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Doctoral Dissertations

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Full-Text Articles in Physical Sciences and Mathematics

Migmatite Formation, Geochronometer Petrogeneisis, And Rare Earth Element Mineralization In The Adirondack Mountains, Ny, Kaitlyn Suarez Nov 2023

Migmatite Formation, Geochronometer Petrogeneisis, And Rare Earth Element Mineralization In The Adirondack Mountains, Ny, Kaitlyn Suarez

Doctoral Dissertations

The Adirondack Mountains in upstate New York contain exposures of complex partially melted rocks, in addition to iron oxide-apatite (IOA) deposits with variable rare earth element (REE) concentrations. Previous workers have suggested that melting occurred during the ca. 1150 Ma Shawinigan and the ca. 1050 Ma Ottawan orogenies. However, there are challenges in determining the timing of melting and the number of partial melt events. Further, tectonic models must be developed to describe the petrogenesis of IOA and REE mineralization. Migmatites are present along Rt. 4/22 near Whitehall, NY. In chapter two, all layers of a single migmatitic rock were …

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Polymer-Based Nanotherapeutics To Combat Difficult-To-Treat Bacterial Infections, Jessa Marie V. Makabenta Nov 2023

Polymer-Based Nanotherapeutics To Combat Difficult-To-Treat Bacterial Infections, Jessa Marie V. Makabenta

Doctoral Dissertations

The continuous emergence and spread of antibiotic-resistant bacteria are a global health emergency, debilitating the capability to prevent and cure various infectious diseases that were once treatable. Antibiotic therapy is further rendered ineffective due to biofilm formation and the ability of bacteria to thrive and colonize inside mammalian cells. Given the diminishing efficacy of available antibiotics combined with the scarcity of new therapeutics entering the antibiotic pipeline, innovative treatment strategies are urgently in demand. Nanomaterial-based strategies offer ‘outside of the box’ approach for the treatment of antibiotic-resistant bacterial infections. Nanomaterials feature tunable physicochemical properties that can be carefully modified to …

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Intersection Cohomology Of Rank One Local Systems For Arrangement Schubert Varieties, Shuo Lin Nov 2023

Intersection Cohomology Of Rank One Local Systems For Arrangement Schubert Varieties, Shuo Lin

Doctoral Dissertations

In this thesis we study the intersection cohomology of arrangement Schubert varieties with coefficients in a rank one local system on a hyperplane arrangement complement. We prove that the intersection cohomology can be computed recursively in terms of certain polynomials, if a local system has only $\pm 1$ monodromies. In the case where the hyperplane arrangement is generic central or equivalently the associated matroid is uniform and the local system has only $\pm 1$ monodromies, we prove that the intersection cohomology is a combinatorial invariant. In particular when the hyperplane arrangement is associated to the uniform matroid of rank $n-1$ …

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When To Hold And When To Fold: Studies On The Topology Of Origami And Linkages, Mary Elizabeth Lee Nov 2023

When To Hold And When To Fold: Studies On The Topology Of Origami And Linkages, Mary Elizabeth Lee

Doctoral Dissertations

Linkages and mechanisms are pervasive in physics and engineering as models for a
variety of structures and systems, from jamming to biomechanics. With the increase
in physical realizations of discrete shape-changing materials, such as metamaterials,
programmable materials, and self-actuating structures, an increased understanding
of mechanisms and how they can be designed is crucial. At a basic level, linkages
or mechanisms can be understood to be rigid bars connected at pivots around which
they can rotate freely. We will have a particular focus on origami-like materials, an
extension to linkages with the added constraint of faces. Self-actuated versions typ-
ically start …

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Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov Nov 2023

Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov

Doctoral Dissertations

Reactive chemistries for protein chemical modification play an instrumental role in chemical biology, proteomics, and therapeutics. Depending on the application, the selectivity of these modifications can range from precise modification of an amino acid sequence by genetic manipulation of protein expression machinery to a stochastic modification of lysine residues on the protein surface. Ligand-Directed (LD) chemistry is one of the few methods for targeted modification of endogenous proteins without genetic engineering. However, current LD strategies are limited by stringent amino acid selectivity. To bridge this gap, this thesis focuses on the development of highly reactive LD Triggerable Michael Acceptors (LD-TMAcs) …

