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2021 DISCOVER Uofsc Research | Scholarship | Innovation

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2021 DISCOVER Uofsc Research | Scholarship | Innovation Office of Research University of South Carolina 2021 DISCOVER UofSC Research | Scholarship | Innovation Collected Abstracts: Collected abstracts that showcase research, scholarship, leadership and creative projects by undergraduate and graduate students, postdoctoral scholars and medical scholars representing the entire UofSC System. Prepared for DISCOVER UofSC April 23, 2021. www.sc.edu/DiscoverUofSC 1 Table of Contents Undergraduate Student presentations 3 - 248 Graduate Student presentations 250 - 336 Postdoctoral Scholar presentations 338 - 346 Medical Scholar presentations 348 - 428 2 Undergraduate Students presentations 3 2020 Cohort, Smart Start Nursing Program Mentor(s): Dr. Robin Dawson, Dr. Sue Heiney “Just be safe and be aware”: UofSC undergraduate student experiences during the COVID-19 pan- demic Background/Significance: The COVID-19 global pandemic has taken thousands of lives, sickened even more, and changed the daily routines of many. It has also resulted in significant challenges for universi- ties, including the need for rapid development of COVID-19 guidelines to mitigate community spread (e.g., mask use, social distancing) and alternative educational delivery strategies (e.g., virtual, and asynchro- nous). Students have also had unique experiences adapting to this “new normal”. Purpose: The purpose of this qualitative descriptive study was to explore the experiences of UofSC under- graduate (UG) students living on campus during the 2020 fall semester. Methods: This study was guided by the Transitions Theory Framework. Participants were recruited via convenience and snowball sampling. Data included audio-recorded, semi-structured phone interviews lasting from 10 to 45 minutes. After transcription, data were analyzed using a thematic analysis approach, including open/axial coding and identification and naming of emergent themes. Results: Participants included thirty-four UG students. The majority were female and white. Seven over-arching themes captured the UG student experience during the COVID-19 pandemic: COVID-19 knowledge and personal safety behaviors; Making the decision to be on campus; Sources of COVID-19 information; Online classes, isolation, and quarantine; Perceptions of the university response to the pan- demic; Perceptions of others’ pandemic-related behaviors; and Suggestions and recommendations as the pandemic continues. Conclusion/implications: Overall, the University implemented successful policies that, although at times met with student confusion, resistance, and noncompliance, were viewed positively by the participants. Student suggestions to enhance the university response included: 1) eliciting student input on the UofSC COVID-19 policies, similar to a course evaluation; 2) the development of a COVID-19 policies module to be completed by students prior to return to campus, similar to the mandatory AlcoholEdu course; and 3) faculty should demonstrate more empathy regarding the unique pressures the COVID-19 pandemic has Abdullah,placed on students. Badr Mentor(s): Dr. Michael Myrick, Ms. Caitlyn English Fluorescence Microscopy Studies of Lyngbya wollei Lyngbya wollei is a large, filamentous, and mat-forming cyanobacterium that is responsible for a large proportion of the harmful algal blooms taking over freshwater bodies in the Southeastern United States. These algal blooms negatively affect water quality through their formation of dense mats that adversely affect aquatic life. Their role in the depletion of water oxygen levels, the blocking of solar radiation, and the production of toxic metabolites such as cyanotoxins have negatively impacted fisheries, water sup- plies, and local agriculture. The growth and spread of Lyngbya wollei are favored by warmer tempera- tures; climate change and rising global temperatures are thus increasing the urgency of understanding and mitigating the impact of Lyngbya on freshwater ecosystems. The analysis of Lyngbya was performed using a customized fluorescence excitation instrument that al- 4lows for excitation of individual cells, as opposed to conventional bulk excitation methods that record the fluorescence of large samples. This technique is well suited to organisms like Lyngbya as their dense mats are prone to trapping sediment and organisms which interfere with the true fluorescence signal. Fluorescence excitation signatures of chlorophyll A, phycoerythrin, and phycocyanin were found at 425nm, 580nm, and 612nm, respectively. The excitation spectra of these pigments were taken at each cell while going down the length of a single filament. The excitation ratios were then plotted as a function of their position along the chain, and trends in pigment