Stander Symposium Projects

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  A new BODIPY photosensitizer capable of excitation within the near-infrared (NIR) region of the electromagnetic spectrum

  Emily Hardie

  Photodynamic therapy is a technique that uses and activates photosensitizing agents through the absorption of light of a certain wavelength in order to produce reactive oxygen species (ROS). When present in a cellular environment, ROS can induce cell damage and oxidative stress leading to cell death. This study introduces a NIR activated BODIPY dye capable of generating both superoxide and singlet oxygen. The synthetic route to this dye along with characterization and evaluation through 1H NMR, electronic absorption spectroscopy, and fluorescence spectroscopy is presented. Using singlet oxygen and superoxide radical quenchers, this dye shows high quantum yields for the production of ROS.

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  An Examination of the Prospective Links between Depressive Symptoms and Delinquency in Late Adolescence

  Jad Abuhilal, Grace Appelbaum, Kaitlyn Lancia, Quinn Willerton

  Depressive symptoms and delinquency are strongly correlated in adolescence, such that higher levels of one is associated with higher levels of the other. However, the direction of the relationship between depressive symptoms and delinquency is not fully understood. The "acting out" hypothesis predicts that delinquency increases risk for future depression, whereas the "social failure" hypothesis predicts that depression increases risk for future delinquency. It is also possible that each contributes to risk for the other, or that their correlation is due to common risk factors. The current study tests these hypotheses by examining the longitudinal associations between depressive symptoms and delinquency from ages 14 to 17 in a large and socioeconomically diverse sample of adolescents.

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  An Experiential Learning Perspective on Student Employment Training

  Justin Long

  At the University of Dayton, student employment provides valuable experiential learning opportunities for students. Student employment training programs often require significant resources and attention to detail. Despite this investment by supervisors, training programs can fall short of their intended purpose by failing to engage participants. This study examines the effectiveness and impact of student employment training programs by conducting a qualitative case study of eight recently graduated students who worked for the University of Dayton’s Campus Recreation Department. The researcher interviewed each participant, asking questions regarding their training experience, learning preferences, and the potential impact the employment experience has on their life post-graduation. The participants revealed a desire for “hands-on” training programs where they could interact with peers, engage in team-building exercises, and ask questions as they completed job responsibilities. The findings suggest that supervisors tasked with developing student employment training programs may benefit from making training interactive and aligned with the preferences of Generation Z.

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  An Extreme Injustice: Evaluating the American Judicial Response to Incidents of Domestic Terrorism

  Kathryn McAuliffe

  Response methods to incidents of domestic terrorism vary greatly but all maintain one common thread: failure, because there is currently no federal charge for domestic terrorism which has led to significant breakdowns in the legal response to acts of domestic terrorism. This also relates to accountability and legitimacy in the American judicial and criminal justice systems. To better understand the current situation, a qualitative, descriptive case study will be used to evaluate specific moments in American politics that are considered domestic terrorism. Through analysis of archival, court and media documents, an assessment of these cases will yield deeper insight into the workings of the American judicial system and the way the nation responds to terrorism. Responses, currently, fail to hold terrorists accountable and do not grant legitimacy to what some consider the greatest threat to America––hate. Policy recommendations and changes should be made to ensure accountability and legitimacy are granted to these threats. Only when acts of domestic terrorism are regarded at the same level as threats of international terrorism will we have granted the proper legitimacy to domestic terrorism. Increased recognition of this danger and possible outcomes will help steer us to a more secure nation.

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  Annual Department of Music Honors Recital Competition

  Brendan Ash, Cara Clark, Duncan Costello, Emily Debevec, Abigail Deeter, Dominic Delligatti, Penelope Fisher, Claire Ginley, Victoria Kozma, Katarina Lagodzinski, Gabriel Lusk, Maggie Lustig, Samantha McIntyre, Dylan Reynolds, Luke de Villiers

  Music students selected by the Department of Music faculty perform for a panel of community-based professional musicians who will choose six finalists to perform on the Honors Recital at the end of the semester. Performances will include a variety of vocal and instrumental music.

