Interdisciplinary – Page 43 – UROP Spring Symposium 2021

Interdisciplinary

Floating LiDAR development project

Emma Remien Pronouns: she/her/hers Research Mentor(s): Tae Kim, PMO Consultant Research Mentor School/College/Department: Copenhagen Offshore Partners, Presentation Date: Thursday, April 22, 2021 Session: Session 1 (10am-10:50am) Breakout Room: Room 8 Presenter: 3 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Tae Kim, Emma Remien, Corinne Pita Research Method: […]

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Floating LiDAR Development Project

Corinne Pita Pronouns: She/Her/Hers Research Mentor(s): Tae Kim, PMO Consultant Research Mentor School/College/Department: Copenhagen Offshore Partners, Presentation Date: Thursday, April 22, 2021 Session: Session 1 (10am-10:50am) Breakout Room: Room 8 Presenter: 3 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Tae Kim, Emma Remien, Corinne Pita Research Method:

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Investigating heme acquisition properties and corresponding conformational changes of heme oxygenase 1

Kelly Deng Pronouns: she/her Research Mentor(s): Stephen Ragsdale, Professor Research Mentor School/College/Department: Biological Chemistry, Michigan Medicine Presentation Date: Thursday, April 22, 2021 Session: Session 1 (10am-10:50am) Breakout Room: Room 8 Presenter: 4 Event Link Abstract Authors: Kelly Deng, Liu Liu, Stephen Ragsdale Research Method: Laboratory Research

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Human Rights and Indigenous Rights in Africa

Throughout the world, indigenous peoples’ ways of life are being threatened due to surrounding governments and economic conquests. In 2007, the United Nations signed the Declaration on the Rights of Indigenous Peoples which states that indigenous peoples have both individual and collective rights to their culture and identity along with other human rights such as education, healthcare, employment, language, etc. It also prohibits the discrimination of indigenous peoples and allows indigenous peoples to continue their traditional ways of life. Despite all of this, indigenous people’s rights that were outlined in this document are being violated. This project investigates the current violations against the rights of indigenous peoples in Africa and the implications on certain indigenous groups. By researching articles that describe these violations and creating case studies that summarize numerous violations across the continent, this project aims to create an interactive website that documents these violations in a way that is easy to access and understand. The purpose of this project is to present these violations to the United Nations in order to get justice for these indigenous populations.

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Data Gathering Data Analysis Toward Better Air Quality Outcomes in SW Detroit

In 2019, a resident of southwest Detroit called SDEV to ask for help with air pollution that was getting into her house. The problem was so bad that she had to change furnace filters monthly, which were completely caked with black soot. SDEV visited the resident’s home to learn more and received a furnace filter from the resident. My project involved launching a survey of residents to see how many are experiencing similar indoor air quality concerns and quantifying the information to present at SDEV’s annual member’s meeting and to the City of Detroit’s Council meeting. Using a google form, the survey was created with feedback from University of Michigan Public Health experts and other professional resources. With the internet, phone, and physical canvassing efforts, data was collected from 48 residents. We have found a majority of residents surveyed do experience some kind of air quality problems inside the house (grime, soot collecting on the walls, furnace filter color black, etc.) persisting for at least over a year. SDEV intends to use this data to push for real change and bring more resources to address the problem in people’s homes. By making the data accessible to the public, government decision-makers, and others who can bring resources, SDEV will work with community members and others to address the problem of indoor air quality. We have and will continue to connect with community members to bring awareness to the resources that can mitigate the impact of pollution at home. This work aligns with the recommendations of the community-based participatory research initiative Community Action to Promote Healthy Environments (CAPHE) facilitated by University of Michigan with SDEV and other local partners.

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Political Beliefs and Bias in Social Network Formation

This project investigates how social networks change during divisive political discussion. In a behavioral experiment, we place student participants in a random communication network with up to 20 others. Participants discuss campus social issues over the course of several rounds. At each round, participants are exposed to differing opinions of their connections and make decisions to “rewire” their network, or to add, drop, or request new social connections to communicate with in the next round. We measure how individuals make these network decisions at both the individual and group level. We also experimentally manipulate a social cue that reveals the closeness of another person in relation to the participant. Experimental sessions are conducted remotely and anonymously, simulating interaction as it might occur on social media. Our data help understand the biases that lead people to form echo chambers, which may contribute to downstream consequences of biased information sharing, misinformation spread, and misbeliefs about public opinion.

