Friday, March 23, 2018

URSP Student Farhaj Murshed Hopes to Uncover the Past and Founding of George Mason University

What got me interested in the Legacy of Slavery at George Mason University Project was the fact that it was about time we address our history. Recently, I was able to work on the Enslaved Children of George Mason Summer Research Project where we began to tell the stories of enslaved black men, women, and children at our university’s namesake’s home of Gunston Hall. Now, we want to continue our innovative work by uncovering the lives of the possibly enslaved people on our campus, while also learning the reasoning behind why our institution was named after George Mason IV and how Virginia's policies of massive resistance and the Jim Crow era played a role in the founding of our university. I see this project being related to my long-term goals as I hope to conduct data-oriented health research, and building off my focus in the Summer, I hope to implement these techniques to focus on the health and wellness of the enslaved people that were most likely on this campus. On a weekly basis, what I’m doing varies, but essentially, I’ve been conducting secondary literature reading, such as “Democracy in Chains” and visiting the Fairfax County Historical Court House Records Office, attempting to use Fairfax County property records as well as old maps to determine what existed on the land where our campus is now. I will also use those property records to determine who owned the land that our campus is built on. If I can find names of the people who owned the land, I can then use wills and probate records to find out names of people that would have been enslaved on the land where we now go to school. Lastly, one thing I discovered this term is how to work backwards to see who owned what pieces of land. At the Courthouse, we are conducting a “chain of title,” and are trying to find out which tax maps the land of Mason sits on in the city (town) of Fairfax. This process is essential in archival work like the one we are conducting and is a useful life skill for any research.

Thursday, March 22, 2018

URSP Student Cydney Dennis Creates a Code to Calculate the Inter- and Intra- Variability of Dance Pieces

I first began to find my interest in this project when working with my current mentor during OSCAR’s summer team project this past summer. The summer team project took my thought process outside the box by integrating dance and bioengineering. I was curious how dance professors actually taught their students. How does a professor know a student is better, what exactly are they seeing that’s different?

This project can be used as a basis for motor learning and rehabilitation for patients with neurodegenerative diseases or spinal injury cases. Knowing how motor skill levels can be quantitatively calculated, clinical experts can use these calculations to decide which path is best for the treatment of patients. With a spinal injury patient, a doctor can quantitatively asses the patient’s motor functions and adjust according to his/her treatment. This is something I’m very interested in because I would love to work with rehabilitation patients and those with bone tissue damage.

On a weekly basis I work to write a code that will analyze the variability of each dance movement for each dancer. My code was created to calculate the inter- and intra- variability of each dance piece. The beginning of the semester was spent collecting data with the dancers. Each week, when the dancers were available, we would take dancers into the studio and collect their motion capture data while they performed a dance piece at least ten times.

I was able to find that dancers who are categorized in the same skill level can show a high level of variability. Dancers that are categorized as seniors can be seen as having a generally high skill set, however between dancers, there is a high level of differences between skill sets. These levels can be calculated quantitatively.

Wednesday, March 21, 2018

URSP Student Benjamin McDowell Researches the Modification of Instrumentation to Emphasize the Detection of Volatiles

Volatile chemical compounds comprise the smells we experience on an everyday basis. My work, under the supervision of Dr John Schreifels, focuses on the modification of instrumentation to emphasize the detection of volatiles. Using mass spectrometry, individual volatile compounds can be identified and quantified, essentially an electronic nose. This semester’s focus aims to improve sensitivity by altering the interface between the low pressure mass spectrometer and ambient sampling conditions (atmospheric pressure). The modifications are designed to allow for implementation of electrospray ionization, an alternative to traditional ionization methods that works well for chemicals with a large vapor component. So far this has included assembling a detector capable of measuring ion flow through the aforementioned interface. Since high potentials must be applied to the sample for analysis, there are a variety of tunable parameters which can be experimented with. One of the most exciting parts of this is observing the vaporization that occurs with sufficient applied potential. Upon graduation this May I hope to pursue a graduate degree in Chemistry. A large portion of this will feature research similar to current projects. Generally, I am interested in the use of physical techniques in the analysis of molecular processes, which fits well with this project. One unexpected skill practiced in this project is 3D modeling. To better communicate various parts of the interface, I designed several of the components using the software Fusion 360. This allows for the individual parts to be assembled as they normally would, albeit with greater aesthetic than my machining skills can provide.

