Physical Sciences and Mathematics Commons^™

Copper-Indazolate Nanojars: Synthesis And Characterization, Nicholas Alexander Rudell

Masters Theses

The field of synthetic supramolecular chemistry has exploded since the first syntheses of crown ethers by Charles Pedersen in the 1960s, leading to further development in the area of macrocycles and incorporation into a vast array of metal-organic structures. Supramolecular chemistry came to the forefront of science with the 1987 Nobel Prize in Chemistry, awarded jointly to Donald J. Cram, Jean-Marie Lehn, and Charles Pedersen “for their development and use of molecules with structure-specific interactions of high selectivity.”

Nanojars are supramolecular metal-organic complexes with a high affinity for hydrophilic anions and can efficiently transfer such anions from water into organic …

Detecting Ai Generated Text Using Neural Networks, Jesus Guerrero

Masters Theses

For humans, distinguishing machine generated text from human written text is men- tally taxing and slow. NLP models have been created to do this more effectively and faster. But, what if some adversarial changes have been added to the machine generated text? This thesis discusses this issue and text detectors in general.

The primary goal of this thesis is to describe the current state of text detectors in research and to discuss a key adversarial issue in modern NLP transformers. To describe the current state of text detectors a Systematic Literature Review was done on 50 relevant papers to machine-centric …

Mapping Past Land Use Changes And Modeling Future Urbanization Patterns In A Mid-Sized American City, Duncan P. Mccurry

Masters Theses

On a global scale, humans have been moving from rural to urban areas at an increasingly fast rate in a process called urbanization. It is crucial to understand and predict the impacts of urbanization because city expansion encroaches on farmland and woodland, reducing regional ecosystem services. Therefore, urbanization must be well planned in a forecasting manner. The objective of this study is to map the land use change in Knox County, Tennessee, from 2001-2019 to identify the urbanization trends and understand the dynamic geospatial relationships between the urban and rural areas. The geospatial mapping was done using USGS land use …

Impact Of Cover Crop Species Diversity On Soil Nutrient Availability And Crop Productivity, Amanda Kramer

Masters Theses

Cover crops provide multiple environmental benefits that improve both soil and water quality; however, farmers only utilize them on approximately 5% of harvested U.S. cropland. Low adoption rates are attributed to yield impact concerns, seed and planting costs, and lack of advocacy. This study, which began in October 2019, assessed the effects of nitrogen rate and cover crop diversity on weed biomass, soil coverage, in-situ residue decomposition, soil nitrogen and phosphorus availability, and cash crop yield to better understand the costs and benefits of cover crop adoption at two locations in Tennessee (Milan and Spring Hill). Treatments were replicated 4 …

Understanding The Polymerization Of Ethyl Cyanoacrylate In The Superglue Fuming Of Latent Prints To Optimize Print Retrieval, Leondra Shawntae Lawson

Masters Theses

The cyanoacrylate fuming method (CFM) is a widespread process used in forensics to make latent prints visible for detection, acquisition, and analysis. CFM is governed by the reaction of ethyl cyanoacrylate (ECA) with biological components in fingerprints, which serve as initiators for this anionic polymerization. CFM is not a well-controlled polymerization and there are different outcomes that may result from lower temperature, one of which fits the generalization of creating more ion-pair initiators. Another effect could be minimizing termination through suppressing side reactions. Alternatively, when paired with humidity, lower temperatures may cause surface condensation, decreasing the quality of the print. …

Survey Of Input Modalities In The Western World, John Ezat Sadik

Masters Theses

Having your account compromised can lead to serious complications in your life. One
way accounts become compromised is through the security risks associated with weak
passwords and reused passwords [22,23]. In this thesis, we seek to understand how
entering passwords on non-PC devices contributes to the problems of weak and reused
passwords. To do so, we conducted a survey that was distributed to people in the
the Western World. In our survey results, we found that users commented about
how the current password model was not created with a variety of device types in
mind, which created frustrations and complexity …

