cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4118/flossmole.sourceforge.2008-06.1353
title: sfRawRealUrlData2008-Jun.txt.bz2

description: SF Project URLs  A .bz2 file of archive/secondary data available as a download from http://flossmole.googlecode.com/files/sfRawRealUrlData2008-Jun.txt.bz2. Data collected from SourceForge as raw HTML and parsed into data files by FLOSSmole. Metadata record available at http://flosspapers.org/1921.
DOI: 10.4118/flossmole.sourceforge.2008-06.1354
title: sfRawRanksData2008-Jun.txt.bz2

description: SF Project Ranks  A .bz2 file of archive/secondary data available as a download from http://flossmole.googlecode.com/files/sfRawRanksData2008-Jun.txt.bz2. Data collected from SourceForge as raw HTML and parsed into data files by FLOSSmole. Metadata record available at http://flosspapers.org/1922.
DOI: 10.34740/kaggle/dsv/6433051
title: WallStreetBets 2022
DOI: 10.57841/casdc.0002117
title: 位移幅值对690合金管/405不锈钢块切向微动磨损特性的影响
DOI: 10.3886/e115791v1-141309
title: Data and Code for: College Quality and Attendance Patterns: A Long-Run View

description: Abstract: We construct a time series of college attendance patterns for the United States and document a reversal: family background was a better predictor of college attendance before World War II, but academic ability was afterwards. We construct a model of college choice that explains this reversal. The model’s central mechanism is that an exogenous surge of college attendance leads better colleges to be oversubscribed, institute selective admissions, and raise their quality relative to their peers, as in Hoxby (2009). Rising quality at better colleges attracts high-ability students, while falling quality at the remaining colleges dissuades low-ability students, generating the reversal.
DOI: 10.26180/24103752.v1
title: 20210319_TEC_threats_IUCN_NESP_scheme.xlsx

description: Most comprehensive dataset on the threats to 85 Australian threatened ecological communities (TECs) listed under the EPBC Act until November 2020. This datasets uses two standardised threat classification schemes: IUCN Classification Scheme (Version 3.3) and Ward et al. (2021) scheme developed to classify threats to Australian threatened species. Threats were collated and synthesised from government documents (e.g. listing advices, conservation advices, recovery plans) within the Australian Government’s online repository Species Profile and Threats Database.
DOI: 10.5281/zenodo.7269245
title: Data and Code Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"

description: Code and Data Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"<br> =========================================================== This directory contains the data and scripts used to create the plots from our publication as well as the source<br> code modifications necessary to run this test case within the CESM and MPAS models. Generating Plots<br> --------------- The `netcdf` directory contains the nominal half-degree runs necessary to generate nearly all of the plots from the paper. The one plot which is not reproducible from these data is the volume-integrated Eddy Kinetic Energy in the Spectral Element model. Storing high-resolution 4D wind fields requires a prohibitive amount of space. These data can be provided by the corresponding author, O.K. Hughes (owhughes@umich.edu). However, because this is several hundred GB of data I would strongly recommend generating these high-resolution runs yourself on your local system if you need them. Using 288 Intel Skylake cores (that is, 8 nodes each with two 18C processors) ran on the order of an hour. <em>In order to generate the plots from the paper, you need only install NCL and then run</em> run.bash. Instructions for installing NCL<br> can be found in the `run.bash` script. Source Code Modifications<br> ---------------- <strong>CESM</strong><br> The `src` subdirectory contains the files `user_nl_cam` and `ic_baroclinic.F90`. Create a case using `--compset=FKESSLER` and `--run-unsupported` options when running `create_newcase`. If your case is located at `${CASE_DIR}`, then from within the directory containing this README, run `cp user_nl_cam ${CASE_DIR}/user_nl_cam`, and then run `cp ic_baroclinic.F90 ${CASE_DIR}/SourceMods/src.cam/`. Then build and run the model using the usual workflow. <strong>MPAS</strong> The MPAS code was run using a branch of the MPAS model provided by the model developers to the authors. While the source code modifications are provided in the `src` directory, I would strongly recommend contacting the corresponding author if you wish to run this test case in the MPAS codebase.
DOI: 10.5281/zenodo.7269246
title: Data and Code Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"

