Master's Theses (Fall 2009 to Present)

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New submissions to the University of Delaware Master's Theses collection are added as they are released by the Graduate College. The Graduate College deposits all master's theses from a given semester after the official graduation date.

University of Delaware master’s theses submitted between 1980 - Summer 2009 are available online through Dissertations & Theses @ University of Delaware. Use the library catalog, DELCAT, to search for all print or microform copies of master's theses 1980 - 2009 that are NOT available in Dissertations & Theses @ University of Delaware because Dissertations & Theses @ University of Delaware does NOT contain the complete collection of University of Delaware master's theses.

Master’s theses in the Longwood Graduate Program in Public Horticulture (now known as the Longwood Fellows Program) submitted between 1970 - 2004 are available online.

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Now showing 1 - 20 of 2224

Production of neo acids from biomass-derived monomers
(University of Delaware, 2024) Andini, Erha Andini
Neo acids are highly branched carboxylic acids currently produced from fossil fuels. In this work, we produce renewable neo acids from lignocellulosic biomass-derived furan and keto acids via C-C coupling through hydroxyalkylation/alkylation (HAA), followed by ring-opening of furans through hydrodeoxygenation (HDO). We show effective C-C coupling over acid catalysts. Catalyst screening and multi-parameter optimization using machine learning optimize the yield and elucidate the correlation between variables and outcomes. We demonstrate selective furan ring-opening without affecting the carboxylic acid to make neo acids using a co-catalyst involving Pd supported on carbon and metal triflate.
Inferring bearing capacity from sonar backscatter: application from a muddy field site
(University of Delaware, 2024) Park, Sun Woo
This study expands on the application of sediment classification using acoustic backscatter and combine it with drop penetrometer data to test if the bearing capacity of the sediment layer can be related to the backscatter intensity. Total area of 5.14 km2 was surveyed using a vessel mounted multibeam sonar and AUV mounted side scan sonar on the Potomac river near Indian Head, Maryland. 9 sediment grabs were taken during October 2022 field work, and 18 contemporaneous grab samples and drop penetrometer measurements were taken during February 2023. Backscatter mosaic with the geotechnical data was used to train a supervised classification algorithm in ArcGIS Pro. Applying the data interpretation techniques developed so far to cohesive fluvial environment has shown good agreement between backscatter intensity and bearing capacity (precision: 0.75, accuracy: 0.78). This could have practical applications in coastal and riverine construction in muddy environments, allowing for fast and cost effective analysis of bearing capacity of a large site. Unexploded ordnance (UXO) in munition test sites could also be managed using sonar surveys since ordnance mobility and burial could have improved prediction with bed bearing capacity data (Trembanis and DuVal, 2021). This coordinated geoacoustic and geotechnical survey approach would reduce the risk of UXO site management since minimal contact with the bottom is necessary.
Understanding the impact of lignin-derivable non-isocyanate polyurethane (NIPU) chemistry on electrospinnability and fiber quality
(University of Delaware, 2024) Mahmood, Maida
Polyurethanes (PUs) are a critical component of the global polymer industry but mainly are derived from fossil fuels and contain hazardous precursors. Non-isocyanate polyurethanes (NIPUs) derived from lignocellulosic biomass, not only provide a safer and sustainable alternative to conventional PUs but also contain functional groups that can alleviate processing challenges and improve electrospinnability. In this work, lignin-derivable bisguaiacol A (BGA)-NIPU (one methoxy group on each aromatic ring with dimethyl bridging substitution) and bisguaiacol F (BGF)-NIPUs (one methoxy group on each aromatic ring without dimethyl bridging substitution) are used to fabricate electrospun fiber mats; and the impact of lignin-derivable NIPU chemistries on electrospinnability and fiber quality is studied. It was found that the presence of methoxy groups in lignin-derivable NIPUs led to a 10-50% increase in viscosity as compared to the bisphenol A (BPA)-NIPU control (no methoxy groups with a dimethyl substitution). Additionally, the absence of dimethyl substitution led to the highest viscosity and completely bead-free fibers in BGF-NIPU in comparison to BPA-NIPU and BGA-NIPU. This work provides an understanding of structure-processing relationships for the electrospinning of lignin-derivable NIPUs. These insights can help inform future studies regarding manufacturing of bio-based NIPU fibers and fiber-composites for different applications.