Interactive Data Analysis Of Multi-Run Performance Data, Vanessa Lama

Masters Theses

Multi-dimensional performance data analysis presents challenges for programmers, and users. Developers have to choose library and compiler options for each platform, analyze raw performance data, and keep up with new technologies. Users run codes on different platforms, validate results with collaborators, and analyze performance data as applications scale up. Site operators use multiple profiling tools to optimize performance, requiring the analysis of multiple sources and data types. There is currently no comprehensive tool to support the structured analysis of unstructured data, when holistic performance data analysis can offer actionable insights and improve performance. In this work, we present thicket, a …

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Evaluating Bulk Carbon And Nitrogen Isotope Compositions Of Acidic Hydrothermal Sediments On Earth– Implications For Mars Astrobiology, Chance Sturrup

Masters Theses

Carbon isotopes have been widely used as unique biosignatures because biologic processes commonly result in distinctive negative delta ¹³C values (-35 to -10 ‰) within organic material on Earth. However, the bulk delta ¹³C analysis in Gale crater sediments on Mars revealed a wider range of values, from -25 to +56 ‰ (Franz et al., 2020), which suggests a more complex origin. To determine if bulk isotope analysis can be successfully used to detect a microbial signature in a martian analog environment, we analyzed concentrations and isotope compositions of C within hydrothermal sediments in Iceland (Námafjall, Krýsuvík, Hveragerdi) …

Development And Study Of Small Database For The Activation Of Nitrous Oxide Towards Formation Of Iron(Iv)-Oxo Species, Tobias Barthalomew Robertson

Masters Theses

Nitrous oxide (N₂O) can undergo an oxygen atom transfer (OAT) reaction resulting in inert nitrogen gas (N₂O) while transferring an oxygen atom to a molecular complex or material. This process is of catalytic importance since this OAT reaction can be leveraged to form iron(IV)-oxo sites, which are known to be catalytic intermediates. Here, an investigation of the ligand field effects on primarily iron(II) complexes for the formation of iron(IV)-oxo sites with nitrous oxide as the oxidant is reported. An initial database of sixty-four molecular complexes with ligand environments varying in field strength and coordination geometry was …

Analysis Of A Controlled Approximation For Explicit Integrations Of Stiff Thermonuclear Networks, Nicholas Brey

Masters Theses

The current standard method to solve stiff coupled differential equations relies on implicit integration methods. Explicit methods are generally avoided due to the extremely small and limiting timesteps they allow when the equations are stiff. However, implicit methods are computationally expensive because of the complex calculations that need to be done at each time step. An explicit integration method can do these calculations quicker and, if allowed to take comparable timesteps to the implicit ones, would allow the entire calculation to be done faster. Previous work by Dr. Guidry, Dr. Endeve, Dr. Hix and Dr. Billings has shown that, in …

The Use Of Biological Soil Health Indicators To Quantify The Benefits Of Cover Crops, Alexander Wu

Masters Theses

Soils provide many essential functions that support the world. With a decline in soil health, these functions also decrease in efficiency, and can threaten the health of billions of people around the world. Typically, soil health tests do not use biological indicators, however microbes drive and perform vital functions to increase soil health. One way to increase soil health is through the use of cover crops to reduce soil erosion during fallow periods, increasing soil organic matter, as well as collecting nutrients from soil into their biomass. These cover crops are then terminated through various methods such as herbicides, disk …

Modeling Spatial Distributions Of Tidal Marsh Blue Carbon Using Morphometric Parameters From Lidar, Bonnie Turek

Masters Theses

Tidal marshes serve as important “blue carbon” ecosystems that accrete large amounts of carbon with limited area. While much attention has been paid to the spatial variability of sedimentation within salt marshes, less work has been done to characterize spatial variability in marsh carbon density. Driven by tidal inundation, surface topography, and sediment supply, soil properties in marshes vary spatially with several parameters, including marsh platform elevation and proximity to the marsh edge and tidal creek network. We used lidar to extract these morphometric parameters from tidal marshes to map soil organic carbon (SOC) at the meter scale. Fixed volume …

