cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25550/v84
title: microCT - Soft Tissue of a Myf5-Cre;Smad4fl/fl at P0

description: Mouse ID: JF266 This dataset includes microCT scans of the skull of a Myf5-Cre;Smad4fl/fl at P0. The scan is in NiFTI format. See Help section for a list of free applications to view files in NiFTI format
DOI: 10.25550/veg
title: Micro-CT images of adult mouse skulls, Collaborative Cross C57BL6 x CAST

description: The dataset consists of a set of images for 7 mice with one parent from the C57BL6 strain and the other from the CAST strain. For each mouse we provide an image file in .aim format, a .txt file with the image data, and a .hx file. Morphometrics will be added for the data as measurements are completed.
DOI: 10.7302/z2p848vs
title: Appendix2

description: Gene ontology data from zebrafish regeneration and mouse degeneration models.
description: Methods are described in the dissertation, "Regulation of Müller Stem Cell Properties: Insights From a Zebrafish Model".
DOI: 10.7302/z2m906kk
title: Simulation Parameters used in the Study titled "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method"

description: We provide the parameters used in Umbrella Sampling simulations reported in our study "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method", namely the set positions and spring constants for each window in simulations. Two tables are provided. Table 1 lists the names of the peptides and their corresponding sequences. Table 2 lists the parameters. The abstract of our work is the following:

We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with Weighted Histogram Analysis Method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse-grained (CG) force field (MARTINI) is less prone to significant error induced by biased-sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3-4 residue peptide segments while leaving the remain-ing peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and relia-bly estimate the binding free energy between an arbitrary peptide and an MHC class II molecule.
description: The simulation parameters supplied in this document can be applied to conduct Umbrella Simulations in GROMACS 4.6.5
Two types of parameters are provided, the set distance parameter along the reaction coordinate and the spring force (K) applied during the simulation.
These parameters can be supplied to GROMACS 4.6.5 via the following commends in mdp file:
pull: umbrella
description: pull-geometry: distance
description: pull-coord1-init: set_distance_in_table
description: pull-coord1-k: K_value_in_table
DOI: 10.7302/8xk2-jw66
title: Quantum-Mechanical Determination of the Incorporation of Pentavalent Plutonium into Carbonate and Sulfate Minerals

description: Files are uploaded as crystallographic information files (.cif), the standard text file format for representing crystallographic information.
These files contain the optimized molecular models for pentavalent plutonium incorporation reactions into/onto barite, anglesite, celestine, anhydrite, aragonite, and calcite host minerals.

description: Data set was generated using Biovia Materials Studio 6.1 Service Pack 2 as described in the associated journal article.
DOI: 10.7302/vd87-wm68
title: On the growth of Si nanoparticles in non-thermal plasma: physisorption to chemisorption conversion

description: Non-thermal plasma systems offer unique opportunities in the fields of bio-imaging, drug delivery, photovoltaics, microelectronics manufacturing. Such interests are largely inspired by the fact that hot plasma electrons coexist with neutral species and ions close to room-temperature under non-thermal plasma conditions. Modeling of these systems requires a deep understanding of the atomistic processes underlying the rich chemistry of the various radicals and ions with the nascent nanoparticle surface. A key parameter for determining the contribution of a certain radical/ion species to the nanoparticle surface growth, called sticking coefficient, is computed as a weighted sum from the simulated sticking outcomes with different collision velocities drawn from a Maxwell-Boltzmann distribution at certain temperatures. In this work, the collisions of SiHx (x=1-4) fragments and silicon cluster (Si4, Si2H6, and Si29H36) surfaces, responsible for the sticking coefficients, are simulated by molecular dynamics (MD) with a reactive force field. The dependence of sticking coefficients on temperature, H coverage of both silane fragments and cluster surfaces, and the size of the cluster, are systematically examined. And the mechanism underlying the sticking events, specifically the conversion of physical aggregation to chemisorption is investigated to better understand the complex interplay between factors influencing the surface growth. The detailed and multi-parameter model of sticking coefficients, accompanied by the mechanism study of physisorption to chemisorption conversion, provides a more accurate and robust approximation of surface growth rate using sticking coefficients, and a deeper understanding of surface growth processes, for the wider non-thermal plasma simulation community.
description: The data are mechanism labeling of the Molecular Dynamics (MD) simulation trajectories at the end of allocated simulation time. The MD simulation is carried out using LAMMPS (https://www.lammps.org) and the atomic interactions were modeled using a classical all-atom reactive force field. The labeling is made by computing the composition and the number of clusters in the system.
Two atoms were assigned to the same cluster if their distance was less than twice their typical bond length, namely 0.44, 0.32 and 0.148 nm for Si/Si, Si/H, and H/H pairs, respectively. 

