Digital Commons Network^™

A Comparative Study Of Novel Methods For Variances, Taoreed Muritala

Boise State University Theses and Dissertations

Understanding variability is fundamental to knowledge advancement across various disciplines, including manufacturing, clinical research, biology and genetics. Population variances play a crucial role in processes such as quality control, treatment evaluation and the interpretation of biological mechanisms. However, statistical procedures for comparing variances across multiple populations remain less developed than those for comparing means. Classical omnibus tests, such as Bartlett's and Levene's, can detect overall variance heterogeneity but fail to identify which populations differ, thereby limiting their usefulness in multi-population analyses and increasing the risk of inflated family-wise error rates through repeated testing.

This thesis develops and evaluates three multiple …

Agricultural Practices’ Impact On Soil Health Indicators In Mid-South U.S. Crop Production Systems, Katherine Suzanne French

Graduate Theses and Dissertations

Soil health and regenerative agriculture are concepts gaining popularity across global agriculture systems. The effect of sustainable farming practices such as nutrient management, cover crops, adoption of no-tillage, and residue retention on crop yield, as well as environmental resilience, is increasingly being studied. This research aimed to evaluate the impacts of (i) cover cropping and nutrient management, and of (ii) soil sampling depth and timing on indicators of soil health in various mid-southern irrigated row crop systems. Soil health indicators like soil organic matter (SOM), carbon dioxide respiration (CDR), beta-glucosidase enzyme activity (BG), permanganate oxidizable carbon (POXC), and the soil …

Evidence Of Backwater Morphodynamics In Stratigraphy On Earth And Mars: Implications For Ancient Mars, Cory Mitchell Hughes

Graduate Theses and Dissertations

Geologic evidence indicates that liquid water once flowed in abundance across the martian surface. For this reason, in the search for evidence of extraterrestrial life, Mars represents a prime target for scientific inquiry. River systems encode climatic and environmental signals in their deposits on Earth and Mars, often in fan-shaped landforms (e.g., alluvial fans, river deltas, etc.). Distal fan-shaped deposits (i.e., river deltas), in particular, act as a relatively high-fidelity record of dynamic geologic processes. As such, NASA frequently sends rovers to locations on Mars’ surface with hypothesized river deltas (e.g., Perseverance and Jezero crater). Problematically, there are many different …

Towards Vision-Brain Understanding At Scales: From Classical To Quantum Machine Learning Approaches, Xuan-Bac Nguyen

Graduate Theses and Dissertations

In recent years, large-scale learning approaches such as unsupervised and self-supervised learning have revolutionized artificial intelligence. These methods enable machines to learn high-level representations without explicit human supervision, achieving remarkable success across vision, language, and multimodal tasks. However, such advances come at a cost—they rely on massive datasets, billions of parameters, and extensive computational resources. Despite these achievements, artificial systems still fall short of the remarkable learning efficiency of the human brain, which can infer, adapt, and generalize from limited experiences. This gap motivates a deeper exploration of how biological intelligence acquires knowledge and how these principles can inspire the …

Novel Radical Chemistry Of Electron-Rich Double Bonds, Claire Allyson Beard

Graduate Theses and Dissertations

This work delves into the reactivity of nucleophilic N-heterocyclic carbenes (NHCs) and their ability to form electron-rich alkene intermediates, which can undergo various chemical transformations depending on the nature of the electrophile. Initial reports by Hahn disclosed the NHC promoted radical nature of electron-rich N,N’-benzyltetraazafulvalenes, which led to 2,2’- biimidazoles. We found that N-aryl substituted pyridinium salts also underwent rapid a similar NHC promoted dimerization when exposed to a base, producing 2,2’-bipyridyls. This is likely due to the adept radical nature of the bipyridinylidene intermediate for C-Naryl bond scission. We have also uncovered an unprecedented C-N bond scission of Breslow-like …

Multiple Aspects Of Environmental Temperature Have Complex Interactions With Avian Parental Behavior To Influence Offspring Outcomes, William H. Kirkpatrick

Graduate Theses and Dissertations

Anthropogenic climate change is projected to shift not only average temperatures across the globe, but also the amount of thermal variation experienced in the natural environment. Exposure to shifts in averages and a wider range of thermal experiences will cause shifts in wildlife behavior. In avian species, behaviors exhibited during reproduction have implications for the well-being of their offspring. Here, I explore specific incubation behaviors in four species: Scaled Quail (Callipepla squamata), Northern Bobwhite Quail (Colinus virginianus), Tree Swallows (Tachycineta bicolor), and Eastern Bluebirds (Sialia sialis). I examined constancy, or the percentage of time on the nest, and off-bout duration, …

