Digital Commons Network^™

Memebuddy: Dialog-Style Audio Representations For Engaging Non-Visual Meme Experiences, Chirag Bhansali, Vikas Ashok, Hae-Na Lee

Computer Science Faculty Publications

Image memes are a pervasive form of online communication, widely used to convey humor, opinions, and cultural references. Prior work has explored making memes accessible to blind users, primarily through auto-generated descriptive captions. While these approaches improve comprehensibility and sometimes incorporate prosodic or emotional cues, they often fail to capture the humor, narrative structure, and contextual nuances that make memes engaging. We present MemeBuddy, a system that models memes as dialog, generating structured, multi-turn audio representations using role-based speakers. MemeBuddy reinterprets a meme as a conversation between two speakers, integrating extracted meme text with contextual knowledge implicitly inferred by a …

Attf-Gnn: An Attention-Based Multi-Omics Graph Neural Network With Modality Learning For Disease Subtyping, Sovon Chakraborty, Eleni Adam, Terry Stilwell, Harold Riethman, Desh Ranjan, Pratip Rana

Computer Science Faculty Publications

We propose AttF-GNN, an attention-based graph fusion strategy for diseases classification and subtyping. In multiomics analysis, not all types of molecular data are equally relevant for disease subtyping and considering all modalities equally may obscure discriminative signals and limit the effectiveness of predictive models by overlooking modality-specific contributions. Therefore, we design an attention-based multimodal GraphSAGE framework that can automatically emphasize the modalities providing the most relevant information for classification. At first, we have constructed three graphs using mRNA, RNA-seq and DNA methylation modalities, and train each omics with individual GraphSAGE encoders. Next, a unified intersection graph is formed using an …

Distributed Semi-Speculative Parallel Anisotropic Mesh Adaptation, Kevin Garner, Polykarpos Thomadakis, Nikos Chrisochoides

Computer Science Faculty Publications

This paper presents a distributed memory method for anisotropic mesh adaptation that is designed to avoid the use of collective communication and global synchronization techniques. In the presented method, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a multicore cc-NUMA-based (shared memory) mesh generation software and a parallel runtime system that is designed to help applications leverage the concurrency offered by emerging high-performance computing (HPC) architectures. First, an initial mesh is decomposed and its interface elements (subdomain boundaries) are adapted on a single multicore node (shared memory). Subdomains are then distributed among the …

Deep Incomplete Multi-View Clustering Via Hierarchical Imputation And Alignment, Yiming Du, Ziyu Wang, Jian Li, Rui Ning, Lusi Li

Computer Science Faculty Publications

Incomplete multi-view clustering (IMVC) aims to discover shared cluster structures from multi-view data with partial observations. The core challenges lie in accurately imputing missing views without introducing bias, while maintaining semantic consistency across views and compactness within clusters. To address these challenges, we propose DIMVC-HIA, a novel deep IMVC framework that integrates hierarchical imputation and alignment with four key components: (1) view-specific autoencoders for latent feature extraction, coupled with a view-shared clustering predictor to produce soft cluster assignments; (2) a hierarchical imputation module that first estimates missing cluster assignments based on cross-view contrastive similarity, and then reconstructs missing features using …

Attention-Based Multi-Omics Fusion For Drug Synergy Prediction, Kusal Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Drug combination therapy in disease management gained popularity in the last few decades. Computational modeling of such combinations is an active area of research in the drug discovery domain. While earlier approaches solely emphasized on the structural features of participating drugs for designing synergistic models, they lack other crucial factors directly linked with drug administration - omics expressions. As differential omics expression is a downstream consequence of the administered drug combinations, utilizing such expressions while designing synergistic models promises robust and dynamic modeling. In this work, we propose SynergyLM that fuses multi-omics features with drug embeddings to build an omics-aware …

A Survey Of Ai Methods For Geometry Preparation And Mesh Generation In Engineering Simulation, Steven Owen, Nathan Brown, Nikos Chrisochoides, Rao Garimella, Xianfeng Gu, Franck Ledoux, Na Lei, Roshan Quadros, Navamita Ray, Nick Winovich, Yongjie Jessica Zhang

Computer Science Faculty Publications

Artificial intelligence is beginning to reduce the manual effort in the CAD-to-mesh pipeline. Written for meshing and geometry practitioners with limited AI background, this survey organizes recent work by workflow step. We cover part classification and segmentation, mesh quality prediction, and defeaturing. We review AI guidance for unstructured meshing, block-structured meshing in 2D and 3D, and volumetric parameterization, including reconstruction from implicit or sampled geometry. We also discuss parallel mesh generation and scripting automation via reinforcement learning and large language models. Across these topics, AI complements established geometry and meshing algorithms rather than replacing them. We conclude with practical lessons …

Environmental Pesticide Exposure In The Etiology Of Pediatric Brain Tumors And Leukemia: A Scoping Review Of Epidemiological Studies, G. N. Vandesteeg, A. R. Russman, M. R. Sandbulte, E. G. Rogan, M. G. Rhodes

School of Natural Resources: Faculty Publications

No abstract provided.

