Physical Sciences and Mathematics Commons^™

Shaping The Future: Emerging Technologies And Their Role In Industry 4.0 And Beyond, Liuliu Qin

Information Technology & Decision Sciences Faculty Publications

This paper provides a comprehensive review of emerging technologies driving the transition from Industry 4.0 to Industry 5.0. It examines the foundational concepts and pillars of Industry 4.0 and explores the transformative roles of Artificial Intelligence (AI), Extended Reality (XR), Collaborative Cobots (Cobots), Brain–Computer Interfaces (BCIs), quantum technologies, and next-generation connectivity (5G/6G). By integrating technological, human-centric, and sustainability perspectives, the study outlines how these emerging technologies reshape industrial systems and enable intelligent, adaptive, and inclusive futures.

Impacts Of Native And Nonnative Plant Species On Avian Community Diversity, Matty John Mackay, Steven Van Dang, Brandon Lee Corn

SPARK Symposium Presentations

Avian communities play an essential role in maintaining a healthy ecosystem dynamic by regulating insect populations, assisting in plant pollination, and seed dispersal. These contribute to the overall health of natural ecosystems and mitigate ecological disruptions that would arise in their absence. However, the introduction of non-native invasive plant species can interrupt the balance avian communities bring to ecosystems by reducing availability of food sources, altering habitat structures, increasing competition among individuals, and disrupting ecological relationships through rapid invasion of ecological spaces. Point count observations of birds at Shelby Bottoms Park, Nashville, Tennessee in areas dominated by non-native privet and …

Assessing Radio Transmitter Weight Effect And Evaluation Of Northern Bobwhite Chick Survival In Coastal North Carolina, Autumn S. Randall, Theron M. Terhune Ii, Matthew T. Springer, Darin J. Mcneil

Forestry and Natural Resources Faculty Publications

Studies on the earliest life stages are essential to our ecological understanding of avian demography; however, monitoring technologies that allow tracking of small birds are still limited in a variety of ways. One critical limitation, until recently, has been the development of methods for attaching transmitters to young birds with precocial development (e.g., Galliformes, Charadriiformes, etc.). The modified suture technique offers a means to attach transmitters to precocial chicks while accommodating rapid growth characterized by birds with precocial young. Although the sutured transmitter method was developed for northern bobwhite (Colinus virginianus) chicks, there remain key unknowns regarding best …

Aggregation Bias In Multi-Industry Economic Contribution Analysis: The Case Of Kentucky Forest Sector, Domena A. Agyeman, Thomas Ochuodho, Omkar Joshi

Forestry and Natural Resources Faculty Publications

Closely related industries are often aggregated in US forest sector economic contribution analysis, yet the choice of aggregation scheme can influence results. The Impact Analysis for Planning (IMPLAN) system is the most widely applied input–output model for forest economic contribution analysis in the US. In IMPLAN, the level of industry aggregation determines which inter-industry transactions are restricted, thereby influencing the magnitude of estimated indirect and induced effects. Although IMPLAN practitioners can model individual industries to avoid aggregation bias, they must still decide whether to analyze forest industries as a single group, as traditional subsectors, or individually. This decision can alter …

Effects Of Headwater Wetland Restoration On The Demography, Fecundity And Ecology Of The U.S. Federally Threatened White Fringeless Orchid (Platanthera Integrilabia) In The Cumberland Plateau Of Kentucky, Tara R. Littlefield, Catherine Hoy, Christopher Barton

Forestry and Natural Resources Faculty Publications

Wetland habitats represent a critical component of biodiversity hotspots that support numerous rare species, including terrestrial orchids. In North America, over half of all terrestrial orchids are found in wetlands, more than a quarter of which are now threatened with extinction (G1–G3). This concerning trend is exacerbated by a lack of information on effective restoration strategies aimed at orchids and other species that inhabit these areas. The white fringeless orchid, Platanthera integrilabia (Correll) Luer, the subject of this study, is restricted to mostly shaded wetland habitats along the Cumberland Plateau of the Appalachian Mountains and has suffered widespread declines due …

Discovery Of Tidal Disruption Event Candidates In The Hubble Catalog Of Variables, Elliot M. Schweitzer

