Undergraduate Research Day 2020

Permanent URI for this collectionhttp://hdl.handle.net/1903/20158

With students involved in so many research opportunities, Undergraduate Research Day provides the perfect opportunity for them to share their work with the campus community. Held each April, Undergraduate Research Day showcases current research, scholarship, and artistic endeavors.

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End date: 2020Subject: search.filters.subject.Gemstone

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Now showing 1 - 9 of 9
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    Interpretable Deep Learning for Toxicity Prediction
    (2020) Banerjee, Aranya; Boby, Kevin; Lam, Samuel; Li, Jeffrey; Polefrone, David; San, Robert; Schlunk, Erika; Wynn, Sean; Yancey, Colin; Feizi, Soheil
    Team TOXIC (“Understanding Computational Toxicology”) seeks to apply interpretability techniques to machine learning models which predict drug safety. Currently, such models have been developed with relative accuracy and are used in industry for drug development. However, because they are not sufficiently rooted in chemical knowledge, they are not widely used in regulatory processes. To contribute towards a solution, we evaluate existing explanation methods for toxicity predction models trained on open-source data sets. Additionally, we are working towards models involving the usage of more interpretable data representations. Ultimately, we hope to demonstrate a proof-of-concept for an interpretable model for predicting drug safety which can illustrate its reasoning.
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    Improving Non-Contact Tonometry through Advanced Applanation Techniques and Measurement of Corneal Deformation
    (2020) Muessig, James; Ackman, Moshe; Cho, Lauren; Do, Kun; Green, Aaron; Klueter, Sam; Krakovsky, Eliana; Locraft, Ross; Wu, Hongyi; Lin, Jonathan; Scarcelli, Giuliano
    Glaucoma, a disease characterized by increased intraocular pressure (IOP) in the eyes, is the leading cause of preventable blindness worldwide. Accurate measurement of IOP is essential to early diagnosis of glaucoma in order to begin treatment and prevent long-term vision loss. Currently, non-contact tonometry, known as an “air-puff test”, is the most common diagnostic method despite its inaccessibility, discomfort, high cost, and reliance on an expert to operate. In order to improve upon this method, we designed an accurate and less invasive measurement system utilizing a novel depth-mapping neural network and a microcontroller-driven valve system. We applanated eyes with a variable-intensity air puff while imaging the deformation with a single camera. Our neural network then processed the image data and generated a three-dimensional deformation map. We compared our results to accepted tonometry measurements in order to validate the accuracy of our system as an alternative diagnostic device. With a lower pressure puff and simplified imaging setup, we were able to accurately measure IOP, improving existing diagnostic techniques in optometry.
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    Robotic Habitat Technologies for Minimizing Crew Maintenance Requirements
    (2020) Broemmelsiek, Rachel; Calderwood, Micah; Callejon Hierro, Jaime; Cueva, Rachel; Harvey, Rachel; Holmes, Scott; Khawaja, Imran; Kleyman, William; Mnev, Peter; Orlando, Wilson; Queen, Jessica; Shenk-Evans, Micah; Skinner, Thomas; Akin, Dave; Bowden, Mary
    NASA’s Lunar Gateway aims to be deployed later in the decade and will serve as an outpost orbiting the moon. This habitat will be utilized as a base for lunar operations as well as future missions to Mars. Unlike the International Space Station (ISS), which maintains three to six astronauts at any given time, the Lunar Gateway will be uncrewed for eleven months out of the year. Over 80% of crew time onboard the ISS is dedicated to logistics, repair, and maintenance, leaving minimal time for scientific research and experimentation. In order to maintain Gateway, robotic systems must be implemented to accomplish maintenance and operational tasks. This paper discusses our team’s proposed dexterous robotic system, which will address routine and contingency operational and maintenance tasks on Gateway. The project is experimentally-based, and split into three approaches: cataloging robotic capabilities via robot/taskboard interactions, logistics management of Cargo Transfer Bags (CTBs), and software development of an AprilTag situational development system. This research project utilizes the unique capabilities of the University of Maryland (UMD) Space Systems Laboratory (SSL), which houses various dexterous robotic manipulators, mock-ups of space habitats, and the Neutral Buoyancy Research Facility (NBRF), a 50-foot diameter, 25-foot deep water tank used to simulate microgravity conditions. By incorporating robotic systems into the architecture of the Lunar Gateway, it will allow for the lunar outpost to be continually operated and maintained while uncrewed, and will allow for astronauts, when present, to focus on maximizing scientific discoveries.
