Interdisciplinary – Page 4 – UROP Spring Symposium 2021

Interdisciplinary

How Do Motivations and Identities Effect Racial Dialogue?

Lauren Lott Pronouns: she/her/hers Research Mentor(s): Koji Takahashi, Graduate Student Research Mentor School/College/Department: Psychology, College of Literature, Science, and the Arts Presentation Date: Thursday, April 22, 2021 Session: Session 6 (4pm-4:50pm) Breakout Room: Room 3 Presenter: 6 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Lauren Lott, Vimukthi […]

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How Do Motivations and Identities Affect Racial Dialogue?

Vimukthi Rupasinghe Pronouns: He/Him Research Mentor(s): Koji Takahashi, Graduate Student Research Mentor School/College/Department: Psychology, College of Literature, Science, and the Arts Presentation Date: Thursday, April 22, 2021 Session: Session 6 (4pm-4:50pm) Breakout Room: Room 3 Presenter: 6 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Lauren Lott, Koji

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Sandy Hook Promise Evaluations

While schools have employed systems for students to report incidents of bullying, drugs, mental health, safety concerns, etc. they are often not anonymous, despite being advertised as so. Often times students are directed to report their concerns to a teacher/counselor directly or to fill out a form of some kind that they ultimately need to deliver to a teacher/counselor, thus defeating the point of “anonymous” reporting. This study aims to investigate how the number and demographics of student reports change when an actual Anonymous Reporting System (ARS) is introduced. This experiment included a school district in Pennsylvania where half of the schools implemented the ARS and taught the students how to use it while the other half of schools carried on with their normal reporting system. At the conclusion of the study, all of the tips were coded and categorized on the basis of type (sexual harassment, drugs, mental health, etc), race, gender, grade/age, and whether or not the victim was the one who reported or if it was a witness. After a careful analysis of the data, we expect to see a higher number of tips related to nonviolent bullying and harassment compared to other types of tips, including violence. This knowledge of how an ARS can be more effective for certain types of tips is part of a growing understanding of how to improve school safety and will lead to new standard legislation and implementation regarding reporting in schools.

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An Analysis of Types of Tips Collected Using an Anonymous Reporting System (ARS) in K-12 Schools

While schools have employed systems for students to report incidents of bullying, drugs, mental health, safety concerns, etc. they are often not anonymous, despite being advertised as so. Often times students are directed to report their concerns to a teacher/counselor directly or to fill out a form of some kind that they ultimately need to deliver to a teacher/counselor, thus defeating the point of “anonymous” reporting. This study aims to investigate how the number and demographics of student reports change when an actual Anonymous Reporting System (ARS) as part of the Safe2Say Something (S2SS) initiative is introduced. This experiment included a school district in Pennsylvania where half of the schools implemented the ARS and taught the students how to use it while the other half of schools carried on with their normal reporting system. At the conclusion of the study, all of the tips were coded and categorized on the basis of type (sexual harassment, drugs, mental health, etc), race, gender, grade/age, and whether or not the victim was the one who reported or if it was a witness. After a careful analysis of the data, we expect to see a higher number of tips related to nonviolent bullying and harassment compared to other types of tips, including violence. This knowledge of how an ARS can be more effective for certain types of tips is part of a growing understanding of how to improve school safety and will lead to new standard legislation and implementation regarding reporting in schools.

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How Technology Discriminates: Education and Outreach Project

Algorithms and Society works to educate young technology users on the associated risks and societal implications of information technology. The project focuses on how bias is embedded in the algorithms behind information technology. To build lesson plans for high school students, I analyzed the Algorithms + Society five-part YouTube video series, designed by researchers on the research team. These videos are short and informational and provided me the premise of each coordinating lesson plan. Based on the Algorithms + Society videos, I did my own research to contextualize and expand on the basic information. The culmination of this work is a set of high school lesson plans to be taught in coordination with the Algorithms + Society Youtube video series. Each lesson contains step-by-step, scripted instructions for teachers, questions for class discussions, and engaging activities for the students. Algorithms and Society explores how algorithmic bias embedded in search engines, social media, smart devices, etc, perpetuates discrimination and bias in our society. In an increasingly digitized world, it is imperative that students understand the risks associated with information technology. Through education, we can raise a generation of technology users and developers who are cognizant of algorithmic bias and actively work against it.

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Party in the Street: Grassroots Protests during (and beyond?) the Presidency of Donald Trump

Many Americans have relied on biased or incomplete news coverage to conclude that grassroots protestors are a monolithic group all motivated by the same ideals. Meanwhile, there has been very little formal research conducted to accurately determine the political and social motivations of grassroots protestors during Donald Trump’s Presidency. This research project conducts, codes, and analyzes surveys filled out by participants from several grassroots protests between 2017 and 2020. Its goal is to get a better understanding of the sentiments of individual grassroots protestors. Through close analysis of completed surveys, the project team has determined that the motivations of grassroots protestors are both varied and complex. Although most grassroots protestors identified themselves as either Democrats or Republicans when asked about their political affiliation, their responses to more specific questions about social identity, values, and interests proved that grassroots protests feature diversity of both identity and thought. This research project serves to challenge common knowledge about grassroots protests that has been skewed by political bias in the United States. It will also assist future researchers studying and further analyzing why individuals felt called to participate in grassroots protests during the Presidency of Donald Trump.