Pitzer Senior Theses

A tidal disruption event (TDE) occurs when a star passes within the tidal radius of the supermassive black hole (SMBH) likely to reside at the center of most galaxies. Within this radius, the star is torn apart as tidal forces overcome the star's binding energy, and roughly half of the stellar debris spirals back towards the SMBH. The formation of an accretion disk produces bright emissions for months to years, modeled to peak in the ultraviolet and extend well into x-ray and optical wavelengths. TDEs occur only about once every 10⁴-10⁵ years per galaxy. As one of …

Mathematics And Political Ideology: A Historical Argument Against The Cultural Understanding Of Mathematics As An Apolitical Field, And A Journalistic Report On The Impact Of The Trump Administration On American Mathematics In 2026, Philo Judson

Pitzer Senior Theses

The interplay between political ideology and mathematics is a recurring theme throughout the history of the academic field. Mathematics has been used as a tool of empire, while mathematicians have been elevated by states as symbols of national genius for political prestige. Political ideologies have also shaped the field from within, both through the suppression of mathematical thought and the enforcement of mathematical authority. Since 2025, the Trump administration has launched large-scale political attacks on American institutions of higher education, which include lawsuits, discrimination investigations, and the removal of federal funding from certain institutions that don’t adhere to the administration’s …

Beyond Fixed Thresholds: Per-Label Calibration For Fine-Grained Emotion Detection On The Goemotions Dataset, Sai Puneet Naga Venkata Subramanyam Patchipulusu

Selected Full-Text Master Theses 2021-

This study investigates the effectiveness of five community fine-tuned transformer models for fine-grained emotion detection on the GoEmotions dataset: SamLowe/roberta- base-go_emotions (RoBERTa-base), cirimus/modernbert-base-go-emotions (ModernBERT), mrm8488/deberta-v3-base-goemotions (DeBERTa-v3-base), bhadresh-savani/bert-base-go- emotion (BERT-base-cased),and tasinhoque/distilbert-go-emotions (DistilBERT) . While the original GoEmotions research by Demszky et al. (2020) established a BERT-base baseline with a macro-F1 of 0.46, this thesis extends that work through independent empirical evaluation of five derivative models, systematic per-label threshold optimization, and comparative analysis of architectural trade-offs across the full transformer model family. Using the GoEmotions simplified test split (5,427 examples across 28 categories), all five models were evaluated at a fixed 0.5 …

Establishing A Public Health Surveillance System For The Opioid Crisis: The Experience Of The Healing Communities Study, Bridget Freisthler, Daniel J. Feaster, Charles Knott, Marc Larochelle, John Mccarthy, Svetla Slavova, Sharon L. Walsh, Jennifer Villani

Biostatistics Faculty Publications

Introduction: Efforts to reduce opioid overdose deaths in the United States have been stymied by the lack of timely and standardized population-level data for local, state, and national levels. The U.S. has a strong national need for linking opioid and other drug overdose surveillance data to service utilization data for overdose prevention and treatment to inform resource allocation and response planning.

Methods: We provide insight on the challenges of identifying, obtaining, and harmonizing administrative outcome data across four states using the collective experience from the HEALing Communities Study to test a community-engaged, data-driven, population-level intervention to reduce opioid overdose deaths. …

Previsit Ai: A Retrieval-Augmented Generation For Patient Readiness In Clinical Encounters, Rolande Umuhoza

All Graduate Theses, Dissertations, and Other Capstone Projects

With healthcare systems under growing pressure from rising patient volumes and shrinking consultation windows, improving how patients communicate with physicians has become essential to delivering quality care. Yet patients routinely arrive at appointments unable to clearly describe their symptoms, recall their medical history, or articulate concerns, contributing to miscommunication, diagnostic inefficiency, and pre-visit anxiety. This study introduces PreVisit AI, a conversational system designed to address this gap through structured, knowledge-based patient preparation. The system is built on a Retrieval-Augmented Generation (RAG) architecture combining HuggingFace sentence embeddings (all-MiniLM-L6-v2), a Chroma vector store, and Google’s Gemini language model over a curated seven-document …

Vision-Language System Using Open-Source Llms For Consent And Instruction Gestures In Medical Interpreter Robots, Tung Ngo, Emma Murphy, Robert Ross

