Stander Symposium Projects

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  Ultrasonic Nest Security System

  Srinivasa Prabhat Josyula

  The Ultrasonic Nest Security System works similar to the Google Nest. Nest, as we know it, is used to arm and disarm an alarm, but in this case, I will use a buzzer. This device is useful to prevent unauthorized entry or movement after a particular period of time and it also prevents thefts from happening. So, with the security system in place, people can be sure that their house is well protected. In this project, I will make use of Arduino UNO R3 as the embedded system. An Ultrasonic sensor will also be installed to detect if there is any movement of the object if it passes the sensor. I will also make use of a buzzer which is a digital component that is connected to digital outputs to generate a sound. In this case, the buzzer will produce a sound when it is triggered. This buzzer is connected to the Arduino UNO R3 and it beeps when an object crosses the threshold. The code will be written in Arduino IDE. I will implement this model on Node-Red and then send the data that is collected by the Ultrasonic Sensor which detects movements and alerts people to Adafruit.io. Adafruit.io is used to read and analyze data in the form of charts, bar graphs etc. With this information, I will be able to improve the security system in my house by installing more CCTVs and take more measures from any unfortunate situations to arise.

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  Un-bee-lievable Ways Location Impacts Pollinators: Identifying Key Geographical Features That Promote Insect Pollinator Activity at Existing Agricultural Sites in an Urban Environment.

  Samantha Urquidez

  Background/Questions/Methods:On a global level, urbanization is increasing exponentially. As urban centers expand, agricultural areas are broken up and oftentimes overlap with urban and peri-urban areas. With urban agriculture becoming more prevalent, there is concern regarding the impact on insect pollinator biodiversity and abundance in these urban environments. There is currently little research looking at the classification of agriculture within urban and peri-urban areas as well as the land use surrounding these areas and how these factors impact pollinator activity. In the area surrounding Dayton, Ohio, 15 agricultural sites will be classified based on surrounding population density and land use. Using ArcGIS, data from the National Land Cover Database 2019, and the most up-to-date Census block group data for the counties of Miami, Montgomery, and Greene. Agricultural sites will be classified into urban, peri-urban, and rural based on population density, and the land use surrounding each site will be calculated into percentages based on developed areas, pollinator habitat, and water. Biological data will also be collected at each of these sites to estimate pollinator activity in the form of timed observations, pan traps, and passive netting. Each of these classifications will help us understand how geographical features impact insect pollinators in an urban agricultural setting. Results: The results suggest land use rather than population density shows a larger impact on pollinator activity at agricultural sites. Areas, where the surrounding area provided stable resources such as habitat and water, showed higher pollinator abundance than areas surrounded by developed urban areas with limited resources. Having water in the surrounding area of the agricultural sites also resulted in higher pollinator activity than in areas without a stable water resource. It is important to know what geographical factors impact pollinator activity levels so they can be considered when suggesting sites for future urban agriculture endeavors.

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  Understanding Cryptocurrency Price via Contextual Information

  Rupal Dubey

  In today's economic market, the determination to purchase or trade cryptocurrency is an exciting challenge encountered by day traders. The prices of cryptocurrencies depend on technical progress, internal contest, market intimidation, financial problems, safety issues, political elements, etc. Therefore, their increased volatility guides the great possibility of high profit if intelligent inventing methods are taken. Unfortunately, compared to conventional financial projections like stock market predictions, cryptocurrencies are relatively challenging to predict because they lack indexes. In the past, the research community only considered cryptocurrencies for predicting crypto prices. A systematic publications review procedure is used to identify relevant peer-reviewed journal articles from the past twenty years, evaluate and categorize studies with identical strategies and contexts, and then resemble the reflections in each class to specify common findings, unique findings, constraints, and areas that need further investigation. This will provide artificial intelligence and finance researchers with guidance for future research into using ML techniques to predict stock market index importance and trends. In this work, I am taking other stocks, i.e., Gasoline, Oil, Gold, Silver, and all Big IT firms, along with the ten cryptocurrencies, into our consideration for predicting the crypto prices.I am building a model which will give insight to the investors and traders not only in the cryptocurrency market but in others contextual market also. I have introduced a few new methods in building the machine learning model for the forecasting of cryptocurrency. This model can incorporate other stocks, i.e., Gasoline, Oil, Gold, Silver, and all Big IT firms' stocks.