description: Code and Data Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"<br> =========================================================== This directory contains the data and scripts used to create the plots from our publication as well as the source<br> code modifications necessary to run this test case within the CESM and MPAS models. Generating Plots<br> --------------- The `netcdf` directory contains the nominal half-degree runs necessary to generate nearly all of the plots from the paper. The one plot which is not reproducible from these data is the volume-integrated Eddy Kinetic Energy in the Spectral Element model. Storing high-resolution 4D wind fields requires a prohibitive amount of space. These data can be provided by the corresponding author, O.K. Hughes (owhughes@umich.edu). However, because this is several hundred GB of data I would strongly recommend generating these high-resolution runs yourself on your local system if you need them. Using 288 Intel Skylake cores (that is, 8 nodes each with two 18C processors) ran on the order of an hour. <em>In order to generate the plots from the paper, you need only install NCL and then run</em> run.bash. Instructions for installing NCL<br> can be found in the `run.bash` script. Source Code Modifications<br> ---------------- <strong>CESM</strong><br> The `src` subdirectory contains the files `user_nl_cam` and `ic_baroclinic.F90`. Create a case using `--compset=FKESSLER` and `--run-unsupported` options when running `create_newcase`. If your case is located at `${CASE_DIR}`, then from within the directory containing this README, run `cp user_nl_cam ${CASE_DIR}/user_nl_cam`, and then run `cp ic_baroclinic.F90 ${CASE_DIR}/SourceMods/src.cam/`. Then build and run the model using the usual workflow. <strong>MPAS</strong> The MPAS code was run using a branch of the MPAS model provided by the model developers to the authors. While the source code modifications are provided in the `src` directory, I would strongly recommend contacting the corresponding author if you wish to run this test case in the MPAS codebase.
DOI: 10.5281/zenodo.7677229
title: Data and Code Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"

description: Code and Data Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"<br> =========================================================== This directory contains the data and scripts used to create the plots from our publication as well as the source<br> code modifications necessary to run this test case within the CESM and MPAS models. Generating Plots<br> --------------- The `netcdf` directory contains the nominal half-degree runs necessary to generate nearly all of the plots from the paper. The one plot which is not reproducible from these data is the volume-integrated Eddy Kinetic Energy in the Spectral Element model. Storing high-resolution 4D wind fields requires a prohibitive amount of space. These data can be provided by the corresponding author, O.K. Hughes (owhughes@umich.edu). However, because this is several hundred GB of data I would strongly recommend generating these high-resolution runs yourself on your local system if you need them. Using 288 Intel Skylake cores (that is, 8 nodes each with two 18C processors) ran on the order of an hour. <em>In order to generate the plots from the paper, you need only install NCL and then run</em> run.bash. Instructions for installing NCL<br> can be found in the `run.bash` script. Source Code Modifications<br> ---------------- <strong>CESM</strong><br> The `src` subdirectory contains the files `user_nl_cam` and `ic_baroclinic.F90`. Create a case using `--compset=FKESSLER` and `--run-unsupported` options when running `create_newcase`. If your case is located at `${CASE_DIR}`, then from within the directory containing this README, run `cp user_nl_cam ${CASE_DIR}/user_nl_cam`, and then run `cp ic_baroclinic.F90 ${CASE_DIR}/SourceMods/src.cam/`. Then build and run the model using the usual workflow. <strong>MPAS</strong> The MPAS code was run using a branch of the MPAS model provided by the model developers to the authors. While the source code modifications are provided in the `src` directory, I would strongly recommend contacting the corresponding author if you wish to run this test case in the MPAS codebase.
DOI: 10.5281/zenodo.8327365
title: Data and Code Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"