Conference papers

Effective communication is vital in healthcare, especially across language barriers, where non-verbal cues and gestures are critical. This paper presents a privacy-preserving vision-language framework for medical interpreter robots that detects specific speech acts (consent and instruction) and generates corresponding robotic gestures. Built on locally deployed open-source models, the system utilizes a Large Language Model (LLM) with few-shot prompting for intent detection. We also introduce a novel dataset of clinical conversations annotated for speech acts and paired with gesture clips. Our identification module achieved 0.90 accuracy, 0.93 weighted precision, and a 0.91 weighted F1-Score. Our approach significantly improves computational efficiency and, …

Regulating Ai Beyond Product Liability, Shruti Trikanad

Michigan Technology Law Review

Artificial Intelligence (AI) is being used by governments across the world to enforce regulatory mandates, adjudicate benefits and privileges, predict and analyze risks, and much more. Although this has significant potential to increase efficiency and responsiveness, it also comes with several risks of transparency, government accountability, and the amplification of discrimination and bias. It is crucial we oversee and regulate these AI systems effectively. This essay argues against the models that current regulatory frameworks are adopting to govern AI use: those resembling product liability.

Through the lens of the European Union's AI Act and Liability Directive, it highlights the unsuitability …

Multimodal Ai For Ed Chest Pain Triage: Prediction Performance And Operational Impact, Yves Najm Mrad, Molham Aldeiri

Gulf Coast Division GME Research Day 2026

No abstract provided.

Co2 Enhanced Oil Recovery In The Dickinson Lodgepole Mounds, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about CO₂ enhanced oil recovery (EOR) in the Dickinson Lodgepole Mounds of Stark County, North Dakota. Includes geological information and how stored CO₂ increases local oil production.

Identification And Characterization Of Tornado Seismic Signals In The Central U.S., Seth Thompson

Theses and Dissertations--Earth and Environmental Sciences

Tornadoes cause extensive property damage and endanger lives. While Doppler radar can indicate the potential for tornado development, it cannot confirm that a tornado is in contact with the ground unless a debris signature is present. While on the ground, a significant amount of a tornado’s energy may be transferred into the earth as seismic vibrations. Thus, seismometers have the potential to detect on-the-ground tornadoes. Since 1960, only five papers have published seismic recordings from tornadoes. These studies have mostly reported on seismic waves generated by tornadoes at a relatively large range, from 0.01-2.5 Hz, representing uncertainty in the dominant …

Guitar Amplifier Directivity, Rachel C. Edelman, Brian E. Anderson, Samuel D. Bellows, Timothy W. Leishman

Directivity

No abstract provided.

Trustworthy Multimodal Ai For Medical Imaging: Enhancing Diagnosis, Reasoning, And Human-Agent Interaction In Extended Reality, Jai Prakash Veerla

Computer Science and Engineering Dissertations

The transition from traditional microscopy to digital pathology has digitized diagnostic data, yet clinical workflows remain constrained by two-dimensional screens and passive, opaque analysis tools that fail to capture the spatial complexity of biological systems. While Foundation Models now promise to reason across histology and genomics, a critical disconnect persists between the richness of this data and the limited cognitive bandwidth of clinicians, who currently lack the immersive interfaces and trustworthy agents necessary to utilize it effectively. This dissertation presents a unified framework for "Embodied Agentic AI," establishing a pipeline that augments physician capabilities through immersive visualization, robust security, and …

Modeling French Language Preservation: An Optimal Control Problem, Charlotte Blasi

Scripps Senior Theses

The French language is one of the most globally spoken languages, with over 300 million speakers and designated the official language of 29 nations. French continues to prosper as a result of its titular nations' imperialist history that emphasized linguistic diffusion as well as the support of international organizations dedicated to promoting both the language and the culture of French-speaking nations. In this thesis, we explore the nuanced history of French-speaking countries and one institution dedicated  to promoting the French language, the OIF. We further examine the media mechanism of the OIF and construct a system of Ordinary Differential Equations …

An Introduction To Modern Conversations On Knot Invariants, Stella Shah

Scripps Senior Theses

Knot Theory is a vast and diverse subfield of modern mathematics involving the classification and abstraction of knots and links. In this thesis, we wish to provide the necessary background for and an explanation of two papers in different subfields of knot theory, The Forbidden Quiver of a Link, and Biquandle Fares and Link Invariants.

In Chapter I, we begin with an introduction to knot theory and knot invariants. We continue to present the example of Fox Colorings, and conclude the chapter with an example of the Fox Coloring Number Invariant.