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  A Non-volatile Ferro-photonic Memory Device

  Asela Perera

  Commercially existing photonic integrated memory device architectures implemented with MRRs are volatile, implying that once the bias is removed, the stored memory is erased. While the functionality is excellent for optical data switching and optical data modulation applications, the volatility is unsuitable for optical memory applications where the bias needs to be ON at all times to store the data in the MRR implying a significant static power consumption. Such a feature is unsuitable for photonic computing applications in neural networks where training weights need to be stored for a long time without any active power consumption. An energy-efficient non-volatile memory is one of the missing photonic building blocks for optical computing. Micro ring resonators (MRRs) are integral components of silicon photonic integrated circuits (PICs) that can change amplitude and phase of light. The resonance wavelength of MRRs can be shifted by changing the refractive index of MRR material. A hybrid ferroelectric material needs to be integrated with silicon to store the shift and hence the data, when the actuating voltage is removed. Recently, foundry compatible hafnium-zirconium-oxide (Hf0.5Zr0.5O2, HZO) has been demonstrated as a suitable ferroelectric in memristor applications in electronics. In this work, we present an initial prototype of a non-volatile high-speed ferroelectric optical memory device with HZO integrated on MRRs.

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  A Numerical Study of a Differential Equations Model of HIV

  Thomas Erdman

  Human immunodeficiency virus infection better known as HIV has spread through communities for decades. As it moves through a person's blood it effectively infects more and more cells and can lead to the development of Acquired Immune Deficiency Syndrome (AIDS). By using differential equations that model the per capita death rate of uninfected cells, infected cells, and virus particles, along with techniques such as Runge-Kutta we can predict the rate at which healthy cells will become infected.

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  A Numerical Study of an Influenza Epidemic Diffusion Model using MATLAB

  Erin Millhouse, Payton Reaver

  The aim of this study is to replicate the results from a publication “Numerical Study of an Influenza Epidemic Model with Diffusion”, 2010. The strategy used to approximate the population was the SEIR (Susceptibility, Exposure, Infected, Recovered) model. This specific model is comprised of four partial differential equations, each with a linear diffusion term and non-linear reaction term. Using Operator Splitting, the authors were able to simulate the solutions of the model. The overarching goal is to replicate the numerical results of the paper.

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  Applying the Social Work Framework to Advocate for Change on Ohio Senate Bill 1

  Fiona Ackroyd, Morgan DiRocco, Madelyn Hales, Abiageal Newell

  In this project prepared for SWK 310, we share our reflections and insights gained from our experience participating in the Social Work Advocacy Day in Columbus, Ohio in March 2025. During our trip we attended advocacy training and planning sessions and met with state legislators and/or their staff. This presentation details our experiences at Advocacy Day, outlines an area of advocacy, and describes how we advocated for change through the lens of the Social Work framework.

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  Artificial Intelligence Applications in Real Estate

  Amira Yousif

  The real estate industry relies heavily on accurately predicting the price of a house based on numerous factors such as size, location, amenities, and season. In this study, we explore the use of machine learning techniques for predicting house prices by considering both visual cues and estate attributes. We collected a dataset (REPD-3000) of 3000 houses across 74 cities in the USA and annotated 14 estate attributes and five visual images for each house's exterior, interior-living room, kitchen, bedroom, and bathroom. We extracted features from the input images using convolutional neural network (CNN) and fed them along with the estate attributes into a multi-kernel deep learning regression model to predict the house price. Our model outperformed baseline models in extensive experiments, achieving the best result with a mean absolute error (MAE) of 16.60. We compared our model with a multi-kernel support vector regression and analyzed the impact of incorporating individual feature sets. In future, we plan to address class imbalance by having the same number of houses in each class and explore feature engineering for improving the model's performance.

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  Artists and Educators: The Relationship of Research Within Practice.

  Ellana Davis, Sophia Eyerman, Gabriela Gomez, Jayonna Johnson, Kaylee Peters

  This presentation will highlight and share five individual qualitative research studies conducted by senior students pursuing BFA degrees in the Department of Art & Design. These presentations include "Encompassing the Reciprocal Relationship of Being an Artist and Art Educator"; "An Investigation into the Relationship between Christian life and Mental Health"; "Diversity in the Art Classroom and the Impact on Student Motivation and Participation"; "A Personal Exploration of Education in the Art Museum"; and Reflections on Student Teaching: What PreService Education Couldn't Have Prepared Me For".

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  Assessing how speakers with non-American accents experience and manage communication accent stigma in health care situations in the United States.

  Gift Olalusi

  The study aims to explore the challenges individuals with non-native American accents face in healthcare settings, examining different experiences based on how they manage communication stigma, and offering solutions to eliminate stigma, stereotypes, and biases. The study employed a qualitative approach, where interviews of individuals with non-native American accents in the United States were coded and discussed thematically. Results from the study seeks to improve healthcare outcomes by ensuring non-native English speakers and people with accents can access care equally and without fear or stigma. The study is an on-going research thesis, and the findings aim to raise awareness among healthcare providers about implicit biases, fostering better patient-provider communication and greater patient satisfaction and inform better healthcare policies in the United States.

