Digital Commons Network^™

Investigating The Temperature Effects On Aedes Aegypti And Dengue Virus In Central Argentina: Perspectives From Mathematical Modeling, Morgan H. Jackson

Theses and Dissertations

Dengue virus (DENV) causes over 390 million infections and around 40,000 deaths worldwide each year. DENV is primarily transmitted by the mosquito Aedes aegypti, and both the life cycle of these mosquitoes and DENV transmission are significantly impacted by temperature. In the temperate region of Central Argentina, where dengue outbreaks first began in 2009, outbreaks only occur following new introductions of DENV from other regions. Due to the relationships between temperature and DENV and temperature and Ae. aegypti, the risk of an outbreak changes throughout the year. Here, we develop and analyze mathematical models for both mosquito population dynamics and …

Modeling Synergistic Effects Of Integrin And Tgf-Β Signaling In Epithelial Mesenchymal Transition, Prerak Thakkar

Theses and Dissertations

The induction of Epithelial Mesenchymal Transition (EMT) is initiated by a

number of protiens and growth factors, one of which is the profibrotic cytokine Trans-

forming Growth Factor β (TGF-β). Within the extracellular matrix (ECM), TGF-β

is found in a latent, inactive form bound to proteins such as fibronectin (FN). For

TGF-β to contribute to EMT induction, it has to be extracted from the latent com-

plexes into a soluble form. This soluble, activated TGF-β can then bind to receptors

on the cell membrane, which causes the transduction of signals that begin EMT. Re-

search has shown that the release …

Substrate Preference And Foraging Behavior Of Two Declining Warblers In Appalachian Shrublands, Samantha Fishman

Theses and Dissertations

Abstract Shrubland and early successional habitats (ESH) support a diversity of wildlife, including many declining songbirds. However, nonnative shrubs increasingly dominate these habitats, potentially altering habitat quality by influencing prey availability. Habitat quality can be assessed by observing foraging behaviors of songbirds and identifying preferred and avoided substrates as well as testing the predictions of optimal foraging theory; specifically that birds will maximize their energy gain relative to the costs. We examined foraging behaviors of Golden-winged Warblers (Vermivora chrysoptera; GWWA) and Chestnut-sided Warblers (Setophaga pensylvanica; CSWA) in ESH on private lands in Virginia with varying amounts …

Hafnium Oxide-Based Nanoheterostructures For Catalytic Radiosensitization And Enhanced X-Ray Radiotherapy, Marlen Dariela Calix Quezada

Theses and Dissertations

Orthovoltage X-ray beams are attractive for surface and intra-operative radiotherapy. Yet, their clinical utility is constrained by rapid attenuation and the limited dose that can be delivered without harming healthy tissue. High-Z hafnium oxide (HfO₂) nanoparticles can boost local energy deposition through the photoelectric effect, while catalytic surface defects accelerate water radiolysis. Harnessing both mechanisms in a single nano-heterostructure could enable potent radiosensitization at diagnostic-range energies.

This thesis develops and evaluates HfO₂-based nanoheterostructures, both bare and Au-decorated, as catalytic radiosensitizers.

Two types of HfO₂ were evaluated, one was synthesized following a specific route and the …

An Exploration Of The Relationship Between School Counselor Access And Latine Students’ College-Going Behaviors, Kristen Tuxbury

Theses and Dissertations

This study examined the relationships between school counselor access and Latine students’ college-going behaviors using data from the High School Longitudinal Study of 2009 (HSLS:09). The study was guided by critical race theory and Yosso’s community cultural wealth model (2005). Binary logistic regression models, Chi-square tests of independence, and descriptive statistics were used to explore the associations between school counselor access, Latine student college-going behaviors, and caregiver expectations. The findings show stronger associations between caregiver expectations and Latine student college-going behaviors than school counselor access. Additionally, findings provide evidence that experiences of oppression are likely barriers to Bachelor’s degree programs …