In Chapter II, we explore the derivation and utilization …

Balancing Wood And Food: Assessing The Drivers And Spatiotemporal Conflicts Of Eucalyptus Plantation Expansion In Guangxi, China, Wen H. Cai, Qiuxia Huang, Jian Yang, Le Yu, Yuanzheng Yang, Jiaxing Zu, Jiali Wang, Zhenxian Li

Forestry and Natural Resources Faculty Publications

Eucalyptus has become one of the most widely cultivated tree genera in subtropical China, generating significant economic returns but raising land-use conflicts with agriculture. Understanding the driving mechanisms behind this expansion is crucial for sustainable land-use management. To inform strategies for balancing wood production and agricultural stability, we investigated the spatiotemporal expansion dynamics and predicted the potential suitable habitat distribution of Eucalyptus plantations using a Boosted Regression Tree (BRT) model. Our analysis revealed three distinct spatiotemporal expansion phases. Crucially, this expansion has progressively shifted from marginal sloped terrain onto flat valley bottoms, intensifying the agriculture-forestry conflict in the region. Climatic …

Evaluating Sampling Strategies To Monitor Southern Fox Squirrel (Sciurus Niger Niger) Populations, Casey Robin Hitchens

Theses, Dissertations and Capstones

Reliable population monitoring is essential for evaluating wildlife translocations and informing conservation management, yet traditional monitoring approaches are often labor intensive and require prolonged sampling. This study evaluated marking techniques, survey methods, and population estimation approaches for monitoring a translocated population of southern fox squirrels (Sciurus niger niger) at Marine Corps Recruit Depot Parris Island, South Carolina, USA (MCRDPI). From January-June 2023, I conducted six live trapping and camera trapping sessions across five survey sites. I compared the performance of color-coded collars and tail shaves for individual identification and the recapture probability between live traps and camera traps. Logistic mixed-effects …

Impact Of Cross-Client Heterogeneity In Federated Learning For Real-World Plant Disease Classification, Ritesh Janga

All Graduate Theses, Dissertations, and Other Capstone Projects

Deep learning applications are being adopted in agricultural image analysis that include challenges of data privacy and limited institutional data and heterogeneity of different types of architectures. However, Federated Learning is a model that allows collaborative training on data that does not have to be shared among parties. Therefore, Federated Learning is an effective method of collaborative training; however, its comparative effectiveness as compared to individual (local) training on diverse architectures has never been examined in an agricultural context. The objective of this study was to examine Federated Learning for the purpose of crop disease classification on extreme non-IID distributed …

Rethinking Ai Literacy Education In Higher Education: Bridging Risk Perception And Responsible Adoption, Shasha Yu, Fiona Carroll, Barry L. Bentley

School of Professional Studies

As AI becomes increasingly embedded across societal domains, understanding how future AI practitioners—particularly technology students—perceive its risks is essential for responsible development and adoption. This study analyzed responses from 139 students in Computer Science, Data Science/Data Analytics, and other disciplines using both explicit AI risk ratings and scenario-based assessments of risk and adoption willingness. Four key findings emerged: (1) Students expressed substantially higher concern for concrete, explicitly stated risks than for abstract or scenario-embedded risks; (2) Perceived risk and willingness to adopt AI demonstrated a clear inverse relationship; (3) Although technical education narrowed gender differences in risk awareness, male students …

Computationally Modelling Nmda Blockages Within A Neural Network, Anya Raetsch

UNH URC Open (2026 and after)

The N-Methyl-D-Aspartate (NMDA) Receptor is fundamentally important to memory formation within the brain due to its control of calcium entry into the cell.  In recent years, there has been an increased interest in long-term effects of NMDA blockages on the brain, due to the “re-wiring” of communication channels (synapses) between neurons. This project models the effects of NMDA blockages due to drugs such as Ketamine, and how the blocking of NMDA receptors affects firing rates, which can then be applied to studying long-term plasticity within the neural hierarchies. Using the Nest Online Simulator, a 50x50 grid of neurons was created …

Soil Organic Carbon And Soil Health Property Responses To Land Management Across Topographic Positions, Mia D. Makovsky

