Physical Sciences and Mathematics Commons^™

Context Engineering For Ai Agents In Open-Source Software, Seyedmoein Mohsenimofidi, Matthias Galster, Christoph Treude, Sebastian Baltes

Research Collection School Of Computing and Information Systems

GenAI-based coding assistants have disrupted software development. The next generation of these tools is agent-based, operating with more autonomy and potentially without human oversight. Like human developers, AI agents require contextual information to develop solutions that are in line with the standards, policies, and workflows of the software projects they operate in. Vendors of popular agentic tools (e.g., Claude Code) recommend maintaining version-controlled Markdown files that describe aspects such as the project structure, code style, or building and testing. The content of these files is then automatically added to each prompt. Recently, AGENTS.md has emerged as a potential standard that …

Dendrimer Nanogels With Built-In Free Radical Scavenging Enable Efficient Topical Delivery Of A Hydrophilic Antioxidant To Restore Lens Redox Balance For Cataract Treatment, Lin Qi, Huari Kou, Anna Chernatynskaya, Da Huang, Vimalin Jeyalatha Mani, Humeyra Karacal, Nuran Ercal, Hu Yang

Chemistry Faculty Research & Creative Works

Cataract is a leading cause of vision impairment worldwide and are primarily caused by oxidative stress that damages and aggregates lens proteins, leading to lens opacification. However, the eye's anatomical barriers limit the penetration and bioavailability of antioxidant therapies. To address this challenge, a dendrimer-based nanogel with a built-in reactive oxygen species (ROS)-scavenging capability developed by us was employed to deliver the antioxidant N-acetylcysteine (NAC) to the lens. NAC was loaded into a generation-5 PEGylated poly(amidoamine) dendrimer (G5-PEG-TK, termed the GPT) nanogel. The resulting NAC-GPT was characterized for its ROS-scavenging activity, bioavailability, and corneal permeability. The efficacy of NAC-GPT was …

Hypersiniel: Guaranteed Output Delivery Comes (Almost) Free In Private Delegation Of Zksnarks, Yunbo Yang, Yuejia Cheng, Junkai Liang, Kailun Wang, Xuanming Liu, Xiaoguo Li, Jianfei Sun, Jiachen Shen, Xiaolei Dong, Zhenfu Cao, Meng Hao, Guomin Yang, Deng, Robert H., Kui Ren

Research Collection School Of Computing and Information Systems

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive that enables a prover to convince a verifier that something is true without leaking the private witness.Current zkSNARKs face significant computational costs in generating proofs, which restricts their use in areas like private payments, confidential smart contracts, and anonymous credentials. Private delegation offers a practical solution by outsourcing the heavy computation to powerful external workers without leaking any private information. In this work, we propose HyperSiniel, an efficient private delegation framework for general zkSNARKs that achieves a new feature called guaranteed output delivery (GOD). HyperSiniel is designed to …

Distributional Vision-Language Alignment By Cauchy-Schwarz Divergence, Wenzhe Yin, Zehao Xiao, Pan Zhou, Shujian Yu, Jiayi Shen, Jan-Jakob Sonke, Stratis Gavves

Research Collection School Of Computing and Information Systems

Vision-language alignment is crucial for various downstream tasks such as cross-modal generation and retrieval. Previous multimodal approaches like CLIP utilize InfoNCE to maximize mutual information, primarily aligning pairwise samples across modalities while overlooking distributional differences. In addition, InfoNCE has inherent conflict in terms of alignment and uniformity in multimodality, leading to suboptimal alignment with modality gaps. To overcome the limitations, we propose CS-Aligner, a novel framework that performs distributional vision-language alignment by integrating Cauchy-Schwarz (CS) divergence with mutual information. CS-Aligner captures both the global distribution information of each modality and the pairwise semantic relationships. We find that the CS divergence …