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  Assessing the behavioral effects of pharmacological SERCA activation in the dizolpine-induced mouse model of psychosis

  Erin Flaherty, Hayden Ott

  Intracellular calcium (Ca2+) homeostasis plays a critical role in a variety of neural processes including neurotransmission, development, and apoptosis. The sarco-endoplasmic reticulum Ca2+ ATPase (SERCA) is a Ca2+-handling regulator that sequesters cytosolic Ca2+ into the neuron's smooth endoplasmic reticulum. Notably, disruption of mechanisms that are responsible for maintaining Ca2+ homeostasis has been implicated in the pathophysiology of neuropsychiatric disorders such as Schizophrenia. In the context of the current study, our lab sought to investigate the effects of chronic pharmacological SERCA activation via administration of CDN1163, an allosteric activator of SERCA, on the dizocilpine (MK801)-induced mouse model of psychosis. Male and female mice of the C57BL/6J strain were chronically treated with daily intraperitoneal injections of CDN1163 and their locomotor activity was assessed upon acute dizocilpine administration. The results of this study provide us with a better understanding of SERCA's role in behavior as well as its putative implication in the neurobiology of schizophrenia.

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  Assessing wildlife diversity in Dayton’s protected areas surrounded by human-modified landscapes

  Trevor Martin

  The region surrounding Dayton, Ohio, is a matrix of human development and agricultural areas, with relatively small areas of natural land in between. Montgomery County’s park system, Five Rivers MetroParks, protects and restores thousands of acres of land, much of which is used for recreation. These patches of forest and undeveloped areas provide essential habitat to local mammal wildlife, such as white-tailed deer (Odocoileus virginianus), northern raccoon (Procyon lotor), Virginia opossum (Didelphis virginiana), eastern cottontail (Sylvilagus floridanus), squirrels (eastern grey squirrel, fox squirrel, red squirrel, Sciurus sp. ), bobcats (Lynx rufus), and coyotes (Canis latrans). However, human-caused habitat fragmentation poses significant challenges for many species of wildlife. Behavioral changes in response to human activity can inevitably lead to shifts in the composition of species in a given area, thus altering the dynamics of the ecosystem. This study aims to quantify species richness and diversity in three Five Rivers MetroParks properties to analyze how the overall composition of mammalian wildlife is affected by varying degrees of human land use and presence. The results will provide insight into potential patterns of species diversity that could apply to other natural areas within the park system. Better understanding of how wildlife communities within these parks respond to human activities will help inform land management decisions that allow park officials and city planners to strike a balance between creating multi-functional landscapes and also preserving biodiversity.

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  Assessment of Similarity Between Two Methods of Calculating Reactive Strength Index for Different Jump Types

  Noah Clemens, Natalie Osiecki, Louisa Piotrkowski

  Reactive Strength Index (RSI) is a measurement of how much force an individual can generate when under a high downward force. It is a tool to predict explosiveness in exercise performance and the amount of stress on the lower extremity joints when performing jumps. RSI is a ratio of jump height and contact time. This study focuses on two methods of calculating the jump height needed to find RSI from force plate data. It is unclear whether these two methods produce similar results. Objective: The purpose of this study was to compare the similarity in the calculated RSI values between two different jump-height calculation methods. Methods: Nine college-aged participants were recruited to perform a series of countermovement and drop jumps. Participants completed the jumps on VALD portable force plates. The first method used the applied force and contact time to estimate takeoff velocity, from which a theoretical jump height was determined. The second method used the total flight time to estimate the jump height, under the assumption that the jumper would reach their maximum height at exactly half of their time in air. A Bland-Altman (BA) plot was used to graphically evaluate similarity in RSI values between the two calculation methods for all three jump types. Results: Between the two methods, the mean difference was 0.248. The limits of agreement (LOA) of the BA plot showed an upper limit of 0.625 and a lower limit of 0.128. There were multiple data points outside of the LOA as well. Conclusion: The presence of a large mean-difference, large LOA, and multiple data points outside of the LOA indicate that the two methods for calculating jump height from force plate data were not similar. When separated by type of jump, the countermovement jumps showed acceptable similarity between the two methods.

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  A Tour of Real and Complex Linear Spaces

  William Hach

  This presentation explores the distinctions and connections between real and complex linear spaces, with a focus on their formal structures and potential applications.

