Student Presentations

Uroob Haris: Light-Mediated Microprinting

https://youtu.be/QE7l6JbfxCk

Techniques for nanofabrication and high resolution lithography are increasingly in demand owing to applications of nanomaterials in technology and therapeutics. This poster will cover research towards a microprinting technique that combines chemistry with structured light patterning to achieve micrometer resolution pattern printing on solid surfaces.

Uroob Haris
Program:
 Chemistry
Faculty Mentor: Alex Lippert

Sara Hatcher (U): Gait Mechanics with Single Leg Elongation

Winner: Simmons (Undergraduate)

https://youtu.be/x2k9DcOZmww

It is common thought that structural asymmetries result in a running disadvantage, and that anatomical and mechanical symmetry is the preferred condition. Our opposition to this stance began in observation of Usain Bolt, who exhibits a 13% force difference in striking with his right versus left leg due to a leg length difference. But there are few studies on gait asymmetries to explain this phenomenon: how can the fastest man in history be asymmetrical? To investigate this, we have created a study in which we lengthen the right leg of athletes and observe the response of both legs. We propose that the body compensates by altering vertical force and contact time in the opposing limb, resulting in an adjustment to both legs. Our subjects ran a control and experimental condition where an 27mm insert was attached to the right shoe at 3, 4, 5, and 6m/s. We hypothesized that the lengthened leg would have a decreased vertical ground reaction force and increased contact time and the unlengthened leg would have an increased vertical ground reaction force and decreased contact time. We further hypothesized that the two-leg average would not change between conditions. We determined both hypotheses to be correct. These findings show that asymmetries are not an inherent disability, but rather, functional asymmetries can increase the body's effectiveness in motion.

Sara Hatcher
Major: Applied Physiology and Health Management
Faculty mentor: Peter Weyand

Matthew Heaney (U): Are azo pigments really azo pigments? Structural and spectroscopic characterization of β-naphthol reds

https://youtu.be/-mYpdUdu15o

Naphthol reds are a group of widely used pigments with prominent historical, commercial, and cultural significance and are frequently characterized as part of a wider group called azo pigments. Azo pigments have two fundamental properties, they have the vibrant colors and low solubilities characteristic of pigments, and the presence of an azo group within their structure. The latter property, however, as other studies have found is oftentimes completely unfounded. Some of these pigments do not even possess azo groups at all, rather they possess a similar, but fundamentally different group known as a hydrazone group. In other cases these pigments can possess both the azo and hydrazone forms at the same time or undergo an enol/keto tautomeric shift under certain conditions. There are however still many common pigments which are still marketed and referred to as azo pigments with frequently little to no evidence. In this study by using the capabilities afforded to us by X-ray diffraction techniques as well as Rietveld refinement it was possible to determine not only the presence of the hydrazone group but also to elucidate the crystal structures of two pigments. Ultimately these results can fundamentally change both how we refer to these pigments from now on and how these pigments may be better used and applied in the future.

Matthew Heaney
Major: Chemistry; Minor: Geology
Faculty mentor: ‪Tomče Runčevski‬

Sabrina Hetzel: Modeling the Spread of COVID-19: A University Study

https://youtu.be/1XW8y8Yz_f4

Understanding, containing, and eradicating COVID-19 is an enormous problem for the scientific community to tackle, and there are myriad facets that need to be solved. Our group in particular wishes to explore the viral spread in a university setting since it is an ideal climate for a COVID-19 outbreak. Up until recently, we aimed to understand how initial mass testing of the student body at the start of the semester, and continual testing throughout the semester reduces the spread of the virus. Looking into the future, we wish to explore the conditions and implications for a nontrivial equilibrium state for the infected population.