Bridge elements' weight determination and components' condition prediction using machine learning approach
(University of Delaware, 2024) Abiona, Qozeem Olatunbosun
Managing the deterioration of the bridge components and elements has continued to be one of the major concerns for the Departments of Transportation (DOTs) in the United States due to the huge cost needed for constructing new bridges. To avert disasters that could lead to severe losses, deterioration models have been created to predict the future condition of the deck while attributing the deterioration to different factors elicited by engineering and statistical techniques. Previous deterioration models have been more like linear regression models and did not predict the discretized value of the deck condition rating. A prediction of 6.51 was approximated to be a condition rating of 7, which is inappropriate for a discrete data type. This research project uniquely combines all the bridge features identified in the literature by applying principal component analysis (PCA) to capture the variance in the dataset needed to predict the condition of the bridge components. Feedforward Artificial Neural Network (ANN) models were created using different numbers of principal components and the performances were compared with that of the base model that uses all the features collected from the literature. It was observed that 9, 9, and 10 principal components are needed to create a deterioration prediction model that gives a better prediction accuracy than the base model that uses all the bridge features in the Deck, Superstructure, and Substructure respectively. The deterioration of the bridge elements is also known to influence the condition rating of the bridge components and the overall condition of the bridge. The weight or importance of the bridge elements influences the maintenance, repair, and replacement (MRR) schedule of the Departments of Transportation (DOTs) and the resource allocation to the structures. The DOTs currently use a cost-based approach to assign weight to bridge elements which can be in terms of the loss accrued during downtime or the amount needed for the replacement of the element. However, this approach does not consider the bridge element's structural relevance to the bridge's overall performance. This research also uniquely uses the Random Forest (RF) algorithm, an ensemble of decision trees, to evaluate the importance of different elements to the condition of the bridge components and the overall condition of the bridge. The analysis focused on 15 bridge design types in Delaware, Maryland, Pennsylvania, Virginia, and West Virginia and discovered that the weight of bridge elements is not constant as insinuated by the cost-based approach but varies based on its relevance to the bridge's structural performance. The resultant bridge elements’ weight can be used to construct the Bridge Health Index (BHI) equations for the different bridge types. The novel approach herein provides the DOT personnel with data-driven evidence to determine which set of bridge elements to prioritize in their maintenance actions to improve the components' condition, and the overall condition of their bridge inventory and to ascertain if the elements receiving the highest priority in the MRR schedule and budget allocation are also the same set of elements that bridge inspectors regard as needing attention. Furthermore, the technique presented also serves as an approach for synthesizing the bridge component and element-level data and aids the conversion process between the two important datasets.
Investigating the role of coastal wetland on per- and polyfluoroalkyl substances (PFAS) transport
(University of Delaware, 2023) Pavia, Ashley
Per- and polyfluoroalkyl substances (PFAS) are a large group of chemicals that have been widely used in manufactured and commercial products. They are persistent emerging contaminants that have been linked to adverse health effects in wildlife and humans. Few studies have assessed how PFAS compounds are transported and distributed throughout coastal watersheds and their effects on coastal ecosystems. This study assesses the spatial distribution and composition of PFAS in a tidal salt marsh and investigates how geochemical and hydrological conditions affect their fate and transport. We used St. Jones Reserve, a tidal marsh positioned between a military base and Delaware Bay, as the study site. We collected groundwater, porewater, and sediment from seven sites that span across three marsh zones with contrasting geochemical and hydrological conditions, and surface water from the tidal creek at high and low tide. Our study reveals a consistent pattern in the vertical distribution of PFAS within the salt marsh and elevated PFAS concentrations in the subsurface environment across seasons. Our findings highlight dissolved organic carbon (DOC) as a potential factor influencing the distribution of PFAS in the marsh ecosystem. The results of this study improve our understanding of PFAS mobility in the environment and the factors that affect their fate and transport as they migrate to the ocean. The information generated in this study can be used to develop models to predict PFAS fate and transport and strategies for protecting coastal water supplies and ecosystems.
