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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.

 
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Equitable Access Policy

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

Theses and Dissertations

DRUM includes all UMD theses and dissertations from 2003 forward.

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St. Dunstan editions prices, 1903-2024
(2024) Hovde, Sarah
This is a dataset of auction and sale prices between 1903 and 2024 for the St. Dunstan Illuminated Editions, a set of de luxe editions published by George D. Sproul between 1901-1904. The data accompanies a forthcoming article introducing the St. Dunstan volumes (this record will be updated upon publication).
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System Analysis for a Fusion Propelled Spacecraft
(2024) Chen, Yuca; Dorris, Zachary; Gallardo, Antonio; Gupta, Aroni; Hoffman, Caleb; Humphreys, Austin; Mejia, Jeremy; Wiedman, Alexander; Sedwick, Raymond J.
Nuclear-fusion-based power generation has a multitude of potential applications, one being spacecraft propulsion. The extreme specific impulse achievable with fusion prod- ucts provides for large total momentum changes while using substantially less propellant. Several auxiliary subsystems are required to support the application of fusion-based power to spacecraft propulsion. These subsystems include one for efficient propellant heating, one for power generation, and one for reactor shielding and structural integrity. Two centrifugally-confined magnetic mirror configurations are utilized, one to confine the fu- sion plasma and one to trap and heat an auxiliary propellant in order to increase thrust. Estimates on propellant mass requirements and design constraints on the propellant cham- ber are derived. Power generation techniques utilizing byproduct radiation from the fusion process are integrated into the reactor structure. Waste heat from neutron power conver- sion provides preheating of propellant, and a radiator was optimally sized for removing the remaining waste heat. Solid-state thermionic power conversion technology is explored to utilize bremsstrahlung radiation. Models for the magnet shielding are created, and the rate of neutron absorption and energy deposition for several different shielding materials are de- termined. In order to address the tensile and compressive stresses resulting from the fusion reactor magnets, support beam cross-sections are optimized. A system of heat pipes, mag- nets, and an enclosing shroud is designed to support reactor functions and prevent damage to system components. Comparisons are drawn between existing propulsion systems and a model fusion system. The viability of our model fusion system for solar system exploration is discussed.
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ADDRESSING ANTIMICROBIAL RESISTANCE: ALOE VERA’S POTENTIAL FOR BACTERIAL INHIBITION AND DERMAL FIBROBLAST PROLIFERATION
(2024) Mansoor, Iman; Rangachar, Nimisha; Lim, Natalie; Arango, Nadia; Tesfamariam, Ruth; Mohommed, Joshua; DeBus, Alexandra; Noguera, Mateo; Thangavelu, Aditi; Cao, Kan
Antimicrobial resistance has been an emerging global issue over the last several decades. Acquired resistance renders antimicrobial agents useless, with a recent report projecting ten million deaths by 2050 caused by drug-resistant infections. In response, research output on biomedical and public health solutions to AMR has significantly increased, including investigations on active compounds in medicinal plants. Aloe vera is known for anti-inflammatory, antibacterial, and cell proliferative properties stemming from its anthraquinones, flavonoids, and polysaccharides. In this review, Team Aloesporin applied qualitative and quantitative techniques to characterize the state of AMR awareness and discuss Aloe vera’s capacity for serving as an antimicrobial, wound-healing agent. First, a public opinion survey was distributed at the University of Maryland, College Park to assess community knowledge of antimicrobial resistance and related practices. Aloe vera’s potency was then investigated through a minimum inhibitory concentration assay with Staphylococcus aureus and Staphylococcus epidermidis. Lastly, a cell proliferation assay was designed for dermal fibroblasts with 2.5% w/v Aloe vera, 100 nM methylene blue, and 100 nM bacitracin-supplemented media. Though the public opinions survey provided insight into the gaps in knowledge surrounding antimicrobial resistance and consumer practices, the preliminary bacterial and dermal fibroblast assays yielded inconclusive results regarding Aloe vera’s respective antibacterial and proliferative effects. This research suggests a need for further investigation of the optimal state and concentration of Aloe vera for wound-healing and effective antimicrobial stewardship to address the escalating issue of antimicrobial resistance.
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Vehicle-to-Vehicle Charging: Prototype Development and Future Potential
(2024) Hatz, Garett; Modh, Samarth; Scarpelli, Levi; Beaudoin, Brian
As widespread electric vehicle (EV) adoption faces hurdles due to limited charging accessibility, this research explores the potential of Vehicle-to-Vehicle (V2V) charging technology, particularly for residents in multi-unit dwellings. To assess the feasibility of this concept, we constructed a functional V2V charger prototype through multiple iterations. Using various Arduino projects focused on PWM and charging circuits, we achieved a successful V2V charger prototype, enabling data collection to inform future advancements in this promising technology.
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Enhancement of Detection and Diagnosis of Non-Small Cell Lung Cancer Through The Improvement of Machine Learning and AI Models
(2024) Beshaw, Yael; Cancro, George; Chang, Darren; Fomengia, Jayda; Mehta, Vanshika; Vedantham, Arjun; Yaragudipati, Ritvik; Feizi, Soheil
Due to low survival rates and an unparalleled burden of non-small cell lung cancer on underserved communities, there is great urgency for innovative and accessible methods that will improve healthcare access for lung cancer patients. To combat this inequity, Team DOC aims to develop an AI model that is able to not only improve lung cancer diagnoses but also predict the progression of non-small cell lung cancer. We intend to evaluate the performance of a convolutional neural network on the LIDC-IDRI dataset and retrain the final layers of the model to improve its performance on the same dataset. Repeating this process on different model architectures allows us to determine which model performs optimally, providing a foundation to develop an end-to-end explainable AI workflow that can extract clinically relevant predictions of cancer progression for further analysis. Throughout our training process, we resolve to address the accuracy and potential for bias. Additionally, we are carrying out a survey among underserved populations and communities to discern the need for our improved cancer detection model. We hope that our model will be able to be implemented in communities with lack of access to healthcare systems to bridge the gap between underprivileged communities and unbiased care.