Architecture

Authors: Richard Ji, Emre Dal, Ayana Srivastava, Beverly Chigarira, Chadi Hage Chehade, Arshit Narang, Georges Gebrael, Neeraj Agarwal, Umang Swami, Haoran Li. Mentors: Neeraj Agarwal. Insitution: University of Utah. Comparative effectiveness of ChatGPT 4.0 and medical oncologists in telemedicine-based management of metastatic prostate carcinoma (mPC).Richard Ji1, Emre Dal1, Ayana Srivastava1, Beverly Chigarira1, Chadi Hage Chehade1, Arshit Narang1, Georges Gebrael1, Neeraj Agarwal1, Umang Swami1, Haoran Li21Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT;2University of Kansas Cancer Center, Westwood, KSBackground: The advent of telemedicine, accentuated during the COVID-19 pandemic, offers a prospective modality, especially when synergized with artificial intelligence (AI) tools such as ChatGPT 4.0. In this investigation, we sought to investigate the proficiency of ChatGPT vs. medical oncologists in the telemedicine-centric management of mPC.Methods: This IRB-approved retrospective study compared the competencies of ChatGPT and oncologists in conducting telemedicine consultations for patients with mPC. Out of 975 patients screened between April 1, 2022, and March 30, 2023, 102 met the inclusion criteria of having a diagnosis of mPC, attending at least one telemedicine consultation during the specified period, and having documentation available for two consecutive visits to enable the analysis of treatment decisions and outcomes. ChatGPT was asked to pre-chart and determine if a face-to-face consultation is needed. Its clinical competence was assessed using miniCEX, and medical decision-making (MDM). The Cohen's kappa test was used to measure the level of agreement between ChatGPT and oncologists in treatment decisions, and the Mann-Whitney U test was used to compare miniCEX and MDM.Results: The majority of patients were White (97.06%), with a median age of 75 years (range:53 to 99). Nearly all patients were diagnosed with adenocarcinoma (96.08%), with a median Gleason score of 7 (range: 6 to 10). The prevalent metastatic sites were bone (47.4%) and lymph nodes (44.16%). 26.88% had an ECOG score of 0, 54.84% had a score of 1, and 18.28% had a score greater than 1. Common coexisting conditions included diabetes mellitus (11.11%), hypertension (29.82%), hyperlipidemia (24.56%), and depression (7.6%). The primary outcome measured the concordance between ChatGPT and oncologists on whether to continue or cease the current treatment There was a statistical significance in sensitivity and specificity between clinicians and ChatGPT (Chi-squared=5.1, p=0.02). Cohen's Kappa showed a moderate concordance (Kappa = 0.43, p<0.001). There was no difference in the number of diagnoses made by the two parties (p=0.13 and 0.06, respectively). ChatGPT's median miniCEX score was 8 (SD=0.59), and its median MDM length was 41 words (SD=6.06). The average time saved by ChatGPT in pre-charting was 41 minutes (SD=6).Conclusions: ChatGPT showed moderate concordance with oncologists for the management of mPC in telemedicine. Subsequent investigations are needed to explore its potential in healthcare.

