Category: Summer Team Impact Project

My Summer Research in Laikipia County, Kenya! – Desire Omotoye

Author(s): Oyinkansola Omotoye

Mentor(s): Michael von Fricken, Global and Community Health

During my stay at Mpala Research Center this summer, I had the opportunity to join Dr. Michael von Fricken in his ongoing research on vector borne diseases in Laikipia County, Kenya. Our work involved both field and lab work, where we collected ticks by setting up CO2 (carbon dioxide) traps and tick drags in a number of areas, and then bringing the samples back to the lab to run PCR tests on them using innovative Biomeme technology. I also had the pleasure of shadowing and assisting Mr. Sandy Oduor””a Kenyan Ph.D. student at the University of Nairobi”” and his lab assistant, Ephantus Wambui, in their ongoing endocrinology work which examines the prevalence of glucocorticoid and T3 hormones found in elephant fecal samples. In pursuit of his Ph.D. degree in Conservation Biology, Oduor has been performing both field and lab work since March of 2022. His work investigates how human interference across differing types of land use systems and environments hormonally affect African elephants. He aims to use his findings to demonstrate the long-term effects of human disturbance on African elephant herds.
Oduor’s work has been funded by Smithsonian Conservation Biology Institute (SCBI) and Save the Elephants, and San Diego Zoo, and Rafford Small Grant.

[VOICE OVER]

This summer, I was given the opportunity to go to Laikipia County in Kenya to be apart of Dr. Michael von Fricken’s ongoing research project””Life at the Watering Hole: a One Health approach to Disease Surveillance. We stayed at Mpala Research Center, which is around 5 hours from Nairobi. Over the course of this three-week trip, I experienced so many exciting things. I learned about Kenyan culture, and picked up on a little bit of Swahili, met amazing individuals, and ate great food. On days we left the campus grounds, we collected ticks to bring back and run different tests on. On our journeys, we explored the land and came across so many different animals, both alone and in herds.

By the second week, I continued some work with the tick processing, but I began to branch off into some other cool research with a Kenyan Ph.D. student and his lab assistant.

Meet Mr. Sandy Oduor and Mr. Ephantus Wambui. I had the pleasure of working with them for the remainder of my trip. Intrigued by what they were studying, I entered their lab one day and asked if I could shadow them and assist them in their work, and they welcomed me with open arms.
Sandy is studying for his Ph.D. in Conservation Biology at the University of Nairobi. He’s been investigating the effects of human interference across differing types of land use systems and environments on the hormones of African elephants. He is exclusively studying glucocorticoid and T3 hormones because they are indicators of stress and nutrition levels.

[INTERVIEW]

– EPHANTUS: Sandy is trying to look at different land uses and how the different land uses affect the stress levels of elephants

– SANDY: Yes, and what is even more related to Desire’s work””I’ll be looking at how past adversity affects long-term survival”¦ because you have individuals who have been orphaned in the past. So, they have to rely on that human intervention to survive. Because we have to take them.and then release them back into the wild.

– EPHANTUS: For glucocorticoid, he told me that it can be used as a proxy for stress””Indication of stress in elephants. T3 is used because, if you have good nutrition, normally your thyroid hormone levels will be high. It’s the most metabolically active, compared to T4.

– SANDY: The main work of glucocorticoid is in energy mobilization, but it can also be used as a proxy for measuring stress. So glucocorticoid helps us to understand how elephants adjust to different environmental conditions. These environmental conditions can be human-mediated or natural.

[VOICE OVER]

Ephantus Wambui is Sandy’s lab assistant. He majored in Biochemistry in undergrad, and aims to pursue a Master’s degree in Bioinformatics in the near future. Although much of his background is in molecular biology, he values the exposure he gets to the dynamics of endocrinology work.
Aside from lab work, I got the chance to accompany Sandy and Ephantus in their field work before I left Mpala. Since Sandy’s research is a longitudinal study, we tracked down a family of elephants so that we could collect a montly fecal specimen from specific members. We placed the samples in a small plastic bag, labeled them with the time and date, and stored them in a cool box to be taken back to the lab.
All in all, I learned so much during my time in Kenya and I am beyond grateful for the experience I had, the people I met, and the memories I made.
Asante sana, Kenya! (“Thank you, Kenya!” in Swahili)

OSCAR Summer Team Impact Project

Summer Team Impact Project

Author(s): Madison Shaw, Isabelle Tomita

Mentor(s): Hand, Social Work

The objective for the scoping review and interviews was to understand risk factors for adults with disabilities facing IPV and sexual violence and any barriers they may face, along with any known solutions for addressing these barriers. Two databases were used to search for peer-reviewed articles based on primary data or articles that promoted theory. A thematic analysis was completed to find key themes within the articles. Nine articles were reviewed for the scoping review, resulting in five themes of: (a) vulnerability to victimization, (b) stereotypical perceptions of disabilities, (c) equal treatment and barriers, (d) abuse by perpetrators, and (e) individuality, intersectionality, and multifaceted experiences. The findings indicated a further need for research into the disability community and their experiences with IPV and sexual violence, especially with men, along with establishing better practice by professionals to cater to the unique needs of people with disabilities.

