cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25909/13393226
title: simulated_summary_statistics_homog.csv

description: Simulated summary statistics, where homogeneous post-settlement migration patterns were used across all migration models.
DOI: 10.25909/13393226.v1
title: simulated_summary_statistics_homog.csv

description: Simulated summary statistics, where homogeneous post-settlement migration patterns were used across all migration models.
DOI: 10.5281/zenodo.17222839
title: The UAH Predictions of the Solar Wind and Magnetic Field at the Parker Solar Probe during Solar Encounter 23 (2025-03-21)

description: 1. Model

The MS-FLUKSS heliospheric MHD model is coupled with the WSA model (Kim et al. 2020), which used ADAPT-GONG input magnetograms, with the PFSS source surface height and the WSA outer boundary at 2.5 and 9 solar radii, respectively. The MHD model propagates the solar wind from 9 solar radii to 236 solar radii (1.1 AU) to fully enclose the PSP trajectory. Hence, field line tracing from PSP to the solar surface is performed through the MHD domain down to 9 solar radii instantaneously at approximately 1 hour cadence, where the origin of the field line on the photosphere is already known in the WSA model. See Badman et al. (2023) for details.

MS-FLUKSS: Multi-Scale Fluid-Kinetic Simulation Suite

MHD: Magnetohydrodynamic

WSA: Wang-Sheeley-Arge

ADAPT: Air Force Data Assimilative Photospheric flux Transport

GONG: Global Oscillation Network Group

PFSS: Potential Field Source Surface

PSP: Parker Solar Probe

 

2. Data

There are two sets of data files as described below:

(A) "PSP_AGONG_R000.dat" - "PSP_AGONG_R011.dat": MS-FLUKSS simulation results extracted along the PSP trajectory labeled by the input magnetogram (each of the 12 realizations of ADAPT-GONG) for the WSA model. 

Each data file consist of a header and 16 columns of numerical values in the following order:

(1) Time (fractional year)

(2) Heliocentric distance (AU)

(3) MS-FLUKSS longitude (rotated by ~180 degrees from inertial heliographic longitude in degrees)

(4) MS-FLUKSS latitude (same as heliographic latitude in degrees)

(5) Solar wind proton number density (cm^-3)

(6) Solar wind Vr (km/s)

(7) Solar wind Vphi (km/s)

(8) Solar wind Vtheta (km/s)

(9) Thermal pressure of solar wind and interstellar pickup ion mixture (picodyne/cm^2)

(10) Br (microgauss)

(11) Bphi (microgauss)

(12) Btheta (microgauss)

(13) Level set value for tracking the heliospheric current sheet

(14) Level set value for tracking the initial MS-FLUKSS longitude at the inner boundary

(15) Level set value for tracking the initial MS-FLUKSS latitude at the inner boundary

(16) Solar wind temperature.

 

(B) "UAH_psp_e23_20250321*_agongWSAmhd.csv": Carrington longitude and latitude of the predicted magnetic footpoint from 2025-03-21 to 2025-04-01.

 

Each data file consists of 4 columns of numeric values in the following order:

(1) Date (YYYY-MM-DD)

(2) Time (hh:mm:ss in UT)

(3) Carrington longitude (degree)

(4) Carrington latitude (degree)

 

3. Figures

There is one figure showing plots of predicted Br, Vr, density, and temperature at PSP: uah_psp_e23_20250321_agongWSAmhd.pdf.

A plot showing the footpoint prediction results projected onto the solar disk is available at the PSP science gateway, at https://psp-gateway.jhuapl.edu/website/SciencePlanning/MissionEvents/, under “Encounter 23”.
DOI: 10.25909/13393232
title: simulated_summary_statistics_east.csv

description: Simulated summary statistics, where we only model migration around the east coast of Australia. This is an extension of the initial migration models, and so each migration model has a different pattern of post-settlement migration.
DOI: 10.25909/13393232.v1
title: simulated_summary_statistics_east.csv

description: Simulated summary statistics, where we only model migration around the east coast of Australia. This is an extension of the initial migration models, and so each migration model has a different pattern of post-settlement migration.
DOI: 10.25909/13393256
title: simulated_summary_statistics_east_homog.csv

description: Simulated summary statistics, where we only model migration around the east coast of Australia and also assume homogeneous post-settlement migration patterns across all migration models.
DOI: 10.25909/13393256.v1
title: simulated_summary_statistics_east_homog.csv

description: Simulated summary statistics, where we only model migration around the east coast of Australia and also assume homogeneous post-settlement migration patterns across all migration models.
DOI: 10.25909/13601165
title: Grammatical phenomena in English L1 Czech L2 speakers found by panel

