Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item PROBING BIOPHYSICAL INTERACTIONS TO UNDERSTAND VIRAL DIFFUSION AND PARTICLE FATE IN THE AIRWAY MUCOSAL BARRIER(2023) Kaler, Logan; Duncan, Gregg A; Biophysics (BIPH); Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The mucus barrier in the airway is the first line of defense against inhaled particulates and pathogens. Within the mucus barrier, large, heavily glycosylated gel-forming mucin proteins form a network to trap particles for removal. Influenza A virus (IAV) must first cross the mucus barrier before reaching the underlying airway epithelial cells to cause infection. On the IAV envelope, hemagglutinin (HA) binds sialic acid on the surface of the cell to initiate viral entry. However, HA preferentially binds sialic acid attached to galactose by either an ⍺2,3 or ⍺2,6 linkage. In addition to the cell surface, sialic acid is found on mucins and is thought to act as a decoy receptor to entrap the IAV within the mucus layer. However, neuraminidase (NA) on the envelope of IAV cleaves the bond between HA and sialic acid, releasing the virus. While the mechanism of IAV infection has been characterized, the interplay between mucus biophysical properties and the binding of IAV within the mucus network prior to infection requires further investigation. The overall objective of this dissertation is to understand how IAV moves through the mucosal barrier to subsequently cause infection. We hypothesize the structural features of the mucus gel network are responsible for the changes in IAV movement, rather than the binding and unbinding of the virus. To investigate this, we first analyzed the movement of IAV in ex vivo mucus from human endotracheal tubes. In order to further analyze this movement, we developed a novel analysis to calculate the dissociation constant of IAV-mucus binding in a 3D gel network environment. Using this data, we established a pipeline for estimating the passage of particles, including IAV, through the airway mucosal barrier. A machine learning-based trajectory analysis was employed to classify individual trajectories in order to calculate the percentage of particles able to cross the mucus barrier within a physiologically relevant time frame. Lastly, we investigated the effect of sialic acid binding preference on diffusion of IAV through mucus collected from different in vitro human airway epithelial cell cultures. The combined results of these studies confirmed our hypothesis that the mucus microstructure rather than the adhesive interactions of IAV to the mucins was responsible for the differences in IAV diffusion. This work provides further insight into role of the mucosal barrier in IAV infection and identifies the mucus gel network microstructure as a target for the development of therapeutics against IAV.Item PARAMETRIC AND NON-PARAMETRIC APPROACHES FOR THE PREDICTION OF THE DIFFUSION OF THE ELECTRIC VEHICLE(2020) Bas Vicente, Javier; Cirillo, Cinzia; Zofío Prieto, José Luis; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Driven by environmental awareness and new regulations for fuel efficiency, electric vehicles (EVs) have significantly evolved in the last decade, yet their market share is still much lower than expected. In addition to understanding the reasons for this slow market penetration, it is crucial to have appropriate tools to correctly predict the diffusion of this innovative product. Recent works in forecasting the EV market combine substitution and diffusion models, where discrete choice specifications are used to address the former, and Bass-type to account for the latter. However, these methodologies are not dynamic and do not consider the fact that innovation occurs through social channels among members of a social system. This research presents two advanced methodologies that make use of real data to evaluate the adoption of the EVs in the State of Maryland. The first consists of a disaggregated substitution model that considers social influence and social conformity, which is then embedded in a diffusion model to predict electric vehicle sales. The second, in contrast, relies on non-parametric machine learning techniques for the classification of potential EV purchasers. Both make use of data collected through a stated choice experiment specifically designed to capture the inclination of users towards EVs.Item YEAR-ROUND DETERMINATION OF METHANE (CH4) SOURCES AND SINKS IN ARCTIC LAKES USING CONTINUOUS AND AUTONOMOUS SAMPLING(2020) McIntosh Marcek, Hadley; Lapham, Laura L; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Methane (CH4) is a potent greenhouse gas and its concentration has been increasing in the atmosphere. While natural emissions from inland water bodies are known to be important, there is large uncertainty in the amount of methane released from lakes to the atmosphere, especially from Northern latitudes. Part of this is due to limited sampling in these systems during dynamic periods, such as ice-over and ice-melt. To better understand these temporal dynamics, I