Digital Commons Network^™

Characterizing The Transient Emission Of Particles And Gases From A Single Puff Of Electronic Cigarette Smoke, Kashala Fabrice Kapiamba, Steven Achterberg, Ta Chun Lin, Philip D. Whitefield, Yue-Wern Huang, Yang Wang

Chemistry Faculty Research & Creative Works

This study employed high-time-resolution systems to examine the transient properties of aerosols and gases emitted from electronic cigarette (EC) puffs. Using a fast aerosol sizer, we measured particle size distributions (PSDs) across various EC brands (JUUL, VUSE, VOOPOO), revealing sizes ranging from 5 to 1000 nm at concentrations of 107 to 1010 cm-3. Most aerosols were found to be in the ultrafine range (below 100 nm), with JUUL-, VUSE-, and VOOPOO-producing aerosols with geometric mean sizes of 19.9, 47.3, and 29.4 nm, respectively. Applying the International Commission on Radiological Protection (ICRP) deposition model and assuming no further evolution of aerosols …

Instantaneous Hydrolysis Of Methyl Paraoxon Nerve Agent Simulant Is Catalyzed By Nontoxic Aminoguanidine Imines, Emmanuel Kingsley Darkwah, Puspa Aryal, Chi Zhang, Charles B. Musgrave, William A. Goddard, V. Prakash Reddy

Chemistry Faculty Research & Creative Works

Exposure to organophosphate-based nerve agents and pesticides poses health and security threats to civilians, soldiers, and first responders. Thus, there is a need to develop effective decontamination agents that are nonhazardous to human health. To address this, we demonstrate that instantaneous hydrolysis of methyl paraoxon (Me-POX), a nerve agent simulant, can be achieved in the presence of aminoguanidine imines at pH 10: ● the pyridine-4-aldehyde aminoguanidine-imine (1) and ● the 2,3-butanedione aminoguanidine-imine (2). The hydrolysis of Me-POX under these conditions is substantially faster than that of the state-of-the-art decontaminating agent, Dekon-139 (2,3-butanedione oxime, potassium salt). Furthermore, Dekon-139 shows adverse effects …

Pla-Based Bone Tissue Engineering Scaffolds Incorporating Hydroxyapatite And Bioactive Glass Using Digital Light Processing, Engin Gepek, Fateme Fayyazbakhsh, Lev Suliandziga, Vadym Mochalin, Osman Iyibilgin, Yue-Wern Huang, Ming C. Leu

Chemistry Faculty Research & Creative Works

Bone tissue engineering (BTE) aims to repair bone defects using biocompatible materials with tailored geometries and pore structures, providing appropriate mechanical support and control over biodegradation kinetics to promote bone growth. In this study, we utilized digital light processing (DLP) 3D printing to fabricate scaffolds with varying pore sizes using polymer–ceramic slurries composed of polylactic acid (PLA) as the main polymer matrix, incorporated with hydroxyapatite (HA) and bioactive borate glass (BBG) at various ratios. We studied the effect of composition on rheological behavior, printability, mechanical properties, bioactivity, degradation rate, and biocompatibility. While HA increased viscosity and reduced printing accuracy, it …

Tricatalytic Organocatalyst-Enzyme Hybrid Cascade For Improving Complete Oxidation Of Glucose To Carbon Dioxide, Adam Milam, Rokas Gerulskis, Jose Intano, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Advancing energy harvesting is crucial for the development of wearable and implantable technologies. Given the high concentration of complex fuels, such as glucose, in biological fluids, biofuel cells present a promising avenue for exploration. However, glucose fuel cells that have been published to date typically catalyze only one or two of the maximum 12 oxidation steps for glucose, resulting in low energy density. Although known multienzyme cascades, which are sequential biochemical reactions where multiple enzymes work in tandem to convert a substrate into a final product, have addressed this inefficiency, they come with several trade-offs, such as reduced power density …

Verification Of Real-Time Smoke Simulations: A Case Study On Early Summer North American Wildfire Events, Daniel Bonilla

