Student Name: Griffin Mahoney

Project Title: Computer simulation of parenting and the life history of the dinosaur Maiasaura

Project description: Maiasaura was a genus of dinosaur that lived in the Upper Cretaceous Period in North America. The discovery of Maiasaura was the first evidence of a dinosaur feeding its young, hence the name given to it, which means "good mother reptile." The number of fossil specimens of Maiasaura that have been obtained is extremely high and have led to a number of fairly low uncertainty estimates for life history statistics (e.g. age distributions, survival rates, etc.) making Maiasaura one of the best understood extinct vertebrates in the fossil record. In this project, we will take these empirically-obtained values and construct a computer simulation, specifically, an agent-based model (ABM), of the species to observe its population dynamics. ABMs are models where individuals (agents) are unique and autonomous and interact with each other and their environment locally. We will adjust survivorship rates simulating a trade-off between parenting and individual survival and see how these effects propagate to the population demographics. The goal of this project is to determine how impactful the role of parenting was in establishing a stable population.

Project Advisor: Alex Capaldi (Mathematics & Statistics)

Project Sponsored by REDI

Student Name: Summer Kantanen

Project Title: Localized pattern control in spatiotemporal patterns using reaction-diffusion equations 

Project description: Research into spatiotemporal self-organization and pattern formation in naturally evolving systems has garnered significant attention within the field of statistical mechanics over the past few decades. These patterns hold immense interest because of their remarkable similarity to crucial biological, chemical, and physical processes, such as DNA oligomers, skin pigment development, and oscillatory chemical reactions. 

While numerous Turing-like models have been proposed to mathematically describe reaction-diffusion systems, only a limited few exhibit the nonlinear and chaotic behaviors closely resembling those found in natural systems. The Gray-Scott model, serving as the primary model of study, uniquely possesses both of these behaviors and boasts a rich parameter space replete with a multitude of intriguing dynamical regimes. 

The Gray-Scott model is a cubic, autocatalytic reaction involving two chemical concentration densities, u and v. This research project centers on the exploration of emerging spatiotemporal patterns within the Gray-Scott model. This exploration involves systematic localized parameter adjustments and the incorporation of electric fields, providing a deeper understanding of the model's intricate behavior and its potential applications in various natural phenomena. 

Project Advisor: Jason Czak (Physics & Astronomy)

Project Sponsored by REDI

Student Name: Emily Euler 

Project Title: Computational investigation of butanol reactivity on gold-titania nanocatalysts  

Project description: When used as a biofuel for vehicles, butanol contributes to cleaner air by reducing unburned hydrocarbons in tailpipe exhaust. 1-butanol and 2-butanol are isomers, which means they have the same chemical formula (C4H9OH) but different structures. When they react on a gold-titania nanocatalyst surface 1-butanol and 2-butanol unexpectedly form different products. To understand why these two similar molecules follow different chemical reaction pathways this computational surface science project will use software based on quantum mechanics to predict the structure and energies of butanol molecules as they react on catalyst surfaces. Research will be conducted using high performance computing (HPC) resources available at JMU, UVA, and Argonne National Laboratory.  

Project Advisor: Kendra Letchworth Weaver (Physics & Astronomy)

Project Sponsored by REDI and Honors College

Student Name: Morgan Jones

Project Title: Discovering conserved genes in sister species of garter snakes

Project description: When vertebrates evolved from aquatic to terrestrial life, natural selection preserved a network of genes to synthesize lipids in the skin to prevent whole-body dehydration. Snakes are an ancient lineage of terrestrial vertebrates but have adapted to a variety of environments, including semi-aquatic habitats. Do closely-related species of garter snakes, despite their divergent habitats, all have and use the same genes for skin lipid synthesis? Recently, we identified some of these skin lipid synthesis genes in one species of garter snake, and these genes are seasonal and sex-specific in their activity. Next, we will extract RNA and make cDNA from skin samples from several other garter snake species and then use traditional and quantitative PCR to measure any differences in skin gene activity. Students involved in this project will read the primary literature and learn molecular biology techniques (RNA extraction, cDNA synthesis, PCR) to test hypotheses on the evolution of gene networks. If successful, and because this project is part of a larger collaborative study, the student will eventually co-author a manuscript that will be submitted for peer review. 

