Archive for August, 2018

Nevada Space Grant Highlight: Joy Immak, UNLV

Multiple regulatory inputs control type three secretion in the bacterial pathogen Shigella flexneri. The goal of this project is to understand transcriptional regulation used by the bacterial pathogen, Shigella flexneri, to control the secretion of effector proteins via the type three secretion system (T3SS) needle. This analysis is important because many bacterial pathogens use the T3SS to inject effector proteins into a human host cell to cause disease. Despite rigorous attempts to maintain a clean room for spacecraft assembly, Shigella flexneri and other bacterial pathogens have been found in air samples obtained at the Johnson Space Center. I hope that my findings can be used to develop novel therapeutics and/or a more effective live-attenuated S. flexneri vaccine.
This project peaked my interest in how bacterial pathogens respond to external signals found within the host environment. The NASA funding provided me with the rare opportunity to focus solely on my research. Altogether, this experience has reinforced my drive to continue academic research pursuits after I graduate.

Nevada Space Grant Highlight: Hung M. La, Huy X. Pham, and David Feil-Seifer, UNR

Collaborative Control of Multiple UAVs for Wildfire Tracking and Monitoring. According to the U.S. Forest Service, an annual average of 70,000 wildfires burn approximately 7 million acres of land and destroy more than 2,600 structures. Wildland firefighting is dangerous and a lack of information is one of the main causes of accidents. Unmanned aerial vehicles (UAVs) provide situational awareness of wildfire scenes because they can augment hazardous fire-tracking activities and significantly save operational costs. The UNR team, lead by Dr. Hung La, developed a distributed control framework for a team of UAVs to monitor wildfire in open space and precisely track its development. The UAVs are designed for flexible deployment and to effectively avoid in-flight collisions and cooperate well with other UAVs. Each UAV self-learns and adjusts its altitude to provide optimal coverage of an unknown field. The proposed controller was tested in simulation (Figures 1 & 2) and on an AR2 drone using a motion capture system in the Advanced Robotics and Automation (ARA) Lab.

Nevada Space Grant Highlight: Michael Founds, DRI

Risk Mapping Salt Mobilization and Mitigation Strategy Evaluation for Rangelands. Although rangeland covers the majority of the western United States, the impact of management practices on rangeland erosion is not well understood. Our team developed a risk mapping process to identify areas where disproportionate amounts of erosion occur within the Upper Colorado River Basin. Our approach leveraged NASA remote sensing and National Resource Inventory datasets to parameterize the Rangeland Hydrology and Erosion Model. The results predict erosion rates over large basins.

Nevada Space Grant Highlight: Scott Forer, UNR

Monopolistic Behaviors in Unmanned Airspace. During my graduate studies at the University of Nevada, Reno (UNR), under Dr. Yliniemi, I worked on a model enhancement to include more realistic unmanned airspace flight patterns for NASA’s Unmanned Traffic Management (UTM) system. The current methods for modeling multiple subsystems of autonomous Unmanned Aerial Vehicles (UAVs) do not account for competitive markets. By making modifications to an existing multi-UAV model, we investigated different behavioral interactions between the multiple subsystems and showed how competitive behaviors affect each subsystem.