description: Code and Data Supplement for "A Mountain-Induced Moist Baroclinic Wave Test Case for the Dynamical Cores of Atmospheric General Circulation Models"<br> =========================================================== This directory contains the data and scripts used to create the plots from our publication as well as the source<br> code modifications necessary to run this test case within the CESM and MPAS models. Generating Plots<br> --------------- The `netcdf` directory contains the nominal half-degree runs necessary to generate nearly all of the plots from the paper. The one plot which is not reproducible from these data is the volume-integrated Eddy Kinetic Energy in the Spectral Element model. Storing high-resolution 4D wind fields requires a prohibitive amount of space. These data can be provided by the corresponding author, O.K. Hughes (owhughes@umich.edu). However, because this is several hundred GB of data I would strongly recommend generating these high-resolution runs yourself on your local system if you need them. Using 288 Intel Skylake cores (that is, 8 nodes each with two 18C processors) ran on the order of an hour. <em>In order to generate the plots from the paper, you need only install NCL and then run</em> run.bash. Instructions for installing NCL<br> can be found in the `run.bash` script. Source Code Modifications<br> ---------------- <strong>CESM</strong><br> The `src` subdirectory contains the files `user_nl_cam` and `ic_baroclinic.F90`. Create a case using `--compset=FKESSLER` and `--run-unsupported` options when running `create_newcase`. If your case is located at `${CASE_DIR}`, then from within the directory containing this README, run `cp user_nl_cam ${CASE_DIR}/user_nl_cam`, and then run `cp ic_baroclinic.F90 ${CASE_DIR}/SourceMods/src.cam/`. Then build and run the model using the usual workflow. <strong>MPAS</strong> The MPAS code was run using a branch of the MPAS model provided by the model developers to the authors. While the source code modifications are provided in the `src` directory, I would strongly recommend contacting the corresponding author if you wish to run this test case in the MPAS codebase.
DOI: 10.25952/vxar-yv25
title: Training individuals in how to help a distressed person

description: This is a dataset for a pilot study to test whether it is possible to training individuals online in how to help distressed individuals.
description: This is a dataset for a pilot study to test whether it is possible to training individuals online in how to help distressed individuals.
DOI: 10.57841/casdc.0002118
title: 定、变载弯曲疲劳钢丝绳失效机理对比研究
DOI: 10.14279/depositonce-18737
title: Mosaik-2 Simulation Experiment

description: This data set was used to conduct a simulation experiment which tests the integration between MATSim and PALM.
DOI: 10.57841/casdc.0002119
title: 燃气热水器用低氮燃烧器相关检验、检测报告及实验数据
DOI: 10.57841/casdc.0002120
title: 磁控溅射银层在载流润滑下的电摩擦学性能研究
DOI: 10.5281/zenodo.7732377
title: dataset for paper Toxicity Test of Propolis Product as Protective and Therapeutic Substance for Embryo of Chicken

description: This data set is free to download
DOI: 10.5281/zenodo.7732378
title: dataset for paper Toxicity Test of Propolis Product as Protective and Therapeutic Substance for Embryo of Chicken

description: This data set is free to download
DOI: 10.5281/zenodo.7796694
title: dataset for paper Toxicity Test of Propolis Product as Protective and Therapeutic Substance for Embryo of Chicken

description: This data set is free to download
DOI: 10.5281/zenodo.8327605
title: dataset for paper Toxicity Test of Propolis Product as Protective and Therapeutic Substance for Embryo of Chicken

description: This data set is free to download
DOI: 10.6084/m9.figshare.24104070
title: data.doc

description: The data for the article.
DOI: 10.6084/m9.figshare.24104070.v1
title: data.doc

description: The data for the article.
DOI: 10.5281/zenodo.8325728
title: First results of online compression of HEP data using Baler