Tracing The Journey Of Dissolved Organic Matter: From Leaf Litter Photodegradation To Microbial Processing In Tropical Streams, Samantha Nicole Sullivan

Chemistry & Biochemistry Theses & Dissertations

Dissolved organic matter (DOM) is a major reservoir of organic carbon in aquatic ecosystems and plays a central role in global carbon cycling through its transformation and remineralization to carbon dioxide (CO₂). As DOM moves from terrestrial environments into streams and rivers, its chemical composition is altered by a combination of microbial and photochemical oxidation processes that regulate both its reactivity and its persistence during transport. However, the molecular mechanisms governing these oxidative transitions, particularly in tropical ecosystems characterized by strong hydrologic seasonality and substantial inputs of plant-derived material, remain insufficiently resolved. This dissertation integrates ultrahigh-resolution mass spectrometry, optical characterization, …

Evaluation Of Ocean Lidar Enhancement Through Miniaturization And Gated Pmt-Based Range Extension, Chandler Austin Slater

OES Theses and Dissertations

Oceanographic lidar systems remotely characterize the vertical structure of the upper ocean by recording the light backscattered from a laser pulse as it propagates through the water column. Historically these systems have been constrained by limited detection ranges, often capturing only a portion of the illuminated water column, typically fading to noise around the 10% isolume. A primary constraint has been the limited dynamic range of digitizers, which inhibits the ability to resolve both intense near-field and faint far-field backscatter signals within a single acquisition. To address this, we developed a novel optical lidar system incorporating gated photomultiplier tubes (PMTs) …

Component Model Development Of Heat Exchangers, Expanders, And Control Valves For Autonomous Cryogenics Plant Cool-Down, William Harris Buhrig Iv

Mechanical & Aerospace Engineering Theses & Dissertations

The traditional method of cryogenic plant cool-down involves having continuous on-call staff to head into the office at any time to modify the existing multi-layered PID control systems if the on-call staff member detects a significant deviation from the cool-down plan. This thesis aims to outline an effective method for modeling the structure of systems with performance characteristics that deviate from design requirements and from ideal inlet-outlet correspondence, enabling the adjustment and modification of existing control structures across all Thomas Jefferson National Accelerator Facility (JLab) cryogenic refrigeration plants. Analytical Modeling and Gaussian Process Regression (GPR) are applied to model the …

Large Language Models (Llms) For Clinical Note Generation: International Classification Of Disease (Icd) Code, Knowledge Graph (Kg) And Prompt Evaluation, Ivan P. Makohon

Computer Science Theses & Dissertations

In the past decade, a surge in the amount of electronic health record (EHR) data in the United States occurred, driven by a favorable policy environment created by the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 and the 21st Century Cures Act of 2016. Clinical notes for patients’ assessments, diagnoses, and treatments are captured in these EHRs in free-form text by physicians, who spend a considerable amount of time entering them. Manually writing these notes is time-consuming, increasing patient waiting times and potentially delaying diagnoses. Large language models (LLMs), such as GPT-4o, possess the ability …

Solar Powered Conservation: The Effects Of Solar Photovoltaic Facilities On Avian Community Composition, Michael Christopher Ferrara

Graduate Theses and Dissertations

The expansion of solar photovoltaic energy infrastructure is transforming landscapes worldwide. Increasingly, facilities are planted with native vegetation, yet how vegetation characteristics and landscape variables shape wildlife communities in solar facilities remains poorly understood. Because avian populations have been in decline and are sensitive to habitat changes, understanding how solar facilities influence avian communities is important. In Chapter 1, we used autonomous recording units, local vegetation measurements, and land use and land cover data to quantify how avian community occupancy is influenced by solar cover in solar facilities and comparable reference sites. We used a Bayesian multi-species occupancy model to …

Climate Change Has Increased Global Evaporative Demand Except In South Asia, Saeed Karimzadeh, Arman Ahmadi, Dennis Baldocchi, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate change alters how strongly the atmosphere draws water from the land, yet a consistent global assessment of this evaporative demand has been lacking. Here, we analyze 45 years of climate data and global models to quantify trends in the key drivers—air temperature, humidity, radiation, wind speed, and cloud cover—that determine the atmosphere’s drying power. We find that evaporative demand has increased worldwide, indicating a stronger atmospheric thirst, except in South Asia, where it has declined. There, widespread irrigation has increased soil and air moisture, enhanced cloud formation, and reduced sunlight reaching the surface, counteracting the global signal. These contrasting …

