Digital Commons Network^™

Hallucination Detection In Scientific Writing: Quantification, Trend Analysis And Benchmarking, Adiba Ibnat Hossain

Graduate Research Theses & Dissertations

The landscape of scientific communication has undergone a significant transformation with the emergence and widespread adoption of Large Language Models (LLMs). LLMs have enhanced productivity and creativity in scientific writing, raising serious questions about the faithfulness and reliability of the generated content. A common problem in LLMs is hallucination, which occurs when models generate fluent but inaccurate or inconsistent content. When hallucinations enter scientific writing, the intended meaning may be distorted, coherence disrupted, and the study’s overall integrity threatened.

This thesis investigates hallucinations in scientific writing from both an analytical and dataset-driven approach. First, it offers a comprehensive analysis of …

Evaluating Planting Methods For Native Seed Production And Exploring Granivory In The Northern Great Plains, Allison Dollen

Electronic Theses and Dissertations

Temperate grasslands have faced immense losses due to land use change in the last 150 years and less than half of the overall grasslands that once covered North America remain today. A portion of historic and remaining U.S. grasslands are located within the northern Great Plains (NGP) region which is home to over 1,600 species of native plants and provides many ecosystem services and economic benefits. Initiatives to restore grasslands and their ecosystem services are currently underway, but barriers such as limited native seed supply and granivory hinder restoration efforts. My first chapter addresses knowledge gaps in planting methods for …

Fifty Years Of Research In The Commonwealth Of The Bahamas: A Quantitative Thematic Analysis Of Scholarly Output, Amina Moss, Krista D. Sherman, Williamson Gustave, Kathleen Sullivan Sealey, Charlotte Dunn, Nicola Simone Smith, Lindy Knowles, Christy Gibson

Gulf and Caribbean Research

This study presents the first longitudinal bibliometric mapping of peer—reviewed research on The Bahamas, analyzing 12,113 Web of Science records (1975–2025) using CiteSpace v.6.4.R2. We identified 36 co—citation clusters (modularity Q = 0.7967; silhouette = 0.9231) and 28 keyword clusters (Q = 0.7523; silhouette = 0.8695), revealing 8 thematic trajectories over 5 decades. Early research (prior to 1990) focused on carbonate geology and sea—level dynamics across the northwestern Bahama Platform and Blake—Bahama Basin (Cluster#0, silhouette = 0.939). From the 1990s–mid—2000s, attention shifted to marine fisheries, Aliger gigas, coral reefs, and ecological resilience (Cluster #1, n = 203). In the …

An Analysis Of Slms For Machine Translation Of Healthcare Documents, Wyatt Clausen

All Graduate Theses, Dissertations, and Other Capstone Projects

The language barrier creates significant healthcare challenges for patients who struggle with English. While large language models (LLMs) have advanced machine translation, their high computational costs, environmental impact, and risk of data breaches have raised concerns. Small language models (SLMs) can address these concerns and be further adapted to specific tasks through parameter-efficient fine-tuning (PEFT) methods, including Quantized Low-Rank Adaptation (QLoRA). This study compares the Spanish-to-English translation quality of two 7-billion-parameter SLMs, Mistral and Llama 2 7B, in the medical domain, using BLEU, chrF, and COMET as evaluation metrics. It further investigates whether QLoRA fine-tuning and Retrieval-Augmented Generation (RAG) on …

The Law Of The Mid-Transition, Alison Gocke

Michigan Law Review

To address climate change, our energy systems need to transition from fossil fuels to clean energy resources. There is a tendency to think this transition will occur in a linear, seamless progression: We will move from the (old) fossil fuel system at Time A to a (new) clean energy system at Time B. But this belies the reality that an energy transition involves not just building a new energy system, but also unwinding an old one. Crucially, both processes will take time. That means there will be a significant period in which both energy systems coexist.

