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- Creator:
- Penner-Hahn, James, Sension, Roseanne, McClain, Taylor, Lamb, Ryan, Alonso-Mori, Roberto, Lima, Frederico, Ardana-Lamas, Fernando, Biednov, Mykola, Chollet, Matthieu, Chung, Taewon, Deb, Aniruddha, Dewan, Paul, Gee, Leland, Huang, Joel, Yifeng, Khakhulin, Dmitry, Li, Jianhao, Michocki, Lindsay, Miller, Nicholas, Otte, Florian, Uemura, Yohei, and van Driel, Tim
- Description:
- UV-visible, X-ray absorption, and X-ray emission data used to characterize the dynamics of aquo and hydroxo cobalamin. Details of data collection and reduction are provided in the associated manuscript. Data files are all text files which contain tab-delimited columns of data corresponding to each figure in the manuscript.
- Keyword:
- Ultrafast, X-ray, Transient absorption, cobalamin, vitamin B12, XAS, XES, and XANES
- Citation to related publication:
- Sension, R.J., et al. (2023). Watching Excited State Dynamics with Optical and X-ray Probes: The Excited State Dynamics of Aquocobalamin and Hydroxocobalamin. J. Am. Chem. Soc. in press. and https://doi.org/10.1021/jacs.3c04099
- Discipline:
- Science
-
- Creator:
- Wallace, Dylan M, Benyamini, Miri, Nason-Tomaszewski, Samuel R, Costello, Joseph T, Cubillos, Luis H, Mender, Matthew J, Temmar, Hisham, Willsey, Matthew S, Patil, Parag P, Chestek, Cynthia A, and Zacksenhouse, Miriam
- Description:
- This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included: 1. Neural features and error labels used to train error classifiers for each day used in the study 2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction. The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
- Keyword:
- Brain-machine interface (BMI), Error detection, and Neural recording
- Citation to related publication:
- Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
- Discipline:
- Engineering, Science, and Health Sciences
-
- Creator:
- Sun, Hu, Ren, Jiaen, Chen, Yang, Zou, Shasha, Chang, Yurui, Wang, Zihan, and Coster, Anthea
- Description:
- Our research focuses on providing a fully-imputed map of the worldwide total electron content with high resolution and spatial-temporal smoothness. We fill in the missing values of the original Madrigal TEC maps via estimating the latent feature of each latitude and local time along the 2-D grid and give initial guess of the missing regions based on pre-computed spherical harmonics map. The resulting TEC map has high imputation accuracy and the ease of reproducing. All data are in HDF5 format and are easy to read using the h5py package in Python. The TEC map is grouped in folders based on years and each file contains a single-day data of 5-min cadence. Each individual TEC map is of size 181*361. and WARNING: 2023-12-01 the data file for 2019-Jan-03 has badly fitted values. Please avoid using it. All other days' files are ready to use.
- Keyword:
- Total Electron Content, Matrix Completion, VISTA, Spherical Harmonics, and Spatial-Temporal Smoothing
- Citation to related publication:
- Sun, H., Hua, Z., Ren, J., Zou, S., Sun, Y., & Chen, Y. (2022). Matrix completion methods for the total electron content video reconstruction. The Annals of Applied Statistics, 16(3), 1333-1358., Sun, H., Chen, Y., Zou, S., Ren, J., Chang, Y., Wang, Z., & Coster, A. (2023). Complete Global Total Electron Content Map Dataset based on a Video Imputation Algorithm VISTA. Scientific Data, in press., and Zou, S., Ren, J., Wang, Z., Sun, H., & Chen, Y. (2021). Impact of storm-enhanced density (SED) on ion upflow fluxes during geomagnetic storm. Frontiers in Astronomy and Space Sciences, 8, 746429.
- Discipline:
- Science and Engineering
-
- Creator:
- Brian, Chen
- Description:
- The procedure followed while creating this data is summarized in Section II of Chen, Brian, et al. "Behavioral cloning in atari games using a combined variational autoencoder and predictor model." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021. This data is not a result of a research but an intermediate product that is used in research. This dataset is generated to train a behavioral cloning framework from gameplay screen captures and keystrokes of an "expert" player. The RL agent that is trained using "RL Baselines Zoo package" acts as the "expert" player, whose decision making process we desire to learn. In addition to behavioral cloning experiments, this dataset is further used to demonstrate the efficacy of a novel incremental tensor decomposition algorithm on image-based data streams.