Slide 1: Hi everybody, my name is Madison and my research partner for this project is Ella, and this summer we were part of the Summer Team Impact Project that was researching barriers that certain communities face in Fairfax County when accessing domestic and sexual violence services. The specific community that we chose to focus on was the disability community.
Slide 2: The objective of our research this summer was to better understand why, in the context of sexual and domestic violence, adults with disabilities are targeted more than adults without disabilities, and to employ the use of an integrative social ecological trauma-informed and intersectional framework to better understand the ways they may relate to barriers to prevention, and potential solutions for addressing any identified barriers.
Slide 3: Research has demonstrated an urgent need to understand why adults disabilities experience sexual and domestic violence at a disproportionate rate compared to adults without disabilities, and effective prevention and intervention methods. Nevertheless, to address such demonstrated need, our research focuses on three questions. Number one: what is known about intersecting factors relating to risks for sexual and domestic violence among adults with disabilities? Number two: What may prevent adults with disabilities from seeking sexual and domestic violence services? And, finally, number three: in addition, what is known about solutions for addressing any such identified barriers?
Slide 4: The search criteria for our scoping review included both peer-reviewed and academic articles, gray sources for prevalent data which was mainly on the statistics of people with disabilities and the rates of IPV and sexual violence, along with articles that advance theory about certain risk factors the population faces. Then, our excluded criteria included articles talking about children, articles that were not based on primary research unless they were the gray sources or the articles promoting theory, any articles that talked about other crimes committed against people with disabilities, and any articles that were outdated or talked about disabilities in a harmful way which were mostly seen in some articles from the 80s. We used two databases for our search that are listed on the slide, and the search terms are included in the table. Then, we also used 50 exclusion terms in our search to limit the amount of articles coming up, and most of those words included other countries or words relating to medicine or drug abuse. Then, from this were able to include nine articles in the results section of our manuscript along with multiple others that weren’t peer-reviewed that we used in the introduction, background, and discussion sections.
Slide 5: For the coding process, we used thematic analysis to come up with codes that were taken from either the results, discussion, or conclusion parts of our screened in articles. We came up with 131 codes that were broken down into 15 second cycle codes, and from those 15 codes we created five themes that summarize the main ideas of the articles that are listed on the slide. The first one of vulnerability to victimization was mentioned in every article about how people with disabilities are targeted more for IPV and sexual violence. There’s general risk factors that contribute to this such as isolation, lower socioeconomic status, and being financially dependent. But there’s also more specific ones to the disability community such as having more difficulty leaving a relationship and being viewed as more susceptible by perpetrators. For the second one of stereotypical perceptions, many people view people with disabilities as fully reliant on others or believe the myth that they are seen as undesirable and won’t be a victim of sexual violence. There’s also the issue of people’s behavior that shows ableism with many not realizing that their views or behaviors may be seen as degrading. Another theme identified through the thematic analysis was equal treatment and barriers which focuses on barriers preventing adults with disabilities from accessing adequate and proper care and services. It included general barriers to equal care and services such as one’s economic and employment status as well as things more specific to the disability community such as language and communication barriers, difficulty talking about a perpetrator on who the victim is dependent, and social desirability bias. A fourth prevalent theme that came up during coding was the types of abuse by the perpetrator which focuses on the individual’s relationship with the perpetrator and intimate partner, personal care assistant, non familial person, acquaintance, or friend and the type of abuse experience such as severe abuse, covert abuse, emotional abuse, and physical abuse. Finally, the last theme that came up during coding was individuality, intersectionality, and multifaceted experiences. Such a theme essentially focuses on autonomy and ableism as well as heterogeneity and disabilities. It also focuses on how the intersectionality between disability and other social statuses such as one’s gender, ethnicity, or socioeconomic status might make adults with disabilities susceptible to victimization.
Slide 6: The demographics for my three interviews were three females, two of which were middle aged, and one who was older. From these interviews, they all had amazing insight into the disability community from their life experiences, but I included some of their main points on the slide. One topic that was brought up multiple times is how people with disabilities, but more specifically intellectual and developmental disabilities are infantilized by others and seen as childlike, when in reality, they are capable of making their own decisions. This infantilization creates lower societal expectations of people with disabilities instead of recognizing individual strengths. Everybody, including those with disabilities have the right to self-determination which ties in the importance of them being taught how to establish healthy boundaries and understanding that they are not responsible to consistently please people even if it may be an authority figure in their life. One myth that was mentioned in the interviews was the idea sexual violence occurs mostly from strangers and that it also isn’t common in the area of Fairfax. Because of this, better awareness is needed on recognizing the signs of abuse especially for people who work with these vulnerable populations such as people with disabilities.
Slide 7: Thank you so much for watching our presentation. If you have any questions or concerns, please feel free to reach out to us.

Carter School for Peace and Conflict Resolution Honors College OSCAR Summer Team Impact Project

Salisbury’s Beth Israel Congregation

Author(s): Jabez Nelson

Mentor(s): Charles Chavis, African American Studies, Carter School for Peace and Conflict Resolution

The Beth Israel Congregation Within Salisbury was once a thriving Jewish Community along the Eastern Shore. Within this brief presentation, learn more about this community’s founders, as well as the previous areas of which were considered to be just as rich in Jewish culture. Furthermore, discover why the Salisbury Beth Israel Congregation is no longer as lively as it was once before, though it still thrives to this day.

