Digital Commons Network^™

White Nose Syndrome In Bats And Infant Mortality In Georgia, Rhys Medcalfe, Sean Medcalfe, Simon Medcalfe

Journal of the Georgia Public Health Association

Background: White nose syndrome (WNS) is a disease in bats caused by the fungus Pseudogymnoascus destructans that can result in bat mortality rates of over 90%. WNS was discovered in Georgia in 2012 in 3 counties but has continued to spread to 14 counties as of 2023, with P. destructans detected in a further seven. Biodiversity loss has been linked to human health outcomes including infant mortality. Understanding the link between WNS, biodiversity loss, and infant mortality in Georgia is important because Georgia ranks 42^nd out of the 50 states for infant mortality rate.

Methods: Using panel data from …

High-Resolution Lidar Observations Of Sedimentation-Induced Size Sorting Of Droplets Near A Laboratory Cloud Top, Fan Yang, Yong Meng Sua, Zipei Zheng, Jesse Anderson, Hamed F. Sadi, Jae Min Yeom, Suryadev Pratap Singh, Pei Hou, Will Cantrell, Ernie Lewis, Alex Kostinski, Raymond Shaw

Michigan Tech Publications

No abstract provided.

Orbital Stability Of Solitary Wave Solutions Of The Generalized Benjamin Equation, Leijin Cao, Binhua Feng, Zhaosheng Feng, Yichun Mo

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we study the existence and stability of solitary wave solutions for the generalized Benjamin equation in both the L2-critical and L2-supercritical cases by applying the variational methods and the non-homogeneous Gagliardo–Nirenberg inequality. Our main results generalize and complement the existing results in the literature.

Hot Ground State Cooling Following Ultrafast Photoisomerization: Time-Resolved Infrared Spectroscopy, James N. Bull, Mark H. Stockett, Pratip Chakraborty, Eleanor K. Ashworth, Anam Fatima, Vincent J. Esposito, Gregory M. Greetham, Partha Malakar, Stephen R. Meech

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The ultrafast photophysics of many isomerizing molecules involves subpicosecond formation of a twisted hot ground state, which transfers energy to the environment through vibrational relaxation (cooling) over several picoseconds. In time-resolved infrared (TR-IR) spectroscopy, hot ground state transients show frequency shifts and band reshapings, which cannot be described through kinetic models that assume static spectral functions. We report a simple anharmonic cascade framework, which uses a single adjustable parameter associated with scaling the probability of vibrational energy transfer to the environment, for describing hot ground state cooling (HGSC) in TR-IR spectroscopy. The model is demonstrated against measurements on the cyan …

Book Of Abstracts, Seton Hall University

2025 Augustine Undergraduate Research Symposium

No abstract provided.

My First Conversation With Chatgpt (February 22, 2023): Origins Of A Generative Dialogue, David Smith

Publications and Research

This working paper presents the first recorded interaction between the author and the generative AI system ChatGPT, written on February 22, 2023 during the initial weeks of a faculty sabbatical in Boston. The document preserves a complete and unedited transcript of an exploratory conversation conducted without predetermined research aims, marking the author’s first encounter with a large-language-model conversational interface. Although the exchange includes creative experimentation—including musical and poetic prompts—the discussion remains informal and wide-ranging, and no theoretical framework is articulated at this stage. Rather, this transcript is published as primary-source material documenting the moment of discovery and experimentation that precedes …

Bayesian Alignment Prior To Connectionist Temporal Classification Loss, Lawry Sorenson

Theses and Dissertations

We propose revisions of Connectionist Temporal Classification (CTC) loss and forced alignment to support longer input sequences. CTC loss is normally used for training in speech and handwriting recognition tasks when the labels are not fully aligned with the data, while forced alignment is a downstream task that finds the optimal path for segmentation purposes. The current implementations consider all possible alignments between the input and label, which grows exponentially with the size of the input. We show that in cases when silence is removed and speaking rate is consistent, the true alignment is a mostly straight line across time …

Commutative Schur Rings Over Characteristic 2 Special Orthogonal Groups, Andrew Haviland

Theses and Dissertations

We study commutative Schur rings over the special orthogonal groups $\mathrm{SO}^{\pm}(n,2)$ that contain the class $\mathcal{C}$ of transvections. We show that the partition of $\mathcal{C}$ determined by a commutative Schur ring has either one or two parts. We classify all remaining partitions of $\mathcal{C}$ that could be determined by a commutative Schur ring.