Sabrina Hetzel
Program: PhD in Mathematics
Faculty mentor: Alejandro Aceves

Rhonda Hodge: Health Disparities and Covid-19 in Underserved Communities

https://youtu.be/KH5974xiJ3M

"ABSTRACT In the United States, COVID-19 has infected over 27 million people; more than 456,000 have died. Like most social, financial, and health emergencies, Black, brown and Indigenous communities have been disproportionally affected by this current pandemic. COVID-19 laid bare the underlying systematic racism that affects these communities. Issues of inadequate healthcare, low wages, dangerous workplaces or conditions, blue collar jobs, and pre-existing medical conditions such as high blood pressure, diabetes, heart disease, and obesity are contributing factors. Now with various treatments —even a vaccine, the reality of the data still points out the disparities in these communities. Research shows that communities of color are lagging behind in having access to the vaccines. Past discriminatory practices, particularly in Black communities have deep negative impacts, rendering these communities not only more vulnerable to the virus, but also to avoid the vaccine. Their concerns must be addressed to help develop a sense of trust and acceptance for available treatments and vaccines. On the ground relationships, relying on trusted community partners such a churches, medical personnel, and fraternal organizations can be utilized. With a focused approach to what is a long-standing problem, communities of color can be successful in their fight against Covid-19."

Rhonda Bellamy Hodge
Program: Master’s of Liberal Studies
Faculty Mentor: Kate Montgomery

Sydney Holder (U): Descriptive Statistics for the Explanatory Factor Analysis of the MMaRS Home Use Survey

https://youtu.be/2TMH6LZCgrU

An analysis of the explanatory factor analysis for MMaRS Home Use Survey. The research was rooted in finding whether the Home Use Survey was a reliable way of measuring at home spacial reasoning.

Sydney Holder
Majors: Applied Mathematics, Statistics, Data Science
Faculty mentor: Leanne Ketterlin Geller

Matthew Hutnyan (U): Alexithymia and Self-Referential Processing in a Healthy Population

Co-authors: Cecile S. Sunahara, Benjamin A. Tabak

https://youtu.be/HjsClBad9bQ

Success in the social world is said to be contingent on how effectively one can decipher the mental and emotional states of others. A growing body of evidence links this ability, known as social cognition, with two psychological constructs: alexithymia – difficulty identifying and describing one’s own emotions – and self-referential processing (SRP) – the process through which we use knowledge of the self to interpret information. This study (n = 396) set out to directly examine the relationship between alexithymia and SRP in a sample of non-clinical individuals. Multilevel modeling was utilized to examine differences in accuracy between words presented in the “self” condition versus the “physical” condition, and then to examine whether alexithymia moderated the effect of referent condition when controlling for age, gender, and depressive symptoms. Results indicated that participants were more accurate at recognizing words that were presented originally with a “self” referent than words presented with a “physical” referent (b = -.39, 95% CI [-.41, -.37], p < .001) and that levels of alexithymia were linked with SRP task accuracy, such that as levels of alexithymia increased, accuracy in the “self” condition decreased. These findings establish a link between alexithymia and SRP at the behavioral level for the first time.

Matthew Hutnyan
Majors: Psychology, Health and Society; Minors: Neuroscience and Cognitive Science
Faculty mentor: Ben Tabak

 

Brooke Istas: Literature Review of Adult Mathematics Anxiety in the United States

https://youtu.be/wWZ2d6hjtK8

Students who have a higher level of mathematics anxiety seem to perceive mathematics as a negative experience. What key features of adults are influenced by their own mathematics anxiety and/or mathematics avoidance? By using eleven peer-reviewed studies, within the last five years, to synthesize literature on adults in the United States, two themes appear. The first theme is situated around a student's perception of mathematics. Students who have a higher level of mathematics anxiety seem to perceive mathematics as a negative experience. The second theme centers around the impact of stress on a student who is learning mathematics. A few of the studies did indicate a correlation between the higher the level of stress to more mathematics anxiety was reported. One of the studies used electroencephalography (EEG) to measure stress on the brain. This review will look at these studies for understanding of the current research on mathematics anxiety and identify areas for further research.

Brooke Istas
Program: PhD in Education
Faculty mentor: Candace Walkington

Shuang Jiang: BayesSMILES: Bayesian Segmentation Modeling for Longitudinal Epidemiological Studies

Winner: Biostatistics (Graduate)

Co-authors: Quan Zhou, Xiaowei Zhan, Qiwei Li

https://www.youtube.com/watch?v=hac49ntMlLQ

The coronavirus disease of 2019 (COVID-19) is a pandemic. To characterize its disease transmissibility, we propose a Bayesian change point detection model using daily actively infectious cases. Our model builds on a Bayesian Poisson segmented regression model that 1) capture the epidemiological dynamics under the changing conditions caused by external or internal factors; 2) provide uncertainty estimates of both the number and locations of change points; and 3) has the potential to adjust for any time-varying covariate effects. Our model can be used to evaluate public health interventions, identify latent events associated with spreading rates, and yield better short-term forecasts.

