Stander Symposium Projects

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  Pilot Performance Analysis in Virtual Environment

  Diya Liz Babu

  Predicting the performance of pilots in the aviation industry is essential for improving safety, efficiency, and overall operational effectiveness. Accurate evaluations of a pilot’s abilities can provide valuable insights for training programs, facilitate the development of customized training interventions, and contribute to the design of human-machine interfaces that align with individual skill sets. Moreover, understanding and predicting pilot performance can assist in identifying potential safety hazards and mitigating human factors that may contribute to errors in complex flight scenarios.This research primarily focuses on predicting and validating models for pilot performance during simulated flight operations, i.e. performing altitude or heading changes. This predictive scope involves essential metrics, the highest pilot entry stage input value (greatest yoke angle), aircraft heading error, aircraft heading change rate (yaw rate) during the pilot's initial recovery stage input, and compensatory corrections during the recovery period.Additionally, the research explores the temporal aspect of predictive accuracy, analyzing how early in the timeline we can effectively forecast pilot performance. Our proposed solution involves the utilization of Machine Learning Regression methods, assessing both Single Output and Multi Output models. Interestingly, the study reveals that Single Output models perform just as effectively as Multi Output models, suggesting a lack of correlation between the target variables for the Multi Output to outperform. Among the algorithms considered, Random Forest emerges as the most proficient in predicting pilot performance.

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  Police Behavior Survey

  Owen Christopher Lawless, Alejandro Jose Morales

  The current study looks to explore the connection between police traffic stops and if the individual who was stopped thought that the police officer behaved. Through many different variables we are able to see if our dependent variable, did the police behave, correlates. Our variables which we will be looking into are the race, age, sex of the individual, if the individual was given a reason for the stop, if the stop was legitimate, if the individual received a ticket, the time of day of the stop, the income of the person being stopped, and the amount of time of the stop. These variables will allow us to determine how the police behave from stop to stop and how the different features of the individuals affect the policies behavior. For the most part our variables are coded as (1) yes (2) no except for age which is categorized by age groups. For our variables we will be using linear regression to find our results. Our models showed that non-white people are more likely to say that the police did not behave more often. In the second model it also showed that non-white people said that police did not behave more often when in the same model as age and sex, but when with all of the variables we found that race was not significant. Our results also showed us that in model three that the reason for the stop, if the stop was legitimate, if you received a ticket, the income of the person, and the amount of time spent at the stop were all significant variables in our model.

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  Police Legitimacy in Low-Income Communities

  Chukwuzimife James Raymond Nwokeji, Christopher A. Peguero

  This research explores a measure of police legitimacy within low-income communities, seeking to uncover the dynamics that shape the intersection of law enforcement practices and community resilience. By examining the association between community trust, procedural justice, and the socioeconomic context, the study seeks to highlight the mechanisms through which police legitimacy may influence the cycle of criminal behavior among disadvantaged youth. Additionally, the research explores potential moderating factors that may amplify or mitigate the relationship between police legitimacy and recidivism, such as race, gender, gang involvement, and other socioeconomic variables.

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  Police Use of Force Towards Suspects

  Riley A. Bendery, Annalisa Benziger

  In 1994, the Phoenix Police Department, in collaboration with Rutgers University and Arizona State University, conducted a study on the use of force by and against Phoenix police officers. The study aimed to evaluate the extent of force employed in various arrest situations and to identify factors that could predict the amount of force used, including the involvement of the officer, the suspect, the nature of the offense, and the circumstances surrounding the arrest. The study generated a set of variables designed to accurately capture the diverse spectrum of forces commonly encountered in typical arrest scenarios. The study's design involved collecting data on all adult arrests made during a two-week period that commenced on June 13, 1994, in Phoenix, Arizona. The researchers obtained survey data from 1,585 adults who were booked by Phoenix police officers at Maricopa County Jail. Simultaneously, the Phoenix Police Department's automated information system recorded 1,826 arrests involving adult suspects being booked. In the second week of this two-week data collection period, the researchers randomly selected 20 out of 56 three-hour periods for conducting screening interviews with both officers and suspects. To understand the results, a statistical analysis using an ordinal regression model was conducted. Contrary to our hypothesis, this study found that race did not play a significant role in police victimization when accounting for other variables. What did play a significant role in understanding when an officer will use force is a suspect's sex, a suspect's age, officer's sex, the suspect's attitude during the encounter, and the suspect's resistance levels.

