cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/yis2qy/cmlmmy
title: IG_Geo_DK.tab

description: :unav
DOI: 10.21227/w4xy-9r38
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.5281/zenodo.3956408
title: Complementary data to "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force"

description: Missing data from "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force" Hoffmann, Christian; Centi, Alessia; Menichetti, Roberto; Bereau, Tristan (2020): Molecular dynamics trajectories for 630 drug-membrane potentials of mean force. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.4641551.v1 Includes: 'bsResult.xvg' of DIM_P2-P3 in DLPC
description: {"references": ["Hoffmann, C., Centi, A., Menichetti, R. et al. Molecular dynamics trajectories for 630 coarse-grained drug-membrane permeations. Sci Data 7, 51 (2020). https://doi.org/10.1038/s41597-020-0391-0"]}
DOI: 10.5281/zenodo.3956407
title: Complementary data to "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force"

description: Missing data from "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force" Hoffmann, Christian; Centi, Alessia; Menichetti, Roberto; Bereau, Tristan (2020): Molecular dynamics trajectories for 630 drug-membrane potentials of mean force. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.4641551.v1 Includes: 'bsResult.xvg' of DIM_P2-P3 in DLPC
description: {"references": ["Hoffmann, C., Centi, A., Menichetti, R. et al. Molecular dynamics trajectories for 630 coarse-grained drug-membrane permeations. Sci Data 7, 51 (2020). https://doi.org/10.1038/s41597-020-0391-0"]}
DOI: 10.21227/cwv3-c456
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.5281/zenodo.3952846
title: Phase II: The Future of LNG for the US and Gulf Coast Economies

description: The continued growth of Liquefied Natural Gas (LNG) production and long-distance trade has traditionally been taken as a given by global energy analysts, who have premised their positive estimates on gas being both relatively scarce and demand for it virtually unquenchable. Unfortunately, current conditions in the global energy market suggest that what many have predicted as a near perpetual increase in the volume of traded LNG is in fact a bubble that is now in the process of bursting. This report represents the efforts by the University of New Orleans Transportation Institute (UNOTI) beginning in 2014 to assist the Port of New Orleans (PONO) in evaluating the feasibility and best practices of equipping the PONO for potential storage and shore-side infrastructure for fueling vessels powered by LNG, as well as research into the feasibility of the widespread use of LNG as marine fuel, considering the new United Nation’s International Maritime Organization’s (IMO) MARPOL Annex VI maritime emissions regulations set to take effect in 2020. Additionally, this report examines both the short and long-term factors behind this new thinking about LNG, explore what it implies for the several multi-billion-dollar export projects being built in Louisiana, and the feasibility of LNG as a US export commodity and industrial feedstock to the petrochemical industry. This report concludes by suggesting that development policy aiming to assist LNG export projects are likely misplaced, and that a primary focus on value-added petrochemical manufacturing, with a secondary value as potential for a marine fuel, is a more robust path for the region’s policymakers to take.
DOI: 10.5281/zenodo.3952845
title: Phase II: The Future of LNG for the US and Gulf Coast Economies

description: The continued growth of Liquefied Natural Gas (LNG) production and long-distance trade has traditionally been taken as a given by global energy analysts, who have premised their positive estimates on gas being both relatively scarce and demand for it virtually unquenchable. Unfortunately, current conditions in the global energy market suggest that what many have predicted as a near perpetual increase in the volume of traded LNG is in fact a bubble that is now in the process of bursting. This report represents the efforts by the University of New Orleans Transportation Institute (UNOTI) beginning in 2014 to assist the Port of New Orleans (PONO) in evaluating the feasibility and best practices of equipping the PONO for potential storage and shore-side infrastructure for fueling vessels powered by LNG, as well as research into the feasibility of the widespread use of LNG as marine fuel, considering the new United Nation’s International Maritime Organization’s (IMO) MARPOL Annex VI maritime emissions regulations set to take effect in 2020. Additionally, this report examines both the short and long-term factors behind this new thinking about LNG, explore what it implies for the several multi-billion-dollar export projects being built in Louisiana, and the feasibility of LNG as a US export commodity and industrial feedstock to the petrochemical industry. This report concludes by suggesting that development policy aiming to assist LNG export projects are likely misplaced, and that a primary focus on value-added petrochemical manufacturing, with a secondary value as potential for a marine fuel, is a more robust path for the region’s policymakers to take.
DOI: 10.18112/openneuro.ds001849.v1.0.1
title: RS_TMSEEG_Data
DOI: 10.21227/q4vd-qg73
title: DNN-GP Training Dataset