Authors: Mallory Hinton, Matthew Madsen, Raechel Hunsaker, April Hulet. Mentors: April Hulet. Insitution: Brigham Young University. Seeding plants post disturbance on rangelands is a challenge due to unique ecological and environmental conditions such as limited water availability, invasive species, soil health, and native seed supply. One of the key factors to address these challenges and have a successful seedings is understanding the relationships between soil characteristics and the plants that grow within them. Our research evaluated plant growth for seventeen grass species in two degraded rangeland soils (a mine tailings impoundment and Santaquin Wildlife Management Area) in Utah. Grasses (10 PLS/5cm 2 pot) were grown in self-watering growth trays in a complete, randomized block design with four replicates per soil type. After 21 days in the greenhouse, plant densities and aboveground biomass were collected and analyzed. Soils differed in mineral content. Iron and nitrogen were 5- and 4-fold greater in Tailings than Santaquin soil; phosphorus, magnesium, and organic matter were 5.5-, 4-, and 18-folds lower in Tailings than Santaquin soil. The average density of plants was significantly different (p < 0.0001) between the two soil types; in the Santaquin soil plant density was 5.73 plants/pot, in Tailings soil plant density was 2.20 plants/pot. No individual grass species were significantly different from each other in the Tailings soil (p = 0.51). However, individual grass species were significantly different from one another in the Santaquin soil (p = 0.05). Both Tailings and Santaquin soil types had the highest densities of slender wheatgrass (Elymus trachycaulus; 4.75 plants/pot and 8.25 plants/pot, respectively) and tall wheatgrass (Thinopyrum ponticum; 4.75 plants/pot and 10.25 plants/pot, respectively). Sandbergs bluegrass (Poa secunda) had the lowest density in both soil types (zero plants in Tailings soil and 2.50 plants/pot in Santaquin soil). To make informed decisions when selecting plant species for seed mixes, soil characteristics should be considered.

Authors: Allison Gabbitas, Kaitlyn Allen, Gene Ahlborn, Shintaro Pang. Mentors: Shintaro Pang. Insitution: Brigham Young University. Mycotoxin contamination on food and feed can have deleterious effect on human and animal health. Agricultural crops may contain one or more mycotoxin compounds; therefore, a good multiplex detection method is desirable to ensure food safety. In this study, we developed a rapid method using label-free surface-enhanced Raman spectroscopy (SERS) to simultaneously detect three common types of mycotoxins found on corn, namely aflatoxin B1 (AFB1), zearalenone (ZEN), and ochratoxin A (OTA). The intrinsic chemical fingerprint from each mycotoxin was characterized by their unique Raman spectra, enabling clear discrimination between them. The limit of detection (LOD) of AFB1, ZEN, and OTA on corn were 10 ppb (32 nM), 20 ppb (64 nM), and 100 ppb (248 nM), respectively. Multivariate statistical analysis was used to predict concentrations of AFB1, ZEN, and OTA up to 1.5 ppm (4.8 µM) based on the SERS spectra of known concentrations, resulting in a correlation coefficient of 0.74, 0.89, and 0.72, respectively. The sampling time was less than 30 min per sample. The application of label-free SERS and multivariate analysis is a promising method for rapid and simultaneous detection of mycotoxins in corn and may be extended to other types of mycotoxins and crops.

Authors: Raechel Hunsaker, Matthew Madsen, Mallory Hinton, Derek Tilley, April Hulet. Mentors: April Hulet. Insitution: Brigham Young University. Many early successional plant species have been considered weeds because of their lack of forage value for livestock. However, early successional plant species have the potential to aid rangeland restoration by providing food sources for pollinators, modifying soil in preparation for climax plant communities, and competing against invasive species. To determine which early colonizing species have the greatest restoration potential, interspecific competitive interactions should be evaluated. Our research objective was to evaluate the competitive abilities of two native pioneer forb species, curlycup gumweed (Grindelia squarrosa) and prairie aster (Machaeranthera tanacetifolia), against three common rangeland grasses including 1) native early successional species, bottlebrush squirreltail (Elymus elymoides), 2) invasive colonizing species, cheatgrass (Bromus tectorum), and 3) climax community species, bluebunch wheatgrass (Pseudoroegneria spicata). Treatments included each of the three grass species seeded at high and low densities with curlycup gumweed or prairie aster in two soils (mine tailings and disturbed rangeland) in a greenhouse. After being cultivated for 54 days, above-ground biomass for both forbs were not significantly different when seeded alone, or with high and low densities of grasses in the mine tailings soil (p ≥ 0.05). However, in soil from the disturbed rangeland, forb biomass differed. When planted alone, curlycup gumweed and prairie aster biomass was on average 2.5- and 3-fold greater than when planted with high and low densities of squirreltail and cheatgrass (p ≤ 0.05). Both forbs had significantly lower biomass when planted with a high density of bluebunch (p ≤ 0.05), however, when planted with a low density of bluebunch, biomass was not significantly different than when planted alone (p ≥ 0.05). Results indicate that high densities of squirreltail, cheatgrass, and bluebunch inhibit curlycup gumweed and prairie aster growth on disturbed rangeland soil, and that interspecific competition may be a barrier to the successful establishment of early successional forbs.