- Keyword:
- Imitation Learning, Behavioral Cloning, Reinforcement Learning, Machine Learning, and Gameplay Data
- Citation to related publication:
- Chen, Brian, et al. "Behavioral cloning in atari games using a combined variational autoencoder and predictor model." 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021., Aksoy, Doruk, et al. "An Incremental Tensor Train Decomposition Algorithm." arXiv preprint arXiv:2211.12487 (2022)., and Chen, Brian, et al. "Low-Rank Tensor-Network Encodings for Video-to-Action Behavioral Cloning", forthcoming
- Discipline:
- Engineering and Science
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CT Data of UMMP VP 68409, Plesiadapis gingerichi, right maxilla with M1/ and roots of P4/ (holotype)
- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for Right maxilla with M1/ and roots of P4/ of Plesiadapis gingerichi (University of Michigan Museum of Paleontology catalog number UMMP 68409) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Plesiadapidae, UMMP, University of Michigan Museum of Paleontology, Paleocene, and cb9a3c69-55da-9032-5b3e-d02dc72013eb
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for Incisor frag. of Plesiadapis gingerichi (University of Michigan Museum of Paleontology catalog number UMMP 68409) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Plesiadapidae, UMMP, University of Michigan Museum of Paleontology, Paleocene, and cb9a3c69-55da-9032-5b3e-d02dc72013eb
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for Right M3/ of Plesiadapis gingerichi (University of Michigan Museum of Paleontology catalog number UMMP 68409) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Plesiadapidae, UMMP, University of Michigan Museum of Paleontology, Paleocene, and cb9a3c69-55da-9032-5b3e-d02dc72013eb
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for Right M2/ of Plesiadapis gingerichi (University of Michigan Museum of Paleontology catalog number UMMP 68409) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Plesiadapidae, UMMP, University of Michigan Museum of Paleontology, Paleocene, and cb9a3c69-55da-9032-5b3e-d02dc72013eb
- Discipline:
- Science
-
- Creator:
- University of Michigan Museum of Paleontology and CTEES
- Description:
- Reconstructed CT slices for Left dentary with P/4-M/1, M/2 trigonid, P/3 roots of Plesiadapis gingerichi (University of Michigan Museum of Paleontology catalog number UMMP 68409) as a series of TIFF images. Raw projections are not included in this dataset. The reconstructed slice data from the scan are offered here as a series of unsigned 16-bit integer TIFF images. The upper left corner of the first image (*_0000.tif) is the XYZ origin.
- Keyword:
- Paleontology, Fossil, CT, Plesiadapidae, UMMP, University of Michigan Museum of Paleontology, Paleocene, and cb9a3c69-55da-9032-5b3e-d02dc72013eb
- Discipline:
- Science
-
- Creator:
- Towne, Aaron, Yeh, Chi-An., Patel, Het, and Taira, Kunihiko
- Description:
- This dataset contains data from a three-dimensional large eddy simulation of Mach 0.3 flow over a NACA 0012 airfoil at Reynolds number 23,000, which features a transitional boundary layer, separation over a recirculation bubble, and a turbulent wake. The dataset contains 16,000 time-resolved snapshots of the mid-span and spanwise-averaged velocity fields. All data are stored within hdf5 files, and a Matlab script showing how the data can be read and manipulated is provided. Please see the ‘airfoilLES_README.pdf’ file for more information. We recommend using the ‘airfoilLES_example.zip’ file as an entry point to the dataset. and The dataset is part of “A database for reduced-complexity modeling of fluid flows” (see references below) and is intended to aid in the conception, training, demonstration, evaluation, and comparison of reduced-complexity models for fluid mechanics. The paper introduces the flow setup and computational methods, describes the available data, and provides an example of how these data can be used for reduced-complexity modeling. Users of these data should cite the papers listed below.
- Citation to related publication:
- Towne, A., Dawson, S., Brès, G. A., Lozano-Durán, A., Saxton-Fox, T., Parthasarthy, A., Biler, H., Jones, A. R., Yeh, C.-A., Patel, H., Taira, K. (2022). A database for reduced-complexity modeling of fluid flows. AIAA Journal 61(7): 2867-2892. and Yeh, C.-A. and Taira, K. (2019) Resolvent-analysis-based design of airfoil separation control. Journal of Fluid Mechanics, 867:572–610.
- Discipline:
- Science and Engineering