Understanding Motivations And Health Outcomes Of College-Aged Triathletes During Covid-19: A Mixed-Methods Study, Patrick Wilson, Eddie Hill, Justin Haegele, Xihe Zhu

Human Movement Studies & Special Education Faculty Publications

A triathlon is a multi-sport event that consists of three simultaneous events: swimming, biking, and running. This sport has experienced significant growth in the past few decades, with colleges and universities now participating. This exploratory mixed-methods study examined the motivations and perceived health benefits of college triathletes during the COVID-19 pandemic, using the Means-Ends of Recreation Scale and the Perceived Health Outcomes of Recreation Scale (N = 29), as well as semi-structured interviews (N = 4). Results indicate no difference in motives or health outcomes between male and female survey respondents. The thematic analysis of open-ended interview questions highlighted lived …

Study Of Fire Regimes In Southwestern Australia Using Geospatial Techniques, Ana Do Carmo Carvalho

Theses: Doctorates and Masters

The Northern Jarrah Forest in Southwestern Australia (SWA), part of a global biodiversity hotspot, is home to fire-sensitive tree species such as marri (Corymbia calophylla) and jarrah (Eucalyptus marginata). As climate change intensifies drought and extreme fire events, understanding the drivers of fire severity is increasingly critical. This thesis analyses fire regimes within the Mundaring drinking water catchment to better understand the spatiotemporal complexity of fire severity in relation to fire history and environmental factors.

The thesis commences with a review of three Fire History Databases (FHDs) used in SWA, highlighting significant inconsistencies and data gaps across time and space. …

Understanding Climate Change And Wellbeing Through Bhutan's Pursuit Of Gross National Happiness, Tashi Dorji

Theses: Doctorates and Masters

Climate change has evolved into one of the biggest global challenges of the twenty first century reshaping ecological systems and social conditions with wide-ranging implications for human wellbeing. Bhutan offers a distinct context to explore interactions between climate change and wellbeing as it remains guided by its wellbeing-centred development philosophy of Gross National Happiness (GNH). At the same time, it remains highly vulnerable to climate change despite being the only carbon negative country in the world. Nonetheless, the intersections between climate change and GNH have not been systematically explored.

This research aims to explore the relationship between climate change and …

Categories, Homology And Sheaves For Hypergraphs, Robert Green

Electronic Theses & Dissertations (2024 - present)

Hypergraphs are a prominent tool for representing networks with connections among three or more entities. There is an inherent flexibility that allows hypergraphs to more naturally represent certain types of networks than graphs or simplicial complexes can on their own. This flexibility, however, comes at a cost, as there is a zoo of various categories and homology theories that are applicable to hypergraphs. The first chapter of this dissertation explores various categorical perspectives on hypergraphs, focusing on what the natural notion of morphism between hypergraphs should be. It also contains an exploration of the functoriality of vertex-edge duality in these …

Crispr-Cas9 Unleashed: Gene-Slicing Adventures In The Cancer Battlefield, Shivakuma Sonnaila, Shilpi Agrawal

Chemistry & Biochemistry Faculty Publications and Presentations

Cancer, a global health menace, continues to pose significant challenges in terms of incidence and mortality, necessitating innovative therapeutic strategies. Despite existing treatments, the limitations persist, prompting a quest for novel approaches. The emergence of immunotherapy marked a transformative era in solid tumor treatments, yet its efficacy is constrained by adverse effects. Concurrently, the integration of advanced technologies into cancer treatment explores the vast potential residing at the molecular level through gene analysis and manipulation. This review articulates the role of state-of-the-art genome editing technology, notably clustered regularly interspaced short palindromic repeats (CRISPR-Cas9), in overcoming the constraints of immunotherapy for …

The Global Orbit ∞-Category And Applications To Assembly Maps, Zoë Pope

Electronic Theses & Dissertations (2024 - present)