Shuang Jiang
Program: PhD in Biostatistics
Faculty mentor: Xiaowei Zhan

Xiaoxian Jing: Parton distributions, nuclear deeply inelastic scattering, and electroweak precision measurements at the LHC

Winner: Combined-STEM (Graduate)

https://youtu.be/Bkl2eIdWpSg

Parton distribution functions (PDFs) for quarks and gluons inside the proton are needed for predicting a variety of processes at the LHC, including Higgs boson production and searches for new physics beyond the Standard Model. PDF parametrizations are obtained by fitting a large number of cross-sections from many experiments at different (x,Q^2). In the global analyses of PDFs by CTEQ collaboration, we find that deeply inelastic scattering experiments on nuclear targets provide important constraints on combinations of PDFs relevant to the LHC electroweak precision measurements. What is the role of these experiments in the LHC era, and how influenced are they by nuclear effects? I explore this complex question using a new statistical indicator called "PDF sensitivity" for analyzing the impact and compatibility of experiments in a PDF fit.

Xiaoxian Jing
Program: PhD in Physics
Faculty mentor: Pavel Nadolsky

Javad Jomehpour: Listen to Scooter Riders

https://youtu.be/Fw6sCnEMRPc

In this study, app store reviews from two major micro-mobility companies are investigated using machine learning techniques to identify the factors that influence rider satisfaction. The Latent Dirichlet Allocation model is applied to over 12,000 rider-generated reviews to identify twelve topics discussed within the reviews. These topics cover areas such as pricing, safety, customer service, refund, payment, app interface, and ease of use, to name a few. Using logistic regression, the most significant factors influencing rider satisfaction were identified. Moreover, name-based gender prediction analysis is employed to identify rider gender and then discover differences in review content and factors of satisfaction across gender. Findings contribute to the existing literature by demonstrating the use of app store reviews in a transportation mobility study. The development of a method to assess factors contributing to user or rider satisfaction offers the ability to evaluate e-scooter rider needs and barriers to access and participation.

Javad Jomehpour
Program: PhD in Civil and Environmental Engineering
Faculty mentor: Janille Smith-Colin

Konstantinos Kalfas: The dynamics of utility poles by considering soil-structure interaction (SSI)

Winner: Civil and Environmental Engineering (Graduate)

Co-author: Nicos Makris

https://youtu.be/qbSOL76aK-8

Motivated from the large number of transmission and distribution utility poles that experience excessive vibrations during wind storms, this work sheds light to the eigenvalue analysis of a partially embedded flexural, prismatic column with embedded length, L, and exposed length, h, and accounts for the interaction with the soil of its embedded portion. The presentation will show that the dynamics of a partially embedded prismatic column depend solely on the embedment ratio, ε = L/h and a dimensionless stiffness that expresses the relative stiffness between the soil surrounding the embedded length (level of fixity) and the exposed portion of the flexural column. A partially embedded prismatic column exhibits a finite number of eigenmodes that are lower than its rigid-body mode; while, the associated eigenfrequencies are lower than the corresponding eigenfrequencies of the fixed-end cantilever. For a typical value of the embedment ratio ε = L/h = 0.15, the study uncovers that for any eigenmode n > 3, of the fixed-end cantilever, the partially embedded, prismatic column exhibits n + 1 eigenmodes. These rich dynamics result from soil-structure interaction and are associated with the way that the flexural patterns of the partially embedded column emerge from the ground.

