Congratulations to all of the students who presented their research at the New Mexico Junior Academy of Science competition.
1st Place – Aditya Kiran Koushik, La Cueva High School, Albuquerque
Designing a Monte Carlo python computer program to model random mutations across T-cell resistant sequences and hotspots in the SARS-CoV-2 spike glycoprotein
The purpose of this experiment is to use Monte Carlo simulations in the Python programming software to predict sporadic mutations in T-cell resistant sequences and hotspots of the SARS-CoV-2 spike glycoprotein. First, the IEDB library was used to get 48 well-validated T-cell epitopes in the SARS-CoV-2 spike protein. Then, using Monte Carlo simulations in Python (MC-P), the number of random mutations needed to change a 9-mer T-cell resistant sequence into a T-cell epitope was recorded. Next, in a separate MC-P model, the number of cycles it took to randomly replace a single amino acid in the 9-mer stretch of spike protein to a new highly transmissible variant of SARS-CoV-2 (D614G, V483A, G4765, and L54F) was recorded. My results show that; 1) Randomly altering amino acids in the 9-mer T-cell resistant sequence (“VLYQDVNCT”) for 10,000,000 cycles didn’t match any of the 48 T-cell epitopes. 2) Single point mutations (D614G, V483A, G4765, and L54F) took an average of 6-7 cycles when ran through the program. Therefore, the conversion of a T-cell resistant sequence into a T-cell epitope is rare, and single point mutations in spike protein are more frequent, which could result in highly transmissible variants of the virus.
2nd Place – Karin Ebey, Los Alamos High School
Climate change on crocodilians: modeling the effects of phenological shifts
Climate change is causing precipitation and temperature patterns to change, and in response species are undergoing phenological shifts, changes in reproductive timing. To explore the effects of phenological shifts on crocodilian’s response to climate change, a model was created, using a novel adaptation of the Lotka-Volterra equations, of a crocodilian population in an ecosystem. Rainfall impacts plant populations, and temperature affects plant growth, energy needs, and ectotherm hatch rates. The model was validated by running with Louisiana rainfall and temperature data and comparing the model outputs with alligator nest count data. First, variations in the timing and magnitude of rainfall and temperature were examined. Populations increase when there is more rainfall overall or during the growing season and decrease with less. Temperature changes harm ectotherms due to suboptimal temperatures for hatching. Then phenological shifts were added. Phenological shifts result in populations increasing if reproduction occurs at a better time in terms of prey availability and temperature. However, phenological shifts do not significantly alter the qualitative ecosystem response. Species-specific phenological shifts based on different cues do not affect other species. Using the results, management implications were developed with recommendations to protect crocodilians from climate change.
3rd Place – McKenna Collins, Albuquerque Institute for Math and Science
Just passing through: using hemispheric sensing with trajectory prediction to mechanically dodge space debris
Space debris, even at the size of a grain of sand, can cause irreparable damage to a multimillion-dollar satellite in an instant. Satellites typically dodge space debris via an orbital maneuver using some of their finite fuel supply. However, doing so can negatively affect length of the mission life span. To avoid space debris without propellant, new satellite systems could be divided into multiple subsections to perform mechanical orbital maneuvers. This approach requires an onboard detection system capable of calculating the predicted trajectory of localized space debris. To detect debris near the satellite, minimize ground-to-satellite communications, and flag potential threats from space junk, the onboard detection system comprised of multiple sensors can be implemented along with a trilateration algorithm. In this approach, a satellite would be sectionalized, its pieces mechanically separated, then reintegrated, after the theoretically detected space debris would pass through the more vacant center of mass. To model this, prototypes were designed, built, and tested. After demonstrating preliminary functionality, the prototypes were tested for separation distance and frequency of successful detection, separation, and reintegration cycles, the latest prototype the most promising. Sensor characterization tests concluded that individual calibration curves and direct sunlight impact interchangeability.
4th Place – Gabriel Gurule, Albuquerque Institute of Math and Science
Solving the issue of inefficiency for multiple faceted variable energy systems
This project is a continuation to solve inefficiency on multiple faceted variable energy systems. Physics concepts were applied to engineer and design a 3D printed wind turbine blade with solar cells embedded into a structure to generate supplemental electricity output. A major disadvantage of conventional wind turbines is intermittency and failure to produce electricity when the wind resource is compromised. An innovative approach that combines twin technologies can overcome inefficient and variable renewable energy systems. Further, the material properties of the turbine’s blades can be adjusted such that the system is economically viable through the end of life. The researcher for this project has applied for and received a provisional patent to advance this technology. This year a utility patent was filed which demonstrates that the standards have been met to satisfy legal requirements to move toward commercialization.
New Mexico Academy of Science