DRUM - Digital Repository at the University of Maryland

DRUM collects, preserves, and provides public access to the scholarly output of the university. Faculty and researchers can upload research products for rapid dissemination, global visibility and impact, and long-term preservation.

Submit to DRUM

To submit an item to DRUM, login using your UMD credentials. Then select the "Submit Item to DRUM" link in the navigation bar. View DRUM policies and submission guidelines.

Equitable Access Policy

The University of Maryland Equitable Access Policy provides equitable, open access to the University's research and scholarship. Faculty can learn more about what is covered by the policy and how to deposit on the policy website.

Theses and Dissertations

DRUM includes all UMD theses and dissertations from 2003 forward.

List of Communities

Collections Organized by Department

A. James Clark School of Engineering

College of Agriculture & Natural Resources

College of Arts & Humanities

College of Behavioral & Social Sciences

College of Computer, Mathematical & Natural Sciences

UM Community-managed Collections

Academy for Excellence in Teaching and Learning Student Essay Award

Alliance for Coastal Technologies

Applied Research Laboratory for Intelligence and Security (ARLIS)

Archaeology in Annapolis

Barrio de Langley Park

Recent Submissions

Essays on Production Economics
(2026) Wang, Shuo; Chambers, Robert G; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation consists of three essays on production economics. Each essay develops and applies structural models to study how producers adapt to uncertainty, weather variability, and pest pressure. The first essay proposes a theory-supervised prediction framework that jointly predicts realized output, total cost, and input demands through an economic model of cost-minimizing behavior. A neural network imputes the unobserved counterfactual outputs, and cost-minimization restrictions discipline these imputations. Applied to three Australian broadacre agricultural zones (1979–2010), the estimator yields moderate transformation elasticities, indicating meaningful but limited capacity to reallocate production across weather events. The second essay develops a structural model to decompose weather impacts on mixed crop-livestock farming systems into output transformation and input adaptation effects. Using longitudinal data from New South Wales, Australia, the analysis shows that water availability is the dominant constraint on farm profitability and that input adaptation partially offsets weather-induced production losses. The third essay investigates the persistence of intensive pesticide use in Chinese cotton production despite the widespread adoption of Bt cotton. Using a damage-control framework embedded in a dual cost structure, the analysis reveals that pest vulnerability declined following Bt diffusion but subsequently rebounded, and that corrective policies would impose substantial private costs on farmers.
MECHANISMS OF MICROBIOTA‑DRIVEN IMMUNE REGULATION IN THE TUMOR MICROENVIRONMENT
(2026) Lam, Khiem Chi; El-Sayed, Najib; Cell Biology & Molecular Genetics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Gut microbiota has emerged as a critical regulator of anti-cancer immunity, yet the mechanisms by which microbial cues shape the tumor microenvironment (TME) remain ill-defined, hampering the development of effective microbiota-targeted interventions. This dissertation addressed this gap by adopting a TME-centric approach, combining single-cell analyses of immune cells across diverse gut microbiota conditions in preclinical models followed by validation with human samples and published datasets. These studies identify a role for microbiota-derived stimulator of interferon genes (STING) agonists in driving type I interferon (IFN) responses in intratumoral monocytes. Such signals program immunostimulatory macrophages and enhance crosstalk between natural killer and dendritic cells. In addition, microbiota-targeted interventions (e.g., supplementation with soluble fiber pectin) remodel the gut microbiome to induce this type I IFN pathway, enhance effector T cell function, and improve tumor control and response to immune checkpoint blockade therapies. Extending this analysis across 19 syngeneic tumor models further demonstrates that the efficacy of microbiota-targeted interventions is not universal but instead depends on tumor-intrinsic factors such as cancer type, immune state, and metabolic requirements. Collectively, this dissertation defines the cellular and molecular mechanisms by which gut microbiota programs the TME to support anti-tumor immunity and identifies key determinants that govern such responses. These findings provide a framework for the development of microbiota-targeted strategies to improve outcomes for individuals with cancer.
A SPECTRAL DATA ASSIMILATION SYSTEM FOR WAVEWATCH III USING THE FOUR-DIMENSIONAL LOCAL ENSEMBLE TRANSFORM KALMAN FILTER
