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  Innovative Consulting & Mediation

  Mason D. Kleinhenz, Ryan D. Lederle, Charles A. Schoen

  Private Mediation Consultant...Develop Online Systems

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  Inspirational Women Stories in STEM

  Alekhya Dontham, Lauren Drankoff, Noel Mathew Lnu, Melissa K. McCabe, Claudia Swinson

  This session will involve a set of posters focused on inspirational women in STEM. The presentation will be about a combination of women that inspired us in different fields of STEM by breaking all stereotypes and gender barriers. The five women we are going to present about will be:

  • Kalpana Chawla
  • Rosalind Franklin
  • Mae Jemison
  • Cynthia Breazeal
  • Hedy Lamarr

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  Investigating the Effects of a p53 Mutation on Glioma Progression and Therapy Resistance in Drosophila

  Kaitlyn M. Alleman

  Gliomas, which are brain tumors that arise from glial cells, are some of the most aggressive and lethal types of tumors. These brain tumors are difficult to treat because not enough information regarding the mutations present in these tumors exists. This project studies effects of a p53 mutation on Drosophila glioma progression and then will test to see if this results in resistance to current chemotherapy. Drosophila are used as model organisms to mimic these processes. The current genetic crosses that have been created will be studied, and an effective p53 knockdown will be made. In essence, this will effectively mimic a human brain tumor so the treatments tested and the data collected from this model can be applied to the current understanding of human gliomas. In addition to studying just the p53 mutation, PI3K and oncogenic Ras signaling will be coactivated. This will lead to an even more accurate glioma model because multiple mutations, such as the ones added are present in human tumors as well. These genetic crosses will be treated with Tyrosine Kinase Inhibitors, which are currently used to treat brain cancer patients in order to find out whether or not this mutation plays a role in resistance to current therapy. The main goal of this endeavor is to investigate the numerous defects occurring at the cellular and biochemical level in gliomas, which will give insight into why these types of tumors are so difficult to treat. Data gathered from this project will lead to further inquiry into the role of p53 mutations in gliomas and hopefully, to better outcomes for those affected by this type of cancer. Here, we present the data gathered from this project thus far.

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  Is it the ‘Most Magical Place on Earth’ for Interns? A Cost-Benefit Analysis of the Disney College Program and its Emotional Labor

  Jacqueline R. Russo

  Any internship for college students demands work and it may appear straightforward to gauge this in terms of energy, time, and the value of the costs associated with the job. How do we understand the full cost, whether physical and emotional, of certain internships, especially at a renowned location such as Walt Disney World? The Disney College Program (DCP) is a semester-long internship for college students and expects its interns to be “on stage” and perform tasks for the entertainment value of guests. To understand the physical and emotional impacts of the DCP, this study utilizes a cost-benefit analysis and applies the concepts of emotional labor, emotional management, and emotional regulation to this internship experience. Specifically, this research asks, “What kinds of emotional labor and regulation do DCP interns give to their job and do they interpret this experience to be worth the costs?” Through snowball sampling, participants were accessed via Facebook groups and includes those who participated in the DCP at Walt Disney World Resort from the years 2012-2019. Exploring the intersections of costs, benefits, and emotional labor, the results of this research show that there are many demands and pressures DCP interns experience. With many lifestyle, personal, academic, and career-oriented adjustments to make to participate in the DCP, interns often experienced stress, emotional dissonance, burnout, alienation, and little room for emotional flexibility. Interns can also gain customer service skills, develop relationships, and a sense of accomplishment from their involvement in the DCP. From these findings, it can be concluded that interns often utilize deep acting in order to reduce the cost of emotional labor applied to tasks, remaining “on stage” during work hours, and managing personal emotions.

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  Is Mental Health Declining? University of Dayton Students in a Pandemic

  Coleen Marie Coffey

  This research asks how the COVID-19 pandemic has affected the mental health of college students at the University of Dayton. Mental health on college campuses can be strenuous as students deal with the anxieties of living independently, classwork, as well as finding their career path. With a combination of these existing stressors and now a pandemic, students at the University of Dayton endure social isolation and a lack of in-person classes. The purpose of this study is to identify the reasons, if any, that have caused a decline in students’ mental health. The study was conducted through an online survey which was sent out via email and messages to students and professors who were asked to forward it to their students. Utilizing the organizations and clubs that I am in I received fifty-eight responses. The survey included Likert scale and open ended questions. Major findings were that many students feel as though their mental health has been ignored when it comes to their schoolwork, and they feel that their mental health has gotten worse since the pandemic. Numerous students explain that they do their best to be around their friends and other people as well as focusing on physical exercise to help with their mental health. Despite a smaller response from first-year students, the study was able to determine that 68% of students are moderately concerned about caring for their mental health. I conclude that there needs to be an increase of access and availability for mental health support from the university so that students can seek the help that they need.