Optimal Data Splitting Methods, Sujay Mudalgi

Theses and Dissertations

In predictive modeling, effective data splitting is crucial for creating statistically representative training and validation sets. The state-of-the-art data splitting methods are based on minimizing the energy distance between the split subsets. However, there are a number of limitations in the existing methods, which this dissertation aims to address. First, the existing methods were computationally inefficient. Thus, Chapter 2 proposes a method to scale up these approaches for big data. Here, we introduce scalable Twinning (s-Twinning), which significantly improves the execution speed of data splitting without sacrificing accuracy. Second, the existing methods did not consider the predictive relationship in the …

Machine Learning Models Leveraging Patient-Similarity And Clinical Temporality For Disease Prognoses, Ahmad F. Al Musawi

Theses and Dissertations

Electronic Health Records (EHRs) constitute a comprehensive and high-dimensional repository of clinical data, encompassing a wide array of patient-level information such as diagnoses, procedures, medications, laboratory results, and unstructured clinical narratives. These data hold immense potential for advancing predictive modeling in healthcare, including tasks such as disease progression modeling, hospital readmission prediction, and length of stay (LoS) estimation. However, the intrinsic complexity of EHR data—manifested in its heterogeneity, sparsity, and temporal dynamics—poses significant analytical challenges that limit the generalizability and interpretability of conventional machine learning models. Recent methodological advancements in deep learning and graph-based learning, particularly Graph Neural Networks (GNNs), …

Visible Modulation Of Epsilon Near Zero Materials, Jonathan M. Weber

Theses and Dissertations

While Epsilon-Near-Zero materials have offered many benefits from their introduction to the field of nonlinear optics, those materials have also narrowed the range of wavelengths often studied. With reliable and proven enhancements to light-matter interaction in the ENZ region, many researchers have had little reason to extend the spectrum measured in experiments. The purpose of this work is to measure the intensity dependent refractive index of Indium Tin Oxide across a broad spectral range, from ultraviolet to near infrared, to improve the understanding of semiconductor nonlinearities far from Lorentz and Drude resonances. Furthermore, the visible region is naturally low-loss in …

Intervertebral Lateral Bending Moment Differences In The Lumbar Spine Of Baseball Pitchers Across Throwing Velocities, Justin Humenay

Theses and Dissertations

Introduction Baseball pitching imposes substantial mechanical demands on the lumbar spine, a crucial link in the kinetic chain responsible for transferring energy from the lower body to the upper extremity. While increased pitch velocity is associated with greater trunk forces the specific intervertebral loading patterns during high-velocity pitching remain unclear. This study investigates differences in lateral bending moments across lumbar spinal segments between collegiate pitchers throwing at high versus low velocities.

Methods Twenty right-handed collegiate pitchers were divided into two groups: high-velocity (n = 10, 90.3 ± 1.6 mph) and low-velocity (n = 10, 81.6 ± 1.1 mph). Motion capture …

Periodic Trends In The Electronic And Magnetic Structure Of Superatomic 3d Transition Metal Chalcogenide Clusters, Gabriel Bohannon

Theses and Dissertations

We have systematically investigated the electronic structure of octahedral transition metal chalcogenide clusters, TM₆S₈(CO)₆, in which the transition metal atoms are from the 3d series in order to identify if periodic properties emerge. We were motivated by the identification of closed electronic shells with electron counts of 96, 100 and 114 in similar clusters from the 4d and 5d transition metal series. Further motivation was the finding of a dual-shell closing in the Fe₆S₈(CN)₆^5- cluster. This cluster is stabilized with a large spin magnetic moment due to the …

Modeling Vaccination Strategies And Intervention Impacts On Infectious Disease Dynamics, Elizabeth B. Amona

Theses and Dissertations

This dissertation explores how mathematical and statistical modeling can inform vaccination strategies and evaluate the impact of interventions during infectious disease outbreaks. Motivated by the challenges observed during the COVID-19 pandemic, the research integrates compartmental modeling, Bayesian inference, and agent-based simulation to assess policy effectiveness and disease control across varying contexts. The first study develops a SEIRDV model that incorporates government interventions and vaccination rollout to examine COVID-19 dynamics in Qatar. A Bayesian approach is used to estimate parameters and compute time-varying transmission rates. The model captures shifts in transmission following policy changes and quantifies the reduction in deaths attributable …