All Graduate Theses, Dissertations, and Other Capstone Projects

uring the last ice age, ice sheets advanced and retreated across the upper Midwest, leaving behind a landscape characterized by poorly drained hummocky topography. Well-aerated soils have formed on uplands and lowlands are dominated by hydric soils. These wetlands and hydric soils have potential to store large quantities of carbon, particularly compared to the well-aerated uplands, but many have been drained and cultivated for decades. Conservation agriculture methods have emerged to protect and conserve soil health from negative effects due to cultivation.The purpose of this study is to determine how agricultural management practices and landscape properties (e.g, topographic position) affect …

Reinforcement Learning-Enabled Control And Design Of Rigid-Link Robotic Fish: A Comprehensive Review, Nhat Dinh, Darion Vosbein, Yuehua Wang, Qingsong Cui

Faculty Publications

With the rising demand for maritime surveys of infrastructure, energy resources, and environmental conditions, autonomous robotic fish have emerged as a promising solution with their biomimetic propulsion, agile motion, efficiency, and capacity for underwater inspection, monitoring, data collection, and exploration tasks in complex aquatic environments. Inspired by fish spines, rigid-link fish robots (RLFRs), a category of robotic fish, are widely utilized in robotics research and applications. Their rigid, actuated joints enable them to reproduce the undulatory locomotion and high maneuverability of biological fishes, while the modular nature of rigid links between joints makes them cost-effective and easy to assemble. This …

Fulbright Project In Iceland In The Summer Of 2026, Irina Filina

Nebraska Academy of Sciences: Programs and Proceedings

This upcoming Fulbright project is inspired by an ongoing debate in the scientific community about the tectonic origin of Iceland. A long-standing theory of Iceland’s formation by excessive magmatism at the Mid-Atlantic spreading center over the well-known hot spot (i.e., oceanic crustal affinity) was recently challenged by the alternative hypothesis that the Icelandic crust is continental in nature and is being stretched and gradually modified by magmatic processes. Based on this hypothesis, a new sunken continent, Icelandia, has been proposed. One of the foundations for the proposed Icelandia is the presence of felsic lavas (indicative of continental flavor in the …

Ordered Mini-Batch Training For Differentially Private And Encrypted Logistic Regression, Ryan Leone

Theses, Dissertations and Culminating Projects

Logistic regression has found extensive use as a supervised machine learning algorithm due to its simplicity and efficiency in binary and multivariate classification tasks. As data sharing grows across connected devices, safeguarding sensitive personal and industrial information is of increased importance. Privacy-preserving machine learning techniques such as differential privacy and homomorphic encryption offer mathematically rigorous security guarantees, but introduce difficult accuracy, privacy loss, and computational overhead issues. This thesis investigates PPML for logistic regression through a collaborative mini-batch training framework. I propose and implement an ordered mini-batch strategy, compare it to standard shuffled methods, then integrate differential privacy noise injection …

A Deep Learning Approach For Mapping Shrubs, Wet Tundra And Surface Water In Arctic Tundra With Very High Resolution Satellite Imagery, Darko Radakovic

Theses, Dissertations and Culminating Projects

Arctic shrub expansion threatens to accelerate permafrost thaw through complex feedbacks, yet whether shrubs primarily indicate or drive degradation remains unresolved. This dissertation integrates deep learning analysis of two decades of satellite imagery with LiDAR canopy structure and radar soil moisture data to reveal that shrubs play a dual role: young, expanding shrubs signal active permafrost thaw, while mature, tall shrubs stabilize underlying permafrost through insulation. By demonstrating that vertical canopy structure predicts thaw depth better than cover extent alone, this work establishes a scalable framework for monitoring permafrost vulnerability across the rapidly changing Arctic. Arctic shrub expansion is accelerating …

Preliminary Investigation Of The Carbon Storage Potential In The Fort Worth Basin: Reservoir Characterization And Modeling Of The Lower Atoka Grant South Sand In Tarrant County, Texas, Mary Ann M. Moody

Earth & Environmental Sciences Theses

Carbon capture and storage (CCS) is crucial for mitigating atmospheric carbon dioxide (CO₂) emissions that rise from industrial activities. Paleozoic sedimentary basins in Texas are significant reservoirs for hydrocarbon production, and when depleted, show promise for CCS. Long-term reservoir storage suitability requires a multifaceted approach, including site screening and ranking, as well as reservoir characterization, modeling, and simulation. This project first evaluates the CCS potential for the Fort Worth Basin in North Central Texas, then focuses on reservoir characterization of the Lower Atoka Grant South (STH) Sand in Tarrant County and finally assesses the sand’s CO₂ storage …