Factors influencing spatial patterns and trends in migratory landbird stopover across Texas and Louisiana
(University of Delaware, 2023) Crandall, Amanda
To optimize energy and speed each migration season, Nearctic-Neotropical landbirds must navigate the climate of the airspace during flight, and the heterogeneity of the landscape as they stopover to rest and refuel. With a diverse environment ranging from arid to temperate, proximity to the Gulf of Mexico, the presence of some of the brightest cities in the United States, and the existence of multiple major migration routes, Texas (TX) and Louisiana (LA) represent a unique landscape to study how climate and land cover factors influence where migrants choose to stopover, how these relationships vary seasonally, and how they change over time. I used 26 years of data (1995-2020) from 15 NEXRAD weather surveillance radars distributed across TX and LA to calculate bird densities and distributions in relation to environmental variables. I first fit boosted regression tree (BRT) models among an ensemble of 196 overlapping modeling frames (400 km x 400 km in extent) stratified across the study area to determine the relative importance and beta relationships between 26 environmental predictor variables and 13 years of seasonal mean bird density. I found a high degree of spatial and seasonal nonstationarity in variable importance and the directions of beta relationships, reflecting potential differences in species compositions and migration strategies, as well as complex interactions between abiotic and biotic factors influencing stopover distributions. Consistently important variables included temperature, precipitation, distance to artificial light at night (ALAN), and east-west winds. Interestingly, I found evidence of attraction to bright light at the broad scale and avoidance of bright light at the fine scale that varied depending on the mean distance to ALAN across the landscape. My results suggest that attraction to bright light was greater in areas that were on average further from ALAN, while avoidance of bright light was greater in areas that were on average closer to ALAN. To expand upon my findings and investigate how changes to the landscape and climate influence changes in stopover densities and distributions over time, I used generalized additive models (GAMs) to examine the relationships between 35 predictor variables, their top-ranking interactions, and trends in seasonal mean bird density from1995-2020. Similar to the results of the spatial BRT models, I found a high degree of seasonal and geographic variability across TX and LA. Generally, however, temperature, east-west winds, and their interactions were highly important variables in influencing bird density trends over time. In the fall, stopover density increased in warmer areas and areas that became warmer over time, while in the spring, cooler areas and areas that became cooler were correlated with increases in bird density. In addition, spring stopover density increased further from bright ALAN where winds were blowing fastest from the east, suggesting that easterly winds may be outweighing the effects of light attraction. Spring stopover density decreased further from bright ALAN where winds were blowing fastest from the west, suggesting that westerly winds may be contributing to the effects of light attraction. In the fall, easterly winds may be outweighing the effects of light attraction. Overall, quantification of the direction and magnitude of these relationships is novel for the south-central region of the U.S. and provides a strong foundation for future studies that investigate the regional relationships I found in more detail. Moreover, understanding the effects of climate trajectories and their combinations with factors like ALAN intensity and urban development, can aid in enacting preventative measures for landbird conservation.
Design of structured illumination via multi-objective optimization in dynamic X-ray tomosynthesis
(University of Delaware, 2023) Restrepo, Carlos
Dynamic coded X-ray tomosynthesis (CXT) uses a set of encoded X-ray sources to interrogate objects lying on a moving conveyor mechanism. The sample is reconstructed from encoded measurements received by uniform linear array detectors. This work introduces a multi-objective optimization (MO) method for structured illuminations, balancing reconstruction quality and radiation dose in dynamic CXT systems. The MO framework is established based on a dynamic sensing geometry with binary coding masks. The Strength Pareto Evolutionary Algorithm 2 (SPEA-2) is used to solve the MO problem by jointly optimizing the coding masks, locations of X-ray sources, and exposure moments. Computational experiments are implemented to assess the proposed MO strategy. Additionally, an analysis based on singular value decomposition was carried out to examine the condition number of the resulting sampling matrices. To ensure that the reconstruction framework does not have dependencies on a particular sample movement, two different movement sequences were employed. The results show that the proposed strategy can obtain a set of Pareto optimal solutions with different levels of radiation dose and better reconstruction quality than benchmark settings under diverse sampling conditions.
A ballast box to study the effect of sand fouling on ballast, track stiffness, track deformation, and predicting maintenance time
(University of Delaware, 2023) Alzhrani, Mohammed Abdullah J
Railroad track crossings through sandy areas, like deserts, face the unique challenge of sand infiltrating into the ballast, leading to ballast fouling. Geographical conditions make these areas particularly prone to windblown sand infiltration, causing fine sand to gradually fill the ballast voids, ultimately resulting in fouling issues. Over time, fouled ballasts become a significant concern because of their negative impacts on track performance. ☐ This study explores the impact of ballast fouling primarily caused by sand infiltration on track deflection, stiffness (modulus), and overall track degradation. The main goal is to establish a clear relationship between these factors and fouling levels due to sand infiltration. ☐ The research was conducted at the University of Delaware's Civil Engineering laboratory, utilizing an 18-cubic-foot (0.67 cubic yards) ballast box. A rail/tie/fastener assembly was placed on the ballast and subjected to cyclic loading at a rate of 12 cycles per minute. The testing began with clean ballast, and dynamic load tests were carried out under simulated vehicle wheel loading conditions for up to five hours, with load-deflection behavior recorded during each cycle. Sand was introduced to the ballast in two series: Series 1, representing unconsolidated tests, and Series 2, simulating progressive fouling. These tests were repeated with varying levels of sand fouling, ranging from moderate to severe. Load deflection curves were analyzed using the Beam on Elastic Foundation (BOEF) theory to determine track modulus (stiffness) values and cumulative deformation, corresponding to cumulative plastic strain under repeated wheel loading. ☐ The study's results reveal a consistent pattern in load deflection curves, track modulus values, and cumulative plastic strain for different levels of sand fouling. It was observed that as sand fouling increased, both track stiffness (modulus) and track settlement also increased, aligning with field measurements conducted under similar conditions. ☐ As a result of these findings, a predictive application was developed to estimate maintenance time based on the degree of fouling. This application can offer valuable insights into maintenance planning and decision-making for tracks traversing sandy regions.