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Political Bias in Social Network Formation

This project investigates how social networks form. Through behavioral experiments, students observe how political and social beliefs influence social network formation and the downstream consequences of selecting into a biased information-sharing environment. This might include general political reasoning, misinformation spread, and ingroup bias. Students work closely with the research mentor and project manager to learn about research design in the social sciences and gain valuable experience collecting data from human participants. Student responsibilities have included reviewing background literature, entering and maintaining data, and conducting internet searches. Students are also trained in analyzing the data for presentation. Experimental sessions are conducted remotely, and students help plan, schedule, and organize sessions.

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The role of FADD in G1 to S cell cycle transition

Our research focuses on the role of FADD in the cell cycle. FADD is known to play an important role in cell death, signaling the cell to enter apoptosis. We are proposing another role of FADD in cell cycle regulation, specifically in the transition of cells from G1 to S phase. To evaluate the role of FADD we observed the level of known factors in cell cycle regulation. Certain proteins, such as Cdt1 and Geminin are only active at specific times of the cell cycle. By adding reporters to these proteins, we were able to track what stage a specific cell was in. We used live-cell microscopical imaging to track the cells as they progressed through the cell cycle. Cells will appear as different colors based on the amount and the type of protein they are expressing. In G1, cells will appear green, in S phase they will appear red, and cells in M/G2 phase will appear orange. The results from these experiments have shown that in cells where FADD is silenced, G1 to S transition is delayed for up to 22 hours. Some cells never pass the G1 to S checkpoint and are stuck in G1 phase. These are very promising results and line up with the assumption that FADD plays a critical role in cell cycle transition. The next step in our research is to collect more data on factors that might influence and regulate FADD. Additionally, we want to examine the effectiveness of several inhibitors, developed as cancer drugs, and determine if, when FADD is blocked, they lead to better outcomes.

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Prediction and Assessment of Acute Respiratory Distress Syndrome: Effects of Assumptions in Imputation Methods

Acute respiratory distress syndrome (ARDS) is a life-threatening lung condition that is under-diagnosed in the clinical setting. With a 43% hospitalized mortality rate, it is critical that diagnosis is made in a timely manner for ventilation strategies to be instituted. The Biomedical and Clinical Informatics lab at U-M has been developing a real-time clinical decision support system to detect ARDS through machine learning methods, specifically a modified support vector machine. A clear distinction from other ARDS-related support systems is the use of “privileged information” “” data accessible at the time of training themachine learning model but which is not available in deployment. In the context of this project, we define privileged information to consist of CT scans, which are required for ARDS diagnosis. Such information is not available to the clinician during the early period of a patient’s stay. Therefore, by incorporating such privileged information, we expect the model to lead to faster ARDS diagnosis in clinical practice. This research investigates the electronic health record (EHR) pipeline of the model. With inconsistencies and missing values, some EHR features are absent from one patient while present in another. We aim to improve the model’s accuracy in ARDS detection by testing a unique data imputation method against different machine learning models and settings. Specifically, missing values will be imputed under the assumption that data is not missing at random but as a result of the clinician’s decision that the patient had optimal health in such cases. This method is implemented by imputing data taken from the Michigan Medicine’s established reference ranges when possible. The proposed method will be compared with different machine learning models and feature reduction techniques.

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Financing and Counter-Financing of Violent Non-State Actors Project

I am working on data collection for the Countering the Financing of Violent Non-State Actors Project. The goal of the project is to develop the first comprehensive database of actions that obstruct the finances of terrorist groups in hopes to measure the efficacy of these actions and whether or not certain counterinsurgent actions either harm or embolden terrorist groups. This project is one of the first of its kind. The data used for this database is obtained from newspaper and online article entries regarding the different groups from the years 1990 to 2018. The articles are accessed on NexisUni then codified by a team of coders. Different coders code the same groups in order to ensure reliability of the data. There are no results yet for the project, as it is projected to take more time to complete the database. When the database is nearing completion, statistical analysis of the data will be performed in order to determine the efficacy of certain counterinsurgent actions.

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