Authors: Reganne Leigh Hales, Laura Sutherland, Melissa Sanchez Herrera, Samantha Standring. Mentors: Seth Bybee. Insitution: Brigham Young University. We explore the phylogeny of Hetaeriinae using a targeted enrichment approach (AHE) on gDNA gathered largely from museums. AHE resulted in 20KB (18.5KB of nuclear and 1.5 of mitochondrial DNA) for each taxon. Previous research, based on sanger data generated from three genes, demonstrated that Hetaerina Hagen in Selys, 1853 is not monophyletic but no taxonomic changes were proposed due to the hope of one day having more data. Our goal for this research was to have a larger dataset to test the monophyly of Hetaerina and update the classification. Our results confirm those of the most recent phylogeny of Hetaerina: the genus is non-monophyletic. We recover Mnesarete Cowley 1934 and Ormenophlebia Garrison 2006 within Hetaerina. We have preliminary data (results not shown) demonstrating that both Iridictyon Needham & Fisher 1940 and Bryoplathanon Garrison 2006 are also within Hetaerina. However, due the placement of these genera there is not a clear way to retain these genera and it is likely they will need to be placed within Hetearina due to priority. We further explore the evolution of some characters associated with habitat preference.

Authors: Lauren Ford, Joel Woolley, Ryan Powers, Paulina Medellin, Hillary Wadsworth, Jordan Yorgason. Mentors: Jordan Yorgason. Insitution: Brigham Young University. Women prescribed psychostimulants have self-reported changes in drug efficacy that coincide with menstrual cycling. Furthermore, cocaine and amphetamine effects on dopamine (DA) transmission are more potent in female rodents, an effect that has been linked to cycling hormone levels. However, it is unknown if changes to DA transmission vary by specific psychostimulant, and striatal DA transmission has not yet been well characterized across the estrous cycle. The present study considers dopamine release and reuptake kinetics across various stages of the estrous cycle in the nucleus accumbens (NAc), a key region for dopamine-mediated learning. The effects of cocaine, methamphetamine, and methylphenidate on female dopamine transmission are examined using slice voltammetry. Our data shows that compared to a male control group, baseline (pre-drug) dopamine release in the NAc was lower in females overall, but not at all estrous stages. Applying increasing concentrations of cocaine or methylphenidate revealed similar patterns of enhanced, then diminished release in all mice. Methamphetamine decreased NAc dopamine release similarly in both males and females, but females in estrus were more affected than males, and those in met/diestrus less. Methamphetamine also slowed dopamine uptake in all mice, and at lower concentrations than cocaine or methylphenidate. We find minimal sex differences between cocaine and methylphenidate effects in the NAc, suggesting that the underlying cause of their observed behavioral sex differences may be specific to other striatal regions. On the other hand, methamphetamine-induced DA release fluctuates distinctly with the estrous cycle and peaks when estrogen levels are at their highest, indicating that estrogen and methamphetamine mechanisms share a target in NAc DA terminals that cocaine and methylphenidate do not. This work refines our understanding of DA transmission in females and indicates potential future directions for understanding female psychostimulant abuse.

