Digital Commons Network^™

Enzymatic Characterization Of Bacterial Enzymes And Inhibitors As Potential Antibiotics With New Mechanisms Of Action, Emma Helene Kelley

Dissertations

Bacteria have become increasingly resistant to antibiotics, therefore there is an urgent need for new drug classes of antibiotics to help fight antibiotic infections. To this end, our research is focused on inhibitors of dizinc metalloenzymes N-succinyl-L,L-diaminopimelic acid desuccinylase (DapE), an enzyme in the lysine biosynthesis pathway, N-acetyl-L-ornithine deacetylase enzyme (ArgE), an enzyme in the arginine biosynthesis pathway, and sodium-dependent NADH: ubiquinone oxidoreductase (Na+-NQR) enzyme, a respiratory complex enzyme as promising drug targets. DapE, ArgE, and Na+-NQR and are only present in bacteria, including ESKAPE pathogens that can cause potentially deadly infections, thus inhibitors of DapE, ArgE, and Na+-NQR offer …

A Spatial Modeling Framework For Identifying Multidimensional Risk Factors Of Colorectal Cancer, Johnna K. Berryhill

Student Theses and Dissertations

Colorectal cancer (CRC) is one of the most common and preventable cancers, yet significant disparities in screening, incidence, and late-stage diagnosis persist across different geographic and socioeconomic contexts. This thesis presents a spatial modeling framework for identifying multidimensional risk factors associated with CRC outcomes across various geographic scales. Using county- and census-tract-level data from national and state sources, the study integrates demographic, socioeconomic, environmental, built environment, and behavioral predictors to analyze geographic variability in CRC risk factors. Advanced spatial modeling techniques, including Geographically Weighted Regression (GWR) and Geographically Weighted Random Forest (GW-RF), are employed to capture spatial heterogeneity in these …

Re: Comment Letter For The Final Butte Reduction Works (Brw) Smelter Area Waste Remediation And Contaminated Groundwater Hydraulic Control Site Air Monitoring Quality Assurance Project Plan (Qapp) For Interim Demolition Activities (Dated May 19, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Draft Final Butte Reduction Works (Brw) Air Monitoring For Interim Demolition Activities – Phase I Data Summary Report (Dated March 21, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A New Model For Educational Program Assessments Using Automated Collective Concept Maps, Andrew R. Paullin

Master's Theses (2009 -)

This paper presents: Epistemological principles; the origins and theoretical foundations of concept maps; the current state of related works; the contributions, methods, results, and future road map of this research; and A New Model for Educational Program Assessments. An understanding that knowledge results from an evolution of cognitive structures enables a scientific approach to enhance the efficiency of learning. Building on prior works, this research provides a novel algorithm and tool to automatically create Collective Concept Maps from Individual Concept Maps by utilizing a dictionary, thesaurus, Natural Language Processing, Machine Learning / Artificial Intelligence, and domain expertise. Abstraction Filters enable …

Virtual Assistant For Pest Management, Viswanada Chakravarthy Karri

Master’s Dissertations

Effective pest identification and management are essential for ensuring agricultural productivity, especially in regions with limited expert access. This work proposes a virtual assistant based on a Retrieval-Augmented Generation (RAG) [1] framework to support pest management tasks. The system utilizes a multimodal dataset consisting of pest images and annotated textual interactions, adapted from the AgriLLaVA corpus [2]. The assistant combines retrieval mechanisms with generative language models to generate contextually grounded responses. It is designed for deployment on local hardware with limited computational resources, integrating open-source models for both retrieval and generation. Preliminary results suggest that this approach can provide accurate, …