If the trajectory outcome is non-sticking (more than one cluster), the label is "-1"
description: If the trajectory outcome is  physisorption (one cluster, but no chemical bond formed), the label is "0"
description: If the trajectory outcome is chemisorption (one cluster, chemical bonds formed), the label is "1", "2", "3", "4", where the numerical value corresponds to the number new bonds formed.
DOI: 10.7302/y1a2-8a66
title: CT Data of UMMP VP 81827, Cantius mckennai right astragalar body

description: Reconstructed CT slices for a right astragalar [astragalus] body of Cantius mckennai (University of Michigan Museum of Paleontology catalog number UMMP VP 81827), as a series of TIFF images. Raw projections are not included in this dataset.
description: Specimen UMMP VP 81827 was scanned with a Nikon XT H 225ST μCT system housed in the Department of Earth and Environmental Sciences at the University of Michigan. Scans were collected with the following settings: energy settings, 110 kV, 80 µA
description: source to object distance, 39.019932 mm
description: scanned with 3141 projections
description: voxel size, x = y = z = 0.014125 mm
description: slice dimension (in pixels),  x = 514, y = 607
description: number of slices, 748 16-bit TIFF images. Additional metadata can be found in the xtek and vgi files.
DOI: 10.7302/z20z71jp
title: Decrease in radiative forcing by organic aerosol nucleation, climate, and land use change

description: The dataset contains the Fortran programs applied in the latest CESM/IMPACT model as well as the data created from this model, which are used in the referenced paper.
description: The CESM/IMPACT model is used to create these data.
DOI: 10.7302/6gk4-6v52
title: Centimeter-Scale Electron Diffusion in Photoactive Organic Heterostructures

description: Mathematica Diffusion Simulation: Programmed by Coburn, Caleb. Simulation of diffusion in organic heterostructures, including least square fits and statistical goodness of fit analysis. Used to calculate fits to transient data in Fig 1, 3 and Extended Data Fig.2. Example data file included for download

Matlab Montecarlo simulation: Programmed by Coburn, Caleb. Montecarlo simulation of charge diffusion on a cubic lattice to determine lateral diffusion length as a function of barrier height, assuming thermionic emission over the barrier.

Matlab 2D Diffusion Simulation:Programmed by Coburn, Caleb. Modified from BYU Physics 430 Course Manual. Simulates diffusion around a film discontinuity, such a cut. Used to generate fits to Extended Data Fig. 1



description: Codes written in Matlab and Mathematica software packages
DOI: 10.7302/z2862dp1
title: Video data of predation and parasitism by arthropods on small vertebrates in lowland Peruvian Amazon

description: Nighttime and diurnal surveys in the lowland Peruvian Amazon of Los Amigos Biological Station were conducted in order to describe herpetological diversity at this site. As a result of these surveys, the predation event between a Pamphobeteus sp. and Marmosops sp. and the myiasis of Ranitomeye uakarii were observed. The video footage was recorded in order to document these interesting interactions between arthropod predators and parasites and vertebrate prey and hosts, and are included for publication in the short communication "Ecological interactions between arthropods and small vertebrates in a lowland Amazon rainforest" in the journal Amphibian and Reptile Conservation.
 
description: On 18 November 2016, at 2313 h during a night survey, we observed a theraphosid spider, Pamphobeteus sp. (Theraphosidae) preying upon a small grey mouse opossum, Marmosops sp. (Didelphidae). We filmed the interaction using an iPhone 5s.

On 20 January 2017, at 1230 h, we observed an individual of Ranitomeya uakarii hopping on the leaf litter
description: we captured it and placed it in a plastic bag and took it to the lab to process it later the same day. When we returned from fieldwork around 1630 h, the frog was dead and we noticed a maggot that periodically emerged from a small lesion on its back. This observation took place in terra firme forest near Madre Selva Biological Station (3°37'14.8" S, 72°14'48.5" W), Loreto region, northern Peru.
DOI: 10.7302/snbp-dn51
title: Action current data for investigating the development and organization of GnRH neuron activity in mice.

description: This data is a subset of that originally produced as part of an effort to characterize GnRH neuron activity during prepubertal development in control and PNA mice and investigate the potential influences of sex and PNA treatment on this process (1). It was later used in (2) to further investigate the firing patterns of GnRH neurons in these categories of mice and determine how these patterns might differ based on age and treatment condition. 