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  Understanding the Barrier to Integrating Empathy Education into Pre-Medical Curriculum

  Angela Galluzzo

  The overwhelming consensus in healthcare research over the past two decades supports that healthcare providers demonstrating empathy is an integral component of quality of care and health outcomes (Reiss). The benefits of empathy in patient-provider relationships range from stronger immune responses from patients to a lowered burden on the healthcare system to fewer malpractice lawsuits against providers (Reiss). Even with this research suggesting that providers should be empathetic in patient interactions, there are barriers to implementation. The barrier that my research will focus on is time–specifically how time constraints throughout professional schooling prevent a broad education that would teach providers how to best demonstrate empathy to patients. My work focuses on a literature review to understand why empathy should be studied as the marker for success in patient-provider relationships and how empathy competency is being taught and subsequently measured in clinical practice. I, then, investigate time as the inescapable barrier to empathy education. With this foundational knowledge, I propose a recommendation that focuses on integrating empathy education, focusing on empathy as an attainable, measurable skill, into the pre-medical curriculum at universities.

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  Unintentional Overdose Deaths in Ohio before and during the COVID-19 Pandemic

  Hailey Hogan, Tyler Yeary

  The COVID-19 pandemic has had a major impact on the availability of healthcare treatment across the United States. This impact on treatment can be seen in the dramatic rise in all-cause deaths during the COVID-19 pandemic (Faust, 2021). Lack of available treatment poses a major challenge for populations that have historically been vulnerable to opioid abuse, including the state of Ohio. Since 2000, Ohio has seen a statistically significant increasing trend in unintentional drug overdose deaths from 1999 to 2016 with different rates of change over time. (CDC, 2016). Many that have lived in Montgomery County for extended periods of time have known people that have fallen victim to the Opioid epidemic. This poster will take a look at how the statistics have changed since the COVID-19 Pandemic and what factors exacerbated the upward trend in unintentional opioid deaths. The purpose of this poster is to compile these statistics in order to help raise awareness and promote greater resource allocation towards unintentional opioid overdose prevention in Montgomery County and the state of Ohio as a whole. All data referenced in this poster is publicly available data from the Centers for Disease Control and Prevention (CDC) and the Ohio Department of Public Health (ODH).

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  University Libraries Dean's Showcase Exhibiting Excellence: A New Special Collection in University Archives

  Sara Wolf, Elena Bellisario

  Professor Suki Kwon from the Department of Art and Design, and students Sara Wolf and Elena Bellisario are engaged in an independent study of a new special collection held in University Archives. An artist’s book is a medium of artistic expression that uses the form or function of “book” as inspiration. It is the artistic initiative seen in the illustration, choice of materials, creation process, layout and design that makes it an art object. The University Libraries acquired the collection this summer and since then Suki has been working with Sara and Elena to create a catalog of the books and to plan for an exhibit that will be held in the Rose Gallery.

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  University Libraries Dean’s Showcase Exhibiting Excellence: Juggling for Mary: Vocation, Gifts, and Performing for Our Lady (Clown of God)

  Kendall Kiss, Mary Horvath, Brynne Kessler

  Students from several disciplines became involved with the Marian Library’s 2022 Christmas exhibit, Juggling for Mary: Vocation, Gifts, and Performing for Our Lady. Centered on a medieval story about a humble juggler in a monastery who struggles to find an appropriate Christmas gift to present to the Virgin Mary, the tale has been adapted and retold through operas, movies, and in contemporary times, many children’s stories. The students in Professor Mary-Kate Sableski and Jennifer Adams course, Foundations of Literacy through Literature, engaged in several experiential learning activities connected to the exhibit. They examined versions of the story from different time periods to explore how the language, morals, and illustrations of children’s literature has evolved. They performed read-alouds in the exhibit space for visiting school groups, selecting books to connect to diverse audiences. Finally, they created a StoryWalk, combining literacy and physical activity, with panels of Tomie dePaola’s Clown of God and activity prompts displayed across campus.

