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Doctoral Dissertations

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Full-Text Articles in Physical Sciences and Mathematics

Characterization Of Biodistribution Of Transferrin And Receptor Binding Mechanism By Mass Spectrometry, Hanwei Zhao Mar 2020

Characterization Of Biodistribution Of Transferrin And Receptor Binding Mechanism By Mass Spectrometry, Hanwei Zhao

Doctoral Dissertations

Protein-based therapeutics have emerged as a key driver of rapid growth in drug development pipelines. However, developing such protein drugs is not straightforward in most cases, the existence of physiological barriers greatly restricts the efficient delivery of many therapeutic molecules, and therefore limits their clinical applications. A promising way to address this challenge takes advantage of certain transport protein which can effectively across and enhance the permeability of these barriers, such as transferrin (Tf) which can be internalized by malignant cells and cross physiological barriers via transferrin receptor (TfR)-mediated endocytosis and transcytosis. However, developing such products is impossible without ...


Compactifications Of Cluster Varieties Associated To Root Systems, Feifei Xie Mar 2020

Compactifications Of Cluster Varieties Associated To Root Systems, Feifei Xie

Doctoral Dissertations

In this thesis we identify certain cluster varieties with the complement of a union of closures of hypertori in a toric variety. We prove the existence of a compactification $Z$ of the Fock--Goncharov $\mathcal{X}$-cluster variety for a root system $\Phi$ satisfying some conditions, and study the geometric properties of $Z$. We give a relation of the cluster variety to the toric variety for the fan of Weyl chambers and use a modular interpretation of $X(A_n)$ to give another compactification of the $\mathcal{X}$-cluster variety for the root system $A_n$.


Probabilistic Inference With Generating Functions For Population Dynamics Of Unmarked Individuals, Kevin Winner Mar 2020

Probabilistic Inference With Generating Functions For Population Dynamics Of Unmarked Individuals, Kevin Winner

Doctoral Dissertations

Modeling the interactions of different population dynamics (e.g. reproduction, migration) within a population is a challenging problem that underlies numerous ecological research questions. Powerful, interpretable models for population dynamics are key to developing intervention tactics, allocating limited conservation resources, and predicting the impact of uncertain environmental forces on a population. Fortunately, probabilistic graphical models provide a robust mechanistic framework for these kinds of problems. However, in the relatively common case where individuals in the population are unmarked (i.e. indistinguishable from one another), models of the population dynamics naturally contain a deceptively challenging statistical feature: discrete latent variables with ...


Dynamic Composition Of Functions For Modular Learning, Clemens Gb Rosenbaum Mar 2020

Dynamic Composition Of Functions For Modular Learning, Clemens Gb Rosenbaum

Doctoral Dissertations

Compositionality is useful to reduce the complexity of machine learning models and increase their generalization capabilities, because new problems can be linked to the composition of existing solutions. Recent work has shown that compositional approaches can offer substantial benefits over a wide variety of tasks, from multi-task learning over visual question-answering to natural language inference, among others. A key variant is functional compositionality, where a meta-learner composes different (trainable) functions into complex machine learning models. In this thesis, I generalize existing approaches to functional compositionality under the umbrella of the routing paradigm, where trainable arbitrary functions are 'stacked' to form ...


Search For Displaced Hadronic Vertices In The Atlas Inner Detector And Muon Spectrometer In P-P Collisions At √S = 13 Tev At The Lhc, Margaret S. Lutz Mar 2020

Search For Displaced Hadronic Vertices In The Atlas Inner Detector And Muon Spectrometer In P-P Collisions At √S = 13 Tev At The Lhc, Margaret S. Lutz

Doctoral Dissertations

A search is performed for long-lived neutral particles using 33 fb−1 of 13 TeV proton-proton collision data produced by the LHC and collected by the ATLAS detector during 2016. This search focuses on the topology in which pairs of displaced hadronic jets are produced, with one in the inner detector and the other in the muon spectrometer. Special techniques are used to reconstruct the displaced decays. One event is found passing the full signal selection, which is consistent with the back- ground estimation. Limits are set at a 95% upper confidence level on the BR × σ for a SM ...


Nanoindentation Characterization Of Elastic Properties Of Shales And Swelling Clay Minerals, Shengmin Luo Mar 2020

Nanoindentation Characterization Of Elastic Properties Of Shales And Swelling Clay Minerals, Shengmin Luo

Doctoral Dissertations

Oil and gas shales are a class of multiscale, multiphase, hybrid inorganic-organic sedimentary rocks that consist of a generally uniform, preferentially oriented clay matrix with randomly embedded silt and sand particles as solid inclusions. A thorough understanding of the mechanical properties of shales is crucial for the exploration and production of oil and gas in the unconventional shale reservoirs, but it can be a challenging task due to their nature of compositional heterogeneity and microstructural anisotropy. In efforts to better characterize the mechanical properties of shales across different length scales and to fundamentally understand the laws of upscaling from individual ...