Biocompatible And Antibacterial Pcl-Tio2@Ag/Γ-Cd Mof Nanocomposite Coating For Corrosion Resistance Of Magnesium Alloy In Simulated Body Fluid, Sara Dehghan-Chenar, Hamid R. Zare, Zahra Mohammadpour, Maryam Sadat Mirbagheri-Firoozabad

Journal of Electrochemistry

Magnesium alloys are promising candidates for bio-implant applications due to their biodegradability and biocompatibility. However, their rapid corrosion remains a critical limitation. This study presents the development of a multifunctional nanocomposite coating designed to enhance the corrosion resistance and antibacterial properties of magnesium alloy implants. The coating comprised γ-cyclodextrin metal-organic frameworks (γ-CD MOFs) decorated with TiO₂@Ag core-shell nanoparticles, embedded in a polycaprolactone (PCL) matrix. Immersion tests in a simulated body fluid (SBF) revealed an initially higher corrosion rate for the PCL-TiO₂@Ag/γ-CD MOF coating compared to the coating without TiO₂@Ag nanoparticles; however, it demonstrated significant …

Transdisciplinary Perspectives On Ai: The Fourth Annual Conference Of The European Culture And Technology Laboratory, Connell Vaughan, Ioana Madalina Moldovan, Silivan Moldovan, Noel Fitzpatrick

Books/Book Chapters

The fourth annual conference of the ECT Lab+ was hosted by Technical University of Cluj-Napoca over two days in October 2024 at the Cluj Innovation Park. The conference brought together experts from the Arts, Humanities, Social Sciences, Technology, and other fields to discuss and reflect on the advent of Artificial Intelligence and how the associated technologies are transforming how we live, work and study. Under the title Transdisciplinary perspectives on AI: Alternative Histories, Current Practices and Possible Futures the conference moved beyond simplistic technophila and technophobia to consider whether we can co-evolve with these new technologies which combine machine learning …

Identification Of Novel Tat-I24-Related Peptides With Antiviral Activities, Hanna Harant, Siegfried Hofinger, Reingard Grabherr, Zsolt Ruzsics, Hartmut Hengel

Michigan Tech Publications

To identify novel peptides with potential antiviral activities, a database search was performed based on the primary sequence of the peptide I24 (CLAFYACFC), the effective part of the antiviral peptide TAT-I24 consisting of peptide I24 and the cell penetrating TAT-peptide (amino-acids 48–60, GRKKRRQRRRPPQ). A Protein BLAST search identified several sequences with high similarity to I24 in diverse proteins, some of which are known to be involved in the interaction with nucleic acids. Selected sequences and newly designed variants of I24 were synthesized as TAT fusion peptides and tested for antiviral activity in two well-established models: baculovirus transduction of HEK293 cells …

A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani

Turkish Journal of Electrical Engineering and Computer Sciences

Midair hand gesture recognition plays a crucial role in applications such as sign language recognition and human-computer interaction, particularly for supporting individuals with partial or complete hearing loss. However, recognizing gestures in midair remains challenging due to the rapid and complex nature of hand movements. To address this, noninvasive techniques like surface electromyography (sEMG)—which captures muscle activity through sensors placed on the skin—have gained attention. sEMG provides rich time-series data that reflect both spatial and temporal muscle dynamics. In this study, we propose a deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to classify …

The Effect Of Noise Pollution On The Diversity And Abundance Of Bird Species At Different Locations At Warner Parks, Nashville, Tn, Jeremy T. Little, Wyatt L. Fooks, Darlene Panvini, Jackson Whiteside

Science University Research Symposium (SURS)

Noise pollution is a significant abiotic factor that can alter bird biodiversity and abundance of birds in urbanized areas. A new road is proposed through a relatively untouched area of Warner Parks in Nashville, TN, which may affect the bird community. Acoustic Song Meters were used to monitor bird sounds and soundscapes in the proposed road site and two areas of the park with different levels of noise pollution (roadside=high noise; isolated=low noise) for three weeks. Recordings were analyzed to determine bird species and abundance at each site to predict how increasing noise pollution may affect bird diversity in the …

Kairiomone Moderated Anti-Predator Responses In Pleurocera Laqueta, Daisy V. Mcleod, John Webb, Amanda Waggoner, John Niedzwiecki

Science University Research Symposium (SURS)