Pitzer Senior Theses

As wildfire intensity and frequency escalate in times of unprecedented climate change and severe droughts, it is important to enhance forecasting models that accurately and efficiently predict wildfire smoke movement. NOAA’s experimental Rapid-Refresh Forecasting System with Smoke and Dust (RRFS-SD) aims to improve upon the High-Resolution Rapid Refresh- Smoke (HRRR-Smoke), by extending the domain to include all of North America and incorporating new developments in physics and wildfire parameterizations. Our work explores the process of adding satellite Aerosol Optical Depth (AOD) data, through AERONET, as an additional method of verification of the RRFS-SD experimental model. Using a case study on …

Optimizing Decision-Making In A Cerebral Palsy Model Using Reinforcement Learning, Richard Ampah

Pitzer Senior Theses

This study presents an original interdisciplinary investigation into how reinforcement learning (RL) can model motor and cognitive defects and potentially improve motor and cognitive functions in individuals with cerebral palsy (CP), a non-progressive neurological disorder that impairs movement and adaptability. Integrating computational neuroscience and machine learning, the research applies policy gradient methods and Markov Decision Processes (MDPs) to simulate adaptive learning in agents with and without CP-related constraints.

The central aim is to compare the cumulative rewards of optimal policies, derived from value iteration, and human-like learning policies using the REINFORCE algorithm, both with and without the Bellman baseline. The …

The Anatomy Of A Reconstruction: From Fourier Space To Image Recovery In Computed Tomography, Charlotte P. Maurer

Honors Theses

This thesis develops the mathematical foundations of computed tomography (CT) reconstruction through the lens of harmonic analysis. Beginning with the Schwartz class, we introduce the Fourier transform and its role in expressing the Radon transform and its inversion via a fractional Laplacian. After constructing the Radon transform in general dimension R^d, we specialize to the cases d = 2 and d = 3, demonstrating explicit inversion formulas and the associated instability in lower dimensions. For its computational advantages, we study filtered back-projection using classical low-pass filters (Ram-Lak, Shepp–Logan, Cosine, Gaussian) and formulate a discrete reconstruction algorithm grounded in …

Predicting Human Steering From Optic Flow Using Deep Convolutional Neural Networks, Katie E. Bernard

Honors Theses

Human driving is a complex visuomotor task and the specific visual clues that guide it remain under investigation. While prior research has emphasized gaze-based strategies such as the Tangent Point and Future Path hypotheses, recent evidence highlights the potential role of optic flow, the visual motion pattern perceived during self-movement, as critical to steering ability. This thesis explores whether raw optic flow alone can support accurate predictions of human steering behavior. We trained a convolutional neural network to map optic flow vector fields to steering angles in a virtual reality driving simulation. The dataset, collected by Giguere et al., included …

Microbial Degradation Of Kelp-Derived Dissolved Organic Matter In The Context Of Carbon Sequestration, Sophia N. Riazi-Sekowski

Honors Theses

Kelp, or brown algae, is an emerging form of ocean-based biological carbon dioxide removal, converting dissolved CO2 into organic molecules via photosynthesis. The export of detritus and dissolved organic carbon (DOC) from coastal beds to beyond the continental shelf contributes to carbon sequestration, especially through the microbial production of refractory DOC (RDOC). The influence of microbial degradation on kelp-derived DOC is not yet well understood, contributing to inconsistency in carbon sequestration estimates. This study utilizes dark bottle incubations of both blades and holdfasts from two farmed kelp species in the Gulf of Maine — Saccharina latissima and Saccharina angustissima — …

Wave Reflections In A Biophysically Detailed Model Of Cardiac Tissue, Grace Moberg

Honors Theses

Regular heart rhythms are governed by the coordinated spread of action potentials through cardiac tissue. The interaction of an action potential with a tissue heterogeneity may lead to a reflection, where both a retrograde and an anterograde wave propagate off of the initial impulse. Reflections have been experimentally linked to cardiac arrhythmias, but their mechanisms of generation are not well-understood. Mathematically, reflections in phenomenological models of cardiac tissue have been linked to an unstable periodic orbit. These models typically sacrifice detail about the variety of ionic currents and processes involved in action potential propagation in favor of mathematical simplicity. Biophysically …

