cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4588902
title: A novel gene signature associated with poor response to chemoradiotherapy in patients with locally advanced cervical cancer

description: Supplementary table for the article "A novel gene signature associated with poor response to chemoradiotherapy in patients with locally advanced cervical cancer"
DOI: 10.5281/zenodo.4588901
title: A novel gene signature associated with poor response to chemoradiotherapy in patients with locally advanced cervical cancer

description: Supplementary table for the article "A novel gene signature associated with poor response to chemoradiotherapy in patients with locally advanced cervical cancer"
DOI: 10.6084/m9.figshare.14182433
title: mortardata.csv

description: The experiment that gave rise to the data set of this work was performed by Canova et al (2009). Themortars weight in specimens was observed over time, considering 10 levels for the treatment variable(Am1:0%, Am2:6%, Am3:8%, Am4:10%, Am5:12%, As1:0%, As2:6%, As3:8%, As4:10%, As5:12%), thisbeing the combination between two types of mortar and five concentrations of a rubber powder content,where the terms Am and As represent two types of mortar, matured mortar (Am) and kiln-dried mortar (As)respectively, in which the first type was produced containing lime and fine sand washed from the river, whichafter receiving the addition of cement, became a compound mortar. The second type was produced containinglime and sand that passed through the maturation process, was kiln dried and received the addition of cementaddition.<br><br>Canova, J.A., de Angelis N. G., Bergamasco, R. (2009). Mortar with unserviceable tire residues. Journal ofUrban and Environmental Engineering, JSTOR 3:63-72.
DOI: 10.6084/m9.figshare.14182433.v1
title: mortardata.csv

description: The experiment that gave rise to the data set of this work was performed by Canova et al (2009). Themortars weight in specimens was observed over time, considering 10 levels for the treatment variable(Am1:0%, Am2:6%, Am3:8%, Am4:10%, Am5:12%, As1:0%, As2:6%, As3:8%, As4:10%, As5:12%), thisbeing the combination between two types of mortar and five concentrations of a rubber powder content,where the terms Am and As represent two types of mortar, matured mortar (Am) and kiln-dried mortar (As)respectively, in which the first type was produced containing lime and fine sand washed from the river, whichafter receiving the addition of cement, became a compound mortar. The second type was produced containinglime and sand that passed through the maturation process, was kiln dried and received the addition of cementaddition.<br><br>Canova, J.A., de Angelis N. G., Bergamasco, R. (2009). Mortar with unserviceable tire residues. Journal ofUrban and Environmental Engineering, JSTOR 3:63-72.
DOI: 10.5281/zenodo.4587630
title: Supplementary dataset: Phytohormones selectively affect plant parasitic nematodes associated with Arabidopsis roots

description: Nematode, bacterial and fungal amplicon sequence data of Arabidopsis roots. qPCR data to quantify <em>Meloidogyne hapla</em> DNA.
DOI: 10.5281/zenodo.4587629
title: Supplementary dataset: Phytohormones selectively affect plant parasitic nematodes associated with Arabidopsis roots

description: Nematode, bacterial and fungal amplicon sequence data of Arabidopsis roots. qPCR data to quantify <em>Meloidogyne hapla</em> DNA.
DOI: 10.5281/zenodo.4587235
title: Data related to unpublished manuscript by Marushchak et al., titled Thawing yedoma permafrost as a neglected nitrous oxide source

description: Data on nitrous oxide (N<sub>2</sub>O) fluxes with related process, soil and microbial data from two thawing yedoma exposures in Northeast Siberia.
DOI: 10.5281/zenodo.4574850
title: Calibration solutions, light curve and dedispersion data for Murchison Widefield Array rapid-response observations of the short GRB 180805A