Higher-Order Representations For Visual Recognition, Tsung-Yu Lin Mar 2020

Higher-Order Representations For Visual Recognition, Tsung-Yu Lin

Doctoral Dissertations

In this thesis, we present a simple and effective architecture called Bilinear Convolutional Neural Networks (B-CNNs). These networks represent an image as a pooled outer product of features derived from two CNNs and capture localized feature interactions in a translationally invariant manner. B-CNNs generalize classical orderless texture-based image models such as bag-of-visual-words and Fisher vector representations. However, unlike prior work, they can be trained in an end-to-end manner. In the experiments, we demonstrate that these representations generalize well to novel domains by fine-tuning and achieve excellent results on fine-grained, texture and scene recognition tasks. The visualization of fine-tuned convolutional filters ...


Learning Latent Characteristics Of Data And Models Using Item Response Theory, John P. Lalor Mar 2020

Learning Latent Characteristics Of Data And Models Using Item Response Theory, John P. Lalor

Doctoral Dissertations

A supervised machine learning model is trained with a large set of labeled training data, and evaluated on a smaller but still large set of test data. Especially with deep neural networks (DNNs), the complexity of the model requires that an extremely large data set is collected to prevent overfitting. It is often the case that these models do not take into account specific attributes of the training set examples, but instead treat each equally in the process of model training. This is due to the fact that it is difficult to model latent traits of individual examples at the ...


Improving Face Clustering In Videos, Souyoung Jin Mar 2020

Improving Face Clustering In Videos, Souyoung Jin

Doctoral Dissertations

Human faces represent not only a challenging recognition problem for computer vision, but are also an important source of information about identity, intent, and state of mind. These properties make the analysis of faces important not just as algorithmic challenges, but as a gateway to developing computer vision methods that can better follow the intent and goals of human beings. In this thesis, we are interested in face clustering in videos. Given a raw video, with no caption or annotation, we want to group all detected faces by their identity. We address three problems in the area of face clustering ...


Optimization And Training Of Generational Garbage Collectors, Nicholas Jacek Mar 2020

Optimization And Training Of Generational Garbage Collectors, Nicholas Jacek

Doctoral Dissertations

Garbage collectors are nearly ubiquitous in modern programming languages, and we want to minimize the cost they impose in terms of time and space. Generally, a collector waits until its space is full and then performs a collection to reclaim needed memory. However, this is not the only option; a collection could be performed early when some free space remains. For copying collectors, which are what we consider here, the system must traverse the graph of live objects and copy them, so the cost of a collection is proportional to the volume of objects that are live. Since this value ...


Modulating Nanoparticle-Protein Interactions Through Covalent Or Noncovalent Approach For Biomedical Applications, Jingjing Gao Mar 2020

Modulating Nanoparticle-Protein Interactions Through Covalent Or Noncovalent Approach For Biomedical Applications, Jingjing Gao

Doctoral Dissertations

Discoveries at the interface of chemistry, biology, and materials science have emerged as a powerful route to impact life science in this century. My research in the Thayumanavan group is focused on problems at this interface. A common theme of all the six projects is the use of modern synthetic organic chemistry to build interesting, novel macromolecules which are chemically rich, to study the molecular self-assembly behavior in solution and then translate to solve problems in the biomedical area. By addressing the design challenge to prepare novel amphiphiles with desired functional groups, controlled molecular weight and the ability to respond ...


An Empirical Assessment Of The Effectiveness Of Deception For Cyber Defense, Kimberly J. Ferguson-Walter Mar 2020

An Empirical Assessment Of The Effectiveness Of Deception For Cyber Defense, Kimberly J. Ferguson-Walter

Doctoral Dissertations

The threat of cyber attacks is a growing concern across the world, leading to an increasing need for sophisticated cyber defense techniques. The Tularosa Study, was designed and conducted to understand how defensive deception, both cyber and psychological, affects cyber attackers Ferguson-Walter et al. [2019c]. More specifically, for this empirical study, cyber deception refers to a decoy system and psychological deception refers to false information of the presence of defensive deception techniques on the network. Over 130 red teamers participated in a network penetration test over two days in which we controlled both the presence of and explicit mention of ...


