone (FSH) may also regulate Cebpa/b in the ovary. However, the mechanism through which FSH regulate Cebpa/b and the function of these transcription factors under FSH regulation remain unknown. In Chapter 3, I determined that FSH regulates the expression of Cebpa/b primarily through extracellular signal-regulated kinase 1/2 (ERK1/2) signaling pathway. Bulk RNA sequencing analysis reveals that C/EBPα/β downstream of FSH regulates genes involved in steroidogenesis and angiogenesis during follicle maturation. While C/EBPα/β are essential for ovulation, their direct effects on the preovulatory stages remain unclear. In Chapter 4, I compared two genetically modified mouse models in which the expression of Cebpa/b was manipulated to different levels at different times in granulosa cells during preovulatory stages. The deletion of Cebpa/b during follicle development results in blocked ovulation, whereas deletion following the LH surge leads to reduced ovulation. Bulk RNA sequencing analysis reveals that C/EBPα/β regulate gene expression via different mechanisms. These findings highlight the complex regulatory mechanisms of C/EBPα/β on its downstream targets. This work provides new insights into the cellular and molecular regulation of ovarian follicle maturation and ovulation, offering potential targets for therapeutic intervention in reproductive disorders.
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    The Evolutionary Impact of Humans on Freshwater Fishes
    Zarri, Liam (2024-08)
    While ecological and evolutionary time have historically been thought to operate at different rates, strong selection has recently been recognized to cause the convergence of these timescales through rapid evolution. Since the industrial revolution, intensive habitat alteration and heightened species mortality have induced strong selection in many wild populations and accelerated extinction rates. This biodiversity crisis is particularly critical for freshwater fishes, which constitute roughly 25% of all known vertebrates yet occupy a tiny and heavily altered slice of Earth’s surface area. However, many species show rapid recent trait change that suggests that they might be adapting to the anthropogenic pressures caused by the sixth mass extinction. Because trait heritability has historically been challenging to estimate in the wild, it is largely unknown whether widespread trait changes are plastic and thus reversible, or heritable and encoded into the genome. Therefore, I blend field ecology with high-throughput genomic sequencing to explore the potential for rapid evolution in freshwater fishes arising from habitat alteration and accelerated mortality. First, I conducted a systematic review, field study, and landscape genetic analysis to explore the evolutionary impacts of habitat alteration arising from river dams. Large dams on mainstem rivers can catalyze plastic trait change ranging from morphology and migration patterns, to chemosensory and behavior patterns. However, tributary dams may be a more severe conservation concern than mainstem dams when small non-migratory fish populations are impounded. Next, I genotyped thousands of archived and field-captured smallmouth bass (Micropterus dolomieu) to explore the evolutionary underpinnings of rapid trait change arising from heightened anthropogenic mortality. I found that a decades-long effort to eradicate bass from Adirondack lakes caused rapid evolutionary change towards early growth and maturation, contributing to an unexpected expansion of the bass population. A comparison of disturbed versus natural lakes suggests that anthropogenic removals also altered reproductive life-history strategies, spawning locations, and spawn timing in nesting bass. In conclusion, freshwater fish populations can persist in a changing environment through both plastic and heritable trait changes acting in concert.
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    Towards Expressive and Robust Learning with Hyperbolic Geometry
    Yu, Tao (2024-08)
    Machine learning models traditionally operate within the confines of Euclidean space, assuming the Euclidean nature of data. However, there is a growing interest in learning within non-Euclidean hyperbolic space, particularly in scenarios where data exhibits explicit or implicit hierarchies, such as in natural languages (with taxonomies and lexical entailment) or in tree-like and graphical data (as seen in biological and social networks). Embracing the geometry of the data not only leads to more expressive models but also offers deeper insights into the underlying mechanisms governing complex datasets. An important foundation of machine learning lies in representing data as continuous values, a process known as embedding. Recent studies have demonstrated both theoretically and empirically that hyperbolic space can embed hierarchical data with lower dimensionality compared to Euclidean space. This insight has spurred the development of various hyperbolic networks, despite the challenge that hyperbolic space is not a vector space. To address this, we propose an end-to-end approach that adopts hyperbolic geometry from a manifold perspective. This approach includes an embedding framework that directly encodes data hierarchies, a method for hyperbolic-isometries-aware learning, and a demonstration of how our framework can enhance the performance of attention models, such as transformers, by capturing implicit hierarchies. While hyperbolic geometry offers theoretical advantages, its practical implementation faces challenges due to numerical errors stemming from floating-point computations, further exacerbated by the ill-conditioned hyperbolic metrics. This issue, often referred to as the ``NaN'' problem, arises when practitioners encounter Not-a-Number while running hyperbolic models. To address this, we introduce several robust and accurate representations using integer-based tilings and multi-component floating-point methods, which offer provably bounded numerical errors for the first time. Additionally, we present MCTensor, a PyTorch library that enables general-purpose and high-precision training of machine learning models. We demonstrate the effectiveness of our approach by applying multi-component floating-point to train large language models at low precision, mitigating the issue of reduced numerical accuracy and producing models of better performances. In conclusion, our work aims to empower individuals and organizations to leverage the potential of hyperbolic geometry in machine learning, drawing a broad audience towards this promising and evolving research direction.
