Physical Sciences and Mathematics Commons^™

Coastal Geomorphic Response To Sea-Level Rise, Storms, And Antecedent Geology: Examples From The Northern Gulf Of Mexico, Clayton Dike

Dissertations

Sea-level rise and tropical cyclone activity are threatening coastlines around the world. Past geologic coastal responses can be used to inform future scenarios. This three-part study examines the response of coastal systems to sea-level rise, storms, sediment supply, and antecedent geology over the past ~ 140 ka.

The first study is of the Bay St. Louis, Mississippi, coastal system along the northern Gulf of Mexico incorporating sediment supply, subsidence, and antecedent topography paired with an examination of geologic response to sea-level fall and rise. I used core and geophysical data that resolve incised valleys and other subsurface deposits from ~ …

Data Collection And Machine Learning Methods For Automated Pedestrian Facility Detection And Mensuration, Joseph Bailey Luttrell Iv

Dissertations

Large-scale collection of pedestrian facility (crosswalks, sidewalks, etc.) presence data is vital to the success of efforts to improve pedestrian facility management, safety analysis, and road network planning. However, this kind of data is typically not available on a large scale due to the high labor and time costs that are the result of relying on manual data collection methods. Therefore, methods for automating this process using techniques such as machine learning are currently being explored by researchers. In our work, we mainly focus on machine learning methods for the detection of crosswalks and sidewalks from both aerial and street-view …

Studying The Synthesis Of 196Hg At Astrophysically Relevant Energies Through The Measurement Of Capture Reaction Cross-Sections Of (P, Γ) (P, N) And (P, Α) Reactions, Khushi Bhatt

Dissertations

Understanding the origin of all the chemical elements is an important question for the nuclear-astrophysics community. There are many unanswered questions like: What astrophysical events are responsible for the synthesis of what particular chemical elements? How many different elements were made in total? What is the abundance of each synthesized element? etc. Currently, scientists are largely depending upon theory and simulations to define nuclear and astrophysical reaction. This makes it critical to have accurate experimental nuclear physics data to input in astrophysical theoretical models. However, out of more than 20000 reactions involved in these calculations, only a very few are …

Probing The Equation Of State Of Neutron Stars With Heavy Ion Collisions, Om Bhadra Khanal

Dissertations

The equation of state (EOS) is a fundamental property of nuclear matter, important for studying the structure of systems as diverse as the atomic nucleus and the neutron star. Nuclear reactions, especially heavy-ion collisions in the laboratories, can produce the nuclear matter similar to those contained in neutron stars. The density and the momentum dependence of the EOS of asymmetric nuclear matter, especially the symmetry energy term, is widely unconstrained. Finding appropriate constrains, especially at higher densities of the nuclear matter, requires the development of new devices, new experimental measurements as well as advances in theoretical understanding of nuclear collisions …

Evidence For An Early Saginaw Lobe Ice Retreat And Drainage Adjustments Across Southern Michigan, Usa, Nathan Erber

Dissertations

The Saginaw lobe of the Laurentide Ice Sheet (LIS), flowed out of Saginaw Bay, across Lower Michigan and into northern Indiana. As it retreated, the Saginaw lobe deposited the Sturgis moraine, a recessional moraine of the lobe in southern Michigan. Positioned to the west and east of the Saginaw lobe were the Lake Michigan and Huron-Erie lobes, respectively. These lobes retreated across the region asynchronously, with the Saginaw lobe retreating first. The asynchronous behavior of the lobes allowed for the Lake Michigan and Huron-Erie lobes to overprint and alter landscapes once occupied by the Saginaw lobe ice.