Hello, my name is Jabez Nelson, and today I’ll be presenting to you information relating to Salisbury’s Beth Israel Congregation. So, a little bit about me. I’m a third-year undergraduate student. I’m currently studying psychology with a concentration in industrial organizational psychology. Most of this research, or all of the research that I’m actually presenting to you today was done under the John Mitchell Junior Program. So before getting into the Beth Israel Congregation in Salisbury, we have to understand what the Jewish hub was before Salisbury. So, that was actually going to be Pocomoke, Virginia, as it was the biggest area where Jewish people are actually going to along the Eastern Shore in the late 1880s. So, many of the Jewish families have initially moved to Pocomoke, including the Finkelsteins, Klaffs, Fines, Glasses, Millers, Rodbells, and Heiligs There are other Jewish families that were also starting to take residence within different cities along the Eastern Shore, such as in Pennsylvania and Maryland. By the early 1900s Sam Feldman was actually one of these people, so he moved from Pottsville, PA, to Salisbury in 1904. He’d actually owned a furniture shop so he was taking it to Salisbury, actually setting it up to like live there permanently. As well as Israel Leon, AKA, “I.L.” Benjamin, who arrived in 1915 from Exmore Virginia. He was also a store runner, but his store was clothes, so he’s here running a clothing store. So these two men, both Jewish, they decided to found the Beth Israel Congregation in 1925, though it wasn’t actually known as the Beth Israel Congregation at the time, it was only known as the “Kehelas Israel”? Which meant the “Community of Israel” in Hebrew. The first President of the foundation was also I.L Benjamin, but I believe that Sam Feldman was also on the board, so he was also there, like helping consistently throughout all of the time I.L. was also present. Moving along to 1939, the congregation meetings were usually held within the second story of a store between Main Street and Camden Street. This was kind of a step up from what they were doing before because they had been going from house to house originally, as they didn’t actually have an official meeting place or building. But this all changed in 1951, when the first, official synagogue building was actually built. As this was happening, membership at the time was also going up exponentially as well as the Jewish population in Salisbury. I believe there were 75 Jewish families in the congregation around this time, which is way more than there are currently, unfortunately, as the modern day Beth Israel is a relatively small congregation. Since many of the families ended up migrating away to various metropolitan areas such as Baltimore, DC and Ocean City, this is the modern day building. By the way. On the last slide we saw that was the building that was first built in 1951, I believe. But the moving away from the Salisbury community primarily happened due to the conflicting viewpoints amongst older and younger members within the church back in the. Late 1980s, as I learned from the person I did an oral history interview with, Andrew Karten as well as the passing away of many of the original members. Yeah, it was very sad, but”¦ Throughout this entire process, I actually did a lot of searching through digital databases such as Ancestry and Newspapers trying to find out like more about each of the digital members of in the community that I was assigned. That also included me clipping different materials and transferring materials in the base camp. I also read through a lot of Jewish history literature. And of course, I had to contact the actual organization Beth Israel Synagogue. And I actually had scheduled the oral history interviews and the once those were done I just transcribed those oral history interviews. But yeah, that was basically all of my research so far, and I’m still doing more trying to like wrap everything up, but I’m looking forward to seeing what you guys have also done so, thank you.

Carter School for Peace and Conflict Resolution OSCAR Summer Team Impact Project

STIP Fellow Michelle Kim – Social Advocacy in Breaking the Silence of Systemic Racism

Author(s): Amber Green, Sewon Michelle Kim, Logan Varker

Mentor(s): Charles Chavis, African and African American Studies

Through the Summer Team Impact Project at George Mason University, I collaborated with the John Mitchell, Jr. Program and Dr. Charles L. Chavis to assist in their work on history and transformational, community-led narrative change. As an aspiring social worker, I was able to see firsthand what cultural competence means through the teachings of Dr. Chavis on the history of the Eastern Shore of Maryland. Building upon that, I was given the opportunity to work with a local nonprofit organization focused on the youth homelessness issue in the city of Salisbury. This offered me an indelible experience to see the strong bond between history and social work, especially in a community fragmented by generations of disenfranchisement and displacement. Through my work with JMJP, I have been given the tools and courage to become a social advocate for not only Fenix Youth Project and Salisbury but of my immediate community as well.

Hello, my name is Michelle Kim and I am a junior at Mason, pursuing a bachelor’s in social work. I was honored to be selected as a Summer Team Impact Project fellow to collaborate with the John Mitchell, Jr. Program for History, Justice, and Race of the Carter School for Peace and Conflict Resolution. As stated on their website, the program “contributes to and promotes a more informed public, political, and academic dialogue on the intersections between historical memory, justice, and racial reconciliation.”
Through the leadership of the director of JMJP Dr. Chavis and his book “The Silent Shore: The Lynching of Matthew Williams and the Politics of Racism in the Free State,” I began to understand concepts such as systemic racism, disenfranchisement, displacement, and historical trauma theory.
The history of the Eastern Shore of Maryland is riddled with racial terror that continues to affect the Black community through generations. The racial disparities that are seen today in the city of Salisbury and the surrounding areas of the Lower Shore can only be understood by revisiting the history, of which has been exposed through the works such as Dr. Chavis.’
“The Silent Shore” provoked the activist in me, as I was confounded by just how systematic racism is in this country, to the point that it has become elusive, to the effect that most people do not raise a question to how things are the way they are now. This all ties to the track that I have taken in this fellowship, which is advocacy and coalition building.
By building upon the history I had learned through Dr. Chavis’ book and thus the knowledge of the dismantlement of a once-affluent Black community called Georgetown that is now present-day Salisbury, I had a useful lens in which I could view the work I did with Fenix Youth Project, a local nonprofit organization.
Fenix Youth Project is founded by local activist Amber Green, whose mission is to uplift the youth of the area by giving them a voice and providing them the resources to thrive and enrich their lives to become active members of their community.
The ever-persisting problem of youth homelessness is what Green has been trying to help solve for the past ten years through her organization. I assisted Fenix Youth Project by searching for and writing grants and finding ways to build upon their fundraising efforts. Grants, both local and federal, are crucial in supplying funds to run the organization, from being able to diversify their programs for the youth, running their drop-in center and youth shelter, and also to pay their staff. I also collected and configured data that painted a more precise picture of the pressing issue of homelessness in the youth, and predominantly Black, community in Salisbury.
Through this infographic I have created, it is clear that the youth homelessness issue is disproportionately affecting the Black community in Wicomico County, where Salisbury is located. Looking through the casework of the clients at Fenix, I was able to draw out stories of the youth in the area and viscerally feel the struggle in their lack of access to resources.
I understand now that the systemic inequity that exists today, such as the problem Amber Green and Fenix Youth Project is trying to solve, stems from a longwinded history of destruction and displacement, one that has continued to grow and stifle the Black community through a system of silence. Although at times I was frustrated to learn the history and see its impact on today’s society, I was more so encouraged and inspired by the connection I saw Green have with the youth in Salisbury. I could see that through her voice, she gave the youth their own voice too.
Through my Summer Team Impact Project fellowship with JMJP, I have learned the importance of history as a future social worker and what it means to be culturally competent, and also how vital it is to keep the spirit of social activism. With this spirit, we can one day dismantle not only the system of silence but the deep-seated relationship that America has with racism.