Altered Pruning In A Generative Neural Network, Sara Momen

Honors Theses

This study examines whether altered pruning in a generative neural network leads to more restricted or repetitive outputs, using Autism Spectrum Disorder (ASD) as a cautious computational analogy rather than as a biological equivalence. A compact denoising diffusion probabilistic model (DDPM) with a U-Net backbone was trained on CIFAR-10, and pruning percentage was treated as the primary structural variable. Instead of relying on a single assumed baseline, the final implemented study evaluated 0%, 10%, 15%, 20%, 35%, and 50% pruning under controlled conditions: the same dataset, the same epoch budget, the same random seed, and 1,000 generated samples per condition. …

Ai-Powered Knowledge Management Systems Across Industries: A Systematic Review Of Applications, Implementation Barriers, And Ethical Challenges, Edmund Evangelista, Ghazala Rizvi

All Works

This systematic literature review (SLR) evaluates the existing literature on the benefits, implementation challenges, and ethical concerns associated with Artificial Intelligence (AI)-driven Knowledge Management Systems (KMS) across industries. The SLR followed PRISMA guidelines to identify studies from Scopus, Web of Science, JSTOR, and Google Scholar, using inclusion and exclusion criteria. Critical Appraisal Skills Programme (CASP) checklists were used to assess methodological quality and risk of bias in the included studies, and a structured narrative synthesis was employed to synthesize the findings. The review of 21 articles reveals benefits like improved knowledge capture and creation, storage, retrieval, personalization, and efficient dissemination, …

Preserving The Past, Innovating The Future: Integrating Metaverse, Blockchain, And Generative Ai For Tourism And Cultural Heritage Preservation, Mousa Al-Kfairy, Amna Ahmed Aaber Ahmed Alqubaisi, Omar Alfandi

All Works

The preservation and accessibility of cultural heritage are seriously threatened by urbanization, mass tourism, neglect, and natural disasters. This study utilizes cutting-edge technologies to address these issues by presenting a novel framework that combines generative AI, blockchain, and the metaverse. The Metaverse provides immersive virtual experiences that lessen the physical strain on delicate locations by enabling the creation of lifelike digital replicas of cultural heritage sites. By creating immutable records, blockchain technology ensures the legitimacy, ownership, and traceability of digital assets, enabling open access and NFT monetization. Rebuilding lost or damaged artifacts, creating lifelike 3D models, and customizing user interactions …

Trash Bot!, Owen Hoffman , ‘26, Ryder Maston , ‘26, Jack Nicholson , ‘26

Senior Theses, Projects, and Awards

Trash Bot! is the prototype of a smart and mobile waste receptacle for Swarthmore’s waste management system. With Swarthmore College committing to embed zero waste into campus culture and achieve a 90% diversion rate by 2035, flexible waste systems must be developed and improved. Trash Bot! seeks to improve the diversion rate and sort accuracy on campus by reducing the human error present in the current waste sorting process. Trash Bot! was also designed to seamlessly integrate with a classroom environment, maintaining safety standards and avoiding collisions. Trash Bot! uses computer vision coupled with a trained classifier algorithm to achieve …

Monitoring Terrestrial Ecosystem Productivity Using Hyperspectral Satellite Data, Serge Tuyambaze

School of Natural Resources: Dissertations, Theses, and Student Research

Accurate estimation of terrestrial Gross Primary Productivity (GPP) is critical for quantifying global carbon sequestration and understanding the terrestrial carbon cycle. While eddy covariance (EC) towers provide standard flux measurements, upscaling these measurements to continuous global coverage remains challenging due to the sparse distribution of flux towers and their small footprints. Remote sensing (RS), especially coupled with eddy covariance data, has been used to estimate GPP at the global scale. Different RS derived productivity models have been developed, including vegetation indices, light use efficiency (LUE) models, solar-induced fluorescence (SIF), dynamic global vegetation models (DGVM), and machine learning. One widely adapted …

