Seed Grant Awards Description FY 2023

On November 19th, 2023, a lone gunman entered Club Q, an LGBTQ night club in Colorado Springs, Colorado, and opened fire with an assault rifle. The gunman killed five people before being tackled to the ground, disarmed, and beaten into submission by Richard (Rich) Fierro, an Army Combat Veteran. Rich was at Club Q attending a drag show with his wife, daughter and his daughter’s boyfriend, Raymond Green Vance. Tragically, Raymond would not survive the night. Rich was well known in the Colorado Springs community as the co-owner of Atrevida Beer Co., a self-described Latina Forward brewery with the motto Diversity, It’s on Tap.

The half-hour documentary Fierro = Steel, the first in a triptych of documentary films exploring violence in American culture, tells Rich’s story. It asks the question, what sort of person runs toward the gun fire? Fierro’s bold insights on diversity, courage, and unity remind us of what it takes to keep America a beacon of hope for all.

We propose to perform high impact research in modeling the ionosphere using deep learning techniques by combining the expertise of Dr. Mark Golkowski in electrical engineering, Dr. Ashis Biswas in Computer Science, and Ms. Srivani Inturi, who is a MS student in Computer Science. We have a novel approach. The novelty of our approach is to model both the lower and upper ionosphere using two different datasets and to also employ Deep Learning (DL) models. Figure 1 shows the ionospheric electron density profile vs. altitude. We will use observations of Very Low Frequency (VLF) waves to obtain information on the lower ionosphere (80 km – 100 km) and Total Electron Content (TEC) measurements for the higher altitudes. We intend to forecast the lower ionospheric behavior by using the ground-based VLF/LF data available in the Waldo database and the forecasting of the upper ionosphere by using the Global Ionospheric Maps (GIM) data, GIM data uses more than 200 receivers over the entire world providing TEC data. Ultimately, we will collect a large amount of input data over multiple seasons, years, and a complete solar cycle. This huge dataset along with appropriate influencing parameters will enable the deep-learning model to capture the variations and patterns within the ionosphere to forecast accurately at least a day ahead.

Research on nonprofit resilience has grown rapidly over the last few years, and especially since the pandemic began. Yet, most research studies are qualitative studies with small sample sizes and were conducted at a single time point and with a few subsectors of nonprofits. The results of these studies have laid the groundwork for researchers to begin understanding nonprofit resilience, but a larger scale of research utilizing a more representative sample and tracking nonprofits over time is needed.

Therefore, this proposed research has two aims. The first aim responds to the call for the “'grand challenge' of studying the role and functioning of organizations during adverse natural or social events" (e.g., van der Vegt et al., 2015). The objective is to examine the resilience of Colorado nonprofits in the post-pandemic era by answering these two overarching questions: 1) what tactics and strategies did Colorado nonprofits adopt in response to the COVID-19 pandemic and what are the impacts of these strategies on nonprofit resilience? 2) what are the organizational and leadership factors that enabled some nonprofits to be more resilient than others?

In order to achieve the first aim, the second aim is to set up a data infrastructure: the Colorado Nonprofit Research Panel, a survey panel that will recruit nonprofit executives to participate in survey 2 questionnaires. The proposed research will use this Research Panel to track participating nonprofits for at least two years post-pandemic. After the grant is completed, the research panel will be maintained for continuing research.