Physical Sciences and Mathematics Commons^™

Quantifying Dust Structure In An Elliptical Galaxy Via Optical–Near-Infrared Color Mapping: A Detailed Study Of Ngc 6251, Luke Reed

Theses and Dissertations

The giant elliptical galaxy NGC 6251 is a well-studied active radio galaxy that hosts one of the largest known relativistic jet systems, with a projected size of approximately 3 Mpc. In addition to its large-scale radio structure, the galaxy hosts a prominent circumnuclear dust feature surrounding the active nucleus, previously interpreted as a warped dust disk. This thesis focuses on the inner morphology and dust structure of NGC 6251 using archival Hubble Space Telescope observations obtained with the WFPC2 and NICMOS instruments.

The central structure of the galaxy was investigated across multiple wavelengths through image calibration, PSF modeling and subtraction, …

Sludge-To-Sod: Sustainability In Action At Bull Creek Water Treatment Plant, Ava Baker

Goal 6: Clean Water and Sanitation

No abstract provided.

Protecting Wetlands In Georgetown County, Sophia Harrison

Goal 6: Clean Water and Sanitation

No abstract provided.

Pseudo-Riesz Bases, Deborpita Biswas

All Dissertations

In this dissertation, we will introduce the concept of pseudo-Riesz bases, extending the influential notion of near-Riesz bases first proposed by J. Holub in the 1990s. Our goal is to develop an analogous theory for pseudo-Riesz bases, obtaining results parallel to those known for near-Riesz bases, with suitable modifications.

We will develop the foundational theory of pseudo-Riesz bases. Unlike classical Riesz bases, these sequences need not be complete or independent; however, they still retain meaningful expansion properties. We will investigate the conditions under which a Bessel sequence can be transformed into a Riesz basis through finite modifications. In particular, we …

Causal Discovery Methods For Single Cell Rna-Seq Data, Melanie Lambert

All Dissertations

The advancement of single cell RNA sequencing (scRNA-seq) has enabled the study of causal relationships between genes at single cell resolution. Although many causal discovery methods have been applied to scRNA-seq perturbation data, they are not well-suited to capture the characteristics of scRNA-seq data. The overall goal of this dissertation is to enhance researchers' ability to gain insight into genetic relationships.

The scRNA-seq data is high-dimensional, typically containing thousands of genes, and is sparse and zero-inflated due to dropout events, as well as noisy and subject to biological variability. Traditional causal discovery methods, such as constraint or score-based approaches, do …

Non-Uniform Mixing Of Quantum Walks On The Symmetric Group, Avah Banerjee

Computer Science Faculty Research & Creative Works

It is well-known that classical random walks on regular graphs converge to the uniform distribution. Quantum walks, in their various forms, are quantization's of their corresponding classical random walk processes. Gerhardt and Watrous (2003) demonstrated that continuous-time quantum walks do not converge to the uniform distribution on certain Cayley graphs of the Symmetric group, which by definition are all regular. In this paper, we demonstrate that discrete-time quantum walks, in the sense of quantized Markov chains as introduced by Szegedy (2004), also do not converge to the uniform distribution. We analyze the spectra of the Szegedy walk operators using the …

Artificial Intelligence (Ai) In Forensic Psychology: An Umbrella Review Of Potentials And Pitfalls, Ysabel Thereze Ang Guevarra, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto

Research Collection School of Social Sciences

Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web …

A Longitudinal Analysis Of Hospital Consumer Evaluation In Virginia, Tulay Akmandor Inac

Health Services Research Dissertations

Suboptimal patient experience signals a need to improve clinical efficacy, patient safety, and healthcare quality. The COVID-19 pandemic intensified hospital resource and staffing demands, reducing hospitals’ capacity to invest in patient experience improvement. Prior studies remain limited because many lack longitudinal structure and organized theoretical models, making temporal inference difficult and weakening analyses of patient experience disparities. To address these limitations, this dissertation incorporates three studies examining patient experience and pandemic-related effects.

