Digital Commons Network^™

Serum Biomarker Trajectory Clusters Predict Functional Outcome And Quality Of Life For Traumatic Brain Injury, Thanh Son Do, Chantal Carnes, Zhihui Yang, Firas Kobeissy, Hamad Yadikar, Gayla R. Olbricht, Olli Tenovuo, Jussi P. Posti, Ewout W. Steyerberg, Lindsay Wilson, Nicole Von Steinbüchel, Endre Czeiter, Andras Buki, David K. Menon

Mathematics and Statistics Faculty Research & Creative Works

Serum brain-enriched biomarkers are increasingly employed in the clinical evaluation of traumatic brain injury (TBI) to assist with triage, neuroimaging decisions, and prognostication. However, the potential of temporal biomarker trajectories to inform disease monitoring and long-term outcomes remains underexplored. We aim to identify distinct biomarker trajectory (TRAJ) profiles in traumatic brain injury patients and to examine their associations with long-term clinical outcomes. The study included 373, CT-positive Intensive Care Unit (ICU) traumatic brain injury patients (256 with initial Glasgow Coma Scale 3–12) from the Collaborative European Neurotrauma Effectiveness Research in TBI (CENTER-TBI) core study who had at least two serum …

Digital Twin Freshness Maximization In Edge Computing, Jing Li, Jianping Wang, Weifa Liang, Quan Chen, Sajal K. Das, Xiaohua Jia

Computer Science Faculty Research & Creative Works

Mobile Edge Computing (MEC) shifts powerful computing resource provisioning from remote powerful data centers to the edge of core networks. Meanwhile, Digital Twin (DT) has surfaced as a promising technology to provide comprehensive and dynamic descriptions of physical objects in cyberspace with bidirectional and real-time interactions. Moreover, Internet of Things (IoT) devices have contributed abundant, heterogeneous and continuous data from interconnected devices to the explosion of DTs. With technologies evolution, there is an increasing necessity to address the freshness of both DT states and DT data, through timely synchronizations between DTs and their objects in a highly dynamic IoT environment. …

On-Device Artificial Intelligence Solutions With Applications To Smart Environments, Fabrizio De Vita, Dario Bruneo, Sajal K. Das

Computer Science Faculty Research & Creative Works

Recent advances in Artificial Intelligence (AI) and the increasing availability of computational power have accelerated the diffusion of Intelligent Cyber-Physical Systems (ICPSs), enabling smart applications with reasoning capabilities. However, the limited resources of embedded and Edge devices significantly constrain the complexity of deep learning models that can be effectively deployed. Traditional approaches rely on cloud-based training and edge-only inference, a paradigm that becomes inadequate when low latency, privacy, security, and high customization are required. In this context, On-device AI is emerging as a new paradigm in which both training and inference are performed directly on the device, avoiding data transfer …

Pahina: Precision-Aware Hierarchical In-Network Aggregation For Edge Distributed Training, Yingpu Nian, Bo Yi, Qiang He, Xingwei Wang, Geyong Min, Keqin Li, Sajal K. Das

Computer Science Faculty Research & Creative Works

The rise of edge intelligence is driving distributed machine learning toward a new paradigm of edge-collaborative computing. To overcome the severe communication bottleneck in this paradigm, In-Network Aggregation is a critical enabling technology. However, its effectiveness is fundamentally undermined by the profound resource heterogeneity of edge networks. Specifically, edge devices, adapting to hardware constraints, operate at varying numerical precisions, leading to significant data inflation as gradients are aggregated. Compounding this, unevenly distributed network resources and traditional, precision-oblivious routing strategies often misallocate critical, high-precision gradients to low-quality paths. This mismatch creates severe network congestion, crippling the efficiency of distributed training. To …

Leading The Change: Staff-Driven Ai Transformation In Smu Libraries’ Collection Team, Siew Khim Lim, Fion Goh

Research Collection Library

Why do libraries need to use AI? It is crucial for Libraries to stay relevant in this digital age by improving efficiency, access, and user experience. By adopting AI, libraries can better manage growing digital collections, provide innovative services, and ensuring they remain essential as hubs for knowledge and learning in an AIdriven world.

High-Resolution Infrared Spectroscopy Of Jet-Cooled 1-Butene, Vladyslav Filatov

Chemistry Honors Papers

A high-resolution absorbance spectrum of 1-butene was obtained in the 994–1000 cm⁻¹ region using a quantum cascade laser-based spectrometer coupled with a supersonic jet expansion source. To mitigate the low number density of the molecular jet, a multi-pass optical configuration was employed to achieve an effective path length of approximately six passes. Experimental spectra were calibrated using a methanol reference and etalon. Supporting calculations for vibrational frequencies and rotational constants were performed at the MP2/cc-pVTZ level of theory. The observed spectral features were assigned to the vibrational band ν25 (centered at 993.67 cm⁻¹), which was identified as a primarily a-type …

Using Nmr Spectroscopy And Linear Discriminant Analysis To Molecular Profile Varietal Honey, Taylor Mac

Master's Theses and Doctoral Dissertations

In recent years, varietal honey has been a massive target of adulteration through mislabeling and the addition of other sugars. Unethical companies do this to cut production costs while still charging the consumer full price. Previous studies have used nuclear magnetic resonance (NMR) to unravel possible adulteration in honey, but currently, there are no standard rapid methods to authenticate varietal honey. In our research, we collected NMR signatures (“fingerprints”) and combined them with linear discriminant analysis (LDA) to predict the varietal, country, and region of varietal honey. As a part of the project, we investigated whether an adjustment to the …