Identifying patterns and drivers of movement of the lesser mealworm Alphitobius diaperinus (Coleoptera: Tenebrionidae)
(University of Delaware, 2023) Sammarco, Ben
Alphitobius diaperinus is a ubiquitous pest of poultry houses found worldwide. They live in the litter of commercial poultry houses, especially broiler chicken houses. In high numbers they reduce poultry feed efficiency, cause stress and injury to birds, act as a reservoir for poultry diseases, and cause damage to structures and insulation in the house. Distribution and patterns of movement of A. diaperinus within broiler houses has been documented, but the specific environmental cues and behavioral drivers that govern those patterns are not well understood. I conducted a series of behavioral assays to evaluate the response of A. diaperinus to several wavelengths of light and the presence of water. I found that A. diaperinus adults and larvae are repelled by several wavelengths of light, but burrowing behavior is not connected to this response to light. I also found that A. diaperinus is repelled by water when in a normal, hydrated state, but is attracted to water when dehydrated, and this attraction is stronger than the repulsion from light. On a broader scale, A. diaperinus is believed to originate in Africa as a nest associate of several bird species, however the historical pattern of dispersal across the world is not known. As a preliminary survey to assess the viability of genetic tools to illuminate these historical patterns I sampled broiler house populations of A. diaperinus from several farms in the Eastern United States and Europe and sequenced the mitochondrial cytochrome oxidase subunit I gene. I analyzed the diversity of this gene between houses, farms, states, and nations, and found that broiler house A. diaperinus populations are very homogenous at the cytochrome oxidase subunit I gene.
Using remote sensing to examine wintering waterfowl distributions and ecology in the United States to create a novel avian influenza virus biosecurity tool for the poultry industry
(University of Delaware, 2023) Hardy, Matthew James
The ongoing global HPAI outbreak in commercial poultry, first reported in the USA in February 2022 has emphasized the need for improved food biosecurity and novel approaches pertaining to nationwide wild bird surveillance. The Mid-Atlantic (MA) and Central Valley of California (CVC) are critical sites for waterfowl species in the winter, which promotes the interface between wild and domestic birds and increases the risk of an HPAI outbreak. Improving the understanding between predictors of wintering waterfowl distributions on both the fine and broad scale will allow facility managers to make more informed biosecurity decisions. Using the network of US NEXRAD’s and fine scale GPS-tracking of known HPAI reservoirs; Greater Snow Geese (Anser caerulescens atlanticus) (N = 59) and Canada Geese (Branta canadensis) (N = 9), my objectives were to 1) model winter waterfowl distributions at the broad scale in the MA and CVC as a function of weather, temporal, and environmental characteristics using boosted regression tree modelling and 9 years of NEXRAD data (2014–2023); 2) use high frequency GPS-tracking of geese for four winters (2019–2023) to demonstrate how a percentile risk ranking system can be used to gauge exposure to wintering waterfowl prior to an HPAI outbreak and discuss a risk management analysis framework for facility managers; and 3) use high frequency GPS-tracking of geese for four winters (2019–2023) to model waterfowl exposure in goose points per hour at individual poultry facilities as a function of temporal, geographic, and landcover predictors. ☐ I was able to capture the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide poultry and egg production. In general, environmental and geographic predictors had the strongest relative effect on predicting wintering waterfowl distributions in both regions, while land cover composition had regional and temporal specific effects. Daily mean temperature was a major predictor of increasing waterfowl distributions in both regions throughout the winter, while precipitation had differing effects, increasing waterfowl densities in the MA, while decreasing in general within the CVC. Increasing waterfowl densities in California are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl distributions in the MA generally increased when distances to the Atlantic coast and lakes decreased, while increasing waterfowl distributions in the CVC were more strongly tied to decreasing distances to lakes. ☐ I demonstrated how a percentile ranking system based on goose points per hour at individual poultry facilities may be successfully used as a metric to predict AI outbreaks at poultry facilities within the Delmarva Peninsula in the Mid-Atlantic region of the US. Seven facilities that had an H5N1 outbreak during a 34-day window were within the 78th – 99th percentile of risk based on this system, with one facility even being ranked within the ‘top-25’ of 6,021 facilities. I was also able to document the first ever fine scale movement of wintering waterfowl in proximity to poultry facilities, with the minimum distance for Canada Geese (CANG) and Greater Snow Geese (GSGO) being documented at 3.9 m and 1.7 m respectively to poultry facilities. Exactly one-third of all Delmarva Peninsula poultry facilities had waterfowl present across winters, which is an alarming rate given our small sample size relative to the entire populations of both species. ☐ I was able to capture the spatial and temporal variability in mean exposure rate of geese in proximity to poultry facilities within a region of high poultry farm production across four winters. Time of the winter was the best predictor of goose exposure for both species, with GSGO generally greater during mid-late winter and CANG fairly consistent across the entire winter. Colder winter temperatures (particularly below 0°C) exponentially increases the rate of GSGO exposure at farms as they feed on waste grain to offset energy deficits. Goose exposure was similarly high for both species across the winter during both the day and night and emphasizes the need for 24 hr surveillance. Facilities that were closer to sewage treatment facilities, national wildlife refuges, waterbodies, or the coast had higher relative goose exposure, highlighting the importance of these sites at various times through the winter for geese. Many inland sites also have relatively high rates of goose exposure and geographic features such reservoirs, lakes, quarries, and gravel/sand pits may play a disproportionate role in supporting large numbers of geese.
