100+ datasets found
  1. Statin prescriptions by year using THIN database 1990–2005.

    • plos.figshare.com
    xls
    Updated Jun 7, 2023
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    Mariam Molokhia; Paul McKeigue; Vasa Curcin; Azeem Majeed (2023). Statin prescriptions by year using THIN database 1990–2005. [Dataset]. http://doi.org/10.1371/journal.pone.0002522.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 7, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Mariam Molokhia; Paul McKeigue; Vasa Curcin; Azeem Majeed
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Statin prescriptions by year using THIN database 1990–2005.

  2. Baseline characteristics of the incident and prevalent cohort in the THIN...

    • plos.figshare.com
    xls
    Updated Jun 6, 2023
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    Emily S. Petherick; Nicky A. Cullum; Kate E. Pickett (2023). Baseline characteristics of the incident and prevalent cohort in the THIN database 2001 to 2006. [Dataset]. http://doi.org/10.1371/journal.pone.0058948.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Emily S. Petherick; Nicky A. Cullum; Kate E. Pickett
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Baseline characteristics of the incident and prevalent cohort in the THIN database 2001 to 2006.

  3. Data from: High Throughput Experimental Materials Database

    • kaggle.com
    Updated Mar 30, 2024
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    Chao Zhuang (2024). High Throughput Experimental Materials Database [Dataset]. https://www.kaggle.com/datasets/chaozhuang/high-throughput-experimental-materials-database
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 30, 2024
    Dataset provided by
    Kaggle
    Authors
    Chao Zhuang
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    This is a condensed version of HTEM database downloaded via HTEM API from National Renewable Energy Laboratory. Due to network constraints, all entries without XRD entries are discarded.

    Dataset Overview

    The index file contains experiment conditions of 1400+ experiments performed by the high-throughput experiment platform in NREL. Each experiments contains 44 samples, whose associated data are stored in the samples folder. The 44 samples in each experiment all have different thin film thickness and composition. Depending on the experiment setup, the sample data files may contain data from X-ray Fluorescence (thin film composition), X-ray Diffraction (crystalline structure), electronic measurement (thin film conductivity), and optical spectra (light absorption).

    This dataset provides a complete record of experimental condition, structural characterization, and properties measurement, making it a valuable resource for data-mining for a better understanding of complex process-structure-property relationships in thin film materials.

    Please cite: A. Zakutayev, N. Wunder, M. Schwarting, J. D. Perkins, R. White, K. Munch, W. Tumas and C. Phillips, Sci Data 5, 180053 (2018).

  4. r

    Observation codelists_THIN UK.xlsx

    • researchdata.edu.au
    • research-repository.rmit.edu.au
    Updated Oct 27, 2022
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    Joanna Zhi Jie Ling (2022). Observation codelists_THIN UK.xlsx [Dataset]. http://doi.org/10.25439/RMT.21398028.V1
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    Dataset updated
    Oct 27, 2022
    Dataset provided by
    RMIT University, Australia
    Authors
    Joanna Zhi Jie Ling
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Observation codelists (AHD codes) for identifying anthropometric, clinical and laboratory data from the THIN UK primary database used for the project:Therapeutic Inertia for Glycaemic and Cardiovascular Risk Factor Control in Patients with Type 2 Diabetes: A Real-world Electronic Medical Records Based Study

  5. w

    Users' guide to PETROG: AGSO's petrography database

    • data.wu.ac.at
    • dev.ecat.ga.gov.au
    pdf
    Updated Jun 26, 2018
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    Corp (2018). Users' guide to PETROG: AGSO's petrography database [Dataset]. https://data.wu.ac.at/schema/data_gov_au/Yjc2NjIwYTgtOTNiZC00ZTI0LTlkOTctNzQ1YjJhMzIzZDJh
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    pdfAvailable download formats
    Dataset updated
    Jun 26, 2018
    Dataset provided by
    Corp
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    PETROG, AGSO's Petrography Database, is a relational computer database of petrographic data obtained from microscopic examination of thin sections of rock samples. The database is designed for petrographic descriptions of crystalline igneous and metamorphic rocks, and also for sedimentary petrography. A variety of attributes pertaining to thin sections can be recorded, as can the volume proportions of component minerals, clasts and matrix.