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  Isolating Antibiotic Producing Pseudomonas From Soil

  Caroline Rose Wattles

  The Tiny Earth Network works to address the decreasing amount of effective antibiotics by testing soil bacteria for antibiotic production. Antibiotics are used in medicine to treat bacterial infections by killing or slowing the growth of bacteria. A threat to the common treatment is antibiotic resistance which has resulted in a health crisis. To combat this, new antibiotics need to be discovered and through the Tiny Earth Initiative bacteria from soil samples are being used as a source. The isolated soil bacteria was tested for antibiotic production against clinical pathogens such as E. coli and S. epidermidis. Laboratory methods such as gram staining, biochemical testing, and 16s rRNA gene sequencing were used to identify the isolated soil bacteria. An organic extract was also prepared from the isolate using ethyl acetate for extraction and methanol as a solvent to confirm the antimicrobial activity and to check for potential toxicity. The methanol solution of the extract was plated onto a water agar plate. Chia seeds were sprinkled onto the plate and left to grow. Chia seed growth indicated the antibiotic extract was not toxic to Eukaryotic organisms while no growth indicated toxicity. Discovery of antibiotic producing bacteria will help the ongoing battle against antibiotic resistance and its effect on bacterial infection treatment options.

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  Isolation and Characterization of Soil Bacteria Having Antibacterial Activity

  Brenna Marie Reilly

  Antibiotic resistance in bacteria against a single or multiple drugs is a burning issue worldwide. According to the 2019 Antibiotic/Antimicrobial Resistance (AR) threats report of the Centers for Disease Control and Prevention (CDC), more than 2.8 million antibiotic-resistance infections occur in the U.S. each year, and more than 35,000 people die as a result. Therefore, the current study was carried out to isolate and characterize soil bacteria having a new compound with antibacterial activity. Soil samples were collected from GPS coordinates of 39.73594418442152, -81.17545763942566 at a depth of 7.62cm. The weather was 16 Fahrenheit, even though the soil was hard, the deeper I dug the soil became moist and soil was collected and placed in a sterile test tube. The appearance of the soil was a dark brown. Individual bacteria from soil were separated and isolated using serial dilution techniques. Bacterial media such as Reasoners 2A Agar and Todd Hewitt were used for bacterial isolation. Six different bacterial isolates based on colony morphology, were screened for antibacterial efficacy against close relative bacteria to ESKAPE pathogens, such as B. subtilis and E. coli. Out of six, one bacterial isolate showed antibacterial activity against B. subtilis. Bacteria which showed the antibacterial activity against B. subtilis was characterized as gram-negative bacillus. Biochemical testing showed that bacteria was motile (by Sulfide Indole Motility), gelatinase positive (by gelatin Agar), non-lactose, sucrose and glucose fermenter (by triple Sugar Iron Agar) and citrate positive (examined by Simmons Citrate Agar). 16S ribosomal gene sequencing result is awaited. Organic extract of this bacteria furthered the antibacterial activity against B. subtilis on Todd Hewitt agar, while awaiting a test for toxicity to chia seeds. In future, organic extract from this bacteria will be characterized for structure of this active compound.

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  JJR Solutions

  Michael William Krug, Danielle B. Lewis, Kate Elizabeth Nawrocki, Adam P. Roe

  JJRS Pulse-Microsoft SharePoint/MS Project Integration

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  Joint kinematics and work adjustments in adults when learning the kettlebell swing without coaching