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  University Libraries Dean's Showcase Exhibiting Excellence: Juggling for Mary: Vocation, Gifts, and Performing for Our Lady (Simple Gifts)

  Logan Groff

  Students from several disciplines became involved with the Marian Library’s 2022 Christmas exhibit, Juggling for Mary: Vocation, Gifts, and Performing for Our Lady. Centered on a medieval story about a humble juggler in a monastery who struggles to find an appropriate Christmas gift to present to the Virgin Mary, the tale has been adapted and retold through operas, movies, and in contemporary times, many children’s stories. Inspired by the theme of gifts, Professor Jerome Yorke directed a new play, titled “Simple Gifts,” which was actually a pop-up performance in the Rose Gallery exhibit space for two nights in November. A cast and crew of UD students interacted with the audience in a performance that included everything from popcorn to puppetry.

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  University Libraries Dean's Showcase Exhibiting Excellence: Rituals of Healing: Body, Mind, Spirit

  Joseph Giagrande, Kevin Brun, Madelaine Sprinkle, Kaden Riggins

  This exhibit Rituals of Healing: Body, Mind, Spirit is a collaboration between assistant professor of English, Liz Hutter, and the University Libraries. This project is the result of over two years of planning that began after Professor Hutter brought her research writing seminar class to the Marian Library in the spring of 2020. Students explored primary source artifacts connected to aspects of health and healing right before students at UD were sent home due to the coronavirus pandemic.While practicing writing as a model of inquiry and discovery, students from Hutter’s first year writing seminar course in Fall 2022 curated this selection of artifacts and wrote narratives to explore what individuals or groups believe about religion, medical expertise, and healing of the body, mind and spirit.

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  University Students' Perceptions of Non-Native Speaking Teachers of English: A Step Towards Social Justice

  Alaa Bader

  English is the global language taught throughout the world by native speakers; however, it is also increasingly taught by multilingual teachers for whom English is not their first language. Problems can arise in TESOL classrooms when students question an international instructor’s qualifications; some evenly prefer native-speaking English teachers despite the knowledge and expertise of their international TESOL instructors. TESOL teachers also encounter other kinds of bias related to their race, ethnicity, or different religious practices. These forms of prejudice can be overtly expressed in the classroom but can also be evidenced in teaching evaluations. Such experiences can lead an instructor to question whether their pedagogies are out of alignment, or if the source of students' negative perceptions might create an overwhelming and unhealthy environment. Therefore, it is worth knowing whether the attitudes or behaviors students display in a non-native English teacher's class seem to be particularly inflected with potential connections with racism, and how teachers might reduce student bias of American English speakers and the “native” identity as a marker of professional excellence. The author collected data from her personal vignettes and Students Evaluation of Teachers (SET) of her two composition classes in the 2021 Fall semester. The data were examined using an autoethnographic methodology, and they demonstrate the existence of both explicit and implicit bias toward the teacher. The project concludes with some recommendations for ways to offer support and resources to TESOL faculty in higher education.

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  Unveil

  Kurtis Neiman

  This project shines a light on internal struggles that many of us deal with daily, yet are rarely acknowledged. On the surface people present the best version of themselves, for work, for family, for friends. Many of us have to find moments alone to process and understand our experiences. This project creates space for people and encourages normalizing sharing your struggles with others. The images are backlit with a pulsing light - acting as a metaphor that illustrates how struggles come and go from the forefront to the background unnoticeable but always lingering. The exhibition's dark lighting creates a vulnerable space for these struggles and invites viewers to reflect on their own experiences within the images. My goal for this project is to invite people to normalize talking about their struggles so everyone can get the help they deserve. NO ONE IS ALONE!

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  Urban Structures’ Effect on Seed-Eating Predators at Old River Park

  Grace Litavsky, Leeha Calaff Marrero, Ailish Luby

  Old River Park is a park located in Dayton, Ohio, an ecosystem supporting many types of life. Within the park, the company, National Cash Registry (NCR), used to have a recreational area for employees to use, but it is no longer managed and has naturally grown over with naturally colonizing plants and wildlife. Some of the man-made structures within the NCR park are still there but have been adopted into the natural woodland ecosystem around it. Because of this, we sought to understand how accustomed to the man-made structures the species living in this area are, and we decided to ask the question of whether seed-eating animals that live in this area have a preference for where they collect and/or eat their food. We hypothesized that seed predators would prefer and take more seeds from the natural areas compared to the man-made structures. We set out ten total bowls of 2,000 seeds, each in different locations, five at other man-made structures, and five in natural wooded areas without structures. We counted how many seeds were eaten from each bowl after two days. This process was repeated twice for a total of three replicates. This study is important because it gives insight into urban ecology and how the human footprint that is left on different environments can impact predation.