    PETROG is one of a family of field and laboratory databases that include mineral deposits, regolith, rock chemistry, geochronology, stream-sediment geochemistry, geophysical rock properties and ground spectral properties for remote sensing. All these databases rely on a central Field Database for information on geographic location, outcrops and rock samples. PETROG depends, in particular, on the Field Database's SITES and ROCKS tables, as well as a number of lookup tables of standard terms. ROCKMINSITES, a flat view of PETROG's tables combined with the SITES and ROCKS tables, allows thin-section and mineral data to be accessed from geographic information systems and plotted on maps.

    This guide presents an overview of PETROG's infrastructure and describes in detail the menus and screen forms used to input and view the data. In particular, the definitions of most fields in the database are given in some depth under descriptions of the screen forms - providing, in effect, a comprehensive data dictionary of the database. The database schema, with all definitions of tables, views and indexes is contained in an appendix to the guide.

  6. Digital images of petrology rock thin sections

    • data.europa.eu
    • metadata.bgs.ac.uk
    • +2more
    unknown
    + more versions
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    British Geological Survey (BGS), Digital images of petrology rock thin sections [Dataset]. https://data.europa.eu/data/datasets/digital-images-of-petrology-rock-thin-sections?locale=en
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    unknownAvailable download formats
    Dataset provided by
    British Geological Surveyhttps://www.bgs.ac.uk/
    Authors
    British Geological Survey (BGS)
    Description

    Digital images of petrology rock thin sections from samples that are referenced in the BGS Petrological Collection Database (Britrocks). Two reference images are being captured for each thin section, one taken in Plane Polarized Light (PPL) and the other in Crossed Polarized Light (XPL). The Britrocks database provides an index to the BGS mineralogical & petrological collection. The computer database covers samples in the UK onshore mapping collection together with worldwide reference minerals and the Museum Reserve collection. The first England and Wales collection sample is from circa 1877, Threshthwaite Comb, Cumbria (collected by the Reverend Clifton Ward). The addition of new samples, transfer of records from registers and updates of existing records is ongoing on a regular basis. Internet access to the database is provided on the BGS web site. Capture of the Scottish Collections began February 2012. Capture of the English and foreign collections began in December 2012.

  7. p

    Thin & Healthy Locations Data for United States

    • poidata.io
    csv, json
    Updated Dec 2, 2025
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    Business Data Provider (2025). Thin & Healthy Locations Data for United States [Dataset]. https://poidata.io/brand-report/thin-healthy/united-states
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    json, csvAvailable download formats
    Dataset updated
    Dec 2, 2025
    Dataset authored and provided by
    Business Data Provider
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    United States
    Variables measured
    Website URL, Phone Number, Review Count, Business Name, Email Address, Business Hours, Customer Rating, Business Address, Brand Affiliation, Geographic Coordinates
    Description

    Comprehensive dataset containing 35 verified Thin & Healthy locations in United States with complete contact information, ratings, reviews, and location data.

  8. r

    Diagnosis codelists_THIN UK.xlsx

    • research-repository.rmit.edu.au
    • researchdata.edu.au
    xlsx
    Updated May 31, 2023
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    Joanna Zhi Jie Ling (2023). Diagnosis codelists_THIN UK.xlsx [Dataset]. http://doi.org/10.25439/rmt.21398025.v1
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    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    RMIT University
    Authors
    Joanna Zhi Jie Ling
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Diagnosis codelists (Read codes) for identifying different conditions from the THIN UK primary database used for the project:Therapeutic Inertia for Glycaemic and Cardiovascular Risk Factor Control in Patients with Type 2 Diabetes: A Real-world Electronic Medical Records Based Study

  9. Case-crossover comparison of myopathy/myalgia based on 16,591 users...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
    + more versions
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    Mariam Molokhia; Paul McKeigue; Vasa Curcin; Azeem Majeed (2023). Case-crossover comparison of myopathy/myalgia based on 16,591 users extracted from the THIN database (1991–2006): Event rates using 12 week cut off for exposure. [Dataset]. http://doi.org/10.1371/journal.pone.0002522.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Mariam Molokhia; Paul McKeigue; Vasa Curcin; Azeem Majeed
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Case-crossover comparison of myopathy/myalgia based on 16,591 users extracted from the THIN database (1991–2006): Event rates using 12 week cut off for exposure.