  Cian J. Callahan

  The Kettlebell swing is a complex, full-body exercise and can be difficult to perform correctly without coaching. This study aimed to assess the ankle, knee, and hip kinematic and kinetic adjustments with short-term practice, as evaluated by joint angles and joint work, in young adults when practicing the kettlebell swing without individualized external feedback. This evaluation would assist the development of effective and safe video instruction tools.Our experiment was conducted by having twelve young adults (7F/5M, 22.62 (2.04) years), with no prior practice of the exercise, perform three sets of 20 repetitions of the kettlebell swing. Their only instruction was from a freely available online video of a skilled individual performing the kettlebell swing and providing verbal instructions. Subjects then performed three sets of 20 repetitions each day for the following three days. On the fifth day, they were retested. Joint flexion and extension data was collected using a motion capture system by placing markers on the hips, thighs, knees, calves, and feet. The force acting on the body was assessed using a force plate.The results showed young adults made minimal adjustments of the ankle, knee, and hips joints from no practice to short term practice. At the start position, the knee and hip joints were less flexed during the short-term session compared to the no practice session. Furthermore, total lower body work and hip joint work decreased between sessions. Our results highlight the general tendencies of young adults to reduce lower body flexion and work less when learning the kettlebell swing through self-directed methods. These findings provide guidance to improve the potential effectiveness of instructional videos by highlighting the need for coaching cues focused on further flexing the hip joint at the start position and thrusting the hips forward throughout the upward swing.

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  Kill Probability in Volleyball

  Maura C. Collins

  This project aims to predict the probability of a kill on left-side and right-side attacks in volleyball. Specifically, it looks at the type of attack, which accounts for it being either a left-side vs a right-side attack and whether it was a fast tempo or a slower tempo set, the grade of the pass for this play, and whether this attack was on a first-ball play or in the transition of a rally. A logistic regression model was used to To look at the relationship of these variables. Using the p-value, it was found that attack type and whether it was a first-ball or transition play were the significant variables for this model.

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  KPMG

  Carmen J. DiGeronimo, Brandon D. Easterling, John P. Mccarthy, XiuLin Wu

  KPMG Cyber Response Incident Response Range-Cloud Implementation

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  LandNET: A Multi-Modal Fusion Network for Classification

  Jonathan Paul Schierl

  There is a need for classifying land coverage by usage. As these classes are somewhat abstract, this provides a challenge in classifying them and a need for as much information as possible. We propose an architecture capable of classify such scenes, using 2D aerial imagery and 3D point clouds. This is done by fusing the learned feature space of each modality, to be classified with fully connected layers. This method provides a high degree of accuracy for each modality and then learns the benefits of data type, for more accurate classification.

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  LatinX Leads Conference: What We Learned

  Juan L. Lopez, Sam Ortiz, Isaac Andrew Perez, Noelia Perez, Camila Isabel Sanchez-Gonzalez

  Four Latinx student leaders will share on topics and themes presented at the Latinx Leads conference. Those themes include empowering Latinx students, combatting anti-blackness, building unity within the Latinx community and navigating a Predominantly White campus as a Latinx student. This presentation is their opportunity to give back to their community and help build up others who are interested in supporting Latinx students.

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  Leonardo de Pisa and Interesting Results of the Fibonacci numbers

  Megan Elizabeth Schaner

  Leonardo de Pisa, better known as Fibonacci, is an Italian mathematician who is responsible for numerous mathematical notions and ideas. The most notable are the use of the Hindu-Arabic numerals in modern society and the famous Fibonacci sequence. These ideas were published in his two books Liber Abaci and Liber Quadratorum published in the early 13th century. The Fibonacci numbers are a set of numbers that make up a recursive sequence where a term is constructed by the sum of the two terms that immediately precede it. There are numerous identities and interesting facts revolving around the Fibonacci numbers such as the approximation of the famous Golden ratio, the sum of the even and odd indices of the Fibonacci numbers, and how consecutive Fibonacci numbers are relatively prime. This presentation will focus on how the fact that the greatest common divisor of two Fibonacci numbers is also a Fibonacci number helps to establish that a Fibonacci number divides another Fibonacci number if and only if the corresponding index of the divisor divides the corresponding index of the dividend.