The Relative Effects Of Functional Diversity And Structural Complexity On Carbon Dynamics In Late-Successional, Northeastern Mixed Hardwood Forests, Samantha Myers

Masters Theses

Late-successional forests provide a unique opportunity to explore adaptive management approaches that mitigate atmospheric carbon dioxide levels through carbon storage while also enhancing ecological resilience to novel climate and disturbances. Typical benchmarks for adaptive forest management include species diversity and structural complexity, which are widely considered to increase ecosystem stability and productivity. However, the role of functional trait diversity (e.g., variation in leaf and stem traits) in driving forest productivity and ecosystem resilience remains underexplored. We leveraged existing continuous forest inventory (CFI) data and collected local functional trait observations from CFI plots within late-successional forests in western Massachusetts to explore …

Differential Toxicity Of Pm2.5 Components And Modified Health Effects Modeling: A Case Study In Nepal, Jeremy Brownholtz

Masters Theses

During the latter part of the 20^th century, a transition away from coal as a major energy source in developed countries was accompanied by a notable decrease in air pollution-related deaths in those countries. Currently the same phenomenon is being observed in developing nations like China and India. However, many areas that do still rely on coal for their energy production or industrial needs also reflect a gap in research on the effects of those specific processes on local populations. Located in Nepal at the foot of the Himalayan Plateau, Kathmandu represents one such location. The local economy of …

Factors Affecting Groundwater Nitrate Concentration In Madinah Area, Saudi Arabia, Majed M. Almutairi

Masters Theses

High levels of nitrate in groundwater are a serious problem in Madinah Area, Saudi Arabia. Identifying factors affecting groundwater nitrate contamination is important for managing groundwater quality. This study examined factors that have significant impacts on the high level of groundwater nitrate in Madinah Area. Factors examined included well-depth and land cover. Relationships between variables were explored using three statistical approaches: the Kruskal-Wallis test and two types of regression (ordinary least squares [OLS] and geographically weighted regression [GWR]).

Nitrate concentration data show that 73% of obtained groundwater samples exceeded the United States Environmental Protection Agency (EPA) maximum contaminant level (MCL) …

Concept Validation: Collecting Composite Samples To Understand The Presence Of Per- And Polyfluoroalkyl Substances (Pfas) In Michigan Forested Areas, Nicole Renee Sanabria

Masters Theses

This research discusses the results of a state-wide study conducted by The Michigan Department of Environment, Great Lakes, and Energy to assess the presence of PFAS in shallow soils of state-owned forested areas in Michigan utilizing a composite sampling method. One sample collected from each of Michigan’s 83 counties reveals the presence of PFAS in all but one sample, with total PFAS concentrations ranging from non-detect to 2.016 μg/kg (dry weight). PFOS is generally detected at the highest concentrations, ranging from non-detect to 0.88 μg/kg, followed by PFBA, with concentrations ranging from non-detect to 0.69 μg/kg, and PFOA, with concentrations …

Dynamic Discounted Satisficing Based Driver Decision Prediction In Sequential Taxi Requests, Sree Pooja Akula

Masters Theses

"Ridesharing platforms rely on connecting available taxi drivers to potential passengers to maximize their revenue. However, predicting the stopping decision made by every driver, i.e., the final task performed during a given day, is crucial to achieving this goal. Unfortunately, little research has been done on predicting drivers’ stopping decisions, especially when they deviate from expected utility maximization behavior. This research proposes a Dynamic Discounted Satisficing (DDS) heuristic to model and learn the task at which human agents will stop working for that day, assuming that the human agents are taking sequential decisions based on their preference order. We apply …

Meta-Analysis Of Mesenchymal Stem Cell Gene Expression Data From Obese And Non-Obese Patients, Dakota William Shields

Masters Theses

"The prevalence of gene expression microarray datasets in public repositories gives opportunity to analyze biologically interesting datasets without running the laboratory aspect in house. Such experimentation is expensive in terms of finances, time, and expertise, which often results in low numbers of replicates. Meta-analysis techniques attempt to overcome issues due to few biological or technical replicates by combining separate experiments together to increase statistical power. Proper statistical considerations help to offset issues like simultaneous testing of thousands of genes, unintended hybridization, and other noises.

