# Physical Sciences and Mathematics Commons™

Articles 1 - 30 of 1895

## Full-Text Articles in Physical Sciences and Mathematics

Geometric Representation Learning, Luke Vilnis Apr 2021

#### Geometric Representation Learning, Luke Vilnis

##### Doctoral Dissertations

Vector embedding models are a cornerstone of modern machine learning methods for knowledge representation and reasoning. These methods aim to turn semantic questions into geometric questions by learning representations of concepts and other domain objects in a lower-dimensional vector space. In that spirit, this work advocates for density- and region-based representation learning. Embedding domain elements as geometric objects beyond a single point enables us to naturally represent breadth and polysemy, make asymmetric comparisons, answer complex queries, and provides a strong inductive bias when labeled data is scarce. We present a model for word representation using Gaussian densities, enabling asymmetric entailment ...

Video Adaptation For High-Quality Content Delivery, Kevin Spiteri Apr 2021

#### Video Adaptation For High-Quality Content Delivery, Kevin Spiteri

##### Doctoral Dissertations

Modern video players employ complex algorithms to adapt the bitrate of the video that is shown to the user. Bitrate adaptation requires a tradeoff between reducing the probability that the video freezes (rebuffers) and enhancing the quality of the video. A bitrate that is too high leads to frequent rebuffering, while a bitrate that is too low leads to poor video quality. In this dissertation we propose video-adaptation algorithms to deliver content and maximize the viewer's quality of experience (QoE).

Video providers partition videos into short segments and encode each segment at multiple bitrates. The video player adaptively chooses ...

Phenomenology Of Fermion Production During Axion Inflation, Michael Roberts Apr 2021

#### Phenomenology Of Fermion Production During Axion Inflation, Michael Roberts

##### Doctoral Dissertations

We study the production of fermions through a derivative coupling to an axion inflaton and the effects of the produced fermions on the scalar and tensor metric perturbations. We show how such a coupling can arise naturally from supergravity with an axion-like field driving large-field inflation and small instanton-like corrections. We present analytic results for the scalar and tensor power spectra, and estimate the amplitude of the non-Gaussianties in the equilateral regime. The scalar spectrum is found to have a red-tilted spectral index, small non-Gaussianities, and can be dominant over the vacuum contribution. In contrast, the tensor power spectrum from ...

Apr 2021

#### Concentration Inequalities In The Wild: Case Studies In Blockchain & Reinforcement Learning, A. Pinar Ozisik

##### Doctoral Dissertations

Concentration inequalities (CIs) are a powerful tool that provide probability bounds on how a random variable deviates from its expectation. In this dissertation, first I describe a blockchain protocol that I have developed, called Graphene, which uses CIs to provide probabilistic guarantees on performance. Second, I analyze the extent to which CIs are robust when the assumptions they require are violated, using Reinforcement Learning (RL) as the domain.

Graphene is a method for interactive set reconciliation among peers in blockchains and related distributed systems. Through the novel combination of a Bloom filter and an Invertible Bloom Lookup Table, Graphene uses ...

Electrospinning Fibers Via Complex Coacervation, Xiangxi Meng Apr 2021

#### Electrospinning Fibers Via Complex Coacervation, Xiangxi Meng

##### Doctoral Dissertations

Electrospun fibers are high-surface-area materials widely used in applications ranging from batteries to wound dressings. Typically, an electrospinning precursor solution is prepared by dissolving a high-molecular-weight polymer in an organic solvent to form a sufficiently entangled solution. Our approach bypasses the requirement for entanglements and completely avoids toxic chemicals by focusing on using an aqueous complex coacervates solution. Coacervates are a dense, polymer-rich liquid phase resulting from the associative electrostatic complexation of oppositely charged macroions.

We were the first to demonstrate that liquid complex coacervates could be successfully electrospun into polyelectrolyte complex (PEC) fibers. A canonical coacervate system was formed ...

#### A Search For New Resonances Decaying Into A Weak Vector Boson And A Higgs Boson In Hadronic Final States With The Atlas Detector At The Large Hadron Collider, Zachary Alden Meadows

##### Doctoral Dissertations

A search for heavy resonances decaying to a $W$ or $Z$ boson and a Higgs boson in the final state is described. The search uses $139\ \mathrm{fb}^{-1}$ of proton-proton collision data at $\sqrt{s} = 13$ TeV collected by the ATLAS detector at the CERN Large Hadron Collider from 2015 to 2018. The results are presented in terms of constraints on a simplified model with a heavy vector triplet. Upper limits are set on the production cross-section times branching fraction for resonances decaying into a W/Z boson and a Higgs boson in the mass range between 1.2 ...