Identifying The Spread Of Invasive Jumping Worms Across Maine’S Forests Using Soil Edna, Rebecca Wanger

Honors Theses

Jumping worms of the Megascolecidae family are invasive earthworms from East Asia that have been spreading across the United States since the late 1800s (Chang et al., 2021). Recently, the earthworms have gained more attention for their expansion into northeastern states, as they are believed to have negative impacts on the soil biogeochemistry, flora, and fauna of these forest ecosystems that have had no native earthworms given the recent nature of the Last Glacial Maximum (~11,000 yrs ago; Bohlen et al. 2004; McCay et al. 2020). The earthworms are distinguished by their thrashing behaviors, milky-white smooth clitellum, and evenly spaced …

Transient Transmembrane-Electrostatically Localized Protons And Transmembrane Potential In A Laser Flashed Bacteriorhodopsin Purple Membrane Open Flat Sheet - Summary, James Weifu Lee

Chemistry & Biochemistry Faculty Publications

The transmembrane-electrostatically localized protons/cations charges (TELCs, also known as TELPs) model may serve as a unified framework to explain a wide range of bioenergetic phenomena. Transient transmembrane-electrostatically localized protons (TELPs) and transmembrane potential in a laser flash-energized bacteriorhodopsin (bR) purple membrane (PM) open flat sheet are now better analyzed. Under the Heberle et al. (1994) experimental conditions, the number of bR molecules is now calculated to be 8200 per PM open flat sheet with a diameter of 600 nm. With a single-turnover laser flash intensity of 3 mJ/cm² to photoexcite 10% of the bR molecules, the laser flash-induced peak TELCs …

From Walking To Parkour: A Structured Survey Of Rl For Dynamic Skills In Legged Robots, Christopher Allred, Chandler Justice, Rosario Scalise, Yan Gu, Jonathan Clark, Mario Harper, Jason Pusey

Computer Science Student Research

This survey reviews recent advances in applying reinforcement learning (RL) to enable dynamic and ballistic motions in legged robots, including running, jumping, stair climbing, and parkour. Focusing on high-agility behaviors that challenge traditional control frameworks, we categorize foundational locomotion tasks and highlight the RL methods, such as Proximal Policy Optimization, curriculum learning, and hybrid model-based strategies that have proven effective. We discuss the key challenges in transferring learned policies to real-world robots, managing uncertainty, and integrating perception and proprioception. Drawing from over 150 recent works, we provide a structured taxonomy of objectives, algorithms, and platforms, and identify trends in simulation …

Applying Machine Learning Methods To Generate Understandings Of Differential Item Functioning In A Flu Knowledge Assessment, William L. Romine, Tanvi Banerjee, Derrick Cox

Computer Science and Engineering Faculty Publications

Current influenza trends, including the severity of the 2025 flu season and the prevalence of H5 bird flu in livestock, necessitate efforts to better understand how to educate students about its transmission. Although validated assessments of influenza knowledge exist, these have not been evaluated for affective and demographic biases. We explore differential item functioning (DIF) effects in four items focused on specific aspects of flu transmission derived from a validated influenza knowledge assessment. In doing so, we introduce and utilize a machine learning framework for exploration of DIF which offers greater flexibility than traditional statistical approaches in terms of studying …

Extraction Of Patient Subtypes Using Llm Generated Knowledge Graphs Integrated With A Transformer Architecture, Benjamin Holmes, Cogan Shimizu

Computer Science and Engineering Faculty Publications

Extracting patient subpopulations (clinically relevant cohorts of individuals who share overlapping symptoms, risk factors, or diagnostic criteria) from unstructured medical notes is an ongoing challenge due to the variability of clinical language and the complex nature of patient conditions. We demonstrate a pipeline that combines named entity recognition (NER), transformer embeddings, guided dimensionality reduction, and LLM-mediated knowledge graph integration to enhance patient extraction. The approach begins with NER using the UMLS metathesaurus [1] to extract clinical terms, followed by transformation into vector embeddings using a biomedical transformer. These embeddings are augmented with structured knowledge graph representations generated through an LLM-driven …