Predator-prey coevolution in freshwater ecosystems often involves chemical communication, where the prey detect predator released compounds known as kairomones. These chemical cues allow prey to alter behavior to reduce risk of predation. In Middle Tennessee streams, the native snail Pleurocera laqueata commonly coexists with predator crayfish, and previous studies have shown that exposure to crayfish kairomones can induce an anti-predator “crawl out” response. This response is commonly demonstrated through snails climbing above the waterline to avoid crayfish predators below. We hypothesized that Pleurocera laqueata would display a similar anti-predator response when exposed to both native and non-native crayfish cues. After …

Physiological Response To Concealed Information In A Mock-Crime Paradigm​, Ezra Koenigsberg, Tamya Mchenry, Jasmine Manzana, Taylor Powell, Samantha Jackson

Science University Research Symposium (SURS)

The Concealed Information Test (CIT), based on Lykken’s guilty knowledge framework, measures physiological responses when individuals recognize crime-related details compared to neutral alternatives. Previous studies show that variations in stimulus presentation enhance the CIT’s accuracy, especially through changes in electrodermal activity and heart rate. However, few studies have tested whether a Qualtrics-based mock-crime version of the CIT can replicate these physiological patterns. This study addresses that gap by adapting the CIT for a digital research environment. The goal is to determine whether participants show greater physiological arousal—measured through skin conductance, heart rate, and respiration—when exposed to crime-related “critical” stimuli compared …

Deconstructing The Black Box: An Explainability Analysis Of Deep Learning Architectures In Cytopathology, Chase A. Garrett

Master's Theses or Doctor of Nursing Practice

Deep learning shows strong potential in medical-image analysis, yet adoption in cyptopathology remains limited. Cytopathology could benefit from deep learning applications by improving diagnostic efficiency and accuracy. However deep learning comes with a notorious “black box” that keeps the models from being transparent and trustworthy for widespread clinical adoption. We conducted a comprehensive and comparative analysis of several deep learning architectures for multi-class classification of acute leukemia types, ALL, AML, and normal healthy cells from peripheral blood smear images. The models in this research include a Vision Transformer (ViT) and a diverse selection of Convolutional Neural Network (CNN) models. The …

2025 - The Sixth Annual Fall Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Fall 2025 Symposium of Student Scholars, held in November 2025. Includes abstracts from the presentations and posters.

Fish-Spec: Fast Identification System For Handheld Spectroscopy And Species Classification, Mitchell Sueker, Nicholas Mackinnon, Gregory Bearman, Amanda Tabb, Diane Kim, Rosalee S. Hellberg, Alireza Akhbardeh, Hamid Reza Marateb, Jianwei Qin, Moon Kim, Fartash Vasefi, Hossein Kashani Zadeh

Food Science Faculty Articles and Research

Accurate fish species identification is critical to prevent mislabeling and fraud in the seafood industry. We present a handheld multi-mode point spectroscopy system that combines fluorescence (365 and 395 nm excitation) and reflectance measurements in the visible to near-infrared (∼350–900 nm) and short-wave infrared (∼900–1700 nm) regions for rapid, non-destructive classification of fish fillets. Tissue spectra were acquired at 25 positions on 68 fillets from 11 species, in both frozen and thawed states. Feature-level fusion across all four modes enabled higher classification accuracy than any single mode alone. A global machine-learning model classified all species with 85 ± 2.8 %, …

Gboost-Ctl: A Novel Method In Multi-Tissue Transcriptome-Wide Associations Studies In Cross-Tissue Learner Incorporating Gwas Information, Md Mutasim Billah, Hairong Wei, Fengzhu Sun, Kui Zhang

Michigan Tech Publications

Genome-wide association studies (GWAS) have uncovered numerous genetic variants linked to complex human diseases, yet linking these variants to transcripts and tissues that drive pathology remains difficult. Multi-tissue transcriptome-wide association studies (TWAS) offer a powerful bridge, but existing analytical methods have some limitations, either by discarding important signals by separately analyzing and then aggregating results across tissues, implying imputation models in individual tissues, or fusing them with weights that ignore how much GWAS signal each tissue actually carries. Therefore, most of the existing methods do not work uniformly across different GWAS cohorts. Here, we propose GBoost-CTL - a GWAS-boosted cross-tissue …

Harnessing Hyperspectral Imaging And Deep Learning For Terrestrial Habitat Mapping In Arid Landscapes: A Case Study In Saudi Arabia, Ali Elgendy, Hesham Morgan, Brandon Tran, Rejoice Thomas, Tamer Ismail, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Muburak, Khaled Allam Harhash, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arid ecosystems remain under-mapped at actionable scales despite their ecological importance. Decision makers lack reliable, high-resolution habitat maps in drylands to prioritize protection and target restoration. This research integrates spaceborne hyperspectral imaging from the Environmental Mapping and Analysis Program (EnMAP) with deep learning semantic segmentation models to produce an updated level of habitat classification based on the International Union for Conservation of Nature (IUCN) for part of the Imam Turki bin Abdullah Royal Reserve, Saudi Arabia. Using ground control points and the full EnMAP spectral cube without band selection, U-Net and DeepLabV3+ architectures were each implemented with VGG19 and ResNet-101 …