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  Use of Additive Manufacturing in Developing Advanced Composite Structures Fabricated by Resin Transfer Molding

  Khalid Aldhahri

  Resin transfer molding (RTM) is a manufacturing process used to produce high-quality composite parts that offer exceptional high strength-to-weight ratios, superb stiffness, and excellent resistance to corrosion and fatigue. These composites are typically comprised of carbon or glass fibers infused with a liquid thermosetting resin that hardens during a high temperature cure cycle. To produce RTM products, a matched metal mold is usually required. The mold cavity is shaped to the desired geometry of the finished composite part, and channels or gates allow resin to flow into it. In reference to cavity mold design, there are many challenges in terms of resin injection gates, vents, and resin flow directions, both in terms of filling time and the flow dynamics of the materials. These issues often require many costly iterations to perfect the cavity design for a given part. This study focuses on the use of AM in developing and fabricating plastic prototype molds that can be used to produce a limited number of finished composite parts, such as T-joints, canted T-joints, and I-beams. This approach allows for rapid and low-cost iteration of composite designs prior to investing in expensive finished metal tooling.

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  Use sensors, measure temperature and humidity, collect sensor data, and visualize and analyze data on IoT platforms

  Haolin Liu

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  Using a Drosophila melanogaster Model to Study the Effects of Nanoparticle Ingestion on Survival and Development

  Brandon Clark; other authors: Arushi Rai, Soubantika Palchoudahry, Madhuri Kango-Singh

  Nanoparticles are tiny (in the range of 5–100 nm) particles composed of inorganic (e.g., metals, oxide compounds, carbon-based nanotubes) and/or organic substances. They hold potential as small, biologically-compatible particles to which drugs and other chemicals could be attached. The eukaryotic model organism Drosophila melanogaster (aka the fruit fly) has a genome that is over 60% homologous to that of humans, with about 75% of human disease-causing genes having homologs in flies. With a brief generation time of only 12 days and high female fecundity (about 100 eggs per day), D. melanogaster is a convenient model to study development in the context of genetics and also effects of chemical exposure/toxicity on development. We are using this model organism to test nanoparticles and their biological effects on different stages of life and survival. For this study, gold (Au), iron oxide (Fe2O3), zinc oxide (ZnO), and poly-2-hydroxyethyl methacrylate (pHEMA) were selected for testing in Canton-S fruit flies. Nanoparticle concentrations of 50 mg, 100 mg, and 200 mg were fed to first instar larvae by layering the nano-materials on the fly food to test for any toxic effects or changes in survival following ingestion or prolonged exposure in comparison to control flies. At all concentrations, there was no significant effect on the survival of nanoparticle-fed larvae in comparison to the control (non-fed larvae). In the future, we will use a food dye to mark nanomaterials, and use immunohistochemistry and confocal imaging in the third instar larva stage to analyze the effects of nanoparticle exposure on several tissues, including the intestinal gut, salivary glands, and the fat body. We will also study whether larvae fed nanoparticles show developmental delays in comparison to control flies. Overall, this system provides a platform for testing toxicity in a simple whole-organism model system.

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  Using an Active Buzzer and an Ultrasonic Sensor to create a proximity alarm from live data as part of IoT

  John Sheehan

  The aim of this project is to design and develop a proximity alarm system using an ultrasonic sensor and an active buzzer, controlled by an Arduino Elegoo microcontroller. The proximity alarm system will be capable of detecting the distance between the sensor and an object in its vicinity and produce an alarm sound through the active buzzer when the object approaches a set distance limit. The project will involve the design of a simple circuit consisting of the sensor and buzzer, which will be interfaced with the Arduino Elegoo board. The code will be written in Arduino IDE and will include the necessary functions to read the sensor's data and generate an alarm sound through the buzzer. The project's overall goal is to demonstrate the application of an ultrasonic sensor and an active buzzer to create a proximity alarm system using Arduino technology, which can be used in various fields, such as security systems and robotics.