The Kalamazoo moraine, …

Designing Dynamic And Degradable Polymeric Materials With Thiol-X Chemistries, Reese Sloan

Dissertations

With plastic production poised to increase in coming years, there arises a need to develop new polymeric materials designed to combat the global pollution crisis. A commonly utilized approach in addressing this challenge is to employ a responsive functional moiety into the polymer architecture. Thiol-X reactions, a commonly utilized class of “click” reactions, have garnered broad implementation in new stimuli-responsive materials. This work specifically focuses on utilizing radical-mediated thiol-ene coupling and base-catalyzed thiol-isocyanate reactions to develop a library of ternary thiol-ene/thiourethane covalent adaptable networks (CANs) and hydrolytically labile poly(thioether ketal) thermoplastics. CANs are a class of network materials capable of …

Mechanism Of Sila- And Germafluorenes For Biological Applications, Shelby Jarrett

Dissertations

2,7-disubstituted silafluorenes and germafluorenes, originally designed for OLED applications, are a class of fluorescent dyes that have gained recent interest as probes for bioimaging and as biosensors to monitor cellular dynamics and interactions. Desirable biological probes absorb in the visible region, have high extinction coefficients, high quantum yield and excellent photostability. Here, their spectral properties are investigated under aqueous conditions for relevant biological applications. These molecules display intense blue fluorescence in the solid state and in solution, have high extinction coefficients, and exhibit appreciable solubility in aqueous solution. To better understand potential applications, the mechanism of fluorescence was investigated. It …

Mixture Of Functional Graphical Models, Qihai Liu

Dissertations

With the development of data collection technologies that use powerful monitoring devices and computational tools, many scientific fields are now obtaining more detailed and more complicatedly structured data, e.g., functional data. This leads to increasing challenges of extracting information from the large complex data. Making use of these data to gain insight into complex phenomena requires characterizing the relationships among a large number of functional variables. Functional data analysis (FDA) is a rapidly developing area of statistics for data which can be naturally viewed as a smooth curve or function. It is a method that changes the frame of data …

Mid To Late Neogene (5.9-3.7 Ma) Epeirogenic Uplift And Associated Ultramafic Volcanism, Canterbury Basin, New Zealand, Katherine Anne Dvorak

Dissertations

Cored marine sediments from Canterbury Basin Integrated Ocean Drilling Program (IODP) Expedition 317 shelf sites U1351, U1353, and upper slope Site U1352 have been resampled with emphasis on benthic foraminifera from the Late Eocene to Late Pliocene. These new data coupled with paleo water-depth and age data from the nearby Clipper-1 petroleum exploration well, are used to develop a 1-dimensional basin subsidence model for the Canterbury Basin. Our model indicates there was widespread epeirogenic uplift of 890  350m, in the mid-Neogene (5.9-3.7 million years ago), which took place during concomitant ultramafic volcanism. Close association of uplift and volcanism could …

Diagnostics Of Dementia From Structural And Functional Markers Of Brain Atrophy With Machine Learning, Tetiana Habuza

Dissertations

Dementia is a condition in which higher mental functions are disrupted. It currently affects an estimated 57 million people throughout the world. A dementia diagnosis is difficult since neither anatomical indicators nor functional testing is currently sufficiently sensitive or specific. There remains a long list of outstanding issues that must be addressed. First, multimodal diagnosis has yet to be introduced into the early stages of dementia screening. Second, there is no accurate instrument for predicting the progression of pre-dementia. Third, non-invasive testing cannot be used to provide differential diagnoses. By creating ML models of normal and accelerated brain aging, we …

Analysis Of The Zebrafish Olfactory System Using Immunohistochemistry And Enhanced Techniques Of Desorption Electrospray Ionization Mass Spectrometry (Desi-Ms), Tara Lynn Maser

Dissertations

Desorption electrospray ionization (DESI-MS) is an ambient ionization technique where the sample is analyzed directly from a surface with very minimal sample preparation under ambient conditions and follows ESI-like ionization mechanisms. DESI-MS has proven powerful in analyzing or imaging lipids and other small molecules directly from biological samples and even allows for subsequent histological staining and analyses. However, DESI-MS is less widely used for protein analysis due to a lack of sensitivity and the complex diversity of proteins in biological samples.