Authors: Chad Hyer, Bradley Bundy, Tyler Free. Mentors: Bradley Bundy. Insitution: Brigham Young University. Current trends in healthcare suggest a movement towards point of care treatment and diagnosis. This transition towards local or even at-home testing necessitates dramatic decreases in costs of diagnostic methods. Cell-free protein synthesis (CFPS) systems prove a potential tool for bringing diagnostic solutions to patients by providing patients with inexpensive, easy to use, and accurate tests that can be stored for long periods of time at ambient temperature. These CFPS diagnostic methods rely on the production of biosensor proteins using isolated molecular machinery from bacterial cell lysates and necessary substrates. When combined with human body fluids, these biosensors can detect the presence of important biomarkers of disease, aiding in diagnosis.CFPS systems, however, can prove difficult to use with human body fluids as CFPS systems rely on mRNA directed production of proteins, and human samples contain significant concentrations of RNAses which inhibit the production of biosensor proteins, preventing proper test results. Traditionally, this issue can be remedied in a CFPS system using commercially sourced RNAse inhibitors, but these inhibitors dramatically increase prices. Here we report on our production of RNAse inhibitors within a CFPS system to decrease costs of CFPS diagnostics by 90%. In our work, we report on the optimization of reaction conditions for producing RNAse inhibitors within a CFPS glutamine biosensor for use as a cancer treatment monitoring diagnostic. Using our methods, we expect to be able to dramatically reduce the cost of CFPS based diagnostic tools, helping empower the shift to affordable point of care healthcare.

Authors: Eliza Ballantyne, Maria Lizio, Anshuman Chaturvedi. Mentors: Dustin Shipp. Insitution: Utah Valley University. We evaluate techniques for enhancing performance of Raman based classifiers of lung cancer and compare them to results from immunohistochemistry and hematoxylin and eosin (H&E) staining for fixed samples. In the United States, more patients die from lung cancer than from any other type, although it ranks as the third most common cancer. For patients with lung cancer, preserving the healthy bronchioles where cancer usually forms is vital to continued lung function. Raman spectroscopy is already a valuable asset in distinguishing between healthy tissue and many types of cancer and decreases discrepancies between diagnosis, saving medical resources and improving patient outcome. Lung cancer is especially challenging for Raman spectroscopy, in part because tar fluorescence often overpowers critical chemical features. We introduce measurement and classification approaches as the first step to overcome this challenge and create reliable Raman based classifiers for lung cancer. By working with fixed tissue sections, we avoid tar fluorescence and demonstrate the ability to detect tumors and premalignant abnormalities in lung tissue. These samples allow collaboration between adjacent sections in both H&E staining and immunohistochemistry. Furthermore, additional measurements of fixed sections can be acquired at any time. These advantages provide flexibility to acquire more detailed training sets, include more detail of any borderline cases, and compare Raman spectroscopy to more specialized histopathological techniques.

Authors: Caroline Torgersen, Tyler O'Loughlin, Ellie Evans, Vern Hart, Clint Flinders. Mentors: Vern Hart. Insitution: Utah Valley University. Stage-IV cancers are commonly identified by tumors having metastasized to other parts of the body. However, studies have shown that cancerous tissues often release “seeds” of circulating tumor clusters (CTCs) into the cardiovascular and lymphatic systems long before metastasized sections of the tumor are identifiable. These CTCs can circulate or remain dormant for long periods of time, even after the lesion is excised. In addition, these structures exist on scales that are not currently identifiable using conventional imaging modalities and are only detectable after being isolated. To address this issue, we demonstrate a simple optical diffraction system utilizing visible laser light and a beam profiler to collect speckle images from polystyrene microbeads (mimicking CTCs) flowing through an IV tube (mimicking a vein or artery). These scattering images were used to train a convolutional neural network, which was able to distinguish bead sizes ranging from 30 to 120 microns (comparable to the diameter of CTCs). A Softmax classifier was included with multiple target categories corresponding to different clusters sizes. As blood cells are significantly smaller (5-20 microns), this system could be used to non-invasively identify the presence of larger scatterers in a blood stream in situ, indicating the presence of CTCs, and providing a potential diagnostic biomarker for early-stage cancer.If a oral presentation is not available we would still love to present a poster.