description: The dataset contains information regarding normalized throughput achieved under five link configuration parameters and a channel condition measured by SNR. In the dataset, there are seven columns: SNR value, MIMO, channel bandwidth, MCS, guard interval, frame aggregation and normalized throughput. "DNNdatagen.dat" is the dataset for training machine learning model.
DOI: 10.21227/7zqy-0a08
title: DNN-GP Training Dataset

description: The dataset contains information regarding normalized throughput achieved under five link configuration parameters and a channel condition measured by SNR. In the dataset, there are seven columns: SNR value, MIMO, channel bandwidth, MCS, guard interval, frame aggregation and normalized throughput. "DNNdatagen.dat" is the dataset for training machine learning model.
DOI: 10.18112/openneuro.ds001849.v1.0.2
title: RS_TMSEEG_Data
DOI: 10.5281/zenodo.3345831
title: ReimagineReview data

description: An export of data about innovative peer review experiments and platforms hosted on reimaginereview.asapbio.org. Note that test listings created by the team have been removed.
description: This work was supported by a grant from CZI.
DOI: 10.5281/zenodo.3746398
title: ReimagineReview data

description: An export of data about innovative peer review experiments and platforms hosted on reimaginereview.asapbio.org. Note that test listings created by the team have been removed.
description: This work was supported by a grant from CZI.
DOI: 10.5281/zenodo.3956416
title: Dataset for the manuscript of the "Experimental investigations on water condensation in the nanopores of shales"

description: Experimental data of the study
DOI: 10.5281/zenodo.3956415
title: Dataset for the manuscript of the "Experimental investigations on water condensation in the nanopores of shales"

description: Experimental data of the study
DOI: 10.5281/zenodo.3955714
title: MONET cost, land cover and CO2 storage capacity data.

description: This dataset contains cost, land cover and CO<sub>2 </sub>storage capacity data used in the MONET (Modelling and Optimisation of Negative Emissions Technologies) framework. For full MONET model description and dataset see Fajardy (2019) available online at https://doi.org/10.25560/80691.
DOI: 10.5281/zenodo.3955713
title: MONET cost, land cover and CO2 storage capacity data.

description: This dataset contains cost, land cover and CO<sub>2 </sub>storage capacity data used in the MONET (Modelling and Optimisation of Negative Emissions Technologies) framework. For full MONET model description and dataset see Fajardy (2019) available online at https://doi.org/10.25560/80691.
DOI: 10.21227/1rmk-2p35
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 54 keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.5281/zenodo.3956461
title: Synthetic earthquake catalogs generated for "Dual seismic migration velocities in seismic swarms"

description: Synthetic earthquake catalog for 40 simulations presented in "Dual seismic migration velocities in seismic swarms" by P. Dublanchet and L. De Barros, submitted to Geophysical Research Letters. Each file corresponds to one simulation described in the original paper. The three columns of each file are: -time of earthquake (in s) -location of earthquake (in m) -size of earthquake (in m)
DOI: 10.5281/zenodo.3956460
title: Synthetic earthquake catalogs generated for "Dual seismic migration velocities in seismic swarms"