A Comparative Analysis Of Data-Driven And Model-Based Neutrosophication Methods: Advancing True Neutrosophic Logic In Medical Data Transformation, Maikel Yelandi Leyva Vázquez, Lorenzo Cevallos-Torres, Omar Mar Cornelio, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophic logic extends fuzzy logic by explicitly modeling indeterminacy (I), offering a robust framework for uncertainty representation. The transformation of crisp data into neutrosophic triplets {T, I, F}—known as neutrosophication—is crucial for applying neutrosophic models in real-world analysis. However, comparative evaluations of existing neutrosophication methods remain limited. This study presents a systematic comparison of five approaches: three model-based methods (Parabolic, Threshold Distance, Fuzzy Membership), one density-based method (Kernel Density Estimation), and a proposed data-driven K-Means clustering method integrating sigmoid membership functions. Using a medical dataset of 299 patients and six continuous clinical variables, we assessed statistical behavior, consistency, and alignment …

Spatial Analysis Of American Chestnut (Castanea Dentata) Distribution And Ecology In Kentucky’S Federal Lands, Jacob Raymond Pease

Murray State Theses and Dissertations

Anthropogenic factors have been the cause of the decline of tree species across the globe. From unsustainable logging and development to disease and improper management, threats to forests have taken their toll. The American chestnut (Castanea dentata) was once an integral basal tree species in Appalachian forests, but chestnut blight drove the species to functional extinction by the mid-1900s. The recent creation of genetically modified chestnuts gives hope for future restoration of the species throughout its historical range. Despite blight resistance, effective restoration will require optimal site selection for finding and planting chestnuts, which will maximize limited resources. …

Comparative Study Of Single Imputation Techniques For The Prediction Of Missing Dairy Data, Ahmed M. Gad Prof, Ahmed Abdelhakim Ahmed Mr, Eman Manaa Prof, Basant Shafik Dr, Sakr Mostafa Prof

Business Administration

Dairy farm records are a crucial component of effective livestock business management. Record analysis allows a farm’s owner to make informed decisions. Incomplete records are less useful for data analysis, so it's important to handle missing values correctly. This study compares different imputation methods for handling missing values in a dataset of dairy records comprising 997 records collected from 234 cows between 2012 and 2022. The dataset was screened against records with missing values and then deleted, resulting in 858 observations from 200 animals. There were missing values in two variables, with a missing percentage of 13.9%: days in milk …

Extraction Of Fine-Grained Research Methods In The Field Of Information Science, Jiayi Hao, Yuzhuo Wang, Chengzhi Zhang

Journal of Scientific Information Research

[Purpose/significance]Research methods in information science are one of the critical research directions in this field. Constructing a fine-grained research method corpus and extracting research method entities can help scholars quickly understand the research methods in this field, explore the evolution of methods and their future development trends, and lay the foundation for the service and application of the research method corpus in the subsequent digital wave. [Method/process]Firstly, based on academic articles published in the Journal of the China Society for Scientific and Technical Information from 2000 to 2023, this study randomly selected 50 articles and manually annotated the research methodology …

Identifying Intangible And Biocultural Heritage Elements Toward Environmental Understanding: Engaging Stakeholders Through Art, Martha B. Lerski

Publications and Research

Grounded in a case study in Barbuda in the Caribbean, this research examines sustainability from the perspective of what arts and heritage can contribute to community engagement and local and broader understandings about the environment. This article documents a growing body of literature recognizing the role of arts and culture, including local knowledge and traditional ecological knowledge (TEK), in climate change endeavors. Art and TEK present expansive world views. Contextual information situates research done on the island of Barbuda pre- and post-Hurricane Irma. Visual arts workshops engaged community members in mixed methods research. Results documented cultural elements, particularly intangible and …