Tuesday, March 20, 2018

URSP Student Alexis Garretson Learns How to Design and Write an Agent-based Model in NetLogo

Ecological data is exciting because it’s messy. Messy data means scientists need to be more creative in finding ways to separate the signal and the noise. Though many biology and ecology students dislike math and statistics, my favorite part of thinking about ecological problems is finding mathematically creative ways to visualize and explore ecological data. I am particularly excited about using mathematical modeling and simulation to investigate complex, dynamic systems. I am interested in applying these tools to investigate ecological systems because ecological systems are inherently interconnected and stochastic systems that are highly dependent on a network of background factors. Modeling ecological problems allows you to formalize your logic in interesting ways and build experiments to test population-level phenomena. As with other complex systems, the process of modeling and simulation can be incredibly useful in producing prediction tools, defining prevention and control policies, and identifying high risk factors for contracting disease. Under the direction of Dr. Michael von Fricken, I am using data collected on Mongolian herders, ticks, and livestock to examine associations between tick-borne disease markers in humans and the number of livestock owned, the disease status of the animals, and the environmental factors. Through this project, I am learning how to design and write an agent-based model in NetLogo and am developing my spatial statistics skills. 

Long term, I am excited about utilizing complexity modeling and simulation to explore environmental data, particularly as it relates to socioeconomic relationships to biodiversity, disease spread, and ecosystem services. I plan to attend a graduate program this fall, and hope to one day become a professor. My experience with undergraduate research, particularly this project, has enabled me to build the quantitative skills necessary to succeed in a graduate research program. This semester, I am learning to code in python, to build an agent-based model from the ground up in NetLogo, and continuing to develop skills using R to evaluate data. Each week, I spend a portion of my time building these skills through reading, practicing my coding, and taking short courses. The second largest portion of time is spent reviewing the literature on agent-based modeling, the natural history of livestock and ticks, and tick-borne disease. Finally, I am starting to formalize and code my model. As the semester continues, a larger and larger portion of my time will be spent focusing on building and testing the model. At the end of the semester, I hope to have a finalized, publishable model that can help us better understand critical human health questions.

Monday, March 19, 2018

URSP Student Michelle Dickerson Quantifies Motion Variability in Technical Dance Movements

 My project is actually an extension of the team project that I was apart of over the summer. This project attracted my attention because of its ability to integrate elements from dance and bioengineering. Because I used to be a dancer, diving more into the performing arts and using it to study bioengineering became very exciting for me. I became more interested

My current project is based on quantifying motion variability in technical dance movements. This involves studying and understanding dancers’ ability to perform sophisticated and intricate dance movements while changing their spatial orientation with little to no variability at all. On a weekly basis, I analyze data that was collected using the Optitrack Motion Capture system located in George Mason’s School of Dance. The data that I analyze includes looking at dancers who are performing a skilled dance sequence during multiple trials in untrained and trained spatial orientations. From this data, I observe the consistency of their anatomical alignment during specific movements in the sequence and how this varies from orientation to orientation.

This is directly related to my long-term goals because it opens the door for further understanding of neural processes in the brain. From the data analysis that I have been doing, I have learned that dancers provide insight on how new patterns of neuron activity are developed over time. This is very important as I plan on continuing to study motor learning and adaptation in the future. From observing these dancers, over periods of time, it seems that the brain is able to adapt fairly quickly to new motor skills that are learned. This could potentially lead to better ways of treating patients with neurodegenerative diseases or with neurocognitive impairments.

From this research, I have learned that our brain is such a complex system, yet, through repetition, it is able to create new patterns of activity in the neurons, which leads to more complex motor skills. This has sparked an interest for me to eventually start to dive more into studying neuron activity in the motor and sensory cortex in the brain. Without the involvement of OSCAR, I would have never discovered my research interests that I plan on pursuing long term.
in dancers and their ability to provide novel insight on the complex motor skills that they demonstrate.