Project Advisor: Rocky Parker (Biology)

Project Sponsored by the College of Science & Mathematics

Student Name: Conor Bourke

Project Title: Evaluating the stability of supramolecular boronic acids gels for targeted drug delivery  

Project description: This project involves the study of peptides with boronic acid handles. Peptides are known to form hydrogels, materials that act like solids despite being predominantly water. The introduction of a boronic acid allows for recognition of drugs, such as L-DOPA. L-DOPA is a Parkinson’s drug that dramatically improves patients’ motor deficits. Despite its benefits, patients taking L-DOPA experience adverse gastrointestinal side effects, which primarily arise from drug breakdown. Transdermal L-DOPA administration with our hydrogel will minimize these side effects and improve drug efficacy. In this project, we will synthesize a library of boronic acid-peptides, use these molecules to form gels, and evaluate their stability under biological conditions. The enzymatic resistance of L-DOPA incorporated materials will also be investigated. 

Project Advisor: Gretchen Peters (Chemistry & Biochemistry)

Project Sponsored by REDI and Honors College

Student Name: Evelyn Page

Project Title: Molecular sponges: Using biopolymer metal-organic framework composites to remove ions from water

Project description: Is my water safe to drink? That’s a question we don’t have to ask at JMU because we have access to safe and reliable water sources. However, there are many places where water contains ions that we want to extract because we have a safety concern (lead) or because the ions are rare and are needed for other applications (gold). In this project, we will synthesize composite materials, or “molecular sponges,” to remove ions from water. These sponges consist of a biopolymer and a metal-organic framework (MOF). We are interested in exploring the biopolymer nanocellulose, nano-sized particles of cellulose, as a support to make molecular sponges that contain MOFs. MOFs are promising for isolating ions from water because MOFs can be modified to control how they interact with ions in solution. In this project, we will synthesize selective molecular sponges by controlling their materials properties and incorporating additives that can be used to selectively remove contaminants from solution.

Project Advisor: Barbara Reisner (Chemistry and Biochemistry)

Project Sponsored by REDI and Honors College

Student Name: Mckenna Witt

Project Title: Data and Disease: How do we use data to better model disease spread and intervention?

Project description: We will be investigating how to use data to study the spread of certain diseases as well as the efficacy of intervention strategies (such as quarantine, vaccination, treatment, etc.). Disease spread in a population will be modeled by using nonlinear dynamics models and/or discrete time models. We will then use statistical methods to approximate parameters from existing data sets. This work is interdisciplinary, touching on math, statistics, data sciences, biology, public health, and medicine.  

Project Advisor: Eva Strawbridge (Mathematics and Statistics)

Project Sponsored by REDI and Honors College

Student Name: Norah Squires

Project Title: Interactive Dimension Reduction for Microbiomes  

Project description: Math is great for combining variables and projecting observations into a 2D visualization space. Humans are great at finding patterns and groups among observations in 2D visualizations. If we let humans adjust the visualization, we can update the math to reflect the patterns the human found or imposed. Software for this human intervention is available in Python, which is great, but most people in the field are using R. So, we are translating code from Python to R and adding other useful features. We will test the code on both generic, publicly available data and on data generated in the biology lab where we study microbiomes - the community of bacteria, fungi, and other microbes living in or on an environment (i.e., in the human gut). While this project doesn't have a “wet” lab component, future projects could. Instead, this project focuses on a data science component, specifically visualization. Data science is one of the fastest growing and highest paying fields in the country right now and this project is a perfect introduction to the field and how it applies to biological data.  

Project Advisor: Laura Tipton (Mathematics & Statistics, and Biology)

Project Sponsored by Honors College

Student Name: Newton Elizabeth

Project Title: Use of JMU tree inventory data to estimate the carbon sequestration and building heating/cooling effect 

Project description: Determining the cooling impact of tree canopies relies significantly on carbon sequestration, wherein carbon dioxide stored in the carbon pool plays a crucial role. This becomes particularly vital in urban environments characterized by a high percentage of impervious surfaces, such as buildings. The Climate Change Resource Center of the U.S. Forest Service has introduced the Tree Carbon Calculator Tool (CTCC) to facilitate this assessment. This tool enables the estimation of carbon dioxide sequestration and energy savings associated with individual trees. Our approach involves employing the CTCC to compute the carbon sequestration of the trees within James Madison University. The essential parameters for the CTCC, derived from the JMU Tree Inventory (available as an ArcGIS Web App), encompass the climate zone, tree species name, tree size (precisely diameter at breast height), or the age of the tree species. Initially, we will estimate the carbon sequestration and cooling effects on a per-species basis. Subsequently, we will determine the overall or total sequestered carbon dioxide and cumulative cooling effect (annual energy savings in kWh in electricity) by aggregating the data from individual tree species. The final step involves leveraging ArcGIS Online to publish the final maps as a Web App or a story map.  