Impact Of In Situ Observations From Three Torus Cases On Model Analyses And Forecasts Of Severe Convection, Robert M. Szot

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

The quality of forecasts of severe deep convection in high-resolution numerical weather prediction is dependent on the representativeness of the model initial conditions. This representativeness may be negatively impacted by limited observation availability and by the presence of mesoscale heterogeneities that were not detected by conventional observations assimilated into convection-allowing models. By assimilating storm-scale observations from the Targeted Observation by Radars and Uncrewed Aircraft Systems (UAS) of Supercells (TORUS) campaign into an ensemble styled after the Warn-on-Forecast System, this study aims to investigate if data from field work platforms can improve the quality of initial conditions in the ensemble, potentially …

Factors Associated With Lapses In Care Among People Living With Hiv In South Carolina, Xueying Yang Ph.D., Fanghui Shi, Shujie Chen, Gavi Samuel, Bankole Olatosi Ph.D., Sharon Weissman, Xiaoming Li Ph.D., Jiajia Zhang Ph.D.

Faculty Publications

Utilizing statewide electronic health records (EHR) data, this study aims to assess the factors determining the occurrence of lapses in HIV care among people with HIV (PWH) in South Carolina (SC). All adult (≥ 18 years old) PWH who were diagnosed with HIV between 2006 and 2018 with at least two HIV care encounters and at least 1-year follow-up record were included in the analysis. The outcome, a lapse in care, was defined as a repeated measure of HIV care encounter that occurs over a year following the previous visit. Generalized Estimation Equation models were employed. The study cohort had …

Exclusive Neutral Pion Electroproduction Cross Section Measurements With A Neutral Particle Spectrometer, Mitchell R. Kerver

Physics Theses & Dissertations

Deep Virtual Compton Scattering (DVCS), the exclusive electron-proton scattering process ep →e′p′γ, provides access to generalized parton distributions (GPDs), which correlate informa tion about the longitudinal momentum and transverse spatial structure of quarks inside the nucleon. Experiment E12-13-010 in Hall C at Jefferson Lab was designed to take high-precision measure ments of the DVCS cross section over an extended kinematic range using the newly commis sioned Neutral Particle Spectrometer (NPS). The NPS features a high-resolution electromagnetic calorimeter and a streaming data acquisition system optimized for operation at high luminosities. This thesis presents the detector and analysis work carried out to …

Behavioral, System, And Informational Cyberattacks: A Human-In-The-Loop Driving Simulator Experiment, Samuel Petkac

Psychology Theses & Dissertations

Advanced technologies such as sensors and AI/ML algorithms have enabled increasing levels of automated driving system that detects, responds, and even predicts changes in a driving environment supported by wireless connectivity to nearby vehicles and infrastructure. Such connected and automated vehicles (CAVs) can be particularly vulnerable to cyberattacks targeting not only infotainment systems but also firmware and other applications, critically compromising driver safety. As we anticipate a “mixed” traffic where vehicles with various levels of automated technologies share the road for the foreseeable future, it is urgent to systematically examine types of possible cyberattacks and control human behaviors in such …

Downstream Effects Of Post Aerobic Digestion And Divalent Cation Treatment: Dewaterability, Phosphorus Mitigation, And Process Odors, Maya Marisol Quijano Garcia

Civil & Environmental Engineering Theses & Dissertations

This study evaluated post-aerobic digestion (PAD) with aeration, mixing, and divalent cation addition to improve phosphorus capture, dewaterability, and odor control in thermal hydrolysis process (THP)–treated anaerobic digestate at the Hampton Roads Sanitation District’s Atlantic Treatment Plant. A three-day PAD process was operated under constant air flow (5 LPM) and dissolved oxygen (DO)-setpoint (0.2 mg/L) aeration conditions with Ca(OH)₂ or Mg(OH)₂ dosing. Aeration and mixing alone increased polymer demand by 14–46 % relative to untreated influent, indicating enhanced extracellular polymeric substance release. Chemical conditioning partially mitigated this increase but did not restore polymer demand to baseline levels. Dewatered cake total …