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  Attitudes Toward Service Dogs In-Training

  Lindsey Person

  The partnership between service dogs and people with disabilities provides important social, psychological, and physical benefits. The early training of service dogs involves learning the basic commands, such as sit and stay, and exposing the dogs to many different people and situations. Some universities partner with service dog training organizations to perform the early training. Such training involves bringing the service dogs in-training into classrooms. Having dogs that are not fully trained in classrooms could be disruptive for reasons such as allergies, religious beliefs, fear, and distraction. Having dogs in a classroom can also improve the mood of and reduce the stress of students and instructors. This study will use a diverse and inclusive sample to investigate the instructor’s, students’, and dog handler’s attitudes toward having the service dog in-training in the classroom. Perceived stressors for the service dogs in-training will be measured. Best practices for mitigating any issues that are found will be created.

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  Automated and data-driven discovery of behavioral signatures in preclinical models of developmental disorders

  Henry Salisbury

  The primary mode of identifying developmental disorders in children involves behavioral analysis. However, behavioral datasets are mainly quantified and analyzed using manual methods that are time-consuming and cumbersome. Automated and data-driven quantification and analysis of neurobehavioral datasets is therefore a pressing need. By leveraging advanced computer vision algorithms, we aim to analyze and interpret the behaviors of mouse models of developmental disorders in specific experimental tasks. By harnessing cutting-edge computer vision algorithms such as automatic detection of body-parts and tracking using DeepLabCut, combined with data-driven identification of “behavioral signatures” using the Behavior Segmentation of Open field in DeepLabCut (B-SOiD) pipeline, we will train a system to objectively perform data analysis on data gathered from videos of mice performing diverse experimental tasks including the three-chamber social test and the Erasmus Ladder test for motor learning. Through this, we seek to find patterns between the neurobiological and behavioral data from these mouse models, to learn how developmental disorders including Down syndrome and premature brain injury impact locomotor learning and neurophysiology. Our methods provide a platform to identify potential treatment options for humans with these developmental disorders.

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  Automated System For Photonic Integrated Circuit Measurement

  Daniel Donnelly

  In recent years, with the advent of mature miniature semiconductor fabrication processes, the photonic integrated circuit (PIC) has emerged as a potential solution for the increased power consumption and bandwidth of conventional electronic computing technologies. As low-energy, optical devices, PICs serve to bring the solutions and advantages of optical technologies down to the form-factor of typical electronic microchips, including applications in telecommunications, high-speed computing, sensing, and quantum computing. However, despite the existing technologies for semiconductor fabrication, PICs, unlike their electronic counterparts, are exceedingly difficult to package and test, with each part of the process individually taking up roughly 30% of the manufacturing cost. Thus, in recent years, much focus has been placed on reducing these costs through increased automation of the various testing processes, particularly the fiber alignment process, in which, for a given device, the input and output fibers are moved to the optimal position for maximum throughput. The following paper describes the construction and implementation of an automated PIC measurement system in the Silicon Photonics Lab at the University of Dayton, including implementations of automated fiber alignment routines. The system exceeds state of the art output metrics in terms of measurement throughput and includes components for both optical and electric device measurement. The paper also describes the system’s use in measuring an innovative miniature on-chip Fourier Transform spectrometer presented at the SPIE Defense+Commercial Sensing 2023 conference.

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  Autonomous Vision System for Hazardous Object Detection in Construction Sites

  Anurag Mallik

  Construction sites pose significant risks to workers due to the presence of various hazardous objects. These items can be sharp or blunt, or even cause electrocution. With the common denominator being that all can lead to serious accidents. During construction, all personnel on site must take proper precautions when handling hazardous objects. While larger items are easily visible, smaller tools like nails, hammers, and drill machines often go unnoticed. If these objects are left unattended in active areas, they can lead to life-threatening incidents in construction zones. In this research work, a computer vision algorithm has been proposed to identify construction tools in a construction zone as part of a larger pipeline for construction hazard detection. Specifically, this work focuses on images of construction zones which have been captured from various angles. The Segment Anything Model (SAM) is used to segment these images allowing them to analyze regions of interest. Regions selected for further processing are done by calculating bounding boxes which are based on the segmented areas. Through experimentation, an optimal size of the bounding boxes to reduce the number of boxes to processes showed bounding boxes that capture an area of 3% to 8% of the total image size are typically relevant to detect a hazardous object in a construction scenario. These resulting bounding box areas in the image are fed to a feature extractor, DINOv2 that returns the object feature matrix to feed into a fully connected three-layer neural network classifier. The classifier identifies an object feature set belonging to one of the twenty predefined hazardous objects if the score of the highest probability output node of the classifier is beyond a predefined threshold value.

