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MARS is a repository service of Mason Publishing and the Digital Scholarship Center (DiSC) at the George Mason University Libraries. MARS provides enduring, stable, well-indexed access to a wide range of scholarship from the Mason community, such as Electronic Theses and Dissertations (ETDs), articles, presentations, reports, and creative work. Learn more about publishing, sharing, and preserving research data with the George Mason University Institutional Dataverse, and our other repository services.

To start publishing your content in MARS, please contact us by using our online form. Questions? Please email publish@gmu.edu.


Recent Submissions

A Systematic and Comparative Study in Deep Learning Approaches in Extraocular Muscle Segmentation and Analysis in Orbit Magnetic Resonance Images
(2023-08) Qureshi, Amad Aamir; Wei, Qi
Strabismus is an ocular condition characterized by binocular misalignment, which impacts about 5% of the global population. It can cause double vision, reduced vision, and impair the quality of life. Accurate diagnosis and treatment planning often benefits from the anatomical evaluation of the extraocular muscles (EOMs) that can be obtained by imaging modalities, such as magnetic resonance imaging (MRI). Such image-based examination requires segmenting the ocular structures from images, which is a labor and time-intensive task, subject to error when done manually. Deep learning-based segmentation has shown promise to outline anatomical structures automatically and objectively. We performed three sets of experimentation for EOM segmentation via DLmethods. Furthermore, we analyzed the performance of the deep learning methods through F-measure-based metrics, intersection over union (IoU) and Dice coefficient, and estimation of the EOM centroid (centroid offset). We first investigated the performance of U-Net, U-NeXt, DeepLabV3+, and ConResNet in multi-class pixel-based segmentation of the EOMs from ocular MRI taken in the quasi-coronal plane. Based on the performance evaluation (visual and the quantitative metrics mentioned), the U-Net model achieved the highest overall segmentation accuracy, and lowest centroid offset. It was noted that segmentation accuracy varied in spatially different image plane – relative to the middle slice (optic nerve junction point) in the MRI stack. In the second set of experiments, we compared the performance of the U-Net model with its variants, UNeXt, Attention U-Net and FD-UNet and subjected the prediction outputs to the same evaluation as before, with U-Net achieving the best performance. We also explored methods in an attempt to improve the model performance – particularly with data augmentation and enhancement, where methods such as Adaptive Gamma Correction and CLAHE enhancement were used with the U-Net model. No significant difference was observed when CLAHE, Adaptive Gamma Correction and a dataset with unenhanced, CLAHE, and adaptive gamma corrected images were tested against unenhanced data, however, did result in better quantitative performance than the standard augmentation technique. Our study provides the insights into the factors that impact the accuracy of deep learning models in segmenting the EOMs, such as spatial slice location, image quality, and contrast and demonstrate the potential of these models in translating into 3D space for potential diagnosis and treatment planning for patients with strabismus and other ocular conditions.
A Queer Wall in the Head: Using Oral Histories to Map Gay Desire Across Cold War Germany
(Johns Hopkins University Press, 2022-10) Huneke, Samuel Clowes
This article uses oral histories to examine divergences in how gay men from East and West Germany remembered the sexuality of their youths. Finding that East German men recalled their sexual exploits in far more detail than did West German men, the article argues that this divergence is the result of a complex interlacing of factors. Ultimately, the article contends that these factors reveal a queer wall in the head that continues to delimit how gay German men understand their actions, their pasts, and their identities.
Comparison of Commercial DNA Extraction Kits for Extraction of DNA From Bones Prepared Using the Novel Theralin Method
(2023-11-06) Bowers, Madalyn; Wilson, Mark
