Gemstone Team Research

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The Gemstone Program at the University of Maryland is a unique multidisciplinary four-year research program for selected undergraduate honors students of all majors. Under guidance of faculty mentors and Gemstone staff, teams of students design, direct and conduct significant research, often but not exclusively exploring the interdependence of science and technology with society. Gemstone students are members of a living-learning community comprised of fellow students, faculty and staff who work together to enrich the undergraduate experience. This community challenges and supports the students in the development of their research, teamwork, communication and leadership skills. In the fourth year, each team of students presents its research in the form of a thesis to experts, and the students complete the program with a citation and a tangible sense of accomplishment.

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Now showing 1 - 20 of 166
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    Developing A Broadly Protective MRNA Influenza Vaccine: A Review
    (2022) Acquah, Wellington; Amini, Cameron; Buddula, Saharsh; Chen, Michelle; Chintala, Navya; Dang, Quinn; Ferziger, Noa; Hollis, Grace; Jameison, Devin; Jayaram, Jyostna; Manus, Joseph Anthony; Rosenberg, Jacob; Zhiteneva, Julia; Yarwood, Stephanie
    Current influenza vaccines are limited in their efficacy due to antigenic drift of the hemagglutinin target; advances in mRNA vaccines in response to the COVID-19 pandemic may provide a new direction for influenza vaccine development. Existing literature shows that mRNA vaccines have higher efficacy in preventing illness, hospitalizations, and death. We evaluated eleven influenza A viral proteins as potential targets for an mRNA vaccine under the following criteria: degree of conservation, ability to elicit a robust immune response, and ability to prevent illness and death. We recommend future researchers direct their efforts towards developing an annually administered tri-sequence mRNA vaccine targeting hemagglutinin head (HA1), the matrix 2 ectodomain (M2e), and nucleoprotein (NP). Development of a highly effective influenza mRNA vaccine would be significant for prevention of disease burden worldwide.
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    Analysis of Whole-Brain Resting-State MRI Using Multi-Label Deformable Offset Networks and Segmentations Based Attention with Explorations into the Ethical Implications of Artificial Intelligence in Clinical Psychiatry Settings and Care
    (2022) Agarwal, Vatsal; Ayoroa, Evan; Burdick, Ryerson; Ganeshan, Aravind; Paliyam, Madhava; Wood, Sam; Lee, Caitlin; Akhtarkhavari, Sepehr; Inala, Shika; Matharu, Sagar; Mupparapu, Neelesh; Deane, Anil
    Due to the poor understanding of the underlying biological mechanisms of psychiatric disorders, diagnoses rely upon symptomatic criteria and clinicians’ discretion. Reviews of these criteria have revealed issues of heterogeneity, over and under specificity, and symptom overlap between disorders. Deep learning provides a method to produce quantifiable diagnostic labels based upon biological markers such as specific features of brain anatomy or functionality. In practice, these methods fail to indicate how a particular result was determined, raising major obstacles for clinical implementation.To improve the efficiency and interpretability of existing deep networks, we have developed a novel atlas-based attention module to more easily capture global information across different areas of brain function. Our model can be extended to symptom level classification using NIMH data to give clinicians usable information outside of broad disorder classification. We have compared our model against leading 3D deep learning frameworks and have shown that our novel atlas-based attention module achieves 88% F1 and 91% accuracy on the UCLA Consortium for Neuropsychiatric Phenomics dataset. We have embedded our model with elements like deformable convolutions, gradient activation visualizations, and occlusion testing to show model attention and function. In addition to the lack of explainability, addressing the ethical issues surrounding clinical implementation of artificial intelligence is necessary before usage can become a reality. We identified a series of regulatory recommendations to address pertinent ethical concerns of equity and bias during both model development and clinical usage. We propose a standardized protocol for developing a clinical reference standard, the development of diversity reports regarding data used by models, and regulation of usage scenarios to reduce contextual bias.