Automated Treatment Planning Framework For Cervical Cancer In Brachytherapy, Suman Gautam

Theses and Dissertations

Brachytherapy (BT) is a critical treatment modality for cervical cancer that delivers ionizing radiation directly to the tumor using intracavitary (IC) and/or interstitial (IS) applicators. In high dose-rate (HDR) BT, a remote afterloader guides the radioactive source to specific dwell positions for defined durations, known as dwell times, allowing for a conformal dose to the tumor while minimizing exposure to surrounding organs at risk (OAR). However, due to the inherent nature of ionizing radiation, some dose to OARs is unavoidable, creating a fundamentally conflicting objective in treatment planning: maximizing tumor coverage while minimizing OAR dose. This characterizes the problem as …

Plasmon-Assisted On-Chip Integration Of Quantum Emitter For Scalable Quantum Networking, Samprity Saha

Theses and Dissertations

In recent decades, quantum theory has sparked a revolutionary outlook on our long-standing perception of information processing and communication technologies. Photon-based quantum systems, relying on single photons governed by quantum mechanics, hold immense promise for quantum networks due to their resilience against decoherence and fast propagation speeds. However, challenges persist in realizing practical quantum networks, including the need for scalable, robust, and cost-effective quantum light. To address these challenges with classical photonic concepts, this thesis focuses on a plasmon-assisted approach for on-chip integration of single-photon sources. The study aims to develop a scalable solution for integrating quantum emitters on-chip, leveraging …

A Mixed Methods Study: High School Teachers’ Perspectives On Incorporating Mindful Artmaking In Their Classroom As A Mental Health Resource, Sherry A. Bosarge

Theses and Dissertations

Mental health concerns and the need for mental health resources for high school students continue to rise in Virginia. Some of the reported benefits to the current mental health services and resources offered in Virginia schools are increased academic outcomes, attendance, and positive behaviors. The reported barriers to current mental health services and resources are lack of participation, lack of training, time constraints, funding, and resources. This explanatory sequential mixed methods study examined high school teachers’ perspectives on the benefits and barriers to incorporating mindful artmaking in their classrooms as a mental health resource at a local high school. This …

Brute Gamification, Catherine Chen

Theses and Dissertations

Digital platforms are surreptitious structures that gamify the ways in which we engage and exchange. They dictate every step of our journeys even as we navigate onward with a sense of absolute agency. The harder that we try to win, the more the platform will win!

In Brute Gamification, I employ image-based installation and performance to unravel the terms and conditions with which these platforms dictate our lives. A literal platform supports a series of image-games, all of which are about to end in a draw. Through prescribing the user to a designated path to focus on this non-ending as …

Facile Synthesis Of Gold, Copper, And Silicon Nanostructures By Laser Ablation In Liquid, Nicholas Simpson

Theses and Dissertations

Metal nanoparticle (NP) synthesis is a continually evolving area of research, owing to the widespread application of NPs in fields such as catalysis, drug delivery, and biosensing. Compared to bulk metal material, NPs contain a larger proportion of surface atoms and exhibit unique optical properties, thus making them ideal for applications where maximizing surface interactions is key. Moreover, their compositions can be altered in several different ways, as evidenced by metal alloy, core/shell, supported, and defective NPs. While conventional synthesis methods are capable of producing NPs in large quantities, they often require conditions of high temperature and pressure, strong reducing …

Knowing By Heart: Philosophical Dimensions Of Humanistic Mathematics Education, Catherine Henney

Theses and Dissertations

This project seeks to revive interest in late twentieth century humanistic mathematics education (HME) so that its principles might cross the boundary of higher education and settle in corners of the K-12 math education space. In particular, HME’s theme of teaching math humanistically directs attention to features and phenomena that bear strongly on students’ daily classroom experiences. Personhood, agency, inquiry, meaning, environment, feelings, relationships: these elements invite a more thorough meditation and philosophical analysis. Though it is a largely philosophical endeavor, this project is enlivened by classroom vignettes and case studies that bring practical relevance to HME’s core principles. Chapters …

