Physical Sciences and Mathematics Commons^™

Gas-Phase Proton Affinities Of Proline- And Pipecolic Acid-Containing Dipeptides, Trinh Ton

Dissertations, Theses, and Masters Projects

Mass spectrometry (MS) is one of the most used techniques in proteomics because it allows for both high-throughput and quantitative analyses. Bottom-up MS-based proteomics involves breaking down proteins into smaller chains of amino acids called peptides, ionizing and fragmenting the peptides, and identifying the fragments using sequencing databases. These databases depend on the random fragmentation at the backbone peptide bond of the peptides, as predicted by the mobile proton model. Research has shown that peptides containing proline or pipecolic acid have selective fragmentations that could lead to incorrect identification in the sequencing algorithms. These selective cleavages are called “the proline …

Chesapeake Bay Carbonate Cycle: Past, Present, And Future, Fei Da

Dissertations, Theses, and Masters Projects

Multiple natural and anthropogenic drivers are expanding the variability of the estuarine carbonate system (CO2 system). These changes in the CO2 system are threatening the health of ecologically and economically important bivalve species. This dissertation investigates the Chesapeake Bay CO2 system by using numerical models and historical water quality data, focusing on the past three decades, the contemporary period, and the late 2060s. In Chapter 2, sensitivity experiments are conducted with a 3-D Chesapeake Bay hydrodynamic-biogeochemical model and reveal that the magnitude of decadal trends in the CO2 system over the past 30 years is much greater than that observed …

Domain-Specific Optimization For Machine Learning System, Yu Chen

Dissertations, Theses, and Masters Projects

The machine learning (ML) system has been an indispensable part of the ML ecosystem in recent years. The rapid growth of ML brings new system challenges such as the need of handling more large-scale data and computation, the requirements for higher execution performance, and lower resource usage, stimulating the demand for improving ML system. General-purpose system optimization is widely used but brings limited benefits because ML applications vary in execution behaviors based on their algorithms, input data, and configurations. It's difficult to perform comprehensive ML system optimizations without application specific information. Therefore, domain-specific optimization, a method that optimizes particular types …

Dataset: A Numerical Simulation Of The Ocean, Sea Ice And Ice Shelves In The Amundsen Sea (Antarctica) Over The Period 2006-2022 And Its Associated Code And Input Files, Pierre St-Laurent

Data

A three-dimensional numerical model of the Amundsen Sea (Antarctica) was used to simulate the period Jan.2006-Mar.2022 under consistent atmospheric/oceanic forcings, bathymetry/ice shelf topography, and model equations/parameters. The model is an implementation of the Regional Ocean Modeling System (ROMS, https://www.myroms.org/) with extensions for sea ice (Budgell 2005) and ice shelves (Dinniman et al. 2011). It simulates the ocean hydrography and circulation, sea ice thermodynamics and dynamics, and the basal melt of the ice shelves, with a uniform horizontal mesh of 1.5km and 20 topography-following vertical levels. Forcings include the ERA5 reanalysis (3-hourly), 10 tidal constituents from CATS 2008, and ocean/sea ice …

Tracing Atlantic Sea Scallops Using Radio Frequency Identification (Rfid) Technology, Will Shoup

Dissertations, Theses, and Masters Projects

Traceable seafood can be linked back to its origin and method of catch. Improving the traceability of marine organisms involves establishing a transparent Chain of Custody (CoC) by collecting data at checkpoints throughout the supply chain, from ship to shore to store. This report explores the feasibility of integrating Radio Frequency Identification (RFID) technology into the United States Atlantic sea scallop (Placopecten magellanicus) fishery in order to improve traceability. This report serves as a forward-looking evaluation of RFID technology that is intended to inform interested stakeholders of its functionality and capabilities. It is not intended to serve as a management …

Mattanock Town Restoration Plan, Katlin Mccarter Grigsby

Dissertations, Theses, and Masters Projects

Mattanock Town's Restoration Plan is a science-based restoration process that evaluates the site's history, the tribal history, and the most current research to maximize native habitats, enhance coastal resilience, and reconnect the Nansemond people to the local river. Restoration priorities include increasing native plant species, incorporating oyster habitat, and addressing erosion. This plan details how synthesizing existing and new physical, biological, and cultural information can help the Nansemond Indian Nation prioritize projects that benefit their community and the surrounding environment.

Achieving Equitable Offshore Wind Development: Lessons From European Stakeholders, Kacey Hirshfeld

Dissertations, Theses, and Masters Projects

The Biden Administration has set aggressive offshore wind energy goals, aiming to have 30 gigawatts of offshore energy in place by 2030. This amount of energy has the potential to power 10 million homes (White House, 2022), helping the administration to reach larger clean energy goals. In Virginia, Dominion Energy aims to have 2.6 gigawatts of offshore wind energy by 2026, enough to power up to 660,000 homes (Dominion Energy).

