Physical Sciences and Mathematics Commons^™

Clinical Utility Of An Fda-Authorized Artificial Intelligence Imaging Platform In Interstitial Lung Disease Diagnosis, Arjun Prakash Tambe, Ryan Boente, Gautam George, Fayez Kheir, Omid Tahamtani Omran, Kavitha Selvan

Division of Pulmonary, Allergy, and Critical Care Medicine Faculty Papers

Background/Objectives: The diagnosis of interstitial lung disease (ILD) is challenging and frequently delayed. Clinically accessible and minimally invasive diagnostic tools are needed to expedite the diagnosis of ILD while minimizing risk to patients. Fibresolve is an imaging artificial intelligence (AI) tool recently approved by the Food and Drug Administration (FDA) for use in ILD diagnosis and made available to clinicians. The objective of this study was to describe its utility in clinical practice. Methods: We conducted a prospective, observational study of patients across the United States (US) in whom Fibresolve was utilized during routine clinical practice between July 2024 and …

Ai-Driven Segmentation And Volumetric Response Modeling Of Liver Regions To Radiotherapy, Aashish Chandra Gupta

Dissertations and Theses (Open Access)

In liver-directed radiotherapy (RT), liver regions receiving higher doses typically undergo atrophy while contralateral/adjacent lower-dose regions may exhibit compensatory hypertrophy through regeneration of healthy tissue. Optimizing the RT plan to promote regional hypertrophy while minimizing the risk of developing atrophy has the potential to enhance post-RT liver function and long-term survivorship. However, current clinical practice largely relies on global liver dose-volume metrics during RT-planning, which may obscure favorable dose-response correlation and limit actionable guidance for clinicians. Therefore, we hypothesized that post-RT regional liver response is governed by a combination of region-specific dose-volume and patient clinical features, and that these responses …

Analysis Of Terpenes In Cannabis Flowers Using Gas Chromatography Via Headspace-Solid Phase Microextraction (Hs-Spme), Hannah I. Bergner

Forensic Science Master's Projects

As cannabis commercialization grows, rigorous profiling of cannabinoids, terpenes, and chemical contaminants is legally required for industry standardization and consumer safety. Terpenes are highly volatile components that dictate the unique aromatic profiles and therapeutic properties of cannabis via receptor pathways. This project focused on a gas chromatography-flame ionization detector/mass selective detector (GC-FID/MSD) combined with headspace-solid phase microextraction (HS-SPME) sampling to analyze terpenes present in four cannabis samples. Cannabis samples were tightly sealed in vials (10 mL) and heated to vaporize terpenes in the headspace above the samples, followed by the extraction of the vaporized terpenes using a polydimethylsiloxane (PDMS)-coated SPME …

Evaluating Machine Learning Models On Classification Of Novel Cyber Attacks In The Healthcare Domain, Promise Ehimen

Dissertations, Theses, and Projects

The increasing adoption of the Internet of Medical Things (IoMT) has improved healthcare delivery through connected medical devices while simultaneously expanding the cybersecurity risks facing healthcare organizations. Although machine learning based intrusion detection systems have demonstrated high detection accuracy, their ability to respond reliably to previously unseen cyberattacks remains uncertain. This study investigated how a Neural Network model and a Logistic Regression model classified novel cyberattacks within the IoMT environment. The Neural Network and Logistic Regression models were both trained and tested using a subset of the CICIoMT2024 benchmark dataset. The Neural Network achieved 99.82% test accuracy and a 0.94 …

Systematic Review Of The Institutionalization Of Service Learning In Higher Education, Wilmer Hernan Cruz Gutierrez

ASEAN Journal of Community Engagement

An increasing number of universities are integrating service-learning (SL) to fulfill their social mission. However, sustainable institutionalization of SL remains a persistent challenge. This study identifies and analyzes the factors, actors, and strategies that drive and inhibit SL institutionalization in higher education. Using the PRISMA 2020 guidelines, a systematic literature review analyzed 52 documents from seven academic databases (including WoS, Scopus, and ERIC). The findings were grouped into three sections: cultural (integration into institutional values/missions), process (articulation within teaching, research, and outreach), and structural dimensions (dedicated support entities). The results obtained reveal a reciprocal relationship where cultural alignment enables processual …