We reformulate the foundations of assembly maps in the context of the global orbit ∞-category of all discrete groups. We first show that the ∞-categorical slice of the global orbit ∞-category over any fixed group G is equivalent to the orbit 1-category of G, and we also frame the subgroup 1-category of G in this global context. We then use the afore-mentioned equivalence to redefine assembly maps as counits of the adjunction between left Kan extension and restriction, and give purely ∞-categorical and conceptual proofs of known results, such as the Transitivity Principle. Additionally, we give equivalent formulations for what …

Drivers Of Extreme Streamflow During A Snowmelt-Enhanced Heavy Rainfall And Atmospheric River Event In The Catskill Mountains Of New York, Christopher A. Gilberti

Electronic Theses & Dissertations (2024 - present)

This study uses atmospheric reanalysis, precipitation and snow water equivalent (SWE) analyses, mesonet observations, and streamflow records to examine the impact of an atmospheric river storm that produced heavy rainfall and snowpack ablation across the Catskill Mountains of New York on 24–25 December 2020. Earlier in December, an antecedent storm produced SWE values in the Catskills above the 90^th percentile for that point in the season. The atmospheric river event followed with strong southerly warm-air advection ahead of an anomalously deep trough, temperatures and dewpoints that exceeded 10°C, and heavy orographically enhanced rainfall and rapid snowmelt. Sensible heat fluxes …

The Predictability And Verification Of Precipitation From Landfalling Tropical Cyclones Using An Object-Based Framework, Melissa Piper

Electronic Theses & Dissertations (2024 - present)

Precipitation from landfalling tropical cyclones (TCs) poses a significant risk to life and property in both coastal and inland communities. Early warning systems can help mitigate the impacts of TC-induced flooding; however, this requires accurate quantitative precipitation forecasts (QPFs). Forecasting precipitation from landfalling TCs is a challenge, as the intensity, duration, and location of precipitation can be dependent on numerous storm-related and environmental factors. Previous studies have attempted to identify and correct NWP model deficiencies and reduce forecast uncertainty by applying traditional and advanced verification metrics to TC QPF. However, these studies have mostly used gridpoint verification metrics, limited samples …

On The City-Scale Energy Balance Under Electrification And Renewable Generation: The New York City Case, Nour Elgalad

Electronic Theses & Dissertations (2024 - present)

Integration of renewable resources to meet the growing energy demand of dense urban regions is becoming a global priority under decarbonization mandates. This study contributes to these ongoing efforts by assessing the feasibility of using locally deployable urban renewable resources, namely offshore wind in the New York Bight region and rooftop photovoltaic (PV) systems over New York City, to meet the electricity demand of the city, and the grid vulnerabilities that emerge, during two contrasting extreme-weather periods: the intense heatwave of June 2025 and a fully electrified winter cold snap in January 2018. A unified, meteorologically driven modelling framework, based …

Digital Technologies And Calculus: Students’ Peaks And Pits, Ricela Feliciano-Semidei, Kevin A. Palencia Infante, Alcibiades Bustillo-Zarate

Faculty Articles, Papers, and Other Scholarship

Understanding calculus students’ perspectives can provide valuable insights into their learning needs and help develop strategies to enhance persistence in STEM programs. Numerous studies have shown that the use of digital technologies (DT) influences student engagement, motivation, and mathematics achievement. In this project, we explored students’ perspectives on using DT in calculus. We interviewed eight calculus students from a midwestern doctorate-granting institution in the United States and used thematic analysis informed by the didactical tetrahedron, accounting for internal and external factors that may influence the teaching and learning process. Students reflected on their use of technology, identifying various benefits, including …

Likelihood-Based Inference For Random Networks With Changepoints, Daniel Cirkovic, Tiandong Wang, Xianyang Zhang

Mathematical and Statistical Science Faculty Research and Publications

Generative, temporal network models play an important role in analyzing the dependence structure and evolution patterns of complex networks. Due to the complicated nature of real network data, it is often naive to assume that the underlying data-generative mechanism itself is invariant with time. Such observation leads to the study of changepoints or sudden shifts in the distributional structure of the evolving network. In this paper, we propose a likelihood-based methodology to detect changepoints in undirected, affine preferential attachment networks where, upon introduction, a new node selects one old to attach to with probability proportional to its degree. In particular, …

Efficient Preservation Of Old Methane-Derived Organic Carbon In Deep-Sea Surface Sediments, Rui Bao, Yangli Che, Mingzhi Liu, Naiyu Zhang, Yang Zhou, Lihua Dong, Shen Li, Owen A. Sherwood, Min Yu, Zongheng Chen, Shengxiong Yang, Nan Wang, Longhai Zhu, Jiawang Chen, Mutai Bao, Haoshuai Li, Luonan Chen, Weifeng Wu, Haiyue Ma, David J. Burdige