description: Within the framework of the HiDA Trilateral Data Science Exchange Program, this internship project unveils preliminary findings on online compression using Baler. It involved the examination of various datasets of different sizes from the High Energy Physics (HEP) domain to evaluate compression performance. All datasets used are subsets of the jet data recorded by the CMS experiment at the LHC in 2012, released as open data under the Creative Commons CC0 waiver (see references). The data is modified (flattened, truncated, formatted, etc.) and packaged in a way that makes it easy for others to reproduce the results. The provided files in this page include comprehensive instructions for replicating the project's results, as well as datasets and outcomes. Below, you'll find a brief overview of the project's folder structure, categorized by the dataset utilized (small dataset/example CMS data/larger CMS data), the online/offline compression method, and resource utilization, particularly regarding GPU usage. Presentations summarizing this project's results can be found here: https://zenodo.org/record/8326707. <strong>Project's folders:</strong> <strong>Reproduction Instructions</strong>: This folder houses all files that offer detailed guidelines for replicating the project's presented results. These files serve as a reference for accessing relevant materials. <strong>GPU with Example CMS Data.zip</strong>: This directory contains all files related to offline compression of the approximately 100MB example CMS dataset provided by Baler. GPU resources were employed in the model training process. <strong>GPU with Larger CMS Data (1).zip</strong>: In this section, you'll find files associated with the compression of a larger CMS dataset, approximately 1.4GB in size. It includes results of offline compression and a split of the dataset into a 50/50 ratio for training and testing, with results provided for various epochs. <strong>GPU with Larger CMS Data (2)</strong>: This folder holds the larger dataset, divided into two halves, with the first half's array values in one file and the second half's in another. <strong>Offline/Online on Small Dataset</strong>: Here, you'll find files related to both offline and online compression of a small dataset, roughly 100KB in size, extracted from the example CMS dataset provided by Baler. <strong>Modifications of Small Dataset</strong>: This section comprises variations of the small dataset, including both normalized and un-normalized datasets. <strong>Materials</strong>: This folder includes fundamental papers and summaries to enhance your understanding of the project. <strong>HiDA</strong>: Within this directory, you'll find a printed webpage from the HiDA program.
description: {"references": ["CMS collaboration. JetHT primary dataset in AOD format from Run of 2012. Tech. rep. 2017. doi: DOI:10.7483/OPENDATA.CMS.KL8H.HFVH. url: http://opendata.cern.ch/record/6010."]}
DOI: 10.5281/zenodo.8325727
title: First results of online compression of HEP data using Baler

description: Within the framework of the HiDA Trilateral Data Science Exchange Program, this internship project unveils preliminary findings on online compression using Baler. It involved the examination of various datasets of different sizes from the High Energy Physics (HEP) domain to evaluate compression performance. All datasets used are subsets of the jet data recorded by the CMS experiment at the LHC in 2012, released as open data under the Creative Commons CC0 waiver (see references). The data is modified (flattened, truncated, formatted, etc.) and packaged in a way that makes it easy for others to reproduce the results. The provided files in this page include comprehensive instructions for replicating the project's results, as well as datasets and outcomes. Below, you'll find a brief overview of the project's folder structure, categorized by the dataset utilized (small dataset/example CMS data/larger CMS data), the online/offline compression method, and resource utilization, particularly regarding GPU usage. Presentations summarizing this project's results can be found here: https://zenodo.org/record/8326707. <strong>Project's folders:</strong> <strong>Reproduction Instructions</strong>: This folder houses all files that offer detailed guidelines for replicating the project's presented results. These files serve as a reference for accessing relevant materials. <strong>GPU with Example CMS Data.zip</strong>: This directory contains all files related to offline compression of the approximately 100MB example CMS dataset provided by Baler. GPU resources were employed in the model training process. <strong>GPU with Larger CMS Data (1).zip</strong>: In this section, you'll find files associated with the compression of a larger CMS dataset, approximately 1.4GB in size. It includes results of offline compression and a split of the dataset into a 50/50 ratio for training and testing, with results provided for various epochs. <strong>GPU with Larger CMS Data (2)</strong>: This folder holds the larger dataset, divided into two halves, with the first half's array values in one file and the second half's in another. <strong>Offline/Online on Small Dataset</strong>: Here, you'll find files related to both offline and online compression of a small dataset, roughly 100KB in size, extracted from the example CMS dataset provided by Baler. <strong>Modifications of Small Dataset</strong>: This section comprises variations of the small dataset, including both normalized and un-normalized datasets. <strong>Materials</strong>: This folder includes fundamental papers and summaries to enhance your understanding of the project. <strong>HiDA</strong>: Within this directory, you'll find a printed webpage from the HiDA program.
description: {"references": ["CMS collaboration. JetHT primary dataset in AOD format from Run of 2012. Tech. rep. 2017. doi: DOI:10.7483/OPENDATA.CMS.KL8H.HFVH. url: http://opendata.cern.ch/record/6010."]}
DOI: 10.57841/casdc.0002121
title: 离心惯性力效应对超临界二氧化碳干气密封流场与密封特性影响分析
DOI: 10.57841/casdc.0002122
title: 聚合物PLL-g-PEG构象变化对宏观摩擦学性能的影响
DOI: 10.57841/casdc.0002123
title: 高频循环载荷下球面滑动副摩擦学特征研究
DOI: 10.5439/1998231
title: sondewndcalc (c1)