Implementing Dataops: A Scalable Framework For Modern Data Warehousing, Dmytro Valiaiev

Theses and Dissertations

DataOps has been coined as a novel term that emerged as a synthesis of data management practices with software engineering concepts, such as DevOps and Agile, with the goal of improving data quality and governance in enterprises. The proliferation of scratch table use and transformation tools, such as dbt, has led to an exponential increase in the number of data models, which complicates standardization efforts and increases maintenance overhead. Although the market is saturated with various flavors of text-to-SQL engines that promote increased productivity and self-service use in organizations, there are limited tools available to optimize individual queries, enforce consistency, …

Modeling Private Debt Using U.S. Consumer Expenditure Data, Stsiapan Dziamentsyeu

Honors Capstones

This project models private household debt among U.S. consumers using data from the Consumer Expenditure Survey (CES) between 2013 and 2023. The analysis focuses on identifying how demographic and economic characteristics, such as income, housing expenditures, education, and occupation, relate to non-mortgage “other” loan balances. After initial model development produced poor residual behavior due to zero-inflation from imputed debt values, the analysis was refined to include only households reporting verifiable debt. Multiple modeling techniques, including AIC-based variable selection and Lasso regularization, were compared under a five-fold cross-validation framework. The Lasso model achieved superior predictive accuracy (RMSE = 1.55, MAE = …

Data For "Large Projected Increases In Area Burned And Wildfire Frequency By 2050 In Utah, Usa", Joseph D. Birch, Yoshimitsu Chikamoto, James A. Lutz

Browse all Datasets

Changes in wildfire regimes may disrupt ecosystem processes as wildfires burn larger areas or burn more frequently than the recent natural range of variability. The climatic drivers of wildfire behavior may change in strength but these effects are not likely to be uniform across space and between different vegetation types. Increased understanding of how weather and climate influence patterns of burn area and frequency across vegetation types may assist in better predicting and managing future wildfire regimes. We examined a dataset of all 1469 wildfires ≥40 ha from 1984 – 2021 in Utah, USA and used antecedent daily weather data …

Synthesis And Characterization Of Copper Nanoparticles: A Laboratory Experiment For Undergraduate Physical Chemistry, Jonathan Batey, Deborah Okyere, Sarah York, Feng Wang, Jingy Chen

Chemistry & Biochemistry Faculty Publications and Presentations

Nonprecious metal nanoparticles have been the subject of intensive research, due to their potential applications in promoting sustainability. This integrated laboratory experiment is designed to provide undergraduate students with hands-on experience in synthesizing and characterizing nonprecious metal nanoparticles, specifically copper nanoparticles. The experiment consists of three sections, each tailored to teach a unique aspect of nanochemistry. Section 1 focuses on the air-free synthesis of copper nanoparticles using a solution-based method with an emphasis on understanding their plasmonic properties and how oxidation impacts them. Section 2 explores the quantitative analysis of copper, where students apply crystal field theory to understand the …

Citizen's Rare Plant Watch 2025 Recap, Nora Dunkirk

Rae Selling Berry Seed Bank and Plant Conservation Program

Citizen's Rare Plant Watch (CRPW) is a community science program which takes volunteers out to visit populations of rare and threatened Oregon native plant species. Volunteers assess their health and viability, update the Oregon Biodiversity Information Center (ORBIC) state database for rare species, and help contribute to data driven management decisions throughout the state. Housed at Portland State University, this program is open to the public and attracts plant lovers from diverse backgrounds. Each spring, CRPW trains volunteers on methods of data collection, and this year we implemented new technology using Survey123 to streamline population assessments. We focus on species …

Online Decision Mamba, Trenton W. Ruf

Dissertations and Theses

Online in-context reinforcement learning enhances offline-trained policies through online fine-tuning. We introduce Online Decision Mamba (ODM), an architecture that replaces the attention mechanism in Online Decision Transformers (ODT) with the Mamba module to improve long-context sequence modeling and overall RL performance. We performed in-depth evaluations on MuJoCo (OpenAI Gym) and Atari benchmarks, comparing ODM against state-of-the-art offline and online baselines—including Decision Mamba (DM) and ODT. Our results show that ODM achieves competitive or superior performance, with particularly robust gains when initial datasets lack expert demonstrations. In the Qbert Atari environment, ODM shows context-length sensitivity similar to offline DM; however, we …

Sustainable Polyaddition Path To Polyesters Via Catalytic Homocoupling Of Renewable Dicrotonate Monomers, Shabbir Asif, Mahsa Saeidi, Braden D. Pickle, Nicholas J. Tabbah, Michael L. Mcgraw

Chemistry & Biochemistry Faculty Publications and Presentations

The development of biorenewable polyhydroxyalkanoate (PHA) chemistry has generated interest in crotonate-based monomers as versatile building blocks. Crotonates can be obtained through the pyrolysis of PHAs, offering both a sustainable end-of-life pathway for PHAs and a renewable route to crotonate monomers. This study presents a new polyaddition-type step-growth polymerization of dicrotonates in which alkene-functionalized polyesters are synthesized using potassium tert-butoxide as a simple base catalyst. The reaction proceeds rapidly at room temperature, achieving >99% conversion within seconds and requiring no byproduct removal. The properties of the resulting polyesters can be tuned via the choice of bridging diol, and the materials …