#### Seismic Characteristics Of The Eastern North American Crust And Upper Mantle: The Formation And Evolution Of Continental Lithosphere, Cong Li

##### Doctoral Dissertations

The impact of past tectonic events on formation and modification of continental lithosphere over the course of Earth’s history remains as an open question of fundamental importance. Physical properties of continental crust and mantle lithosphere, such as their age, thickness, composition, temperature, and velocity, contain crucial information for informing this question. Eastern North America provides at least two complete records of supercontinent assembly and breakup over the past 1.3 Ga, serving as a natural laboratory for our understanding of continental lithosphere evolution and for integrating geologic and geophysical observations. In this thesis, I have investigated the seismic properties ...

Compact Representations Of Uncertainty In Clustering, Craig Stuart Greenberg Apr 2021

#### Compact Representations Of Uncertainty In Clustering, Craig Stuart Greenberg

##### Doctoral Dissertations

Flat clustering and hierarchical clustering are two fundamental tasks, often used to discover meaningful structures in data, such as subtypes of cancer, phylogenetic relationships, taxonomies of concepts, and cascades of particle decays in particle physics. When multiple clusterings of the data are possible, it is useful to represent uncertainty in clustering through various probabilistic quantities, such as the distribution over partitions or tree structures, and the marginal probabilities of subpartitions or subtrees.

Many compact representations exist for structured prediction problems, enabling the efficient computation of probability distributions, e.g., a trellis structure and corresponding Forward-Backward algorithm for Markov models that ...

Utilizing Graph Structure For Machine Learning, Stefan Dernbach Apr 2021

#### Utilizing Graph Structure For Machine Learning, Stefan Dernbach

##### Doctoral Dissertations

The information age has led to an explosion in the size and availability of data. This data often exhibits graph-structure that is either explicitly defined, as in the web of a social network, or is implicitly defined and can be determined by measuring similarity between objects. Utilizing this graph-structure allows for the design of machine learning algorithms that reflect not only the attributes of individual objects but their relationships to every other object in the domain as well. This thesis investigates three machine learning problems and proposes novel methods that leverage the graph-structure inherent in the tasks. Quantum walk neural ...

Apr 2021

#### Neural Methods For Answer Passage Retrieval Over Sparse Collections, Daniel Cohen

##### Doctoral Dissertations

Recent advances in machine learning have allowed information retrieval (IR) techniques to advance beyond the stage of handcrafting domain specific features. Specifically, deep neural models incorporate varying levels of features to learn whether a document answers the information need of a query. However, these neural models rely on a large number of parameters to successfully learn a relation between a query and a relevant document.

This reliance on a large number of parameters, combined with the current methods of optimization relying on small updates necessitates numerous samples to allow the neural model to converge on an effective relevance function. This ...

Apr 2021

#### Sociolinguistically Driven Approaches For Just Natural Language Processing, Su Lin Blodgett

##### Doctoral Dissertations

Natural language processing (NLP) systems are now ubiquitous. Yet the benefits of these language technologies do not accrue evenly to all users, and indeed they can be harmful; NLP systems reproduce stereotypes, prevent speakers of non-standard language varieties from participating fully in public discourse, and re-inscribe historical patterns of linguistic stigmatization and discrimination. How harms arise in NLP systems, and who is harmed by them, can only be understood at the intersection of work on NLP, fairness and justice in machine learning, and the relationships between language and social justice. In this thesis, we propose to address two questions at ...

Photothermal And Photochemical Strategies For Lightinduced Shape-Morphing Of Soft Materials, Alexa Simone Kuenstler Dec 2020

#### Photothermal And Photochemical Strategies For Lightinduced Shape-Morphing Of Soft Materials, Alexa Simone Kuenstler

##### Doctoral Dissertations

Engineering materials with the capability to transform energy from photons into mechanical work is an outstanding technical challenge with implications across myriad disciplines. Despite decades of work in this area, comprehensive understanding of how to prescribe shape change and work output in photoactive systems remains limited. To this end, this dissertation explores strategies to assemble photothermal and photochemical moieties in soft material systems to fabricate photoaddressable devices capable of specific shape changes upon illumination. Chapters 2 and 3 describe a methodology for spatially patterning plasmonic nanoparticles in liquid crystal elastomer fibers and sheets to specify local photothermally-induced strain profiles. Using ...