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  Political Representation, Democracy, and the Electoral College: An Applied Theoretical Analysis

  Jordan A. Marsh

  Though a key institution in the United States presidential election, the Electoral College has often been overlooked for close theoretical analysis and even less frequently dissected for a deeper understanding of its consistency with theories of representative democracy. As such, this presentation summarizes a study of the Electoral College through a theoretical lens to ultimately investigate the degree to which it is democratically representative. The first section analyzes the Electoral College through both a historical and a modern contextual lens. The second section of this paper explores various theories of representation, including the works of Pitkin, Rehfeld, Manin, and Mansbridge, among others. The third section scrutinizes the Electoral College’s representative nature through the frameworks of these theorists. Finally, the fourth section brings the representative nature of the Electoral College in conversation with the ideals of representative democracy, making the case that the Electoral College, in its current form, lacks critical aspects of democratic representation.

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  Porous Materials as a Thermal Protection System for Hypersonic Flight Vehicles

  Megan Colleen Sieve

  Hypersonic flight is defined as speeds of Mach 5 and faster. A critical problem that arises at those speeds is the immense heating of the vehicle. Hypersonic vehicles have thermal protection systems (TPS) to aid in thermal regulation; however, as faster speeds require large TPS, a design concern is how to make the TPS so to not cause any harm to the vehicle’s performance. This research project will investigate the most prominent instability that causes turbulence, and consequently, heat, on a flat-plate at Mach numbers of 4 and above: the second-mode boundary-layer instability. Different porous materials have been shown to dampen acoustic waves, which are the cause of second-mode boundary layer instabilities and is the focus of this study. This project is a continuation of the study “Effect of Porosity on the Ability of Silicon-Carbide Foams to Attenuate the Second-Mode Boundary-Layer Instability” (Bemis et al.). Experimental techniques used were PCB pressure sensors, Schlieren imaging, infrared thermography, and Rayleigh scattering. Silicon-carbide porous foams, wavy wall samples, and impermeable samples were tested on two different sized flat plates. The goals of these experiments were to study boundary-layer transition and the effect that different porous materials had on the boundary-layer.

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  Positive Psychology Interventions With Vulnerable Populations

  Anna Ružena Kopsick

  This poster will review research on the use of positive psychology interventions in the community, with a focus on the utilization of such interventions for vulnerable populations. Then, the poster will summarize success this semester in developing and utilizing such interventions with a homeless shelter population.

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  Power and Ideology Analysis: Escaping Twin Flames

  Hope Clegg, Tristan Fountain, Grace McMonagle

  Rhetoric drawing on religious stories, ideals, concepts, and experiences surround us in our daily lives. These posters represent a sampling of the rhetorical analyses conducted by students from CMM 357 Religious Rhetoric throughout the Spring 2024 semester. Groups presented several themed reports prior to Stander and picked one to showcase at the symposium.

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  Predicting Weather Dependent Energy Savings for Low-Income Residential Buildings for Specific Upgrades with Limited Building Data