Comparison of efficacy of appliances to be used at home and other places for fresh produce decontamination and cleaning
(University of Delaware, 2023) Raymond, Kassidy
Consumers need assistance in avoiding food-borne outbreaks associated with bacteria such as Salmonella. For fresh produce, heat treatments are not typically an option. In this study, three appliances with non-thermal technology were tested to determine efficiency and efficacy of washing and sanitizing fresh produce. Two of the appliances are currently available to the public, while one is still in development and testing in our laboratory. Grape tomatoes and spring salad mixes were used as samples to provide different surface textures: smooth and rough. They were inoculated using two methods, dip or spot inoculation, with a four-strain Salmonella cocktail to achieve an initial population of approximately 8-log CFU/g. The apparatuses involved used either ozone, ultrasonic, or ultrasound to treat the samples, and the samples are treated within 4 gallons of water at 3, 6 and 9 minutes, respectively. The results for inactivation of the Salmonella included about a 3-log reduction for tomatoes, and about less than a 1-log reduction for salad when sanitized with ozone, and ozone with ultrasound, and about a 3-log reduction for tomatoes and about a 2-log reduction for salad when sanitized with shortwave ultraviolet light radiation. The effect of duration of treatment time on Salmonella inactivation can be noted here, as the longer the samples underwent each treatment, the number of bacterial colonies reduced. At 3 minutes, the UV apparatus had the best inactivation amount compared to the other two apparatuses. In terms of texture and color change, the UV with water agitation did not significantly affect texture and color, the use of ozone significantly affected texture, and the combination of ozone with ultrasound significantly affected texture and color. In the future, UV with water agitation could be a viable alternative – instead of washing under running water- for consumers who want to keep the quality of their fresh produce.
Investigating the impact of hydrogen bonding in blends containing lignin-derivable polymers
(University of Delaware, 2023) Li, Sonia C.
In this work, poly(acrylic acid) (PAA) was blended with lignin-derivable polymers to investigate the effects of hydrogen bonding on phase behavior. Polymers are ubiquitous to society, but many are made from petroleum-based products that cause environmental concerns. The use of lignocellulosic biomass (LCB) reduces the burden of petroleum products. Lignin is an underused component of LCB that can be deconstructed and used as a platform for high-value products. Lignin-derivable polymethacrylates, such as poly(guaiacyl methacrylate) and poly(syringyl methacrylate), have desirable glass transition temperatures (Tgs) and provide various mesophases for applications like pressure-sensitive adhesives if used in biobased block polymers. Polymer blends are synthetically less intensive and could provide alternative methods to leverage the desirable properties for these polymethacrylates. Fourier transform infrared spectroscopy was used to show that hydrogen bonding occurs between the methoxy group of the polymethacrylates and the hydroxyl group of the PAA. The phase behavior of the blends was estimated for a range of compositions and temperatures, compared to differential scanning calorimetry results, and used to determine the limitations of the model. Overall, the results of this work provided insight into the hydrogen-bonding interactions in the system and an estimation of its phase behavior across a range of compositions and temperatures.
Structure function analysis of the conserved WWD domain in the System I bacterial holocytochrome C synthase, CcmF
(University of Delaware, 2022) Grunow, Amber L.
Cytochromes c are highly conserved proteins found in nearly all organisms including bacteria, plants and humans that function in electron transport chains for critical cellular functions 1. Each cytochrome c contains at least one molecule of covalently attached heme which is required for protein folding, stability and function 1–3. The covalent attachment of heme to apocytochrome c is referred to as cytochrome c biogenesis. There are three known pathways that accomplish heme attachment within the inner membrane space of the mitochondria in eukaryotes (System III) or the periplasm of prokaryotes (System II and I) 1. All Systems function to covalently attach heme to apocytochrome c yet use different mechanisms. This thesis will focus on the integral membrane protein, and holocytochrome c synthase, CcmFH, of System I which attaches heme to apocytochrome c in the final step of the pathway 4. CcmF has key features that are required for function including four conserved histidines, a stable b-heme located in the transmembrane domain and a highly conserved WWD domain that has been shown to directly interact with heme in other proteins 5,6. Therefore, I hypothesize that the WWD domain in CcmF is required for holocytochrome c synthase activity. ☐ To test this hypothesis, alanine scanning was performed on the WWD domain in CcmF to determine which amino acids are necessary for cytochrome c biogenesis. Further biochemical analyses of each alanine mutant determined the heme environment in each variant and their protein interaction partners. These studies have shown that two alanine mutants in the WWD domain of CcmF displayed non-functional phenotypes. The inability of these two variants to perform the holocytochrome c synthase function was not due to a defect in heme binding nor to the disruption of known protein-protein interactions. Overall, this study demonstrates that the WWD domain is necessary for synthase function in CcmF.