description: These sentences are instances of grammatical phenomena found in the English of L1 English L2 Czech speakers living in the Czech Republic. <br>These phenomena were identified by a panel of L1 English speakers living in the US, UK and Australia (the same nationalities as the participants studied). <br>These are not all of the sentences; the remainder of the examples are in the paper "Expats in Prague: Czech borrowings in L1 English speakers".
DOI: 10.25909/13601165.v1
title: Grammatical phenomena in English L1 Czech L2 speakers found by panel

description: These sentences are instances of grammatical phenomena found in the English of L1 English L2 Czech speakers living in the Czech Republic. <br>These phenomena were identified by a panel of L1 English speakers living in the US, UK and Australia (the same nationalities as the participants studied). <br>These are not all of the sentences; the remainder of the examples are in the paper "Expats in Prague: Czech borrowings in L1 English speakers".
DOI: 10.25909/13783528
title: Supplementary Tables S1-3.xlsx

description: Table S1: All DEG between the challenged and nonchallenged birds. Table S2. Differentially expressed long non-coding RNA Table S3. significantly impacted pathways by virulent NDV challenge.
DOI: 10.25909/13900901
title: Rare genera differentiate urban green space soil bacterial communities in three cities across the world
DOI: 10.25909/14091062
title: Fungal NSI enzyme HMM

description: HMM files for each recognised fungal nucleotide sugar interconversion enzyme family.
DOI: 10.25909/14134331
title: Cont Area vs Latitude Neopro - Collins et al ComEEnv

description: Continental Area versus Latitude from Merdith et al 2021 - Earth-Science Reviews used to create Fig 3a in Collins et al. 2021 - Communications Earth and Environment<br>
DOI: 10.25909/14134331.v1
title: Cont Area vs Latitude Neopro - Collins et al ComEEnv

description: Continental Area versus Latitude from Merdith et al 2021 - Earth-Science Reviews used to create Fig 3a in Collins et al. 2021 - Communications Earth and Environment<br>
DOI: 10.25909/14159054
title: Identifying the genetic control of salinity tolerance in the bread wheat landrace Mocho de Espiga Branca - data

description: Marker and genotype data for F2 Mocho x Gladius bread wheat mapping population used for QTL analysisPhenotypic data of of F2 Mocho x Gladius bread wheat population after salt stress (includes ionic concentrations (Na+, K+ and Cl-), projected shoot areas (PSA), Absolute Growth Rate (AGR), Relative Growth Rate (RGR), <br>
DOI: 10.25909/14273693
title: Images of Emydocephalus annulatus scale protuberances

description: Imaging showing gross morphology of scale protuberances in Emydocephalus annulatus. Images were taken of 59 museum specimens from the Australian Museum (AM), the Museum and Art Gallery of the Northern Territory (MAGNT) and the Western Australian Museum (WAM).<br>
DOI: 10.25909/14329754
title: Raw data on use on #neoEBM on Twitter: 2018-2021

description: Raw data describing the use of the hashtag #neoEBM on Twitter (social media platform) by numbers of Twitter users and use of the hashtag (monthly). <br><br>The datasheet includes the top 20 users of the hashtag and details about each one (publicly available information about each of these users available on the social media platform). <br>
DOI: 10.25909/14329754.v1
title: Raw data on use on #neoEBM on Twitter: 2018-2021

description: Raw data describing the use of the hashtag #neoEBM on Twitter (social media platform) by numbers of Twitter users and use of the hashtag (monthly). <br><br>The datasheet includes the top 20 users of the hashtag and details about each one (publicly available information about each of these users available on the social media platform). <br>
DOI: 10.25909/14504133
title: Mitochondrial consensus sequences from: Mitchell et al. (2021) "Disparate origins for endemic bird taxa from the 'Gondwanan Rainforests' of Central Eastern Australia" Biological Journal of the Linnean Society.

description: Mitochondrial consensus sequences from: Mitchell et al. (2021) "Disparate origins for endemic bird taxa from the 'Gondwanan Rainforests' of Central Eastern Australia" Biological Journal of the Linnean Society.<br>FASTA file containing multiple unaligned sequences.<br>Sequence identification:(Genus)_(museum accession)_(GenBank accession)<br>
DOI: 10.25909/14504277
title: Phylogenetic analysis files from: Mitchell et al. (2021) "Disparate origins for endemic bird taxa from the 'Gondwanan Rainforests' of Central Eastern Australia" Biological Journal of the Linnean Society.