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Towards Robust Long-Form Text Generation Systems, Kalpesh Krishna Nov 2023

Towards Robust Long-Form Text Generation Systems, Kalpesh Krishna

Doctoral Dissertations

Text generation is an important emerging AI technology that has seen significant research advances in recent years. Due to its closeness to how humans communicate, mastering text generation technology can unlock several important applications such as intelligent chat-bots, creative writing assistance, or newer applications like task-agnostic few-shot learning. Most recently, the rapid scaling of large language models (LLMs) has resulted in systems like ChatGPT, capable of generating fluent, coherent and human-like text. However, despite their remarkable capabilities, LLMs still suffer from several limitations, particularly when generating long-form text. In particular, (1) long-form generated text is filled with factual inconsistencies to …

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Human-Centered Technologies For Inclusive Collection And Analysis Of Public-Generated Data, Mahmood Jasim Nov 2023

Human-Centered Technologies For Inclusive Collection And Analysis Of Public-Generated Data, Mahmood Jasim

Doctoral Dissertations

The meteoric rise in the popularity of public engagement platforms such as social media, customer review websites, and public input solicitation efforts strives for establishing an inclusive environment for the public to share their thoughts, ideas, opinions, and experiences. Many decisions made at a personal, local, or national scale are often fueled by data generated by the public. As such, inclusive collection, analysis, sensemaking, and utilization of pubic-generated data are crucial to support the exercise of successful decision-making processes. However, people often struggle to engage, participate, and share their opinions due to inaccessibility, the rigidity of traditional public engagement methods, …

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Quantifying And Enhancing The Security Of Federated Learning, Virat Vishnu Shejwalkar Nov 2023

Quantifying And Enhancing The Security Of Federated Learning, Virat Vishnu Shejwalkar

Doctoral Dissertations

Federated learning is an emerging distributed learning paradigm that allows multiple users to collaboratively train a joint machine learning model without having to share their private data with any third party. Due to many of its attractive properties, federated learning has received significant attention from academia as well as industry and now powers major applications, e.g., Google's Gboard and Assistant, Apple's Siri, Owkin's health diagnostics, etc. However, federated learning is yet to see widespread adoption due to a number of challenges. One such challenge is its susceptibility to poisoning by malicious users who aim to manipulate the joint machine learning …

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Sources And Controls Of Carbon Dioxide In Inland Waters At Watershed, Regional, And Continental Scales, Brian Saccardi Nov 2023

Sources And Controls Of Carbon Dioxide In Inland Waters At Watershed, Regional, And Continental Scales, Brian Saccardi

Doctoral Dissertations

Inland waters are significant sources of carbon dioxide to the atmosphere, and estimates of emissions are similar in magnitude to those of the carbon dioxide sequestered by the net terrestrial sink. Currently, methods of estimating carbon dioxide emissions are based on statistical approaches and often do not consider landscape attributes such as human development, agriculture, or the hydrologic connectivity of the stream network. The following research addresses these issues in chapter 1 by developing and validating a reactive transport model at the watershed scale, then in chapter 2 by applying the reactive transport model at the continental scale across US …

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Search For Exotic Higgs Boson Decay To Multiple B-Quarks With The Atlas Detector At Lhc Using Machine Learning Methods, Yuan-Tang Chou Nov 2023

Search For Exotic Higgs Boson Decay To Multiple B-Quarks With The Atlas Detector At Lhc Using Machine Learning Methods, Yuan-Tang Chou

Doctoral Dissertations

The discovery of the Higgs boson has opened up new possibilities for investigating physics beyond the Standard Model (SM). New particles may interact with the SM through the Higgs boson, and deviations from SM predictions can indicate the presence of new physics. This dissertation focuses on the search for exotic Higgs decay, $H\rightarrow aa \rightarrow (b\bbar)(b\bbar)$ where a is a new scalar boson and focuses on the case where the Higgs boson is produced in association with a Z boson. The data were collected by the ATLAS detector at the Large Hadron Collider at center-of-mass energy $\sqrt{s} =~13~\TeV$ from 2015 …