Bridging The Gap In Science Research: Preparing Students For College- Level Research In The Sciences, Victoria Helwig, Yaoguang Li

UConn Library Presentations

Many first-year students enter college unprepared to fully engage with scientific literature and academic library resources. Drawing on experiences from academic librarians working with STEM students, this session explores common gaps in science research skills, including navigating databases, identifying scholarly sources, and understanding the structure of scientific literature. Participants will be introduced to practical strategies and classroom-ready activities to better prepare students for college-level research. Discussion questions: What science research skills do students struggle with most when entering college? How can high school instruction better support these skills? Where can librarians and educators collaborate to support student success?

Mapping And Modeling Threat-Evoked Brain States After Early Life Adversity, Taylor W. Uselman

Biomedical Sciences ETDs

Early life adversity (ELA) increases lifelong neuropsychiatric vulnerability. Yet how ELA reorganizes brain-wide activity and circuit coordination across later experience remains unclear. This dissertation tests the hypothesis that ELA alters adult brain-wide activity and responses to threat through disrupted coordination among neural systems that regulate emotional experience, including prefrontal-limbic and monoaminergic systems. Longitudinal manganese-enhanced MRI of adult mice exposed to standard or fragmented early care, combined with computational processing and statistical modeling, quantified brain states before, during, and long after innate predator threat. These studies established that acute threat evokes large-scale, distributed brain activity that evolves over time. ELA potentiates …

Interpretable Case-Control Inference Through Log-Linear General Location Models, Zacharia Stuart

Mathematics & Statistics ETDs

This dissertation analyzes one of the few publicly available NFL injury datasets to study field type and non-contact lower-limb injuries. Field type is studied jointly with other risk factors to understand how these factors interact to affect injury risk. The data were gathered through a case-control sampling scheme, which limits direct inference on absolute injury probabilities. While not the most common approach for case-control data, this dissertation models the retrospective distribution directly through Log-Linear General Location Models (Log-Linear GLOMs). Through a log-linear structure placed on a log-odds-ratio reparameterization, the model provides directly interpretable marginal and interaction contributions to injury log-odds …

Cultural Traits May Replace Human Mobility Data In Forecasting Covid-19 Mortality: A Deep Learning Approach, Saif Abbas, Tamer Oraby, Michael G. Tyshenko, Samit Bhattacharyya

School of Mathematical & Statistical Sciences Faculty Publications

The COVID-19 pandemic highlighted the need for accurate epidemic forecasting to support public health decision-making. Most existing approaches depend heavily on human mobility data, while largely neglecting population behavior shaped by socio-cultural norms. In this study, we analyze daily COVID-19 mortality and Google mobility data from 72 countries during the first 130 d of the pandemic, a period characterized by high uncertainty and behavioral heterogeneity. In particular, we examine whether Hofstede’s country-level cultural dimensions can serve as latent behavioral forecasters of mortality in lieu of dynamic mobility indicators. Using 100 d for training and 30 d for forecasting, we employ …

Continuous 1:1 Sitter Observation Versus Standard Safety Interventions To Reduce Falls In Hospitalized Adults At Risk, Zainab Williams

Student Scholarly Projects

Practice Problem: Patient falls remain a significant patient safety concern among hospitalized adults, particularly those at high risk. Traditional fall-prevention strategies, including continuous 1:1 sitter observation, require evaluation to determine their effectiveness in reducing falls and fall-related injuries.

PICOT: In hospitalized adult patients at high risk for falls (P), does continuous 1:1 sitter observation (I), compared to standard safety interventions (C), reduce fall rates (O) as measured by reported falls per 1,000 patient days during hospitalization over 12 weeks (T)?