description: Phylogenetic analysis files from: Mitchell et al. (2021) "Disparate origins for endemic bird taxa from the 'Gondwanan Rainforests' of Central Eastern Australia" Biological Journal of the Linnean Society.
DOI: 10.25909/14504277.v1
title: Phylogenetic analysis files from: Mitchell et al. (2021) "Disparate origins for endemic bird taxa from the 'Gondwanan Rainforests' of Central Eastern Australia" Biological Journal of the Linnean Society.

description: Phylogenetic analysis files from: Mitchell et al. (2021) "Disparate origins for endemic bird taxa from the 'Gondwanan Rainforests' of Central Eastern Australia" Biological Journal of the Linnean Society.
DOI: 10.25909/14529147
title: Alignment of 118 kakapo mtDNA genomes and 9 Macleay Museum mtDNA genomes in NEXUS format

description: DNA sequences alignment of 118 published kakapo mtDNA genomes and 9 mtDNA genomes from Macleay Museum kakapo specimens. Alignment is saved in NEXUS format and includes a TRAITS block for analysis in PopArt
DOI: 10.25909/14593869
title: kalyna fullKeyAtt

description: We did experiments on recovering the FULL key of 128/128 Kalyna. The dataset indicates that we are able to recover the full master key in 49 hours.
DOI: 10.25909/14604180
title: Supporting data for "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021)

description: This dataset contains post-processed rainfall forecast (hincast) data used in the study "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021).<br>This dataset was produced by the Australian Bureau of Meteorology. <br><br>Rainfall forecasts are produced using the Australian Community Climate Earth-System Simulator - Seasonal (ACCESS-S Version 1) (Hudson et al., 2017).<br>The ACCESS-S forecasts are then post-processed to reduce biases and improve reliability (Schepen et al., 2018).<br><br>References<br>Hudson, D., Alves, O., Hendon, H. H., Lim, E., Liu, G., Luo, J. J., MacLachlan, C., Marshall, A. G., Shi, L., Wang, G., Wedd, R., Young, G., Zhao, M. & Zhou, X. 2017. ACCESS-S1 The new Bureau of Meteorology multi-week to seasonal prediction system. Journal of Southern Hemisphere Earth System Sciences, 67, 132-159.<br>McInerney, D., Thyer, M., Kavetski, D., Laugesen, R.,Woldemeskel, F., Tuteja, N. & Kuczera, G. Improving the reliability of short-term forecasts of high and low flows by using a flow-dependent non-parametric model (under review).<br>Schepen, A., Zhao, T., Wang, Q. J. & Robertson, D. E. 2018. A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments. Hydrol. Earth Syst. Sci., 22, 1615-1628.<br>
DOI: 10.25909/14604180.v1
title: Supporting data for "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021)

description: This dataset contains post-processed rainfall forecast (hincast) data used in the study "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021).<br>This dataset was produced by the Australian Bureau of Meteorology. <br><br>Rainfall forecasts are produced using the Australian Community Climate Earth-System Simulator - Seasonal (ACCESS-S Version 1) (Hudson et al., 2017).<br>The ACCESS-S forecasts are then post-processed to reduce biases and improve reliability (Schepen et al., 2018).<br><br>References<br>Hudson, D., Alves, O., Hendon, H. H., Lim, E., Liu, G., Luo, J. J., MacLachlan, C., Marshall, A. G., Shi, L., Wang, G., Wedd, R., Young, G., Zhao, M. & Zhou, X. 2017. ACCESS-S1 The new Bureau of Meteorology multi-week to seasonal prediction system. Journal of Southern Hemisphere Earth System Sciences, 67, 132-159.<br>McInerney, D., Thyer, M., Kavetski, D., Laugesen, R.,Woldemeskel, F., Tuteja, N. & Kuczera, G. Improving the reliability of short-term forecasts of high and low flows by using a flow-dependent non-parametric model (under review).<br>Schepen, A., Zhao, T., Wang, Q. J. & Robertson, D. E. 2018. A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments. Hydrol. Earth Syst. Sci., 22, 1615-1628.<br>
DOI: 10.5281/zenodo.17223059
title: The UAH Predictions of the Solar Wind and Magnetic Field at the Parker Solar Probe during Solar Encounter 23 (2025-03-22)

description: 1. Model

The MS-FLUKSS heliospheric MHD model is coupled with the WSA model (Kim et al. 2020), which used ADAPT-GONG input magnetograms, with the PFSS source surface height and the WSA outer boundary at 2.5 and 9 solar radii, respectively. The MHD model propagates the solar wind from 9 solar radii to 236 solar radii (1.1 AU) to fully enclose the PSP trajectory. Hence, field line tracing from PSP to the solar surface is performed through the MHD domain down to 9 solar radii instantaneously at approximately 1 hour cadence, where the origin of the field line on the photosphere is already known in the WSA model. See Badman et al. (2023) for details.