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  Using an Arduino to regulate fan speed in accordance with temperature

  Swecha Dorepally

  One of the biggest issues we currently have is energy waste. We frequently neglect to turn off the fan. This occurs as a result of carelessness, forgetting to turn off the fan, or being in a rush. Therefore, in this project, we consider how to solve this issue.The temperature sensor is employed in this endeavor to regulate the fan's speed. Therefore, the fan does not turn on when the room's temperature is below the minimum temperature specified in advance, and it turns on when the room's temperature is higher than the minimum temperature. This can be used for other electronic appliances, such as an air conditioner or heater, decreasing energy waste.

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  Using the Five-Choice Serial Reaction Time Test (5CSRTT) to Assess the Behavioral Impact of Chronic SERCA Activation in Mice

  Ben Klocke, Hayden Ott

  Calcium (Ca2+) is a critical ionic messenger implicated in a wide variety of cellular processes including gene transcription, muscle contraction, and neurotransmitter release. A Ca2+-handling player of particular interest is the sarco-endoplasmic reticulum Ca2+ ATPase (SERCA), an intracellular regulator of Ca2+ homeostasis that functions by sequestering Ca2+ into the endoplasmic reticulum (ER). Indeed, previous research has implicated dysfunction of SERCA regulation as a contributor to neurodegenerative diseases such as Alzheimer’s disease and neurodevelopmental disorders including Autism-spectrum disorder (ASD). In the current study, we sought to investigate how chronic pharmacological activation of SERCA may affect executive functioning in mice. Mice of both sexes were chronically administered the small allosteric SERCA activator CDN1163 and were then subjected to behavioral testing by use of the five-choice serial reaction time test (5CSRTT), a learned task that can be used to assess behaviors including attention and impulsivity. The results of this study contribute to our ongoing investigations into the behavioral and neurobiological mechanisms implicating SERCA in the underlying mechanisms of complex neurodegenerative and neurodevelopmental disorders.

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  Using Transgenic Mouse Models to Dissect a Novel Calcium Signaling Pathway in the Mouse Brain

  Ben Klocke

  Calcium (Ca2+) ions comprise a critical second messenger involved in a constellation of cellular processes, including cell proliferation and death, metabolism, and gene expression. Naturally, neuronal Ca2+ signaling is vital in processes such as long-term potentiation (LTP) and synaptic transmission, among others. A critical key component of the neuronal Ca2+ handling toolkit is the sarco/endoplasmic reticulum Ca2+ ATPase 2 (SERCA) pump. Further, dysfunction of SERCA2 has been implicated in many brain pathologies. Interestingly, our group has identified a regulator of SERCA2 being expressed in the mouse thalamus; global genetic ablation of this gene (GKO) in mice results in an ADHD-like behavioral phenotype. Our lab has recently developed a novel Cre-LoxP conditional knockout mouse model (cKO) to assess the effects of this Ca2+-handling player in the brain. Behavioral analysis of cKO mice showed that they exhibit locomotor hyperactivity and altered sleep architecture. Further, testing in the 5-choice serial reaction time task (5-CSRTT), a behavioral paradigm used to assess attentional capacity and impulsivity, showed that cKO mice exhibit impulsivity. Altogether, these findings strongly support a novel role for this Ca2+-handling player in the regulation of brain function and behavioral processes.