While the upcoming offshore wind energy development will create clean energy and green jobs, the ocean is no longer an open field for development and already supports a complex matrix …

Spectroscopy And Dynamics Of Atmospherically And Combustion-Relevant Collision Complexes, John Patrick Davis

Dissertations, Theses, and Masters Projects

Potential energy surfaces describing bimolecular collisions sensitively depend on the chemical functionality and the relative orientation of colliding partners, thus defining the accessibly reactive and nonreactive pathways. Herein, we investigate the peculiar product outcomes arising from Jahn-Teller distortion of the nitric oxide and methane complex (NO-CH4). We have reported an in-depth spectroscopic and dynamics study of NO-CH4 by utilizing conformation-specific and action spectroscopy, as well as velocity map imaging, to understand the fundamental dissociative mechanisms at play. Ultimately, we have gained information about how the Jahn Teller effect possibly impacts the potential product energy transfer pathways. There is a translationally …

Recoverable Memory Bank For Class-Incremental Learning, Jiangtao Kong

Dissertations, Theses, and Masters Projects

Incremental learning aims to enable machine learning systems to sequentially learn new tasks without forgetting the old ones. While some existing methods, such as data replay-based and parameter isolation-based approaches, achieve remarkable results in incremental learning, they often suffer from memory limits, privacy issues, or generation instability. To address these problems, we propose Recoverable Memory Bank (RMB), a novel non-exemplar-based approach for class incremental learning (CIL). Specifically, we design a dynamic memory bank that stores only one aggregated memory representing each class of the old tasks. Next, we propose a novel method that combines a high-dimensional space rotation matrix and …

Biotic And Abiotic Factors Associated With Temporal And Spatial Variability Of Constitutive Mixotroph Abundance And Proportion, Marcella Dobbertin Da Costa

Dissertations, Theses, and Masters Projects

Mixotrophic protists, which combine the use of photosynthesis and prey ingestion to obtain nutrients for growth, comprise a substantial portion of the plankton community. However, there is a major gap in our understanding of how mixotroph prevalence varies spatially and temporally and under what conditions they dominate. I utilized a recently developed molecular technique to experimentally identify active mixotrophs (taxa identified to be grazing when samples were collected) and combined this with microscopy data to estimate active mixotroph abundance and proportion at two locations in a temperate estuary over a year. Active mixotroph abundance was compared to potential mixotroph (taxa …

Intelligent Software Tooling For Improving Software Development, Nathan Allen Cooper

Dissertations, Theses, and Masters Projects

Software has eaten the world with many of the necessities and quality of life services people use requiring software. Therefore, tools that improve the software development experience can have a significant impact on the world such as generating code and test cases, detecting bugs, question and answering, etc. The success of Deep Learning (DL) over the past decade has shown huge advancements in automation across many domains, including Software Development processes. One of the main reasons behind this success is the availability of large datasets such as open-source code available through GitHub or image datasets of mobile Graphical User Interfaces …

Appearance Driven Reflectance Modeling, James Christopher Bieron

Dissertations, Theses, and Masters Projects

Creating realistic computer generated imagery is essential for modern movies and video games. Recreating the appearance of materials is integral to generating such photo-realistic images. While the problem of how to model materials is well studied, here we will focus on the question of how to recreate the appearance of specific materials found in the real world. In this dissertation we will begin with a short introduction to rendering, followed by a discussion of various material models, techniques for measuring reflectance, and strategies for fitting these models to reflectance data. We will then introduce a novel two-stage process for fitting, …

Achieving Real-Time Dnn Execution On Mobile Devices With Compiler Optimizations, Wei Niu

Dissertations, Theses, and Masters Projects

Deep learning, particularly deep neural networks (DNNs), has led to significant advancements in various fields, such as autonomous driving, natural language processing, extended reality (XR), and view synthesis. Mobile and edge devices, with their efficient and specialized processors and suitability for real-time scenarios, have become the primary carriers for these emerging applications. The advancements in AutoML tools (e.g., Network Architecture Search) and training techniques have resulted in increasingly complex and deep DNN architectures with larger computational requirements. However, achieving real-time DNN execution (inference) on mobile devices is a challenging task due to the limited computing and storage resources available on …

Matfusion: A Generative Diffusion Model For Svbrdf Capture, Samuel Lee Sartor

Dissertations, Theses, and Masters Projects

We formulate SVBRDF estimation from photographs as a diffusion task. To model the distribution of spatially varying materials, we first train a novel unconditional SVBRDF diffusion backbone model on a large set of 312,165 synthetic spatially varying material exemplars. This SVBRDF diffusion backbone model, named MatFusion, can then serve as a basis for refining a conditional diffusion model to estimate the material properties from a photograph under controlled or uncontrolled lighting. Our backbone MatFusion model is trained using only a loss on the reflectance properties, and therefore refinement can be paired with more expensive rendering methods without the need for …

Subsurface Structure And Impacts Of Marine Heatwaves In The Chesapeake Bay, Nathan P. Shunk