Project Advisor: Dhanuska Bandara Wijesinghe (Department of Geology and Environmental Science)

Project Sponsored by the College of Science & Mathematics

Student Name: Evan Poindexter 

Project Title: Monarch Butterflies and Milkweed species

Project description: Climate change is affecting pollinator species, such as the monarch butterfly. In experimental studies, we are determining monarch butterfly preference and caterpillar growth on eight species of native milkweed which may be increasing in toxicity due to increased levels of CO2. We will determine toxin levels in the plants as well as the caterpillars feeding on them. This may have an effect on the OE parasite that is infecting them. The student will cultivate milkweed species in the greenhouse in the early spring and plant the species in experimental plots in the late spring. The student will count eggs and measure caterpillars on milkweed species in garden plots during the fall semester if they continue in our lab.  Monarch butterflies are also captured to test for presence of the OE parasite. 

Project Advisor: Heather Griscom (Biology)

Project Sponsored by the College of Science & Mathematics

Student Name: Mikhail Rolsen

Project Title: Developing a measure of Community Cultural Wealth

Project description: Students from minoritized identities are critically underrepresented in STEM fields. Many institutions attempt to address this education debt by providing minoritized students with “cultural capital”, an accumulation of skills valued by the majority community. These training initiatives support the perception that minoritized students operate at a deficit; they lack the necessary skills to be successful in higher education but will improve if they are provided adequate resources. Many researchers have challenged this narrow view of capital. They argue that people from minoritized communities possess Community Cultural Wealth (CCW), different forms of capital that are built on resilience, community, and culture, and that these strengths enable students from minoritized identities to be successful in academic spaces. In most research, CCW is measured using qualitative methods, but few studies have attempted to measure CCW quantitively (i.e., through Likert-style survey questions). The goal of this study is to develop a quantitative measure of CCW (i.e., a survey), and to collect evidence of validity for the measure. Evidence of validity refers to the body of evidence suggesting that an established survey measures what it is designed to measure.  

This semester, research on the team will involve writing research protocols for the JMU Institutional Review Board, conducting cognitive interviews with undergraduate students, qualitatively analyzing student responses, and using student responses to revise or accept questions within the measure. It may also include virtual meetings with researchers across the nation to plan mass distribution of the measure. Subsequent semesters will include analyzing quantitative survey data using R Studio and conducting student focus groups. 

Project Advisor: Rosario Marroquin-Flores (Biology)

Student Name: Charlotte Haacke-Golden

Project Title: Monarch Butterflies and Milkweed species

Project description: Climate change is affecting pollinator species, such as the monarch butterfly. In experimental studies, we are determining monarch butterfly preference and caterpillar growth on eight species of native milkweed which may be increasing in toxicity due to increased levels of CO2. The student will cultivate milkweed species in the Bioscience greenhouse in the spring semester and plant the seedlings in experimental plots outside of Bioscience in the late spring. We will monitor seedling growth and survival in the greenhouse as some species are more difficult to propagate than other species. The student will count eggs and measure caterpillars on milkweed species in garden plots during the fall semester if they decide to continue research in our lab. 

Project Advisor: Heather Griscom (Biology)

Student Name: Neema Ajandeh

Project Title: Molecular sponges: Functionalizing sustainable materials to remove ions from water

Project description: Is my water safe to drink? That’s a question we don’t have to ask at JMU because we have access to safe and reliable water sources. However, there are many places where water contains ions that we want to extract because we have a safety concern (lead) or because the ions are rare and are needed for other applications (gold). In this project, we will synthesize composite materials, or “molecular sponges,” to remove ions from water. These sponges consist of a biopolymer or mineral framework that can be chemically modified to adsorb specific contaminants. We are interested in exploring these materials because of their sustainability. In this project, we will synthesize selective molecular sponges by controlling their materials properties and incorporating other molecules that can be used to selectively remove contaminants from solution. 

Project Advisor: Barbara Reisner (Chemistry and Biochemistry)

Student Name: Josephine Funderburg

Project Title: Computer simulation of parenting and the life history of the dinosaur Maiasaura

Project description: Maiasaura was a genus of dinosaur that lived in the Upper Cretaceous Period in North America. The discovery of Maiasaura was the first evidence of a dinosaur feeding its young, hence the name given to it, which means "good mother reptile." The number of fossil specimens of Maiasaura that have been obtained is extremely high and have led to a number of fairly low uncertainty estimates for life history statistics (e.g. age distributions, survival rates, etc.) making Maiasaura one of the best understood extinct vertebrates in the fossil record. In this project, we will take these empirically-obtained values and construct a computer simulation, specifically, an agent-based model (ABM), of the species to observe its population dynamics. ABMs are models where individuals (agents) are unique and autonomous and interact with each other and their environment locally. We will adjust survivorship rates simulating a trade-off between parenting and individual survival and see how these effects propagate to the population demographics. The goal of this project is to determine how impactful the role of parenting was in establishing a stable population. 