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    Artificially Intelligent Medical Assistant Robot (AIMAR)
    (2020) Ronin, Dana; Horne, Nina; Daniel, Paulos; Jacobson, Ben; Kuo, Kevin; Marsandi, Michelle; Offenberg, Natalie; Utz, Ryan; Vandergriff, Johan; Deane, Anil
    Healthcare providers face financial, regulatory, and logistical obstacles in supplying quality care. Applying robotics and artificial intelligence (AI) to healthcare reduces demands on providers, increases accuracy by supplementing medical diagnoses, and improves patient outcomes. Team AIMAR (Artificially Intelligent Medical Assistant Robot) has constructed a modular robotic healthcare AI system, consisting of advanced diagnostic features as supplements to a generic base. The team focused on analyzing images with machine learning to identify skin conditions. The base robot can move around the home or hospital, pick up objects, and interact with patients and doctors. The patient can log in using face authentication so that patient data is secure, and interact verbally and visually through the user interface. New features can easily be added to the base robot's existing integrated features, making AIMAR adaptable for many desired contexts.
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    Investigation of 1P-LSD as a Novel Drug Therapy for Autism Spectrum Disorders
    (2020) Foster, Kayla; Hansen, Abigail; Lee, Matthew; Mohammed, Alan; Morrell, Matthew; Nguyen, Thach-Vu; Olson, Caroline; Pascale, Lucas; Sunny, Nishanth
    Autism spectrum disorders (ASD), defined by repetitive behaviors or impaired social communication, is a prevalent yet relatively misunderstood set of conditions. ASD encompasses a series of neurodevelopmental disorders that have various physiological manifestations (Goines & Ashwood, 2013). Due to the heterogeneity of ASD, the true mechanisms leading to the development of ASD and its symptoms remain unclear and require more research (Rossignol & Frye, 2012; Watts, 2008). The purpose of this project is to test whether or not 1P-LSD, an analogue of LSD (lysergic acid diethylamide), has the potential to treat symptoms of ASD, specifically the hyperexcitation of N-methyl-D-aspartate (NMDA) receptors in the brain which causes the neuronal excitotoxicity highly implicated in the pathology of ASD. We will determine the two highest doses of 1P-LSD which do not result in any hallucinogenic side effects in Phase 1 of this protocol and utilize these doses towards treatment of symptoms associated with ASD in Phase 2 of this protocol. We will monitor NMDA receptor activity, which is usually impaired in ASD, following microdosing of 1P-LSD. For these experiments, we will be using an autistic mouse model (Slc6a4) compared to normal mice (C57BL/6J). The efficacy of the treatment model will be assessed by measuring the levels of a subunit of the NMDA receptor, the NR2B subunit, using western blotting and immunohistochemistry, and by measuring the levels of glutamate using gas chromatography-mass spectrometry (GC-MS).
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    Inhibiting Degranulation in Immune Cell Signaling Pathways
    (2020) Fadul, Naja; Kasica, Zachary; Laurence, Kyeisha; Moy, Stephanie; Murugan, Sindhu; Pamala, Chinmayi; Robinson, Morgan; Shah, Rohan; Shrestha, Mansu; Smith, Marcus; Vashi, Bhavya; Frauwirth, Kenneth
    Allergies are a pervasive issue and require novel ways of alleviating symptoms. Existing treatments are focused on symptom management and immunotherapy, but there is also potential to target the molecules involved in the downstream pathway, particularly the PLCγ enzymatic pathway. Our research aimed to identify important target molecules involved in this pathway that result in the degranulation of mast cells. We intended to inhibit these molecules in order to hinder mast cell degranulation and therefore prevent allergic symptoms. Our results were tested and measured in MC/9 (mouse mast cell) and RBL-2H3 (rat basophilic) cell lines with multiple cell degranulation assays such as the beta-hexosaminidase and tryptase assay. The results were evaluated based on the comparative effect as well as specificity of inhibitors on mast cell degranulation. We aim to find the most ideal inhibitor for the PLCγ, SK, S1P2 enzymatic pathways in the signalling cascade in order to most effectively reduce degranulation and thus reduce the allergic response.