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    Exploration of the Security and Usability of the FIDO2 Authentication Protocol
    (2022) Breit, Zachary; Dean, Hunter; Generrette, Tai-Juan; Howard, Samuel; Kodali, Balaji; Kong, Jim; Tash, Jonah; Wang, Phillip; Wu, John; Baras, John
    Fast IDentity Online (FIDO) is a passwordless authentication protocol for the web that leverages public key cryptography and trusted devices to avoid shared secrets on servers. The current version of FIDO, FIDO2, has become widespread and is directly integrated into popular systems such as Windows Hello and Android OS. This thesis details two contributions to the advancement of FIDO2. The first is a modification to the protocol which uses Trusted Execution Environments to resolve security vulnerabilities in the Client To Authenticator Protocol Version 2 (CTAP2), which is a component of FIDO2. It is formally demonstrated that this modification provides a stronger security assumption than CTAP2. The second contribution is an outline of procedures and resources for future researchers to carry out a study of the usability of FIDO2 authenticators via a within-subjects experiment. In the study, subjects register an account on a custom web app using both passwords and FIDO2 credentials. The web app collects metrics about user behavior such as timing information for authentication sessions. Over the course of a week, subjects log in to the same web app every day using both authentication methods. Subjects complete entrance and exit surveys based on the System Usability Scale (SUS) according to their experiences. The surveys and user metrics would then be analyzed to determine whether users perceive FIDO2 as more usable than passwords.
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    Knowledge, Attitudes, and Practices Towards Teaching of Menstruation and Sexual Health Among Parents of Middle School Students
    (2022) Adkins, Aaliyah G.; Barrett, Christina S.; Fano, Gabby M.; Hospes, Katrina C.; Kilby, Christina F.; Mareno, Michael C.; Ollila, Elizabeth L.; Pettit, Jessica C.; Savoy, Jayme G.; Rowe, Tatiana; Wilkerson, Lucy A.; Mittal, Mona
    Menarche (the onset of menstruation), along with puberty in general, presents as a trying time for adolescents as they adjust to changes occurring in their bodies. Family life and sexual education are imperative during this transitional stage as they set the foundation for future reproductive health decisions adolescents may make. Prior research on menstruation and menstrual health has primarily focused on rural populations in developing countries; few studies on this topic have been conducted in the United States (U.S.). The findings of these studies show disparities in knowledge related to menstruation and menstrual health among different racial and socio-economic groups in the U.S. We added to current literature by conducting a mixed-method study to investigate knowledge, attitudes, beliefs, and parenting practices related to menstruation and sexual health education among the parents of middle school students in the U.S. We conducted an online study and collected survey data from parents of middle school students, followed by qualitative interviews with select parents (those who opted-in for this portion) to gain further insight into the attitudes and sentiments regarding menstruation and menstrual health.
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    Fabrication of Soft, Ferromagnetic Films and Devices and their Properties, Printability, and Applications
    (2022) Carlson, Elizabeth; Chen, Anson; Chung, Stephen; Dhamsania, Anjali; Mah, William; Mueller, Lillian; Sivarajan, Arjun; Ting, John; Das, Siddhartha
    Materials enabling fabrication of multifunctional devices are a cornerstone of present-day materials science and engineering. Multifunctionality enables use for novel applications in fields like energy, health, sensing, etc. We conducted an extensive literature review into the development of one material capable of multifunctional device fabrication, elastic magnetic films and devices, which have two notable properties: magnetizability, and physical softness and compliance. We highlighted materials, fabrication, characterization, and resulting interactions harnessed to develop inks used to fabricate these films, as well as broadscale applications. We also experimented with an Fe3O4-PDMS compliant magnetic film to characterize magnetic properties under modes of deformation. Through bending and twisting, the magnetic saturation, coercivity, and retentivity were measured. Results revealed that bent configurations preserved magnetic characteristics better than twisting configurations; out of tested twisting angles, a 180° rotation displayed properties closest to the undeformed state. We concluded by describing the potential of future research endeavors.