Towards Fair Sequential Resource Allocation: Algorithmic Designs, Interventions, And Evaluations, Ashwin Kumar

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis develops a comprehensive framework for fair sequential resource allocation in multi-agent systems where a centralized allocator coordinates actions under global feasibility constraints, while satisfying preferences of different agents. Ranging from ridesharing platforms and homelessness intervention programs to power grid management, such systems play a critical role in shaping access to essential resources. Yet, existing approaches to resource allocation often prioritize aggregate utility, leading to systematic inequities across individuals and groups, particularly in sequential settings where decisions unfold over time. To address this challenge, we introduce the Distributed Evaluation, Centralized Allocation (DECA) framework, which unifies a broad class of …

Accessing Cation And Anion Redox In Mixed-Valent One-Dimensional Iron-Chalcogenides, Na1.5fe1s2–Xsex(X = 0, 1, And 2), For Na-Ion Batteries, Santhoshkumar Sundaramoorthy, Milad Aghayi-Anaraki, Sutapa Bhattacharya, Amitava Choudhury

Chemistry Faculty Research & Creative Works

Sodium-ion batteries (NIBs) have attracted considerable attention as a cost-effective and sustainable alternative to lithium-ion batteries (LIBs), owing to the abundance and low cost of sodium resources. Here, we investigate previously reported mixed-valent (Fe^3+/2+) one-dimensional (1D) iron chalcogenides: Na1.5FeS2, its selenide analogue Na1.5FeSe2, and newly developed solid solution Na1.5FeSSe, focusing on their synthesis, structural characterization, and electrochemical performance in NIBs. While the full Fe²⁺sulfide version (NaFeS2) of the compound is explored in solid-state cells for its dual cation–anion redox mechanism, we reveal the effect of anion substitution on the electrochemical behavior of Na1.5FeS2–xSex(x = 0, 1, …

Gwtc-4.0: An Introduction To Version 4.0 Of The Gravitational-Wave Transient Catalog, A. G. Abac, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

The Gravitational-Wave Transient Catalog (GWTC) is a collection of short-duration (transient) gravitational-wave signals identified by the LIGO–Virgo–KAGRA Collaboration in gravitational-wave data produced by the eponymous detectors. The catalog provides information about the identified candidates, such as the arrival time and amplitude of the signal and properties of the signal’s source as inferred from the observational data. GWTC is the data release of this dataset, and version 4.0 extends the catalog to include observations made during the first part of the fourth LIGO–Virgo–KAGRA observing run up until 2024 January 31. This Letter marks an introduction to a collection of articles related …

Is Hockey Still Canada’S Game? How Usa Teams Have Won Every Stanley Cup Since 1994, Aaron Montgomery, Long Doan, Joe Demaio, Michael Frankel

Symposium of Student Scholars

The last Canadian team to win Lord Stanley’s cup in the National Hockey League was the Montreal Canadiens in 1993. Since then, each championship has been claimed by a team geographically located in the United States. Is this streak unusual? Perhaps it is particularly unusual in light of the fact that Hockey is known as Canada’s game. Is Hockey in its modern incarnation still Canada’s game? Given the long history of the NHL should we expect such a streak to occur at some point in time? Are we too fixated on the geographic location of the teams in question? Perhaps …

Prism (Proxy Recognition And Inclusion Scoring Method), Destiny Raburnel, Crystal Tubbs, Md Abdullah Al Hafiz Khan

Symposium of Student Scholars

AI-driven automated hiring tools are reshaping how companies find talent, but they often reproduce the hidden biases embedded in their training data. Our project, PRISM (Proxy Recognition and Inclusion Scoring Method), investigates how subtle demographic signals, specifically first names associated with gender and race, influence AI resume screening even when candidates have identical qualifications. We built a controlled dataset of resumes that are identical in every way except for the applicant's first name, with each resume using a racially neutral surname to isolate how first names alone affect scoring. We tested these resumes against job postings in technology, healthcare, and …

Degeneracies In A Weighted Sum Of Two Squares, Ishan V. Ramesh

Rose-Hulman Undergraduate Mathematics Journal

This work is an attempt to classify and quantify instances when a weighted sum of two squares of positive integers, 3n2 1 +n2 2, can be realized in more than one way. Our project was inspired by a particular study of two-dimensional quantum billiards [S. G. Jackson, H. Perrin, G. E. Astrakharchik, and M. Olshanii, SciPost Phys. Core 7, 062 (2024)] where the weighted sums of interest represents an energy level with the two integers being the billiard’s quantum numbers; there, the 3-fold degeneracies seem to dominate the energy spectrum. Interestingly, contrary to the conventional paradigm, these degeneracies are not …