Konstantinos Kalfas
Program: PhD in Civil and Environmental Engineering
Faculty mentor: Nicos Makris

Chengyu Ke: Iteratively Reweighted Group LASSO Based on Log-composite Regularization

Co-authors: Miju Ahn, Sunyoung Shin and Yifei Lou

https://youtu.be/6f52fbME99A

This paper addresses supervised learning problems with grouping information on model coefficients given a priori. We focus on non-overlapping groups such that coefficients for each disjoint group shall be simultaneously either zero or nonzero. To deal with such group sparsity structure, we introduce a novel log-composite regularizer, which can be minimized by an iterative algorithm. In particular, our algorithm iteratively solves for a traditional group LASSO problem that involves summing up the L2 norm of each group until convergent. By updating group weights, our approach enforces a group of smaller coefficients from the previous iterate to be more likely to set to zero, compared to the group LASSO. Theoretical results include a minimizing property of the proposed model as well as the convergence of the iterative algorithm to a stationary solution under mild conditions. We conduct extensive experiments on synthetic and real datasets, indicating that our method yields superior performance over the state-of-the-art methods in linear regression and binary classification.

Chengyu Ke
Program: PhD in Operations Research
Faculty mentor: Miju Ahn

Lisa Kim (U): Measuring Nitric Oxide Metabolites as a Biomarker of Concussion

https://youtu.be/bHQxBQYfZRk

A concussion is a traumatic injury that affects brain function. Although sports-related concussions are so common, the physiology of concussions is still not yet fully understood. Nonetheless, several types of research are focusing on this study to explain the physiology of concussion and identify possible biological markers. Since blood vessels in the brain behave similarly to those in the other parts of the body, one can further study the brain and the concussion by measuring the blood pressure and flow. With this idea, a research study has found nitric oxide (NO) as an important biological marker for concussion, indicating either possible inhibition or stimulation of nitric oxide synthase (NOS) in our body. By incorporating this information into my project, I have performed Griess assay to measure nitrate and nitrite in blood samples extracted from SMU athletes who have experienced concussions.

Yujin Lisa Kim
Major: Biochemistry; Minor: Chinese
Faculty mentor: Alex Lippert

Tryna Knox: Reinventing Home, How Middle School Leaders Conceptualize STEM in the Context of Structured Program Implementation

https://youtu.be/7CyzzNbTFuw

The purpose of this research was to examine how middle school leaders conceptualize STEM education program implementation and to more fully understand how their leadership practices are enacted within their situational context of an intensive structured STEM education program, subsequently referred to as the STEM Academy. The STEM Academy, a four-year project launched in 2016 was designed to promote STEM interests by developing teachers and leaders through intensive summer academies and providing coaching support throughout the school years. Findings reveal that school leaders conceptualize STEM education in similar ways across different campuses and describe challenges and barriers faced while navigating internal and external expectations during implementation of the STEM Academy. While some common themes emerged that led to interpretations across the four cases, each leader contributed a unique lens and perspective and no single, absolute, truth was ascertained from this analysis.

Tryna Knox
Program: PhD in Education
Faculty mentor: Leanne Ketter-Geller

Nancy Le: Moderated Mediation Analysis with Dichotomous Outcome and/or Mediator Variables

https://youtu.be/s8srz0NfmuA

In this presentation, I will provide a brief history of moderated mediation analysis, introduce the types of moderated mediation models, and explain how moderated mediation models work with two types of variables: continuous mediator/outcome variables and categorical mediator/outcome variables. Moreover, I will explain why we need to treat categorical outcome variables differently, and provide an example using moderated mediation model with dichotomous outcome variable from the literature.

Nancy Le
Program: PhD in Education
Faculty mentor: Akihito Kamata

Wren Lee (U): Gay & Greek: Designing for LGBTQ Fraternity and Sorority Members

https://youtu.be/_acdtoh4b6c

College is a time of exploration and growth for many individuals. It is especially important for LGBTQ folxs; for some LGBTQ folxs, college is the first time they can explore their LGBTQ identities free of judgment. Others seek community and find it within fraternities and sororities. Yet, traditional fraternities and sororities are notoriously not LGBTQ friendly. These organizations promote a hypermasculine, heteronormative, homophobic, and transphobic environment. For LGBTQ Greeks, the situation can be emotionally taxing. Through this project, the investigators aim to deepen their learning about these experiences to build solutions to help LGBTQ Greeks feel confident in their LGBTQ identities in Greek spaces. In the long term, the investigators aim to learn more about how to develop systems to protect and empower LGBTQ individuals in anti-LGBTQ spaces. They will learn about the Greek experience for LGBTQ members at Southern Methodist University and co-create a solution for their intersectional needs. They will employ human-centered design methods to help the LGBTQ Greek community feel comfortable in spaces they might not typically occupy.