Project Advisor: Alex Capaldi (Mathematics & Statistics)

Student Name: Soren Doucette

Project Title: Investigating Population Effects on Stellar Cluster HR diagrams 

Project description: Clusters of stars have stars forming at the same time. One way astronomers probe stellar evolution is by creating synthetic HR diagrams (luminosity versus temperature plots) that help identify a star's properties at a given time. It turns out that many stars are actually binary or multiple stars (but so far away they appear to be a single star). In this project, the student will create a series of simplified HR diagrams using blackbodies to model the individual stars of a large cluster. Each HR diagram will consist of a different population of single or single+multiple stars. The stellar models will be made by the student in python. The models will be compared to see the effects of (1) different populations on the spread of the luminosity in HR diagram for stars of the same nominal age and, if time allows, (2) how the aging of stars affect the apparent distribution of stars in the HR diagram. Models from the literature will be used to define how stars of a given initial temperature/size might age. Where appropriate, the various models also will be compared to existing studies of stellar cluster populations.

Project Advisor: Harold Butner (Physics and Astronomy)

Student Name: Lekhika Karki

Project Title: Cumulative impact of food preservatives on gut health, gut microbiome, and gut-brain axis

Project description: My lab focuses on understanding the role of dietary ingredients in our health and behavior. Recent increase in the body of knowledge of gut-brain-axis (the communication between our gut and the brain) shows how significant a role the gut bacteria are playing in shaping up one’s overall health and even behavioral changes. Different dietary ingredients promote or inhibit certain groups of bacteria and thus change the signaling between the gut and the brain, hence impacting our bodily functions. My lab currently investigates whether the long-term consumption of food preservatives changes the gut bacterial population and thus overall health and behavior. We use mice as our experimental model and study the changes in the gut wall composition and mucosal integrity as well as the changes in the relative increase or decrease in certain bacterial species in the gut in response to consuming food preservatives for an extended period of time.

Project Advisor: Bisi Velayudhan (Biology)

Student Name: Madison Cervenak

Project Title: Cracking Absurdle: The Hidden Math Behind the Ultimate Word Game

Project description: Are you someone who enjoys puzzles, games, or trying to outsmart tricky challenges? If so, this project is for you! In this research experience, we’ll dive into Absurdle — a sneaky, ever-changing version of the popular game Wordle. Unlike Wordle, where the word is fixed, Absurdle changes its hidden word based on your guesses, trying to make the game as hard as possible. But with the power of math and strategy, we can outsmart the game! 

In this project, we’ll explore the mathematical secrets behind Absurdle, learning how concepts like probability, combinatorics, and game theory can help us develop strategies. You don’t need to have any experience with advanced math or programming — we’ll start with the basics and work our way up. Along the way, you’ll pick up coding skills and simulate strategies to see what really works. 

This project is all about curiosity and problem-solving. By the end, you’ll have the tools to take on any puzzle-based challenge through the lens of mathematics.  

Project Advisor: Johnathan Bush(Mathematics and Statistics)

Student Name: Sydney Hartman

Project Title: Computational Investigation of Ethanol Reactivity on Copper Catalyst Surfaces 

Project description: The chemicals needed for textiles, pharmaceuticals, plastics, and other commercial products are typically produced as byproducts of fossil fuels. Ethanol derived from corn is a promising renewable source of these chemicals, however the reaction pathways for oxidation and reduction of ethanol are poorly understood. Oxygen adsorbed on copper catalyst materials can influence the selectivity of the reaction, determining whether ethanol oxidizes to form acetaldehyde or reduces to form ethylene. This computational surface science project will use software based on quantum mechanics to predict the structure and energies of ethanol molecules as they react on copper catalyst surfaces, exploring the role of adsorbed oxygen in determining which products form. Research will be conducted using high performance computing (HPC) resources available at JMU and Argonne National Laboratory. 

Project Advisor: Kendra Letchworth-Weaver (Physics and Astronomy)

Student Name: Margaret Mallet

Project Title: Assessing animal locomotion using machine learning  

Project description: Animal locomotion is often assessed using video. My lab uses video to assess the locomotor performance and contexts in primates. Specifically, we are interested in chimpanzee locomotor behavior as they are human's closest living relatives, and their body plans are similar. This project specifically aims to assess joint angles in chimpanzees through machine learning. The project involves recognizing joint centers of rotation (shoulder, hip, knee, elbow) and training a network to do the same. This data is important for understanding how chimpanzees move and the evolution of locomotion in humans. 