Draft Final 2025 Residential Metals Abatement Program (Rmap) Quality Assurance Project Plan (Qapp) Annual Update (Non-Residential Parcels And Residential Daycares), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Human Gut Commensal Alistipes Timonensis Modulates The Host Lipidome And Delivers Anti-Inflammatory Outer Membrane Vesicles To Suppress Colitis In An Il10-Deficient Mouse Model, Ethan Older, Mary K. Mitchell, Andrew Campbell, Xiaoying Lian, Michael Madden, Yuzhen Wang, Lauren E. Van De Wal, Thelma Zaw, Brandon N. Vanderveen, Rodney Tatum, E. Angela Murphy, Yan-Hua Chen, Daping Fang, Melissa Ellermann, Jie Li

Faculty Publications

Correlative studies have linked human gut microbes to specific health conditions. Alistipes is one such microbial genus negatively linked to inflammatory bowel disease (IBD). However, the protective role of Alistipes in IBD is understudied, and the underlying molecular mechanisms remain unknown. In this study, colonization of Il10-deficient mice with Alistipes timonensis DSM 27924 delays colitis development. Colonization does not significantly alter the gut microbiome composition, but instead shifts the host plasma lipidome, increasing phosphatidic acids while decreasing triglycerides. Outer membrane vesicles (OMVs) derived from Alistipes are detected in the plasma of colonized mice, carrying potentially immunomodulatory metabolites into the …

Virtual Reality’S Impact On Tourist Attitudes In Islamic Religious Tourism: Exploring Emotional Attachment And Vr Presence, Eman Alkhalifah, Ramy Hammady, Mahmoud Abdelrahman, Alyaa Darwish, Ella Cranmer, Ons Al-Shamaileh, Aikaterini Bourazeri, Timothy Jung

All Works

This study explores the integration of immersive technologies, specifically virtual reality (VR), to enhance tourist experiences in the rapidly expanding religious tourism sector. Despite VR’s potential, limited research has examined its impact on religious tourism. This study addresses this gap by investigating the role of emotional attachment in influencing VR presence during pre-, on-site, and postexperiences of VR-mediated religious tourism. A quantitative survey was conducted with 201 respondents who participated in VR religious tourism activities. The empirical analysis, conducted using SPSS and AMOS structural equation modeling (SEM), assessed how VR-mediated religious tourism impacts VR presence and tourist attitudes before actual …

Re: Comment Letter For Butte Priority Soils Operable Unit (Bpsou) Superfund Operation And Maintenance (O&M) Request For Maintenance – Kelley Stormwater Channels (Dated April 22, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Effects Of Elevated Temperatures On Tooth Structure During Polymerization Of Composite Resin With A Variety Of Light Sources, Enas G. Yonis

Al-Bahir

This study investigated the impact of high temperatures on dental tissues during the polymerization of optical fillings using a diode laser and two types of pulsed and continuous LED devices. Three distinct light source units were employed: a laser diode, an LEDition, and a LED.B. Temperature increases were measured at a distance of 1 mm from the thermocouple to the tip of the device. To create an experimental model, we fixed the operational voltage of the polymerization device and maintained a 1 mm gap between the terminal and the thermocouple wire. Temperature readings and thermal background (TO) measurements were taken …

Incorporating Propensity Score Weighting And Nonresposne Adjustments Into Complex Survey Data With Survival Outcomes, Xinrui Shi

Theses and Dissertations

Propensity score weighting (PSW) plays a key role in minimizing confounding in observational research, especially when estimating treatment effects for time-to-event outcomes. However, its integration into survey data with complex design – particularly data with multiple stage sampling and censoring – remains underexplored. One significant challenge in such settings is the presence of nonresponse, which can introduce additional bias and complicate the use of standard weight adjustments. Moreover, there has been limited study on how PS weights can be effectively combined with nonresponse weighting adjustments in complex survey data that include survival outcomes. This dissertation aims to extend current methodologies …

Draft Final 2025 Residential Metals Abatement Program (Rmap) Quality Assurance Project Plan (Qapp) Annual Update (Residential Parcels), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Cannabis Concentrate Vaping Chemistry, Kaelas R. Munger, Killian M. Anreise, Robert M. Strongin

Chemistry Faculty Publications and Presentations

Background:

This review article addresses the vaping chemistry of manufactured cannabis concentrates—a topic that remains under-researched despite the widespread availability and growing popularity of these products. Given their current prevalence and the fact that many of the findings discussed herein are from early-stage investigations, further research is essential to fully assess the public health risks associated with concentrate use. The purpose of this article is to help begin to bridge this knowledge gap by outlining the technical challenges of studying cannabis concentrates and to present evidence-based data concerning toxicant exposures as a foundation for future investigations.