To learn more about Dr. Chavis’ work in Salisbury, Maryland, you can visit www.hiddeninfullview.com to register to see the documentary based on his book The Silent Shore.

College of Engineering and Computing Summer Team Impact Project

Pupil as an Indicator for Neuropathic Pain

Author(s): Justin Matthews, Venkat Kalyan Reddy Yasa

Mentor(s): Nathalia Peixoto, Engineering

While brightness, near fixation, and arousal/mental effort are the main three kinds of stimuli to which human pupil (herein after pupil) may react to, people were on a search for more ways that may affect the pupil size. Previous research suggests that pupil diameter increases when exposed to heat stimuli. While that was based on external stimuli, there are chances that similar pattern may occur with internal stimuli (pain from inside). As far as our knowledge extends, there was no previous research conducted on pupil response from internal pain. This paper presents how pupil size increases 22.4 – 33.1% more than normal pupil size under internal stimuli.

Opening
Hello, for the Summer Team Impact Program, Venkat Kalyan Reddy Yasa and I, Justin Matthews, worked on this project titled Pupil as an Indicator for Neuropathic Pain. It is under the scientific field of pupillometry, but what exactly is pupillometry?

First slide
It is the study of changes in the diameter of the pupil as a function of cognitive processing. To put it in simpler terms, it is the study of how the pupil changes size due to different stimuli. Research in this field began as early as the 1960s with the first researchers being Eckhard H. Hess and James M. Polt. Their first paper, published in 1960, found that the pupil size increases when viewing emotional or interesting visual stimuli. As cheaper and more reliable eye tracking equipment became accessible, pupillometry research has had a renaissance within the last two decades. Now that you know some of the history behind pupillometry, let’s look at some of the past research.

Second slide
Researchers have narrowed down pupil response to three distinct kinds of stimuli. The pupil will tend to change size in response to brightness, near fixation, and increases to arousal and mental effort. For brightness, researchers were looking at how the pupil responds to different amounts of light. For near fixation, researchers were looking at how the pupil responds when fixating on an object at different distances. For arousal/mental effort, researchers were looking at how the pupil responds when focusing on a task. While these are the main three stimuli, there is another one that is currently being looked into and that is pain.

Third Slide
Experiments conducted that were observing the relation between pupil dilation and pain concluded that the pupil diameter increases as a response to pain. The goal of our experiment is to support that idea, with the difference being the way the pain stimulus is inflicted on the participants.

Fourth Slide
We had a very simple set up for this experiment. An external webcam was taped to the top of the desktop and the recording was done with the camera app. Participants sit on a chair and position themselves so that their eye is in frame. A one minute and thirty second video is then recorded of the participant’s eye. The first thirty seconds is them without pain, while the remainder of that video is the participant in pain after eating 1.2 grams of Tabasco hot sauce. After separating the sections of the film and cropping them we got the length of the pupil (in pixels) in each frame. We then calculated the median length of the pupil without pain and counted how many times the pupil length (while in pain) went over and under the median.

Fifth Slide
Here is an example of one of the graphs created. The x-axis is the pixel length and the y-axis is the number of times the pupil was at that length. Looking at the “w/o pain” graph, we can see that the median is roughly here. If we put the same median on the “w/ pain” graph, it is clear to see that the pupil has more instances of dilating over the median. This supports the finding in previous research as the pupil size goes over the normal average size repeatedly in response to pain.

Sixth Slide
Thank you for your time and thanks to Mason and the OSCAR office for this opportunity. If you want to know more about our project you can visit the following website.

College of Engineering and Computing Summer Team Impact Project

Finger Detection Movement Project

Author(s): Justin Matthews

Mentor(s): Luciano de Oliveira Neris, Information Technology

Object detection is a form of machine learning that utilizes computer vision and deep learning techniques. It can be used to identify targeted objects in images and videos with precise accuracy. For detecting hand gestures, the method most commonly used is computer vision. When using computer vision, there are some factors to consider that could impact the results of the experiment. Due to this, a variety of different techniques were developed in order to mitigate the significance those factors have on the data. This paper will present one technique to use when creating a machine to detect hand gestures

Hello, my name is Justin Matthews, and for the Summer Team Impact Program I worked on this project titled Finger Detection Movement.

For some background knowledge, Machine learning is “a field of study that gives computers the ability to learn without being explicitly programmed”. The origin of machine learning begins with a psychologist named Frank Rosenblatt from Cornell University. He based the design of the machine on the human nervous system. The machine was named “perceptron” and its purpose was to recognize the letters of the alphabet. A task that falls under machine learning is called object detection. Object detection is a form of machine learning that utilizes computer vision and deep learning techniques. It can be used to identify targeted objects in images and videos with precise accuracy. For my project, I created a machine to detect hand gestures during a real time video streamed from a webcam.

Materials that I used for this project include: Visual Studio Code, Anaconda Prompt, Tensorflow, Python, and OpenCV. Visual Studio Code was used to edit my code. Anaconda Prompt was used to run my code. Tensorflow in combination with Keras, was used to save and load the data of the model that was created and trained. Python was used to code the project. Lastly, OpenCV was used to access my laptop’s webcam and display real time video coming from it.