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    Analysis of Gene Targeting Techniques for Huntington’s Disease and Gene Expression in Human Cells
    (2022) Fields, Eric; Tripu, Deepika; Vaughan, Erik; Lim, Isabelle; Conway, Jessica; Salib, Nicole; Jacobsen, Michael; Lee, Yubin; Dhamsania, Akash; Woo, Ashley; Shrout, Katie; Cao, Kan
    Huntington’s disease (HD) is an inherited neurodegenerative disorder that is caused by a CAG trinucleotide repeat expansion in the huntingtin (HTT) gene. Our team performed a literature analysis to investigate the current state of research for treating HD and identified a new technology called prime editing that could be applied to HD in combination with single nucleotide polymorphisms (SNPs). We found that at least 729 SNPs within the HTT gene are compatible with our proposed approach. Experimentally, we performed preliminary studies using Western Blots and RT-qPCR to examine the differences in expression of HTT in a variety of cell lines. Our literature-based work suggests that prime editing is a promising tool for addressing the basis of a variety of genetic disorders. Our experimental-based work confirms that human fibroblast cells express HTT and therefore may be used in proof of concept studies of gene targeting techniques to address HD.
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    Cognitive Testing, Neuroimaging, and Blood Biomarkers in the Development and Progression of Alzheimer's Disease
    (2022) Cieslak, Zofia; Hemani, Danny; Kubli, Anjali; Lee, So Min; Mgboji, Rejoyce; Nallani, Madhulika; Park, Michael; Samson, Mahalet; Wu, Benjamin; Smith, J. Carson
    Alzheimer’s disease (AD) is a progressive neurodegenerative disorder, characterized by significant loss of memory and cognitive dysfunction. It has a significant impact on an individual’s health and may financially and socially burden these individuals and their loved ones. Although the disease has been researched extensively, there is still no clear understanding of the proposed mechanisms behind the development of AD and factors aside from genetics which potentially influence the risk of developing AD. The purpose of this research is to compile and analyze data on cognitively healthy participants, participants with MCI, and participants with AD to better understand the importance of genetic risk and changes in cognitive function, bioimaging and biomarker levels, as recorded on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. There are complex and significant relationships among these three variable groups with genetics and time. Executive function scores in healthy participants and participants with MCI were decreased with age and increased with education. In participants with AD, scores decreased over time. Language scores in healthy participants decreased with age, increased with education and for women. In participants with MCI, scores decreased with risk and time, and there was an interaction between these two variables. They also decreased with age and increased with education. In participants with AD language scores decreased over time. Memory scores in healthy participants increase with time and education and for women. In participants with MCI, scores increased with education and decreased with risk and time, and there was an interaction between these two variables. For participants with AD, there was a decrease over time. Visuospatial ability scores in healthy participants decreased with education. In participants with MCI, scores decreased with genetic risk and increased with education. In participants with AD, scores decreased over time and increased with age. Left hippocampal volume in healthy participants decreased with time, age, and education, and is increased in women. In participants with MCI, volume decreased with risk, time, age, and education. In participants with AD, volume decreased with time and age. Right hippocampal volume in healthy participants decreased with time, age, and education. In participants with MCI, volume decreased with risk and time, and there was an interaction between these two variables. Volumes also decreased with age. For participants with AD, volume decreased with risk, time, and age. Total hippocampal volume in healthy participants decreased with time, age, and education, and was increased for women. There was also an interaction between risk and time. In participants with MCI, volumes decreased with risk and time, and there was an interaction between these two variables. Volumes also decreased with age and education. For participants with AD, volumes decreased with risk, time, and age. Aβ42 levels in healthy participants decreases with risk and increased with time. In participants with MCI, levels increased with time and age, and were lower in women. In participants with AD, levels increased with time. Aβ40 levels in healthy participants increased with time and were lower for women. For participants with MCI, levels increased with time and age, and were lower for women. In participants with AD, levels increased over time. The Aβ42/40 ratio in healthy participants decreased with risk and time, and decreased with time in participants with MCI. The findings give insight into AD development and contribute to a greater understanding of longitudinal changes in AD progression. In relation to the study of AD includes the perpetuation of racial inequalities. People