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Party in the Street: Grassroots Protests During the Presidency of Donald Trump

Many Americans have relied on biased or incomplete news coverage to conclude that grassroots protestors are a monolithic group all motivated by the same ideals. Meanwhile, there has been very little formal research conducted to accurately determine the political and social motivations of grassroots protestors during Donald Trump’s Presidency. This research project conducts, codes, and analyzes surveys filled out by participants from several grassroots protests between 2017 and 2020. Its goal is to get a better understanding of the sentiments of individual grassroots protestors. Through close analysis of completed surveys, the project team has determined that the motivations of grassroots protestors are both varied and complex. Although most grassroots protestors identified themselves as either Democrats or Republicans when asked about their political affiliation, their responses to more specific questions about social identity, values, and interests proved that grassroots protests feature diversity of both identity and thought. This research project serves to challenge common knowledge about grassroots protests that has been skewed by political bias in the United States. It will also assist future researchers studying and further analyzing why individuals felt called to participate in grassroots protests during the Presidency of Donald Trump.

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Role of STING pathway in photosensitivity and interferon-kappa responses in keratinocytes

Cutaneous Lupus Erythematosus (CLE) is an autoimmune disorder marked by scarring skin lesions, often triggered by exposure to ultraviolet (UV) light resulting in a significant loss of quality of life for CLE patients. Better understanding of the molecular mechanisms driving CLE is needed as currently, the lack of Food and Drug Administration (FDA)-approved therapies for CLE presents a fundamental challenge in the treatment of CLE patients. The outermost layer of the skin is known as the epidermis, which consists of mostly keratinocytes. Interferon kappa (IFN-?), a member of the type I IFN family, is constitutively expressed in keratinocytes. IFNK overexpression in lesional lupus skin predisposes CLE patients to inflammation and photosensitivity, thus it is an intriguing target for novel therapeutics. Previously, we had observed a significant delay in IFNK expression relative to IFN-ß, another member of the type I IFN family, following stimulation with poly-IC, an activator of the antiviral TLR3 signaling pathway, or UVB. In addition, upregulation of IFNK was dependent on STING, an endoplasmic reticulum adaptor protein. We thus sought to further understand the regulation of different IFNs in keratinocytes. Using CRISPR-Cas9, we generated knockout keratinocytes for IFNB expression. Here, we reveal that in the absence of IFN-ß, IFNK expression is significantly reduced in keratinocytes treated with poly-IC or UVB. Elimination of mediators downstream of the type I IFN receptor, such as STAT1, also abrogated IFNK but not IFNB expression. Further, IFNK, but not IFNB, expression remained dependent on STING signaling upon UVB-irradiation. Given this information, therefore, we suggest that early triggering of IFNB is required to drive a STING-mediated upregulation of IFNK. Currently, we are examining whether this regulation is aberrant in CLE vs. healthy control keratinocytes, which would provide a mechanism for dysfunctional overexpression of IFNK in CLE skin. If so, this pathway would serve as a target for reducing inflammation and photosensitivity in CLE patients.

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Targeting Candida albicans Virulence

Fungal pathogens like Candida albicans can cause devastating human disease. Treatment of candidemia is complicated by the high rate of resistance to common antifungal therapies and the toxicity of many antifungal compounds due to the conservation between essential mammalian and fungal proteins. As the number of immunocompromised and hospitalized patients vulnerable to fungal infections increases, it is essential to discover new targets and approaches for targeting these deadly fungal pathogens. An attractive new approach for antimicrobial development is to target virulence factors; these are non-essential processes that are required for the organism to cause disease in human hosts. This approach expands the potential target space while reducing the selective pressure towards resistance, as these targets are not essential for viability. In C. albicans, the key virulence factor is a morphogenetic switch from yeast to filaments. We have developed a high-throughput image analysis pipeline that can readily distinguish between yeast and filamentous growth in C. albicans and identify cytotoxic molecules. Based on this clear phenotypic assay, we have screened compounds for their ability to inhibit this important virulence factor or cause fungistatic or fungicidal effects. Also, to avoid host cell toxicity, the compounds screened are compounds used as treatments for other medicinal purposes. We have begun to use these compounds to screen for resistant mutants of C. albicans, and in the future we will use these resistant mutants to leverage the tractable genetic systems of C. albicans to determine mechanism of action, thus allowing for targeted development of new antifungal therapies. Overall, this approach will build a platform for rapidly developing new molecules for antifungal therapeutics.

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Searching for Single Event Upsets in Muon Spectrometer Data for the ATLAS experiment at the LHC

ATLAS is one of the four major experiments at the Large Hadron Collider (LHC) at CERN. It ia general-purpose particle physics experiment run by physicists from all around the world. ATLAS physicists test the predictions of the Standard Model, which encapsulates our current understanding of what the building blocks of matter are and how they interact. These studies can lead to ground-breaking discoveries, such as that of the Higgs boson, physics beyond the Standard Model, and the development of new theories to better describe our universe. ATLAS is made up of many different instruments and subsystems, and this research focuses specifically on the Muon Spectrometer. Specifically within the Muon Spectrometer, this research analyzes data from Monitored Drift Tubes (MDTs). In short, muons are one of the very few things that get through the first three detectors within ATLAS, and MDTs work to trace the curved path of the muon as it passes through, which then allows for the calculation of its momentum. MDTs are filled with gas, and as the muon passes through a number of tubes, it leaves a trail of charged electrons that drift to the center of each tube. Recording the time of this drift process is what leads to the tracing the muon’s path. The goal of this research is to understand the issues that may develop in these drift tubes while everything is running and data is being taken. An example of this is a Single Event Upset (SEU). SEUs occur when a large energy deposition from one of the charged particles disrupts the functioning of the electronics, specifically, a state change of a logical element (a memory bit). The study will produce and compare a large variety of histograms from the beginning and ends of runs, and checking for any discrepancies. The research will look at different types of issues and their frequencies in 2018 proton-proton collision data.

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