In state-level markets comparable to Virginia, limited research has examined longitudinal patient experience trends across regional hospital systems using HCAHPS scores. The first study uses descriptive trend analysis …

Energy Transition In Africa: A Comparative Analysis Of Five African Countries, Boluwatife G. Ayankojo

Graduate Program in International Studies Theses & Dissertations

Global energy transition remains a critical challenge for reducing carbon emissions and protecting the environment, with solar energy adoption driving improvements in both energy efficiency and conservation. This research focuses on Africa's transition from fossil fuels to solar energy. As population growth and blackouts increase, African countries must transition from unreliable, centralized national grids to decentralized, low-carbon alternatives that ensure quality household electricity. While some countries have advanced in this transition to sustainable solar energy, others lag behind. The limited access to electricity hinders the African continent's healthcare, education, economic growth, and mortality rates. This research establishes the importance of …

Atomic-Scale Investigation Of Functional Molecular Systems And Graphene Nanoribbons Using Scanning Probe Microscopy, A.M. Shashika D. Wijerathna

Physics Theses & Dissertations

Emerging molecular electronics, molecular devices, and carbon-based nanotechnologies increasingly rely on the precise control of molecular structures and interfaces at the atomic scale. Advancing these systems requires experimental techniques capable of resolving atomic structures, quantifying molecular behavior, and revealing the mechanisms governing nanoscale assembly. Scanning probe microscopy uniquely provides these capabilities by combining atomic-resolution imaging with local spectroscopy and manipulation. This dissertation employs ultra-high-vacuum low-temperature scanning tunneling microscopy (UHV-LT-STM) and qPlus atomic force microscopy (qPlus AFM) to address three complementary challenges: (i) atomic-scale characterization of complex supramolecular architectures, (ii) quantitative investigation of mechanically induced conformational switching of individual molecules, and …

Towards More Realistic And Practical Graph Backdoor Attacks, Jiawei Chen

Computer Science Theses & Dissertations

Graph Neural Networks (GNNs) have demonstrated remarkable performance on graph-based learning tasks and are increasingly deployed in security-critical applications. However, recent studies have shown that they are highly vulnerable to graph backdoor attacks (GBAs), where adversaries implant malicious triggers to induce targeted misclassification during inference. Despite their effectiveness, existing GBAs are often developed under unrealistic assumptions, such as focusing exclusively on simple homogeneous graphs or assuming the adversary possesses privileged access to target nodes during inference. This dissertation aims to systematically investigate and design graph backdoor attacks under significantly more realistic graph settings and adversarial constraints.

First, we investigate the …

Exploring The Determinants Of User Discontinuance In Ai-Driven Usage-Based Insurance, Wenzhuo Li

Theses and Dissertations in Business Administration

While interest in algorithmic decision-making continues to grow, limited research has examined the post-adoption phase. This study examines how users evaluate their post-adoption experiences with algorithmic decision-making in the context of usage-based insurance (UBI), focusing on how expectation disconfirmation shapes satisfaction and the intention to discontinue use. It explores two key questions: What factors influence users’ discontinuance intention toward AI-based UBI systems? And how do specific algorithmic characteristics alter how users form these post-adoption evaluations? To investigate these questions, this study develops a comprehensive theoretical model that integrates the Expectation Confirmation Model and Reactance Theory, incorporating additional factors such as …

Proxy Interfaces For Enhancing Non-Visual Web Usability, Md Javedul Ferdous

Computer Science Theses & Dissertations

People with blindness or visual impairments (BVI) face significant barriers when navigating the web, even when digital content is technically accessible. These challenges arise not from a lack of access, but from a mismatch between vision-centric user interfaces and the linear, audio-based interaction paradigms of screen readers. Sighted users rely on spatial layout, grouping, and visual cues to interpret structure quickly, while blind users must explore elements sequentially, often without sufficient context. As a result, they expend greater cognitive effort, become disoriented more easily, and struggle with tasks that are usually trivial for sighted users. Although accessibility initiatives have focused …

Modeling The Psychological And Technical Factors Influencing The Use Of Artificial Intelligence Tools Among Non-Native Arabic Learners: A Comparative Study In Egypt, Saudi Arabia, And Jordan., Mohammad Odeh, Alaa Al Din Musa, Ahmed Ragab Ali Ghalish, Montaser Adel Sayed Ahmed