Advanced Air Preheater Sealing Systems For Enhanced Efficiency And Reliability In Thermal Power Plants, Pavan Kumar Ravulaparthy

Theses and Dissertations

Global electricity generation still relies heavily on thermal power plants, which consume vast amounts of fuel and emit significant amounts of carbon dioxide. A major but often overlooked source of inefficiency in these plants lies within the rotary regenerative air preheater (RAPH), a critical heat-exchange component where air leakage can exceed 20% in aging units. This leakage increases fuel consumption, parasitic fan power, and CO₂ emissions, while degrading boiler reliability.

This research introduces advanced adaptive sealing systems designed to mitigate these losses by dynamically compensating for rotor eccentricity, thermal distortion, and wear under harsh operating conditions. Brush seals, composed of …

Machine Learning-Driven Optimization For Utility-Scale Quantum Optimization, Bao Tran

Theses and Dissertations

Hard combinatorial optimization problems, often mapped to Ising models, promise potential solutions with quantum advantage but are constrained by limited qubit counts in near-term devices. We present an innovative quantum-inspired framework that dynamically compresses large Ising models to fit available quantum hardware of different sizes. Thus, we aim to bridge the gap between large-scale optimization and current hardware capabilities. Our method leverages a physics-inspired GNN architecture to capture complex interactions in Ising models and accurately predict alignments among neighboring spins (aka qubits) at ground states. By progressively merging such aligned spins, we can reduce the model size while preserving the …

Implementation Of Quantized Artificial Neural Networks With Spintronic Stochastic Computing, Saadi Sabyasachi Mr.

Theses and Dissertations

Artificial intelligence or machine learning is going through a rapid expansion. It also incurs significant costs for power and device footprints. Various approaches are being explored to design energy and hardware efficient machine learning models. Stochastic computing has been proposed for efficient machine learning implementation. It requires a source of random number generation which poses some practical challenges. So spintronic solutions such as magnetic tunnel junction has been used for random number generation. Again, spintronic random number generation to implement high precision circuit is prone to device-to-device variations. Hence we designed quantized artificial neural network with spintronic stochastic computing which …

Learning From Non-Stationary Data Streams, Gabriel Jonas Aguiar

Theses and Dissertations

The rapid growth of data from sources such as mobile applications, sensors, and network monitoring has increased the need for machine learning algorithms capable of handling non-stationary data streams. However, learning from such streams presents significant challenges due to their evolving nature and the presence of concept drift. One of the most complex issues is learning from imbalanced data streams, where shifting data distributions, combined with feature space drifts, complicate continuous adaptation. These challenges become even more pronounced in multi-class scenarios, which are common in real-world applications. Detecting concept drift in such contexts is particularly demanding, as it requires tracking …

Establishing A Conventional Linac-Based Electron Flash Beam, Justin Defrancisco

Theses and Dissertations

Problems: A rediscovered radiotherapy technique, FLASH, involves increasing the dose rate to >40 Gy/s. For a given dose, FLASH is shown to decrease the normal tissue complication probability without affecting the tumor control probability. More preclinical studies are necessary to confirm and enable these desirable properties on humans. Current preclinical investigations have diverse constraints, requiring FLASH apparatuses with flexible parameters and accurate control. However, there are limited FLASH platforms available, the existing ones are costly. Our institution is not in possession of any such infrastructure. Even if available, dosimetry and beam control in FLASH are extremely lacking. There is …

Three Essays On Investment Strategies, Machine Learning And Risk Management, Nafise Aalipour

Open Access Dissertations

This dissertation explores the role of frictions, regime dynamics, and predictive modeling in understanding persistent anomalies and managing financial risk in equity markets. Across three essays, I examine how transaction costs limit arbitrage opportunities, how market regimes shape the evolution of return anomalies, and how a hybrid econometric-machine learning framework can enhance risk forecasting.