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    STRUCTURE-REACTIVITY PRINCIPLES OF SODIUM HEXAMETHYLDISILAZIDE AND SODIUM ALKYL(TRIMETHYLSILYL)AMIDES
    You, Qiulin (2024-08)
    The solvent-dependent reactivity of sodium hexamethyldisilazide (NaHMDS) toward carbon-centered electrophiles reveals reactions that are poorly represented or unrepresented in the literature including direct aminolysis of aromatic methyl esters to give carboxamides, nitriles, or amidines, depending on the choice of solvent. S$_N$Ar substitutions of aryl halides and terminal epoxides are also examined. A combination of $^1$H and $^{29}$Si NMR spectroscopic studies using [$^{15}$N]NaHMDS, kinetic studies, and computational studies reveal the complex mechanistic basis of the preference for simple aryl carboxamides in toluene and dimethylethylamine promote and arylnitriles or amidines in THF. A prevalence of dimer- and mixed dimer-based chemistry even from the observable NaHMDS monomer in THF solution is notable. Following extensive studies on sodium hexamethyldisilazide (NaHMDS), the solution structures and reactivity of sodium isopropyl(trimethylsilyl)amide (NaPTA), sodium (2-phenylethyl)amide (NaPETA), sodium tertbutyl(trimethylsilyl)amide (NaBTA), and their isotopomers [$^{15}$N]NaBTA have been investigated. Solution structural studies using a combination of $^{29}$Si NMR spectroscopy, the Method of Continuous Variations (MCV), and density functional theory (DFT) computations provided insights into aggregation and solvation in a range of solvents including toluene, $N,N$-dimethylethylamine, triethylamine, MTBE, THF, dimethoxyethane (DME), diglyme, $N,N,N’,N’$-tetramethylethylenediamine (TMEDA), $N,N,N’,N’$-tetramethylcyclohexanediamine (TMCDA), $N,N,N’,N’’,N’’$-pentamethyldiethylenetriamine (PMDTA), 12-crown-4, 15-crown-5, and 18-crown-6 revealed solvent- and substituent-dependent dimer-monomer mixtures with affiliated solvation numbers. Complexation of the three crown ethers documented both crown and substituent dependencies. Qualitative studies of reactivity showed a variety of reactions of NaPETA. Aminolysis of methyl benzoate with dialkylamines mediated by NaPTA afforded high yields of benzamides. Quantitative rate studies of aminolysis of methyl benzoate by NaPTA revealed a 47,000-old range of rates. Detailed rate studies in toluene and THF showed dimer-based mechanisms. The role of primary- and secondary-shell solvation by THF is discussed, including nuances of methods used to separate the two contributions. PMDTA-solvated NaPTA monomer reacts as a monomer whereas bis-diglyme solvated monomer reacts as a dimer. Rate studies exploring the structure-reactivity correlations of the three crown ethers show mono- and bis-crown-based pathways in which 15-crown-5—the crown ether often said to be of choice for sodium—was decidedly inferior as an accelerant.
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    Biomimetic, Microfluidic In Vitro Models to Recreate the Glymphatic Microenvironment and Investigate Astrocyte Involvement in Alzheimer's Disease
    Yslas, Aria (2024-08)
    The glymphatic system of brain waste clearance consists of the perivascular bulk convective fluid flow of cerebrospinal fluid (CSF) and interstitial fluid (ISF) and is responsible for fluid and solute clearance in the brain parenchyma, a portion of the human body without true lymphatic vessels. Key components of this system include aquaporin-4 (AQP4)-rich astrocyte endfeet and the basement membrane of cortical blood vessels creating a perivascular space (PVS) that allows CSF flow influx and ISF efflux. This system was only recently characterized in in vivo mouse models with later investigations with human patients via medical physics imaging modalities yet lacked a three-dimensional (3D) microfluidic in vitro model until this study. By creating a microfluidic biomimetic in vitro organ-on-chip model of the glymphatics system (glymphatics-on-chip) with primary human astrocytes and blood endothelial cells (BECs) housed a biomimetic extracellular matrix (ECM) with inducible ISF, we were able to investigate the regulation of dystrophin-associated complex (DAC) components with the presence of ISF, concluding that changes in AQP4 endfeet polarization may be ISF dependent via the DAC mechanism. Alzheimer’s disease (AD) is marked by the aggregation of extracellular amyloid-β (Aβ) and hyperphosphorylated tau (p-tau) as well as astrocyte dysfunction. For Aβ oligomers (oAβ) or aggregates to be formed, there must be Aβ monomers (mAβ) present; however, the roles of these isoforms in astrocyte pathogenesis are poorly understood. We cultured astrocytes in our 3D ECM and revealed that both isoforms caused astrocytic atrophy and hyper-reactivity but showed distinct Ca2+ changes in astrocytes. This was further explored with our glymphatics-on-chip model, which not only reproduced the astrocytic atrophy, hyper-reactivity, and Ca2+ changes induced by mAβ and oAβ, but recapitulated that the components of the DAC and AQP4 were dysregulated by mAβ and oAβ. Collectively, mAβ and oAβ cause distinct AD pathophysiological characteristics in the astrocytes. P-tau caused changes in astrocyte morphology in addition to vasoconstriction in the engineered blood vessels (BVs) and impaired glymphatic clearance, confirming findings from both in vivo models and patient samples. Altogether, our model provides a novel and innovative platform to further investigate the glymphatics system and AD with fewer animal studies.