GOES_flare_list: contains a list of more than 10,000 flare events. The list has 6 columns, flare classification, active region number, date, start time end time, emission peak time, GOES_B_flare_list: contains time series data of SDO/HMI SHARP parameters for B class solar flares
, GOES_MX_flare_list: contains time series data of SDO/HMI SHARP parameters for M and X class solar flares, SHARP_B_flare_data_300.hdf5 and SHARP_MX_flare_data_300.hdf5 files contain time series more than 20 physical variables derived from the SDO/HMI SHARP data files. These data are saved at a 12 minute cadence and are used to train the LSTM model., and B_HARPs_CNNencoded_part_xxx.hdf5 and M_X HARPs_CNNencoded_part_xxx.hdf5 include neural network encoded features derived from vector magnetogram images derived from the Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager (HMI). These data files typically contains one or two sequences of magnetograms covering an active region for a period of 24h with a 1 hour cadence. We encode each magnetogram with frames of a fixed size of 8x16 with 512 channels.
The dataset contains bulk sedimentary d15N, TOC, and TN data measured every 2 mm on the core SPR0901-03KC. Flood and turbidite layers are shaded with blue and orange in the files. and This work is supported by NSF OCE-1304327.
The modeling research conducted to produce this dataset focuses on the solar wind dynamic pressure drop events and how they affect the Earth's intrinsically coupled Magnetosphere, Ionosphere and Thermosphere systems. This study specifically focuses on the 11 June 2017 event, where the solar wind dynamic pressure dropped significantly following a period of higher pressure. We model the response to this pressure drop using University of Michigan Space Weather Modeling Framework ( http://csem.engin.umich.edu/tools/swmf/). The simulation results were created using BATS-R-US and GITM models. The observational data required for model comparisons were taken from OMNI ( https://omniweb.gsfc.nasa.gov) and CDAWeb ( https://cdaweb.gsfc.nasa.gov/sp_phys/) Databases.
The Liquid Metal Battery (LMB), a promising energy-storage device that contains liquid-metal interior, is studied numerically in the paper. The metal pad roll instability was modeled based on the open-source CFD software, OpenFOAM. It's based on the solver for simulations of incompressible multiphase flows multiphaseInterFoam modified to include the electromagnetic fields and account for the sharp variations of the electrical conductivity.
The data and the scripts are to show that seizure onset dynamics and evoked responses change over the progression of epileptogenesis defined in this intrahippocampal tetanus toxin rat model. All tests explored in this study can be repeated with the data and scripts included in this repository. and Dataset citation: Crisp, D.N., Cheung, W., Gliske, S.V., Lai, A., Freestone, D.R., Grayden, D.B., Cook, MJ., Stacey, W.C. (2019). Epileptogenesis modulates spontaneous and responsive brain state dynamics [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/r6vg-9658
This data and scripts are meant to test and show seizure differentiation based on bifurcation theory. A zip file is included which contains real and simulated seizure waveforms, Matlab scripts, and metadata. The matlab scripts allow for visual review validation and objective feature analysis. The file “README.txt” provides more detail about each individual file within the zip file. and Data citation: Crisp, D.N., Saggio, M.L., Scott, J., Stacey, W.C., Nakatani, M., Gliske, S.F., Lin, J. (2019). Epidynamics: Navigating the map of seizure dynamics - Code & Data [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/ejhy-5h41
Manganese in the sedimentary record has been interpreted by many as a powerful redox proxy for paleoenvironments, and yet very little work has been done to ensure that the manganese-rich minerals in the rock record are actually recording primary signals. In the accompanying manuscript, we present an in-depth characterization of the manganese mineralogy from two correlated regions recording the Transvaal Supergroup in South Africa with markedly different alteration histories to investigate if there can be post-depositional emplacement of manganese-rich minerals. The data uploaded here are X-ray absorption spectra of (1) manganese standard minerals that were useful in our analyses and (2) minerals from an important well-characterized sample that may be useful as comparative standards in future studies.
This dataset is associated with the University of Michigan Dept. of Physics dissertation titled "Shedding Light on the Dark: Exploring the Relation Between Galaxy Cluster Mass and Temperature Through Weak Gravitational Lensing" by Rutuparna Das. It is also associated with a paper, currently in preparation, by Das et al (details to be added once paper is submitted/accepted)., This work contains information about shapes of galaxies observed by the Dark Energy Survey (DES) during its Science Verification (SV) run. The official DES SV shape catalog has already been released to the public (see details in Jarvis et al. (2016), henceforth called "J16"). This work follows the methods presented in J16, and contains shapes from areas of the sky that were not processed as part of the official DES-SV catalog but were necessary for the work presented in the aforementioned dissertation. Each catalog contains information for galaxies in a 80′ × 80′ cutout centered at a given galaxy cluster., Note that these catalogs are not entirely analogous to the official DES-SV catalog. For one, we only measure shapes for galaxies, as stars and other objects were not needed for the dissertation. Our catalogs also only extend to a magnitude of 24 in r-band, whereas a small fraction of the objects in the official Im3shape catalog are dimmer (see Figure 29 of J16)., We also include other information necessary for weak lensing studies. Aside from all fields from Im3shape and noise bias calibration (listed and described in J16), these catalogs contain columns for object positions (“ra_gold”, “dec_gold”) and magnitudes in various filters (“mag_detmodel_g”, “mag_detmodel_r”, “mag_detmodel_i”, “mag_detmodel_z”) from the SVA1-Gold catalog ( https://des.ncsa.illinois.edu/releases/sva1/docs/docs-gold). Additionally, we include mean redshift measurements from two DES photo-z measurement pipelines, TPZ and DESDM Neural Network (“z_TPZ”, “z_DESDMnn”) (more details in Sanchez et al. (2014))., and References:
Jarvis, M., Sheldon, E., Zuntz, J., et al. 2016, Monthly Notices of the Royal Astronomical Society, 460, 2245.
Sanchez, C., Carrasco Kind, M., Lin, H., et al. 2014, Monthly Notices of the Royal Astronomical Society, 445, 1482.