Toward mental health prediction using browsing history for predictive and soft labeling
(University of Delaware, 2022) Nilipour, Sahar
Web browsing data is increasingly being explored as a passive window into the daily lives of users to assess levels of internet addiction and other mental health markers. In this work, I determine whether such approaches can be applied to data generated by the HabitLab platform to assess the community of users for signs of anxiety, depression, and loneliness. HabitLab is a Chrome-based browser plugin that offers users tools to monitor and optimize the time they spend on various websites that negatively impact their productivity while passively logging their browsing sessions. As part of an initial explorative study, 66 HabitLab users completed a paid Qualtrics survey during the height of the COVID-19 pandemic in the US. I analyzed their response to several psychometric scales included on the survey and paired their results with their web browsing data. I then developed several features from this data to characterize their behaviors and used Machine Learning techniques (e.g., SVM, Random Forest) to attempt to learn relationships between their responses. I trained both Classification and Regression models, as I had access to both the real valued scores and their interpretations for most of the mental health scales. The results suggest that the models (specifically regression models), are capable of learning some of the scales; achieving over 80% accuracy for predicting Anxiety and Sleep Disturbance. As the long-term goal of the HabitLab team is to transform the plugin into a Digital Wellbeing and Occupational Health platform, these results can be used to inform: (i) future onboarding and demographic intake questionnaires, (ii) efforts to develop features based on web usage data and predictive models of mental health status, and (iii) facilitate anonymous community assessment through soft labeling approaches.
The effects of repetitive head impacts on neurocognitive function
(University of Delaware, 2022) Fasoranti, Zarek O.
Introduction: There has been an increase in concern regarding the effects of sports related Repetitive Head Impacts (RHI) during contact and/or collision sport participation. Furthermore, the duration of an athlete’s participation in collision sports may present a “dose-response” effect whereby longer duration of play results in poorer cognitive function. Therefore, the purpose of this study was to utilize an established cognitive assessment, the Trail Making Test (TMT), to assess how neurocognitive functioning is affected by sport type played (i.e., collision, contact, and non-contact) and collision sport career duration. ☐ Methods: The TMT (TMT-A, TMT-B, TMT-Diff) completion times of collegiate student-athletes from two universities participating in non-contact, contact, and collision sports were utilized. A One-Way ANOVA compared TMT-A, TMT-B, and TMT-Diff times between non-contact, contact, and collision sport athletes and significant main effects were followed with Tukey post-hoc tests. A regression analysis was used to assess whether sports career duration predicted TMT performance. ☐ Results: There was a significant main effect for TMT-B and TMT-Diff. For the TMT-B, the collision sports group (43.8 + 13.0 sec) were significantly slower (p<0.001) than non-Contact (39.1 + 10.6 sec, d= 0.4). In the TMT-Diff score, the Collision sports group had a significantly larger difference (p = 0.001, d= 0.55) (23.4 + 11.6 sec) than the non-contact sport (17.6 + 9.2 sec). Years of sport participation was not a significant predictor for TMTA (p = 0.60, R2=0.0008), TMTB (p = 0.29, R2=0.003) or TMT-Diff performance (p = 0.17, R2=0.006). ☐ Conclusion: In conclusion the results suggest that career duration at the collegiate level may not be a predictor of neurocognitive performance. However, collision sports participation in college results in small (d= 0.4) but significant differences in cognitive function which raises concern about cognition across the lifespan. Future studies need to continue to monitor former contact and collision sports athletes as they age to identify potential neurophysiological effects of RHI and aging.
AMBERff at scale: multimillion-atom simulations with AMBER force fields in NAMD
(University of Delaware, 2022) Jones, Peter Eugene
All-atom molecular dynamics (MD) simulations are an essential structural biology technique with a demonstrated record of groundbreaking biological discoveries. The application of MD simulations to study large-scale biomolecular systems containing millions of atoms can reveal incredible details about viral and cellular processes that are inaccessible to experimental methods. Classical MD simulations rely on "force fields" carefully parameterized for each class of biomolecule to accurately describe molecular motion. Importantly, the AMBER family of force fields (AMBERff) includes a more accurate and extensively validated description of nucleic acids. Yet, it is not currently tractable to use AMBERff for multimillion-atom simulations, the minimum scale required to study the activity and emergent properties of biologically-relevant systems. To address this, the authors take advantage of the direct cancellation between the potential energy functions to refactor several popular force fields within AMBERff into the CHARMM file format. These refactored files are compatible with the freely-available NAMD software, which supports MD simulations of biomolecular systems up to two billion atoms on leadership-class supercomputers. Direct comparison of the single point energies for a comprehensive set of test systems show that this process preserves the integrity of the AMBERff force fields. Further, case studies using wellcharacterized biological systems show that these refactored files faithfully reproduce a number of biophysical properties across several classes of biomolecules. Implementation of AMBERff for NAMD will enable application of the leading nucleic acid force field for investigation of viral and cellular processes that involve genome.