Quantifying Nutrient Fluxes Across The Sediment-Water Interface In The Lafayette River Estuary, Adriana E. Amrhein

OES Theses and Dissertations

The Lafayette River, a shallow, eutrophic tributary of the Chesapeake Bay, experiences seasonal harmful algal blooms (HABs). While management efforts focus on reducing external nutrient inputs, internal loading from benthic sediments remains poorly constrained. This study quantifies spatial and seasonal variability in nutrient and radium isotope fluxes across the sediment–water interface at three sites where HABs are known to initiate and represent contrasting sediment textures and hydrodynamic conditions. Sediment cores and porewater samples were collected in summer 2023 and winter 2024 to measure grain size, porosity, dissolved nutrients (NH₄⁺, NOₓ⁻, PO₄³⁻), and radionuclide activities (²²⁴Ra and ²²⁸Th). Radium isotope disequilibrium …

Biocrude From Organic Waste And Its Conversion To Hard Carbon: Experimental And Modeling Study, Isamu Umeda

Civil & Environmental Engineering Theses & Dissertations

This study establishes a technical and theoretical foundation for the efficient conversion of organic waste into biocrude and high-value carbon materials, aiming to facilitate the industrialization of hydrothermal and solvothermal liquefaction. The dissertation research is structured as follows:

Chapter 2 developed a novel chemical kinetic model for the HTL of corn stover based on elemental balances (C, H, N, and O). By incorporating temperature, residence time, solid loading as an independent variable, the model successfully predicted product yields and properties, revealing that there was non-pseudo-first-order reaction pathways in the conversion of water soluble organics in aqueous phase (AP) to hydrochar. …

A Study Of Short-Range Correlated Pair Formation Mechanisms, Noah S. Swan

Physics Theses & Dissertations

Short-Range Correlations (SRCs) refers to pairs of nucleons that are temporary high density fluctuations with high relative momenta and lower center-of-mass momenta com pared to the nuclear Fermi momentum (kF). SRCs account for 20–25% of the nucleons in medium to heavy nuclei, make up essentially all nucleons with momentum greater than kF, and contribute most of the kinetic energy carried by nucleons in nuclei.

The existing semi-inclusive and exclusive measurements only cover a handful of light nu clei or heavy elements. This does not allow for a systematic study of the dependence of SRC pairs on nuclear mass and proton-neutron …

Inferring The Breakdown Scales Of The Chiral Expansions For GA And MN, Andreas Ekström, Daniel R. Phillips, Lucas Platter, Matthias Schindler

Faculty Publications

We apply Bayesian inference to the order-by-order chiral perturbation theory (χPT) expansions for the axial-vector coupling constant g_A and the nucleon mass m_N, and thereby infer the scales at which χPT breaks down for these two observables. Using a pointwise Bayesian analysis, we find that the inferred breakdown scales are notably different for the two observables. For the chiral expansion of g_A, we obtain 251⁺²⁰₋₅₀ MeV and 211⁺²⁰₋₃₀ MeV using two distinct sets of low-energy constants, while for the chiral expansion of m_N we infer a significantly …

The Psychology Behind Ai-Generated Phishing And Social Engineering Attacks, A’Shya Reynolds

School of Cybersecurity Master's Level Projects and Papers

Cybercrime has evolved significantly with the integration of artificial intelligence (AI), transforming traditional phishing and social engineering attacks into highly sophisticated and personalized threats. While early phishing attempts relied on generic messaging and low success rates, modern AI-driven attacks leverage advanced data analytics, natural language processing, and behavioral prediction to manipulate victims more effectively.