The first essay investigates whether transaction costs and idiosyncratic risk constrain the profitability of long-term reversal and medium-term momentum strategies. Using a comprehensive dataset from 1927 to 2022, I estimate stock-level trading frictions through three distinct methods - Limited Dependent Variable models, Gibbs cost estimators, and …

Maximum Trimmed Likelihood Estimation For Discrete Multivariate Vasicek Processes, Thomas M. Fullerton Jr., Michael Pokojovy, Andrews T. Anum, Ebenezer Nkum

Mathematics & Statistics Faculty Publications

The multivariate Vasicek model is commonly used to capture mean-reverting dynamics typical for short rates, asset price stochastic log-volatilities, etc. Reparametrizing the discretized problem as a VAR(1) model, the parameters are oftentimes estimated using the multivariate least squares (MLS) method, which can be susceptible to outliers. To account for potential model violations, a maximum trimmed likelihood estimation (MTLE) approach is utilized to derive a system of nonlinear estimating equations, and an iterative procedure is developed to solve the latter. In addition to robustness, our new technique allows for reliable recovery of the long-term mean, unlike existing methodologies. A set of …

United States Environmental Protection Agency Scientific Integrity Policy

Copyright, Fair Use, Scholarly Communication, etc.

US EPA SIP

Yars 18(32)

Yearbook of Antitrust and Regulatory Studies

YARS Vol. 18(32)

Cheshire 4-H Presents 2025 Demonstrtion Info, Extension

UNH Cooperative Extension

No abstract provided.

Chromatographic And Electrophoretic Analysis Of Lignin-Derived Monomers And Dimers: Extraction Method Development And Evaluation Of Cyclodextrins For Recovery, Anjam Sadik

Theses and Dissertations--Chemistry

Biorefineries play a vital role in reducing dependence on fossil fuels and addressing global warming concerns. Unfortunately, investment in biorefineries remains limited due to economic sustainability concerns. One approach to enhance the economic viability of biorefineries is by fully utilizing the potential of feedstocks, particularly lignocellulosic biomass, which is commonly used in these processes. Traditional processing methods often alter the lignin portion of biomass, making it unsuitable for further utilization. However, when retained in its native form, lignin can serve as a valuable source of chemicals that contribute to the economic sustainability of biorefineries.

The lignin-first approach, which removes lignin …

Catalytic Deoxygenation Of Oleaginous Biomass To Renewable Diesel And Sustainable Aviation Fuel Via Decarboxylation/Decarbonylation, Chukwudalu Great Umenweke

Theses and Dissertations--Chemistry

Several technologies have been developed to produce hydrocarbon biofuels – renewable diesel (RD) and sustainable aviation fuel (SAF) – from fats, oils, and greases (FOG), with the hydroprocessing of esters and fatty acids (HEFA) representing one of the most mature pathways. In its current form, HEFA is mainly reliant on the hydrodeoxygenation (HDO) reaction, which has several drawbacks since HDO requires large amounts and pressures of hydrogen, feedstocks of high purity and cost, as well as problematic sulfided catalysts that risk contaminating the biofuel product with sulfur. A process based on decarboxylation/decarbonylation (deCO_x) offers an attractive alternative to …

Insights Into Factors Influencing Radical Coupling Chemistry Of Monolignols During Lignification And Induced Changes In Plant Secondary Metabolism, Rachel Poornima Sutherland

Theses and Dissertations--Chemistry

Lignin is a complex aromatic biopolymer and an important constituent in plant cell walls. The process of lignin biosynthesis, known as lignification, is poorly understood and challenging to study but has important implications in a variety of fields including sustainable energy, bioengineering, and materials science and is therefore of interest to pursue. In the final stage of lignification, H-, G-, and S-monolignols are oxidized by laccase and peroxidase enzymes to generate radical species that couple to form dimers and further oligomeric species to ultimately produce the lignin polymer. Biomimetic lignin model systems utilize in vitro oxidative coupling reactions as an …