Authors: Mohamed Askar, Matthew Roberts, Jeremy Matney, Andrew Larsen, Edwin Cansaya Sanchez. Mentors: Mohamed Askar, Matthew Roberts. Insitution: Southern Utah University. Stormwater infrastructures in the U.S. are aging and deteriorating, with most municipalities historically treating stormwater runoff or drainage problems during an emergency or structural failure. What if we could address such issues before they became problematic? Our main objective is to help decision-makers deal effectively with long-term control measures of the budget-limited, ambiguous, and inconsistently applied operation and maintenance of stormwater infrastructures. To this end, an innovative Five-Dimensional Assessment Model (5D-SAM) for the operation and maintenance of stormwater control measures will be developed and tested in the economically disadvantaged rural community of Cedar City, Utah. The model’s strategic approach will employ a prioritized list to create innovative green stormwater infrastructure solutions (clean-energy technologies) for sustainable urban development. The proposed 5D-SAM model includes research on its broader impacts, with a theoretical focus on the nexus of stormwater control measures and design to enhance urban sustainability and resilience. This focus is on the translational and transdisciplinary link between the operation and maintenance of stormwater research outcomes in Cedar City. Performance indicators of the stormwater system will be designed to assess five conditions: assets, functionality, time-effectiveness, cost-effectiveness, and environmental and social impact. 5D-SAM will calculate the performance/health index of the stormwater infrastructure, predict the future state, manage the quantity, and improve stormwater runoff quality. The built-in GIS database will aim to preserve the natural features and functions of stormwater infrastructures while providing a list of cost-effective and environmentally friendly alternatives if a distressed stormwater system is better off demolished, repaired, rehabilitated, or retrofitted. The model benefits society as it applies to other water infrastructure systems, including groundwater wells, dams, reservoirs, treatment facilities, sewer lines, flood prevention, and hydropower. Finally, the proposed research is a valuable and growing resource for students, faculty, urban researchers/practitioners worldwide, and the general public.

Authors: Davi Cavinatto. Mentors: Steven Allen. Insitution: Brigham Young University. Previous work indicates that magnetic gradients oscillating at the same frequency and direction as ultrasound (US) longitudinal displacement can encode particle movement into the complex phase of a magnetic resonance (MR) image. Until now, the coil configuration (Helmholtz) used to generate this oscillating magnetic gradient has constrained the use of this technique to small imaging volumes. Here, we explore the feasibility of using a single coil configuration to improve the versatility of the apparatus, making it possible to visualize US waves as they propagate through tissue that was previously inaccessible through the technique, such as the human brain. This novel approach to the visualization of US waves could potentially be used to establish the missing correlation between the results of neuromodulation treatments and their mechanism of action, thus improving the scientific rigor of this field of research.Wolfram’s Mathematica and COMSOL’s Multiphysics were used for developing a single-coil configuration in silico. The coil design was constrained by the minimum imaging distance from the coil (20mm), gradient needed for an image with signal-to-noise ratio of approximately 10 (0.4 T/m), minimum coil inner radius for fitting the US transducer (20mm), maximum peak current at the coil (20A), and frequency of operation (500kHz). Using Biot-Savart’s Law and Mathematica, we estimated the number of turns needed and the total length of the wire. In order to reduce the skin effect and proximity effect due to the frequency of operation (500kHz), a specific Litz wire configuration was chosen for the windings. Plots for the magnetic gradient over the central axis of the coil were created and compared on both programs to confirm the accuracy of the model.Plots of both the mathematical and in-silicon models matched and proved the high efficiency of the coil system at the frequency of application. The two magnetic field gradient plots corroborate the feasibility of the proposed single coil system for imaging US waves and verification of the functioning of neuromodulation in the extension of the cerebral cortex.

Authors: Kasielynn Bussard, Dakota Stringham. Mentors: Matthias Pleil. Insitution: Salt Lake Community College. We are two students from Salt Lake Community College who participated in a summer research workshop in the cleanroom at the University of New Mexico. We were taught the pressure sensor fabrication process, along with the post-production testing methods. For our research project we decided to test how using different biocompatible metals, and different combinations of said metals, for the circuit would affect the pressure sensors functionality. To test this, we prepped five 4” inch wafers and used photolithography to define the Wheatstone bridge pattern, followed by sputter metal deposition. When sputter coating, we coated each wafer in a Venn diagram pattern. This left us with two areas of a single metal on the outside edges, and an area in the middle with both metals present. We then measured the resistance of each section to determine how it changed with different metals.