This research examines how cybercriminals utilize AI to enhance psychological manipulation techniques in phishing and social engineering attacks, increasing victim susceptibility. Drawing from interdisciplinary literature in cybersecurity and psychology, this study explores key psychological mechanisms, including cognitive biases, emotional triggers, and decision-making processes that influence victim …

Directory Of Landscape Professionals Trained In Ecological Landscaping For Water Quality Protection, Julia Peterson

UNH Cooperative Extension

The individuals and businesses listed have completed UNH Cooperative Extension training programs for professionals as indicated, and have agreed to be listed in the directory. Individuals looking for related products or services are encouraged to contact one or more of the professionals listed in your area.

Observations Of An Oscillatory Mechanochemical Reaction Between Tetrathiafulvalene And Chloranilic Acid, Alastair Deans

Physics Theses & Dissertations

Mechanochemistry is the study of chemical reactions driven by the input of mechanical en ergy in addition to thermal activation. Mechanochemical reactions from powders are carried out by manual grinding or milling using various types of ball mills, or in twin extruders. While mechanochemistry has great potential affording economically and environmentally advantageous “green” synthetic methods, a drawback is that its chemical mechanisms are not well understood. One example of such a reaction currently under study involves tetrathiafulvalene, an organic elec tron donor with two polymorphs (orange and brown), and chloranilic acid, an electron acceptor. Previous results show that neat grinding …

Optimization Of Niobium Film For Particle Accelerators And Quantum Applications, Bektur Abdisatarov

Electrical & Computer Engineering Theses & Dissertations

Niobium (Nb) films play a central role in superconducting technologies used in particle accelerators and superconducting quantum circuits. Optimizing the physical properties of Nb films is therefore critical for improving both radiofrequency (RF) performance in superconducting radiofrequency (SRF) cavities and coherence in superconducting qubits. This thesis investigates the relationship between Nb film microstructure, impurity content, and electromagnetic response across these two application domains.

For particle accelerator applications, we studied Nb films deposited using high-power impulse magnetron sputtering (HiPIMS) with DC bias onto a 1.3 GHz elliptical SRF cavity. Nb film cavities exhibit a pronounced medium-field Q-slope, limiting their achievable accelerating …

Radiation Protection Factor Research: The Keystone For Conventional-Nuclear Integration (Cni), Andrew W. Decker

Faculty Publications

This article briefly describes Defense Threat Reduction Agency (DTRA) vehicle Radiation Protection Factor (RPF) research and explains its critical role in enabling future Operations in a Nuclear Environment (ONE) and Conventional-Nuclear Integration (CNI) on behalf of the US Department of War (DoW).1 As such, the background and practical utility of RPF values is discussed, as well as the justification for renewed Army and DoW investment into RPF research to enhance Joint military planning, survivability, and lethality on tomorrow’s nuclear battlefields. Advances in DTRA RPF research directly strengthen US strategic and extended deterrence efforts and support all Agencies and Departments responsible …

Freedom Readers And Sustainable Development Goal 4: Advancing Literacy In Low-Income Communities Of South Carolina, Madison Hayes

Goal 4: Quality Education

No abstract provided.

Generative Ai In Enterprises: Optimizing Applications With Large Language Models, Donghao Huang

Dissertations and Theses Collection (Open Access)

This dissertation investigates how to deploy Large Language Models (LLMs) effectively in enterprise settings, where accuracy, reliability, cost, privacy, and operational constraints often matter more than benchmark performance alone. Drawing on seventeen peer-reviewed publications (eleven published and six accepted for publication), the work develops and validates optimization strategies across three connected themes: retrieval-augmented generation (RAG), agentic AI for workflow automation, and deployment guidelines for real-world enterprise environments.