  10. d

    Data from: Geochemical data, thin section images, and modal mineralogy of...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Sep 14, 2025
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    U.S. Geological Survey (2025). Geochemical data, thin section images, and modal mineralogy of selected bedrock samples in the western half of the Emporia 30’ x 60’ quadrangle, Virginia and North Carolina [Dataset]. https://catalog.data.gov/dataset/geochemical-data-thin-section-images-and-modal-mineralogy-of-selected-bedrock-samples-in-t
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    Dataset updated
    Sep 14, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    This data release contains geochemical data, thin section images, and modal mineralogy from bedrock samples collected in the western half of the Emporia 30’ x 60’ quadrangle, Virginia and North Carolina. The geochemical data comprise whole-rock major oxide and trace element abundances in 246 samples. Pairs of thin section images in plane-polarized light and cross-polarized light are included for 125 samples. Modal mineralogy was obtained by powder X-ray diffraction and the Rietveld method for 97 samples.

  11. Z

    Data from: Dataset: Impact Events for Structural Health Monitoring of a...

    • data.niaid.nih.gov
    • data-staging.niaid.nih.gov
    Updated Oct 15, 2022
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    Ioannis Katsidimas; Thanasis Kotzakolios; Sotiris Nikoletseas; Stefanos H. Panagiotou; Konstantinos Timpilis; Constantinos Tsakonas (2022). Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin Plate [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7199346
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    Dataset updated
    Oct 15, 2022
    Dataset provided by
    Department of Mechanical Engineering and Aeronautics, University of Patras, Greece
    Department of Computer Engineering and Informatics, University of Patras, Greece and Computer Technology Institute and Press ``Diophantus'', Greece
    Department of Computer Engineering and Informatics, University of Patras, Greece
    Authors
    Ioannis Katsidimas; Thanasis Kotzakolios; Sotiris Nikoletseas; Stefanos H. Panagiotou; Konstantinos Timpilis; Constantinos Tsakonas
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This repository contains a novel time-series dataset for impact detection and localization on a plastic thin-plate, towards Structural Health Monitoring applications, using ceramic piezoelectric transducers (PZTs) connected to an Internet of Things (IoT) device. The dataset was collected from an experimental procedure of low-velocity, low-energy impact events that includes at least 3 repetitions for each unique experiment, while the input measurements come from 4 PZT sensors placed at the corners of the plate. For each repetition and sensor, 5000 values are stored with 100 KHz sampling rate. The system is excited with a steel ball, and the height from which it is released varies from 10 cm to 20 cm.

    To the best of our knowledge, we are the first, to publish a public dataset that contains PZT sensors measurements concerning low-velocity, low-energy impact events in a thin plastic plate. In addition, we also contribute with our methodology on data collection using an SHM IoT system with resource constraints (based on Arduino NANO 33 MCU), as opposed to the majority of the literature that uses Oscilloscopes for data acquisition. This concept of an MCU-based system for data collection in SHM is especially important nowadays, due to the fast rise of extreme-edge and embedded machine learning practices solutions that enable a variety of real-time data-driven SHM applications. Finally, we wish to highlight that by using this specific Microcontroller Unit (MCU) and sensors, the proposed implementation aims for an overall low-cost data collection solution.

    The dataset has been published as a dataset paper in 20th ACM Conference on Embedded Networked Sensor Systems (SenSys 2022), in the following workshop: The Fifth International Workshop on Data: Acquisition To Analysis (DATA '22).

    The dataset is also available at https://github.com/Smart-Objects/Impact-Events-Dataset.