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    Localizing Chemotherapeutic Drug Release to Treat Stage III Colorectal Cancer
    (2020) Sebastian, Ria; Atalla, Anthony; Coley, Morgan; Hamers, Matthew; Tiberino, Matthew; Nagler, Matthew; Nassar, Yomna; Nichols, Alison; Minahan, Eva; Karodeh, Nima; McGrath, Jennifer; Wendeu-Foyet, Kevin; Kofinas, Peter; Ayyub, Omar
    These studies focused on the incorporation of chemotherapeutic drugs into biodegradable polymers, specifically poly(lactide-co-caprolactone) (PLCL), as a localized form of cancer treatment. In conjunction with the surgical resection of a tumor, this polymer can be used to deposit drugs directly at the site and minimize the risks posed by systemic chemotherapy. The methodology focused on Stage IIIA colorectal cancer due to its high recurrence rate and the common use of surgery as a form of treatment. In our experiments, data was collected to compare the various physical, chemical, and mechanical properties between PLCL fiber mats loaded with Capecitabine in order to evaluate the most ideal drug release pattern. Results found that the combinations we had tested thus far had shown a delayed release, meaning at least a week passed before initial drug dissociation from the polymer. Current results suggest a possible relationship between molecular weight and the delay period length, which has implications in future research. Different polymers will also be studied to assess the chemical impact on the release patterns we found in our data.
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    Examining Biomechanical Correlates to Playing-Related Musculoskeletal Disorders in Professional Guitarists
    (2020) Coley, Katie; Dapkus, Katie; Kapoor, Divya; Murphy, Lucas; Patriarca, Laura; Rhee, Hannah; Solomon, Julianna; Waugh, Lauren; Widmer, Abigail; Shim, Jae Kun
    Playing-related musculoskeletal disorders (PRMDs) are painful conditions that may hinder musicians’ ability to play their instruments, affecting them financially, emotionally, and physically (Kenny & Ackermann, 2015; Zaza et al.,1998). Biomechanical risk factors associated with occupational health disorders include repetitive anatomical movements (Candia et al., 2006), excessive force exerted on the upper-body (Chiang et al., 1993), awkward postures (Blanco et al., 2017), and inefficient muscular contraction patterns while playing (Horisawa, 2013). Despite the high prevalence of PRMDs in guitarists, research on biomechanical correlates of PRMDs is limited (Fjellman-Wiklund & Chesky, 2006). Previous research also suggests that biological females experience significantly greater rates of PRMDs than biological males (Ajidahun et al., 2017; Baadjou et al., 2016; Kok et al., 2018; Ranelli et al., 2011), yet little research investigates why this disparity exists. Therefore, the present research aims to investigate potential mechanisms underlying PRMDs in guitarists and this sex-based disparity. Participants will answer a modified Nordic Musculoskeletal Questionnaire (NMQ; Kuorinka et al., 1987) to assess the presence, location, and frequency of PRMD pain. We will utilize the combination of a novel force-measuring guitar, Vicon motion capture system, and electromyography to compare finger force and torque, posture, muscular activation and co-contraction, and variability in playing technique between male and female guitarists with and without symptoms of PRMDs. We hypothesize that biological females and those with PRMDs will exert higher finger contact forces and joint torques, more joint torques in unnatural anatomical positions, greater muscle co-activation, and decreased variability in contact forces and joint torques.
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    Utilizing macroalgae for heavy metal remediation of effluents from industrial wastewater
    (2020) Baitman, Benjamin; Chang, Justin; Croce, Bryan; Parker, Joshua; Seibert, Paul; Weiss, Emma; Weller, Joseph; Zhou, Wen; Andrade, Natasha
    Algae as a biosorbent is an emerging technology that offers a renewable and economically efficient means of removing heavy metals from wastewater effluent. While there are a multitude of studies demonstrating the effectiveness of algae as a heavy metal adsorbent, there are a lack of studies that attempt to use algal biosorption as their primary removal method. This study looks to examine the biosorption efficiency of inactive algae strands Spirilina and Uluthrix in a non batch reactor. Tannery effluent is used as a model for a generalized heavy metal effluent, because it is well defined in the literature. The algae was analyzed first at a lab scale to determine the maximum carrying capacity of the algae, examining the optimal conditions for adsorption. Our laboratory results are currently being run to determine optimal pH, temperature, and contact time for adsorption. A pilot scale system is currently being tested to determine how well a system can implement this novel approach to biosorption.