ASU Scholarship Showcase

Urea is an added value chemical with wide applications in the industry and agriculture. The release of urea waste to the environment affects ecosystem health despite its low toxicity. Online monitoring of urea for industrial applications and environmental health is an unaddressed challenge. Electroanalytical techniques can be a smart integrated solution for online monitoring if sensors can overcome the major barrier associated with long-term stability. Mixed metal oxides have shown excellent stability in environmental conditions with long lasting operational lives. However, these materials have been barely explored for sensing applications. This work presents a proof of concept that demonstrates the applicability of an indirect electroanalytical quantification method of urea. The use of Ti/RuO2-TiO2-SnO2 dimensional stable anode (DSA®) can provide accurate and sensitive quantification of urea in aqueous samples exploiting the excellent catalytic properties of DSA® on the electrogeneration of active chlorine species. The cathodic reduction of accumulated HClO/ClO− from anodic electrogeneration presented a direct relationship with urea concentration. This novel method can allow urea quantification with a competitive LOD of 1.83 × 10−6 mol L−1 within a linear range of 6.66 × 10−6 to 3.33 × 10−4 mol L−1 of urea concentration.

There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.

Mexicans and Mexican Americans have resided in Arizona since the early 16th century. Their history, however, is severely under-documented in the state’s archival repositories. As of 2012, this community is represented in a mere 1-2% of the state’s known archival holdings, and 98% of such documentation is held at Arizona State University’s Chicano/a Research Collection (CRC). This article provides a historical review of the CRC’s establishment in 1970 and how its founding Curator, Dr. Christine Marín, transformed a small circulating book collection into Arizona’s largest repository for Mexican American history. It goes on to examine how the CRC’s sitting Archivist is using social media in tandem with a community-based workshop, bilingual promotional materials and finding aids, and description of unprocessed collections as community outreach and collection development tools in order to remedy the under-documentation of Mexican American history in Arizona. We argue that augmenting traditional archival field collecting methods with these strategies enables the CRC to build a more robust relationship with Arizona’s Mexican American community, allows us to continue expanding our archival holdings, and serves as an example for other repositories seeking to enhance their documentation of marginalized communities.