Wren Lee
Major: Creative Computation; Minors: Human Rights and Women and Gender Studies
Faculty mentor: Dustin Grabsch

Bo Li: Chemiluminescent H2S and peroxynitrite probes synthesis

Co-authors: Lucas Ryan, Briley Bezner and Husain Kagalwala

https://youtu.be/LHoCo4omytM

Hydrogen sulfide (H2S) and peroxynitrite are important biological signaling molecules that have been recognized alongside nitric oxide and carbon monoxide which could impact multiple physiological functions. To detect them, there has been a focus on developing fluorescent probes to target particular analytes; however, fluorescent probes lack sensitivity and depth penetration due to background autofluorescence and light scattering. Chemiluminescence does not require light excitation, which greatly reduces the amount of autofluorescence and photoactivation. In order to detect them in living systems with high sensitivity, a series of sterically stabilized 1,2-dioxetane chemiluminescent reduction-reaction based hydrogen sulfide probes have been synthesized.

Bo Li
Program: PhD in Chemistry
Faculty mentor: Alex Lippert

Jonathan Lindbloom (U): A Bayesian Gaussian Process Model for COVID-19

Winner: Undergraduate Top 3
Winner: Dedman III (Undergraduate)

https://youtu.be/q6II2XvecSM

We present the Bayesian approach to parameter inference for SIR ODE models using Markov Chain Monte Carlo (MCMC) methods, along with its computational implementation using the PyMC3 probabilistic programming library. We show how changes in the transmission rate over time can be captured by change-point models. However, these change-point models fail to learn the underlying dynamics of the time-dependent transmission rate. To overcome this pitfall, we demonstrate how using Gaussian processes to place a functional prior over the time-dependent transmission rate does a better job at characterizing uncertainty in forecasts. Our approach removes the need to specify priors over change-points, captures uncertainty in the dynamics of the effective reproduction number, and flexibly fits county or state-level data without modification. To validate our model, we evaluate the accuracy of our model’s forecasts using scoring rules and compare its performance with that of other competing models submitted to the Center for Disease Control (CDC).

Jonathan Lindbloom
Majors: 
Mathematics, Finance
Faculty Mentor: Alejandro Aceves

Lizuo Liu: Multiscale DNN for Stationary Navier Stokes Equations with Oscillatory Solutions

Co-authors: Bo Wang, Wei Cai

https://youtu.be/VBxKOu0j2ug

In this talk, we develop new multi-scale deep neural network to compute oscillatory flows for stationary Navier-Stokes equation in complex domains. The multiscale neural network is the structure that can convert the high frequency components in target to low frequency components thus accelerate the convergence of training of neural network. Navier-Stokes flow with high frequency components in 2-D domain are learned by the multiscale deep neural network. The results show that the new multiscale deep neural network can be trained fast and accurate.

Lizuo Liu
Program: PhD in Mathematics
Faculty mentor: Wei Cai

Jiapeng Liu: Solve inverse problem with physics assisted Deep Learning

https://youtu.be/xDllNa3txfg

Deep learning has been widely used for solving ill-posed inverse problem in the past few years. With sufficient training data, data-driven deep neural networks can serve as good approximation of mapping between input and solution. However, training set can be expensive to obtain, and consequentially, the network may not generalize well. Starting with the Deep Image Prior by Ulyanov et al, convolutional neural networks are proven to be strong prior that can solve inverse problems without training data. Recent works have explored the notion of using dataset to supervise the training process, physics priors can be added to the network architecture for even stronger constraints, and the input will be self-supervising the network. By iteratively updating the weights of the network the output generated by the network is forced to satisfy the physical model and that converges to the correct solution.