description: sondewndcalc
DOI: 10.5439/1998232
title: aerisummary (a2)

description: The atmospheric emitted radiance interferometer (AERI) is a ground-based instrument that measures the downwelling infrared radiance from the Earth’s atmosphere. The observations have broad spectral content and sufficient spectral resolution to discriminate among gaseous emitters (e.g., carbon dioxide and water vapor) and suspended matter (e.g., aerosols, water droplets, and ice crystals). These upward-looking surface observations can be used to obtain vertical profiles of tropospheric temperature and water vapor, as well as measurements of trace gases (e.g., ozone, carbon monoxide, and methane) and downwelling infrared spectral signatures of clouds and aerosols.
DOI: 10.5439/1998233
title: aerich1 (a2)

description: The atmospheric emitted radiance interferometer (AERI) is a ground-based instrument that measures the downwelling infrared radiance from the Earth’s atmosphere. The observations have broad spectral content and sufficient spectral resolution to discriminate among gaseous emitters (e.g., carbon dioxide and water vapor) and suspended matter (e.g., aerosols, water droplets, and ice crystals). These upward-looking surface observations can be used to obtain vertical profiles of tropospheric temperature and water vapor, as well as measurements of trace gases (e.g., ozone, carbon monoxide, and methane) and downwelling infrared spectral signatures of clouds and aerosols.
DOI: 10.5439/1998234
title: aerich2 (a2)

description: The atmospheric emitted radiance interferometer (AERI) is a ground-based instrument that measures the downwelling infrared radiance from the Earth’s atmosphere. The observations have broad spectral content and sufficient spectral resolution to discriminate among gaseous emitters (e.g., carbon dioxide and water vapor) and suspended matter (e.g., aerosols, water droplets, and ice crystals). These upward-looking surface observations can be used to obtain vertical profiles of tropospheric temperature and water vapor, as well as measurements of trace gases (e.g., ozone, carbon monoxide, and methane) and downwelling infrared spectral signatures of clouds and aerosols.
DOI: 10.5439/1998235
title: mplcbh1scott (c1)

description: mplcbh1scott
DOI: 10.5439/1998236
title: csphotaotfiltqa (a1)

description: The Cimel sunphotometer (CSPHOT) is a multi-channel, automatic sun-and-sky scanning radiometer that measures the direct solar irradiance and sky radiance at the Earth’s surface. It takes measurements at predetermined discrete wavelengths in the visible and near-infrared parts of the spectrum to determine atmospheric transmission and scattering properties. The CSPHOT only operates during daylight (sun above horizon).
DOI: 10.5439/1998237
title: csphotaotfilt (a1)

description: The Cimel sunphotometer (CSPHOT) is a multi-channel, automatic sun-and-sky scanning radiometer that measures the direct solar irradiance and sky radiance at the Earth’s surface. It takes measurements at predetermined discrete wavelengths in the visible and near-infrared parts of the spectrum to determine atmospheric transmission and scattering properties. The CSPHOT only operates during daylight (sun above horizon).
DOI: 10.5439/1998238
title: lblch1 (c1)

description: lblch1
DOI: 10.5439/1998240
title: sondewrpr (a0)

description: The balloon-borne sounding system (SONDE) provides in situ measurements (vertical profiles) of both the thermodynamic state of the atmosphere, and the wind speed and direction. Sonde operations can provide important constraints for model simulations if used during field campaigns where multiple stations are operated around a central location with baseline measurements, such as a mobile facility. When deployed, sondes are launched at scheduled intervals.