Molecular Design Of Organic Semiconductors For Interfacial And Emissive Material Applications, Marcus David Cole Mar 2020

Molecular Design Of Organic Semiconductors For Interfacial And Emissive Material Applications, Marcus David Cole

Doctoral Dissertations

This dissertation describes the synthesis and characterization of functional optoelectronically active materials. Synthetic techniques were used to prepare polymers containing perylene diimide (PDI) or tetraphenylethylene (TPE) moieties in the polymer backbone. PDI-based structures were prepared with embedded cationic or zwitterionic moieties intended to tailor organic/inorganic interfaces in thin film photovoltaic devices. The aggregation-induced emission (AIE)-active TPE polymers were synthesized to study how AIE properties evolve in π-conjugated polymers. The syntheses discussed here focused on modulation of molecular architecture to give rise to materials with tailored optoelectronic properties.

Chapter 1 provides a brief overview of the field of organic ...


Motion Segmentation - Segmentation Of Independently Moving Objects In Video, Pia Katalin Bideau Mar 2020

Motion Segmentation - Segmentation Of Independently Moving Objects In Video, Pia Katalin Bideau

Doctoral Dissertations

The ability to recognize motion is one of the most important functions of our visual system. Motion allows us both to recognize objects and to get a better understanding of the 3D world in which we are moving. Because of its importance, motion is used to answer a wide variety of fundamental questions in computer vision such as: (1) Which objects are moving independently in the world? (2) Which objects are close and which objects are far away? (3) How is the camera moving?
My work addresses the problem of moving object segmentation in unconstrained videos. I developed a probabilistic ...


Elliptic Curves And Power Residues, Vy Thi Khanh Nguyen Nov 2019

Elliptic Curves And Power Residues, Vy Thi Khanh Nguyen

Doctoral Dissertations

Let E1 x E2 over Q be a fixed product of two elliptic curves over Q with complex multiplication. I compute the probability that the pth Fourier coefficient of E1 x E2, denoted as ap(E1) + ap(E2), is a square modulo p. The results are 1/4, 7/16, and 1/2 for different imaginary quadratic fields, given a technical independence of the twists. The similar prime densities for cubes and 4th power are 19/54, and 1/4, respectively. I also compute the probabilities without the technical assumption on ...


Petrogenesis Of Basaltic Lavas In Iceland And The Springerville Volcanic Field, U.S.A.: The Influence Of Tectonic Setting, Depth Of Melting And Volatiles, Marissa Mnich Nov 2019

Petrogenesis Of Basaltic Lavas In Iceland And The Springerville Volcanic Field, U.S.A.: The Influence Of Tectonic Setting, Depth Of Melting And Volatiles, Marissa Mnich

Doctoral Dissertations

Icelandic basalts were long thought to be low in water (e.g. Gunnarsson et al., 1998), but more recent studies suggest that hotspots, like the Iceland mantle plume, may be a source of hydrous basaltic melts (Nichols et al., 2002). To explore a possible link between location, volatile concentration and resulting petrogenetic implications, samples were collected from eleven volcanic centers throughout Iceland. Water concentrations were measured in melt inclusions and phenocrysts using Fourier transform infrared (FTIR) spectroscopy. Results for a subset of samples indicate variable water in melt inclusions ranging from approximately 50 ppm to over 3000 ppm. Samples from ...


Tools For Tutoring Theoretical Computer Science Topics, Mark Mccartin-Lim Nov 2019

Tools For Tutoring Theoretical Computer Science Topics, Mark Mccartin-Lim

Doctoral Dissertations

This thesis introduces COMPLEXITY TUTOR, a tutoring system to assist in learning abstract proof-based topics, which has been specifically targeted towards the population of computer science students studying theoretical computer science. Existing literature has shown tremendous educational benefits produced by active learning techniques, student-centered pedagogy, gamification and intelligent tutoring systems. However, previously, there had been almost no research on adapting these ideas to the domain of theoretical computer science. As a population, computer science students receive immediate feedback from compilers and debuggers, but receive no similar level of guidance for theoretical coursework. One hypothesis of this thesis is that immediate ...


Neural Models For Information Retrieval Without Labeled Data, Hamed Zamani Oct 2019

Neural Models For Information Retrieval Without Labeled Data, Hamed Zamani

Doctoral Dissertations

Recent developments of machine learning models, and in particular deep neural networks, have yielded significant improvements on several computer vision, natural language processing, and speech recognition tasks. Progress with information retrieval (IR) tasks has been slower, however, due to the lack of large-scale training data as well as neural network models specifically designed for effective information retrieval. In this dissertation, we address these two issues by introducing task-specific neural network architectures for a set of IR tasks and proposing novel unsupervised or \emph{weakly supervised} solutions for training the models. The proposed learning solutions do not require labeled training data ...