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Learning To See With Minimal Human Supervision, Zezhou Cheng Nov 2023

Learning To See With Minimal Human Supervision, Zezhou Cheng

Doctoral Dissertations

Deep learning has significantly advanced computer vision in the past decade, paving the way for practical applications such as facial recognition and autonomous driving. However, current techniques depend heavily on human supervision, limiting their broader deployment. This dissertation tackles this problem by introducing algorithms and theories to minimize human supervision in three key areas: data, annotations, and neural network architectures, in the context of various visual understanding tasks such as object detection, image restoration, and 3D generation. First, we present self-supervised learning algorithms to handle in-the-wild images and videos that traditionally require time-consuming manual curation and labeling. We demonstrate that …

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Foundations Of Node Representation Learning, Sudhanshu Chanpuriya Nov 2023

Foundations Of Node Representation Learning, Sudhanshu Chanpuriya

Doctoral Dissertations

Low-dimensional node representations, also called node embeddings, are a cornerstone in the modeling and analysis of complex networks. In recent years, advances in deep learning have spurred development of novel neural network-inspired methods for learning node representations which have largely surpassed classical 'spectral' embeddings in performance. Yet little work asks the central questions of this thesis: Why do these novel deep methods outperform their classical predecessors, and what are their limitations? We pursue several paths to answering these questions. To further our understanding of deep embedding methods, we explore their relationship with spectral methods, which are better understood, and show …

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Thermodynamic Laws Of Billiards-Like Microscopic Heat Conduction Models, Ling-Chen Bu Nov 2023

Thermodynamic Laws Of Billiards-Like Microscopic Heat Conduction Models, Ling-Chen Bu

Doctoral Dissertations

In this thesis, we study the mathematical model of one-dimensional microscopic heat conduction of gas particles, applying both both analytical and numerical approaches. The macroscopic law of heat conduction is the renowned Fourier’s law J = −k∇T, where J is the local heat flux density, T(x, t) is the temperature gradient, and k is the thermal conductivity coefficient that characterizes the material’s ability to conduct heat. Though Fouriers’s law has been discovered since 1822, the thorough understanding of its microscopic mechanisms remains challenging [3] (2000). We assume that the microscopic model of heat conduction is a hard ball system. The …

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Positive Factorizations Via Planar Mapping Classes And Braids, Richard E. Buckman Nov 2023

Positive Factorizations Via Planar Mapping Classes And Braids, Richard E. Buckman

Doctoral Dissertations

In this thesis we seek to better understand the planar mapping class group in
order to find factorizations of boundary multitwists, primarily to generate and study
symplectic Lefschetz pencils by lifting these factorizations. Traditionally this method
is applied to a disk or sphere with marked points, utilizing factorizations in the stan-
dard and spherical braid groups, whereas in our work we allow for multiple boundary components. Dehn twists along these boundaries give rise to exceptional sections of Lefschetz fibrations over the 2–sphere, equivalently, to Lefschetz pencils with base points. These methods are able to derive an array of known examples …

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Experiments With Monopoles, Rings And Knots In Spinor Bose-Einstein Condensates, Alina A. Blinova Nov 2023

Experiments With Monopoles, Rings And Knots In Spinor Bose-Einstein Condensates, Alina A. Blinova

Doctoral Dissertations

Topological excitations are ubiquitous in nature, their charge being a naturally-quantized, conserved quantity that can exhibit particle-like behavior. Spinor Bose-Einstein condensates (BECs) are an exceptionally versatile system for the study and exploration of topological excitations. Between the spin-1 and spin-2 87Rb condensates there are seven possible broken-symmetry magnetic phases, with each one hosting unique opportunities for topological defects. We have created and observed several novel topological excitations in a spinor 87Rb BEC. In this dissertation I present and discuss three principal experimental findings: (1) The discovery of an Alice ring, or a half-quantum vortex ring, emerging from a …