(2026) DiPasqua, Samuel; Ide, Kayo; Mathematics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Ocean waves are created from energy passing through water with severe weather, such ashurricanes, creating hazardous waves. These hazardous waves pose risks to offshore operations, maritime operations, and coastal communities. Accurate wave forecasting provides critical information to these fields. Conventional wave data assimilation (DA) systems typically update mean wave parameters such as significant wave height, which limits their ability to represent the full wave spectrum and enforce physical consistency. This dissertation develops and evaluates a spectral wave data assimilation system for WAVEWATCH III based on the Local Ensemble Transform Kalman Filter. The LETKF analysis directly updates weights of the ensemble members, which makes it a versatile analysis for updating different analysis control variables. This proposed system introduces a logarithmically transformed spectral analysis control variable to weakly constrain the non-negative model state from WAVEWATCH III. Then, the 3D and 4DLETKF are compared to determine the impact of incorporating the model trajectory into the analysis. Lastly, shortest path and shortest distance localization are compared to determine the impact of observations across landmasses. Together, these factors result in a unique wave DA system that focuses on improving the physical characteristics of the wave spectrum. Observing system simulation experiments (OSSEs) were performed using significant wave height observations from buoys and satellite altimeters. Results show that spectrally-averaged root mean square error (RMSE) is similar across the different tested analysis control variables at the time of analysis. However, the analysis in significant wave height space reveals more meaningful corrections in RMSE and bias over a 24 hr forecast period. In significant wave height forecasts, changing the analysis control variable leads to significantly different forecasts. Comparisons between 3D and 4D-LETKF configurations demonstrate that 4D DA achieves persistent improvements to significant wave height forecast skill across each of the analysis control variables. The comparison between shortest path and shortest distance localization shows minimal aggregate differences because of the limited regions affected by the change in localization method and because the model, WAVEWATCH III, is wind-driven. These findings demonstrate the importance of the analysis control variable and wave evolution for wave DA systems.
Disequilibrium in Methane Clumped Isotopologue Signatures as a Tool for Assessing HIstorical Models and Thermometry
(2026) Turner, Austin R.; Farquhar, James; Geology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
As the simplest organic compound, methane is an important component in environments that contain evidence of life – including both the troposphere and deep ocean hydrothermal vents. In the atmosphere, methane acts as a greenhouse gas and contributes to the changing climate. In hydrothermal vent environments, methane acts as a source of electrons and powers these ecosystems via chemosynthesis. Methane can have thermogenic, abiotic, and microbial sources with overlapping bulk isotope signatures, which causes sources to be difficult to distinguish; additionally, methane undergoes sink and equilibrations processes that further change its isotopic signatures. In this thesis, new and updated methods of analyzing methane for its clumped isotopologue (∆13CH3D and ∆12CH2D2) signatures were developed to further disentangle contributing sources and constrain isotope effects. These were explored in two ways: 1) by using methane in archived ambient air sampled from different latitudes (25 °N to 60 °S) aboard a polar expedition called Deep Freeze ‘02 that took place almost 25 years ago to assess the validity of previous historical models of clumped isotopologue trends (projected backwards form modern values), and 2) by generating methane from catalyzed and uncatalyzed high temperature/pressure reactions (using the methyl-bearing tetrakis(trimethylsilyl)silane as a reactant and simulating hydrothermal conditions) in water of varying δD to assess to what extent the resulting isotopic signatures reflect an approach towards theoretical thermodynamic equilibrium. The analysis of methane in archive air found expected latitudinal trends in concentration (high concentrations in the Northern Hemisphere and a gradient going towards lower values in the Southern Hemisphere) as well as bulk isotopic signature (a shift towards more positive isotopic values going from N-S). No significant trend in clumped isotopologue signatures was found along the latitudinal range present in the samples, which should be investigated further. Mixing and Rayleigh sink fractionation models were also employed, and it was found that both bulk and clumped isotopic data from the archived samples showed agreement with models (except for the Rayleigh sink model of 13CH3D trends). Historical models which assumed higher and/or underreported fossil fuel methane were also supported by the data. Future work will involve the construction of multiple-box models (to account for the latitudinal gradient and interhemispheric transport) as well as repeated measurements of these samples and analysis of other