description: Synthetic earthquake catalog for 40 simulations presented in "Dual seismic migration velocities in seismic swarms" by P. Dublanchet and L. De Barros, submitted to Geophysical Research Letters. Each file corresponds to one simulation described in the original paper. The three columns of each file are: -time of earthquake (in s) -location of earthquake (in m) -size of earthquake (in m)
DOI: 10.21227/v43f-gg22
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 54 keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.21227/44b3-ct92
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 54 keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.21227/mqbw-yc27
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page). Below is the quick overview of this dataset.| Number of tweets : 148,848 tweets
DOI: 10.21227/n6wq-z067
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.5281/zenodo.3956451
title: SoSEN-KG: Knowledge Graph Dump v0 for SoSEn: Software Search Engine.

description: SoSEn is a semantic search engine for scientific software. We index scientific software in a knowledge graph, which is used for search and understanding of the software. The graph `graph.ttl` contains information about the software, and `keywords.ttl` contains keyword information about the software. `graph.ttl` can be used alone, or it can be combined with `keywords.ttl` to facilitate tf-idf based keyword search.
description: Work performed under REU Site program supported by NSF grant #1659886
DOI: 10.5281/zenodo.3956450
title: SoSEN-KG: Knowledge Graph Dump v0 for SoSEn: Software Search Engine.

description: SoSEn is a semantic search engine for scientific software. We index scientific software in a knowledge graph, which is used for search and understanding of the software. The graph `graph.ttl` contains information about the software, and `keywords.ttl` contains keyword information about the software. `graph.ttl` can be used alone, or it can be combined with `keywords.ttl` to facilitate tf-idf based keyword search.
description: Work performed under REU Site program supported by NSF grant #1659886
DOI: 10.21227/r4pq-f945
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page). Below is the quick overview of this dataset.| Number of tweets : 148,848 tweets
DOI: 10.21227/vgv8-yn04
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.— Number of tweets : 329,834,758 tweets
DOI: 10.21227/7jjw-jf08
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page). Below is the quick overview of this dataset.— Number of tweets : 148,848 tweets
DOI: 10.17876/rave/dr.5/007
title: RAVE DR5 crossmatch Tycho2

description: Crossmatch RAVE and Tycho2
DOI: 10.17876/rave/dr.5/008
title: Crossmatch RAVE DR5 and TGAS

description: Crossmatch RAVE DR5 and TGAS
DOI: 10.25387/g3.12581324.v1
title: Supplemental Material for Kim et al., 2020

description: <b>Supplementary Figures S1 to S10 and Tables S1 to S7 for </b><b>Genome resequencing, improvement of variant calling, and population genomic analyses provide insights into the seedlessness in the genus <i>Vitis</i></b>
DOI: 10.25387/g3.12581324
title: Supplemental Material for Kim et al., 2020

description: <b>Supplementary Figures S1 to S10 and Tables S1 to S7 for </b><b>Genome resequencing, improvement of variant calling, and population genomic analyses provide insights into the seedlessness in the genus <i>Vitis</i></b>
DOI: 10.5281/zenodo.3956096
title: Dataset for Narrowing the parameter space of collapse models with ultracold layered force sensors

description: PSD - Original power spectral densities at different temperatures (in mK). For accounting the spectral leakage due to the FFT resolution, one has to remove the central 6 points. The columns are: frequency (Hz), value of PSD (Phi_0^2/Hz), PSD error (same units) Final data - Excel reporting the results of the PSD fits and that of the linear fit of B for the high temperatures. Final upper bound for the value of S_{F0}
DOI: 10.21227/zkpx-8708
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 54 different keywords that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Below is the quick overview of this dataset.— Number of tweets : 148,848 tweets
DOI: 10.17632/tdngvdyx35.7
title: Data of role of Sodium tetraborate in the Modulation of Cardiac Hypertrophic