of color have an increased risk of developing AD and are disproportionately affected by the disease, yet are severely underrepresented in most research studies, including the research collected in the ADNI database. Racial minorities also often do not have the same access to healthcare as white people, thus contributing to the decreased possibility of early detection and treatment of AD. Black Americans, specifically, often face socio-economic barriers, which further renders the burden of AD development and progression more serious for minority families. In order to promote awareness of AD among underrepresented communities, Team Brain virtually presented to the African American Health Program, a local community of minority elders, via virtual presentations. Overall, this research concluded that hippocampal atrophy and cognitive tests appear to be the most consistent factors in the progression of MCI and AD. The analysis of blood biomarkers produced inconclusive results. This research indicates a clear set of imaging and cognitive factors that can be used to create less invasive and novel diagnostic methods for AD as well as supports the need for further research on blood biomarkers to understand their relationship with cognitive decline and progression of AD.
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    LEMMA: A Data-Driven Approach to Modeling the Spread of Extremism Over Online Platforms
    (2022) Fream, Mitchell; Hayes, Nathan; Kochar, Sahil; Kolbeck, Paul; Schneider, Charlie; Schwartz, Russell; Sharon, Olivia; Shen, Yuang; Weiss, Winslow; Wolle, Robert; Jabin, Pierre-Emmanuel
    The online spread of extremist ideas has been a growing problem. Team LEMMA has worked to quantitatively model the spread of extremist ideas over Reddit in order to gain insight into how they may spread. A modest dataset of Reddit comments were manually rated on the level of extremist rhetoric present and used to train a machine learning algorithm to automatically classify large swaths of Reddit data. These ratings were then fit to a predictive agent-based model with the hopes of better understanding past trends and potentially forecasting future spread of extremism.
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    Measuring Mental Workload and Brain Dynamics in Prosthesis Motor Learning over Multi-Session Practice
    (2022) Asenso, Maxine; Brown, McCauley; Dayanim, Gabriel; Doyle, Erin; Greenbaum, Maya; Lavarias, Gabrielle; Mercado, Natalia Nava; Nguyen, Christina; Russell, Ashley; Still, Alexys; Subramaniam, Carolyn; Varma, Anagha Rama; Gentili, Rodolphe
    The capability of humans to adapt their motor behavior and learn new motor skills is critical to interact with their changing environment as well as for integration with new machine interfaces, such as assistive technology (Casadio, Ranganathan, & Mussa-Ivaldia, 2012; Kitago & Krakauer, 2013; Mussa-Ivaldi et al., 2011). Such learning capability depends on the recruitment of cognitivemotor resources (Wickens, 2002). Mental workload (MWL), which is an important component in understanding learning, can be defined as the relationship between the deployment of neural resources and imposed task demands (Sharples & Megaw, 2005; Young et al., 2015). Although a large body of work has examined the behavior and cortical dynamics underlying the motor learning processes, most of this prior effort generally did not examine changes in mental workload through multiple practice sessions and did not consider individuals with upper limb (UL) loss (Marchand, de Graaf, & Jarrassé, 2021; Park & Zahabi, 2022). In this work, UL amputees were approximated by considering healthy individuals using bypass prostheses (Bloomer, Wang, & Kontson, 2018; Wang et al., 2021). Based on the work by Bloomer and Wang, able-bodied individuals can serve as a reasonable proxy for amputees while using these bypass prostheses. From a methodological standpoint, the use of human-body interfaces such as a bypass prosthesis is interesting since it requires participants to acquire a novel and unusual sensorimotor mapping, mitigating the influence of prior motor experiences and ultimately offering a fairly unbiased learning paradigm (Casadio, Ranganathan, & Mussa-Ivaldia, 2012; Mussa-Ivaldi et al., 2011). Thus, we employed this approach here, along with electroencephalography (EEG), which was used to assess the cortical dynamics as participants completed the learning task in order to objectively assess mental workload. In addition, surveys were employed to subjectively assess the level of workload perceived by the participants along with performance (e.g., time, smoothness, number of blocks transported within a fixed time period) collected via an inertial measuring unit. Overall, the aim of this research was to examine the concomitant changes in performance (e.g., number of blocks transported within a fixed time period) and in mental workload (by means of surveys and the cortical dynamics indexed by EEG) that occur when healthy individuals learn to operate a bypass prosthetic device via multi-session practice to perform a variety of motor tasks of daily living. This work can inform not only the human cognitive-motor processes underlying mental workload and performance during learning but also, to some degree, the rehabilitation/training of UL amputees, as well as the design and evaluation of prosthetic devices.