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  Bachelor of Fine Arts Fine Art Senior Thesis Presentations

  Gretel Helm, Jacqueline Patton, Sarah Ryan, Kyleigh Streeter

  Senior Bachelor of Fine Arts student presentations

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  Benchmarking Sustainable Procurement for Higher Education: Procurement for the Common Good - Spring 2025 Update

  Angelo Catapano

  I will be presenting my current research regarding the vendors of the University of Dayton. The goal of my work is to understand these vendors from a sustainable perspective, both for the environment and social considerations, and see how their goals align with those of UD. Topics of discussion will include data collection methods, interpretation of such data, and a fundamental understanding of UD goals for vendors.

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  Benefits of an Intervention to Enhance Self-Efficacy for Diabetes Care in Homeless Shelter Residents

  Maggie Hofner, Samantha Jordan, Ella Lamb, Emma Petraglia, Mia Venanzi

  Despite a great need for healthcare, unhoused individuals encounter significant barriers to utilizing public healthcare. Given the inequities in access to healthcare, accompanied by disabilities and health risks associated with homelessness, self-efficacy for self-care is particularly critical. Because of barriers associated with the system (e.g. lack of healthcare insurance), homelessness (e.g., lack of transportation), and the healthcare system (e.g., stigmatizing attitudes) encountered by unhoused people in attempts to access public healthcare, it is necessary to provide (and evaluate) self-care interventions on site (e.g., in homeless shelters). The prevention/management of diabetes is one of many problems among unhoused individuals. Driven by self-efficacy theory and the health psychology knowledge based on diabetes risks, this study examines the benefits of an intervention designed to enhance self-efficacy for the prevention/management of diabetes among residents at the St. Vincent de Paul Gateway Shelter for Men (Dayton, Ohio). The intervention is implemented by supervised undergraduate students within a long-standing participatory community action research project for homeless shelters. The primary purpose of the research is to examine the hypothesis that the intervention will lead to improvements in self-efficacy for prevention/management of diabetes. It is also hypothesized that the intervention will be (a) approximately equal in effectiveness for residents with disabilities versus those without disabilities and (b) approximately equal in effectiveness for residents with diabetes versus those with pre-diabetes. The Self-Efficacy for Diabetes Management Scale, which includes Likert-like items and prompts to collect qualitative data, is used to assess pre- to post-intervention changes in self-efficacy. The study uses a multifactorial design with two between-subject factors (i.e., disability versus non-disability status and diabetes versus pre-diabetes status) and one within-subjects factor (pre- versus post-intervention). A secondary purpose is to examine the psychometric properties of the new measure (Self-Efficacy for Diabetes Management Scale).

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  Benefits of Collaborative Learning in High School Math Classes

  Matthew Carpenter

  Group work, collaboration, and cooperation in high school math classes promote student learning. In the studies shared, findings include strong benefits of group work in high school math classes and how teachers can include it in their teaching. Benefits include peer-to-peer learning, self-evaluation skills, and increased conversation in class.

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  Benzalkonium chloride enhances Listeria monocytogenes biofilm formation under various conditions

  Evelyn Joynt

  Listeria monocytogenes is a bacterial foodborne pathogen that can cause severe invasive infections with high mortality rates. To protect vulnerable populations from L. monocytogenes infections, there is a stringent cleaning, disinfecting, and surveillance process in place in the food facilities. However, outbreaks as well as recalls of potentially contaminated food products continue to occur regularly. L. monocytogenes can persist in the environment because of its ability to survive various harsh conditions, including low temperatures, and to form biofilms on food-contact surfaces. To eliminate L. monocytogenes, benzalkonium chloride (BC) is one of the major disinfectants used in the food industry. However, multiple studies have shown mechanisms of L. monocytogenes developing resistance to BC, potentiating the future need for higher concentrations of BC. In this study, we investigated the effects of higher BC concentrations on L. monocytogenes biofilm formation. Using the standard crystal violet staining method, we observed that at concentrations (1% or 5% [wt/vol]) that inhibit planktonic growth, biofilm formation was significantly enhanced, compared to no BC controls, regardless of oxygen availability, surface materials, and temperatures. These results suggest that higher concentrations of BC will not be an effective strategy to remove L. monocytogenes biomass from surfaces and could potentially create additional adhesion sites for other biofilm-forming bacteria in the same environment.