Authors: Joshua Lim. Mentors: Nathan Crane. Insitution: Brigham Young University. Metal additive manufacturing (3D printing) technologies have evolved in the past decade to produce intricate parts in aerospace, car, and biomedical industries. While previous work has been done on single materials, metal-metal composites can expand performance but hasn’t been thoroughly explored. This work investigates ways of creating composites by molted bronze infiltration. At a certain temperature, bronze is melted and seeps through parts that are made via additive manufacturing. By altering the geometry of the pathways that the molten bronze will travel through or the metal particles themselves, one can create unique parts that control where the bronze infiltrates. Initial results indicate that mechanical properties were measurably strengthened by the addition of molten bronze and hypothetically could be used to create thermally graded parts, optimized for specific applications where heat transfer is a parameter of interest.

Authors: Aldo Chipana, Sarah G Sanderson, Joseph Moore, Jeffery R Hill, Christopher R Dillon. Mentors: Chris Dillon. Insitution: Brigham Young University. Nitinol shape memory alloys have shown immense promise in biomedical engineering, with their exceptional biocompatibility and corrosion resistance. Interestingly, most biomedical applications rely on Nitinol’s super elasticity rather than its hysteretic properties. Previous research in this lab has highlighted the challenges and potential of using focused ultrasound to effectively heat Nitinol wire without causing damage to adjacent tissue. Building upon these findings, our current study presents an extension of the initial experiments, incorporating more realistic in-body conditions. This includes simulating blood flow, which influences the heat transfer taking place in our control volume. Furthermore, we utilize artery mimicking materials to recreate the conditions of human arterial walls. Through comprehensive experimentation and accurate temperature measurements using embedded thermocouples, we aim to enhance our understanding of the interactions between Nitinol wires, surrounding tissues, and focused ultrasound heating. An integral part of our investigation is to discern whether the focused ultrasound directly heats the Nitinol wire or if actuation is achieved indirectly by heating the surrounding tissue. These results will offer insights into the applications of shape memory alloys in diverse biomedical settings, potentially paving the way for more effective and safer medical use.

Authors: Peter Seely, Joseph Henderson, Benjamin Webb. Mentors: Benjamin Webb. Insitution: Brigham Young University. A longstanding result in spectral graph theory is that some of the eigenvalues of a network can be obtained by identifying equitable partitions within the graph's structure. We have discovered that the remaining eigenvalues can be recovered using theoretical constructs which we call Local Equitable Partitions (LEPs). We have developed a procedure to find LEPs in a way that allows us to efficiently compute a graph's spectrum using this theory. Our procedure finds LEPs by identifying patterns in the coarsest equitable partition of a graph. We utilize these LEPs in a novel algorithm for computing the spectrum of a graph. Under certain mild assumptions on the equitable partition, we can find eigenvalues of a graph faster using this method when compared to the standard method. This is potentially useful as many real-world data sets have nontrivial equitable partitions.

Authors: Benjamin D Kearsley, Jacob H Norby, Micah R Shepherd, R Ryley Parrish. Mentors: Micah R Shepherd. Insitution: Brigham Young University. Status epilepticus (SE) is a seizure which lasts more than five minutes and requires time sensitive treatment to prevent brain damage and even death. Thus, it is crucial to understand and predict the brain signal patterns preempting SE. Previous research into seizure monitoring techniques in humans suggests that seizure occurrence follows non-random patterns, and that big data and machine learning may be key in discovering detection and prediction models for SE events. This provides a promising foundation for our investigation into a prediction algorithm for SE using data-driven methods.Using a state-of-the-art Multiple Electrode Array (MEA) recording device, high-resolution signals have been recorded that demonstrate the voltage that occurs within mice brain cells during SE. In this study, voltage traces from these brain cells are being examined to identify predictors and indicators of SE events in the brain. Signal processing techniques, such as digital filtering, spectral analysis via spectrograms, and wavelet transforms, are being investigated to analyze these signals and compare them to brain signals exhibiting normal activity. Statistical methods surrounding the first through fourth moments, as well as clustering algorithms may also be used to classify and study the signals.