  Phillip Allen Clayton

  The pathway to sustainability is challenging. Multiple paths exist, but the key will be to achieve carbon reduction with the least cost. This could be achieved through large scale deployment of renewable energy; however, many studies have shown how important it is to reduce demand first. This study employs machine learning to analyze detailed energy profiles from the National Renewable Energy Laboratory (NREL), estimating potential energy savings for natural gas heating, electric heating, and electric cooling through modifications such as insulation improvements, setpoint changes, infiltration reduction, or system efficiency enhancements. By comparing these building models with actual building data from Cincinnati, Ohio, via a nearest neighbor approach, mean savings are calculated for the ten most similar simulated houses. This process allows for the use of limited data (annual energy usage for heating and cooling and house area) to identify comparable model sets and estimate potential areas for energy-saving improvements. When savings estimates vary significantly (coefficient of variation greater than 0.2), clustering is applied to find a more consistent subgroup, enhancing the accuracy of the energy savings predictions.This methodology proves particularly effective for high energy-consuming residences, which are often found within low-income housing sectors. By focusing on buildings with the highest potential for energy savings, this approach offers targeted insights for utilities and city planners looking to prioritize energy reduction initiatives effectively. It highlights buildings where interventions could have the most substantial impact, both in terms of energy savings and cost efficiency.The next steps will involve validating the estimated savings against actual data. This validation process is crucial for refining the methodology and ensuring its applicability and accuracy in real-world scenarios. Focusing on high-consumption, low-income buildings, this study aims to reduce energy demand, enhance sustainability, and help vulnerable communities achieve greater energy efficiency.

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  Prediction of Hydrocarbon Density with Machine Learning Models

  Austin Christopher Grewell

  The approval procedure for new sustainable aviation fuels (SAFs) is a lengthy and costly process as it requires extensive testing. Several physicochemical properties must be measured for a new jet fuel, and their values must fall within specific required ranges. The ability to mitigate actual testing and measurements with predictive models would accelerate the certification process and reduce the associated costs. Machine learning (ML) algorithms are increasingly attractive tools for developing predictive models for the physicochemical properties of jet fuels.This project used machine learning methods to predict the density of hydrocarbon mixtures based on specific molecular descriptors. A dataset comprised of 17060 hydrocarbons with known density and corresponding molecular descriptors (group functionalities and topological indexes) was used to train ML models. Random forest and artificial neural networks were chosen as training algorithms. A hyperparameter optimization was used to determine the optimum parameters for each model.The random forest models trained with 80% of the dataset yielded R2 values greater than 0.98 for the remaining 20% of the dataset, indicating good performances and minimal to no overfitting. Models were tested on a set of random binary, tertiary and quaternary mixtures, yielding R2 values greater than 0.88.

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  Pre-health Interview Workshop

  Rachel Victoria Bull, Katarina Lucyna Lagodzinski, Kayla Deanne Ogburn

  This workshop is for Pre-Health students, or any other students who are interested in seeing what the Pre-Health interview process is like. The live mock interview session will allow students to hear feedback and commentary from the interviewer. In addition, there will be a Q&A session at the end for students. This will be a session helpful to under-classmen and juniors who have questions about the interview process. We hope this presentation will give students tips and insight into the interview process they will encounter in the future.

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  Preparation and Studies of New Difunctional Spirobicyclic Epoxy Monomers

  Andrew Michael Kelly

  We are presenting results on the investigation of a novel, spirocyclic, P-containing bifunctional epoxy compound, envisioned as a potential reactive flame retardant. We will report results from our synthesis efforts, the use of the target in epoxy formulations, and flammability studies of the resultant epoxy resins.

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  Preparing subunit vaccine for Influenza A virus and measuring its immune response in rats