Dataset For "The Role Of Metacognition And Confidence In Quantitative Reasoning In College Biology Courses", Joseph Dauer, Anum Khushal, Brian A. Couch, Robert L. Mayes, Kent Rittschof

School of Natural Resources: Faculty Publications

Quantitative modelling is a fundamental skill for biology students with performance determined by a host of cognitive and metacognitive resources and requiring instructors to integrate key quantitative dimensions into teaching biology. Using an assessment of quantitative modelling in biology, we explored biology students’ (n = 930 higher education students) modelling practices (i.e., abilities to create, test, revise), metacognition about the nature of models and confidence in their capabilities to model. Students performed best on items related to understanding variables used in models and performed more poorly on items related to interpreting, creating, and using models to understand biological phenomena. …

The Arctic Ocean Region : Biodiversity, Governance And Protective Measures, Antonios Andreadakis, Graeme Chesters, Dimitrios Dalaklis, 90 North Foundation

Reports

EXECUTIVE SUMMARY

• The Arctic Ocean region stands at the forefront of global environmental transformation, serving as a harbinger of climate change and a frontier for emergent geopolitical and economic interests.

• The Arctic region's economic potential, particularly in shipping and resource extraction, appears to offer shorter trade routes, reduced fuel consumption, and increased access to high-value resources. However, this analysis largely ignores the complex geo-physical, environmental and geographical limitations of the region.

• The fragility of Arctic Ocean ecosystems – characterized by slow ecological recovery, specialised biodiversity, and extreme environmental conditions – renders them especially vulnerable to anthropogenic disturbances. …

Toward Biocompatible Assessment Of N-15 Hyperpolarized Metronidazole For Hypoxia Sensing, Faisal Asif

Wayne State University Theses

Recent advances in hyperpolarization, particularly Signal Amplification by Reversible Exchange (SABRE), have enhanced molecular magnetic resonance imaging (MRI) for in vivo applications. This study investigates [15N3]metronidazole, a tri-nitrogen-labeled derivative of an FDA-approved antibiotic, as a hypoxia-sensitive imaging agent. Under hypoxic conditions, the nitroimidazole group undergoes stepwise reduction to an amino group, inducing significant 15N chemical shift changes (30–600 ppm). We aim to develop an iridium catalyst-free, biocompatible hyperpolarized (HP) [15N3]metronidazole formulation exhibiting robust polarization (up to 15%) and extended T1 lifetimes (~10 min). Three specific objectives guide this work: (1) formulation of a HP injectable with enhanced 15N detection, (2) …

The Future Of Shipping At The Biodiversity-Climate Nexus : Round Table Report, Mary S. Wisz, Fabio Berzaghi, Mikaela Gomez, Maud C. Quinzin, Renis Auma Ojwala, Emily Nuckolls

Reports

This report presents the outcomes of a cross-disciplinary Round Table hosted by the World Maritime University (WMU) from May 13-15, 2024, in Malmö, Sweden. The event brought together 51 experts from academia, industry, NGOs, and international organizations, including the IMO, to explore shipping’s role at the biodiversity-climate nexus. The Round Table had a particular focus on the impacts of shipping that are currently unregulated or under-regulated, and opportunities to address biodiversity loss and pollution as the sector decarbonizes. The report highlights the need to apply comprehensive, ecosystem-based approaches to effectively manage shipping's impacts, including cumulative impacts, on the environment, people, …

Durable Oxyfluoride Waste Forms For Salt Wastes From Molten Salt Reactors, Alevtina A. Maksimova, Jake W. Amoroso, Matthew Page, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

Molten salt reactors (MSRs) are promising technology to replace traditional light and heavy water reactors in the near future. Waste management for MSRs, however, remains a pressing concern that needs to be resolved prior to realizing deployment of MSRs. Specifically, the generated salt waste needs to be safely sequestered, a task made difficult by the high solubility of the salt waste that can cause the release of radionuclides into the environment. This work demonstrates a new approach to immobilize multiple fluoride salts into a single waste form by converting highly-soluble fluorides to durable and stable oxyfluorides. Notably, we report a …