Jiapeng Liu
Program: PhD in Electrical Engineering
Faculty mentor: Prasanna Rangarajan

Cameron Matson: Benefits of MIMO in 3D UAV-to-UAV topologies

Winner: Electrical Engineering (Graduate)

Co-authors: Syed Muhammad Hashir, Sicheng Song

https://youtu.be/Pf7At2Bz_AU

Unmanned Aerial Vehicles (UAVs) often lack the size, weight, and power to support large antenna arrays or a large number of radio chains. Despite such limitations, emerging applications that require the use of swarms, where UAVs form a pattern and coordinate towards a common goal, must have the capability to transmit in any direction in 3D space from moment to moment. In this work, we design a measurement study to evaluate the role of antenna polarization diversity on single-antenna and multi-antenna UAV systems communicating in arbitrary 3D space. To do so, we construct flight patterns where one transmitting UAV is hovering at a high altitude (80 m) to focus on the impact of heterogeneous drone-based antenna polarization without multipath effects. Then, a receiving UAV hovers at 114 different positions that span an ellipsoid surrounding the transmitting UAV with a radius of approximately 20 m along equally-spaced elevation and azimuth angles. To understand the role of diverse antenna polarizations and multiple antennas, both UAVs have a dedicated radio chain to a horizontally-mounted antenna and a dedicated radio chain to a vertically-mounted antenna, creating four wireless channels. With this measurement campaign, we seek to understand how single-antenna systems could optimally select an antenna orientation or multi-antenna systems could have the greatest gains.

Cameron Matson
Program: Master’s in Electrical Engineering
Faculty mentor: Joe Camp

Emily McClelland: Why men get higher than women: The biology and mechanics of sex differences in jumping performance

https://youtu.be/-IJPdvT7QiQ

Men clearly outperform women in athletic events that require moving their body through space. However, the magnitudes of the difference varies by event. For Olympic running events men run 10-12% faster than women in events ranging from 100 meters to the marathon. In contrast, for the high jump men outperform women by nearly twice the running offset (20%), and in the conventional countermovement jump the sex difference is greater yet at 25%. These observations suggest an interaction between event mechanics and bodily differences between males and females. Running differences are well explained by close alignment between the additional proportion of the female body comprised of fat (+10%) with the 11% difference in performance. However, it is unclear why jumping performance differences are so much greater. Jumping differs from running in that performance depends largely on a single powerful contraction on take-off. Here, we evaluated the possibility that due to the mechanical differences between running and jumping, sex differences in height also factor into the sex difference in jumping performance. Results to date suggest that sex differences in height and body composition do account for the male-female jump differences. Therefore we conclude that sex differences in athletic performance are set by an interaction between bodily differences and mechanical demands of the event.

Emily McClelland
Program: PhD in Education-Applied Physiology
Faculty mentor: Peter Weyand

Christina McConville: Peritectic phase transition of benzene and acetonitrile into a cocrystal relevant to Titan, Saturn’s moon

Winner: Chemistry (Graduate)

https://youtu.be/avwu36FZq4g

Titan, Saturn’s largest moon, is the only body in the solar system known to have stable bodies of liquid—lakes, rivers, and seas—that undergo dynamic processes similar to Earth’s hydrological cycle. To study the potential formation of minerals on Titan, we use a combination of structural characterization methods including high-resolution synchrotron powder X-ray diffraction (PXRD) and differential scanning calorimetry (DSC) to analyze the constituents present on Titan's surface and evaluate their potential for cocrystal formation. Among the compounds detected on the surface of Titan are two common laboratory solvents: benzene and acetonitrile. Here we report the phase diagram of mixtures of acetonitrile and benzene, which features incongruent melting and a peritectic phase transition of solid benzene and liquid acetonitrile into a 1:3 acetonitrile:benzene cocrystal. The crystal structure of this cocrystal was solved and refined from in situ diffraction data using synchrotron radiation. Additionally, to mimic the environment on Titan more accurately, we tested the stability of the structure under liquid ethane. These results provide new insights into the structure and stability of potential extraterrestrial minerals and contribute to a better understanding of the surface composition of Titan.

Christina McConville
Program: PhD in Chemistry
Faculty Mentor: Tomče Runčevski

Avery Mercurio (U): Mustangs For Hope: A Community Based Nonprofit Bringing Virtual Learning to Dallas Children

https://www.youtube.com/watch?v=0ITz_QF2pcU

Mustangs For Hope is a new nonprofit organization that provides free, virtual, one-on-one tutoring for underprivileged Dallas children whose families have been affected by COVID-19 after-school program closures. Mustangs For Hope works in conjunction with Voice of Hope Ministries to match K-12th grade students with a college-aged mentor in order to foster community between young learners and college-aged students. Mustangs For Hope believes that virtual learning will remain a cornerstone in education for years to come. For this reason, Mustangs For Hope stands committed to creating an environment where academically at-risk children are never afraid to seek the help they need, to be intellectually curious and to excel in their academic journey.

