Changing Gears

Bioinformatics study on protein modeling

Determining the structure of proteins can be a long expensive task. However, using new applications of deep learning ai it is possible to formulate a protein structure using its sequence. Through many supporting applications the final goal is becoming more attainable.

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El Problema con el Marianismo: ERI and Intragroup Discrimination in Latinx Women

juliatok

Past research asserts that Latinx children receive differential treatment and socialization based on their gender, and this likely relates to their ethnic-racial identity (ERI) in adulthood (Raffaelli & Ontai, 2004). The present study aims to understand the relationship between Latinx adult women and how they perceive discrimination. The study also examines other ways that discrimination and ERI may affect Latinx women. This study focuses on the topic of marianismo (defined as a gender norm in Latinx culture that emphasizes familism, dependency and submissiveness in women (Sanchez, Smith & Adams, 2018) as opposed to machismo) and the ways in which traditional values and intragroup discrimination towards women in the Latinx community affect self-esteem and other mental health factors. Marianismo also encourages passivity in women while machismo emphasizes assertiveness in men (Nuñez et al., 2015). Data were collected using a Spanish-language Qualtrics survey completed by a large sample of adult Latinx women from the United States. I hypothesize that Latinx men will score more positively on measures of ERI affirmation and resolution than women and will likely have higher self-esteem and less depressive symptoms. Measures used for this Spanish-language study include a Self-Esteem Measure, a Depressive Symptoms Measure, and an ERI measure. The ERI measure assesses the topics of ERI exploration, affirmation, and resolution (Douglass & Umaña-Taylor, 2015). Projected results provide insight into the relationship between Latinx women’s ERI and their mental health, while also delving into the complexity of intersectional identities as they pertain to overall well-being. Key words: Latinx, marianismo, Ethnic-Racial Identity, depressive symptoms, self-esteem, gender, discrimination

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On the Crossroad of Gendered Experience: Women, Memory, and Revolution

mkhanam

Experience and narratives of violence and injustice within pre-revolutionary, revolutionary, and post-revolutionary societies shape the memory of people who live them. We seek to understand the role memory plays in the context of protests and how people employ it to achieve justice and delegation. Our goal is to tie the concept of memory with women in revolution to show how it lends insight to their gendered experience and their demands for rights. By collecting data from different perspectives and reviewing existing literature on memory, we aim to reflect on the concept of memory using diverse frames of reference. The findings indicate a fluidity in how people employ their memory and illustrate a strong correlation between gender identity and women’s fight for justice. How does individual memory impact collective memory in the post-revolutionary setting? What is the role of memory in helping individuals and community members face traumatic experiences of injustices and how do they use these memories to question the present and to predict a better future in a similar context.

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Application for Cardiac Signal Visualization and Annotation

stefanhg

Massive amounts of data are being generated at a high velocity in the medical industry, at a rate and dimension that humans cannot catch up understanding them. Machine learning (ML) has the potential to analyze the medical time series data to support physicians in clinical decision making. However, in order to build useful machine learning (ML) algorithms, it is important to have annotated medical data set that can be used to train ML models. This project at the start is about building a viewer for surface ECG and intracardiac electrogram signals acquired during cardiac ablation procedures. Building the framework at early stages to support basic functionality is engineering-oriented with design decisions. We are currently developing a web application in Python. Specifications were created based upon the needed functionality of the application after talking with multiple cardiologists. The next step would be inviting medical students and cardiologists to use the app and gather feedback. Eventually, we want to build a platform/infrastructure that allows for development and evaluation of ML algorithms, and to improve cardiovascular disease management and treatment. By working with cardiologists and intelligent algorithms, we want to build a tool that can quickly review, search, annotate and analyze signals at high throughput. The end goal is that researchers across the country can use our tool to review their own data, and also deploy a real-time graphical decision support tool to assist cardiac procedures.

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Whole Health Educational Resource Development and Evaluation for Veterans and VA Staff

heantal

The Veterans Association (VA) is one of the largest integrative healthcare systems in the country. Its success in patient outcomes is contributed to the widespread practice of Whole Health in the VA system. Whole Health is known as “Personalized, Proactive, Patient-driven Care” and it focuses on several areas of health and well-being while empowering the patient to take an active role in their healthcare alongside providers. The impact of Whole Health and use of its techniques and practices among veterans and patients who receive this healthcare is not widely known. This study aims to assess how many skills and practices from the Whole Health system are being used and applied by patients (Veterans) in their everyday lives. Specifically, questions are designed to reflect practices from the 8 modalities of Whole Health. To conduct our test, we created an online survey using Qualtrics and distributed it among colleagues, students, patients, and veterans in association with the VA Ann Arbor. We collected basic demographic information including sex, age range, and Veteran status and asked a series of questions designed to assess the practice of mindfulness and other techniques among respondents and also to assess how much of the Whole Health practice they have experienced. At the time of publication of this abstract, the data has been collected and preliminary analysis is in process. Specific, detailed, and final results will be available at the time of the Symposium presentation.

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Examining the co-seasonality of historical respiratory infections

xiaziy

Scarlet fever and diphtheria are two historical infectious disease in 20th century. It has been shown that the occurrence of influenza outbreak has seasonal pattern.The occurrence of Scarlet fever and diphtheria also have this characteristics. We want to fins such pattern based on the data gained from each states of the United States from 1928-1951 for scarlet fever and 1928-1948 for diphtheria. Though one is bacterium while the other is virus, researchers found there is link between them. In order to understand these two pathogens better, we plot many different kinds of graphs of these two separately and together, weekly and yearly in R, based on the weekly data of number of infected people in the United States. We will also plot some wavelets and cross-wavelets to find the co-seasonality within states and between disease. The expected result will be that some patterns between these two pathogens that deserve further research and study do exist. Though these two are historical infectious disease, studying these two pathogens may provide us with more information on the potential link between them and many other disease, which will benefit other disease study or even help find potential method to forecast other diseases forecast and take them under control.

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Demographic Impacts of Covid-19 in the US and Europe

williano

The Covid-19 pandemic has had disproportionate impacts across the globe. When comparing the impact of the pandemic on different nations, researchers rely on metrics such as national excess mortality which often fail to capture demographic differences between populations. This study aims to construct a comparative framework of excess mortality in the US and select European countries which accounts for age and sex. In this context, excess mortality is the difference between the observed number of deaths during the 2020 Covid-19 pandemic from the expected number of deaths based on historical data. To construct this framework, monthly mortality data from 2015-2019 segregated by age and sex was analyzed from the US and EU. This data was used to estimate the mortality of specific age and sex cohorts by country, which was compared to the observed monthly mortality of those cohorts in 2020. When compared to the reported deaths attributed to Covid-19, a robust and nuanced comparison of the relative impacts of Covid-19 in the US and EU is possible.

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