Response Retrieval In Information-Seeking Conversations, Liu Yang Oct 2019

Response Retrieval In Information-Seeking Conversations, Liu Yang

Doctoral Dissertations

The increasing popularity of mobile Internet has led to several crucial changes in the way that people use search engines compared with traditional Web search on desktops. On one hand, there is limited output bandwidth with the small screen sizes of most mobile devices. Mobile Internet users prefer direct answers on the search engine result page (SERP). On the other hand, voice-based / text-based conversational interfaces are becoming increasing popular as shown in the wide adoption of intelligent assistant services and devices such as Amazon Echo, Microsoft Cortana and Google Assistant around the world. These important changes have triggered several new ...


Extracting And Representing Entities, Types, And Relations, Patrick Verga Oct 2019

Extracting And Representing Entities, Types, And Relations, Patrick Verga

Doctoral Dissertations

Making complex decisions in areas like science, government policy, finance, and clinical treatments all require integrating and reasoning over disparate data sources. While some decisions can be made from a single source of information, others require considering multiple pieces of evidence and how they relate to one another. Knowledge graphs (KGs) provide a natural approach for addressing this type of problem: they can serve as long-term stores of abstracted knowledge organized around concepts and their relationships, and can be populated from heterogeneous sources including databases and text. KGs can facilitate higher level reasoning, influence the interpretation of new data, and ...


Residual Stress Models For Large Eddy Simulation Of Stratified Turbulent Flows, Felipe Augusto Ventura De Bragança Alves Oct 2019

Residual Stress Models For Large Eddy Simulation Of Stratified Turbulent Flows, Felipe Augusto Ventura De Bragança Alves

Doctoral Dissertations

The residual stresses and scalar fluxes are required to close the momentum and scalar transport equations in simulations of turbulence that are not fully resolved in space.

In stratified turbulence, the stress and fluxes are statistically anisotropic unless the smallest resolved length scale is smaller than the Ozmidov scale and the buoyancy Reynolds number is sufficiently high for there to exist a range of scales that is statistically isotropic.

In this work, a tensorial basis set is derived analytically that potentially contains sufficient information about the anisotropic interaction between resolved and residual scales.

The residual stress tensor is evaluated by ...


Efficient Self-Supervised Deep Sensorimotor Learning In Robotics, Takeshi Takahashi Oct 2019

Efficient Self-Supervised Deep Sensorimotor Learning In Robotics, Takeshi Takahashi

Doctoral Dissertations

Deep learning has been successful in a variety of applications, such as object recognition, video games, and machine translation. Deep neural networks can automatically learn important features given large training datasets. However, the success of deep learning in robotic systems in the real world is still limited mainly because obtaining large datasets and labeling are costly. As a result, much of the successful work in deep learning has been limited to domains where large datasets are readily available or easily collected. To address this issue, I propose a framework for acquiring re-usable skills efficiently combining intrinsic motivation and the control ...


Machine Learning Models For Efficient And Robust Natural Language Processing, Emma Strubell Oct 2019

Machine Learning Models For Efficient And Robust Natural Language Processing, Emma Strubell

Doctoral Dissertations

Natural language processing (NLP) has come of age. For example, semantic role labeling (SRL), which automatically annotates sentences with a labeled graph representing who did what to whom, has in the past ten years seen nearly 40% reduction in error, bringing it to useful accuracy. As a result, a myriad of practitioners now want to deploy NLP systems on billions of documents across many domains. However, state-of-the-art NLP systems are typically not optimized for cross-domain robustness nor computational efficiency. In this dissertation I develop machine learning methods to facilitate fast and robust inference across many common NLP tasks.

First, I ...


Protein Detection And Structural Characterization By Mass Spectrometry Using Supramolecular Assemblies And Small Molecules, Bo Zhao Oct 2019

Protein Detection And Structural Characterization By Mass Spectrometry Using Supramolecular Assemblies And Small Molecules, Bo Zhao

Doctoral Dissertations

Mass spectrometry (MS) has played an increasingly prominent role in proteomics and structure biology because it shows superior capabilities in identification, quantification and structural characterization of proteins. To realize its full potential in protein analysis, significant progress has been made in developing innovative techniques and reagents that can couple to MS detection. This dissertation demonstrates the use of polymeric supramolecular assemblies for enhanced protein detection in complex biological mixtures by MS. An amphiphilic random co-polymer scaffold is developed to form functional supramolecular assemblies for protein/ peptide enrichment. The influences of charge density and functional group pKa on host-guest interactions ...