All Works

This study aimed to develop a predictive longitudinal model of the psychological and technical factors influencing the use of artificial intelligence tools among non-native Arabic learners (international students) in three Arab countries: Egypt, the Kingdom of Saudi Arabia, and Jordan. The study adopted an extended Technology Acceptance Model (TAM) incorporating two psychological variables: trust in artificial intelligence and artificial intelligence anxiety. A quantitative longitudinal design with two time waves (T1 and T2) over a full academic semester was employed using Hierarchical Multiple Regression Analysis and PROCESS Macro for mediation. The sample consisted of 812 international students from public universities in …

2026 August - Tennessee Climate Snapshot, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

2026 August - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

The main weather stories in Tennessee for August 2026 included a strong heat wave that impacted the state in the middle of the month, and severe storms that caused a major power outage in the Memphis area, as well as a derecho event that impacted the northeast corner of the state.

The first event to impact Tennessee this month was the derecho on August 11, which moved through the northeast corner of Tennessee and produced some tree and powerline damage. The following week a heat wave impacted the state bringing high temperatures across the state, with 11 weather …

Automated Testing And Enhancement For Autonomous Driving Systems, Mingfei Cheng

Dissertations and Theses Collection (Open Access)

Autonomous Vehicles (AVs) rely on Autonomous Driving Systems (ADSs) to perceive their surroundings, predict the behavior of traffic participants, plan driving actions, and control vehicle motion in complex traffic environments. As AVs move toward large-scale real-world deployment, ADSs are expected not only to avoid collisions and traffic-rule violations, but also to make robust decisions, cooperate effectively with other AVs, and maintain high-quality driving behavior. However, the open, dynamic, and uncertain nature of driving environments makes the systematic testing and enhancement of ADSs a challenging problem.

Although scenario-based testing has made substantial progress in discovering safety-critical violations, several important limitations remain. …

Practical On-Device Intelligence For Resource-Constrained Embedded And Wearable Devices, Xiao Ma

Dissertations and Theses Collection (Open Access)

Embedded and wearable devices increasingly rely on deep neural networks to support intelligent sensing applications directly on the device. However, building practical on-device intelligence remains challenging throughout the deployment lifecycle. Before deployment, models must remain accurate despite severe memory, computation, and energy budgets, and a single device often needs to support multiple sensing applications without deploying a separate model for each application. After deployment, the device continues to operate in changing real-world environments, where shifts in data distribution can degrade the model’s performance over time, so the model must be able to adapt to such shifts efficiently.

The first challenge …

Forest Cover Effects On Canopy Interception Loss, Evapotranspiration, And Soil Infiltration On Stormwater Detention Basins, Alexandria N. C. Perez

Electronic Theses and Dissertations

Developing cities and increased impervious surfaces has resulted in more surface runoff and severe flooding. Harris County, Texas has experienced major flooding events, such as Hurricane Harvey in 2017 which was estimated to be a 9,000-year flood event. The Harris County Flood Control District (HCFCD) is dedicated to creating, maintaining, and finding new ways to reduce flooding damage such as the use of detention basins as green infrastructure. These basins are either populated by grass or are planted with various tree species. This study will identify the planted trees’ canopy interception loss, reference evapotranspiration, and enhanced soil infiltration effects within …

Stratigraphic Analysis Of The Buda Limestone With Implications On Hydrocarbon Production Constraints, Madison And Houston County, Texas, Jeffrey C. Bridges

Electronic Theses and Dissertations

The Fort Trinidad and Alabama Ferry fields located in eastern Madison and southern Houston County, Texas, have produced approximately 100 million barrels of oil equivalent to date, with approximately 65% of this being oil. However, there has been considerable variation in production within this Cretaceous carbonate play of the Fort Trinidad field, despite similar well completions and perforated intervals. The Buda Limestone, a key producing formation in the Cretaceous interval, is described as under-pressurized and often has lost circulation problems during drilling due to sub-pressure vertical fractures. Within the producing interval, the mechanisms for water production versus oil production are …