Evidence: Current evidence supports multifactorial fall-prevention programs that combine patient assessment, staff engagement, and proactive nursing interventions through intentional rounding. …

Comparative Analysis Of Traditional And Deep Learning Time Series Architectures For Influenza A Infectious Disease Forecasting, Edmund Fosu Agyemang, Hansapani Rodrigo, Vincent Agbenyeavu

School of Mathematical & Statistical Sciences Faculty Publications

Influenza A remains a major cause of respiratory mortality worldwide, motivating accurate forecasting to support timely preparedness and resource allocation. This study presents a comparative evaluation of two traditional seasonal time series baselines, ARIMA and Holt–Winters exponential smoothing (ETS), and six deep learning (DL) architectures (Simple RNN, LSTM, GRU, BiLSTM, BiGRU, and a Transformer) for forecasting monthly Influenza A case counts in the United States. Data from January 2009 to December 2023 were analyzed, using January 2009 to December 2022 for training and January 2023 to December 2023 for out-of-sample testing. Models were tuned using a validation split and assessed …

Healthcare Access And The Persistent Racial Disparities In Low Birth Weight, Zaheda A. Hussain, Yadanar Moe

DePaul Discoveries

Low birth weight (LBW), defined as less than 2,500 grams, is an influential factor contributing to infant mortality in the United States, with significant racial disparities between Black and White mothers. This study analyzed data from 3,054 Black and White mothers collected from the 2018 National Health Interview Survey to explore the association between access to medical care and LBW within different racial groups. The prevalence of LBW was 8.0%. Overall, mothers without a usual place of medical care had, on average, an 18% higher risk of LBW than those with a usual place (OR = 1.18, 95% CI: 0.80–1.74). …

Fish Tissue Digestion And Microplastic Polymer Identification Protocol Using Open-Source Ftir Database, Shawn L. Kissinger, Vick-Ariel Privert, Jason Bystriansky, Kyle A. Grice

DePaul Discoveries

Microplastic (MP) contamination in aquatic ecosystems poses significant concerns for environmental and public health, as seafood represents a critical food source worldwide. Despite increasing evidence of MP presence in marine organisms, efficient and accessible detection methods remain essential for characterizing contamination patterns and informing regulatory frameworks. This study extracted MPs from brain, gill, intestine, liver, and muscle tissues of gilt-head bream (Sparus aurata) and European sea bass (Dicentrarchus labrax), two commercially important species from the Gulf of Cádiz, Spain, using a NaOH–HNO₃ chemical digestion protocol. Isolated particles were characterized by Fourier Transform Infrared (FTIR) spectroscopy, with …

Crystal Structural Analysis Of Medieval Human Bones Using Wide-Angle X-Ray Scattering, Selly Altangerel, Leslie Gracia

DePaul Discoveries

Female human second metacarpal (mc2) bones from a medieval cemetery at Wharram Percy, England, were studied using high-energy Wide-Angle X-ray Scattering (WAXS) at beamline 1-ID of the Advanced Photon Source at Argonne National Laboratory. The age-at-death of 33 samples was determined from molar wear and classified into 3 groups:  18-30, 30-50, and 50+ years old.  Rietveld refinements of the WAXS data were performed to obtain lattice parameters of the hexagonal carbonated apatite phase (cAp). Individual fittings for cAp peaks 00.2, 00.4, and 31.0 were performed to obtain their widths and correlate them to collagen retention. For the three samples described …

Clearing The Air: Tracking Spatial And Temporal Pm2.5 Variability Along A Biking Transect In Chicago, Beau R. Rass

DePaul Discoveries

Fine particulate matter (PM₂.₅) poses significant risks to human health and disproportionately affects marginalized communities in urban environments (World Health Organization [WHO], 2021; Tessum et al., 2021). Using low-cost mobile sensors, this study explored spatiotemporal PM₂.₅ concentration patterns along a north–south transect of Halsted Street in Chicago. A 2B Technologies Portable Aerosol Monitor (PAM) mounted on a bicycle was used to continuously record PM₂.₅ concentrations with associated GPS coordinates at approximately two-second intervals during 16 sampling events between 08-12-2025 and 10-05-2025. PM₂.₅ concentrations did not differ significantly among the South Side, West Loop, and North Side regions, contrary to the …

Depaul Discoveries Volume 15 Cover Art, Dina Khdair

DePaul Discoveries

No abstract provided.