In the engineering literature, …

Algorithmic Medicine And The Duty To Disclose: Informed Consent Through The Lens Of Radiology, Lee Rodriguez

Michigan Law Review

Informed consent is the law’s mechanism for protecting patient autonomy by requiring disclosure of facts that bear on the decision to accept or refuse care. Artificial intelligence now helps decide what is medically true for patients, yet informed consent law still assumes that diagnostic judgment is rendered by a human mind whose reasoning is at least in principle communicable. Radiology has become the leading setting for this tension. AI systems triage worklists, flag suspected abnormalities, and anchor first-pass impressions in ways that guide radiologists’ attention and, in practice, can coauthor diagnostic conclusions while remaining invisible to patients. When patients are …

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 …

Reclaiming Agency: Ai Hallucinations And Translingual Interrogations In The City Tech Writing Center,, Joseph Franklin, Anna Laura Falvey

Publications and Research

No abstract provided.

Near Real-Time Adaptive Isotropic And Anisotropic Image-To-Mesh Conversion For Cerebral Aneurysm Simulations, Kevin Garner, Chander Sadasivan, Nikos Chrisochoides

Computer Science Faculty Publications

This paper presents two performance optimization techniques for a mesh adaptation method that is designed to help streamline the discretization of complex vascular geometries within the numerical modeling process. This method is integrated into a pipeline with an image-to-mesh conversion tool to generate adaptive anisotropic meshes from segmented medical images. The pipeline is shown to satisfy quality, fidelity, smoothness, and robustness requirements while providing near real-time performance for medical image-to-mesh conversion. Tested with two brain aneurysm cases and utilizing up to 96 CPU cores within a single, multicore node on Purdue University’s Anvil supercomputer, the parallel adaptive anisotropic meshing method …

Sage: Spatially Aware Gene Selection And Dual-View Embedding Fusion For Domain Identification In Spatial Transcriptomics, Yi He, Yunpei Xu, Liqing Ding, Hong-Dong Li, Yaohang Li, Shaokai Wang

Computer Science Faculty Publications

Despite enabling high-resolution mapping of gene expression within tissues, spatial transcriptomics (ST) still faces challenges in accurately segmenting spatial domains due to complex tissue architecture and limitations of current methods. Most approaches rely on local spatial priors, lack gene-level interpretability, and fall short in capturing structure-discriminative genes or long-range functional relationships, limiting their ability to resolve biologically meaningful architectures. We present Spatially Aware Gene selection and dual-view Embedding fusion (SAGE), a unified and reproducible framework for domain identification in spatial transcriptomics that combines topic-driven gene selection with dual-view embedding fusion to address these gaps. SAGE integrates non-negative matrix factorization (NMF)-based …

Adaptive Self-Attention For Enhanced Segmentation Of Adult Gliomas In Multi-Modal Mri, Evan P. Savaria, Jiangwen Sun

Computer Science Faculty Publications

Every year there are an estimated 80,000–90,000 new glioma cases, highlighting the need for reliable imaging-based decision support. Although deep learning has improved tumor sub-region segmentation, many state-of-the-art models fail to fully capture complementary information across T1, T1Gd, T2, and FLAIR MRI modalities and often operate as “black boxes,” limiting physician trust when precise delineation is critical for surgical planning, radiation targeting, and treatment monitoring. To address these limitations, we propose AIMS, an Adaptive Integrated Multi-Modal Segmentation framework that maintains modality-specific feature streams and employs adaptive self-attention within a hierarchical CNN-Transformer architecture to prioritize and fuse multi-modal MRI features. We …

Voxvista: Enhancing Screen Reading Experience For Online User Comments, Yash Prakash, Akshay Kolgar Nayak, Mohammed Shoaib Alyaan, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Online discussions have become integral to how people exchange ideas, form opinions, and participate in collective deliberation. While sighted users can comfortably engage with online discussions, blind users who are dependent on screen readers are forced to listen to long threads narrated in a single, monotonic voice that lacks prosodic variation, rhythm, or emotion. This robotic auditory experience not only deteriorates the user engagement with the content but also increases cognitive strain, by making it difficult to remain attentive and discern meaning beyond literal words. In an interview study, most blind participants reported that monotonous narration hindered their ability to …

The Privacy Paradox Of Llms: User Perceptions And The Reality Of Pii Leakage, Shuai Cheng, Haitao Xu, Shu Meng, Shuai Hao, Chuan Yue, Zhao Li