OES Faculty Publications

Methane released from the subseafloor is significantly attenuated during upward migration, yet the preservation of methane-derived organic carbon (OC) in global deep-sea sediments remains poorly understood. Here, we measured carbon isotopes coupled with temperature-ramped analyses on various methane seepage sediments. Our results reveal a correlation between the radiocarbon (¹⁴)C) content in deep-sea surface sediments and sulfate-methane transition depth. Notably, our findings suggest that a substantial amount of (¹⁴)C-depleted OC may originate from deep-seated methane and is efficiently preserved in surface seepage sediments. We propose that the efficient OC preservation is related to microbial-mediated aggregate formation at the seawater-sediment interface, where …

Differences In Sideerophore Production During The Growth Of Phytoplankton In Southern Ocean Incubation Experiments Under High- And Low-Iron Conditions, Randelle M. Bundy, Kristen N. Buck, Bethany D. Jenkins, P. Dreux Chappell, Daniel J. Repeta, Alexa Sterling, Shannon M. Yang, Laura Holland, Léo Mahieu, Laura E. Moore

OES Faculty Publications

Iron is an important micronutrient required by marine microorganisms. The Southern Ocean is an ecosystem where primary production is limited by the availability of iron, but how microorganisms in this region adapt to low-iron conditions or respond to episodic iron inputs is understudied. We tested how external iron additions would impact bacterial production of siderophores during phytoplankton growth using shipboard incubation experiments under a range of iron conditions. Similar heterotrophic bacteria communities and phytoplankton biomass were observed whether iron was added from the continental margin or as inorganic iron. Under both high- and low-iron conditions, the heterotrophic bacteria community remained …

The Distribution Of A-Numbers Of Hyperelliptic Curves In Characteristic Three, Derek Garton, Jeffrey Lin Thunder, Colin Weir

Mathematics and Statistics Faculty Publications and Presentations

In this paper we present a new approach to counting the proportion of hyperelliptic curves of genus g defined over a finite field Fq with a given a-number. In characteristic three this method gives exact probabilities for curves of the form Y 2 = f(X) with f(X) ∈ Fq[X] monic and cubefree, probabilities that match the data presented by Cais et al. in previous work. These results are sufficient to derive precise estimates (in terms of q) for these probabilities when restricting to squarefree f. As a consequence, for positive integers a and g we show that the nonempty strata …

Numerics: A .Net Library For Numerical Computing, Statistical Analysis, And Risk Assessment, C. Haden Smith, Woodrow L. Fields, Julian Gonzalez, Sadie Niblett, Brennan Beam, Brian Skahill

Mathematics and Statistics Faculty Publications and Presentations

Numerics is a free and open-source numerical computing library for .NET, developed by the U.S. Army Corps of Engineers Risk Management Center (USACE-RMC). The library provides 43 univariate probability distributions with L-moment and maximum likelihood parameter estimation, eight Markov Chain Monte Carlo (MCMC) samplers for Bayesian inference, bootstrap uncertainty quantification, bivariate copulas, optimization algorithms, and numerical methods for integration, differentiation, root finding, and linear algebra. Numerics targets engineers, scientists, and analysts working in infrastructure risk assessment, flood frequency analysis, and Monte Carlo simulation within .NET-based enterprise systems. The library supports .NET 8.0 through 10.0 and .NET Framework 4.8.1 and is …

Legal Ethics Of Ai Snake Oil: Navigating The Hype, Harm, And Hope Of Legal Ai, Drew Simshaw

Scholarly Works

This paper argues that the legal ethics of AI extend far beyond competence and hallucinations. It shows how AI often functions as a mirror, exposing deeper ethical questions about institutional incentives, lawyer wellbeing, access to justice, and AI's broader social and environmental impacts.