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  Lesion Synthesis Algorithm and Multi-Scale U-Net for Lung and Lesion Segmentation

  Dhaval Dilip Kadia

  Artificial Intelligence (AI) is growing exponentially with novel computational architectures and their cognitive capabilities. AI helps solve complex problems in medical imaging. Lung segmentation is essential since it processes the volumetric information of the lungs, removes the unnecessary areas of the scan, and segments the actual area of the lungs in CT scan. This research focuses on deep learning applications to segment lungs and further develop a novel algorithm to make them robust. Supervised learning requires data to train a deep neural network. The deep learning model, such as U-Net, outperforms other network architectures for biomedical image segmentation. We propose a deep neural network based on U-Net for the lung and lung lesion segmentation tasks. The proposed model integrates convolution into the sophisticated Multiscale Recurrent Residual Neural Network based on U-Net. Both deep neural network (DNN) and availability of diverse annotated data make the given deep learning based solution robust and generalized for practical use. Even if having sophisticated DNN, scarcity of annotated data challenges the expected outcomes. Robust segmentation of COVID-19 infected lungs requires rich labeled data. Accurate pixel-level annotation tasks to generate such data are time-consuming, and that delays data preparation. We propose a novel algorithm to generate lesion-like artificial patterns, and U-Net based deep neural network for robust lung segmentation further helps segment COVID-19 lung infection. The pattern generation algorithm generates 2D and 3D patterns to create an enormous amount of synthetic data. This algorithm and DNN give accurate lung segmentation results for highly infected lungs and provides infection segmentation. This research applies to the preprocessing stages of different applications of deep learning, medical imaging, and data annotation. The proposed work helps the deep neural network to generalize on a given domain to accomplish robust segmentation results in the absence of exact data.

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  Let’s Co-Teach Together!

  Caitlin M. Crews

  Co-teaching is a format that is becoming more common in everyday learning environments. Yet, co-teaching perceptions are often mixed in reviews. These studies discuss the many benefits and change in perceptions amongst teachers after training and implementing co-teaching in their classrooms.

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  Let’s Get Mental! : How Mental Health and Religion Work Together to Support the Common Good

  Caroline Lavin Herling, Gabriel Christopher Janus, Gabrielle N. Wilson

  This study asks how religion addresses mental health, with a focus on how it can provide for the common good. The purpose was to explore how religions or religious contacts have been intermingling with the more common dialogue around mental health within the past 20 years. A literature review of relevant articles in Psychology, Sociology and Anthropology revealed that from India to the United States, religion and mental health are concurrent topics in the lives of those individuals who have mental illnesses and practice spirituality. Some of the key points we found are that being in a community, such as being in a religious community can help the mental health of the people and helps them to form better social skills and mental processes. While there is no one way to approach mental health, if you have a role within religion, those individuals mental health seems to be better than those who do not. In India, the impact of the caste system has an effect on the mental health and religious groups are working to ameliorate those effects. The meaning that people can take away from this presentation on mental health in religion is that participation in religious communities can provide outlets and resources to help people stay mentally positive and happy.

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  Living Through and Dealing with Addiction in Families

  Amelia Grace Vancamp

  Drug Addiction is one of the many leading causes of fatality, mental illness, homelessness, and family tragedy. As much as drug addiction affects an individual, it also affects the family. From being able to see the effects and emotional costs to peers and family members, we can understand drug addiction better and the mental/emotional tolls it inflicts to all involved. The purpose of this study is to educate the public about the hardships families go through when living with someone with addiction. Participants were chosen based on convenience sampling and recommendations from other interviewees. The research explored the accounts of recovering addicts, family members of an addict and those who have known or seen someone’s family go through this family disease. Through an analysis of seven semi-structured interviews, I was able to identify six themes. The six themes seen were different genders instinct approach when trying to help, time and focus not evenly distributed between parents and non-addicted siblings, Families financial strains, lack of trust, and relationships.These findings provide information the community needs to assist families that suffer from this disease.

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  Living Wage in Dayton: Human Rights for Whom?

  Kinsleigh A. Jones, Ahmi' Moore, Christianna J. Surratt

  The purpose of this HRS200 Project is to explore the way in which advocacy work has been done in Dayton, and its surrounding areas, through the concept of Living Wage. Our group is looking to examine the way that administrative assistants, technical staff, and others advocate for their needs, especially in regard to the concept of living wage. The presentation that our group is doing seeks to highlight the research that we have completed for our HRS200 class. We have found material in the Dayton’s City Commission records and the University of Dayton’s Archive files. This research sheds light on Universal Human Rights issues 23 through 25 as well as the UN Global Goals one (No Poverty), three ( Health and Well-Being ), and eight (Decent Work and Economic Growth) . Furthermore, this research is important to our team, our community, and our course because it showcases the way in which worker and economic rights intersect with human rights. A living wage is the foundation to sustain what’s at the base of the UDHR-- free expression, dignity, and liberties that all humans are entitled to. Per our research we have found many connections between human rights and economic justice that the living wage exemplifies.