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Probing The Physical Mechanisms Responsible For Brown Dwarf And Giant Planet Formation, Sarah Betti Nov 2023

Probing The Physical Mechanisms Responsible For Brown Dwarf And Giant Planet Formation, Sarah Betti

Doctoral Dissertations

The disks that form around young stellar objects provide the essential material for their continued growth as well as the formation of planets, making them ideal laboratories to investigate the mechanisms and environments key for substellar and planetary formation. In this dissertation, I explore two main formation processes: the transportation of water necessary for giant planet formation, and the accretion and growth of young brown dwarfs. First, I study the water ice content in the circumstellar disk of AB Aurigae, a young Herbig Ae star. I detect and map icy grains on the disk surface using high contrast observations taken …

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Nonparametric Derivative Estimation Using Penalized Splines: Theory And Application, Bright Antwi Boasiako Nov 2023

Nonparametric Derivative Estimation Using Penalized Splines: Theory And Application, Bright Antwi Boasiako

Doctoral Dissertations

This dissertation is in the field of Nonparametric Derivative Estimation using
Penalized Splines. It is conducted in two parts. In the first part, we study the L2
convergence rates of estimating derivatives of mean regression functions using penalized splines. In 1982, Stone provided the optimal rates of convergence for estimating derivatives of mean regression functions using nonparametric methods. Using these rates, Zhou et. al. in their 2000 paper showed that the MSE of derivative estimators based on regression splines approach zero at the optimal rate of convergence. Also, in 2019, Xiao showed that, under some general conditions, penalized spline estimators …

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Bayesian Structural Causal Inference With Probabilistic Programming, Sam A. Witty Nov 2023

Bayesian Structural Causal Inference With Probabilistic Programming, Sam A. Witty

Doctoral Dissertations

Reasoning about causal relationships is central to the human experience. This evokes a natural question in our pursuit of human-like artificial intelligence: how might we imbue intelligent systems with similar causal reasoning capabilities? Better yet, how might we imbue intelligent systems with the ability to learn cause and effect relationships from observation and experimentation? Unfortunately, reasoning about cause and effect requires more than just data: it also requires partial knowledge about data generating mechanisms. Given this need, our task then as computational scientists is to design data structures for representing partial causal knowledge, and algorithms for updating that knowledge in …

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Applying Density Functional Theory Simulations To Study The Charge Balancing And Structure Directing Roles Of Fluoride In Zeolite Synthesis, Tongkun Wang Nov 2023

Applying Density Functional Theory Simulations To Study The Charge Balancing And Structure Directing Roles Of Fluoride In Zeolite Synthesis, Tongkun Wang

Doctoral Dissertations

Zeolites represent a major cornerstone of today’s energy industry as the most-used petrochemical catalyst by weight in the world. Constituted by tetrahedra of T-atoms including Si, Al, Ge and Ti, zeolites form a huge family of nano-porous crystalline materials which also provide reliable candidates for novel, energy related applications such as efficient separations, hydrogen-purifying/storing and conversions from biomass to biofuel. However, the formation mechanism of zeolite is still not clear, as synthesis processes are complicated by requirements including structure directing agents (SDAs), hydroxide or fluoride medium, and experimental conditions like temperature. Attempts for designing new zeolite structures still fall in …

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Effective And Efficient Transfer Learning In The Era Of Large Language Models, Tu Vu Nov 2023

Effective And Efficient Transfer Learning In The Era Of Large Language Models, Tu Vu

Doctoral Dissertations

Substantial progress has been made in the field of natural language processing (NLP) due to the advent of large language models (LLMs)—deep neural networks with millions or billions of parameters pre-trained on large amounts of unlabeled data. However, these models have common weaknesses, including degenerate performance in data-scarce scenarios, and substantial computational resource requirements. This thesis aims to develop methods to address these limitations for improved applicability and performance of LLMs in resource-constrained settings with limited data and/or computational resources. To address the need for labeled data in data-scarce scenarios, I present two methods, in Chapter 2 and Chapter 3, …