Project Advisor: Lauren Sarringhaus (Biology)

Student Name: Amaro Otero

Project Title: Data-Driven Analysis of Localized Control Patterns in Spatiotemporal Systems Using Reaction-Diffusion Equations

Project description: Research into spatiotemporal self-organization and pattern formation in naturally evolving systems has garnered significant attention within the field of statistical mechanics over the past few decades. These patterns hold immense interest because of their remarkable similarity to crucial biological, chemical, and physical processes, such as DNA oligomers, skin pigment development, and oscillatory chemical reactions. 

While numerous Turing-like models have been proposed to mathematically describe reaction-diffusion systems, only a limited few exhibit the nonlinear and chaotic behaviors closely resembling those found in natural systems. The Gray-Scott model, serving as the primary model of study, uniquely possesses both of these behaviors and boasts a rich parameter space replete with a multitude of intriguing dynamical regimes. 

The Gray-Scott model is a cubic, autocatalytic reaction involving two chemical concentration densities, u and v. This research project centers on the exploration of emerging spatiotemporal patterns within the Gray-Scott model. This exploration involves systematic data generation and analysis utilizing standard data science tools to study and categorize generated spatiotemporal patterns. Additionally, the project will involve the development and testing of machine learning toolkits designed to create Fisher information matrices. The Fisher information matrices will be used along with generated spatiotemporal data to gain insights into the role of machine learning in studying spatially localized patterns. 

Project Advisor: Jason Czak (Physics and Astronomy)

Student Name: Ethan Legaspi

Project Title: Investigation into the structure-property relationship of Gd- and Nd-doped ErBa2Cu3O7-? Superconductor  

Project description: Superconductors are materials that can carry electric current without resistance when cooled below a certain temperature, called the critical temperature (Tc). This allows them to conduct electricity with no energy loss, making them useful for reducing energy costs. Superconductors can also create strong magnetic fields, which are important in technologies like MRI machines and Maglev trains. However, most superconductors require either extremely low temperatures or very high pressures to work, which limits their widespread use. 

RE123 (REBa2Cu3O7, where RE=rare earth element) is a superconductor class which has different crystal structures with varying number of CuO2 planes and CuO chains display different critical temperatures (Tc), under normal pressures. Er123 (ErBa2Cu3O7-x) is one significant member of this class of superconductors having a Tc of about 90 K and high stability. Gadolinium (Gd) and (Nd) neodymium are magnetic rare-earth ions and doping Er with Gd and/or Nd will introduce additional magnetic interactions making Gd- and Nd-Doped ErBa2Cu3O7-? superconductor an interesting system to study the interaction between superconducting and magnetic phases in the same system.  

In this project, the student will synthesize several materials of different doping levels of Gd- and Nd-doped ErBa2Cu3O7-? Superconductor using high-temperature furnaces, measure their crystal structures using an x-ray diffractometer and analyze the data. After the student synthesizes good samples, we will measure magnetic susceptibility data to better understand how superconducting and magnetic phases interact.  

Project Advisor: Sachith Dissanayake (Physics and Astronomy)

Student Name: Isabella Caldwell

Project Title: What floral traits lead to pollinators maintaining or ignoring species boundaries? 

Project description: In my lab, we study the floral phenotypes that attract pollinators in two locally growing species, Silene virginica (red flowering, hummingbird pollinated) and Silene caroliniana (pink flowering, bee and butterfly pollinated). These two species rarely hybridize, but there are some local populations that appear to be hybrids. I am looking for a student who is interested in evolution and speciation to measure several flower traits in the greenhouse to (1) compare the naturally occurring hybrids to artificially generated hybrids in the greenhouse and (2) later in the spring, assist in pollinator observations outdoors (hummingbirds, butterflies, bees). This will help us understand which traits (e.g. floral color, petal size, nectar amount) between the two species and hybrids are associated with pollinator preference. While each species has their own dedicated pollinators, butterflies have been observed pollinating both species. Another goal of outdoor pollinator observations would be to see whether we can observe butterflies moving pollen between the two species. Weekly tasks would include measurements of floral color (photographic and biochemical), nectar measurements (volume and sugar content), flower morphology (size, length, cell surface), and recording data in a spreadsheet. Ultimately, we will use the phenotypic measurements to understand the genetic basis of the traits and that of speciation. 

Project Advisor: Andrea Berardi (Biology)