description: This repository includes the final datasets derived from Murchison Widefield Array (MWA) rapid-response observations of gamma-ray burst (GRB) 180805A used for analysis in the paper "Murchison Widefield Array rapid-response observations of the short GRB 1808085A". All raw MWA data for this observation can be obtained from the Murchison Widefield Array All-sky Virtual Observatory (https://asvo.mwatelescope.org/), and include observation identification (ObsID) numbers 1217495184, 1217495304, 1217495424, 1217495544, 1217495664, 1217495784, 1217495904, 1217496024, 1217496144, 1217496264, 1217496384, 1217496504, 1217496624, 1217496744, 1217496864 under project code D0009. These 15 observations are referred to as snapshots in the following. The files attached files to this repository are described below. Calibration solutions (1217495544_infield_solutions.bin): The calibration solutions applied to all ObsIDs, which were derived from an infield calibration of ObsID 1217495544 using the GLEAM model (Hurley-Walker et al. 2017). Light curves (GRB180805A_2m_lc.csv, GRB180805A_30s_lc.csv, GRB180805A_5s_lc.csv, GRB180805A_05s_lc.csv): All observations were imaged on 2 minutes, 30 seconds, 5 seconds, and 0.5 seconds timescales. Priorized fitting was performed at the position of the GRB to obtain monitoring light curves. These csv files list the resulting flux density as a function of time for these four different timescales. Dynamic spectrum: This is the dynamic spectrum created at the pixel position of GRB 180805A by splitting the full 30-minute MWA integration (15 snapshot observations) into the 0.5-second coarse channel (1.28 MHz frequency resolution) images. The first 4s and last 5.5s of each individual snapshot observation are flagged due to instrumental reasons. The axes are Frequency (MHz) vs Time post-GRB (seconds) with the greyscale showing Jy/beam. This dynamic spectrum was used to create a dedispersed time series, for which we search from prompt, dispersed signals. Dedispersed time series: The mean flux density (Jy/beam) for the path swept across the dynamic spectrum (see above) for every dispersion measure (DM) trial ranging from 100-3000 pc cm<sup>-3 </sup>at 1.0 pc cm<sup>-3 </sup>intervals for all time steps at a resolution of 0.1s following the GRB detection. This dedispersed time series was searched for evidence of prompt signals but there were no significant signals (above signal-to-noise ratio of 6) for DM &gt; 200 pc cm<sup>-3</sup>, which is the lowest DM that we expect short GRBs to be detected (corresponding to a minimum redshift of z~0.1).
description: {"references": ["Hurley-Walker, N., et al., 2017, MNRAS, 464, 1146"]}
DOI: 10.5281/zenodo.4133884
title: Satellite Constellation Internet Affordability and Need

description: Large satellite constellations in low-Earth orbit seek to be the infrastructure for global broadband Internet and other telecommunication needs. We briefly review the impacts of satellite constellations on astronomy and show that the Internet service offered by these satellites will primarily target populations where it is unaffordable, not needed, or both. The harm done by tens to hundreds of thousands of low-Earth orbit satellites to astronomy, stargazers worldwide, and the environment is not acceptable. This dataset shows that there is a small population that both needs and can afford satellite Internet service. The remainder either does not need or cannot afford it. For each country, we plot the estimated cost of satellite constellation Internet service as a percentage of gross domestic product (GDP) per capita against percentage of individuals currently with Internet access. Affordable access is classed as &lt;10% of GDP per capita; need is classed as &lt;75% of the population currently having Internet access. Data and code to reproduce Figure 1 from the Research Note <em>Satellite Constellation Internet Affordability and Need</em> are at https://github.com/mrawls/sky-high-starlink
DOI: 10.5281/zenodo.4133883
title: Satellite Constellation Internet Affordability and Need

description: Large satellite constellations in low-Earth orbit seek to be the infrastructure for global broadband Internet and other telecommunication needs. We briefly review the impacts of satellite constellations on astronomy and show that the Internet service offered by these satellites will primarily target populations where it is unaffordable, not needed, or both. The harm done by tens to hundreds of thousands of low-Earth orbit satellites to astronomy, stargazers worldwide, and the environment is not acceptable. This dataset shows that there is a small population that both needs and can afford satellite Internet service. The remainder either does not need or cannot afford it. For each country, we plot the estimated cost of satellite constellation Internet service as a percentage of gross domestic product (GDP) per capita against percentage of individuals currently with Internet access. Affordable access is classed as &lt;10% of GDP per capita; need is classed as &lt;75% of the population currently having Internet access. Data and code to reproduce Figure 1 from the Research Note <em>Satellite Constellation Internet Affordability and Need</em> are at https://github.com/mrawls/sky-high-starlink
DOI: 10.7298/8sxf-b977
title: Data from the Cornell coherent scatter radar imager
DOI: 10.5281/zenodo.4516526
title: Comparison of COVID-19 vaccine prioritization strategies in the United States

description: Simulated population data and COVID-19 death risk estimates for California for running simulations in article "Comparison of COVID-19 vaccine prioritization strategies in the United States"
description: This dataset does not contain any raw or aggregated California Department of Public Health COVID-19 case data. Individuals interested in accessing such data should contact the California Department of Public Health. The associated study was supported by funding from the California Department of Public Health. NCL is supported by the University of California, San Francisco (Department of Medicine). The work represents the viewpoints of the authors alone and not necessarily those of the California Department of Public Health.
DOI: 10.5281/zenodo.4516525
title: Comparison of COVID-19 vaccine prioritization strategies in the United States