An examination of multiple components of emotional processing theory as predictors of symptom change in prolonged exposure for posttraumatic stress disorder
(University of Delaware, 2022) Kelly, Alyssa
Cyclospora cayetanensis is a lesser studied member of the Apicomplexan family of protozoa, which includes more well studied protozoan genera like Cryptosporidium, Eimeria, and Toxoplasma. However, C. cayetanensis is an important protozoan parasite that continues to cause outbreaks of gastroenteritis associated with contaminated fresh produce. Cyclospora oocysts may be transmitted through contaminated surface water, thereby making reliable detection imperative for public health and produce safety. Cyclospora is still considered an emerging pathogen by many, due to the limited understanding and large data gaps surrounding the transmission and survival of oocysts in the environment limitations in detection of oocysts. Polymerase chain reaction (PCR) analysis is used for detection of a presumptive positive water sample. Filtration using the ZVI-sand filtration achieved a 4.30-log reduction of Cryptosporidium parvum compared to 1.82 log reduction using sand filtration. When comparing the two filtration systems, there was a significant difference in efficacy (p < 0.05) with ZVI-sand filtration yielding larger reductions of C. parvum oocysts. For reduction of Eimeria tenella oocysts, ZVI-sand filters achieved a 6-log reduction, whereas sand-only filtration achieved a 2.3-log reduction. There was a significant difference (p < 0.05) in ability to inactivate and remove E. tenella oocysts, the ZVI-sand filtration performed better compared to the sand alone filtration. This study investigated the effects of gaseous chlorine dioxide at varying treatment times on Cryptosporidium parvum on produce, baby cut carrots and grape tomatoes. Grape tomatoes (approx.40g) and baby-cut carrots (approx. 35g) were spot inoculated (106 oocysts) with 100-µl of C. parvum suspension in 10-µl droplets randomly distributed on the produce samples. Inoculated produce samples were treated with 50 g of each gaseous chlorine dioxide precursor for 0, 1 and 3 hours in a 35-L enclosed chamber. Significant reductions were shown at both 1 hour and 3-hour treatment times for both produce types. The results of this work will facilitate the development of novel on-farm filtration technology and guidelines for commercial applications to control parasitic pathogens in agricultural water, thus improving the safety of produce and control of protozoa in agricultural water. A total of seventy-two water samples were collected regularly from various sites in Delaware and Maryland over the course of 17 months (June 2017-October 2018). DNA Primer Sequences for Cryptosporidium Genus-specific PCR Amplification (18S rRNA) used, followed by further testing using VspI and DraII restriction fragment length polymorphism enzyme for speciation confirmation. The nested PCR amplicons were digested with one unit of VspI for distinction between C. parvum and C. hominis. For distinction of C. parvum, C. baileyi and C. serpenti, the nested PCR amplicon were digested with one unit DraII. Twenty-four out of seventy-two water samples were confirmed to contain Cryptosporidium parvum. Through further testing using restriction fragment length polymorphism analysis, one water sample was confirmed to harbor C. cayetanensis or E. neischulzi, which have genetic similarities to Cryptosporidium species. A single sample was identified to be either C. baileyi or C. serpenti, which do not infect humans. Knowledge of parasitic organisms in potential irrigation water sources are essential for correct implementation of water testing and water treatment.
Investigating the role of MARF1-like (MFL) endoribonuclease genes in Arabidopsis
(University of Delaware, 2021) Bogdan, Catherine J.