Dec 2020

#### Reasoning About User Feedback Under Identity Uncertainty In Knowledge Base Construction, Ariel Kobren

##### Doctoral Dissertations

Intelligent, automated systems that are intertwined with everyday life---such as Google Search and virtual assistants like Amazon’s Alexa or Apple’s Siri---are often powered in part by knowledge bases (KBs), i.e., structured data repositories of entities, their attributes, and the relationships among them. Despite a wealth of research focused on automated KB construction methods, KBs are inevitably imperfect, with errors stemming from various points in the construction pipeline. Making matters more challenging, new data is created daily and must be integrated with existing KBs so that they remain up-to-date. As the primary consumers of KBs, human users have ...

Dec 2020

#### Understanding The Dynamic Visual World: From Motion To Semantics, Huaizu Jiang

##### Doctoral Dissertations

We live in a dynamic world, which is continuously in motion. Perceiving and interpreting the dynamic surroundings is an essential capability for an intelligent agent. Human beings have the remarkable capability to learn from limited data, with partial or little annotation, in sharp contrast to computational perception models that rely on large-scale, manually labeled data. Reliance on strongly supervised models with manually labeled data inherently prohibits us from modeling the dynamic visual world, as manual annotations are tedious, expensive, and not scalable, especially if we would like to solve multiple scene understanding tasks at the same time. Even worse, in ...

#### Composite Network Of Actin And Microtubule Filaments, Self-Organization And Steady-State Dynamics, Leila Farhadi

##### Doctoral Dissertations

Actin and microtubule filaments, with their auxiliary proteins, enable the cytoskeleton to perform vital processes in the cell by tuning the organizational, mechanical properties and dynamics of the network. Despite their critical importance and interactions in cells, we are only beginning to uncover information about the composite network. Here, I use florescence microscopy to explore the role of filaments characteristics, interactions and activities in the self-organization and steady-state dynamics of the composite network of filaments. First, I discuss active self-organization of semiflexible actin and rigid microtubule filaments in the 2D composite network while myosin II and kinesin-1 motor proteins propel ...

Dec 2020

#### Distortion-Controlled Isotropic Swelling And Self-Assembly Of Triply-Periodic Minimal Surfaces, Carlos M. Duque

##### Doctoral Dissertations

In the first part of this thesis, I propose a method that allows us to construct optimal swelling patterns that are compatible with experimental constraints. This is done using a greedy algorithm that systematically increases the perimeter of the target surface with the help of minimum length cuts. This reduces the areal distortion that comes from the changing Gaussian curvature of the sheet. The results of our greedy cutting algorithm are tested on surfaces of constant and varying Gaussian curvature, and are additionally validated with finite thickness simulations using a modified Seung-Nelson model.

In the second part of the thesis ...

#### Searching For New Physics At Colliders And From Precision Measurements, Yong Du

##### Doctoral Dissertations

Beyond the great triumph of the Standard Model of particle physics, several fundamental questions remain unknown with the framework of the Standard Model. Among them are the non-zero neutrino masses, the dark matter and the baryon asymmetry of the Universe. Answers to these questions require new physics beyond the Standard Model and searching for the new physics beyond the SM has been a major task for modern particle physicists. The signal of this new physics can be searched through colliders, low- and high-energy precision measurements, as well as precision cosmological observation. Here I present my work in searching for the ...

Experimental Study Of Viscoelastic Fluid-Structure Interactions, Anita Anup Dey Dec 2020

#### Experimental Study Of Viscoelastic Fluid-Structure Interactions, Anita Anup Dey

##### Doctoral Dissertations

It is well known that when a flexible or flexibly-mounted structure is placed perpendicular to a Newtonian fluid flow, it can oscillate due to the shedding of vortices at high Reynolds numbers. Unlike Newtonian fluids, viscoelastic fluid flow can become unstable even at infinitesimal Reynolds numbers due to a purely elastic flow instability occurring at large Weissenberg numbers. This thesis focuses on exploring the mechanisms of viscoelastic fluid-structure interactions (VFSI) through experimental investigations on several different combinations of flexible and flexibly-mounted circular cylinders, micro and macro-scale cantilevered beams and viscoelastic fluids such as wormlike micelle solutions and polymer solutions.

VFSI ...