The next portion of this video will be a demonstration on how my program works. What you are seeing now is Anaconda Prompt. This is the normal set up I do before starting to code, test, etc. What I am doing is going into the proper directory and checking to make sure I am on the right path. You can see that I have a folder named dataset and when I enter and display the contents, notice how it is empty. That is because we have to populate that folder which is what my “builDataset” script does. I have to type python *script name* *name I want the image folder to be* *# of images*. Unfortunately I am unable to record the window that appears but as you can see by the next line, 300 images are saved. Once I open my dataset folder you can see that a new folder title Zero appears and in it are all the photos that were taken. I repeat this process for the rest of the numbers (1-5). Once all of that is done it is now time to build and train the model. I simply run the command that you see there and a bunch of text that you can ignore appears. You can see that a loading bar will appear and next to it loss and accuracy. Accuracy is pretty self explanatory and that just means how accurate your model is at guessing the finger position and loss is how much data was lost during that training period. In total there are 10 total training periods each taking roughly 40 seconds each. But with the power of movie magic we can cut all of that. Once the training is complete a graph of the accuracy and lost will be displayed (but my recording software couldn’t record that). Now we can test to see if the model is accurate. First I’ll be testing if it can detect the number three which is does successfully. Let’s try it again but with a different photo. Again success. Now let’s see if it can detect zero. Success once again

These are the graphs that display after the training is complete. On the left is the accuracy graph and on the right is the loss graph. As the accuracy of the model increases, the data loss during training decreases. This means that accuracy and loss have an inverse relationship with one another.

This next screenshot is the window that appears after running the buildDataset script. The way it works is simple as you hold up your hand so that it is within the parameter of the rectangle. You then press the ‘a’ key to start taking screenshots. To pause the screenshot process you just hit the ‘a’ key again. To exit the window early, just press the ‘q’ button. Once the specified number of screenshots are taken, the window will automatically close.

Thank you for your time and thanks to Mason and the OSCAR office for this opportunity. If you want to know more about my project you can visit the following websites: https://detect.onmason.com/

College of Engineering and Computing College of Science Summer Team Impact Project

Pupil as an Indicator for Neuropathic Pain

Author(s): Justin Matthews, Venkat Kalyan Reddy Yasa

Mentor(s): Nathalia Peixoto, Electrical and Computer Engineering

Sixth Slide
Thank you for your time and thanks to Mason and the OSCAR office for this opportunity. If you want to know more about our project you can visit the following website.

College of Science Summer Team Impact Project

Finger Detection Movement Project

Author(s): Justin Matthews

Mentor(s): Luciano de Oliveira Neris, Information Technology

Hello, my name is Justin Matthews, and for the Summer Team Impact Program I worked on this project titled Finger Detection Movement.

Thank you for your time and thanks to Mason and the OSCAR office for this opportunity. If you want to know more about my project you can visit the following websites: https://detect.onmason.com/

College of Education and Human Development College of Public Health College of Science Honors College Summer Team Impact Project Undergraduate Research Scholars Program (URSP) - OSCAR

How do sleep, physical activity, and diet contribute to aerobic fitness in U.S. firefighters?

Author(s): Hana Khan

Mentor(s): Joel Martin, Marcie Fyock-Martin; Kinesiology

Abstract: Firefighting involves high intensity work and requires firefighters to maintain optimal levels of health. Unfortunately, due to the nature of their occupation, firefighters’ sleep, diet, and physical activity (PA) are often compromised, contributing to low aerobic fitness.

Purpose: To determine how sleep, PA, and diet behaviors contribute to low respiratory fitness in U.S firefighters. Methods: Participants included [10 males, 3 females, age: 36(30, 41), years of service: 14(10, 18), height(cm): 181.9(177.5, 185), mass(kg): (122.4(109.6, 121.7)] and needed to be Prince William County Firefighters and have no prior history of CVE, pulmonary, renal, and metabolic disease. Participants took a diet (REAP-S), sleep (PSQI), and PA survey (IPAQ-SF). Anthropometric measurements were taken using a BOD-POD®. The 3-minute step test was used to determine aerobic fitness. A Mann-Whitney U test with a p value of 0.05 was used to determine significant variables between two groups: those who performed poorly on the step test versus those who performed above poor. Effect size was calculated using Glass rank biserial correlation coefficient. The project was exploratory, so alpha was set to <0.01. Results- Variable(W-score, p-value): BF %(15, 1), PSQI(18.5, 0.6086), REAPS(18.5, 0.6066), and MPA(21, 0.3458), LPA (18, 0.6709), and Sitting time(12, 0.6709) FFM(11, 0.5541) showed no significant differences between groups. However, FM(4, 0.07593) and VPA(29, 0.02139) were statistically different between the groups. Conclusion: Post- statistical analysis showed that only VPA(29, 0.02139) and FM(4, 0.07593) were statistically different between the two groups. Vigorous physical activity is necessary in firefighters given the intense nature of their work. Excess fat mass is also a hindrance to performance and health as it can increase risk for cardiovascular events. Fire stations need to work towards implementing fitness programs to sustain firefighter aerobic fitness.[/expand] [expand title="Audio Transcript"]Hello! My name is Hana Khan. I'm currently an undergraduate student at George Mason and I am majoring in Community Health with a concentration in Nutrition. I'm so excited to share my research question with everyone that I worked on during my Summer Team Impact Project. So, my research question is: How do sleep, physical activity, and diet contribute to aerobic fitness in U.S. firefighters? You might be wondering, why is this an important or relevant question to ask? As I spent time in the project, it became apparent to me that many firefighters are not able to maintain healthy fitness levels, despite often having to perform physically difficult tasks. Their sleep, diet, and physical fitness levels have been shown in numerous studies to be sub-optimal, and studies have pointed to correlations between these three. Research has shown that aerobic fitness is especially important in firefighters- and yet, many do not have the required fitness levels needed to safely perform their jobs. It turns out, CVD is a leading cause of death in firefighters, most likely due to their work duties. Aerobic capacity is also correlated to CVD, where a low capacity means a higher risk. So I really wanted to focus on that with this topic. There were 13 participants in total, and their specific demographic information is listed on the slide under the methods section. The participants took a few surveys to assess their diet, sleep, and physical activity status. They then had some measurements taken, such as height, weight, body fat, etc. And finally, they performed a three minute step test, which is essentially a test that is used to determine aerobic fitness that involved stepping on and off plates raised to 12 inches to a metronome set to 96bpm. We divided the participants based on how they performed on the 3 minute step test. So one category was for those who performed poor, and one was for those who performed above poor. So after looking at all these variables from the surveys and measurements as seen in the table, and running them through a Mann-U-Whitney test, we found that only Vigorous Physical Activity (which we got from the physical activity survey) and Fat Mass (which we got from the anthropometric measurements) were significantly different between these two groups. Now, I will say that a limitation of this study is definitely that the surveys have self reported values, which means the participants may over or underestimate their responses. However, it cannot be ignored that fat mass and vigorous physical activity are both very important to firefighter fitness and performance. Vigorous physical activity is needed on the job when climbing and carrying things is needed, and excess fat mass can be a hindrance to performance and also increase CVD risk. Thus, I believe it would be beneficial for fire stations to provide individualized fitness programs aimed at targeting aerobic fitness and keeping firefighters active instead of launching them into a physically intense situation from a very low active situation. That's all from me, thank you for listening and I hope you gained something valuable from this presentation![/expand]