Aim5b: Ai Integrated Semantic Framework For 5g And Beyond Network Management, Thanveer Sulthana, Ava Sharif Jourabchi, Venkat Rao Manavarthi, Jayadithya Nalajala, Ankitha Srirama Reddy, Baek Young Choi, Sejun Song

Computer Science Faculty Research & Creative Works

Scalable, interpretable, and intelligent network monitoring and management are critical for 5 G and future networks. This paper introduces Aim5B, an AI-integrated semantic framework for 5 G and beyond network management to address these challenges. Aim5B processes unstructured logs from key 5G core network functions, and transforms them into a knowledge graph aligned with the semantic structure of control-plane events. Leveraging a large language model (LLM), Aim5B enables natural language queries to be translated into Cypher graph queries, facilitating precise log retrieval, event analysis, temporal correlation, and statistical summarization-without relying on static parsing rules or predefined dashboards. Integrated on a …

Triangulating Primary Sources, Professional Judgement, And Llm-Generated Summaries: Educating Nurses In An Ai-First World, Sarah Oerther, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Synthesis Of The Naga(S1−Xsex)2 Solid Solution From Mechanically Activated Precursors, Louisiane Verger, Julien Trébosc, Santhoshkumar Sundaramoorthy, Amitava Choudhury, Olivier Hernandez, Eric Furet, Sébastien Chenu, David Le Coq, Laurent Calvez, Olivier Lafon

Chemistry Faculty Research & Creative Works

NaGaS₂ and NaGaSe₂ are two recently discovered compounds that crystallize in the same structure type. In this work, NaGa(S_1−xSe_x)₂ (x = 0.5, 0.75 and 1) are prepared using an alternative synthesis route, mechanochemistry followed by heat treatment. Na₂S, Na₂Se, Ga₂S₃ and Ga₂Se₃ are milled in stoichiometric proportions. Differential scanning calorimetry, X-ray diffraction and solid-state nuclear magnetic resonance (²³Na and ⁷¹Ga) show that the compounds after milling are composed of crystalline NaGa(S_1−xSe_x)₂ with an amorphous part. …

Raw Data For The Manuscript "Silicon-Stabilized Three-Dimensional Covalent Networks In High Entropy Diborides", Michael Yeung, Reza Mohammadi

Chemistry Department Faculty Scholarship

Abstract for data:

Raw data for the journal publication, Silicon-stabilized three-dimensional covalent networks in high entropy diborides. ReadMe file provided.

Abstract for Journal publication: 

High entropy ceramics offer a pathway to stabilize unconventional chemistries beyond traditional alloying rules. We report the incorporation of silicon into an AlB₂-type high entropy diboride, Cr_0.2Nb_0.2Si_0.2Ta_0.2Ti_0.2B₂, despite silicon violating classical Hume-Rothery rules for alloying. Arc melting produced a phase-pure, chemically homogeneous structure, as confirmed by powder X-ray diffraction (pXRD) and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM–EDS). Silicon occupies …

Greenhouse Gas Report For Western Australian Wild-Catch Fisheries And Aquaculture 2004-2025, Christophe D'Abbadie, Johnny Machon, Dipesh Maharjan, Mark Goninon, Pia Dobson, Jason How, Rodney Duffy Dr., Ainslie Denham, Shaye Carman, Trina Anderson

Climate Science Published Reports

This report provides a comprehensive analysis of greenhouse gas (GHG) emissions from Western Australian wild-catch fisheries and aquaculture for the fiscal years (FY) 2004/05 to 2024/25. These industries represent important components of the Western Australian primary production sector, with distinct emissions profiles and trends.

Key Findings:

Emissions from wild-catch fisheries have declined significantly over time, from approximately 0.341 million tonnes of carbon dioxide equivalent (Mt CO₂e) in FY 2004/05 to 0.136 Mt CO₂e in FY 2024/25, a reduction of approximately 60%.

Emissions from aquaculture in FY 2024/25 were approximately 0.350 Mt CO₂e, reflecting substantial industry growth from near-negligible levels in …

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, …

Type Ii Diabetes Treatment Comparison Via Compartment Modeling, Abigail M. Collins

Theses and Dissertations

Type II diabetes mellitus affects one in ten adults worldwide, yet the effects of treatment type and adherence level on developing complications and quality of life have not been well characterized at the population level, and mathematical modeling offers a structured way to examine these dynamics. This thesis adapts the Boutayeb et al. (2004) model to incorporate dynamic treatment types and levels of adherence, producing nine scenarios in which complication development rate and complication recovery rate differed, to compare peak complications and quality of life across treatment and adherence conditions. Using a system of ordinary differential equations and compartment modeling, …

Fostering A Growth Mindset In Mathematics: Faculty And Student Experiences, Yolanda G. Rush

Theses and Dissertations

According to the Center for Community College Student Engagement (2019), many students attending two-year institutions need productive persistence strategies, including the development of a growth mindset. Although some growth mindset interventions have been effective in improving academic achievement among students (Boaler, 2016; Canning et al., 2024) and persistence (Lewis, 2019) among students, especially those with developmental needs (Suh et al., 2019) and those in mathematics, little is known about the experiences of students and teachers (i.e., students’ perceptions of teachers’ intentions and implementation) as teachers work to foster a growth mindset culture (Murphy et al., 2021). In this dissertation, I …

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.