Methods:

A search of …

Comprehensive Insights Into The Cholesterol-Mediated Modulation Of Membrane Function Through Molecular Dynamics Simulations, Ehsaneh Khodadadi, Ehsan Khodadadi, Parth Chaturvedi, Mahmoud Moradi

Chemistry & Biochemistry Faculty Publications and Presentations

Cholesterol plays an essential role in biological membranes and is crucial for maintaining their stability and functionality. In addition to biological membranes, cholesterol is also used in various synthetic lipid-based structures such as liposomes, proteoliposomes, and nanodiscs. Cholesterol regulates membrane properties by influencing the density of lipids, phase separation into liquid-ordered (Lo) and liquid-disordered (Ld) areas, and stability of protein-membrane interactions. For planar bilayers, cholesterol thickens the membrane, decreases permeability, and brings lipids into well-ordered domains, thereby increasing membrane rigidity by condensing lipid packing, while maintaining lateral lipid mobility in disordered regions to preserve overall membrane fluidity. It modulates membrane …

Temporal Modeling And Forecasting Of Blood Glucose Dynamics In Individuals With Diabetes Mellitus, Mj Ruff

University Honors Theses

People living with Diabetes Mellitus face significant health risks, including an increased likelihood of heart disease, stroke, and fluctuations in blood glucose levels. The unpredictable nature of glucose levels can lead to dangerous conditions such as ketoacidosis and hypoglycemia. This study employs advanced time series analysis tools to forecast the glucose levels for an individual diagnosed with Type 1 Diabetes Mellitus.

Session 2: The Cases For Industry Self-Regulation And Government Regulation Of Ai, Boaz Ashkenazy, Kevin Bartholomew, Kevin De Liban, Christopher Yoo

SITIE Symposiums

In Session Two of the SITIE 2025 Symposium titled “The Cases for Industry Self-Regulation and Government Regulation of AI,” moderated by Seattle University Technology Ethics Initiative Director and Professor Onur Bakiner, the panelists discuss their perspectives and experiences with AI regulation. They share observations about the industry and delve into the topics of AI complexity, concerns around accountability, the shift to agentic AI, the current state of AI regulation, existing legal guardrails, and their outlook on AI regulation.

Session 1: Guidance From International Regulation Sources, Charlotte Tschider, Marie-Charlotte Roques-Bonnet

SITIE Symposiums

In Session One of the SITIE 2025 Symposium titled “Regulating Artificial Intelligence: From Where and When?”, Professor Mark Chinen moderated a panel featuring Professor Charlotte Tschider and Dr. Marie-Charlotte Roques-Bonnet. The discussion focused on international AI regulation, privacy, data governance, and the EU’s regulatory approach to AI oversight.

Leveraging Usage Of Ai In Education: Knowledge, Attitude And Behavioral Analysis On Students, Bipllab Roy, Purnendu Bikash Acharjee, Rohit Kumar Sharma, Ruptaheen Kramsapi, Shruti P

Northeast Journal of Complex Systems (NEJCS)

The paper explores the possible advantages and drawbacks of artificial intelligence (AI) on sustainability, with an emphasis on using AI to positively achieve SDGs. The study finds a significant vacuum in the literature on the association between knowledge, attitudes, and behaviors towards the use of AI tools and techniques in education and demographic characteristics (sex, age, education level, area of study, and city of origin). The purpose of this research is to close this knowledge gap and advance our understanding of how these demographic factors affect the integration of AI in educational environments. The study specifically aims to comprehend how …