From Vulnerability To Robustness: A Survey Of Patch Attacks And Defenses In Computer Vision, Xinyun Liu, Ronghua Xu

Michigan Tech Publications

Adversarial patch attacks have emerged as a powerful and practical threat to machine learning models in vision-based tasks. Unlike traditional perturbation-based adversarial attacks, which often require imperceptible changes to the entire input, patch attacks introduce localized and visible modifications that can consistently mislead deep neural networks across varying conditions. Their physical realizability makes them particularly concerning for real-world security-critical applications. In response, a growing body of research has proposed diverse defense strategies, including input preprocessing, robust model training, detection-based approaches, and certified defense mechanisms. In this paper, we provide a comprehensive review of patch-based adversarial attacks and corresponding defense techniques. …

Exploring Inorganic And Organometallic Chemistry, W. Christopher Boyd Phd

MSL Academic Endeavors eBooks

This textbook, Exploring Inorganic and Organometallic Chemistry, covers the fundamentals of inorganic and organometallic chemistry for undergraduate and graduate students. Both theories of structure and bonding and reaction chemistry are covered, with applications to the catalysis of organic reactions, biochemistry, and drug design. A modular approach allows for basic materials of each chapter to be covered in an undergraduate course, with more advanced material suitable for M.S. and Ph.D. students."

Doughnut Economics And Strong Sustainability: Rethinking The Role Of Financial Investment, Isabelle Pierotti

Electronic Theses and Dissertations

This thesis investigates how private investment could align doughnut economic framework. Doughnut economics is a strong sustainability economic framework where the economy operates within planetary boundaries while ensuring social equity. Theories of sustainable development, weak sustainability, and strong sustainability are discussed to provide theoretical context for doughnut economics and mainstream economics. The analysis concludes that conventional, profit maximizing private investment does not support a doughnut economics system by supporting the depletion of natural resources and exacerbating social issues. Sustainable mainstream investment also fails to support a doughnut framework. Lastly, while impact investment is theoretically committed to social and financial returns, …

Archaeological Predictive Meta-Modeling In Pre-Columbian Mexico, Peter Stamm

Electronic Theses and Dissertations

Archaeological Predictive Modeling stands firmly as an important tool for Archaeologists to predict undiscovered sites from civilizations all across the globe. While powerful, this methodology is not without its own set of qualms. Striking a balance between pure a data-driven approach while also observing leading expert theories can be a complicated task. Going further, deciding on the specific domain of features to emphasize or overlook can be a challenge within itself, as one misstep can drastically change the output of model, sometimes for the worst. In addition, creating models that can expose their reasoning process can be rather difficult to …

Novel Eco-Friendly Synthesis Of Coo Nps: Evaluation Of Their Diode Laser-Enhanced Inhibitory Activity Through Combined In Silico And In Vitro Approaches., Arshad Mahdi Hamad, Sahar Naji Rashid

Karbala International Journal of Modern Science

In our study, for the first time worldwide, to the best of our knowledge, cobalt oxide nanoparticles (CoO NPs) were synthesized using naringin (Nar) extracted from citrus peels. The properties of the prepared Nar-CoO NPs were studied using field emission scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDX), ultraviolet-visible (UV-Vis), X-ray diffraction (XRD), and Fourier transform infrared (FTIR) spectroscopy. All the test results demonstrated the efficiency and success of the nanofabrication process. The solution was then exposed to three types of diode lasers: red (650 nm), green (532 nm), and blue (405 nm). The purpose of this study was …

The Odds Don’T Lie: Mathematical Reasoning And Societal Ignorance In Don’T Look Up, Nysa Vedwan, Shane Carey

LASER Journal

In Adam McKay’s 2021 satirical sci-fi movie Don’t Look Up, two astronomers discover a comet heading directly toward Earth. Despite overwhelming evidence and near-certainty of global extinction, their warnings are ignored and ridiculed. This paper discusses the mathematical and scientific foundations of the movie’s social and political reception, and specifically focuses on orbital prediction and probabilistic modeling as they relate to public understanding of risk. This paper shows how data is often undermined by political and social dynamics, by connecting the fictional events of the movie with real-world crises like the COVID-19 pandemic and the climate emergency. In Don’t Look …