A major goal of this research has been to obtain new neurobiological knowledge by combining histology and mass spectrometry …

The Design, Synthesis, And Characterization Of Copper-Based Metal-Organic Frameworks For Their Investigation Against Cancer And Their Effect As Anti-Microbial Agents, Sandy Elmehrath

Dissertations

A wide range of nanomaterials have been developed for biomedical applications, such as drug delivery, biomedical imaging, and sensors. Nanomaterials can include nanoparticles (NPs) and nanofibers with various dimensions that are both natural and synthetic. A successful nanomaterial, for use in biological applications, is characterized by its biocompatibility, biodegradability, intrinsic high surfaces area, high interconnected porosity, and functionality. These features were achieved with the development of metal-organic framework (MOF) nanostructures. MOFs are assemblies of metal ions and organic linkers that are built into different geometries and can exist in all dimensions (up to 3-D). The choice of linkers with well-defined …

One-Stage Blind Source Separation Via A Sparse Autoencoder Framework, Jason Anthony Dabin

Dissertations

Blind source separation (BSS) is the process of recovering individual source transmissions from a received mixture of co-channel signals without a priori knowledge of the channel mixing matrix or transmitted source signals. The received co-channel composite signal is considered to be captured across an antenna array or sensor network and is assumed to contain sparse transmissions, as users are active and inactive aperiodically over time. An unsupervised machine learning approach using an artificial feedforward neural network sparse autoencoder with one hidden layer is formulated for blindly recovering the channel matrix and source activity of co-channel transmissions. The BSS sparse autoencoder …

Planning Methodology For Alternative Intersection Design And Selection, Liran Chen

Dissertations

The recent publication of the 6th Edition of the Highway Capacity Manual included a chapter on Ramp Terminals and Alternative Intersections that introduces various alternative intersection designs and assesses the performance of Median U-turn, Restricted crossing U-turn and Displaced left-turn intersections. Missing from the literature is an alternative intersection selection tool for identifying whether an alternative intersection would be successful under local conditions. With limited information of organized alternative intersection research, most planners must rely heavily on their personal judgement while selecting the most suitable intersection designs. As appealing as alternative intersections are, there is no comprehensive methodology for planners …

Understanding The Voluntary Moderation Practices In Live Streaming Communities, Jie Cai

Dissertations

Harmful content, such as hate speech, online abuses, harassment, and cyberbullying, proliferates across various online communities. Live streaming as a novel online community provides ways for thousands of users (viewers) to entertain and engage with a broadcaster (streamer) in real-time in the chatroom. While the streamer has the camera on and the screen shared, tens of thousands of viewers are watching and messaging in real-time, resulting in concerns about harassment and cyberbullying. To regulate harmful content—toxic messages in the chatroom, streamers rely on a combination of automated tools and volunteer human moderators (mods) to block users or remove content, which …

Waves And Oscillations In A Sunspot: Observations And Modeling Of Noaa Ar 12470, Yi Chai

Dissertations

Waves and oscillations are important solar phenomena not only because they can propagate and dissipate energy in the chromosphere, but also because they carry information about the structure of the atmosphere in which they propagate. Among these phenomena, the one of the most interesting ones occurs in the sunspot umbra. In this area, continuously propagating magnetohydrodynamic (MHD) waves generated from below the photosphere create the famous 3-minute sunspot umbral oscillations that affect the line profile of spectral lines due to temperature, density, and velocity changes of the plasma in the region. In the past decades, numerous observations and models have …

Nondestructive Evaluation Of 3d Printed, Extruded, And Natural Polymer Structures Using Terahertz Spectroscopy And Imaging, Alexander T. Clark

Dissertations

Terahertz (THz) spectroscopy and imaging are considered for the nondestructive evaluation (NDE) of various three-dimensional (3D) printed, extruded, and natural polymer structures. THz radiation is the prime candidate for many NDE challenges due to the added benefits of safety, increased contrast and depth resolution, and optical characteristic visualization when compared to other techniques. THz imaging, using a wide bandwidth pulse-based system, can evaluate the external and internal structure of most nonconductive and nonpolar materials without any permanent effects. NDE images can be created based on THz pulse attributes or a material’s spectroscopic characteristics such as refractive index, attenuation coefficient, or …

