Florencia Larsen presented a poster at the 2016 Special Interest Group on Computer Science Education in Memphis, Tennessee. The poster gathered a lot of interest and feedback for the project due to its novelty in immersive technologies in middle-school educational gaming.
Angel U. Ortega presented a poster at IEEE's 2016 Research Challenges in Information Science Conference in Grenoble, France. The poster gathered a lot of interest and feedback for the project due to its novelty in immersive technologies and data science and visualization in culturally-relevant educational gaming.
Angel U. Ortega presented a poster at the 2015 Computing Alliance for Hispanic Serving Institutions' Summit in San Juan, Puerto Rico. The poster gathered a lot of interest and feedback for the project due to its novelty in regional and cultural aspects in gaming focused in STEM outreach.
________ presented a poster at the 2014 Emerging Researchers National Conference in Washington, D.C. The poster gathered a lot of interest and feedback for the project due to its novelty in culturally immersive educational gaming.
CONSTRUCTING NEGOTIATED MEANING AND KNOWLEDGE FOR THE SOL Y AGUA PROJECT’S ROLE! PLAYING ADVENTURE GAME FOCUSED ON SUSTAINABILITY PROBLEMS IN THE EL PASO-RIO GRANDE AREA
Video games that address environmental sustainability issues could engage students. However, video games make simplifications and establish idealistic expectations that do not resemble real life sustainability challenges and settings. Game developers and scholars believe that depicting the complexity of the real world could help video games become effective educational tools. They call for additional procedures that incorporate information from actual settings and real life situations. Furthermore, scholars have argued that video games addressing sustainability issues can be improved or made more meaningful with the participation of youth from underrepresented populations, e.g., Latinos.
The Sol y Agua project at The University of Texas at El Paso exemplifies efforts to create a video game informed by real life circumstances. As a member of this project, I aimed to gather local environmental and cultural information to inform the development of the video game. Through a case study, I examined how the underlying values, beliefs, meanings, and knowledge of six community members in the fields of agriculture, urban systems, ground water systems, desert ecology, and traditional ecological knowledge function as hidden logics that collide, intersect, and aggregate to construct new meaning and knowledge of local sustainability issues.
Study results indicated that some community members added a personal dimension to the professional view of collaboration held by other community members who presented themselves strictly as scientists. Furthermore, the study yielded the concept of the "largest water user." Community members' perceptions of the largest water user intersected and created a new viewpoint, in which the largest water user is a changing concept that would continue adjusting as local circumstances fluctuate. Also, community members' perspectives collided. The majority of community members believed that students could develop a deeper connection with the Rio Grande River by participating in outdoor opportunities that foster insightful understanding of nature. However, some community members suggested that students foster deep connections with nature through everyday activities as part of their own culture and background. Tracking community members' logics revealed their individual values, knowledge, and beliefs. In turn, the individual logics helped construct new knowledge that could inform the development of the video game at a community level.
DEVELOPMENT OF 3-D SHEAR WAVE MODELS USING A MULTI-OBJECTIVE OPTIMIZATION SCHEME
Evidence of geologic activity still occurring in Rio Grande Rift (RGR) includes quaternary faulting, seismicity, and widening at a small rate. We map the crustal thickness and seismic velocity ratio to create crustal model cross sections that highlights the regional extension of the Southern Rio Grande Rift (SRGR). Specifically, we compute receiver functions and receiver function stacks for 147 USArray and previously collected data, and interpolate the crustal and velocity results using a kriging interpolation scheme. By incorporating gravity, magnetics, receiver functions, velocity models, and the interpretation of seismic reflection/refraction data, we produce a constrained crustal model that characterizes the evolution of the SRGR. In consequence, important questions related to tectonic and lithospheric activity of the Rio Grande Rift remain unresolved. To address some of these geological questions, we developed a 3D crust and upper mantle velocity model using a constrained optimization approach for joint inversion of surface wave and receiver functions. Our 3D models show a thin lower velocity crust anomaly along the southern east portion of the Rio Grande Rift, a persistent low velocity anomaly underneath the Colorado Plateau and Basin and Range province, and another one at depth beneath the Jemez lineament, and the southern RGR.
Furthermore, to make the joint inversion process more robust, we repeatedly solve the joint inversion problem with different possible combinations of variances known as the multi-objective optimization technique. From the mathematical viewpoint, such solutions form a Pareto front of the corresponding multi-objective optimization problem. If a certain geological feature is visible in all these solutions, then we can be confident that this feature is also present in the actual solution corresponding to the actual (unknown) values of the variances – i.e., that it is the feature of the actual Earth structure. We applied this more robust optimization technique to the Texas region and we also compared the structure of the upper mantle with other ancient and/or active rift systems within the Texas region. Our resulting 3-D velocity models will helps us to better understand the tectonic history and physical properties of the Earth structure and also determine if an ancient rift system within Texas is reactivated or not.
3-D STRUCTURE OF THE RIO GRANDE RIFT FROM 1-D CONSTRAINED JOINT INVERSION OF RECEIVER FUNCTIONS AND SURFACE WAVE DISPERSION
The Southern terminus of the Rio Grande Rift region has been poorly defined in the geologic record, with few seismic studies that provideinformation on the deeper Rift structure. In consequence, important questions related to tectonic and lithospheric activity of the Rio Grande Rift remain unresolved. To address some of these geological questions, we collect and analyze seismic data from 147 EarthScope Transportable Array (USArray) and other seismic stations in the region, to develop a 3-D crust and upper mantle velocity model. We apply a constrained optimization approach for joint inversion of surface wave and receiver functions using seismic S wave velocities as a model parameter. In particular, we compute receiver functions stacks based on ray parameter, and invert them jointly with collected surface wave group velocity dispersion observations. The inversions estimate 1-D seismic S-wave velocity profiles to 300 km depth, which are then interpolated to a 3-D velocity model using a Bayesian kriging scheme. Our 3-D models show a thin lower velocity crust anomaly along the southeastern Rio Grande Rift, a persistent low velocity anomaly underneath the Colorado Plateau and Basin and Range province, and another one at depth beneath the Jemez lineament, and the southern RGR.
Different geophysical data sets such as receiver functions, surface wave dispersion measurements, and first arrival travel times, provide complementary information about the Earth structure. To utilize all this information, it is desirable to perform a joint inversion, i.e., to use all these datasets when determining the Earth structure. In the ideal case, when we know the variance of each measurement, we can use the usual Least Squares approach to solve the joint inversion problem. In practice, we only have an approximate knowledge of these variances. As a result, if a geophysical feature appears in a solution corresponding to these approximate values of variances, there is no guarantee that this feature will still be visible if we use the actual (somewhat di erent) variances. To make the joint inversion process more robust, it is therefore desirable to repeatedly solve the joint inversion problem with di erent possible combinations of variances. From the mathematical viewpoint, such solutions form a Pareto front of the corresponding multi-objective optimization problem.