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  Using viral tracing methods to identify connectivity deficits between cerebellum and the thalamus in the Ts65Dn mouse model of Down Syndrome

  FNU Mir Abbas Raza

  I.Objective: Down Syndrome (DS) is a genetic disorder characterized by behavioral abnormalities in multiple brain regions. The cerebellum, a key area of the brain responsible for governing motor coordination and motor learning, has been implicated as being affected in many different Neurodevelopmental Disorders (NDDs), including DS. The cerebellum forms an extensive network of connections with other brain regions during development - also known as the ‘cerebellar connectome’. If there is dysfunction in the cerebellum during critical periods of circuit formation, it could result in altered development and dysfunction of extracerebellar targets such as the thalamus. Therefore, it is crucial to examine the development of the cerebellar connectome in the context of complex disorders like DS. However, the connections between the cerebellum and other brain regions have not been systematically mapped out across postnatal development. Most importantly, potential disruption in these connections has not been mapped out at the synaptic level in DS. Our goal is to determine the connectivity between the cerebellum and one of its major targets - the thalamus across postnatal development and how this connectivity is potentially disrupted in a mouse model of DS.II.Methods: To visualize connections between the cerebellum and the thalamus, we will use a precise and efficient Cre-dependent viral tracing strategy. This will enable us to specifically target the cells in the cerebellar nuclei that project to the thalamus. To accomplish this, Cre-expressing promoter specific Adeno Associated Viral vectors along with Cre-dependent viral vector carrying the Double-floxed inverse open reading frame (DIO) system and Green Fluorescent Protein (GFP) reporter gene will be injected into the cerebellar nuclei of the DS mouse model. This system will control the timing and specificity of gene expression, enabling the labeling of only the cells that have been infected with both viruses. The GFP reporter gene will allow for the visualization of the labeled cells and their projections. Histological analyses will be performed to visualize the GFP-labeled cells and their projections in thalamic nuclei. High-resolution images of the labeled cells and their projections will be obtained using confocal microscopy. The morphology of the labeled cells, including their dendritic and axonal arborization, as well as their connectivity patterns, will be analyzed using ImageJ and MATLAB.III.Significance: Although the prevalence of DS is on the rise, there has been little improvement in the development of innovative therapies to enhance behavioral outcomes for children with DS in recent times. One of the contributing factors to this lack of progress is the inadequate basic research on the neural connection deficits in the DS brain. The proposed study will help provide crucial data in understanding atypical brain development in DS, specifically, alterations in neural circuitry. Mapping connections between the cerebellum and the thalamus and studying the deficits in these connections during development in the Ts65Dn mouse brain will allow us to understand more deeply the underlying mechanism of dysfunction related to these regions and provide avenues to eventually develop targeted interventions towards treating deficits in children with DS.

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  Utilizing Deep Learning Methods and Semantic Segmentation to Detect and Map Glacial Lakes in the Central Himalayas

  Alison Hardie

  Glacial lakes provide insight into the melting rates of glaciers; thus, the ability to detect and map them opens possibilities for improved monitoring of the changing size of glacial lakes. An accurate automated method for glacial lake segmentation would provide the means to perform constant monitoring without the need for tedious manual labeling. This work utilizes a deep learning approach using semantic segmentation in MATLAB with convolutional neural networks (CNNs) to automatically detect and map glacial lakes. This work can be used to produce quick estimates of lake areas in order to monitor changes in their size. The network inputs include Landsat 8 spectral bands, ASTER Global Digital Elevation Model V003, which is processed into geomorphic features as an additional input into the network. Glacier outline data is sourced from the Global Land Ice Measurements from Space (GLIMS) database; this data is processed into a glacier distance band and fed into the network. Lake polygon data is sourced from the Annual 30m Dataset for glacial lakes in High Mountain Asia from 2008 to 2017. These labels were loaded and the boundaries were reduced to remove edge and mixed pixels from the training data. The CNN used is DeepLab v3+ with the Resnet 18 backbone. This presentation will include a detailed concept of deep-learning based automated lake mapping and performance analysis, including quantitative result metrics and network output lake boundaries.

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  Validation of effective removal of PFAS from glassware sampling train used for evaluation of thermal treatment of PFAS

