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  • Centimeter-Scale Electron Diffusion in Photoactive Organic Heterostructures

    Creator: Forrest, Stephen R., Panda, Anurag, Qu, Yue, Che, Xiaozhou, Coburn, Caleb, and Burlingame, Quinn
    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
  • Low-Fe(III) Greenalite Was a Primary Mineral from Neoarchean Oceans (Raw Data)

    Creator: Johnson, Jena E.
    Description: Note: The "Readme_Metadata" file was updated on March 15, 2018 to include a citation to the related article making use of this data and was reformatted to be presented as a pdf file rather than as a docx file. and This data set is comprised of synchrotron-based X-ray transmission and absorption spectroscopy data as well as X-ray diffraction patterns that were performed to characterize the best-preserved examples of nanoscale iron silicate mineral inclusions from 2.5 billion-year-old Banded Iron Formations (BIFs) and ferruginous cherts.
  • Retinal fundus images for glaucoma analysis: the RIGA dataset

    Creator: Almazroa, Ahmed
    Description: The dataset includes 3 different files: 1) MESSIDOR dataset file contains 460 original images and 460 images for every single ophthalmologist manual marking in total of 3220 images for the entire file. 2) Bin Rushed Ophthalmic center file and contains 195 original images and 195 images for every single ophthalmologist manual marking in total of 1365 images for the entire file. 3) Magrabi Eye center file and contains 95 original images and 95 images for every single ophthalmologist manual marking in total of 665 images for the entire file. The total of all the dataset images are 750 original images and 4500 manual marked images. The images are saved in JPG and TIFF format.
  • Gelada foraging ecology in the Simien Mountains, Ethiopia

    Creator: Jarvey, Julie C
    Description: This includes data used for analysis for the publication: "Graminivory and fallback foods: Annual diet profile of geladas (Theropithecus gelada) living in the Simien Mountains National Park, Ethiopia". A revised version of the "foraging.scans.xlsx" file was uploaded as a csv file on Dec 13, 2017 to include the addition of the "crop" as category in the "Diet.Item" column. Previously "crop" was included in the "other" category. An updated version of the "readme_foraging.scans.txt" was uploaded on Dec 13, 2017 to account for this change, provide additional information on variables in the "season" column and to include contact information for the creator of the data set. Revised versions of two other files "readme_rainfall.txt" and "readme_underground.samples.txt" were also uploaded on Dec 13, 2017. Both revisions include additional information to account for missing variables and contact information for the creator of the data set. The original files are retained in this data set and are marked as being the originals in the file name. Note: A citation to the related article was added to the metadata on March 12, 2018.
  • Demographically diverse crowds are typically not much wiser than homogeneous crowds

    Creator: de Oliveira, Stephanie and Nisbett, Richard E.
    Description: These studies assess the effect of social identity on judgement and are described in "Demographically diverse crowds are typically not much wiser than homogeneous crowds" (de Oliveira, S., & Nisbett, R. E. Proceedings of the National Academy of Sciences, 2018) and the article’s Supporting Information appendix. Some studies use a variety of questions to assess multiple social identity factors; the other studies are narrowed to particular social identity variables. Each study includes some type of estimation or prediction task, collects social identity variables, and asks participants to indicate their answer strategies. Study 1 is a trivia and prediction task based on football team fan identity. Study 2 reports on demographics plus political and religious identity and asks participants to predict vote percentages in presidential primaries. Study 3 participants estimate the percentage of Americans that support statements on various polarizing political views and give likelihood ratings for presidential candidates to win the Iowa caucus; a variety of identity questions are asked including political and religious identity. Study 4 includes demographics plus political and religious identity questions and asks participants to predict how the candidates would perform in the 2016 United States presidential election. Study 5 asks participants to guess the popularity rating of books that had either gender-specific or gender-neutral appeal, and also to rate their own interest in the books. Demographic-based social identity variables such as sex are included. Study 6 includes a wide variety of social identity variables and asks participants to estimate the likelihood of events occurring in the near future. Study 7 participants are from diverse national backgrounds and completed judgement tasks that predicted stock prices, Olympic performance, and news events outcomes. The data are generally interpretable when examined in conjunction with the target article. Codebooks are in preparation and further information can be obtained from the first author.
  • FCAV Simulation Dataset

    Creator: Vasudevan, Ram, Barto, Charles, Rosaen, Karl, Mehta, Rounak, Matthew, Johnson-Roberson, and Nittur Sridhar, Sharath
    Description: A dataset for computer vision training obtained from long running computer simulations
  • Bayesian Population Correlation: A probabilistic approach to comparing detrital zircon age distributions