Summer Team Impact Project Undergraduate Research Scholars Program (URSP) - OSCAR

EKG based Heart Rate Monitoring and Reliability with Arduino

Author(s): Omar Alsuhaibani, Cynthia Love

Mentor(s): Nathalia Peixoto, ECE

We built a heart rate monitoring system with an Arduino microcontroller and ADS1292r analog-digital converter, that would allow real time monitoring of user heartbeat in a computer program. This computer program would also present live feedback to the user about their heart rate. One of the main aims of this project would be to explore if live biofeedback would help the user of the program control their breathing or heart rate, as well as test the reliability of the monitoring system, especially in comparison to the Empatica E4 wristband. Results suggested that the computer program monitoring heart rate in real time is similarly reliable to proprietary commercial monitors such as the Empatica E4 wristband.

Hello, we are one of the groups taking part in the STIP program for the summer of 2022. Our group consists of three members that worked on this research project over the summer. They are me, Omar Alsuhaibani, the group’s project manager German Kuznetsov, and Cynthia Love. The topic of our group’s project focused on attempting to use an Arduino microcontroller and an ADS1292r to create a system where a computer program can monitor the heartbeat of a user in real-time, and evaluate its effectiveness when the user is playing a video game.
Computer programs typically use devices like keyboards and mice to get input from the user. In our project we explore another form of input – biofeedback, primarily heart-rate, and test its reliability in different environments – such as when the user is sitting still, or playing a game on the computer.
While devices to get user heart rate in real time already exist, such as the E4, they do not provide direct access to the data. Because of this we chose to use an arduino with a ADS1292r sensor shield to monitor the user’s ecg signal and calculate their heart rate from the signal. The user will have two electrodes placed on their wrist, which will be connected to the ADS1292r sensor and arduino. The arduino will read the raw data from the sensor and send it to a PC for processing. The raw data signal goes through multiple filters in the computer program, which help remove noise from the signal and make it easier for the code to detect the heartbeats.
The result we reached is that the process is not 100% reliable. Even small movements by the user can disrupt the signal enough to where the computer program can no longer correctly identify heartbeats. Incorrect electrode placement or inadequate adherence can contribute to weakened connectivity.
However, since heartbeats are periodic and happen from around 40 to 200BPM, we can analyze the acquired heartbeats and make assumptions and conclude if they were detected correctly. By comparing the number of heartbeats detected correctly to those incorrectly, we can estimate the reliability of the acquisition method.
Using this setup, games and other computer programs will be able to incorporate biofeedback to measure the heartbeat and stress of the user. This can potentially be
used as a biofeedback visual that can aid the user in analyzing their heart rate and detect stress throughout a video game, VR simulation, or any other related activities.

College of Humanities and Social Science Honors College Summer Team Impact Project

Correctional Compassion: How does Empathy’s Association with age Influence the job Performance of Correctional Officers Working in Restricted Housing Units?

Author(s): Ella Tomita, Alexa Buckner

Mentor(s): Taylor Hartwell, Criminology

Currently, no research considers empathy among those working in restricted housing units (RHUs), which is also known as solitary confinement. Our research focuses on how empathy and other characteristics influence correctional officers in RHUs. The data used was collected from six male prisons and one female prison between 2017 to 2019. Ethnographic observations were the main method of data collection. 45–60-minute semi-structured interviews were conducted for 89 correctional officers. We coded 89 correctional officer interviews using ATLAS and used 73 of those interviews in the analysis. While coding we took note of concepts like age, positive or negative characteristics mentioned, interpersonal relationships, and the correctional officers’ definitions and perceptions of empathy. After coding, each interview was analyzed. The correctional officers were then grouped into the following age groups: young adults (aged 20 to 39 years old), middle adults (aged 40 to 59 years old), and older adults (aged 60 to 80 years old). Within their respective age groups individuals were placed in subgroups pertaining to their displayed empathy and positive or negative characteristics. The three subgroups were, “displayed empathy and positive characteristics”, “not enough information”, and “lacking a display of empathy and/or displayed negative characteristics”. We found that out of the three age groups, the correctional officers in the “Older Adults” group consistently displayed the most negative characteristics and lacked the most empathy compared to the other age groups. In the context of our research, the theoretical implication is that a person’s age may influence their empathy and job performance. Additionally, the practical implication is that older correctional officers displayed the least amount of empathy, which leads us to wonder if there should be an age cap for working in RHUs.