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Tev-Scale Lepton Number Violation: 0Νββ Decay, The Origin Of Matter, And Energy Frontier Probes, Sebastian Urrutia Quiroga Nov 2023

Tev-Scale Lepton Number Violation: 0Νββ Decay, The Origin Of Matter, And Energy Frontier Probes, Sebastian Urrutia Quiroga

Doctoral Dissertations

Lepton number violation (LNV) offers promising theoretical pathways to several unresolved problems in particle and nuclear physics and unveils a diverse range of phenomenology across different energy scales. TeV-scale LNV is especially relevant for both its experimental accessibility and its broad-ranging impact, making it a key area of interest for both theoretical and experimental physicists. In this thesis, we explore three distinct scenarios within the LNV research landscape. Our first analysis concerns the implications of TeV-scale LNV effects in thermal leptogenesis and its complementary sensitivity in neutrinoless double beta (0νββ) decay and collider experiments. We employed a simplified model to …

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The Fate Of The Crossbridge After Phosphate Rebinding: Implications For Fatigue, Christopher P. Marang Nov 2023

The Fate Of The Crossbridge After Phosphate Rebinding: Implications For Fatigue, Christopher P. Marang

Doctoral Dissertations

In response to repeated intense contractile activity, a muscle’s ability to generate force decreases due to the created state of muscular fatigue. This compromised force production state is dependent on changes within the microenvironment of muscle thought to alter the function of the force generating, contractile protein myosin. For example, phosphate (Pi), elevated during fatigue, has been suggested to alter how myosin generates force. However, the effects of Pi are not straightforward, as muscle fiber data suggest that Pi's interaction with myosin may be force-dependent. In particular, Pi has no effect on maximal shortening …

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Semi-Infinite Flags And Zastava Spaces, Andreas Hayash Nov 2023

Semi-Infinite Flags And Zastava Spaces, Andreas Hayash

Doctoral Dissertations

ABSTRACT SEMI-INFINITE FLAGS AND ZASTAVA SPACES SEPTEMBER 2023 ANDREAS HAYASH, B.A., HAMPSHIRE COLLEGE M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Ph.D, UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ivan Mirković We give an interpretation of Dennis Gaitsgory’s semi-infinite intersection cohomol- ogy sheaf associated to a semisimple simply-connected algebraic group in terms of finite-dimensional geometry. Specifically, we construct machinery to build factoriza- tion spaces over the Ran space from factorization spaces over the configuration space, and show that under this procedure the compactified Zastava space is sent to the support of the semi-infinite intersection cohomology sheaf in the Beilinson-Drinfeld Grassmannian. We also construct …

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Atomistic Simulations Of Intrinsically Disordered Protein Folding And Dynamics, Xiping Gong Nov 2023

Atomistic Simulations Of Intrinsically Disordered Protein Folding And Dynamics, Xiping Gong

Doctoral Dissertations

Intrinsically disordered proteins (IDPs) are crucial in biology and human diseases, necessitating a comprehensive understanding of their structure, dynamics, and interactions. Atomistic simulations have emerged as a key tool for unraveling the molecular intricacies and establishing mechanistic insights into how these proteins facilitate diverse biological functions. However, achieving accurate simulations requires both an appropriate protein force field capable of describing the energy landscape of functionally relevant IDP conformations and sufficient conformational sampling to capture the free energy landscape of IDP dynamics. These factors are fundamental in comprehending potential IDP structures, dynamics, and interactions. I first conducted explicit solvent simulations to …

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Facets Of The Union-Closed Polytope, Daniel Gallagher Nov 2023