description: Simulated population data and COVID-19 death risk estimates for California for running simulations in article "Comparison of COVID-19 vaccine prioritization strategies in the United States"
description: This dataset does not contain any raw or aggregated California Department of Public Health COVID-19 case data. Individuals interested in accessing such data should contact the California Department of Public Health. The associated study was supported by funding from the California Department of Public Health. NCL is supported by the University of California, San Francisco (Department of Medicine). The work represents the viewpoints of the authors alone and not necessarily those of the California Department of Public Health.
DOI: 10.5517/ccdc.csd.cc26ygbz
title: CCDC 2054101: Experimental Crystal Structure Determination

description: Related Article: Rajarshi Mondal, Jason D. Braun, Issiah B. Lozada, Rachel Nickel, Johan van Lierop, David E. Herbert|2021|New J.Chem.|45|4427|doi:10.1039/D1NJ00254F
DOI: 10.5517/ccdc.csd.cc26ygc0
title: CCDC 2054102: Experimental Crystal Structure Determination

description: Related Article: Rajarshi Mondal, Jason D. Braun, Issiah B. Lozada, Rachel Nickel, Johan van Lierop, David E. Herbert|2021|New J.Chem.|45|4427|doi:10.1039/D1NJ00254F
DOI: 10.5517/ccdc.csd.cc26ygf2
title: CCDC 2054104: Experimental Crystal Structure Determination

description: Related Article: Rajarshi Mondal, Jason D. Braun, Issiah B. Lozada, Rachel Nickel, Johan van Lierop, David E. Herbert|2021|New J.Chem.|45|4427|doi:10.1039/D1NJ00254F
DOI: 10.5517/ccdc.csd.cc26ygh4
title: CCDC 2054106: Experimental Crystal Structure Determination

description: Related Article: Rajarshi Mondal, Jason D. Braun, Issiah B. Lozada, Rachel Nickel, Johan van Lierop, David E. Herbert|2021|New J.Chem.|45|4427|doi:10.1039/D1NJ00254F
DOI: 10.5517/ccdc.csd.cc26ygk6
title: CCDC 2054108: Experimental Crystal Structure Determination

description: Related Article: Rajarshi Mondal, Jason D. Braun, Issiah B. Lozada, Rachel Nickel, Johan van Lierop, David E. Herbert|2021|New J.Chem.|45|4427|doi:10.1039/D1NJ00254F
DOI: 10.5281/zenodo.3942354
title: ODP Leg 131, Hole 808B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 131: Nankai Trough
DOI: 10.5281/zenodo.3942353
title: ODP Leg 131, Hole 808B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 131: Nankai Trough
DOI: 10.5281/zenodo.3942356
title: ODP Leg 131, Hole 808C - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 131: Nankai Trough
DOI: 10.5281/zenodo.3942355
title: ODP Leg 131, Hole 808C - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 131: Nankai Trough
DOI: 10.5281/zenodo.3942358
title: ODP Leg 131, Hole 808E - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 131: Nankai Trough
DOI: 10.5281/zenodo.3942357
title: ODP Leg 131, Hole 808E - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 131: Nankai Trough
DOI: 10.5519/qd.w6aby0cz
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (69 records)
DOI: 10.5281/zenodo.3942362
title: ODP Leg 133, Hole 812B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942361
title: ODP Leg 133, Hole 812B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942364
title: ODP Leg 133, Hole 814A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942363
title: ODP Leg 133, Hole 814A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942366
title: ODP Leg 133, Hole 815A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942365
title: ODP Leg 133, Hole 815A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942368
title: ODP Leg 133, Hole 816C - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942367
title: ODP Leg 133, Hole 816C - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942372
title: ODP Leg 133, Hole 817D - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942371
title: ODP Leg 133, Hole 817D - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942374
title: ODP Leg 133, Hole 819A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942373
title: ODP Leg 133, Hole 819A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.4420313
title: Long read proteogenomics codeathon

description: Datasets for the CSHL LRP Codeathon team
DOI: 10.5281/zenodo.3942376
title: ODP Leg 133, Hole 820B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942375
title: ODP Leg 133, Hole 820B - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942378
title: ODP Leg 133, Hole 821A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin
DOI: 10.5281/zenodo.3942377
title: ODP Leg 133, Hole 821A - Well Logging Data

description: Logging data are measurements of physical properties of the formation surrounding a borehole, acquired in situ after completion of coring (wireline logging) or during drilling (Logging-While-Drilling, LWD). The range of data (resistivity, gamma radiation, velocity, density, borehole images,…) in any hole depends on the scientific objectives and operational constraints.
description: ODP Leg 133: Northeast Australian Margin