Investigation Of Topological Phonons In Acoustic Metamaterials, Wenting Cheng

Dissertations

Topological acoustics is a recent and intense area of research. It merges the knowledge of mathematical topology, condensed matter physics, and acoustics. At the same time, it has been pointed out that quasiperiodicity can greatly enhance the periodic table of topological systems. Because quasiperiodic patterns have an intrinsic global degree of freedom, which exists in the topological space called the hull of a pattern, where the shape traced in this topological space is called the phason. The hull augments the physical space, which opens a door to the physics of the integer quantum Hall effect (IQHE) in arbitrary dimensions. In …

A Self-Learning Intersection Control System For Connected And Automated Vehicles, Ardeshir Mirbakhsh

Dissertations

This study proposes a Decentralized Sparse Coordination Learning System (DSCLS) based on Deep Reinforcement Learning (DRL) to control intersections under the Connected and Automated Vehicles (CAVs) environment. In this approach, roadway sections are divided into small areas; vehicles try to reserve their desired area ahead of time, based on having a common desired area with other CAVs; the vehicles would be in an independent or coordinated state. Individual CAVs are set accountable for decision-making at each step in both coordinated and independent states. In the training process, CAVs learn to minimize the overall delay at the intersection. Due to the …

Local Learning Algorithms For Stochastic Spiking Neural Networks, Bleema Rosenfeld

Dissertations

This dissertation focuses on the development of machine learning algorithms for spiking neural networks, with an emphasis on local three-factor learning rules that are in keeping with the constraints imposed by current neuromorphic hardware. Spiking neural networks (SNNs) are an alternative to artificial neural networks (ANNs) that follow a similar graphical structure but use a processing paradigm more closely modeled after the biological brain in an effort to harness its low power processing capability. SNNs use an event based processing scheme which leads to significant power savings when implemented in dedicated neuromorphic hardware such as Intel’s Loihi chip.

This work …

Numerical Methods For Optimal Transport And Optimal Information Transport On The Sphere, Axel G. R. Turnquist

Dissertations

The primary contribution of this dissertation is in developing and analyzing efficient, provably convergent numerical schemes for solving fully nonlinear elliptic partial differential equation arising from Optimal Transport on the sphere, and then applying and adapting the methods to two specific engineering applications: the reflector antenna problem and the moving mesh methods problem. For these types of nonlinear partial differential equations, many numerical studies have been done in recent years, the vast majority in subsets of Euclidean space. In this dissertation, the first major goal is to develop convergent schemes for the sphere. However, another goal of this dissertation is …

Optimization Opportunities In Human In The Loop Computational Paradigm, Dong Wei

Dissertations

An emerging trend is to leverage human capabilities in the computational loop at different capacities, ranging from tapping knowledge from a richly heterogeneous pool of knowledge resident in the general population to soliciting expert opinions. These practices are, in general, termed human-in-the-loop (HITL) computations.

A HITL process requires holistic treatment and optimization from multiple standpoints considering all stakeholders: a. applications, b. platforms, c. humans. In application-centric optimization, the factors of interest usually are latency (how long it takes for a set of tasks to finish), cost (the monetary or computational expenses incurred in the process), and quality of the completed …

Towards Practicalization Of Blockchain-Based Decentralized Applications, Songlin He

Dissertations

Blockchain can be defined as an immutable ledger for recording transactions, maintained in a distributed network of mutually untrusting peers. Blockchain technology has been widely applied to various fields beyond its initial usage of cryptocurrency. However, blockchain itself is insufficient to meet all the desired security or efficiency requirements for diversified application scenarios. This dissertation focuses on two core functionalities that blockchain provides, i.e., robust storage and reliable computation. Three concrete application scenarios including Internet of Things (IoT), cybersecurity management (CSM), and peer-to-peer (P2P) content delivery network (CDN) are utilized to elaborate the general design principles for these two main …

Representation Learning In Finance, Ajim Uddin

Dissertations

Finance studies often employ heterogeneous datasets from different sources with different structures and frequencies. Some data are noisy, sparse, and unbalanced with missing values; some are unstructured, containing text or networks. Traditional techniques often struggle to combine and effectively extract information from these datasets. This work explores representation learning as a proven machine learning technique in learning informative embedding from complex, noisy, and dynamic financial data. This dissertation proposes novel factorization algorithms and network modeling techniques to learn the local and global representation of data in two specific financial applications: analysts’ earnings forecasts and asset pricing.