latitudinal samples from different time periods. The analysis of methane from hydrothermal experiments found that the δDCH4 signatures display an approach towards equilibrium with increasing temperature. There was also an observed approach towards equilibrium in ∆12CH2D2 signatures when excluding outliers at extreme initial δDH2O, though ∆13CH3D data show no significant trend towards equilibrium. Additionally, limited comparisons between catalyzed and uncatalyzed samples support the formation of CH4 by the addition of 1 H/D from H2O, as well as a potential interaction between methane and the catalyst which shifts bulk carbon signatures. This prompts more investigation into gaps in the temperature and initial δDH2O composition ranges (and into the precipitates that form in the reactions) as well as the kinetics of the equilibration (which may be addressed by timed experiments).
Essays in Public Finance and Transportation
(2026) Braslavskiy, Arseniy; Cropper, Maureen; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Economic models often focus on optimal governmental actions and abstract from the actual implementation. This dissertation considers practical implications of public policies in the complex system of U.S. fiscal federalism. These policies may have unexpectedly large effects due to intergovernmental interactions, as in Chapter 1. At the same time, the incentives of local officials tasked with spending money might not be aligned with what the federal government intended, as I show in Chapter 2. Finally, some policies might have unintended consequences and the patchwork of state laws, instead of being a policy laboratory, may conceal this, as I demonstrate in Chapter 3. While transportation is the joint theme of these three chapters, their conclusions can be applied to a wide range of policy domains. Chapter 1 examines how targeted federal grants affect spending on public transit in a three-level fiscal system. The analysis uses comprehensive U.S. expenditure data from 2000–2019 and exploits an exogenous shock from the 2009 American Recovery and Reinvestment Act (ARRA). ARRA funds were apportioned to Urbanized Areas through preexisting formula programs, independent of potential changes in transit investment. I find that each $1 of ARRA apportionment led to an additional $1.76 of capital spending from all sources over 2009–2019, or $2.31 when scaled by the first-stage effect on federal capital grants. This reflects two distinct phases: an initial rise in federally funded expenditures with no displacement of state or local spending (the flypaper effect), followed by substantial crowding-in of state funding to the same localities. This additional spending was directed primarily toward maintaining existing bus fleets and did not increase service provision or ridership. Cross-state variation in institutional characteristics points to the negotiation channel as the primary mechanism: ARRA lowered the cost for local officials of securing flexible state funding. Chapter 2 studies how local transit agencies spent $8.4 billion of one-time capital from the 2009 stimulus, distributed by a formula and left to local discretion. Using a large language model to extract project-level data from grant texts, I find that 22 percent of projects added service capacity, 30 percent improved the quality of existing service, and 48 percent maintained it, while agencies' pre-existing characteristics explain almost none of this split. On the other hand, the type of spending mattered for the outcomes: areas that spent on expansion fared no differently from those that spent on maintenance, while areas that spent on quality improvement provided more service afterward. A simple model explains why. A system with excess capacity already carries the riders its quality attracts, so added vehicles sit unused and only an improvement in quality can attract new passengers. Empirical results thus suggest that the average American transit system overinvests in capacity and underinvests in quality. A back-of-the-envelope reallocation toward quality implies roughly 3 to 4 percent more national ridership. Chapter 3 re-examines the finding by Anderson, Hansen, and Rees (2013) that medical marijuana laws decrease traffic fatality rates by 10.4%. I document that legalizing states were already experiencing declining fatalities prior to legalization, even after controlling for state-specific linear trends in a Two-Way Fixed Effects model. To address these pre-trends, I apply the Imputation Procedure (IP) by Borusyak, Jaravel, and Spiess (2024), which estimates state-specific trends using only not-yet-treated observations. Depending on the inclusion of potentially confounding covariates, my IP estimates suggest either a 12% increase or a zero effect on fatalities. I also show that the average state effect differs substantially from the average individual effect, indicating large heterogeneity across states. Much of the original negative result is driven by California, which accounts for over half of the population-weighted estimate. This state consistently exhibits one of the largest estimated negative effects and one of the steepest negative pre-trends.