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    On the Mechanism of Electron Beam Radiation-Induced Modification of Poly(lactic Acid) for Applications in Biodegradable Food Packaging
    (2022) Acha, Chris; Blanchard, Robert; Brodsky, Jon; Ding, Lilly; Fox, Andrea; Grosvenor, Eleanor; Gibson, Kalina; Hoy, Annie; Hughes, Justin; Lee, Kristen; Mihok, Olivia; Stanfield, Cade; Uniyal, Ananya; Whitaker, Sydney; Al-Sheikhly, Mohamad
    Poly(lactic acid) (PLA) is a biodegradable polymer used for food packaging. The effects of electron beam radiation on the chemical and physical properties of amorphous PLA were studied. In this study, amorphous, racemic PLA was irradiated at doses of 5, 10, 15, and 20 kGy in the absence of oxygen. Utilizing electron paramagnetic resonance spectrometry, it was found that alkoxyl radicals are initially formed as a result of C-O-C bond scissions on the backbone of the PLA. The dominant radiation mechanism was determined to be H-abstraction by alkoxyl radicals to form C-centered radicals. The C-centered radicals undergo a subsequent peroxidation reaction with oxygen. The gel permeation chromatography (GPC) results indicate reduction in polymer molecular mass. The differential scanning calorimetry and X-ray diffraction results showed a subtle increase in crystallinity of the irradiated PLA. Water vapor transmission rates were unaffected by irradiation. Further mechanical testing showed mechanical properties in line with reduced molecular mass. In conclusion, these results support that irradiated PLA is a suitable material for applications in irradiation of food packaging, including food sterilization and biodegradation.
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    In-Situ Conformal 3D Printing for Targeted Repairs
    (2022) Chintala, Rohith; Cutick, Brendan; Han, Tyler; Myers, Elizabeth; Oh, Eric; Sandman-Long, Aidan; Sheng, Cynthia; Spicer-Davis, Nathan; Mitchell, Steven; Edelen, David
    Additive manufacturing is an emerging technology whose users seek to benefit from repair methods to reduce time and material costs. We explored an application of this technology for targeted repairs, such as mending holes or cracks, on 3D printed parts. Using conformal tool-pathing, we combined the precision of additive manufacturing with the strength and homogeneity of material adhesion to repair damage. To characterize the efficacy of targeted 3D printing repair for Fused Filament Fabrication (FFF) plastics, repair configurations varying in shape, size, material, infill and loading type were tested in 3-point bending for structural strength and strain. We provided and summarized the collected data in addition to a structural analysis and optimization of parameters relevant to reparative 3D printing. The collected data found that 3D printed repairs were effective in replacing the strength properties of a damaged area through the use of conformal 3D printing.