description: Using, a hypertrophy model was established. Sodium tetraborate is a cardioprotective and / or competitive agent that modulates genetic reprogramming in neonatal cardiomyocytes treated with para isoproterenol as a hypertrophic stimulus.
DOI: 10.23708/h0vxh0
title: Gold Standard du projet MeDo

description: Cet ensemble de données comporte les documents utilisés pour l’apprentissage des modules NER (Named Entity Recognition) du projet MeDo (http://webmedo.msem.univ-montp2.fr/?page_id=12). Les documents originaux ont été requêtés sur le web, convertis au format texte et nettoyés. Les fichiers ont été anonymisés en remplaçant les caractères ne correspondant pas aux annotations par des X. Les fichiers .txt correspondent aux fichiers anonymisés (encodage UTF-8). L’annotation a été réalisée avec le logiciel Brat (http://brat.nlplab.org/index.html). Les fichiers .ann correspondent aux résultats de l’annotation manuelle sous Brat. Le guide d'annotation est aussi disponible au téléchargement (https://doi.org/10.23708/DAAKF1). Les mots clés des requêtes, ainsi que les liens URL des documents originaux sont détaillés dans le fichier info.JSON joint à ce dépôt. This dataset contains the documents used to train the NER (Named Entity Recognition) modules of the MeDo project (http://webmedo.msem.univ-montp2.fr/?page_id=228=en). The original documents have been scraped from the web, converted into text format and cleaned. The files were anonymized by replacing all characters not corresponding to the annotations by « x ». The .txt files correspond to the anonymized files (encoded in UTF-8). The annotation was carried out under Brat (http://brat.nlplab.org/index.html). The .ann files correspond to the Brat outputs of the manual annotation. The annotation guide is also available (https://doi.org/10.23708/DAAKF1). The keywords used for the queries and the URL links to the original documents are detailed in the accompanying info.JSON file.
DOI: 10.5281/zenodo.3956497
title: Data from "Reversible Control of Protein Corona Formation on Gold Nanoparticles Using Host–Guest Interactions"

description: This file contains raw data for the manuscript:<br> "Reversible Control of Protein Corona Formation on Gold Nanoparticles Using Host–Guest Interactions"<br> <em>ACS Nano</em> 2020, 14, 5, 5382–5391, DOI: 10.1021/acsnano.9b08752 The data is transmission electron microscopy (TEM) images of of gold nanoparticles.
DOI: 10.5281/zenodo.3956496
title: Data from "Reversible Control of Protein Corona Formation on Gold Nanoparticles Using Host–Guest Interactions"

description: This file contains raw data for the manuscript:<br> "Reversible Control of Protein Corona Formation on Gold Nanoparticles Using Host–Guest Interactions"<br> <em>ACS Nano</em> 2020, 14, 5, 5382–5391, DOI: 10.1021/acsnano.9b08752 The data is transmission electron microscopy (TEM) images of of gold nanoparticles.
DOI: 10.5281/zenodo.3956533
title: Murphy_Hydrate is non-wetting phase data

description: Experimental dataset for relative permeability measurements in the presence of methane hydrate.
DOI: 10.5281/zenodo.3956532
title: Murphy_Hydrate is non-wetting phase data

description: Experimental dataset for relative permeability measurements in the presence of methane hydrate.
DOI: 10.5519/qd.e6dda87z
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (255 records)
DOI: 10.5519/qd.ll607g38
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (244 records)
DOI: 10.5519/qd.919c2g5c
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (620 records)
DOI: 10.5519/qd.h92nvg25
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1779 records)
DOI: 10.5519/qd.4b1fi94l
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1235 records)
DOI: 10.5519/qd.oc1tebto
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (495 records)
DOI: 10.17632/wp5mnc3gbc.1
title: Huang, YH et al., 2020-01

description: Source data; Huang, YH et al, 2020; Structure-Based Mechanisms of a Molecular RNA Polymerase/Chaperone Machine Required for Ribosome Biosynthesis