Dec 2020

#### Engineered Proteins As Tools To Understand Ubiquitin Signaling, Lin Hui Chang

##### Doctoral Dissertations

Ubiquitin is a 76 amino acids protein that is evolutionary conserved in eukaryotes. It is an important signaling molecule in a plethora biological events, such as protein degradation, DNA damage response, and transcription. This thesis aims to develop engineered protein as a tool to study ubiquitin signaling. Through targeted mutagenesis and directed evolution, a deubiquitinase is reprogrammed into a transamidase, which lead to the generation of ubiquitinprotein conjugates with discrete ubiquitin linkages through auto-ubiquitination. These ubiquitin-protein conjugates could be used as a model substrate to profile their interaction of different ubiquitin interacting proteins. In addition, using directed evolution and deep ...

Filaments, Fibers, And Foliations In Frustrated Soft Materials, Daria Atkinson Dec 2020

#### Filaments, Fibers, And Foliations In Frustrated Soft Materials, Daria Atkinson

##### Doctoral Dissertations

Assemblies of one-dimensional filaments appear in a wide range of physical systems: from biopolymer bundles, columnar liquid crystals, and superconductor vortex arrays; to familiar macroscopic materials, like ropes, cables, and textiles. Interactions between the constituent filaments in such systems are most sensitive to the distance of closest approach between the central curves which approximate their configuration, subjecting these distinct assemblies to common geometric constraints. Dual to strong dependence of inter-filament interactions on changes in the distance of closest approach is their relative insensitivity to reptations, translations along the filament backbone. In this dissertation, after briefly reviewing the mechanics and geometry ...

Dec 2020

#### Investigating The Accumulation, Sub-Organ Distribution, And Biochemical Effects Of Nanomaterials Using Mass Spectrometry, Kristen Nicole Sikora

##### Doctoral Dissertations

Gold nanoparticles (AuNPs) are attractive materials for use in various biomedical applications, such as therapeutic delivery, due to their unique chemical properties and modular tunability. Mass spectrometry methods, including laser desorption/ionization mass spectrometry (LDI-MS) and inductively coupled plasma mass spectrometry (ICP-MS) have been successfully used to evaluate the distribution of AuNPs in complex biological systems. As new AuNP-based materials are developed for applications in therapeutic delivery, it is essential to simultaneously develop analytical techniques that can comprehensively assess their behavior in vivo. In this dissertation, novel mass spectrometric methods have been developed and utilized to evaluate the uptake, distribution ...

Dec 2020

#### Algorithms For Massive, Expensive, Or Otherwise Inconvenient Graphs, David Tench

##### Doctoral Dissertations

A long-standing assumption common in algorithm design is that any part of the input is accessible at any time for unit cost. However, as we work with increasingly large data sets, or as we build smaller devices, we must revisit this assumption. In this thesis, I present some of my work on graph algorithms designed for circumstances where traditional assumptions about inputs do not apply.
1. Classical graph algorithms require direct access to the input graph and this is not feasible when the graph is too large to fit in memory. For computation on massive graphs we consider the dynamic ...

Dec 2020

#### System Design For Digital Experimentation And Explanation Generation, Emma Tosch

##### Doctoral Dissertations

Experimentation increasingly drives everyday decisions in modern life, as it is considered by some to be the gold standard for determining cause and effect within any system. Digital experiments have expanded the scope and frequency of experiments, which can range in complexity from classic A/B tests to contextual bandits experiments, which share features with reinforcement learning.

Although there exists a large body of prior work on estimating treatment effects using experiments, this prior work did not anticipate the new challenges and opportu- nities introduced by digital experimentation. Novel errors and threats to validity arise at the intersection of software ...

Dec 2020

#### Analysis Of Titanium Dioxide Nanoparticles In Foods Using Raman Spectroscopic Techniques, Janamkumar Pandya

##### Doctoral Dissertations

Titanium dioxide (TiO2) and its nanoparticles (NPs) are widely used in various applications. Recently, the presence of TiO2 NPs in food and consumer products raised safety concerns to human health and the environment. The goal of this project is to explore the capability of Raman Spectroscopy in the analysis of TiO2-NPs and apply this technique for the analysis of TiO2-NPs in food and environmental samples. Two approaches, i.e. the ligand-based and the mapping-based, were evaluated. The ligand-based approach utilized the surface enhanced Raman scattering (SERS) property of the TiO2 NPs as a substrate to enhance the signal of a ...