used autonomous, continuous samplers (OsmoSamplers) to collect lake water year-round over two years (2015-2017). Lake water was collected at a fine temporal resolution to provide time-integrated (~1 week) samples from multiple Arctic lakes within the Mackenzie Delta. The Mackenzie Delta is a lake-rich, productive environment that is expected to be a significant source of methane to the atmosphere. Lakes spanning the central delta and outer delta were sampled for methane concentration and stable carbon isotope ratio (δ13C-CH4) changes, ion concentrations, and water column characteristics were measured with continuous sensor data (temperature, water pressure, conductivity, light, and dissolved oxygen). These unique time-series datasets show lakes exhibit a close coupling of dissolved oxygen, and other electron acceptors, with the timing of methane increasing during ice-cover. The increase in methane concentrations is primarily from diffusion out of sediments and possibly water-column methanogenesis. One lake in the outer delta exhibited thermogenic gas bubble dissolution that contributed to under-ice methane concentration increases. Following ice-melt, lake depth appears to impact methane release to the atmosphere. Shallower lakes exhibit rapid fluxes followed by significant microbial methanotrophy. Deeper lakes in the central delta are connected to groundwater, though it does not appear groundwater transports methane. This is the first study of dissolved methane and gas bubble 14C-age in the Mackenzie Delta and shows that dissolved methane is produced primarily from modern carbon sources, such as macrophyte biomass and terrestrial material, but some methane transported in gas bubbles is significantly older, with seeps in the outer delta rapidly releasing radiocarbon-dead, thermogenic methane. This study demonstrates the importance of multi-lake studies particularly with fine scale temporal sampling to understand methane processes in seasonally ice-covered lakes.Item Information Diffusion: A Study of Twitter During Large Scale Events(2014) Rogers, Christa Daniella; Herrmann, Jeffrey; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The diffusion of information through population affects how and when the public reacts in various situations. Thus, it is important to understand how and at what speed important information spreads. Social media platforms are important to track and understand such diffusion. Twitter provides a convenient and effective way to measure it. This study used data obtained from 15,000 Twitter users. Data was collected on the following events: Hurricane Irene, Hurricane Sandy, Osama Bin Laden's capture, and the United States' 2012 Presidential Election. Information such as the time of a tweet, the user name, content, and the ID was analyzed to measure the diffusion of information and track the trajectory of retweets. The spread of information was visualized and analyzed to determine how far and how fast the information spread. The results show how information spreads and the content analysis of data sets indicate the importance of different topics to users.Item Modeling the Resupply, Diffusion, and Evaporation of Cesium on the Surface of Controlled Porosity Dispenser Photocathodes(2013) Pan, Zhigang; O'Shea, Patrick G; Jensen, Kevin L; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)High quantum efficiency (QE) photocathodes are useful for many accelerator applications requiring high brightness electron beams, but suffer from short operational lifetime due to QE decay. For most photocathodes, the decrease in QE is primarily attributed to the loss of a cesium layer at the photocathode surface during operation. The development of robust, long life, high QE photoemitters is critically needed for applications demanding high brightness electron sources. To that end, a controlled porosity dispenser (CPD) photocathode is currently being explored and developed to replace the cesium during operation and increase photocathode lifetime. A theoretical model of cesium resupply, diffusion, and evaporation on the surface of a sintered wire CPD photocathode is developed to understand and optimize the performance of future controlled porosity photocathodes. For typical activation temperatures within the range of 500K--750K, simulation found differences of less than 5 % between the quantum efficiency (QE) maximum and minimum over ideal homogenous surfaces. Simulations suggest more variation for real cases to include real surface non uniformity. The evaporation of cesium from a tungsten surface is modeled using an effective one-dimensional potential well representation of the binding energy. The model accounts for both local and global interactions of cesium with the surface metal as well as with other cesium atoms. The theory is compared with the data of Taylor and Langmuir comparing evaporation rates to sub-monolayer surface coverage of cesium, gives good agreement, and reproduces the nonlinear behavior of evaporation with varying coverage and temperature.Item LAMINAR SMOKE