Artificial Intelligence In Insurance Fraud Detection: Applications And Implications For Internal Audit, Maria Davis

Honors Projects

Artificial Intelligence (AI) is being used in accounting and the insurance industry to assist with auditing and fraud detection. The Big Four public accounting firms have invested heavily in AI implementation efforts. Across these firms, AI has been used to reallocate auditors’ time from mundane tasks to more complex tasks that require human judgement. Within the insurance industry, machine learning, deep learning, and natural language processing, among other AI tools, have proven helpful in fraud detection efforts. While the positive impacts of AI usage are clear, concerns surrounding the replacement of human jobs, a lack of transparency in auditing, heavy …

Math Meets Climate: The Energy Balance Model, Maria I. Sanchez Muniz

Open Educational Resources

This assignment introduces students to the mathematics of Earth’s climate through the classical energy balance model. Students analyze how incoming solar radiation, outgoing thermal radiation, and temperature-dependent albedo interact to determine Earth’s equilibrium temperature. Using analytical calculations and computational tools, students identify equilibrium states, assess their stability, and interpret the results through the lens of dynamical systems and bifurcation theory. The activity builds conceptual understanding of climate feedbacks, greenhouse effects, and tipping behavior using a transparent, one-variable model. Designed for applied mathematics and interdisciplinary STEM courses, this assignment emphasizes computation, physical interpretation, and real-world relevance. It is released as a …

Water Circulation Beneath A Hovering Suas For Water Quality Monitoring Applications, Erin E. Hackett, Boone Fleenor, Jensine C. Coggin, Duvall Dickerson-Evans, Nikolaos Vitzilaios, Whitney E. Schuler, Paige K. Williams, Michael L. Myrick

Marine Science

Water quality has traditionally been measured via in situ sensors and satellites. The latter has limited applicability for smaller inland water bodies, while the former requires significant logistics, labor, and expense for routine sampling, and reactive/spurious sampling is often not feasible as a result (e.g., sampling pre-/post-storm). Consequently, small uncrewed aircraft system-based (sUAS-based) sampling has emerged as a potential solution to bridge these sampling gaps and challenges. But sampling from an sUAS is complicated by the need to pump water from depth, rather than suspending a sensor from the sUAS, due to concern over sampling sUAS-impacted waters. Here, we measure …

An Assessment And Comparison Of Expert System Performance And Large Language Model Performance, Carter A. Lange

ATU Honors Projects

This study compares the performance of knowledge-based expert systems (KBES) and large language models (LLMs) in narrow-domain tasks. Using Akinator as the representative KBES and ChatGPT as the representative LLM, fifty character-identification trials were conducted. Results show that both systems ultimately succeeded in identifying all characters, but their efficiency and accuracy differ. Akinator required fewer incorrect guesses and produced no identifiable total failures, or “errors,” while ChatGPT occasionally erred beyond possible continuation despite similar average guess counts. Statistical analysis revealed no significant difference in the number of questions required before success, but McNemar’s test indicated that ChatGPT made significantly more …

Jer-2021 Assistance To The State Water Resources Research Institute Program (Year 1 Of 5) For The 104(B) Program, David Tarboton

Funded Research Records

No abstract provided.

Bcser: Learning Analytics For Process-Driven Computer Programming Assignments, Hamid Karimi

Funded Research Records

No abstract provided.

Predicting Skin Concern Severity From Genetic And Lifestyle Factors: A Comparative Multi-Output Machine Learning Framework, Yassine Benachour, Lina Maloukh, Sadok Bouamama, Barbara Geusens

All Works

Personalized dermatology increasingly leverages both genetic predispositions and lifestyle behaviors to model individual skin health outcomes. This study proposes a multi-output machine learning framework to predict the severity of six dermatological phenotypes—acne, redness, dryness, sensitivity, scarring, and pigmentation—using a multimodal dataset of 5,254 individuals. Input features include mutation profiles for six skin-related genes (FLG, MMP1, MMP3, AQP3, SOD2, GPX) and 22 lifestyle variables such as sun exposure, stress, and hydration. We train and evaluate LightGBM models under independent, multi-output, and chained configurations. Performance is assessed using Mean Absolute Error (MAE) and average Quadratic Weighted Kappa (QWK). The proposed ordinal-aware independent …

Career: End-To-End Active Region-Based Heliospheric Forecasting System Using Multi-Spacecraft Data And Machine Learning, Soukaina Filali Boubrahimi

Funded Research Records

No abstract provided.

Wf-2453 Post-Wildfire Hydrogeomorphic Risk Management Assessment, Belize A. Lane

Funded Research Records

No abstract provided.