  Kelechi Richie Okere

  Influenza A virus (IAV) is an enveloped, negative-sense, single-stranded, segmented RNA virus.It is one of the highly infectious viruses that resulted in at least 14 or more viral pandemics inhistory, including influenza virus pandemics in 1918, 1957, 1968, 1977, 2009, and 2013.Inactivated whole virus and live attenuated virus vaccines effectively control seasonal influenzavirus infections. Subunit vaccines are considered safer than inactivated or live attenuated virusvaccines, especially among elderly people. The current experiment in the Immunology lab (BIO496L) was designed to prepare a subunit vaccine for IAV using its nucleoprotein (NP) andanalyze for vaccine response in rats against the virus. IAV A-NP, strain A/PR/8/35 was mixedwith Freund's complete adjuvant and injected into the rats (Sprague Dawley) subcutaneouslyaccording to the University of Dayton IACUC protocol. A booster dose was given after oneweek of primary vaccination and blood was collected after two weeks of booster vaccination.The serum was separated and analyzed for IAV A nucleoprotein (NP) specific antibodies using aprecipitation test, Enzyme-Linked Immunosorbent Assay (ELISA), and hemagglutination (HA)/hemagglutination inhibition (HI) assays. Results showed IAV A nucleoprotein (NP) specificantibodies in the precipitation test, while ELISA showed a 10.74±0.71 increase in antigen-specific antibodies in the rat serum vaccinated with the subunit vaccine, whereas HA/HI assayshowed 80 HI units for influenza virus A neutralizing antibodies. Overall, the current experimentshowed that the subunit vaccine prepared in the lab induced a protective immune responseagainst the influenza A virus.

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  Probing for the developmental mechanisms underlying repeated tooth loss in frogs

  Jacob A. Szafranski

  Teeth have been lost several times during the evolution of vertebrates, resulting in toothlessness, but is most widespread in frogs with over 20 independent losses. Investigations in toothless fishes, reptiles, and mammals have found that the tooth development program is not completely lost. These species maintain early molecular signaling and can develop transient tooth bud rudiments prior to the termination of the tooth development program that is disrupted via multiple pathways (loss of expression for different genes). We investigated convergent tooth loss in frogs by examining a developmental series of several toothed and toothless species using histological sectioning, microanatomical investigation, and gene expression analyses. We hypothesized that several different mechanisms arrest tooth development in the upper jaw across toothless frog species that have independently lost teeth. Unexpectedly, we have found little anatomical or molecular evidence that the tooth development program initiates in the upper jaws of any toothless frog species investigated. These results suggest that frogs are capable of losing teeth without a trace, driven by an underlying mechanism that is distinct from the patterns identified in all other toothless vertebrates.

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  Problem based learning for a problem based society

  Brendan Patrick Lacke

  Since the 1960’s, problem-based learning, also known as PBL, teaches students lessons and morals through real-world problem examples. I will define Problem-based learning, discuss the history, and current application of this method in schools.

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  PUND Behavior of an HZO Device

  Tristan David Quach

  Ferroelectric materials form the backbone of silicon electronic memristor devices in silicon electronics and are gradually becoming more prevalent in silicon photonics for optical memory applications. In this context, hafnium zirconium oxide (HZO), an established material in the silicon electronics foundry, is making inroads in silicon photonics aided by its nearly zero absorption at near-infrared wavelengths that makes it compatible for integration with silicon photonic waveguides and resonators. A fundamental measurement technique to characterize ferroelectric material behavior is PUND. The acronym stands for positive up negative down. A PUND measurement is a series of five pulses based around the values of max voltage, period, and pulse width. PUND starts with a negative pulse used to preset the sample. The next two pulses are in positive volts. The last two pulses are in negative volts. This project aims to find ferroelectric properties of a HZO device using PUND measurements. To this end, the needed parameters for the PUND measurement must be found to adequately characterize the hysteresis behavior of the devices. The desired voltage and pulse width are 1V and 1 millisecond respectively. The pulse delay (the time from the end of one pulse to the start of the next) must be long enough to allow the device to discharge between PUND pulses. Once the necessary pulse delay for discharge between pulses is found, the number of PUND cycles the device must go through in order to show ferroelectric behavior, the wake-up effect, must be found. We will present initial measurement results.