Financial analysts’ earnings forecast …

Periodic Fast Multipole Method, Ruqi Pei

Dissertations

Applications in electrostatics, magnetostatics, fluid mechanics, and elasticity often involve sources contained in a unit cell C, centered at the origin, on which periodic boundary condition are imposed. The free-space Green’s functions for many classical partial differential equations (PDE), such as the modified Helmholtz equation, are well-known. Among the existing schemes for imposing the periodicity, three common approaches are: direct discretization of the governing PDE including boundary conditions to yield a large sparse linear system of equations, spectral methods which solve the governing PDE using Fourier analysis, and the method of images based on tiling the plane with copies of …

Nystrom Methods For High-Order Cq Solutions Of The Wave Equation In Two Dimensions, Erli Wind-Andersen

Dissertations

An investigation of high order Convolution Quadratures (CQ) methods for the solution of the wave equation in unbounded domains in two dimensions is presented. These rely on Nystrom discretizations for the solution of the ensemble of associated Laplace domain modified Helmholtz problems. Two classes of CQ discretizations are considered: one based on linear multistep methods and the other based on Runge-Kutta methods. Both are used in conjunction with Nystrom discretizations based on Alpert and QBX quadratures of Boundary Integral Equation (BIE) formulations of the Laplace domain Helmholtz problems with complex wavenumbers. CQ in conjunction with BIE is an excellent candidate …

Atmospheric Mercury Chemistry: Detection, Kinetics, And Mechanism, Na Mao

Dissertations

The presence of mercury in the environment is of global concern due to its toxicity. The atmosphere is an important transient reservoir for mercury released by human activities and natural sources. The knowledge of atmospheric mercury chemistry is critical for understanding the global biogeochemical cycle. In the atmosphere, mercury primarily exists in three forms: gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM). Over the last decade, the existing knowledge of mercury cycle has dramatically changed: (1) There has been increasing evidence that current detection methods do not accurately quantify gaseous oxidized mercury and a technique which …

Private Information Retrieval And Function Computation For Noncolluding Coded Databases, Sarah A. Obead

Dissertations

The rapid development of information and communication technologies has motivated many data-centric paradigms such as big data and cloud computing. The resulting paradigmatic shift to cloud/network-centric applications and the accessibility of information over public networking platforms has brought information privacy to the focal point of current research challenges. Motivated by the emerging privacy concerns, the problem of private information retrieval (PIR), a standard problem of information privacy that originated in theoretical computer science, has recently attracted much attention in the information theory and coding communities. The goal of PIR is to allow a user to download a message from a …

Graph Enabled Cross-Domain Knowledge Transfer, Shibo Yao

Dissertations

The world has never been more connected, led by the information technology revolution in the past decades that has fundamentally changed the way people interact with each other using social networks. Consequently, enormous human activity data are collected from the business world and machine learning techniques are widely adopted to aid our decision processes. Despite of the success of machine learning in various application scenarios, there are still many questions that need to be well answered, such as optimizing machine learning outcomes when desired knowledge cannot be extracted from the available data. This naturally drives us to ponder if one …

Reactive Iron Mineral Coatings In Redox Transition Zones Of A Site With Historical Contamination: Abiotic Attenuation, Xin Yin

Dissertations

Reactive iron mineral coatings are found throughout reduction-oxidation (redox) transition zones and play a significant role in contaminant transformation processes. In this study, an 18.3-meter core is collected, subsampled, and preserved under anoxic conditions to maintain its original redox state. Screening analyses are conducted at sampling increments of 5.08 cm in depth for the following: elemental concentrations with X-ray fluorescence (XRF), sediment pH, sediment oxidation-reduction potential (ORP), total volatile organic carbon (TVOC) in the sample headspace, and abundant bacteria (16S rRNA sequencing). Using the Fe and S gradients correlated with microbial data, five RTZs are delineated. To characterize iron mineral …