Microarrays contain light intensities from tens of thousands of hybridized probes giving a measure of gene …

Assessing The Knowledge On Sustainability And Barriers To Daily Sustainable Practices Among Faculty And Students In Higher Education: The Case Of Eastern Illinois University, Joel Edem Holison

Masters Theses

The concept of sustainable development gained prominence with the publication of the Brundtland Report, which emphasized economic progress without jeopardizing future generations' well-being. Following that, the Education for Sustainability (EfS) program was created by the United Nations to raise sustainability awareness. However, the transition to sustainable living is fraught with difficulties, including a lack of knowledge, financial constraints, infrastructure gaps, and political ideologies. This study focuses on sustainable practices among Eastern Illinois University (EIU) students and faculty, as well as the barriers to daily sustainable behaviors. As independent variables influencing sustainable practices, the study evaluates sustainability knowledge/awareness, personal financial situation, …

The Application Of Statistical Modeling To Identify Genetic Associations With Mild Traumatic Brain Injury Outcomes, Caroline Schott

Masters Theses

"Traumatic brain injury (TBI) is a growing health concern, with millions of TBI diagnoses in the United States each year. The vast majority of TBI diagnoses are mild traumatic brain injuries (mTBI), which can be challenging to manage due to variation in symptoms and outcomes. Most individuals with mTBI successfully recover quickly, but a small subset has a delayed recovery. Although the factors that contribute to this variation in recovery are not clearly understood, it is possible that genetic differences may play a role. Very few studies have investigated the association between single nucleotide polymorphisms (SNPs) with mTBI outcomes and …

Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara

Masters Theses

"Computer vision based on deep learning is an essential field that plays a significant role in object detection, image classification, semantic segmentation, instance segmentation, and other applications. However, these models face significant challenges in adverse conditions, such as small objects, low-resolution images, and edge deployment. These challenges limit the accuracy and efficiency of computer vision algorithms, making it difficult to obtain reliable results.

The primary objective of this thesis is to assess the performance of deep learning- based computer vision models in challenging conditions and provide viable solutions to overcome the obstacles. The study will specifically address three key challenges, …

Mat: Genetic Algorithms Based Multi-Objective Adversarial Attack On Multi-Task Deep Neural Networks, Nikola Andric

Masters Theses

"Vulnerability to adversarial attacks is a recognized deficiency of not only deep neural networks (DNNs) but also multi-task deep neural networks (MT-DNNs) that attracted much attention in the past few years. To the best of our knowledge, all multi-task deep neural network adversarial attacks currently present in the literature are non-targeted attacks that use gradient descent to optimize a single loss function generated by aggregating all loss functions into one. On the contrary, targeted attacks are sometimes preferred since they give more control over the attack. Hence, this paper proposes a novel targeted multi-objective adversarial ATtack (MAT) based on genetic …

Investigation Of Defect Production And Displacement Energies In Wurtzite Aluminum Nitride, Sean Anderson

Masters Theses

"Aluminum Nitride is an active element of sensors that monitor the performance and well-being of the nuclear reactors due to its piezoelectric properties. Yet, the variations of its properties under irradiation are largely unexplored. We report the results of the molecular dynamics simulations of the structural changes in AlN under irradiation via the knock-on atom technique. By creating and evolving the irradiation cascades due to energetic particle interaction with the atom of the crystalline lattice we determine the rate of the defect production as a function of the deposited energy. Further, we determine a displacement energy, a key characteristic that …