First, we study RAG optimization through systematic evaluation of open and proprietary models, highlighting conditions under which efficient open-weight models can match or exceed proprietary alternatives. To address a pervasive failure mode in …

Explainable Artificial Intelligence In The Image Domain And Its Applications To The Medical Field, Mirtha Lucas

Theses and Dissertations from DePaul University

This dissertation investigates the development of Explainable Artificial Intelligence (XAI) methods for deep learning models in the image domain, with a particular focus on medical imaging applications. Although neural networks achieve high predictive performance, their lack of interpretability limits their adoption in critical domains such as healthcare, where transparency and trust are essential. This work addresses this challenge by proposing novel approaches that improve the interpretability and reliability of model predictions.   A primary contribution is the introduction of Riemann–Stieltjes Integrated Grad-CAM (RSI Grad-CAM), a gradient-based attribution method that generates more relevant and spatially localized saliency maps. The method is evaluated …

Multiple Variable Regression Assignment, Sam Loyd

Distinguished Student Scholarship Collection

This paper applies multiple linear regression analysis to examine whether life outlook and sociability predict happiness. Using a dataset of 38 observations, the study employs IBM SPSS to conduct exploratory data analysis, assess regression assumptions, and evaluate model validity. Key assumptions—including linearity, homoscedasticity, independence of residuals, multicollinearity, normality, and the presence of influential outliers—are systematically examined using statistical tests and visual diagnostics. While some deviations from normality and potential nonlinear patterns are identified, the analysis proceeds based on sample size considerations and overall assumption adequacy. Results indicate that the regression model is not statistically significant and explains only a small …

Synthesis Of Piperidine Heterocycles With Specific Functional Groups Via Sn2 Reactions, Teyanna Monroe

Honors Theses

Piperidine is a heavily utilized nitrogen containing heterocycle found in numerous pharmaceutical agents, solidifying its importance as a building block in drug development. The focus of this research is to investigate different mechanisms of action for adding and replacing various functional groups utilizing readily available lab materials. These findings would lead to determining the overall influence of substitution patterns and functional groups have on stereochemistry, reactivity, and overall conformation of the piperidine ring. The synthetic approach involves the formation of 3-bromo-5-methoxy-tosylpiperidine intermediate through acid promoted cyclization, followed by nucleophilic substitution reactions to introduce various functional groups. Reaction progress and product …

Implementation And Costs Of A Food Insecurity Resource Navigation Program For Primary Care Patients With Diabetes And Hypertension In South Carolina, Deeksha Gupta, Darin Thomas, Stella Coker Watson Self Ph.D., Ms, Edward A. Frongillo Jr. Ph.D., Alain H. Litwin, Joseph A. Ewing, Lynnette Ramos-Gonzalez, Lynnette Ramos-Gonzalez

Faculty Publications

Objective

To examine food insecurity resource navigation program costs and how navigation intensity relates to clinical outcomes, healthcare costs, and quality of life (QOL) for diabetes and/or hypertension patients.

Methods

This retrospective study included patients receiving resource navigation (July 12, 2021-December 31, 2022 with twelve-month follow-up) across three primary care practices in South Carolina's largest health system. Participants were 18+ years old (from electronic medical records/Epic), had food insecurity (from Hunger Vital Sign™), and diabetes and/or hypertension (from Epic registries). Matched controls came from food insecurity screening-only practices. Patients in each group (n= 219) had diabetes (9.13%), hypertension …

Math 242: Elements Of Probability And Statistics (Syllabus), Ahmad Almomani Ph.D.

School of Arts & Sciences

This syllabus was developed by SUNY Geneseo Professor Ahmad Almomani during the spring 2026 semester.

Course Objectives:

Upon successful completion of Math 242, R/Elements of Probability and Statistics, a student will be able to: 

• Organize, present and interpret statistical data, both numerically and graphically; 
• Use various methods to compute the probabilities of events; 
• Analyze and interpret statistical data using appropriate probability distributions, e.g. binomial and normal. 
• Apply central limit theorem to describe inferences; 
• Construct and interpret confidence intervals to estimate means, standard deviations and proportions for populations; 
• Perform parameter testing techniques, including single and multi-sample tests for means, standard deviations …