Quantum Machine Learning For Battery Health And Thermal Risk Prediction, Alexander Mutiso Mutua, Ruairí De Fréin

SAML-25 Workshop on Statistical and Machine Learning

The rapid growth of connected Electric Vehicles (EV) as part of modern Intelligent Transport Systems (ITS) motivates the need for real-time management of Lithium-ion (Li-ion) battery health and thermal risks. Li-ion batteries, although widely used, are prone to degradation and thermal runaway, posing significant challenges for safe and efficient EV operation. We present a Quantum Machine Learning (QML) and Agent-Based Model (ABM) that simulates and predicts EV behaviour under various battery degradation con- ditions. We use a Variational Quantum Neural Network (VQNN) trained on NASA battery datasets to classify EVs into four cate- gories: healthy, degraded for fixed chargers, degraded …

Tellings Of The Pacific Ocean: A Landscape-Based Approach For Multispecies Design And Hci, Maliheh Ghajargar

Engineering Faculty Articles and Research

Environmental disturbances induced by climate change have caused significant changes in our ecosystems and are threatening the health of our environments. As a response to this issue, a growing body of work has emerged in HCI and design, which seeks to foreground more-than-human stories in support of making more sustainable and just futures. This research contributes to this broad agenda by probing graphic novels as a multispecies storytelling method for design and HCI. Combining ideas from Anna Tsing’s adventures of landscape and from HCI and design’s use of sequential art (e.g., storyboards), we use landscape as the main protagonist of …

Lighting Up The Cell: Developing A Luminescent Lanthanide Probe For Detecting Rnas, Jonathan Savell

Honors Projects

An anion detecting luminescent probe, Tb:DO2A-Cs124, was repurposed for use in RNA imaging. Potential RNA aptamers were identified for the molecule using Capture-SELEX and MinION sequencing. Fluorimetry data revealed these aptamers did not allow for the probe to luminesce in the presence of target RNAs due to adenosine monophosphate’s ability to quench the emission signal.

Colonization-Persistence Trade-Offs In The Human Microbiome, Liam F. Nokes

Environmental Studies Senior Theses

Understanding how diverse microbial taxa coexist in the human body without competitively excluding one another remains a key challenge in microbiome ecology. One proposed explanation is the colonization-persistence trade-off, where species with high colonization ability are poor persisters, and vice versa. We test for this trade-off across human associated microbial communities among many individuals and in multiple body sites using a large-scale participant-level meta-analysis of longitudinal microbiome datasets curated from the MGnify database. We applied island biogeography-based models to calculate effective colonization and persistence rates for microbial families and genera across 606 individuals over twenty-six studies. Regression of the log-transformed …

Final 2025 Residential Metals Abatement Program (Rmap) Rock Creek Cattle Company Borrow Submittal #1, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Forecasting Influenza Rates Using Machine Learning: A Study Of Chatgpt's Predictive Accuracy, Sara Saleh

University Honors Theses

This study evaluates ChatGPT's ability to forecast influenza rates, such as the number of flu cases, hospitalizations, and death during peak season periods using CDC data, and comparing forecasts against actual results to calculate statistical accuracy and consistency. Influenza forecasting is essential for public health planning, but traditional methods may not always provide timely or accurate predictions. In this research study, ChatGPT was utilized to predict the influenza rates for the following week based on the previous week's data obtained from the FluView surveillance system. The predicted rates were compared to the actual influenza rates to assess the model's overall …

Development And Photophysical Characterization Of Bioinspired Materials, Qaisar Maqbool