Dec 2020

#### Implications And Significance Of Partial Melting On The Tectonic History Of The Eastern Adirondack Mountains, Claire Rose Pless

##### Doctoral Dissertations

The eastern Adirondack Mountains contain abundant exposures of high-grade metamorphic rocks. These exposures are interpreted to be a window into the mid/deep crust of an ancient, large, hot, long-duration orogen, allowing the Adirondack Mountains to be used as an analogue to the deep processes of modern orogens. Currently interpreted thermo-tectonic events in the eastern Adirondack Mountains include the ca. 1245-1220 Ma Elzevirian orogeny, the ca. 1190-1150 Ma Shawinigan orogeny, emplacement of the ca. 1150 Ma AMCG igneous suite, the ca. 1090-1050 Ma Ottawan orogeny, and a ca. 1050-1020 Ma extensional collapse phase. This dissertation focuses on six migmatite domains ...

#### Controlled Membrane Remodeling By Nanospheres And Nanorods: Experiments Targeting The Design Principles For Membrane-Based Materials, Sarah Zuraw-Weston

##### Doctoral Dissertations

In this thesis we explore two experimental systems probing the interactions of nanoparticles with lipid bilayer membranes. Inspired by the ability of cell membranes to alter their shape in response to bound particles, we report two experimental studies: one of nanospheres the other of long, slender nano-rods binding to lipid bilayer vesicles and altering the membrane shape. Our work illuminates the role of particle geometry, particle concentration, adhesion strength and membrane tension in how membrane morphology is determined. We combine giant unilamellar vesicles with oppositely charged nanoparticles, carefully tuning adhesion strength, membrane tension and particle concentration.

In the case of ...

#### Transitions Between Radial And Bipolar Liquid Crystal Drops In The Presence Of Novel Surfactants, Jake Shechter

##### Doctoral Dissertations

Liquid crystals (LCs) are a class of molecules that form a variety of configurations easily influenced by external interactions. Of particular interest are rod-like LC molecules confined to a spherical geometry, which have a competition between interfacial tension and elastic deformations. The configuration of the liquid crystal inside a droplet can be controlled using surfactants, influencing the boundary conditions, in an oil-in-water emulsion. I tested the effects of novel surfactants on the configuration of the LC droplets. These novel surfactant molecules, synthesized by collaborators, are oligomers with either a variable length hydrophobic domain or protein sensitive hydrophilic domain. I tested ...

#### Interacting Effects Of Climate And Biotic Factors On Mesocarnivore Distribution And Snowshoe Hare Demography Along The Boreal-Temperate Ecotone, Alexej P. Siren

##### Doctoral Dissertations

The motivation of my dissertation research was to understand the influence of climate and biotic factors on range limits with a focus on winter-adapted species, including the Canada lynx (Lynx canadensis), American marten (Martes americana), and snowshoe hare (Lepus americanus). I investigated range dynamics along the boreal-temperate ecotone of the northeastern US. Through an integrative literature review, I developed a theoretical framework building from existing thinking on range limits and ecological theory. I used this theory for my second chapter to evaluate direct and indirect causes of carnivore range limits in the northeastern US, using data collected from 6 years ...

#### Nano- And Micro-Structured Temperature-Sensitive Hydrogels For Rapidly Responsive Devices, Qi Lu

##### Doctoral Dissertations

This thesis aims to extend the understanding and explore the application of temperature-responsive hydrogel systems by integrating microelectromechanical systems (MEMS). Stimuli-responsive hydrogel systems are immensely investigated and applied in numerous fields, and interfacing with micro- and nano-fabrication techniques will open up more possibilities.

In Chapter 2, the first biologically relevant, in vitro cell stretching device based on hydrogel surface instability was developed. This dynamic platform is constructed by embedding micro-heater devices under temperature-responsive surface-attached hydrogels. The fast and regional temperature change actuates the stretching and relaxation of the seeded human artery smooth muscle cell (HASMC) via controllable surface creasing instability ...

Latent Class Models For At-Risk Populations, Shuaimin Kang Jul 2020

#### Latent Class Models For At-Risk Populations, Shuaimin Kang

##### Doctoral Dissertations

Clustering Network Tree Data From Respondent-Driven Sampling With Application to Opioid Users in New York City

There is great interest in finding meaningful subgroups of attributed network data. There are many available methods for clustering complete network. Unfortunately, much network data is collected through sampling, and therefore incomplete. Respondent-driven sampling (RDS) is a widely used method for sampling hard-to-reach human populations based on tracing links in the underlying unobserved social network. The resulting data therefore have tree structure representing a sub-sample of the network, along with many nodal attributes. In this paper, we introduce an approach to adjust mixture models ...