The data files can be opened and examined using Wavemetric's Igor Pro software. Code used to further examine and visualize the data can be found at https://gitlab.com/um-mip/mc-project-code.

This research was supported by National Institute of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development R01 HD34860 and P50 HD28934. 

(1) Dulka EA, Moenter SM. Prepubertal development of gonadotropin-releasing hormone (GnRH) neuron activity is altered by sex, age and prenatal androgen exposure. Endocrinology 2017; 158:3941-3953

(2) Penix JJ, DeFazio RA, Dulka EA, Schnell S, Moenter SM. Firing patterns of gonadotropin-releasing hormone (GnRH) neurons are sculpted by their biology. Pending.
description: Action currents, which are associated with action potential firing, were recorded from GFP-identified neurons in acutely-prepared brain slices from control and PNA female mice at three weeks of age and adults. These events were detected, confirmed, and later analyzed with custom software written in Igor Pro. For more specific details on the data acquisition process, please refer to the following:

Dulka EA, Moenter SM. Prepubertal development of gonadotropin-releasing hormone neuron activity is altered by sex, age and prenatal androgen exposure. Endocrinology 2017
description: 158:3943-3953
DOI: 10.7302/z2736p4b
title: Transmission of Oral microbiome and Sequencing - Influenza Susceptibility

description: Data include variables used to run mixed effects models examining the association between the nose/throat microbiome and influenza virus infection. Certain individual participant data have been excluded due to identifiability concerns. Data also include the oligotype count table and taxonomic classifications.;Curation Notes: Readme updated Nov. 29, 2018 with context for oligotype and taxonomy files, and citation to associated article.
description: Index cases of influenza were identified at a major healthcare facility in Managua, Nicaragua. Index cases and their family members were enrolled for follow up and with nose/throat samples collected at 2-3 day intervals for up to 13 days. Sociodemographic and household data were collected at enrollment. 16S rRNA sequencing (V4, Illumina MiSeq) was conducted on samples collected at enrollment and at the last day of follow up. Generalized linear mixed effects models were used to examine 1) the role of the nose/throat microbiota on susceptibility to influenza virus and 2) changes in the nose/throat microbiota during influenza virus infection.
DOI: 10.7302/z26t0jw6
title: Dataset for the "Response of the Geospace System to the Solar Wind Dynamic Pressure Decrease on 11 June 2017: Numerical Models and Observations"

description: 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.  
description: The simulation data were generated through the use of the following models: the Block Adaptive Tree Solarwind Roe Upwind Scheme (BATS-R-US), Comprehensive Ring Current Model (CRCM), Ridley Ionosphere Model (RIM) and the Global Ionosphere Thermosphere Model (GITM). The simulations were performed on the Yellowstone and Cheyenne Supercomputer Clusters provided by National Center for Atmospheric Research (NCAR) Computational and Information Systems Laboratory, sponsored by the National Science Foundation.
DOI: 10.7302/qnsq-cs38
title: Data and Data products for machine learning applied to solar flares

description: 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.;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.
description: The data deposited here are the both the input and resulting output of our machine learning efforts for predicting solar flare events. The input data are produced by our pre-processing pipeline, which is built to extract from two sources -- the Geostationary Operational Environmental Satellites (GOES) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) . The GOES files provide a list of flare events in excel csv format.  The SHARP files provide time sequences of more than 20 physical parameters derived from SDO/HMI data, which are saved in hdf5 format.

The remaining files (B_HARPs_CNNencoded_part_XXX.hdf5, and M_X_HARPs_CNNencoded_part_XXX.hdf5) are the output from the convolutional neural network (CNN), a deep learning algorithm used here to extract/select features from raw HMI data.  The CNN is a deep learning model trained to capture both the spatial and temporal information from HMI magnetogram data for strong/weak flare classification and for predictions of flare intensities.  The input data for the CNN are HMI Active Region Patch (HARP) 3-component vector magnetograms available online from the Stanford Joint Science Operations Center (JSOC) at  http://jsoc.stanford.edu/.
DOI: 10.7302/xsjc-1k55
title: Data and Syntax for Gainsburg & Earl (2018) in JESP