The extraction of DNA from bones to produce high quality samples is extremely important in cases involving unidentified human remains and victims of mass disasters, and many times in these cases, only human bone is available as a source of DNA that can be used to identify the individual. A novel method of preparing bones for extraction using TheralinTM, a precipitating fixative that demineralizes bone, has been developed by researchers at George Mason University. This novel method essentially transforms the bone into a gum-like state that allows for the bone material to be cut into smaller pieces and then digested using lysis buffers. Research has not yet been performed to determine an ideal method of DNA extraction from Theralin-prepared bone, and this study seeks to answer that question. In this study, four different methods of DNA extraction using commercial extraction kits were carried out on bone samples that were prepared using the Theralin method. These extraction methods were the Qiagen QIAamp® DNA Investigator kit protocol with MinElute columns, the PrepFilerTM BTA Forensic DNA Extraction kit protocol with PrepFiler magnetic beads, a combination method using the Qiagen lysis buffers with the PrepFiler magnetic beads, and a combination method using the PrepFiler BTA lysis buffers with the Qiagen MinElute columns. Following extraction with these four methods, the DNA extracts were quantified using the QuantifilerTM Trio DNA Quant kit, and the quantification values of the extracts were compared to determine which method provided the highest amount of DNA. The extracts were amplified using the GlobalFilerTM PCR Amplification kit and genotyped using the Applied Biosystems 3500 Genetic Analyzer with GeneMapperTM ID-X v1.6 software. The STR profiles were compared to the known profiles of the bone samples and analyzed for allelic dropout and signal strength metrics to determine the quality of each DNA extract. The results of this study provided insight into the usefulness and efficiency of the Theralin method of bone preparation, combined with a commercially available DNA extraction technique, to give quality DNA extracts that can be used for downstream applications.
A Comparative Analysis of How Skills-based and Scenario-based Simulations Support Learning with EFAST as an Exemplar Skill
(2015-12) Battista, Alexis; Kitsantas, Anastasia
This study presents an investigation into how learning was supported in skills- and scenario-based simulations, and examines the influence of simulation context on the activities, guided participation, self-efficacy, and learning outcomes of student healthcare professionals. Using a mixed-methods comparative case study design, eight student healthcare professionals, naïve to ultrasound, were recruited to learn the Extended Focused Assessment using Sonography for Trauma (EFAST) exam. Following completion of a pretest evaluation of EFAST performance, students were randomly assigned to partake in either two skills-based or scenario-based simulation practice sessions. Qualitative data included video recordings of simulations, and student’s written reflections. Quantitative data included the EFAST self-efficacy scale and the Radiology Direct Observation of Procedural Skills (RAD-DOPS), which assessed students’ performance of the EFAST. Activity theory and guided participation informed analysis of students’ engagement during participation in skills-based and scenario-based simulations. Descriptive statistics were used to examine students’ performance on RAD-DOPS assessments and self-efficacy beliefs. Findings suggest that learning was supported in both simulation contexts when students, together with peers and faculty, engaged in clinically relevant activities, using culturally relevant tools and artifacts. The findings also suggest that students’ activities, guided participation, learning reports, and SE differed. All students reported learning the EFAST; however, scenario-based students reported learning about their role as member of the healthcare team, and how to integrate the EFAST into patient care. Students in skills-based simulations rated their self-efficacy for EAST numerically higher than did scenario-based students. Skills-based students were rated more highly on the posttest. Recommendations for practice are discussed.
An Introduction to Applications of Access
(Network Design Lab, University of Sydney, 2021) Ermagun, Alireza; Levison, David
From its source Latin accedere, the assimilated form of ad and cedere, access means "to approach." It conveys the "habit or power of getting into the presence of someone or something." The contemporary meaning differs, but has not strayed too far from the origin. Access means freedom, possession rights, and other means of benefiting from resources. It offers neither what people will do, nor what people want to do, rather what people could do. Transport access is a product of mobility and place and immediately relates to the transport network and the relative location of human activities and housing. However, there is still confusion among engineers and planners in differentiating access from mobility. Mobility indicates one’s ability to move easily. It encompasses both speed and travel time by defining how far one can travel in a given time. Access, however, is concerned with the opportunities that can be reached in a given time.