    Creator: Tye, Alexander R, Wolf, Aaron S, and Niemi, Nathan A
    Description: Detrital zircon age distributions provide robust insights into past sedimentary systems, but these age distributions are often complex and multi-peaked, with sample sizes too small to confidently resolve population distributions. This limited sampling hinders existing quantitative methods for comparing detrital zircon age distributions, which show systematic dependence on the sizes of compared samples. The proliferation of detrital zircon studies motivates the development of more robust quantitative methods. We present the first attempt, to our knowledge, to infer probability model ensembles (PMEs) for samples of detrital zircon ages using a Bayesian method. Our method infers the parent population age distribution from which a sample is drawn, using a Monte Carlo approach to aggregate a representative set of probability models that is consistent with the constraints that the sample data provide. Using the PMEs inferred from sample data, we develop a new estimate of correspondence between detrital zircon populations called Bayesian Population Correlation (BPC). Tests of BPC on synthetic and real detrital zircon age data show that it is nearly independent from sample size bias, unlike existing correspondence metrics. Robust BPC uncertainties can be readily estimated, enhancing interpretive value. When comparing two partially overlapping zircon age populations where the shared proportion of each population is independently varied, BPC results conform almost perfectly to expected values derived analytically from probability theory. This conformity of experimental and analytical results permits direct inference of the shared proportions of two detrital zircon age populations from BPC. We provide MATLAB scripts to facilitate the procedures we describe.
  • Input files for the Global Ionosphere Thermosphere Model for 2010

    Creator: Ridley, Aaron
    Description: These files (2010_gitm_input_files.tgz) were used to run GITM for 2010 for each month. GITM paper is here: (10.1016/j.jastp.2006.01.008 <>) GITM code is in file gitm_170809.tgz and PLEASE NOTE THAT THIS IS A LARGE DATA SET (3.56 TB) AND IS AVAILABLE FOR DOWNLOAD VIA GLOBUS:
  • Model results for "Modeling study of geospace system response to the solar wind dynamic pressure enhancement on March 17, 2015"

    Creator: Dogacan Ozturk
    Description: -3D binary files from BATSRUS/CRCM/RIM [2 files] -2D ascii files from RIM [5 files] -1D asci files for virtual ground magnetometers [5 files] -3D binary files from GITM [5 files] -1D ascii file from GITM [1 file]
  • The KSU-UMD Dataset for Benchmarking for Audio Forensic Algorithms

    Creator: Hafiz Malik and Muhammad Khurran Khan, King Saud University
    Description: Details of the microphone used for data collection, acoustic environment in which data was collected, and naming convention used are provided here. 1 - Microphones Used: The microphones used to collect this dataset belong to 7 different trademarks. Table (1) illustrates the number of used Mics of different trademarks and models. Table 1: Trademarks and models of Mics Mic Trademark Mic Model # of Mics Shure SM-58 3 Electro-Voice RE-20 2 Sennheiser MD-421 3 AKG C 451 2 AKG C 3000 B 2 Neumann KM184 2 Coles 4038 2 The t.bone MB88U 6 Total 22 2- Environment Description: A brief description of the 6 environments in which the dataset was collected is presented here: (i) Soundproof room: a small room (nearly 1.5m × 1.5m × 2m), which is closed and completely isolated. With an exception of a small window in the front side of the room which is made of glass, all the walls of the room are made of wood and covered by a layer of sponge from the inner side, and the floor is covered by carpet. (ii) Class room: standard class room (6m × 5m × 3m). (iii) Lab: small lab (4m × 4m × 3m). All the walls are made of glasses and the floor is covered by carpet. The lab contains 9 computers. (iv) Stairs: is in the second floor. The place of recording is 3m × 5m (v) Parking: is the college parking. (vi) Garden: is an open space outside the buildings. 3- Naming Convention: This set of rules were followed as a naming convention to give each file in the dataset a unique name: (i) The file name is 19 characters long, and consists of 5 sections separated by underscores. (ii) The first section is of 3 characters indicates the Microphone trademark. (iii) The second section of 4 characters indicates the microphone model as in table (2). (iv) The third section of 2 characters indicates a specific microphone within a set of microphones of the same trademark and model, since we have more than one microphone of the same trademark and model. (v) The fourth section of 2 characters indicates the environment, where Soundproof room --> 01 Class room --> 02 Lab --> 03 Stairs --> 04 Parking --> 05 Garden --> 06 (vi) The fifth section of 2 characters indicates the language, where Arabic --> 01 English --> 02 Chinese --> 03 Indonesian --> 04 (vii) The sixth section of 2 characters indicates the speaker. Table 2: Microphones Naming Criteria Original Mic Trademark and model --> Naming Convenient Shure SM-58 --> SHU_0058 Electro-Voice RE-20 --> ELE_0020 Sennheiser MD-421 --> SEN_0421 AKG C 451 --> AKG_0451 AKG C 3000 B --> AKG_3000 Neumann KM184 --> NEU_0184 Coles 4038 --> COL_4038 The t.bone MB88U --> TBO_0088 For example: SEN_0421_02_01_02_03 is an English file recorded by speaker number 3 in the soundproof room using microphone number 2 of Sennheiser MD-421