Avery Mercurio
Majors: EMIS and Mathematics
Mentors: Gheorghe Spiride and Lindsay Davis

Robert Mirr (U): #BlackAtSMU

Winner: Meadows (Undergraduate)

https://youtu.be/RCGdcBmF7es

This documentary is important because it will serve as an exploration into the issue of systemic racism and white supremacy that is deeply ingrained in our SMU community which so necessarily needs to be talked about. Our documentary will also serve as a mode of education and a dialogue starter to promote better understanding of these issues and create meaningful change in the actions of those on campus. The community being served by this project is vast, but one highlighted community is that of the black students, faculty, and alumni of SMU. Our goal with this project is to create a pedagogical tool to be used to spark conversation around all areas of SMU, from the residential commons to PRW I classes, to administration meetings. We aim to create dialogue around how people of color are treated in all areas at SMU and spark change to create a more inclusive, diverse, and accountable community. I personally hope to create a change and a dialogue within the SMU community. These issues have gone both unnoticed by the administration and student body for too long. By sparking this dialogue I hope to ensure a change so students can no longer feel this white supremacy. I hope to see a change that benefits the greater SMU community for good and forever.

Robert Mirr
Major: Film production; Minor: Graphic Design and Advertising
Faculty mentor: Amber Bemak

Rebekah Napier-Jameson: RNA binding proteins coordinately control lifespan in C. elegans

Co-authors: Victoria Schatzman, Adam Norris

https://youtu.be/rnGsL5AALpM

In order to identify genes that coordinately control gene expression with important phenotypic consequences, we performed a CRISPR/Cas-9 based Synthetic Genetic Interaction (CRISPR-SGI) screen in C. elegans. We focused on conserved neuronally-expressed RNA binding proteins, and identified many double mutants with unexpected fitness defects. In one notable interaction between the MBNL1/2 ortholog mbl-1 and the ELAVL ortholog exc-7, double mutants displayed a severely shortened lifespan (~70% decrease). We have used RNA-Seq data to investigate which RNAs may be uniquely dysregulated in the double mutant. nhx-6, a predicted Na/H exchanger, which was identified from our RNA Seq data contributes to the phenotype and is expressed in the intestine. mbl-1 and exc-7 are neuronally-enriched genes. Initial experiments have shown partial rescue of the lifespan phenotype with mbl-1 re-expression in the nervous or intestinal tissues of the double mutant but not muscle tissue. Shortly we will be conducting experiments to test whether exc-7 expression in the nervous system is the critical tissue affecting whole-worm lifespan. Through these studies we hope to identify how these RNA binding proteins are contributing to the lifespan phenotype seen in the mbl-1;exc-7 double mutants.

Rebekah Napier-Jameson
Program: PhD in Biological Sciences
Faculty mentor: Adam Norris

Samantha Navarro and team: How might we improve procedural justice for the Dallas Police Department?

Winner: Combined Non-STEM (Graduate)

Co-authors: Hope Anderson, Ramisa Faruque, Kaci McCartan

https://youtu.be/K0uZqO1yv_M

Master of Arts in Design and Innovation students, Hope Anderson, Ramisa Faruque, Kaci McCartan and Samantha Navarro are working directly with the Dallas Police Department over the spring 2021 semester to approach the design question: How might we improve procedural justice for the Dallas Police Department? Following seven-step Human-Centered Design process, we will ultimately test our hypotheses through a series of prototypes. Our design solution will be submitted to DPD and has the potential for real-world implementation. This semester presents a unique challenge of navigating sensitive social and political issues on the heels of a heightened Black Lives Matter Movement and push to defund the police across the nation.

Hope Anderson, Ramisa Faruque, Kaci McCartan, and Samantha Navarro
Program: Master of Arts in Design and Innovation (MADI)
Faculty mentor: Jessica Burnham