heterogeneities were then correlated as functions of cell age, growth stage, injury, and environmental stress. This was done to find spectroscopic indicators of the organism’s state, with the end goal of elucidating the cellular physical conditions that favor toxin Ablonczy,production, Lukacs which can then be used in the development of tools to determine risks of water toxicity. Mentor(s): Dr. Homayoun Valafar, Dr. Cynthia Corbett Improving on existing annotation procedures for the training of nascent artificial neural networks Background: Artificial intelligence (AI) is a highly versatile and growing field in computing. Human-supervised AI approaches heavily rely on a set of annotated data to initiate their training process. Training defines the upper boundary of an AI’s performance, therefore training data must be well annotated to be effective. Currently the hand annotation of data introduces obstacles including accuracy and speed when imple- menting AI solutions within healthcare. Therefore, there is a palpable gap in the existing technology to assist and facilitate data annotation. Purpose: Our aim is to develop an automated mechanism for annotating accelerometer data intended to train AI solutions to interpret human medication-taking activity. Methods: Our approach develops a progressively automated method to annotate accelerometer data. First, we develop a nascent neural network using a small set of hand-annotated data. The second stage will utilize the classification results of the nascent network to annotate active and inactive portions of data. This newly annotated data will be used to further refine the detection capabilities of the initial net- work. During the final stage, reinforcement learning principles will be utilized to further enhance the accuracy of the detection network that will be used to annotate the sensor data. This progressively enhanced and automated annotation/detection system will facilitate a faster annotation process. This approach requires occasional confirmation by a human supervisor. Results: We have obtained and manually annotated 1690 individual gestures from 22 participants. The nascent ANN exhibits a performance of more than 95% accuracy in identifying data from nearly 15 participants. Our efforts are now focused on leveraging the existing network in developing a semi-automated annota- tion of the remaining participants. Conclusion and Implications: There are many use cases for this method in improving automated annotation. For instance, the method could use hand-annotated data from only ten participants to train a nascent network. After, the trained network could automatically, but with supervision, annotate more than 95% of the data from the remain- ing participants. A second generation of network could then be trained based on the new annotated data, improving its capabilities comparatively. This can then be repeated. 5 Abraham, Amy Mentor(s): Ms. Wendy Chu, Dr. Kimberly Becker The Role of Paraprofessionals in the Mental Health Structure of India The mental health treatment gap in India is part of a growing public health crisis, with over 95% of those in need of services never receiving them. Over 197 million Indians suffer from at least one diagnosable mental health disorder, and this number continues to grow given the treatment gap. The treatment gap is a result of four major factors: lack of government support, stigma, limited treatment facilities, and dearth of professionals able to provide treatment. The current study aimed to analyze several factors of parapro- fessional-led mental health interventions including setting, treatments delivered, treatment models, and client outcomes. A narrative literature review was conducted to synthesize the current available research on paraprofessional-led mental health interventions in India. Twelve studies published between 2010 and 2020 were included in the review. Most studies (n = 10, 83%) with paraprofessionals were conducted in both peri-urban and rural areas, and in a variety of different clinical settings (e.g., healthcare facilities, schools). All (100%) paraprofessional interventions used evidence-based treatments for mental health problems, including psychotherapy and pharmaceutical treatment. Paraprofessionals provided services under a collaborative stepped care model in many studies (n = 9, 75%). Of the studies that used quantita- tive methods to evaluate changes in client outcomes, all ten (100%) found that paraprofessionals signifi- cantly reduced the severity of symptoms of mental disorders and improved functioning. These findings provide support for the efficacy of paraprofessional-led interventions in treating the mental health needs of the Indian population. Moreover, they illustrate that paraprofessionals can be a solution to mitigating Ackroyd,the mental Madison health treatment gap in India.
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