Llm-As-A-Judge For Infection Prevention And Control And Antimicrobial Resistance Impact: Comparing Three Main Llms Vs. Human Experts' Assessment, Marcello Di Pumpo, Leonardo Villani, Maria Rosaria Gualano, Danilo Buonsenso, Francesca Raffaelli, Daniele Donà, Patrizia Laurenti, Vittorio Maio, Stefania Boccia, Walter Ricciardi

College of Population Health Faculty Papers

BACKGROUND: Large language models (LLMs) are increasingly used to generate health information, yet their reliability as evaluators remains unclear. This study investigated the feasibility of an LLM-as-a-judge methodology in the context of infection prevention and antimicrobial resistance (AMR), comparing automated ratings with human expert benchmarks.

METHODS: We performed a secondary analysis of an expert-annotated dataset of health messages. Three leading LLMs (ChatGPT, Claude, Gemini) independently evaluated the same messages using an adapted DISCERN tool across five domains: information reliability, quality, AMR impact, persuasiveness, and overall score. We utilized descriptive statistics, intra-rater reliability tests, and mixed-effects ordinal regression to analyze divergence …

Signal And Substance: Why Methodological Sophistication Fails To Guarantee Inference, Aamir Rashid, Rizwana Rasheed

Publications and Research

Despite increasing analytical sophistication, empirical research in organization studies continues to suffer from fragile inference, uneven theoretical accumulation, and contested credibility. This paper seeks to explain why these problems persist by shifting attention from authors’ methodological choices to the evaluative dynamics of peer review. Adopting a conceptual and theory-analytic approach, the paper theorizes peer review as an inferential gatekeeping system. Drawing on research design, theory evaluation, and philosophy-of-science literatures, this study develops an analytical framework to examine how evaluative routines shape what constitutes empirical rigor during the review process. The analysis identifies five recurring reviewer blind spots: inferential scope inflation, …

Feasibility And Acceptability Of Automated Texts To Offer, Screen, And Enroll Patients In A Cancer Clinical Trial Financial Reimbursement Program: Mixed Methods Study, Ashley E Santaniello, Hena Patel, Sarah Milinski, Mohan Balachandran, Vivian Nguyen, E. Paul Wileyto, Robert H. Vonderheide, Dana Dornsife, Robert G. Johnson, Carmen E. Guerra

Student Papers, Posters & Projects

BACKGROUND: Out-of-pocket (OOP) costs pose a significant barrier to participating in cancer clinical trials (CCTs). Financial reimbursement programs (FRPs) that reduce the burden of OOP costs can support participation in CCTs if the information is readily available to participants at the time of enrollment. Prior studies have shown the importance and impact of FRPs, but despite improvements, significant barriers still remain.

OBJECTIVE: This study was designed to explore the feasibility and acceptability of automated texts designed to offer, screen, and enroll CCT participants in an FRP for OOP travel and lodging-related clinical trial costs.

METHODS: This study used a mixed …

Decoding The Allosteric Grammar Of Protein Kinases: A Dual-Stream Framework Integrating Protein Language Models And Energy Landscape Frustration Analysis, Will Gatlin, Max Ludwick, Lucas Turano, Brandon Foley, Kamila Riedlova, Vít Škrhák, Marian Novotný, David Hoksza, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The spatial and energetic encoding of allosteric regulatory sites remains a major challenge in structural biology, frequently representing a “blind spot” for sequence-based artificial intelligence (AI) models. We present a protein language model (PLM)-guided approach complemented by the energy landscape frustration analysis as a dual-stream framework to investigate the relationship between AI prediction of binding sites and biophysical organization of regulatory pockets across the human kinome. By probing a fine-tuned residue-level PLM classifier across 453 kinase structures, a clear performance gap is discovered between highly predictable orthosteric pockets (Types I, I.5, and II) and poorly resolved distal allosteric sites (Type …

Ecorxchoice.Com— An Sidp-Funded Calculator Integrating Environmental Metrics With Antimicrobial Stewardship, Pamela S. Lee, Hugh Gordon, Theresa Ferguson, Tien Dinh, Misty Vu, Marina Nguyen, Chaynor Hsiao, Gary Fong