  Elizabeth Riedel

  Per- and polyfluoroalkyl substances (PFAS) are anthropogenic chemicals that are extremely stable and highly toxic to the environment and human health. PFAS are used in a myriad of common products including nonstick cookware, water-resistant fabrics, personal care products, cosmetics, and aqueous film forming foam (AFFF). Because of their widespread use and resistance to degradation, PFAS have infiltrated the environment, including drinking water sources. To combat the spread of PFAS, various methods for treatment and removal of PFAS are being researched. A promising solution that has been identified for PFAS removal is thermal treatment, where degradation of PFAS occurs after exposure to exceedingly high temperatures. However, chemical characteristics of certain PFAS create the potential for them to adhere to equipment used during experimentation. For proper assessment of PFAS removal, it is essential to confirm that there is no carry over from sampling or contamination on the experimental equipment. This paper evaluates two techniques for their potential to effectively eliminate PFAS carry over on glassware used in a sampling train for thermal treatment. The first is a procedure used to clean glassware in the field when sampling for PFAS. The second is a modified version of the glassware cleaning procedure recommended in the OTM 45 protocol from EPA for PFAS sampling. In this experiment, glass impingers contaminated with solutions containing two of the most prevalent PFAS, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), were cleaned following the two separate procedures. Results from an analytical laboratory following EPA Method 537 showed that the second cleaning procedure was approximately five times more effective at removing PFOA and about two times more effective than the first cleaning procedure at the removal of PFOS from the impingers. Therefore, the second cleaning procedure is recommended for glassware used in PFAS experimentation.

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  Vapor Diffusion Crystallography of the Polymerase Acidic Protein

  Juliano Aquilino

  Current treatments of an Influenza infection target frequently mutating surface proteins. This causes increased variability in the effectiveness of modern treatment methods, as a single mutation in the protein could cause the antiviral to be ineffective. A component of the RNA-dependent-RNA-polymerase (RdRp) of the Influenza A virus, the Polymerase Acidic (PA) protein, is a promising antiviral target for a new generation of Influenza treatments because of its highly conserved nature. PA has been shown to have a similar structure and sequence across known strains of Influenza. Drug design research utilizes crystal structures to synthetically improve viral inhibitors through in silico analysis that can prevent the binding of PA to an additional protein, Polymerase Basic 1 (PB1). Years of research to make a soluble and pure PA sample that is binding-pocket solvent-exposed has led to the culmination of crystalizing the protein construct as the final step to capturing an image using X-ray crystallography. Various techniques involving a pure PA sample and many different thermodynamic conditions make forming a structure difficult and time-consuming. A large “shotgun” approach over a broad spectrum of reagents, concentration, pH, buffers, and the occasional additive help to narrow in on the highly specific mother liquor necessary to grow PA crystals. The presentation will discuss the current methodologies and chemical types and how they played a role in the vapor diffusion of PA Crystallography.

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  Vehicle Counting and Classification from Traffic Videos

  Jaswant Prabhakaran

  Using a trained neural network, counted and classified vehicles in different Vietnamese traffic conditions (day, night, rain, and flash floods). The algorithm automatically tracks and counts the number of vehicles passing through a specific area while also categorizing them as cars, motorcycles, trucks, and buses. This provides an accurate representation of traffic patterns and flow for the specified region in Vietnam, under specific weather conditions and time of day. Another group then integrated this information into a traffic simulation system which allowed for improved traffic management strategies to be developed based on the accurate traffic flow data obtained from the simulation.

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  Virtual Mirror Illusion

  Lucy Kuempel

  Awareness of body and limb location typically comes from neural pathways within the skin, muscles, and joints as well as visual information from peripheral vision. This study employs a virtual version of the mirror illusion to examine the importance of visual and body-based information in spatial body awareness. In the mirror illusion, the seen location of the hand differs from the felt location of the hand. With this conflicting information, the perceived location of the hand is biased toward the visually-specified limb information. The current study extends this phenomenon into virtual reality to determine whether visual information in a virtual environment influences perceived body part location. Each participant is seated at a table, outfitted with a virtual reality (VR) helmet in which they view a virtual tabletop and a virtual depiction of their right hand. The participant’s actual right hand is positioned at a location that is either aligned or misaligned with the virtual right hand. After repeatedly flexing their right index finger while viewing a corresponding movement in VR, participants are asked to point with the left hand to the perceived location of their actual right hand. Errors in pointing to the hand location are compared in instances in which the virtual hand is aligned versus misaligned with the real hand. It is predicted that when the real and virtual hands are misaligned, participants will point closer to the seen virtual hand location than to the actual hand location. This suggests that body part awareness is dominated by visual information and suggests a sense of ownership of the virtual limb.