Dissertations, Theses, and Masters Projects

Extreme temperature events known as Marine Heatwaves (MHW), akin to atmospheric heatwaves, have only recently received attention by the estuarine scientific community. Thus far, studies have focused solely on surface events due to scarcity of long-term subsurface data. This study investigates, for the first time, the subsurface temperature and dissolved oxygen (DO) anomalies associated with surface MHW events in a large, temperate, partially mixed estuary: the Chesapeake Bay (CB). Using over three decades (1986-2021) of in-situ data from several long-term monitoring programs in the CB (including sub daily moored measurements and monthly/bimonthly cruises along the main stem) and a global …

Program Analysis For Software Engineers And Students, Jialiang Tan

Dissertations, Theses, and Masters Projects

Software inefficiencies are inevitable in computer systems. At the code level, software packages have become increasingly complex, they are comprised of a large amount of source code, sophisticated control and data flow, and growing levels of abstraction. This complexity often introduces inefficiencies across software stacks, leading to performance degradation. At the resource level, the evolution of hardware outpaces the performance optimization of software, leading to resource wastage and energy dissipation in emerging architecture. To better understand program behaviors, software developers take advantage of performance profiling tools. Existing profiling techniques, whether fine-grained profilers or coarse-grained profilers focus on identifying hotspots, which …

Efficient Parallelization Of Irregular Applications On Gpu Architectures, Qihan Wang

Dissertations, Theses, and Masters Projects

With the enlarging computation capacity of general Graphics Processing Units (GPUs), leveraging GPUs to accelerate parallel applications has become a critical topic in academia and industry. However, a wide range of irregular applications with a computation-/memory-intensive nature cannot easily achieve high GPU utilization. The challenges mainly involve the following aspects: first, data dependence leads to a coarse-grained kernel; second, heavy GPU memory usage may cause frequent memory evictions and extra overhead of I/O; third, specific computation patterns produce memory redundancies; last, workload balance and data reusability conjunctly benefit the overall performance, but there may exist a dynamic trade-off between them. …

Environmental Education In The Classroom: Selected Early-Career Teachers' Experiences Navigating Pre-Service And In-Service Activity Systems, Sarah Mcguire Nuss

Dissertations, Theses, and Masters Projects

Recent publications argue that to prepare teachers of all grade levels to be confident and competent in incorporating environmental education into their classrooms, pre-service teacher training is effective (e.g., J. T. McDonald & Dominguez, 2010). But the systems in which teachers learn and work are complex, making professional learning about, and implementation of, environmental education both disparate and limited (Franzen, 2017). This study sought to understand the nature of participants’ experiences within and between teacher preparation and in-service learning systems as they relate to environmental education. Cultural historical activity theory (CHAT) provided a framework to allow for deeper understanding of …

Characterizing Molecular Environments In Acrylic Paint Via Single-Sided Nmr, Lyndi Kiple

Dissertations, Theses, and Masters Projects

Acrylic paint is a modern artistic material made of colored pigment and polymeric binder. Acrylic binder requires fundamental study at the molecular level to understand its physical properties for purposes of art conservation and general polymer chemistry. The research presented in this thesis uses single-sided nuclear magnetic resonance (NMR) as a non-invasive and non-destructive way to measure relaxation and self-diffusion, which provide insight to molecular mobility and physical properties of proton-containing samples. Specifically, this study relies on T2 relaxation to gain insight to regions within acrylic paint with different molecular mobilities. In both dry and wet paint, relaxometry data revealed …

Emerging Red Sore Disease Of American Eel (Anguilla Rostrata) In Chesapeake Bay: Etiology, Epidemiology, And Impacts In Aquaculture And The Wild, Amanpreet Kaur Kohli

Dissertations, Theses, and Masters Projects

Emerging infectious diseases in aquatic systems, both in aquaculture and in the wild, are a global concern. Many have proposed an uptick in marine diseases as a result of environmental changes including a warming climate, habitat modifications, trade and transfer of wildlife and aquaculture products, pollution, overharvesting of resources, and other anthropogenic impacts. These perturbations can disturb the delicate host-pathogen relationships and result in new diseases or exacerbate the existing diseases in a population. Diseases can lead to several direct and indirect effects in the ecosystem such as population declines and extinctions, and thereby a change in population dynamics, as …

Climate Impacts On Spatiotemporal Habitat Usage Of Mid-Atlantic Fishes, Adena Jade Schonfeld

Dissertations, Theses, and Masters Projects

Climate change has altered marine environments, most notably by increasing water temperatures and reducing dissolved oxygen concentrations. These persistent changes have impacted the phenology and spatiotemporal habitat usage of mobile species, often through distributional shifts poleward or to deeper water. Climate-driven distributional shifts have been documented for numerous species inhabiting the Atlantic Ocean along the US East Coast, a region disproportionately affected by climate change. Adjacent estuaries are experiencing similar alterations to their physical environments and biotic community composition. Many estuarine species are seasonal residents and changes to environmental conditions within an estuary can result in altered usage and residence …