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    Autocycle: Design, Construction, and Validations of an Autonomous Bicycle
    (2022) Allen, Michael; Bartolomei, Jacob; Carter, Jeremy; Grill, Cooper; Khrenov, Mikhail; Mirenzi, Jack; O’Leary, Joseph; Rose, Isaac; Ruderman, Evan; Sanguesa, Andoni; Swaisgood, Logan; Gomez, Romel
    Efficient urban transportation has time and time again proved to be a difficult problem to rectify. One modern solution is the bike-sharing system, where many bicycles are available either at hubs or spread across a city for short-term use. However, usage is limited to those who are located close enough to a bicycle hub that travelling to and from it is time-effective. As for hubless bike-sharing systems, bicycles require redistribution over time to remain conveniently available to many. In this thesis, we propose the concept of a dual-mode bicycle that may either be used by a cyclist manually or operated independently utilizing autonomous locomotion, sensing, and control. Such a bicycle could be implemented into a larger bike-sharing system that autonomously manages balanced redistribution and allows users to summon a bicycle to their location, expanding range of use and encouraging environmentally-friendly transportation solutions in an urban setting. We will explore existing literature that have informed later design choices and data collection methods and propose our own methodology for designing, creating, and testing an autonomous bicycle.
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    Localizing Chemotherapeutic Drug Release Through the Use of Polymer-Based Surgical Sealants to Treat Stage III Colorectal Cancer
    (2021) Atalla, Anthony; Coley, Morgan; Hamers, Matthew; Karodeh, Nima; McGrath, Jennifer; Minahan, Eva; Nagler, Matthew; Nassar, Yomna; Nichols, Alison; Sebastian, Ria; Tiberino, Matthew; Wendeu-Foyet, Kevin; Kofinas, Peter
    Current cancer treatments, such as systemic chemotherapy, induce several complications that affect the entire body; localizing chemotherapy to the tumor site has the potential to minimize harmful side effects. Solution blow spinning (SBS) offers the possibility of incorporating chemotherapy drugs into a polymer solution through the use of a compressed airbrush. This would allow for direct deposit of a polymer mat after surgically removing the tumor. Sutures, in combination with polymer sealants, could be used to prevent complications after surgery. This study focuses on stage IIIA colorectal cancer because cancer cells have not spread distantly yet, and treatment typically involves surgery followed by chemotherapy. Three key aims were addressed in this study to assess polymer-drug combinations’ compatibility with SBS, observe drug release patterns, and evaluate the effect of drug incorporation on polymer adhesion to intestinal tissue. Our results suggested that the polymer-drug combination of poly(L-lactide-co-ε-caprolactone) (PLCL) and capecitabine shows promise as an adhesive surgical sealant with a drug release pattern that is complementary to a typical resection healing timeline.
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    Investigating the Application of Interpretability Techniques to Computational Toxicology
    (2021) Banerjee, Aranya; Boby, Kevin; Lam, Samuel; Polefrone, David; San, Robert; Schlunk, Erika; Wynn, Sean; Yancey, Colin
    A barrier to the incorporation of predictive models for drug design lies in their lack of interpretability. To this end, we examine on three fronts the interpretability of benchmark models for the 2014 Tox21 Data Challenge, an initiative in the domain with a dataset of measurements across twelve toxicity experiments. On existing measures of model performance, we assess the current benchmark metrics' ability to describe model behavior and recommend an alternative set of metrics for the task. On the existing interpretability methods for machine learning models, we quantitatively and qualitatively evaluate their application to this domain by measuring desirable properties of explanations they produce. Additionally, we incorporate a recently described method for partial charge prediction as novel input for a toxicological model and observe its resulting model performance and model interpretability.