An Empirical Framework For Evaluating Semantic Preservation Using Hugging Face, Nan Jia, Anita Raja, Raffi Khatchadourian

Publications and Research

As machine learning (ML) becomes an integral part of high-autonomy systems, it is critical to ensure the trustworthiness of learning-enabled software systems (LESS). Yet, the nondeterministic and run-time-defined semantics of ML complicate traditional software refactoring. We define semantic preservation in LESS as the property that optimizations of intelligent components do not alter the system's overall functional behavior. This paper introduces an empirical framework to evaluate semantic preservation in LESS by mining model evolution data from HuggingFace. We extract commit histories, $\textit{Model Cards}$, and performance metrics from a large number of models. To establish baselines, we conducted case studies in three …

All Games Have Equilibria, M. Ali Khan, Arthur Paul Pedersen, Maxwell B. Stinchcombe

Publications and Research

Research on Nash equilibrium existence for infinite games has grown into a patchwork of technical preconditions and counterexamples. This paper presents a unified program in equilibrium theory by revising the predominant model of mixed strategies based on countable additivity. A game is specified by a nonempty set of players and, for each player, a nonempty action set and a bounded von Neumann-Morgenstern utility function. Every such game is shown to admit a Nash equilibrium in finitely additive mixed strategies. In addition, the equilibrium correspondence for any such game is shown to be nonempty, compact-valued, and upper hemicontinuous, and the same …

Resilience For Whom? A Study In Pathways And Production Of Unequal Risk In The Rockaways, Aaryan M. Nair

Publications and Research

This paper investigates how climate adaptation policies in the Rockaway Peninsula of New York City produce unequal outcomes despite their ostensibly neutral design, framing resilience as an environmental and climate justice problem. Situated within a landscape marked by stark socioeconomic disparities, aging housing stock, and high exposure to coastal flooding, the study demonstrates that existing adaptation strategies—centered on uniform technical standards, insurance frameworks, and large-scale coastal infrastructure—systematically advantage actors with greater financial and institutional capacity while leaving low-income residents, particularly renters, disproportionately vulnerable.

The analysis identifies three core dynamics underlying this “unequal-by-design” resilience regime: (1) the stratified feasibility of compliance …

Quantifying Uncertainty In Landscape Evolution And Provenance Analysis: Insights From Statistical And Numerical Modelling, Vivian Carmello Grom

LSU Doctoral Dissertations

Landscape evolution models (LEMs) and detrital zircon provenance are widely used to investigate Earth surface processes, yet both face challenges related to quantifying model behavior and interpreting sedimentary signals under realistic, heterogeneous conditions. This thesis addresses these challenges through analysis and case studies that develop and apply new approaches for analyzing landscape dynamics and assessing uncertainties in sediment provenance.

Chapter 1 introduces a quantitative framework for evaluating LEM outputs using Shannon Entropy, Moran’s I, and Geary’s C. Applied to simulations with steady uplift, periodic uplift, spatially variable uplift, and a timeseries of DEMs, these metrics capture spatial organization and information …

Key To Spartina Of The West Coast Based On Vegetative Characteristics, Mary Pfauth, Mark D. Sytsma, Mitchell Kloer, Jennifer Riddle, Jacob Rose, Gabriel E. Campbell

Center for Lakes and Reservoirs Publications and Presentations

In their natural condition, Pacific Coast estuaries have extensive open mudflats in the intertidal area that are important shorebird feeding habitat and are used for oystering and recreational fishing. Several non-native cordgrass species are invading Pacific estuaries and damaging these functions and uses. Early detection is critical to effective management of cordgrass infestation. This key is intended to provide an easy-to-use reference for quick identification of Spartina (synonym: Sporobolus) species on the Pacific coast. We choose to focus on vegetative characteristics here, since flowers are not always visible when it can be advantageous to survey.

This publication is intended to …

Inferential Statistics For Industrial Organizational Psychologists: A Practical Guide For Testing Hypotheses Using R, Caitlin Lapine

Open Touro Created

2026

This text aims to provide a practical guide for students in industrial organizational psychology or related fields to complete inferential statistics using R open-source programming language. It provides information about when to use particular statistical analyses and how to perform those with statistical software.

Investigating Effects Of The Macroalga Caulerpa Prolifera On Restoration Of The Seagrass Halodule Wrightii In The Indian River Lagoon, Florida, Luciana M. Banquero

Graduate Studies Theses and Dissertations 2026

Seagrass restoration efforts have been motivated by global decreases in coverage associated with anthropogenic influences on the environment. In the Indian River Lagoon (IRL), FL, seagrass declined by 75% between 2011 and 2021. During this time, abundance of the macroalga Caulerpa prolifera increased substantially in the IRL. The macroalga is native to this estuary, however C. prolifera abundance has fluctuated widely in the past few decades. Being highly opportunistic, C. prolifera took advantage of areas formerly inhabited by seagrass. It is not known how dense, continuous beds of C. prolifera impact seagrass restoration projects or natural recovery of seagrass. Previous …