Authors: Joseph Henderson, Peter Seely, Benjamin Webb. Insitution: Brigham Young University. A classical result in spectral graph theory states that if a graph has an equitable partition then the eigenvalues of the associated divisor graph are a subset of the original graph’s eigenvalues. A natural question is whether it is possible to recover the remaining eigenvalues of the graph using this method of creating divisor graphs. We show that any weighted undirected graph can be decomposed into a number of subgraphs each with a nontrivial equitable partition whose collective spectra contain the remaining eigenvalues. We call these constructs Local Equitable Partitions (LEPs). We have developed an algorithm that leverages this result to compute LEPs and calculate the remaining eigenvalues of the original graph from them. This is potentially useful as many real-world data sets have a nontrivial equitable partition. To show the potential performance advantage of our algorithm over traditional methods, we present an ideal graph for which our algorithm performs optimally. Using a speed test, we demonstrate the improved temporal complexity of our method on the ideal graph.

Authors: Joseph Stahle. Mentors: Jeb Branin. Insitution: Southern Utah University. Asian theatre has been a significantly ever-present force for millenniums from countries such as China, Japan, Thailand, and more. However, as modernization and globalization have come to the forefront, we have seen a decline in traditional theatrical practices. This begs the question of why these shows have seen a decline, and it also brings up the potential need for more positive representation in contemporary performance studies. This project seeks to view the historical context of Asian theatre from Noh and Peking opera to modern shows like “Miss Saigon”, “The King and I”, and “The Mikado”. Additionally, it explores the lack of Asiatic representation in our modern theatrical society. Through traditional research methods, further understanding will be gained about Asian theatrical practices such as Noh, Kabuki, Peking opera, and shadow puppetry. Most importantly the use of critical approaches such as cultural studies, feminist criticism, and historical criticism, will reveal the lack of non-stereotypical representation of Asians within modern theatre. A key portion of the research will be conducted through personal interviews with Asian Studies and Asian Theatre professors. Leo Shingchi Yip, an associate professor of Japanese studies at the University of Gettysburg, spoke about the misrepresentation of Chinese people during medieval Japan. Yip states, “The portrayals of the Chinese characters featured in these [Noh] ‘Chinese plays’ do not necessarily remain faithful to their Chinese origins. Attuning to the audience’s tastes, expectations, and knowledge was a key factor in shaping [Noh] into an artistic institution, which in turn determined the making and staging of ‘Chinese plays’ in medieval Japan.” This quote discusses how ancient Japan would adapt to the audience’s wants and wishes within their Noh performances. In present times, we do the same thing on Broadway and in local productions to best please our target demographic. If this selective representation was present during medieval Japan, then what is the expected outcome of change over time?In most cases, if something is not termed as insensitive then it likely does not change. When looking at Broadway today, a vast majority of Asian interpretation falls under stereotypes and a minority of the cast’s proportions. Additionally, the presentation of women within the theatre is severely lacking; also, most modern Asiatic heroines fall under the depressive, suicidal, and manipulative Asian women stereotype. The key goal of this presentation is to reveal the inequality and lack of positive Asian depictions in contemporary theatrics. The audience will learn about Asian historical productions as previously mentioned. This presentation forces them to look at their own biases and face the lack of representation within their own local communities as well. The audience’s understanding will blossom and see the harmful portrayals of Asians and seek to create a new hopeful future for all who want to participate in theatre. This hope provides equality for all regardless of skin color, body size, and gender identity.