description: This research explores trigger warnings as an interpersonal emotion-regulation strategy, introducing a temporal dimension to interpersonal emotion-regulation by regulating others' future, anticipated emotions. Across studies, believing that trigger warnings are protective (versus coddling) increased their effect on anticipated negative affect, but weakened their effect on experienced negative affect. Study 1 demonstrated that anticipated anxiety for warned-of content predicts intentions to avoid information. Furthermore, beliefs about trigger warnings as protective (versus coddling) best predicted anticipated anxiety for warned-of content and subsequent intentions to avoid. In Study 2, participants had higher anticipated negative affect for videos with trigger warnings, compared to those without, and this mediated increased avoidance for warned-of videos. In Study 3, trigger warnings preceding essays increased anticipated negative affect and attentional-regulation strategies, but reduced experiences of negative affect. For more information, please see the article Gainsburg, I., & Earl, A. (2018). Trigger warnings as an interpersonal emotion-regulation tool: Avoidance, attention, and affect depend on beliefs. Journal of Experimental Social Psychology, 79, 252–263. https://doi.org/10.1016/j.jesp.2018.08.006
description: Data was collected on MTurk, downloaded as a .sav file for SPSS, and cleaned/analyzed within SPSS.
DOI: 10.7302/z2kh0k8v
title: Citations to Open and Closed Access Articles: Treatment and Control Group Data

description: This random sample of OA articles comes from Deep Blue <deepblue.lib.umich.edu/documents>, the University of Michigan’s institutional repository service. Each OA article has the following characteristics: Prior to a known date (ranging from 2006 to the 2013) these articles—the final published version—were only available by subscription. After that date, they became freely available via Deep Blue. Meanwhile, other articles from the same journal issue as the now-OA article continued to only be available to subscribers. None of the OA articles were self-selected; authors did not choose to deposit the articles in question in Deep Blue, since we made them open via blanket licensing agreements between the publishers and the library.
description: These data are a random selection of 3,850 papers—peer-reviewed and review articles only
description: bibliographies, book reviews, corrections, discussions, editorials, letters, notes, etc. were not considered—from Deep Blue <deepblue.lib.umich.edu/documents> with original publication dates ranging from 1990 to 2013. These are matched with the 89,895 corresponding articles which remained closed, using the specific journal issue as a proxy for comparability of subject matter and quality. These citations are matched with data from citation information from Thomson Reuters’ Web of Science and Journal Citation Reports databases.
DOI: 10.7302/pnmm-4v40
title: Effect of financial incentives on head CT use dataset

description: SPSS is required to access processed dataset in .sav format. Model output is provided as a word document, and Qualtrics survey instrument is included as PDF and .docx, where .docx version contains survey logic and question numbers.
description: We conducted a cross-sectional survey of patients at the University of Michigan Emergency Department (ED). Each participant was presented with a hypothetical scenario involving an ED visit following minor traumatic brain injury. Participants were given information regarding potential benefit (detecting brain hemorrhage) and risk (developing cancer) of head CT scan, as well as an incentive of $0 or $100 to forego testing. We used 0.1% and 1% for test benefit and risk, and values for risk, benefit, and financial incentive varied across participants. Our primary outcome was patient preference to undergo testing. We also collected demographic and numeracy information. Then, we used logistic regression to estimate odds ratios, which were adjusted for multiple potential confounders. Our sample size was designed to find at least 300 events (preference for testing) to allow for inclusion of up to 30 covariates in fully adjusted models. We had 85-90% power to detect a 10% absolute difference in testing rate across groups, assuming a 95% significance level.
DOI: 10.7302/0qnz-fw92
title: Survey Distributional Methods Analyses Data

description: We compared the response rates, cost, and the average income of participants pertaining to 6 different survey distribution methods used in an initial study about mobility-on-demand services. We used the data to identify survey and recruitment methods that are more effective in reaching hard-to-reach populations. All the raw data used for calculations and the calculations themselves can be found in the attached spreadsheets.;Initial analyses have identified in-person onsite recruitment as one of the better methods of reaching hard-to-reach populations, and is calling for continued work in improving research methods in the field of HCI.
description: The data used for this study comes from the survey responses of a study on Mobility-on-Demand in 2019. From the survey responses, we gathered the income information of the participants and the method through which they were recruited. From the study, we gathered the cost associated with each survey distributional method, and data such as number of people contacted, number of people responded, and number of complete/valid responses. We calculated a series of rates, including response rates, cost effectiveness, and average income through simple Excel functions, such as sums, additions, divisions, and means.
DOI: 10.7302/xtsr-jx10
title: Inferring the behavior of distributed energy resources from incomplete measurements (project outputs)

description: This is the code that resulted from NSF grant ECCS-1508943, "Inferring the behavior of distributed energy resources from incomplete measurements." The project focused on developing control, estimation, and modeling methods for residential demand response and electric distribution networks. 

The talks, papers, and poster in Deep Blue: http://hdl.handle.net/2027.42/149480
description: 1. Online learning
2. Kalman filtering
3. Optimal control (MPC and LQR)
4. Aggregate modeling