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  Long Term Inflation Trends and the 2008 Recession; An Empirical Analysis 2001-2019

  Breanne M. Greene, Mary Ann Tully

  In this study, we look at inflation trends pre and post the 2008 "great" recession to determine if there was a recession effect on inflation. The following measures of inflation are used in the study: (1) CIP-ALL, (2) CPI- Less Food and Energy, (3) Personal Consumption Expenditures (PCE), (4) Employment Cost Index (ECI). We test several hypothesis; (1) inflation rates post 2008 recession are lower than inflation rates pre 2008 recession, (2) CPI inflation measures trend higher than PCE measures, (3) ECI cost inflation measures post 2008 rend lower than pre 2008 measures, (4) lower demand poll inflation measures (e.g. CPI-ALL) post 2008 recession are partly due to lower cost push inflation measures (ECI) post 2008 recession.

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  Low Cost VR Interaction

  Yagnik Vinodkumar Trivedi

  In the current time, we have VR systems used in varied field for very different kind of application and uses. But the devices (VR headset & controllers) are costly. The aim is to create a VR system which is affordable and gives user the best possible VR experience. This system will let user interact in the VR world with the low-priced head mounted VR device and controllers. Creating a low-cost VR interaction system in which users can do task like rearranging furniture in a room, learn juggling and other task/games like Pong game using cheap and reusable devices like old phones, sensors etc.

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  Making Culture-Centered Music Therapists: Resources for Working with Young Adults in Latinx Communities

  Michaela Ann Miller

  This thesis investigates the lack of music therapy literature related to this topic and identifies considerations music therapists should take when working with Latinx communities. I illustrate how social justice and culture-centeredness can be integrated into music therapy practice with the identified communities. I use interviews collected from Latinx university students to learn about the diverse musical preferences and cultures that different members of Latinx communities hold. I describe necessary changes in the American Music Therapy Association’s Competencies for Music Therapists in order to equip music therapy students to better work with diverse populations. Finally, I provide examples of music experiences and hypothetical case studies to demonstrate what music therapy could look like in a culture-centered context with this young adult population. The purpose of this thesis is to make music therapy a more equitable, accessible, and appropriate treatment option for Latinx communities.

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  Marijuana Decriminalization Policy and its Effect on Drug-Related Arrest Rates in the New England Region

  Maura Hanley, Michael Lawless

  Marijuana decriminalization policy is a rapidly growing legislative trend of policy change in the United States. Our research examines if marijuana decriminalization policy implementation has affected the rates of drug-related arrests in six states in the New England region of the United States. Maine, Vermont, Rhode Island, New Hampshire, Connecticut and Massachusetts were chosen specifically because the New England region was very progressive when it came to marijuana decriminalization and implemented policy in the 2000s and early 2010s. Our research goal was to analyze the arrest rates of marijuana sales and possession per state per year, and examine how the data reflects the relationship of policy implementation and drug arrest rates.

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  Marijuana Usage by College Students

  Alec R. Warren

  The usage of marijuana by college students has been a heavily researched topic over the years. In 2017, marijuana usage by college students was at an all time high. Researchers believe that it will continue to rise for a variety of reasons. However, there has been a lack of current up to date research on the topic. The research conducted below offers statistics and answers to a range of questions in regards to college students marijuana usage as well as breaking it down by gender. This quantitative study examines survey responses from 299 undergraduate college students from across the United States. The survey asks questions in regards to marijuana usage and accessibility on their respective campuses. The research findings support the idea that marijuana usage by college students is still at an all time high.

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  Masked Face Analysis via Multitask Learning

  Vatsa Sanjay Patel

  Facial recognition with mask/noise has consistently been a challenging task in computer vision, which involves human wearing a facial mask. Masked Face Analysis via Multi-task learning is a method which will answer to many questions. In this paper, we propose a unifying framework to simultaneously predict human age, gender, and emotions. This method is divided into three major steps; firstly, Creation of the dataset, Secondly, 3 individual classification models used for the system to learn the labelled (Age, Expression and Gender) images, Thirdly, the multi-task learning (MTL) model; which takes the inputs as the data and shares their weight combined and gives the prediction of the person’s (with mask) age, expression and gender. However, this novel framework will give better output then the existing methods.