ASU Scholarship Showcase

Green infrastructure serves as a critical no-regret strategy to address climate change mitigation and adaptation in climate action plans. Climate justice refers to the distribution of climate change-induced environmental hazards (e.g., increased frequency and intensity of floods) among socially vulnerable groups. Yet no index has addressed both climate justice and green infrastructure planning jointly in the USA. This paper proposes a spatial climate justice and green infrastructure assessment framework to understand social-ecological vulnerability under the impacts of climate change. The Climate Justice Index ranks places based on their exposure to climate change-induced flooding, and water contamination aggravated by floods, through hydrological modelling, GIS spatial analysis and statistical methodologies. The Green Infrastructure Index ranks access to biophysical adaptive capacity for climate change. A case study for the Huron River watershed in Michigan, USA, illustrates that climate justice hotspots are concentrated in large cities; yet these communities have the least access to green infrastructure. This study demonstrates the value of using GIS to assess the spatial distribution of climate justice in green infrastructure planning and thereby to prioritize infrastructure investment while addressing equity in climate change adaptation.

The current study examined heterogeneity in emerging adult children's routine and self-disclosure to parents using mixture modeling and explored predictors and outcomes associated with the patterns of disclosure. Participants consisted of 449 emerging adults (49% male, 68% European American, 65% college students, 33% single-parent families) who completed questionnaires every year across three waves (Mage at Time 1 = 18.4 years). Latent profile analyses suggested that large groups of emerging adults reported moderate levels of routine disclosure and low levels of self-disclosure to both mothers (79%) and fathers (36%), while other groups (20%) reported high levels of routine and self-disclosure to both parents. Profile membership was associated with predictors (parental autonomy granting, self-disclosure to friend, gender, family structure, college attendance) at Time 1 and outcomes (delinquency, depression, and prosocial behavior) at Time 3. Implications regarding the continued parent-child relationship and disclosure to parents in the third decade of life are discussed.

The following literature review talks about the driving simulation platforms commercially available for automated vehicle development. It is also a comparison of the simulation packages, their advantages and drawbacks, and an insight into what is missing in the simulators of today. Automated vehicle safety and reliability are the important requirements when developing automated vehicles. These requirements are guaranteed by extensive functional and performance tests. Conducting these tests on real vehicles is extremely expensive and time consuming, and thus it is necessary to develop a simulation platform to perform these tasks. In most cases, it is difficult for system or algorithm developers in the testing process to evaluate the massive design space. To test any algorithm change, developers need to test a functional module alone, and later setting up a whole physical testing environment that consists of several other modules, leading to enormous testing costs. Fortunately, many of the testing tasks can be accomplished by utilizing simulator. The key to the success of a simulation is how accurately the simulator can simulate the physical reality.