  12. r

    Prescription codelists_THIN UK.xlsx

    • research-repository.rmit.edu.au
    • researchdata.edu.au
    xlsx
    Updated May 31, 2023
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    Joanna Zhi Jie Ling (2023). Prescription codelists_THIN UK.xlsx [Dataset]. http://doi.org/10.25439/rmt.21398022.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    RMIT University
    Authors
    Joanna Zhi Jie Ling
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Prescription codelists (drug, BNF and ATC codes) for identifying antidiabetic, antihypertensive and lipid-lowering drugs from the THIN UK primary database used for the project:Therapeutic Inertia for Glycaemic and Cardiovascular Risk Factor Control in Patients with Type 2 Diabetes: A Real-world Electronic Medical Records Based Study

  13. h

    narrow-data

    • huggingface.co
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    Eric Michaud, narrow-data [Dataset]. https://huggingface.co/datasets/ericjm/narrow-data
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    Authors
    Eric Michaud
    Description

    Narrow AI: Experimental Model Repository

    This repository contains experimental model checkpoints and data from the paper "On the creation of narrow AI: hierarchy and nonlocality of neural network skills" by Eric Michaud, Asher Parker-Sartori, and Max Tegmark.

      Repository Contents
    

    This dataset provides the hard-to-reproduce LLM experimental artifacts that support the paper's key figures, particularly training curves and model performance data for scaling analysis and… See the full description on the dataset page: https://huggingface.co/datasets/ericjm/narrow-data.

  14. GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 -...

    • data.nasa.gov
    Updated Mar 31, 2025
    + more versions
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    nasa.gov (2025). GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033 - Dataset - NASA Open Data Portal [Dataset]. https://data.nasa.gov/dataset/glas-icesat-l2-global-thin-cloud-aerosol-optical-depths-data-hdf5-v033
    Explore at:
    Dataset updated
    Mar 31, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.

  15. b

    The relationship between body dissatisfaction and attentional bias to thin...

    • data.bris.ac.uk
    Updated Aug 16, 2023
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    (2023). The relationship between body dissatisfaction and attentional bias to thin bodies in Malaysian Chinese and White Australian women: A dot probe study. - Datasets - data.bris [Dataset]. https://data.bris.ac.uk/data/dataset/dn7ra6z7uats2asgp5k401te4
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    Dataset updated
    Aug 16, 2023
    Area covered
    Australia, Malaysia
    Description

    This study used a cross-sectional design to investigate the relationship between body dissatisfaction and attentional bias towards thin bodies. We recruited 150 Malaysian Chinese women in Malaysia and 150 White Australian women in Australia. However, for the Malaysian Chinese participants, we did not obtain explicit consent to share their data. This repository therefore contains real data for the 150 White Australian participants and synthetic data for the 150 Malaysian Chinese participants.

  16. s

    Super Thin Import Data & Buyers List in USA

    • seair.co.in
    Updated Apr 14, 2025
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    Seair Exim Solutions (2025). Super Thin Import Data & Buyers List in USA [Dataset]. https://www.seair.co.in/us-import/product-super-thin.aspx
    Explore at:
    .text/.csv/.xml/.xls/.binAvailable download formats
    Dataset updated
    Apr 14, 2025
    Dataset authored and provided by
    Seair Exim Solutions
    Area covered
    United States
    Description

    Get the latest USA Super Thin import data with importer names, shipment details, buyers list, product description, price, quantity, and major US ports.

  17. Materials Data on ThIn by Materials Project

    • osti.gov
    Updated May 2, 2020
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    LBNL Materials Project; Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States) (2020). Materials Data on ThIn by Materials Project [Dataset]. https://www.osti.gov/dataexplorer/biblio/dataset/1710072-materials-data-thin-materials-project
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    Dataset updated
    May 2, 2020
    Dataset provided by
    Office of Sciencehttp://www.er.doe.gov/
    LBNL Materials Project; Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
    Description

    ThIn is Tetraauricupride structured and crystallizes in the orthorhombic Pmmm space group. The structure is three-dimensional. Th is bonded to eight equivalent In atoms to form a mixture of distorted edge, face, and corner-sharing ThIn8 cuboctahedra. All Th–In bond lengths are 3.40 Å. In is bonded in a distorted body-centered cubic geometry to eight equivalent Th atoms.