Computer Science Faculty Publications

Large language models (LLMs) are increasingly deployed, yet they introduce significant privacy risks by disclosing personally identifiable information (PII) during interactions. Although prior work has demonstrated the feasibility of extracting PII from LLMs, no comprehensive study has evaluated the actual extent of PII leakage across mainstream LLMs or investigated user perceptions, literacy, and behavioral responses to these risks. To address these gaps, we conduct a large-scale evaluation of PII leakage in popular LLMs, demonstrating that attackers can extract email addresses and phone numbers with high success rates. Through a mixed-methods study involving 20 interviews and 204 survey participants, we identify …

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 …

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 Sustainable & Universal Redesign Of Hickory Hill Park In Richmond, Virginia, Ren Hollis, Cynthia Lin, Kira Miller, Jackson Nivera, Patrick O’Shea, Corinne Tsou, Hayston Wines

UROP Posters

Urban green spaces provide essential environmental, psychological, and physical benefits, yet access to these resources is often inequitable. Cities are increasingly vulnerable to climate change, highlighting the need for adaptive design. This study focuses on the redesign of Hickory Hill Park in Southside Richmond, selected through a combination of site suitability analysis and qualitative survey. The guiding research question is: How can a park in Richmond be designed to optimize environmental resilience, accessibility, and community benefits?

The selection of a research location and scope used a mixed-methods approach integrating spatial analysis, environmental assessment, and community engagement. A site suitability analysis …

Reduction Of Cr(Vi) With Infrared Light And Chemical Adsorption Of Cr(Iii) By A God-Crown/Bentonite Composite For Electroplating Waste Remediation, Andre Taufik Kurniawan, Muhammad Djoni Bustan, Sri Haryati

Applied Environmental Research

Heavy metal pollution, particularly chromium (Cr) from electroplating industrial waste, has severely threatened environmental quality and human health. This study aims to develop a composite adsorbent material based on bentonite and god crown biomass capable of removing chromium ions from liquid waste through a combination of reduction and adsorption mechanisms. The god crown/bentonite (GC/Bt) composite was synthesized at a mass ratio of 2:1 and calcined at 900°C. FTIR characterization revealed active functional groups (–OH, C=O, Si–O, and Al–O–Si), whereas BET analysis revealed a mesoporous structure (surface area 31.12 m2 g-1, pore diameter 4.37 nm) suitable for ion diffusion. The reduction …

Heavy Metals And Organic Carbon In Sediments Of Seagrass Sediments Of Trang Province, Thailand, Siriporn Pradit, Pornthep Wirachwong, Thongchai Nitiratsuwan, Sujaree Bureekul, Supraewpan Lohalaksanadech, Thawanrat Kobkeatthawin, Monticha Jirajaras, Prakrit Noppradit, Sanya Sirivithayapakorn

Applied Environmental Research

In this study, the accumulation of heavy metals (Cd, Cr, Cu, Fe, and Pb) in water, suspended sediments, sediments, and seagrass in Kalase Bay, Trang Province, Thailand, during the 2024 dry season was investigated. These findings indicate that the enrichment factor (EF) for all the metals was less than 1, suggesting that anthropogenic contamination is not a significant concern in the area. The translocation factor (TF) values were less than 1 for all the metals except Cu, whose TF was greater than 1; however, these values were not statistically significant, indicating limited phytoextraction capacity. The bioconcentration factor (BCF) values for …

Spatial Modeling Of Natural Disaster Risk By Integrating Hazard, Vulnerability, And Exposure Factors Using Geospatial Techniques : Evidence From Mueang Tak District, Thailand, Suphatphong Ruthamnong

Applied Environmental Research

This study presents a comprehensive multihazard risk assessment for Mueang Tak District, Thailand, that integrates hazard, vulnerability, and exposure (H-V-E) dimensions. By utilizing geographic information systems (GIS) and remote sensing, the analytic hierarchy process (AHP) was employed to prioritize critical risk factors. GIS analysis integrated multisource spatial data, including Landsat 9 and Sentinel-2 imagery, CHIRPS precipitation, and SRTM-derived topography, while AHP weights were established on the basis of expert judgment and socioeconomic indices such as the relative wealth index (RWI) and population statistics. The results delineate distinct spatial risk clusters: high landslide potential is concentrated in the steep terrain of …

Carbon Stock Assessment In Sonneratia Apetala Afforested Mangroves : A Case Study From Cox’S Bazar, Bangladesh, Mohammad Ismail, Sayed Abu Johany, Tanmoy Dey, Zakia Sultana Teasa, Trishna Das, Prabal Barua, Tonima Hossain, Sajib Ahmed