Top-Down And Bottom-Up Fabrication Of Key Components In Miniature Energy Storage Devices, Wenhao Li Oct 2019

Top-Down And Bottom-Up Fabrication Of Key Components In Miniature Energy Storage Devices, Wenhao Li

Doctoral Dissertations

The advent of miniature electronic devices demands power sources of commensurate form factors. This spurs the research of micro energy storage devices, e.g., 3D microbatteries. A 3D microbattery contains nonplanar microelectrodes with high aspect ratio and high surface area, separated by a nanoscale electrolyte. The device takes up a total volume as small as 10 mm3, allowing it to serve on a chip and to provide power in-situ. The marriage of nanotechnology and electrochemical energy storage makes microbattery research a fascinating field with both scientific excitement and application prospect. However, successful fabrication of well-functioned key components and the ...


Characterization Of The Anomalous Ph Of Aqueous Nanoemulsions, Kieran P. Ramos Oct 2019

Characterization Of The Anomalous Ph Of Aqueous Nanoemulsions, Kieran P. Ramos

Doctoral Dissertations

Aqueous water-in-oil nanoemulsions have emerged as a versatile tool for use in microfluidics, drug delivery, single-molecule measurements, and other research. Nanoemulsions are often prepared with perfluorocarbons which are remarkably biocompatbile due to their stability, low surface tension, lipophobicity, and hydrophobicity. Therefore it is often assumed that droplet contents are unperturbed by the perfluorinated surface. However, in microemulsions, which are similar to nanoemulsions, it is known that either the pH of the aqueous phase or the ionization constants of encapsulated molecules are different from bulk solution. There is also recent evidence of low pH in perfluorinated aqueous nanoemulsions. The current underlying ...


Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee Oct 2019

Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee

Doctoral Dissertations

Internet of Things (IoT) devices are becoming an essential part of our everyday lives. These physical devices are connected to the internet and can measure or control the environment around us. Further, IoT devices are increasingly being used to monitor buildings, farms, health, and transportation. As these connected devices become more pervasive, these devices will generate vast amounts of data that can be used to gain insights and build intelligence into the system. At the same time, large-scale deployment of these devices will raise new challenges in efficiently managing and controlling them.

In this thesis, I argue that the IoT ...


Providing Molecular Insight For Understanding Anion Exchange Membrane Conductivity, Michael Kwasny Oct 2019

Providing Molecular Insight For Understanding Anion Exchange Membrane Conductivity, Michael Kwasny

Doctoral Dissertations

Anion exchange membranes (AEMs) are notorious for having both low alkaline stability and poor ion conductivity in fuel cell operation conditions, with solutions to these two challenges often being developed independent of each other. The chemical instability of an AEM is viewed through degradation of the polymer backbone and the cationic species and improving a material’s stability is approached by altering the polymer backbone, the cation, or both. On the other hand, poor ion conductivity is typically addressed by modifying bulk membrane properties such as increasing the ion exchange capacity (IEC), changing the morphology, or increasing the water uptake ...


Observational Studies Of Fragmentation In Molecular Clouds, Riwaj Pokhrel, Riwaj Pokhrel, Riwaj Pokhrel Oct 2019

Observational Studies Of Fragmentation In Molecular Clouds, Riwaj Pokhrel, Riwaj Pokhrel, Riwaj Pokhrel

Doctoral Dissertations

In this dissertation, I explore fragmentation physics in multiple scales in nearby molecular clouds and discuss some implications of fragmentation for cloud structure formation and star formation, primarily by analyzing multi-wavelength observations of dust emission. First, I tested the complete thermal and combined thermal and nonthermal support mechanisms that balance gravitational contraction at multiple scales in the Perseus molecular cloud. I found that the observed multiscale structures in Perseus are consistent with an inefficient thermal Jeans fragmentation, where the Jeans efficiency increases from the largest scale ($\gtrsim$10s of pc) to the smallest scale ($\sim$10s of AU). Next, I ...


Energy-Aware Algorithms For Greening Internet-Scale Distributed Systems Using Renewables, Vani Gupta Oct 2019

Energy-Aware Algorithms For Greening Internet-Scale Distributed Systems Using Renewables, Vani Gupta

Doctoral Dissertations

Internet-scale Distributed Systems (IDSs) are large distributed systems that are comprised of hundreds of thousands of servers located in hundreds of data centers around the world. A canonical example of an IDS is a content delivery network (CDN) that delivers content to users from a large global deployment of servers around the world. IDSs consume large amounts of energy and their energy requirements are projected to increase significantly in the future. With carbon emissions from data centers increasing every year, use of renewables to power data centers is critical for the sustainability of data centers and for the environment.

In ...