Pharmacy Faculty Articles and Research

Healthcare sustainability is a multidisciplinary field that seeks to mitigate healthcare’s environmental consequences. Antimicrobial stewardship and healthcare sustainability both aim to reduce wasteful resource use while maximizing patient safety. However, a strong partnership between antimicrobial stewardship and healthcare sustainability has yet to develop. To facilitate environmentally sustainable decision-making in antimicrobial prescribing, we developed a web-based calculator (EcoRxChoice (www.ecorxchoice.com)) where users can enter different antimicrobial regimens and compare how much plastic waste each regimen creates. This work was supported in part by the Society of Infectious Diseases Pharmacists (SIDP), reflecting SIDP’s commitment to strengthening sustainability as a practical extension of antimicrobial …

Mental Health Self-Perceptions And Resource Utilization In Undergraduate Students At Binghamton University, Nicole J. Dreznin, Sarah Marcus

Binghamton University Undergraduate Journal

Undergraduate students face increasing rates of mental health challenges, however discrepancies in mental health literacy and utilization of resources may exist across student populations. This study examined the perceptions of mental health in undergraduate students at Binghamton University and if they differed among STEM vs non-STEM, man vs. women, and first-generation vs. continuing generation undergraduate students. A 20-question survey, containing 5 demographic questions and 15 mental health related questions was distributed through Qualtrics to 9 undergraduate classes. The available response choices were based on the Likert scale. A total of 1266 students participated.  Chi square tests of independence were done …

Perspectives Of Scholars, Families, And Advisors On 360-Degree Video Technology In Graduate Education, Oluwatobi A. Mogbojuri, Bridget A. Walsh, Matthew Aguirre

Journal of Human Sciences and Extension

This study explored the experiences of scholars in creating and sharing 360-degree videos, as well as the perspectives of families and advisors who viewed the videos. Focus groups and individual interviews were conducted online using a videoconferencing platform. Perspectives from 20 participants (15 scholars, three advisors, and two family members) were analyzed using thematic analysis. Three primary themes were identified: (1) barriers to 360-degree video use, (2) perspective shifts and limited change, and (3) storytelling and scholar visibility. Findings suggest that 360-degree video technology may be an innovative tool for enhancing recruitment and retention, especially for historically marginalized groups, through …

Pharmed. System Manual: Hololens Application, Eden Woldeselassie

Systems Manuals - 2026

This document provides the full life cycle of PharmEd HoloLens. PharmEd stands for Pharmacy Education. The overall document will go through the complete system manual by going over requirements, followed by design, how to install the application, how to upload the application to Microsoft store, troubleshooting and source code. The first section will explain the background, the existing problems and why the need to develop PharmEd.  Here techniques of requirement gathering and some statistics will elaborated. The following section discusses about functional requirements. The requirement section includes subtopics: functional and nonfunctional requirements for both -programmer and end user- and the …

Tumor-Immune Dynamics With Memory And Time Delay: A Fractional-Order Model With Ctla-4 Regulation, Mutaz Mohammad, Mohyeedden Sweidan, Alexander Trounev, Fathalla Rihan

All Works

This study develops a fractional-order tumor-immune interaction model incorporating Caputo memory effects, delayed immune activation, and CTLA-4 checkpoint regulation. The model describes the coupled dynamics of tumor cells, CD4^+ T cells, IFN-γ, and CTLA-4, and extends classical integer-order tumor-immune models by accounting for hereditary immune responses and biologically motivated latency effects. Theoretical properties, including positivity, boundedness, equilibrium structure, and fractional-order stability, are examined to establish the biological and mathematical consistency of the model. The delayed fractional system is then investigated computationally by comparing several numerical methods, including finite difference discretization, Daubechies wavelet collocation, Euler wavelet collocation, and a predictor-corrector scheme. …

A Mathematical Model For Managing Diphtheria Outbreaks In Nigeria Via Vaccination, Enhanced Surveillance, Effective Quarantine, And Social Distancing Measures, Hycienth Ortser Orapine, Nyiutya Cephas Ine, Dekera Jacob Washachi, Ali Audu Baidu, Lubem Matthew Kwaghkor