Semi Analytical Solution Ofmhd And Heat Transfer Of Couple Stress Fluid Over A Stretching Sheet With Radiation In Porousmedium, Sara Abdelsalam, M. Khairy, W. Abbas, A.M. Megahed, M.S. Emam

Basic Science Engineering

This comprehensive research examines the dynamics of magnetohydrodynamic (MHD) flow and heat transfer within a couple stress fluid. The investigation specifically focuses on the fluid’s behavior over a vertical stretching sheet embedded within a porous medium, providing valuable insights into the complex interactions between fluid mechanics, thermal transport, and magnetic fields. This study accounts for the significant impact of heat generation and thermal radiation, crucial factors for enhancing heat transfer efficiency in various industrial and technological contexts. The research employs mathematical techniques to simplify complex partial differential equations (PDEs) governing fluid flow and heat transfer. Specifically, suitable similarity transformations are …

Numerical Simulation Via Homotopy Perturbation Approach Of A Dissipative Squeezed Carreau Fluid Flow Due To A Sensor Surface, Sara Abdelsalam, W. Abbas, A.M. Megahed, H. M.H. Sadek, M.S. Emam

Basic Science Engineering

This study rigorously examines the interplay between viscous dissipation, magnetic effects, and thermal radiation on the flow behavior of a non-Newtonian Carreau squeezed fluid passing by a sensor surface within a micro cantilever channel, aiming to deepen our understanding of heat transport processes in complex fluid dynamics scenarios. The primary objective is to elucidate how physical operational parameters influence both the velocity of fluid flow and its temperature distribution, utilizing a comprehensive numerical approach. Employing a combination of mathematical modeling techniques, including similarity transformation, this investigation transforms complex partial differential equations into more manageable ordinary ones, subsequently solving them using …

Eugenol Loaded Calcium Citrate Particle As A Ph Triggered Drug Release System And A Reducing Agent For Au (Iii), Sadia Afrin

Dissertations and Theses

The study demonstrated that eugenol affects the morphology of calcium citrate particles during their formation, as confirmed by SEM micrography and PXRD analysis. Coating of eugenol loaded calcium citrate particles (CaCit MPs) with casein improves their known pH-dependent drug release profile, as confirmed by UV absorption spectroscopy. The casein-coated eugenol-loaded CaCit MPs (CCaCit(eu) MPs) can effectively control and sustain drug release under different pH conditions, particularly at acidic pH values (4.8 and 5.5), which mimics the environment of tumor tissues. To further explore the biomedical applications of calcium citrate, a bulk nanostructured precursor to the known anti-cancer calcium citrate phosphate-based …

Ripples: An Automated Embedding Generation Algorithm For The Forward-Forward Algorithm, Spencer Connolly

All Graduate Theses, Dissertations, and Other Capstone Projects

The Forward-Forward algorithm (FF) is yet another novel invention by Geoffrey Hinton, the creator of the famous backpropagation algorithm (BP). Since its proposal, many papers have been published exploring its potential, and good progress has been made in increasing its viability. Though FF continually falls short of BP, its purpose is not to replace BP and preliminary research shows that there is plenty of room for growth. In this paper, we present a literature review for FF algorithms applied to Convolution Neural Networks (CNN) for image classification tasks and set the stage for applying FF to more complex datasets. The …

Future Of Bse Days 2025: Growing A Regenerative Bse, Derek M. Heeren, Santosh Pitla, Jennifer R. Keshwani, Mark Stone

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

The Future of BSE Days 2025: Growing a Regenerative BSE brought together over 150 faculty, staff, students, and partners to envision the next quarter-century of the Department of Biological Systems Engineering. The event emphasized regeneration—not only of resources and ecosystems, but also of ideas, learning models, and relationships. Across seven major sessions—three Spark Talks and four Pillar Workshops—participants explored how BSE can thrive amid technological disruption, demographic change, and societal transformation.

Key Outcomes

Redefining Impact: This session challenged participants to evolve from counting outputs to valuing relationships, collaboration, and community well-being.

Adaptive Learning Models: This discussion introduced design studios, micro-credentials, …