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    A SYSTEMATIC REVIEW AND META-ANALYSIS OF PLAYING-RELATED MUSCULOSKELETAL DISORDERS IN MUSICIANS RELATING TO BIOLOGICAL SEX AND INSTRUMENT PLAYED
    (2021) Coley, Katherine M.; Widmer, Abigail G.; Dapkus, Katherine M.; Kapoor, Divya S.; Murphy, Lucas J.; Patriarca, Laura E.; Rhee, Hannah J.; Solomon, Julianna A.; Waugh, Lauren J.; Bell, Elizabeth; Shim, Jae Kun
    Playing-related musculoskeletal disorders (PRMDs) are occupational health concerns that cause pain, discomfort, or disability for musicians. We utilized a systematic review and meta-analysis to analyze disparities in prevalence based on sex and instrument, and assess whether instrument choice was associated with sex-based prevalence disparities. Six databases were searched for studies containing prevalence rates for males or females, or specific instruments. Studies were evaluated for methodological quality and data was statistically evaluated in a meta-analysis. Our initial search yielded 5961 articles, of which 23 articles met quality assessment criteria and were included in quantitative analyses. Sex-based disparities were observed such that being female increased one’s odds of having a PRMD by 88% when compared to males. Limited available studies with relevant data prevented analysis of the interaction between instrument and sex.
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    An Analysis of the Factors that Influence Vaccination Rates
    (2021) Bock, Kellyann; Cecil, Tara; Huppert, Amelia Claire; Jones, Molly; Kozimbo, Daniel; Pitt, Alyssa; Ruvinov, Alexei; Lombardi, Doug
    Due to the current rise of the vaccine hesitancy movement, there has been an increase in vaccine-preventable disease outbreaks (Mnookin, 2011; Reich, 2016). Parental rationalizations for opting out of vaccinations vary; however, some of the more commonly cited rationalizations include concerns for their child’s safety, distrust of medical professionals, and protection of civil liberties and individual decision-making processes (Glanz et al., 2013). Team IPOV has added to the literature body by examining how parents’ levels of knowledge about diseases, vaccine beliefs, and trust in institutions, medical professionals, and vaccines influence their levels of vaccine hesitancy, while adding the additional scope of the varicella and influenza vaccines and diseases. A hierarchical linear regression test revealed that trust exhibits the highest marginal impact on vaccine acceptance, followed by beliefs, and then, knowledge. Thus, while all three factors provided significant predictive insight into parents’ levels of vaccination hesitancy, parents’ trust in the varicella and influenza vaccines appear to possess the most significant impact over parents’ levels of vaccine hesitancy. Consequently, in considering future methods of alleviating vaccine hesitancy and increasing herd immunity, it is important to consider the ways in which trust can be built for the varicella and influenza vaccines.
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    ALTERNATIVE METHODS OF DESALINATION FOR SUB-SAHARAN AFRICA: A REVIEW OF PREFILTRATION AND MICROBIAL DESALINATION CELL TECHNOLOGY
    (2021) Adewale, Ayotemi Naomi; Amin, Shivani; Bahnsen, Lauren; Boyer, Jessica; Caponetti, Stephen A.; Halevi, Sharon; Oliphant, Brandon E.; Sow, Pauline; Kjellerup, Birthe V.
    Our research project has addressed the global need for greater accessibility to potable drinking water, specifically within the regions of sub-Saharan Africa. Initially, we planned to design a unique desalination system that was composed of a pre-filtration unit, a microbial desalination cell (MDC) and a post-desalination treatment unit. When in-person lab work was no longer feasible due to COVID-19 guidelines, we refocused our project to review the construction, efficiency, and cost effectiveness of the different designs of potential prefiltration units and MDC configurations. Our review of potential prefiltration systems included both chemical and physical separation methods, and the review of the MDC included the air cathode, biocathode and stacked configurations. While researching the technical details of the prefiltration and MDC systems, we also considered the cultural and societal impacts of introducing a technology such as the MDC into our project region. Our project started as an analysis of an emerging technology, but as the team has grown, the project has transformed into a comprehensive review of the emerging microbial desalination technology and the societal impacts of implementing it into some of the water scarce regions of coastal sub-Saharan Africa.