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  PV Orientation Optimization for Residential & Commercial Buildings Considering Fixed & Bi-annual Orientation with a Constant or Varying Tariff

  Jacob J. Brenner

  Optimizing photovoltaic (PV) panels beyond the use of additional technology is one method that many have analyzed to make PV panels as valuable as possible. It often comes in the form of orienting the tilt and azimuth of a panel for the most energy collected. This does improve the value of PV panels, but there are other considerations for the optimum orientation, as having the most energy collected does not guarantee the greatest value. This has culminated in a great amount of analysis of the optimum orientation for revenue over the past decade. The goal of this study was to add to this growing analysis by analyzing cases of commercial and residential buildings across four separate cities in the US using three separate possible tariff plans that are shared amongst every location. Results for savings were found for each location and building type for annual and biannual orientations using PVWatts API version 8. It was found that the maximum difference in the percentage of savings for an annual energy bill between a panel oriented for the purpose of energy and one for savings is 2.45% for annual and 3.12% for biannual. It was also found that when export value is nonexistent the optimum orientation will go for collection during peak hours, and when export value is overwhelmingly larger than the import the optimum orientation will go towards the times when electricity is used the least. It was also found that commercial buildings have their optimum revenue orientation closer to the optimum orientation for energy than residential buildings, and so the overall differences between the two orientations for savings for commercial buildings is smaller.

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  Quantifying the impacts of precipitation seasonality and intensity on groundwater availability in Hosanna, Ethiopia.

  Rose H. Weisgerber

  Understanding the link between precipitation and groundwater is vital for ensuring water resources' availability, reliability, and sustainability, particularly in arid regions such as Ethiopia that are vulnerable to climate change. To understand the main controls of groundwater recharge and estimate the seasonal contribution of precipitation, we conducted a comprehensive water isotope study in Hosanna, southern Ethiopia. Due to the complex interconnection of climate, rainfall, and groundwater recharge in this region, we used multiple approaches. Using stable isotopes of Hydrogen (δD) and Oxygen (δ18O) as a conservative tracer, we developed a local meteoric water line (LMWL) and employed isotope mass balance. These analyses provide a quantitative estimate of groundwater recharged and recharge mechanisms.Additionally, Hybrid Single Lagrangian Integrated Trajectory (HYSPLIT) modeling, correlation analysis of climate data, and intensity threshold analysis shed further light on the source of moisture, atmospheric, and climatic controls. Our findings indicate that precipitation in Hosanna mainly originates from recycled moisture sources, evidenced by d-excess, with the oceanic advected moisture seasonally alternating between the North and South Indian Oceans. The wet season provides most of the annual precipitation, with groundwater recharge biased (~65.5%) towards the wet season. However, the intensity threshold analysis suggests extreme rainfall events had the most significant impact on groundwater recharge. The amount-weighted δ18O values of five extreme precipitation events occur during the wet season and have a similar isotopic composition (0.86‰ difference) with the groundwater δ18O values. While wet season and high-intensity precipitation account for most groundwater recharge, slow diffuse recharge, focused recharge from rivers, and dry season precipitation account for the rest of groundwater recharge. This study establishes the source and main contributors of regional groundwater recharge in Hosanna. It provides invaluable information for surface water contaminant transport, water resource management, sustainable development, and climate change adaptation strategies.

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  Quantitative Concentration and Density Measurements in Subsonic and Supersonic Helium Jets Using Rainbow Schlieren Deflectometry

  Henry H. Jacques

  Rainbow Schlieren Defectometry (RSD) has been applied to acquire quantitative concentration and density measurements in both subsonic and supersonic conditions. Experiments were conducted using a helium jet expelled into air for two distinct regimes: initially laminar, momentum-driven at subsonic speeds, and subsequently at supersonic speeds. Comprehensive full-field measurements were captured, encompassing the laminar, transition, and fully turbulent regions of the jet in both subsonic and supersonic conditions. The subsonic (momentum-driven) regime was validated against Rayleigh scattering data in the literature. The supersonic regime utilizes a novel approach for acquiring density, where the mixing field is delineated into three portions: the potential core, the non-isobaric mixing shear layer, and the isobaric far field. Results from the RSD technique demonstrate robust mixing measurement capabilities for both subsonic and supersonic applications. The results from this work show promise for future applications involving the use of quantitative RSD for fuel injection studies.