Mathematical Modelling and Numerical Simulation with Applications

Diphtheria is a highly infectious respiratory and skin disease that poses a significant threat to global public health. In Nigeria, children and adults with low immunity remain at high risk due to recurring annual outbreaks in the last decade, with a death rate of as high as 68.8\%. This paper presents a deterministic compartmental model to evaluate the effectiveness of interventions implemented by the Nigerian government. The model's mathematical and epidemiological validity is established through proofs of non-negativity and boundedness. The basic reproduction number ($R_0$) is derived, and stability analysis confirms that the diphtheria-free equilibrium is locally and globally asymptotically …

Stochastic Analysis Of Epidemic Size And Peak Infection In An Svir Model With Imperfect Vaccine And External Source Of Infection, María Gamboa Pérez

Mathematical Modelling and Numerical Simulation with Applications

The dynamics of an infectious disease outbreak are studied under a stochastic framework in a closed population where individuals are homogeneously mixed. A vaccination program is implemented in the community prior to the start of the epidemic. The administered vaccine is imperfect, meaning that vaccinated individuals may still become infected upon contact with infected individuals. The mathematical Susceptible-Vaccinated-Infected-Recovered (SVIR) model describing the evolution of the epidemic is formulated as an absorbing, continuous-time, three-dimensional Markov chain with compartments for vaccinated, susceptible, infected and recovered individuals. The aim of this study is to characterize two fundamental epidemiological quantities: the maximum number of …

Tumor–Immune Dynamics With Memory And Time Delay: A Fractional-Order Model With Ctla-4 Regulation, Mutaz Mohammad, Mohyeedden Sweidan, Alexander Trounev, Fathalla Rihan

Mathematical Modelling and Numerical Simulation with Applications

This study develops a fractional-order tumor-immune interaction model incorporating Caputo memory effects, delayed immune activation, and CTLA-4 checkpoint regulation. The model describes the coupled dynamics of tumor cells, CD4$^{+}$ T cells, IFN-$\gamma$, and CTLA-4, and extends classical integer-order tumor-immune models by accounting for hereditary immune responses and biologically motivated latency effects. Theoretical properties, including positivity, boundedness, equilibrium structure, and fractional-order stability, are examined to establish the biological and mathematical consistency of the model. The delayed fractional system is then investigated computationally by comparing several numerical methods, including finite difference discretization, Daubechies wavelet collocation, Euler wavelet collocation, and a predictor-corrector scheme. …

Forecasting Covid-19 New Cases Using Nbeats Deep Learning And Mobility Data, Amril Nazir, Mohammad Shorfuzzaman, Muhammad Lujaini Lotfi, Firuz Kamalov, Sufian Badawi, Maen Takruri, Abdul Halim Jallad

All Works

COVID-19 is a highly contagious disease transmitted primarily through human contact. Therefore, understanding population mobility is essential for predicting COVID-19 case trends. In this paper, we propose a novel deep learning approach for forecasting new COVID-19 cases using a neural architecture called Neural Basis Expansion Analysis for Interpretable Time Series (N-BEATS). The N-BEATS model effectively handles long input sequences and large output horizons without information loss or increased computational complexity. We compare the performance of N-BEATS with a state-of-the-art benchmark model, LSTM-Markov, across four major countries: the United States, the United Kingdom, Russia, and Brazil. Three distinct COVID-19 datasets from …

Teachers’ Awareness Of Family Engagement In Multilingual Education, Sedighe Zamani Roodsari

Journal of Multicultural Affairs

This study investigated public school teachers’ awareness of family engagement as a linguistic and cultural resource for multilingual students. Multilinguals are typically described as individuals who can communicate in more than one language, with English not being their native language, and their linguistic choices are influenced by societal norms and systems (Šifrar Kalan et al., 2024; Wei, 2008). Preparing pre-service teachers to enhance opportunities for multilingual students remains a critical need in teacher education programs, as they strive to move beyond monolingual ideologies in their teaching practices (Cárdenas Curiel et al., 2024; Kim & Choi, 2020; Williams & Ewing, 2019). …