POINTS OF COFLOWING DIFFUSION FLAMES IN MICROGRAVITY(2012) DeBold, Thomas; Sunderland, Peter B; Fire Protection Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Nonbuoyant laminar jet diffusion flames in coflowing air were observed aboard the International Space Station with an emphasis on laminar smoke points. The tests extended the 2009 Smoke Points In Coflow Experiment (SPICE) experiment to new fuels and burner diameters. Smoke points were found for methane, ethane, ethylene, and propane burning in air. Conditions included burner diameters of 0.76, 1.6, 2.1, and 3.2 mm and coflow velocities of 3.0 - 47 cm/s. This study yielded 57 new smoke points to increase the total number of smoke points observed to 112. Smoke point lengths were found to scale with burner diameter raised to the -0.67 power times coflow velocity raised to the 0.27 power. Sooting propensity was observed to rank according to methane < ethane < ethylene < propane < 50% propylene < 75% propylene < propylene. This agrees with past normal gravity measurements except for the exchanged positions of ethylene and propane. This is the first time a laminar smoke point has been observed for methane at atmospheric pressure.Item Moving Social Disorder Around Which Corner? A Case Study of Spatial Displacement and Diffusion of Benefits(2011) Wyckoff, Laura Ann; Paternoster, Ray; Criminology and Criminal Justice; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Prior research seeking to understand the spatial displacement of crime and diffusion of intervention benefits has suggested that place-based opportunities - levels and types of guardianship, offenders, and targets - explain spatial intervention effects to places proximate to a targeted intervention area. However, there has been no systematic test of this relationship. This dissertation uses observational and interview data to examine the relationship, in two street-level markets, between place-based opportunities and spatial displacement and diffusion of social disorder. The street segment is the unit of analysis for this study, since research shows crime clusters at this level and it is a unit small enough to accurately represent the context for street-level crime opportunities. The study begins by investigating if catchment area (an area proximate to an intervention area) segments with similar opportunities to the target area segments differentially experienced parallel intervention effects as compared to segments with dissimilar opportunity factors. These analyses resulted in null findings. The second set of analyses examined if place-based opportunities predicted the segments which fall into a high diffusion group or a displacement group, as compared to a low/moderate group. These analyses resulted in primarily null findings, except for the measures of public flow and the average level of place manager responsibility which positively predicted the segments in the high diffusion group, as compared to the low/moderate diffusion group. A third set of analyses was also performed where the outcome measure was the odds of the occurrence of a social disorder incident in a measured situation period in the segment during the intervention. These analyses revealed that the situations within segments which had a greater number of possible targets and offenders with a lack of guardianship were more likely to experience incidents of social disorder, reinforcing past findings about the relationship between social disorder and opportunities at place. Place-based opportunity factors are likely important factors in understanding parallel spatial intervention effects, but the null findings suggest additional research is needed to better understand these effects.Item The Failure to Innovate: A Study of Non Adoption of Computerized Crime Mapping in American Police(2008-05-19) Mazeika, David Michael; Weisburd, David; Criminology and Criminal Justice; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Scholars have noted a recent accumulation of innovations in policing (Bayley, 1994; Weisburd & Braga, 2006; Weisburd & Eck, 2004). Due to the increase and scope of these innovations, some scholars have called this the most dramatic period of innovation in policing (Bayley, 1994). Studies have tried to explain why this dramatic period of innovation occurred, but while in general the study of the diffusion of innovations is widespread (Rogers, 2003), there have been relatively few in policing (Klinger, 2003; Weisburd & Braga, 2008). Particularly, little is known about the relationship between resources and innovation. The current work attempts to better explain this relationship by increasing the scope of resources measured and by disentangling the effects of measures employed in the extant literature. In contrast to previous studies (Chamard, 2004; King, 1998; Mastrofski et al., 2003; Mastrofski et al., 2007; Skogan & Hartnett, 2005; Weisburd et al., 2003), findings from the current work indicate that various measures of resources are not related to innovation and those who fail to innovate.