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    IMPROVING NON-CONTACT TONOMETRY: A DEEP NEURAL NETWORK BASED METHOD FOR CORNEAL DEFORMATION MAPPING
    (2021) Ackman, Moshe; Cho, Lauren; Do, Kun; Green, Aaron; Klueter, Sam; Krakovsky, Eliana; Lin, Jonathan; Locraft, Ross; Muessig, James; Wu, Hongyi; Scarcelli, Giuliano
    Glaucoma, a disease characterized by increased intraocular pressure (IOP), is one of the leading causes of preventable blindness worldwide. Accurate measurement of IOP is essential in monitoring glaucomatous progression in order to deliver treatment and prevent long-term vision loss. Currently, non-contact tonometry, known as an "air-puff test", is a common diagnostic method despite its inaccessibility, discomfort, high cost, and reliance on a trained professional. To improve upon these shortcomings, we designed a cheaper tonometer integrating a novel depth-mapping neural network with a custom air-puff generation system. We deformed porcine corneas with a controlled-intensity air-puff while imaging the deformation with a single stationary camera-- a contrast to the standard Scheimpflug method. From the footage, our neural network predicted a three-dimensional map of corneal deformations. The network was able to predict a general negative trend between the IOP and the corneal deformation extracted. We compared our results to accepted literature deformation values and ground truth footage, allowing us to determine that the deformation amplitudes were physically plausible. With a more robust imaging setup, we present a promising alternative to traditional IOP measurement methods. Future studies should make the simulated footage more representative of clinical conditions to increase the generalizability of the neural network. Additionally, anatomical differences between porcine and human eyes as well as corneal variability due to socio-demographic differences must be addressed for our results to be applied to clinical settings.
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    DYNAMIC WIRELESS POWER TRANSFER USING DC POWER
    (2021) Antomattei, Marcus; Freno, Brian; James, Emily; Kemp, Katherine; Medina, Karla; Mullee, Michael; Quinn, Trevor; Sinha, Rohit; Warthen, Justin; Yu, Sijing; Zhao, Tingyu Kevin; Quinn, Bryan
    Constant stops for charging and lengthy recharging times make electric vehicles (EVs) inconvenient to operate for extended travel. Innovative charging methods are necessary if EVs are expected to gain traction in the market over the coming years. Current advancements allow EVs to be charged wirelessly while parked over a charging source. This method does not mitigate the issue of interrupting a trip to spend a significant amount of time charging the vehicle. We theorized that – by expanding on the current technology – EVs could be charged while in motion. The primary goal of this project was to develop a model that optimized the operation of a dynamic wireless power transfer (DWPT) system using DC power. Through a combination of digital simulations and physical tests, the team determined the factors that significantly impacted the power transfer to a receiving wire coil as it moved over a series of stationary transmitting coils. The results were used to confirm the feasibility of a DWPT system and to make recommendations as to the optimum operating conditions.
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    EVALUATING THE BIOSORPTIVE PROPERTIES OF ANACOSTIA RIVER BIOMASS TO FACILITATE HEAVY METAL REMOVAL FROM CONTAMINATED WATER
    (2021) Baitman, Benjamin; Chang, Justin; Croce, Bryan; Parker, Joshua; Seibert, Paul; Weiss, Emma; Weller, Joseph; Zhou, Wen; Andrade, Natasha
    Arsenic, cadmium, and chromium are among the major industrial heavy metal pollutants that can cause adverse effects on human and environmental health. Conventional remediation treatments tend to be financially and environmentally disadvantageous. Algal biosorption is an alternative that utilizes the functional groups on algae’s surface to remove metals from solution. We tested the remediating capabilities of algae in both a laboratory and prototype setting. We observed how arsenic, cadmium, and chromium were sorbed by the algae at select time intervals. We found that 100% of chromium and arsenic and 35% of cadmium were removed after 24 hours, with peak rates occurring for all three metals at two hours. Results from the prototype show promise, but shortcomings suggest this technology is better suited for use in pretreatment, not for immediate discharge. More research is needed to improve the system’s practicality in real world application.