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MURI/AUSMURI Project

MURI/AUSMURI Project: Rationalization of Interphase Instabilities during Thermo-Mechanical Gyrations Typical Showcase

Rationalization of Interphase Instabilities during Thermo-Mechanical Gyrations Typical

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1970
2024
1970 2024
36 results
  • Temperature Dependent Dynamic Response of High-Density Polyurethane Foams
    This data corresponds to work done by Daniel Morrison for a Master of Science degree at the Colorado School of Mines, focused on understanding temperature and time dependencies, and understanding microstructure damage on open-cell, polyurethane foams.
    • Dataset
  • Soil_carbon_remote_sensing_studies_1969-2022
    A detailed database of soil carbon remote sensing studies compiled in preparation for the meta-analysis and review titled "Soil carbon remote sensing: A meta-analysis and systematic re-view of published results from 1969 – 2022".
    • Dataset
  • Voltage Dependent Collection Efficiency Losses in RbF Treated CIGS
    This data investigates the extent and sources of voltage dependent collection efficiency losses in RbF treated CIGS solar cells.
    • Dataset
  • The 2020 US Presidential election and Trump's wars on trade and health insurance
    Dataset for replication of results in "The 2020 US Presidential election and Trump's wars on trade and health insurance" (2023), European Journal of Political Economy. Only changes from version 1 replication package published 7 Dec 2022 are updated paths in lines 12, 14 and 23 of [estimation]/regressionsEJPE.do and line 16 of [figures]/figuresEJPE.do
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  • Data_set for driver behavior
    Driver distraction activities analysis
    • Dataset
  • Progammable Autonomous Water Sampler - PAWS
    Water chemistry conditions in freshwater and marine environments can change rapidly over both space and time. This is especially true in environments that are exposed to anthropogenic impacts such as sedimentation, sewage, runoff and other types of pollution. It is critical in studying these systems that researchers have tools capable of accurately collecting water samples across relevant spatial and temporal scales. Here we present an inexpensive, open-source Programmable Autonomous Water Sampler (PAWS) that is open source, compact, robust, highly adaptable and submersible to 40 meters. PAWS utilizes a time-integrated sampling approach by collecting a single sample in a syringe slowly over hours to days. Once analyzed, data from the sample collected represents and integrated average of water chemistry conditions over time. Due to its adaptability and low cost, PAWS has the potential to vastly improve the spatial and temporal coverage of many freshwater and marine studies.
    • Dataset
  • Difficulty Mindsets, Self-Doubt, and Possible Selves
    I. SPSS Data File (Study 1) II. SAS Data Files & Syntax (Study 2) Testing (1) Interaction of Difficulty Mindsets, Self-Doubt, and Possible Self-Imagery (File 1) and (2) Simple Slopes within the control condition (File 2) and Difficulty-as-Improvement Mindset condition (File 3).
    • Dataset
  • Potash dust dataset
    Data from cutting potash rock block
    • Dataset
  • Mass flows maps at Mount Cleveland from DEMs
    These data are the results in a paper entitled "Quantifying mass flows at Mt. Cleveland, Alaska between 2001 and 2020 using satellite photogrammetry" submitted to JVGR in 2022. It includes the 2-m resolution surface elevation change and uncertainty maps for the 2001 Cleveland eruption (Fig. 1a in the paper), the 2-m resolution surface elevation change, and uncertainty maps corresponding to the accumulative changes of the following three eruptions: February 3, 2017, to January 20, 2019 eruption, the November 7 to November 15, 2019 eruption, and the June 1, 2020 eruption (Fig. 3a). This data set also includes the boundary of the deposit field, the boundary of mass loss, and the boundary of snow. Here we also share the digitized outlines from mass flows in previously published material (e.g., Smith (2005) and an image from the Alaska Volcano Observatory). The GeoTIFF files can be viewed in free and open-source software QGIS, in Google Earth, or by Matlab using code https://github.com/ihowat/setsm_postprocessing/blob/master/readGeotiff.m. The shapefiles can be viewed in QGIS. Google Earth may not show some of the shapefiles well. Smith, S.J., 2005. Chronologic multisensor assessment for Mount Cleveland, Alaska from 2000 to 2004 focusing on the 2001 eruption (Doctoral dissertation). Dai, C., Howat, I.M., Freymueller, J.T., Lu, Z., Vijay, S., Liljedahl, A.K., Jones, M.K.W., Bergstedt, H. and Lev, E., 2022. Quantifying mass flows at Mt. Cleveland, Alaska between 2001 and 2020 using satellite photogrammetry. Journal of Volcanology and Geothermal Research, p.107614.
    • Dataset
  • A new zonal wave 3 index for the Southern Hemisphere
    Zonal wave 3 index time series from Goyal et al., 2022 "A new zonal wave 3 index for the Southern Hemisphere" by Goyal, R., Jucker, M., Sen Gupta, A., England, M. DOI: https://doi.org/10.1175/JCLI-D-21-0927.1 Python code to calculate the ZW3 index can be found here - https://github.com/rishavgoyal55/NEW-ZONAL-WAVE-3-INDEX.git
    • Dataset
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