Macroscopic Classical And Quantum Models Of Inverse Compton Scattering, Emerson Penn Rogers

Physics Theses & Dissertations

Inverse Compton sources — in which a relativistic electron beam scatters a laser pulse to produce tunable, collimated, high-energy radiation—have emerged as among the most promising compact radiation sources, with applications ranging from nuclear photonics to medical and nanoscale imaging and metrology. The most viable current tabletop configuration couples laser-wakefield acceleration with inverse Compton scattering, producing GeV-scale electron beams over millimeter distances. As laser intensities increase and electron energies grow, the interaction enters the radiation reaction regime, where the energy radiated by the electron becomes a significant fraction of its kinetic energy. Predicting the scattered electron energy spectrum — the …

A Comparison Of Ahdrift And Pitfall Traps For Surveying Small Vertebrates, Gabrielle Risko

All-Inclusive List of Electronic Theses and Dissertations

Understanding species occupancy is necessary to inform wildlife management and conservation decisions. To minimize the invasiveness of occupancy studies, some wildlife researchers have deployed game cameras to detect the presence of small vertebrates instead of utilizing stressful traditional live-capture methods. The Adapted Hunt Drift Fence Technique (AHDriFT) is an increasingly popular method for modifying and deploying camera traps to detect small vertebrates; however, no studies have directly compared AHDriFT to traditional pitfall traps operating at the exact same time, even though both are deployed along drift fences to capture small vertebrates. I compared these two methods (pitfall trapping and AHDriFT …

Reconstruction Of Copepod Populations In Sierra Nevada Lakes Using The Diatom Fragilaria Cyclopum, Rorie Reisner

All-Inclusive List of Electronic Theses and Dissertations

Copepods are one of the most abundant types of zooplankton, and their populations are often a vital part of the food chain, but their past populations cannot be estimated from lake sediments because their exoskeleton usually does not fossilize. Gull Lake is a glacial lake located in the subalpine region of the Sierra Nevada, California, which stands out due to the presence of the diatom Fragilaria cyclopum, which is rarer in diatom assemblages. Fragilaria cyclopum exclusively grows on copepods in lakes. Diatoms have an opaline silica skeleton that often fossilizes in lake sediments, so we can use this relationship with …

Reconstructing Stand-Age Structure In A Wet Miombo Woodland Using Dendrochronology, Zambia, Clara Tiyembekeze Zulu

All-Inclusive List of Electronic Theses and Dissertations

Dendrochronological research in tropical Africa has remained limited, leaving critical gaps in stand-age structure and climate-growth relationships in seasonally dry tropical woodlands. This study reconstructed stand-age structure and assessed climate sensitivity in the wet Miombo woodland of African Explosives Limited (AEL) forest, Copperbelt Province, Zambia. Field sampling was conducted during four African Dendrochronology Fieldschools (2021-2024) using a Modified Variable Area Transect (MVAT) design across nine plots. The series intercorrelation was 0.351; the average mean sensitivity was 0.423. The oldest tree was 170 years old, and more than 70% of the sampled species showed potential for dendrochronology. Markhamia obtusifolia was the …

Performance Of The Denitrification-Decomposition Model In Simulating Agronomic Properties And N2o Emissions Under Smallholder Climate-Smart Farming Systems, Esphorn Kibet, Collins M. Musafiri, Milka Kiboi, Onesmus K. Ng'etich, David K. Kosgei, Abdirahman Zeila, Franklin Mairura, Felix K. Ngetich

All Peer-Reviewed Publications

The DeNitrification-DeComposition (DNDC) model is a crucial tool for estimating soil greenhouse gas fluxes and understanding soil-plant interactions. This study evaluates the performance of the DNDC model in simulating soil temperature, moisture, crop yield, and nitrous oxide (N2O) fluxes across different land utilization types in Western Kenya. The land utilization types included: i) agroforestry M (agroforestry with Markhamia lutea, ii) sole sorghum, iii) agroforestry L (agroforestry with Leucaena leucocephala), iv) sole maize, and v) grazing Land, each replicated thrice. Fertilizer and manure were applied as part of the management practices, with manure applied at 2t ha⁻¹. Soil greenhouse …