Correctional Compassion Script

Title Slide: (Alexa and Ella)
Alexa Introduction:
“Hello, my name is Alexa Buckner. I am going to be a senior this year at George Mason, and I am studying Criminology, Law and Society with a minor in forensic psychology.”

Ella Introduction:
“Hello, my name is Ella Tomita. I am going to be a sophomore this year at George Mason, and I am studying Criminology, Law and Society with a double minor in forensic psychology and social justice and human rights.”

Introduce our Project (Alexa):
“We are a part of a project that is aims to acquire a better understanding of the experiences of inmates, who we refer to as residents, and correctional officers living and working in solitary confinement units which is also known as RHUs or restricted housing units. For our research this summer Ella and I focused on how empathy and other characteristics influence correctional officers and their work.”

Previous Literature: (Alexa)
Transition/Introduction:
“While reading literature for our topic, we examined empathy broadly because there is a lack of literature examining empathy within the criminal justice system.”
First article:
“We first found that there is a negative association between age and empathy. This negative association is most often known to be caused by life experiences like physical disabilities, socioeconomic status, widowhood, and personal characteristics.”
Second article:
“Overall, within the research we found, Older adults have displayed an age-related decline in cognitive empathy and social functioning.”
Third article:
“We looked to other professions’ research on empathy and found that health care professionals who are more empathetic have been found to provide better treatment. This increased quality of treatment has been shown to increase patient compliance. Additionally, it was found that health care professionals who had interpersonal relationships have more empathy.”

Gaps in the Literature: (Ella)
“Currently, no research considers empathy among those working in restricted housing units. Consequently, there is no research that specifically addresses how the combination of empathy and age influence the ability of restricted housing unit correctional offices to do their job well.”

Research Questions: (Alexa)
Intro/Transition: “This gap in the research provided us with these research questions.”
First Question: “Our first question was if there are specific characteristics that lead correctional officers to be more empathetic towards residents.”
Second Question: “We also wondered if emotional empathy, (which is empathy that stems from sharing an experience, being willing to help other people, or experiencing distress in response to another person’s pain), or cognitive empathy, (which is empathy that stems from imagining what it would be like to be in another person’s shoes and understanding that person’s feelings), would be more important for correctional officers to display.
Third Question: “Our final question was what types of interpersonal relationships affect a correctional officer’s overall empathy.”

Data Collection: (Ella)
“The data used by our team was collected from 7 prisons – 6 male prisons and 1 female prison– between 2017 to 2019. Such data collection consisted of semi-structured interviews, which were about 45 to 60 minutes long, and ethnographic observations. During the data collection, interviews with 89 correctional officers were conducted.”

Data and Methods Slide One: (Alexa)
“We coded 89 correctional officer interviews using ATLAS. 73 of those interviews were used in the current analysis. This is a list of the majority of the topics or ideas within the interviews that we took note of while coding. Some of the most important here to note for the purposes of this analysis would be age, the positive or negative characteristics mentioned, interpersonal relationships, the correctional officers’ definitions and perceptions of empathy, the different types of empathy the correctional officers displayed, the correctional officers’ perceptions of inmates and their co-workers, and their willingness to report issues.”

Data and Methods Slide Two: (Ella)
“After coding, we analyzed the codes in each interview and then grouped the correctional officers by the following age groups: young adults (which consisted of individuals age 20 to 39 years old), middle adults (which consisted of individuals age 40 to 59 years old), and older adults (which consisted of individuals age 60 to 80 years old). Individuals were then grouped into three different subgroups, within their respective age groups, pertaining to displayed empathy and positive or negative characteristics. The subgroups consisted of displayed empathy and positive characteristics, not enough information, and lacking a display of empathy and/or displayed negative characteristics”

Examples of Categorizing Empathy: (Alexa)
“These are some examples of quotes from the interviews that we felt displayed empathy or a lack of empathy. One quote that we felt showed a correctional officers’ empathy reads, ‘At the end of the day, they’re still people (he is referring to the residents here).’ He goes on to say, ‘They deserve forgiveness… I’m not here to punish them anymore than their sentence.’ This next quote would be an example of a quote from an correctional officer that we found was lacking empathy. While discussing the mental health of residents in the RHU this correctional officer said, ‘ask me what bipolar is and I’ll tell you it’s a gay polar bear. I don’t care.’

Examples of Characteristics: (Ella)
“To preface, what we classified as positive and negative characteristics among correctional officers stemmed from what the correctional officers themselves said about themselves in response to questions throughout the interviews. Nevertheless, here are some examples of both positive and negative characteristics of correctional officers.”

“The first quote which states “Establishing a rapport with inmates is so important because every situation is unique. You need to know what every inmate needs in order for these units to keep running smoothly” demonstrates being prosocial with inmates, which is a positive characteristic. Contrarily speaking, an example of a negative characteristic among correctional officers is passiveness, which is demonstrated in an exchange where the interviewer asked a correctional officer, “Would you go to management if there were a problem with a coworker?” to which the correctional officer replied “No, I never would”

Findings: (Ella first, Alexa second)

Main Findings (Ella):
“Ultimately, we found that out of the three age groups, the correctional officers in the “Older Adults” group consistently displayed the most negative characteristics and lacked the most empathy compared to the other age groups.”

Categories (Alexa):
“Here within our three age groups, we have a breakdown of how many correctional officers were placed in each category after analysis. For the young adult age group which consisted of correctional officers between the ages of 20 and 39, 40% displayed positive characteristics and empathy, 35% did not have enough information, and 25% displayed negative characteristics and a lack of empathy. Within the middle adult age group which consisted of correctional officers between the ages of 40 and 60, 73% displayed positive characteristics and empathy, 10% did not have enough information, and 17% displayed negative characteristics and a lack of empathy. For our older adult age group that consisted of any correctional officer over the age of 60, 100% displayed negative characteristics and a lack of empathy. These findings aligned with the conclusions previous research about empathy have made.