USF Tampa Graduate Theses and Dissertations

Porphyrins are versatile aromatic macrocycles with unique photophysical properties that make them attractive for applications in light harvesting, photocatalysis, and sustainable energy conversion. Incorporating porphyrins into metal-organic frameworks (MOFs) offers a unique opportunity to modulate their photophysical behavior through spatial confinement and host–guest interactions. This thesis explores how structural modifications influence porphyrin excited-state behavior through a multi-stage investigation. The work begins by comparing the photophysical properties of two cationic porphyrins: tetra(N-methylpyridyl) porphyrin(TMPyP) and tetra(4-N,N,N-trimethylanilinium) porphyrin(4TANP). While TMPyP exhibits significant singlet–charge transfer (S₁–CT) state mixing due to charge delocalization onto peripheral pyridinium groups, 4TANP lacks comparable behavior. The localized nature of …

Enhancing Dermatological Skin Lesion Classification With Multi-Modal Attention-Based Models And Explainability, Conan Oreilly

SAML-25 Workshop on Statistical and Machine Learning

Accurate classification of skin lesions is critical for early detection of melanoma and other malignancies, particularly in resource-limited settings. This study presents a novel multi-modal machine learning framework that integrates dermoscopic images and structured clinical metadata to improve diagnostic performance. Leveraging the PAD-UFES-20 dataset, which includes over 2,000 smartphonecaptured lesion images and associated patient metadata, we benchmark a series of unimodal and multimodal models. Our results demonstrate that modality attention fusion (MAF) applied to a frozen SwinV2-Tiny vision transformer and metadata multi-layer perceptron (MLP), augmented with focal loss, yields a state-ofthe- art weighted F1-score of 0.84 and balanced accuracy of …

Intention To Commute By Public Transportation And/Or By Foot: Findings From A Pls Structural Equation Model, Simona Balzano, Houyem Demni,, Edoardo Pascucci,, Luisa Natale, Giuseppe Cappelli, Sofia Nardoianni, Giovanni C. Porzio

SAML-25 Workshop on Statistical and Machine Learning

Sustainable mobility stands at the forefront of contemporary discussions, driven by the clear imperative to transition towards more environmentally friendly transportation and patterns. This shift is widely recognized as a crucial opportunity to address the challenges and inherent dangers posed by climate change. It is then crucial to introduce attitudes to encourage voluntary behavioral changes toward different sustainable solutions. In this perspective, to foster a future where sustainable personal mobility options are widely embraced and integrated, it is crucial to comprehend the inclination of younger generations to use them. For this reason, a survey on the use of sustainable mobility …

Ai-Driven Personalized Radiotherapy Planning, Nithin Venkatesh, Marco Pota, Maged Shaban

SAML-25 Workshop on Statistical and Machine Learning

The planning of radiation oncology treatment is made more dynamic and individualized by Artificial Intelligence (AI). Routine radiotherapy practice applies normative procedures indifferent to patient-specific parameters such as tumor volume, patient anatomy, and heterogeneity in the delineation of treatment response. Inadequate and over-radiation treatment is the most prevalent outcome. Further, with the inclusion of AI, it can facilitate enhancing the healthcare industry through optimizing radiotherapy using an array of patient information such as molecular profiles and imaging data. The product offers an end-to-end AI-driven solution to all aspects of radiotherapy, from initial consultation (diagnosis) to adaptive treatment planning. All the …

A Machine Learning Approach To Improve Prediction In Chemical Exposure Risk Assessment, Michele Marro, Cédric Koller, Hasnaa Chettou, David Vernez

SAML-25 Workshop on Statistical and Machine Learning

Exposure models play a crucial role in predicting chemical exposure in workplaces, offering an essential alternative to measurements, which are resource-intensive and time-consuming and sometimes not possible. Despite their widespread use and continuous development, significant challenges persist, including variability in predictions, limited model updates, and difficulties in accessing the required input data. In this study, we investigate how modern machine learning techniques can contribute to the improvement of exposure models by addressing these limitations. To overcome the frequent lack of data, we explore the use of synthetic datasets generated through existing exposure models. This approach allows for the study of …