Spring Ai 2026 Workshop And Speaker Series Report, Gregory Blike, Hannah (Nyingi) Brown, Dora (Dawn) Nguyen, Rami Huu Nguyen, Ajanee Igharo, Frayni Calderon, Moumita Saha, Chengjie Zheng

Paul English Applied Artificial Intelligence (AI) Institute Publications

The AI Workshop and Speaker Series was organized by the Student Advisory Council of the Paul English Applied Artificial Intelligence Institute at the University of Massachusetts Boston with the guidance of Distinguished Professor of Computer Science Wei Ding to create a practical and student-centered AI learning space. The Spring 2026 series included workshops on LinkedIn Optimization, Data Mining, GitHub, Prompt Engineering, Machine Learning of Structured Data, and Applied LLMs with Responsible AI Use in Research, while the broader speaker series introduced students to AI career development, generative AI and LLMs for cybersecurity, transportation security, political sciences, and AI in biomedicine. …

Multi-Particle Reactions In Lattice Field Theories: From Euclidean To Quantum Computations, Marco Antonio Carrillo Bernal

Physics Theses & Dissertations

Amplitudes of multi-particle processes provide a probe of the dynamics described by relativistic quantum field theories. In the context of quantum chromodynamics, these amplitudes encode the way in which quarks and gluons are bound together by the strong nuclear force to form hadrons and govern their interactions. The non-perturbative nature of the strong interactions complicates the study of hadronic amplitudes from first principles. The most effective way of studying hadronic reactions non-perturbatively is the numerical framework known as lattice quantum chromodynamics. This method relies on theoretical formalisms that establish relations between numerical observables, such as finite-volume energy levels and matrix …

Understanding The Correlation Between Prediction Performance And Trust In Ai Through Scenario-Based Tasks, Likhitha Kammara

Theses and Dissertations

Trust in artificial intelligence is commonly assessed through self-reported scales or behavioral reliance, yet behavioral reliance is retrospective and can only be observed after a decision has already been made. This thesis examines whether prediction accuracy — a user's ability to predict what an AI system will recommend before its output is revealed — can serve as a prospective correlate of trust in the same empirical sense as behavioral reliance. The study was conducted in two phases using scenario-based AI decision tasks across disaster response, healthcare, and infrastructure restoration contexts, employing a between-group design in which participants either predicted AI …

Magnetic Properties And Ultrafast Spin Dynamics In Quantum Materials, Trung Kien Mac

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern electronics mostly work by moving electric charge, which generates heat and hence wastes energy, especially as devices become smaller and faster. An alternative is to use the spin of electrons (a tiny magnetic property) and related “valley” states in certain atomically thin materials to store and process information more efficiently. This thesis explores how magnetism and spin behavior can be created and measured in a family of ultra-thin materials known as van der Waals quantum materials. Three kinds of materials are studied. First, atomically thin semiconductors are shaped into narrow nanoribbons. Because of their narrow size, their edges can …

Lessons Learned From The Adrenalin Load Disaggregation Challenge, András Balázs Tolnai, Zheng Ma, Igor Sartori, Clayton Miller, Stephen White, Matt Amos, Gustaf Bengtsson, Akram Hameed, Nørregaard Bo Jørgensen

Research Collection College of Integrative Studies

Crowdsourced data science competitions have emerged as a powerful mechanism for advancing research in energy informatics, offering scalable pathways for developing machine learning solutions that enhance energy efficiency and smart building operations. The ADRENALIN Load Disaggregation Challenge addressed a central problem in energy analytics—non-intrusive load monitoring (NILM) of heating and cooling loads in commercial buildings—while emphasizing the importance of model generalization across different buildings. This paper presents a comprehensive reflection on the lessons learned from organizing and executing the ADRENALIN competition, including technical insights, organizational challenges, and recommendations for future energy data challenges. In addition to the ADRENALIN case, a …