  18. Mid Atlantic Thin Layer Deposition Data Index

    • noaa.hub.arcgis.com
    Updated Dec 6, 2017
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    NOAA GeoPlatform (2017). Mid Atlantic Thin Layer Deposition Data Index [Dataset]. https://noaa.hub.arcgis.com/maps/8aadc69773cc4cff87e48320e8f34114
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    Dataset updated
    Dec 6, 2017
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    Area covered
    Description

    Data Layers showing the footprints and locations of data defined as being useful for projects and decisions related to thin layer deposition in Mid-Atlantic marshes. Layers were identified by "A Needs Assessment Exploring Connections Between National Estuarine Research Reserves and Sentinel Site Data and Thin Layer Sediment Placement for Wetland Restoration in the Mid-Atlantic Region"

  19. d

    Data from: Phylogenetic relatedness determined between antibiotic resistance...

    • search.dataone.org
    • data.niaid.nih.gov
    • +2more
    Updated Mar 31, 2025
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    Marketa Sagova-Mareckova; Dana Ulanova; Petra Sanderova; Marek Omelka; Zdenek Kamenik; Jana Olsovska; Jan Kopecky (2025). Phylogenetic relatedness determined between antibiotic resistance and 16S rRNA genes in actinobacteria [Dataset]. http://doi.org/10.5061/dryad.td742
    Explore at:
    Dataset updated
    Mar 31, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Marketa Sagova-Mareckova; Dana Ulanova; Petra Sanderova; Marek Omelka; Zdenek Kamenik; Jana Olsovska; Jan Kopecky
    Time period covered
    Feb 20, 2016
    Description

    Background: Distribution and evolutionary history of resistance genes in environmental actinobacteria provide information on intensity of antibiosis and evolution of specific secondary metabolic pathways at a given site. To this day, actinobacteria producing biologically active compounds were isolated mostly from soil but only a limited range of soil environments were commonly sampled. Consequently, soil remains an unexplored environment in search for novel producers and related evolutionary questions. Results: Ninety actinobacteria strains isolated at contrasting soil sites were characterized phylogenetically by 16S rRNA gene, for presence of erm and ABC transporter resistance genes and antibiotic production. An analogous analysis was performed in silico with 246 and 31 strains from Integrated Microbial Genomes (JGI_IMG) database selected by the presence of ABC transporter genes and erm genes, respectively. In the isolates, distances of erm gene sequences were significantly correlated ...

  20. Z

    Database of New Phase Change Materials

    • data.niaid.nih.gov
    • portalinvestigacion.uniovi.es
    • +2more
    Updated Jul 11, 2024
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    Josef Resl; Yael Gutiérrez; Maria Losurdo (2024). Database of New Phase Change Materials [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_8010146
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    Dataset updated
    Jul 11, 2024
    Dataset provided by
    CNR-NANOTEC
    University of Oviedo
    Johannes Kepler University Linz
    Authors
    Josef Resl; Yael Gutiérrez; Maria Losurdo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Database of structural and optical properties of Gallium sulfide (GaS), Antimony sulfide (Sb2S3), Gallium Selenide (GaSe), Selenium (Se), and Molybdenum oxide (MoOx) thin film phase change materials. Contains Raman spectra and room temperature optical constants from spectroscopic ellipsometry for amorphous and polycrystalline phases. Also includes temperature dependent optical constants measured in-situ during thermal annealing to induce crystallization. Thin films fabricated by chemical vapor deposition, exfoliation, and solution processing methods. Provided by the PHEMTRONICS project (Deliverable 2.7).

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Close
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Mariam Molokhia; Paul McKeigue; Vasa Curcin; Azeem Majeed (2023). Statin prescriptions by year using THIN database 1990–2005. [Dataset]. http://doi.org/10.1371/journal.pone.0002522.t002
Organization logo

Statin prescriptions by year using THIN database 1990–2005.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 7, 2023
Dataset provided by
PLOShttp://plos.org/
Authors
Mariam Molokhia; Paul McKeigue; Vasa Curcin; Azeem Majeed
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Statin prescriptions by year using THIN database 1990–2005.

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