Facets Of The Union-Closed Polytope, Daniel Gallagher

Doctoral Dissertations

In the haze of the 1970s, a conjecture was born to unknown parentage...the union-closed sets conjecture. Given a family of sets $\FF$, we say that $\FF$ is union-closed if for every two sets $S, T \in \FF$, we have $S \cup T \in \FF$. The union-closed sets conjecture states that there is an element in at least half of the sets of any (non-empty) union-closed family. In 2016, Pulaj, Raymond, and Theis reinterpreted the conjecture as an optimization problem that could be formulated as an integer program. This thesis is concerned with the study of the polytope formed by taking …

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Graph Representation Learning With Box Embeddings, Dongxu Zhang Aug 2023

Graph Representation Learning With Box Embeddings, Dongxu Zhang

Doctoral Dissertations

Graphs are ubiquitous data structures, present in many machine-learning tasks, such as link prediction of products and node classification of scientific papers. As gradient descent drives the training of most modern machine learning architectures, the ability to encode graph-structured data using a differentiable representation is essential to make use of this data. Most approaches encode graph structure in Euclidean space, however, it is non-trivial to model directed edges. The naive solution is to represent each node using a separate "source" and "target" vector, however, this can decouple the representation, making it harder for the model to capture information within longer …

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Deformations Of Geometrically Frustrated Elastic Sheets, Meng Xin Aug 2023

Deformations Of Geometrically Frustrated Elastic Sheets, Meng Xin

Doctoral Dissertations

The wrinkling and buckling of thin solids are common phenomena in our daily life and can be observed in many situations, such as crumpled papers, stretched plastics, compressed metals, clothes on our bodies and even furrowed human skin. Understanding of these phenomena has therefore long drawn interest of scholars. In this thesis, we discuss two buckling problems numerically and analytically. First, we study the wrinkling mechanism of stretched sheets with clamped edges. A central puzzle underlying this canonical example of “tensional wrinkling” has been the origin of compressive stress, which eventually leads to buckling instability. We elucidate the source of …

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Analysis Of Nonequilibrium Langevin Dynamics For Steady Homogeneous Flows, Abdel Kader A. Geraldo Aug 2023

Analysis Of Nonequilibrium Langevin Dynamics For Steady Homogeneous Flows, Abdel Kader A. Geraldo

Doctoral Dissertations

First, we propose using rotating periodic boundary conditions (PBCs) [13] to simulate nonequilibrium molecular dynamics (NEMD) in uniaxial or biaxial stretching flow. These specialized PBCs are required because the simulation box deforms with the flow. The method extends previous models with one or two lattice remappings and is simpler to implement than PBCs proposed by Dobson [10] and Hunt [24]. Then, using automorphism remapping PBC techniques such as Lees-Edwards for shear flow and Kraynik-Reinelt for planar elongational flow, we demonstrate expo-nential convergence to a steady-state limit cycle of incompressible two-dimensional
NELD. To demonstrate convergence [12], we use a technique similar …

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Improving User Experience By Optimizing Cloud Services, Ishita Dasgupta Aug 2023

Improving User Experience By Optimizing Cloud Services, Ishita Dasgupta

Doctoral Dissertations

Today, cloud services offer myriads of applications, tailor made for different users in the field of weather, health, finance, entertainment, etc. These services fulfill varying genres of user demands over the Internet. For example, these services can be live (live weather radar, ESPN Live) or on-demand services (weather forecasting, Netflix). While these applications cater to different customer requirements, it is necessary for these services to be efficient with respect to latency, scalability, robustness and quality of experience. These systems need to constantly evolve to provide the best user experience and meet the most current demands of the customer. For instance, …

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An Introspective Approach For Competence-Aware Autonomy, Connor Basich Aug 2023

An Introspective Approach For Competence-Aware Autonomy, Connor Basich

Doctoral Dissertations

Building and deploying autonomous systems in the open world has long been a goal of both the artificial intelligence (AI) and robotics communities. From autonomous driving, to health care, to office assistance, these systems have the potential to transform society and alter our everyday lives. The open world, however, presents numerous challenges that question the typical assumptions made by the models and frameworks often used in contemporary AI and robotics. Systems in the open world are faced with an unconstrained and non-stationary environment with a range of heterogeneous actors that is too complex to be modeled in its entirety. Moreover, …

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