Applied Environmental Research

Sonneratia apetala is a key species for mangrove afforestation projects in Bangladesh and plays a crucial role in ecosystem restoration and carbon sequestration. The research on how the total carbon stock (TCS) varies across S. apetala plantations in Cox’s Bazar remains limited. Thus, in this study, the biomass and soil carbon stock were quantified across nine S. apetala afforested sites in Cox’s Bazar to assess spatial variation and influencing factors. The total biomass carbon (TBC) was calculated by summing the aboveground (AGBC) and belowground (BGBC) biomass carbon, while the soil organic carbon stock (SOCS) was determined from the 0–40 cm …

Seasonal Wastewater Monitoring And Quantitative Microbial Risk Assessment Of Escherichia Coli In A University Wastewater System, Pathum Thani, Central Thailand, Natsima Tokhun, Natagarn Tongphanpharn, Weerawat Ounsaneha, Montip Jankeaw, Wiriyabhorn Klomsungcharoen, Patsara Wongsudi, Yawanart Ngamnon, Cheerawit Rattanapan, Kwang Mo Yang

Applied Environmental Research

In this study, the physicochemical properties of wastewater were characterized, and a quantitative microbial risk assessment (QMRA) of E. coli was conducted in the wastewater treatment system of the Faculty of Science and Technology, Valaya Alongkorn Rajabhat University, under the Royal Patronage, Pathum Thani, Thailand (VRU-SciTech). This study was conducted because the current water-quality assessment does not include the QMRA or evaluate the occupa-tional and incidental public risk of infection. Over a one-year monitoring period, this study quantified wastewater generation (~6.09 L person-1 day-1; ~3.21 × 103 m3 year-1) and analyzed its physicochemical parameters and E. coli concentrations. High concentrations …

Evaluation Of Soil Moisture Content, Ph, And Dominant Microorganisms In Crude Oil–Contaminated Soil Treated With Cow Dung, Indole-3-Acetic Acid (Iaa), And Simulated Microgravity, Amenze Ovenseri, Tawari-Fufeyin P.

Applied Environmental Research

Crude oil negatively affects soil physicochemical properties and microbial activity, thereby hindering plant growth and posing notable environmental and agricultural issues. The combined effects of cow dung, indole-3-acetic acid (IAA), and simulated microgravity on the recovery of soil degraded by crude oil were explored using Zea mays as the test plant. Soil was contaminated with crude oil at different concentrations (0%, 1%, 3%, and 5% v/w), with each concentration comprising eight treatments: cow dung, Zea mays seeds exposed to microgravity, and IAA alone or in combination. Changes in plant height, soil pH, soil moisture content, and soil microbial diversity were …

Time Series Decomposition And Forecasting Of Alzheimer’S Disease Mortality Using A Kolmogorov-Zurbenko Filter, Jack D. Farrell

Electronic Theses & Dissertations (2024 - present)

Alzheimer’s disease mortality has substantially risen in recent history, placing a significant burden on public health infrastructure and highlighting the need for improved analytical methods to better understand mortality data patterns and offer reliable predictions. Time series methods often struggle to balance both accuracy and interpretability, which hinders the ability to gather meaningful insights from time series data. To address these limitations, this study applies the Kolmogorov-Zurbenko (KZ) filter to monthly U.S. Alzheimer’s mortality data spanning from 1999 to 2023 and decomposes the series into long-term trend, seasonal, and noise components on a logarithmic scale. Long-term trend accounts for 86.49% …

Entropic Dynamics Approach To The Classical Limit Of Quantum Mechanics: Decoupling Of The Center Of Mass Motion For A Mesoscopic Particle, Fatimah Judayba

Electronic Theses & Dissertations (2024 - present)

In the Entropic Dynamics (ED) approach, quantum mechanics is derived from the principles of entropic inference and information geometry. The ED approach differs from other interpretations by making a clear commitment to distinguishing which variables are ontic (real) and which are epistemic. The classical limit for the center of mass (CM) coordinate is achieved for a large number of particles, M →∞, while Planck’s constant ℏ remains finite. Typically, the emergence of the classical limit requires decoherence through interactions with the external environment. In this work, we investigate whether the classical behavior of the CM coordinate in a mesoscopic system …