MS-FLUKSS: Multi-Scale Fluid-Kinetic Simulation Suite

MHD: Magnetohydrodynamic

WSA: Wang-Sheeley-Arge

ADAPT: Air Force Data Assimilative Photospheric flux Transport

GONG: Global Oscillation Network Group

PFSS: Potential Field Source Surface

PSP: Parker Solar Probe

 

2. Data

There are two sets of data files as described below:

(A) "PSP_AGONG_R000.dat" - "PSP_AGONG_R011.dat": MS-FLUKSS simulation results extracted along the PSP trajectory labeled by the input magnetogram (each of the 12 realizations of ADAPT-GONG) for the WSA model. 

Each data file consist of a header and 16 columns of numerical values in the following order:

(1) Time (fractional year)

(2) Heliocentric distance (AU)

(3) MS-FLUKSS longitude (rotated by ~180 degrees from inertial heliographic longitude in degrees)

(4) MS-FLUKSS latitude (same as heliographic latitude in degrees)

(5) Solar wind proton number density (cm^-3)

(6) Solar wind Vr (km/s)

(7) Solar wind Vphi (km/s)

(8) Solar wind Vtheta (km/s)

(9) Thermal pressure of solar wind and interstellar pickup ion mixture (picodyne/cm^2)

(10) Br (microgauss)

(11) Bphi (microgauss)

(12) Btheta (microgauss)

(13) Level set value for tracking the heliospheric current sheet

(14) Level set value for tracking the initial MS-FLUKSS longitude at the inner boundary

(15) Level set value for tracking the initial MS-FLUKSS latitude at the inner boundary

(16) Solar wind temperature.

 

(B) "UAH_psp_e23_20250322*_agongWSAmhd.csv": Carrington longitude and latitude of the predicted magnetic footpoint from 2025-03-22 to 2025-04-01.

 

Each data file consists of 4 columns of numeric values in the following order:

(1) Date (YYYY-MM-DD)

(2) Time (hh:mm:ss in UT)

(3) Carrington longitude (degree)

(4) Carrington latitude (degree)

 

Note that these predictions were submitted on time (before 1 PM EDT), but not included in the March 22 consensus prediction due to communication error. Instead, they were part of the March 23 consensus prediction.

 

3. Figures

There is one figure showing plots of predicted Br, Vr, density, and temperature at PSP: uah_psp_e23_20250322_agongWSAmhd.pdf.

A plot showing the footpoint prediction results projected onto the solar disk is available at the PSP science gateway, at https://psp-gateway.jhuapl.edu/website/SciencePlanning/MissionEvents/, under “Encounter 23”.
DOI: 10.5281/zenodo.17223060
title: The UAH Predictions of the Solar Wind and Magnetic Field at the Parker Solar Probe during Solar Encounter 23 (2025-03-22)

description: 1. Model

The MS-FLUKSS heliospheric MHD model is coupled with the WSA model (Kim et al. 2020), which used ADAPT-GONG input magnetograms, with the PFSS source surface height and the WSA outer boundary at 2.5 and 9 solar radii, respectively. The MHD model propagates the solar wind from 9 solar radii to 236 solar radii (1.1 AU) to fully enclose the PSP trajectory. Hence, field line tracing from PSP to the solar surface is performed through the MHD domain down to 9 solar radii instantaneously at approximately 1 hour cadence, where the origin of the field line on the photosphere is already known in the WSA model. See Badman et al. (2023) for details.

MS-FLUKSS: Multi-Scale Fluid-Kinetic Simulation Suite

MHD: Magnetohydrodynamic

WSA: Wang-Sheeley-Arge

ADAPT: Air Force Data Assimilative Photospheric flux Transport

GONG: Global Oscillation Network Group

PFSS: Potential Field Source Surface

PSP: Parker Solar Probe

 

2. Data

There are two sets of data files as described below:

(A) "PSP_AGONG_R000.dat" - "PSP_AGONG_R011.dat": MS-FLUKSS simulation results extracted along the PSP trajectory labeled by the input magnetogram (each of the 12 realizations of ADAPT-GONG) for the WSA model. 