RNA decay in eukaryotes is mainly carried out by exoribonucleases and endoribonucleases, but the latter have been underappreciated. In metazoan nonsense-mediated mRNA decay (NMD), the endoribonuclease SMG6 cleaves certain mRNAs, leaving the 5' and 3' fragments to be degraded by the exosome and XRN1, respectively. Though SMG6 orthologs are absent in plants, recent studies in Arabidopsis thaliana indicate that some NMD transcripts are cleaved by an unknown endoribonuclease, and their 3' fragments over-accumulate in the absence of XRN4 (the plant cytosolic homolog of XRN1). Metazoan MARF1 is an endoribonuclease in humans and mice that cleaves targeted mRNAs via its catalytic NYN domain. Arabidopsis has several different NYN domain-containing proteins that we predicted to be homologs of metazoan MARF1. Importantly, one of these proteins (AtMFL1) localizes to P-bodies and has an RNA-dependent association with critical NMD factor AtUPF1. I therefore hypothesized that MARF1-like (MFL) endoribonucleases play a role in post-transcriptional control of gene expression in plants. ☐ The major goal of this project was to study the role of selected MFL endoribonucleases in Arabidopsis, particularly AtMFL1. Here I report the organ-specific expression of the AtMFL genes- AtMFL1 and AtMFL2 are ubiquitously expressed in all major organs, while AtMFL3 is minimally expressed in certain organs. I also report the subcellular localization of the AtMFL proteins- AtMFL1 localizes to cytosolic foci, AtMFL2 localizes to the cytosol and cytoskeleton, and AtMFL3 localizes to the nuclear membrane and cytosolic aggregates. Additionally, I report that AtMFL1-like proteins with catalytically active NYN domains are evolutionarily℗ conserved across many plant species. Finally, I provide evidence for the role of AtMFL1 as a cytosolic endoribonuclease that is involved in mRNA degradation.
Apiaceous vegetables mitigate acrolein-induced lung injuries in C57BL/6J male mice
(University of Delaware, 2021) Redding, Mersady C.
Acrolein (Acr) is a ubiquitous, highly reactive aldehyde, abundant in polluted air and cigarette smoke. Acr causes oxidative stress and a cascade of catalytic events and has, thereby, been associated with increased risk of pulmonary disease and other inflammatory diseases. Apiaceous vegetables (carrot family vegetables) are noteworthy for dietary prevention of inflammation and various cancers. However, whether API could prevent Acr-induced pulmonary toxicity has not yet been explored. In this study, we investigated the effects of API on Acr-induced pulmonary damages in male C57BL/6J mice. A total of 20 mice were assigned to either negative control (NEG group; AIN-93G diet only), positive control (POS group; AIN-93G+Acr) or apiaceous vegetable intervention group (API group; AIN-93G+21% API+Acr). After one week of dietary intervention, the POS and API mice were exposed to Acr (10 µmol/kg body weight daily) for five days. During the treatment period, assigned diets remained the same. Prominent indicators of toxicity within the lungs of POS mice were found, including mucus accumulation, macrophage infiltration, and hemorrhage, which appeared to be ameliorated in API mice. Serum and lung inflammation markers, such as tumor necrosis factor alpha (TNF-α) and interleukin 1 beta (IL-1β), were also increased by Acr while reduced by API. Furthermore, poly (ADP-ribose) polymerase (PARP; a necrosis marker) was increased in the POS group while decreased in the lungs of API mice. Similarly, DNA repair genes [e.g., breast cancer type 1 susceptibility protein (Brca1) and proliferating cell nuclear antigen (Pcna)] within the lungs were decreased in POS compared to NEG, but the genes were normalized in API mice. In the liver, API upregulated expression of glutathione S-transferases (GST), which enhanced the metabolism of Acr into water-soluble 3-hydroxypropyl mercapturic acid for excretion, which is consistent with observed reductions in serum Acr-protein adducts. In conclusion, apiaceous vegetables may provide protection against Acr-induced pulmonary damages via downregulation of inflammatory pathways and/or enhancement of the detoxification of Acr.
The course of breastfeeding and duration of feeding human milk in infants with congenital heart disease
(University of Delaware, 2021) Russel, Sarah M.
Background: Although mothers of children with congenital heart disease are able to breastfeed successfully, the research on this population is limited and the effect of breastfeeding challenges and social support on human milk duration is unknown. Research aims/questions: This study aimed to describe the course of breastfeeding in infants with CHD from birth to 12 months of age, with a focus on breastfeeding characteristics (e.g., early lactation experiences, breastfeeding challenges, sources of breastfeeding support) and their relationship to the exclusivity and duration of feeding human milk. Methods: This study was a prospective, observational study conducted at The Children's Hospital of Philadelphia between 2015-2018. Participants were followed throughout the infant's first year of life, with 9 total contacts. Questionnaires were administered to mothers at each visit to obtain information on feeding type, sources of support, and challenges faced during breastfeeding. Results: 75 mother-infant dyads were enrolled. 93% of mothers reported having challenges, the most common (38%) being the infant having trouble latching. The majority of support was received within the first 0.5 months of the infant's life from lactation consultants (72%) and nurses (62%). The mean duration of 'any human milk' and 'human milk only' was 6.4 months and 3.19 months, respectively. Duration of 'human milk only' was related to mothers reporting infants having trouble sucking (p=0.03) and not having enough milk (p=0.04). Human milk durations were not related to receiving support. Conclusion: Mothers of infants with congenital heart disease were able to successfully provide their infants with human milk, despite commonly facing breastfeeding challenges and rehospitalizations.

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