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These videos depict two miscible liquids with different densities and viscosities coming into contact. This study explores how a swellable test pad can be deployed for measuring urea in saliva by partially prefilling the pad with a miscible solution of greater viscosity and density. The resultant Korteweg stresses and viscous

These videos depict two miscible liquids with different densities and viscosities coming into contact. This study explores how a swellable test pad can be deployed for measuring urea in saliva by partially prefilling the pad with a miscible solution of greater viscosity and density. The resultant Korteweg stresses and viscous fingering patterns are analyzed using solutions with added food color through video analysis and image processing. Image analysis is simplified using the saturation channel after converting RGB image sequences to HSB. These videos are conjunction to an article submission to MDPI Bioengineering journal as supplementary files to enhance the breadth and depth of the content therein.

ContributorsClingan, H. (Author) / Rusk, D. (Author) / Smith, K. (Author) / Garcia, A. (Author)
Created2018-03-15
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Description

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

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.

ContributorsConway, Matthew Wigginton (Author) / Byrd, Andrew (Author) / van der Linden, Marco (Author)
Created2017