Discussion: (Ella first, Alexa second)

Limitations (Ella):
“One of the limitations of our research was the availability of interviews with Older Adults. In other words, we had well over 20 interviews for the other two age groups, but only 4 with the Older Adults”

Theoretical Implications (Ella):
“The theoretical implication in the context of our research is that a person’s age may influence their empathy and job performance.”

Practical Implications (Ella):
“Additionally, the practical implication in the context of our research is that older correctional officers displayed the least amount of empathy, which all together leads us to wonder if there should be an age cap for working in restricted housing units.”

First Next Step (Alexa):
“The first step we would like to take next regarding our research is to investigate whether correctional officers nearing the older adult age bracket begin showing signs of a decline in empathy or social functioning. We would also like to code resident interviews to investigate their perceptions of positive correctional officer characteristics. Additionally, we could do a mixed methods longitudinal study to see if individual correctional officers’ empathy and social functioning changes overtime and with aging.”

Conclusion (Alexa):
“Thank you so much for your time, and for listening to us today.”

Summer Team Impact Project

Curating the Chinese Anti-Rightist Campaign of the 1950s

Author(s): Joel Adeniji, Bailey George, Kristie Phan, Weilon Price

Mentor(s): Shanshan Cui, Art and Design Building

Curating the Chinese Anti-“Rightists” Campaign in the 1950s

The Chinese “Rightist” Archive is a collection of testimonials, biography, and images of intellectuals who were accused for being against the government during the Chinese Anti-“Rightist” movement between 1957 and 1959. While there is great potential of large-scale analytics and historical research in the archive due to over 40,000 documents, the unstructured nature of the collection and their data format of plain text make it difficult for users to access necessary information. Our 2022 Summer Team Impact team aimed to make this collection accessible and searchable by leveraging computational archival science (CAS) methods and design methodology from the field of Human-Computer Interaction (HCI). Specifically, we (1) developed automatic data pipelines to structure, translate, and standardize the raw data using Python, Amazon Web Services, and OpenRefine, (2) designed a real-time database schema to ensure data management efficiency and searchability, (3) designed the user interfaces and user experiences using the scenario-based design methodology, and (4) implemented the web-based archival platform using Firebase, Angular, and other cloud-based APIs. The final application not only resolves the information accessibility issues by providing searchability and navigability of the data, but also makes it possible to add additional data by providing public contribution pages. This research can contribute to CAS with the data processing pipeline for language translation and structuring and to HCI with the adjusted design methodologies in the context of individual-level historical data.

00:01
Hello, we are the summer 2022 impact team for the project, Curating the Chinese Anti-Rightists Campaign in the 1950s. For our project, we created a website that focuses on the Anti-Rightist Campaign through our research and data we currently have in our database.

00:16
To give some background information about the Anti-Rightist movement, it began in 1957 which lasted for two years from 1959. The Chinese Communist party reeducated, imprisoned, and executed those who were counter-revolutionaries of the government. For our research, we have 40,000 files in our database to include in our project website which contains rightists who were impacted by this movement. While 40,000 may seem a lot, this is only a small portion out of the millions of lives that were affected by this campaign.

00:45
The research problem of our project contains 3 components. One, the information accessibility contains the 40,000 files we have in our database. So our team needs to figure out how to implement that factor into our website to help users search for specific files. Two, the data management contains unstructured data which makes it hard for the practitioners to manage and organize the data. Finally, the design problem is that even if the data are well organized, it is hard for users to use the data intuitively, so we need to use UX/UI design to help improve usability in the system.

01:19
To briefly explain our approach in the CAS also known as the Computational Archival Science, the problem lies within the information accessibility and data management. We have to create easy navigation and searchability through digitizing the archival collection while structuring the data using Python scripts and managing the data in the firebase database. Finally, the design problem lies within the human computer interaction, or HCI, which uses a scenario based methodology to generate requirements and usability in the system.

01:50
During the beginning of our project, we brainstorm some of the timeline we need to take for us to view the application and some of the architecture and the schema aspect of it.

02:03
We recurate through a lot of the database, so we develop Python scripts to translate the raw files into a more schema format.

02:16
We use Angular, Github, and Firebase for setting up the front end aspect of it to use Angular and we use Github to maintain and manage the code base. And we also use Github to set up the workflow for automation view and automation testing deployments. And for the firebase, we use this to all the applications both the authentication and the domain aspect of it.

02:46
So, here are some of the wireframes the design team that created for the interface and database design once the user scenarios were tested.

02:55
Here are the overall final designs of the website and database that were just completed.

3:04
Here’s a close up of the archive collection views and the rightist file page. The two on the left showcase our most important feature on the website, which is the ability to search the entire database for a rightist.

03:17
And then, here are some close ups of the account pages for a logged-in public user which displays their contributions shown on the left and on the right, if they were to upload a new rightist file for the database.

03:33
For the Computational Archival Science, we basically developed a new data processing pipeline for unstructured Chinese data.

03:43
And we are going to move on with the DEMO of the website.

03:48
When you first come to the website, this will be the homepage. We have a search bar right here, which will allow the user to search for any of the documents.

03:58
The basic overview of the homepage and the users are also going to switch between Chinese and English, like so.

04:08
Now let’s move on to the login functionality. Users can register with Google or Facebook or login with Google. I will login to Google in this case.

04:22
And users are also able to upload additional files that contribute to our existing database. And we are able to search this new contribution in our search functionality. By the way, here we have the archive of all the other individuals.

04:43
And this is our project and those are the main functionality. Of course, we have other pages the user can visit and I’ll just leave that for you guys to explore, so thank you.