Physical Sciences and Mathematics Commons^™

Relativity Lite: A Pictorial Translation Of Einstein’S Theories Of Motion And Gravity, Jack C. Straton

PDXOpen: Open Educational Resources

Relativity Lite is designed for the General Astronomy sequence (PH 361-2U, SCI 315-6U) whose primary book glosses over Special Relativity and General Relativity while trying to explain the Cosmology that is based on those subjects. Relativity Lite translates the mathematical equations conventional relativity texts rely upon into pictures that are readily understood and contain within them the mathematical essentials. This book provides the comprehensive coverage needed to understand, in sufficient depth, these three linked areas of our reality.

Readers seeking this knowledge on their own, and those in other courses for nonscientists, may also find it helpful.

Adopt/Adapt
If you …

Lectures On Mathematical Computing With Python, Jay Gopalakrishnan

PDXOpen: Open Educational Resources

This open resource is a collection of class activities for use in undergraduate courses aimed at teaching mathematical computing, and computational thinking in general, using the python programming language. It was developed for a second-year course (MTH 271) revamped for a new undergraduate program in data science at Portland State University. The activities are designed to guide students' use of python modules effectively for scientific computation, data analysis, and visualization.

Adopt/Adapt
If you are an instructor adopting or adapting this open educational resource, please help us understand your use by filling out this form

Climate Toolkit: A Resource Manual For Science And Action - Version 2.0, Frank Granshaw

PDXOpen: Open Educational Resources

The Climate Toolkit is a resource manual designed to help the reader navigate the complex and perplexing issue of climate change by providing tools and strategies to explore the underlying science. As such it contains a collection of activities that make use of readily available on-line resources developed by research groups and public agencies. These include web-based climate models, climate data archives, interactive atlases, policy papers, and “solution” catalogs. Unlike a standard textbook, it is designed to help readers do their own climate research and devise their own perspective rather than providing them with a script to assimilate and repeat. …

Modeling Post-Fire Successional Trajectories Under Climate Change In Interior Alaska Using Landis Ii, Shelby A. Weiss

Systems Science Friday Noon Seminar Series

Alaska boreal forest ecosystems are experiencing a greater frequency of wildfire relative to the region’s historic fire regime. These increases in fire frequency, as well as annual burned area, increase the probability of forests re-burning within shorter intervals than were experienced historically. Such changes to the fire regime have the potential to shift successional trajectories in this ecosystem. To better understand potential changes in vegetation composition following short-interval, repeat fires, we are using LANDIS-II, a forest landscape model, to simulate changes in forest composition in response to climate change and increasing fire frequency. This seminar will include a description of …

Statistical Analysis Of Social Network Change, Teresa D. Schmidt

Systems Science Friday Noon Seminar Series

We explore two statistical methods that infer social network structures and statistically test those structures for change over time: regression-based differential network analysis (R-DNA) and information theory-based differential network analysis (I-DNA). RDNA is adapted from bioinformatics and I-DNA employs reconstructability analysis. Both methods are used to analyze Medicaid claims data from one-year periods before and after the formation of the Health Share of Oregon Coordinated Care Organization (CCO). We hypothesized that Health Share’s CCO formation would be followed by several changes in the healthcare delivery network.

Application of R-DNA and I-DNA to claims data involves three steps: (a) the inference …