Developments And Applications Of Transport Of Intensity Equation Imaging And Optical Diffraction Tomography In Bioimaging, Shane D. Carney

Electronic Theses & Dissertations (2024 - present)

Non-invasive imaging schemes are highly sought after methodologies in biology and metrology, where maintaining the physical state of a sample is important. Quantitative phase imaging (QPI) techniques non-invasively reconstruct the relative phase delay imparted onto an optical field due to transmission through a sample. Phase delay is proportional to the thickness and refractive index of the sample, but is lost in the intensity measurement process. Digital holographic microscopy (DHM) and transport of intensity equation (TIE) phase imaging are two high-resolution QPI techniques. DHM is a well-researched, accurate, and widely implemented technique, but can be difficult to implement in labs without …

Cross-Temporal Statistical Approaches For Evaluating Predictor-Outcome Relationships, Jeff Joseph

Dartmouth College Ph.D Dissertations

Central auditory function is linked with cognitive deficits, but few research projects use existing statistical approaches or develop new ones to forecast cognitive deficits using the results of central auditory tests. To address this limitation, we use a series of statistical learning frameworks for predicting a child’s cognitive abilities based on his/her central auditory performances and demographic factors. Two key challenges exist. First, children may start the study at a time when they are unable to perform the central auditory tests or cognitive tests. Second, cognitive performance is age-dependent, particularly in the early formative years of childhood and adolescence. To …

Final Annual Operations And Maintenance (O&M) Report: Butte Treatment Lagoon (Btl) System – 2023, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Charge Transport Modeling Of Multifunctional Molecular Transistors, Romena Akter

Graduate Studies Theses and Dissertations 2026

Distinguishing between the current–voltage characteristic curves associated with different transport mechanisms in a molecular electronic device and an artifact arising from device-level disorder is a central challenge in the study of molecular electronics. Characterizing these mechanisms and connecting them qualitatively to molecular-level orbital alignment, electrode coupling, voltage division, energetic disorder, and reorganization energy requires not only experimental data but also a rigorous theoretical framework for extracting physically meaningful parameters from measured transfer characteristics. This dissertation addresses this challenge in Chapters 2, 3, and 4 by developing and applying four complementary transport models —Simmons tunneling, single-level Landauer, Marcus hopping, and McConnell …

Life Cycle Assessment Of Co2-To-Methanol: Comparative Evaluation Of Direct And Alcohol-Assisted Hydrogenation Routes, Chayet Worathitanon, Naphat Chansonthi, Pawat Pinthong, Kritsana Suwanamad, Viganda Varabuntoonvit

Applied Environmental Research

The increasing severity of global warming, primarily driven by greenhouse gas emissions, underscores the urgent need for CO2 reduction and utilization strategies. Converting CO2 into methanol presents a promising approach, as methanol serves both as a fuel and a feedstock in various industries. This study evaluates the life cycle environmental impacts of three methanol production routes: (1) direct CO2 hydrogenation, (2) ethanol-assisted CO2 hydrogenation, and (3) propanol-assisted CO2 hydrogenation. Two energy scenarios are considered: conventional energy and wind power. Process simulations were performed using Aspen Plus V.14, and inventories were analyzed through Life Cycle Assessment (LCA) using the ReCiPe 2016 …

Activated Carbon Prepared From Residual Eucalyptus Wood For The Removal Of Methyl Orange: Equilibrium, Kinetics, Thermodynamics, And Desorption, Mathin Jaikua, Phuthidhorn Thanaphu, Sunisa Ungwiwatkul, Jakkrawut Maitip, Kanyarak Prasertboonyai

Applied Environmental Research

This research utilizes activated carbon derived from residual Eucalyptus wood (EW) for the removal of methyl orange (MO). The residual Eucalyptus wood-based activated carbon (EWAC) was produced through carbonization at 400 °C (EWC) followed by activation with a mass ratio of H3PO4 to EWC of 1:3, which was conducted at 800 °C for 1 h. The characterization of the EWAC involved various analytical techniques, including FTIR, XRD, BET, and CHN analysis. The adsorption parameters, such as pH (range: 3–8), adsorbent dose (range: 0.01–0.5 g per 50 mL of MO solution), contact time (range: 5–720 min), initial MO concentration (range: 5–600 …