While collaboration with industry is paramount to innovation, the recent emphasis on industrial relationship transparency has sparked new guidelines, research studies, and standardizations focused on re-defining COI. There is limited data on defining the specific financial amount wherein a COI is relevant. This study is the first to assess the potential financial effects on high-quality clinical data, or the “indirect sponsorship”.
The dataset includes the reproducible search strategies for all literature databases searched during the review, the key articles used to generate relevant search terms and test the effectiveness of the searches, the Endnote library that has all citations considered for inclusion, a flow chart describing the screening process, and the screening forms used for inclusion and exclusion.
This work investigates what features e-commerce sites use to encourage impulse buying and what tools consumers desire to curb their online spending. We present supplementary material for two studies: (1) a
systematic content analysis of 200 top e-commerce websites in the U.S. and (2) a survey of online impulse
(1) Study 1 Code book for content analysis of websites
(2) Study 1 CSV data file resulting from the content analysis
(3) Study 1 PDFs (N=200) of e-commerce websites analyzed
(4) Study 2 Online survey questionnaire
(5) Study 2 Survey code book for free response questions
This Collection is a compilation of data measured in the TCC engine at the University of Michigan, Department of Mechanical Engineering, Quantitative Laser Diagnostics Laboratory. The posted Work Deposits are never changed. However, this collection will be expanded with additional Work Deposits as new experimental data become available. The intent of the collection is to provide a comprehensive experimental data set from the TCC-III engine, for fundamental discovery research on in-cylinder flow and spark-ignited combustion. Also, to enable in-depth support for CFD development and validation. The collection includes data files of in-cylinder flowvelocity and flame imaging, as well as engine and system geometry needed to set up 1-D and CFD simulations. and README for TCCIII_Collection: https://umich.box.com/v/Collection-README-rev20180202
This collection was produced as part of the project, “A ‘Big Data’ Approach to Understanding Neighborhood Effects in Chronic Illness Disparities.” The Investigators for the project are Tiffany Veinot, Veronica Berrocal, Phillipa Clarke, Robert Goodspeed, Daniel Romero, and VG Vinod Vydiswaran from the University of Michigan. The study took place from 2015-2016, with funding from the University of Michigan’s Social Sciences Annual Institute, MCubed, and the Sloan and Moore Foundations.
Contact: Tiffany Veinot, MLS, PhD
Office: 3443 North Quad
Wind exposure is a key physical driver of coastal systems in aquatic environments influencing circulation and wave dynamics. A measure of wind exposure is fetch, the distance over which wind can travel across open water. In large lake systems, such as the Laurentian Great Lakes, estimating fetch has proved to be difficult due to their vast size and complex topobathymetry. Here we describe the development of two spatially discrete indicators of exposure to provide a more accurate indicator of influence of wind exposure in the nearshore of the Laurentian Great Lakes. We summarized wind data from offshore buoys and leveraged existing tools to calculate effective fetch and relative exposure index (effective fetch scaled by mean wind speed) at a 30 m grid cell resolution. We validated these models by comparing our exposure maps to the U.S. Army Corps of Engineers Wave Information Studies models and found general agreement. These exposure maps are available for public download for the years 2004-2014.