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  Quantitative Methods for the Diagnosis of Traumatic Brain Injury Using Eye Gaze and Biometric Sensors

  Tanner Anthony Cuttone, Nathaniel Robert Doll, Ryan J. French, Isabella M. Saylor, Meredith Katharine Tropeano

  This poster provides a summary of an IRB approved research study on the optical response of the human eye using a GazePoint eye tracking system and biometrics hardware. Pupil dilation, gaze position, blink rate, and reaction time were recorded for human subjects in response to various visual stimuli on a computer screen. In addition, heart rate and galvanic skin response were recorded using a suite of biosensors. The experimental tasks were designed with varying levels of complexity and included both memory-recall and computational tasks. The overall aim of this study was to establish baseline data sets across multiple demographics, which can be used in the future to advance clinical diagnostic methodologies using quantitative methods for various types of traumatic brain injury, including concussion.

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  Quantitative Scalar Supersonic Boundary Layer Measurements on a Conical Geometry using Rainbow Schlieren Deflectometry

  Joseph Kastner

  This study utilizes an optically accessible shock tube to emulate supersonic flow conditions for the purpose of a novel optical diagnostic development. A simple conical cone is used to develop a methodology to acquire full-field, quantitative scalar measurements in the boundary layer via Rainbow Schlieren Deflectometry (RSD). RSD will be implemented for the first time to record quantitative full-field density and pressure measurements inside the boundary layer. A parametric study is performed to investigate the full-field evolution of the density and pressure fields under the effects of Mach number. The results of this study will be validated with pressure probe data gathered from within the shock tube.

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  Quantization of Thermal Radiation in Blackbody Radiation

  Thomas Silvio De Santis, Matthew Joseph Sandor, Nathan Charles Sowder

  A black body is an ideal object that when heated emits thermal radiation but absorbs all radiation shined on it. In the early 1900’s physicists were interested in describing radiation emission of such objects, but to no avail. Classical physics was simply unequipped to describe black bodies. One theory, Rayleigh-Jeans equations, is one such failed attempt. One of the problems of using classical physics known at the time to describe blackbodies was the so called "ultraviolet catastrophe." The ultraviolet catastrophe comes about because classical physics assumes that energy is continuous and as such the calculated total energy emitted by a blackbody becomes infinite, which is physically unrealistic. Max Plank, a theoretical physicist, hypothesized that energy absorbed or emitted by molecules is quantized, thereby leading to what is known Planck's equation that solved the ultraviolet catastrophe and gave birth to a new field of physics called quantum mechanics. The theoretical treatment of black bodies has resulted in many applications. It is now used in medical and thermal imaging, understanding the temperature and composition of stars, just to mention a few.

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  Quantum Entanglement

  Claire Olivia Hogshead, Madeline L. O'Mahoney, Ian Jacob Sundeen

  Did you know that two particles could interact instantaneously across vast distances? This is possible through quantum entanglement. One way to do this is to correlate two particles in an entangled state. These particles can have two different spins, where the chance of a particle having either spin up or down is completely random. However, when the two particles are entangled and the spin of one particle is measured, the other entangled particle will always have the opposite spin. Strangely, this can happen regardless of the distance between them, exhibiting non-local interdependence! This “quantum spookiness” has been experimentally demonstrated with photons and electrons. Quantum entanglement has potential applications in many fields, particularly quantum computing and cryptography.

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  Quantum Field Theory : An Overview

  Joseph Michael Kopp

  Quantum Field Theory (QFT) is considered to be one of the most successful scientific theories of all time. It explains 3 of the 4 fundamental forces nearly perfectly, with the fourth being described by general relativity. In this poster, I will talk about what exactly a field theory is, the 3 fundamental types of fields, their equations, and their interactions, as well as give a few applications of QFT in physics.

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  Queer Joy on Our Screens

  Reagan Marie Lloyd

  This THR/VAR 250 Diversity in the Creative and Performing Arts poster presentation project requires each student to research and present on a topic relevant to the interdisciplinary fields of visual and performing arts through a critical multicultural and social justice lens that foregrounds the appreciation of diversity and enables the expansion of personal cultural competencies.