Each data file consist of a header and 16 columns of numerical values in the following order:

(1) Time (fractional year)

(2) Heliocentric distance (AU)

(3) MS-FLUKSS longitude (rotated by ~180 degrees from inertial heliographic longitude in degrees)

(4) MS-FLUKSS latitude (same as heliographic latitude in degrees)

(5) Solar wind proton number density (cm^-3)

(6) Solar wind Vr (km/s)

(7) Solar wind Vphi (km/s)

(8) Solar wind Vtheta (km/s)

(9) Thermal pressure of solar wind and interstellar pickup ion mixture (picodyne/cm^2)

(10) Br (microgauss)

(11) Bphi (microgauss)

(12) Btheta (microgauss)

(13) Level set value for tracking the heliospheric current sheet

(14) Level set value for tracking the initial MS-FLUKSS longitude at the inner boundary

(15) Level set value for tracking the initial MS-FLUKSS latitude at the inner boundary

(16) Solar wind temperature.

 

(B) "UAH_psp_e23_20250322*_agongWSAmhd.csv": Carrington longitude and latitude of the predicted magnetic footpoint from 2025-03-22 to 2025-04-01.

 

Each data file consists of 4 columns of numeric values in the following order:

(1) Date (YYYY-MM-DD)

(2) Time (hh:mm:ss in UT)

(3) Carrington longitude (degree)

(4) Carrington latitude (degree)

 

Note that these predictions were submitted on time (before 1 PM EDT), but not included in the March 22 consensus prediction due to communication error. Instead, they were part of the March 23 consensus prediction.

 

3. Figures

There is one figure showing plots of predicted Br, Vr, density, and temperature at PSP: uah_psp_e23_20250322_agongWSAmhd.pdf.

A plot showing the footpoint prediction results projected onto the solar disk is available at the PSP science gateway, at https://psp-gateway.jhuapl.edu/website/SciencePlanning/MissionEvents/, under “Encounter 23”.
DOI: 10.25909/14978817
title: GRAFT systematic review data

description: Data collected from systematic review used to generate GRAFT recommendations
DOI: 10.25909/14978817.v2
title: GRAFT systematic review data

description: Data collected from systematic review used to generate GRAFT recommendations
DOI: 10.25909/14986014
title: Scirtid_Exabayes_RAXML.nex. Phylogeny of Scirtinae inferred with UCE’s.

description: Nexus alignments for the manuscript "Evolutionary history of the Australasian Scirtinae (Scirtidae; Coleoptera) inferred from ultraconserved elements"
DOI: 10.25909/14986014.v2
title: Scirtid_Exabayes_RAXML.nex. Phylogeny of Scirtinae inferred with UCE’s.

description: Nexus alignments for the manuscript "Evolutionary history of the Australasian Scirtinae (Scirtidae; Coleoptera) inferred from ultraconserved elements"
DOI: 10.25909/14986020
title: Scirtid_Beast.nex. Phylogeny of Scirtinae inferred with UCE’s

description: Nexus alignments for the manuscript "Evolutionary history of the Australasian Scirtinae (Scirtidae; Coleoptera) inferred from ultraconserved elements"
DOI: 10.25909/14986020.v2
title: Scirtid_Beast.nex. Phylogeny of Scirtinae inferred with UCE’s

description: Nexus alignments for the manuscript "Evolutionary history of the Australasian Scirtinae (Scirtidae; Coleoptera) inferred from ultraconserved elements"
DOI: 10.25909/15132666
title: Dataset_Experiment 1 Figure 1 Impact of delaying blood processing on cryopreserved total viable cell number and viability

description: The impact of delaying blood processing on cryopreserved total viable cell number and viability
DOI: 10.25909/15132666.v1
title: Dataset_Experiment 1 Figure 1 Impact of delaying blood processing on cryopreserved total viable cell number and viability

description: The impact of delaying blood processing on cryopreserved total viable cell number and viability
DOI: 10.25909/15132678
title: Dataset_Experiment 1 Figure 2 Impact of delaying blood processing on post thaw and post incubation parameters

description: The Impacts of delaying blood processing on post thaw and post incubation parameters
DOI: 10.25909/15132678.v1
title: Dataset_Experiment 1 Figure 2 Impact of delaying blood processing on post thaw and post incubation parameters

description: The Impacts of delaying blood processing on post thaw and post incubation parameters
DOI: 10.25909/15132684
title: Dataset_Experiment 1 Functional analysis and Immunophenotyping analysis

description: Functional analysis: CEF and PHAImmunophenotyping analysis: Low density neutrophils, monocytes, lymphocytes, T-cells, NK cells and B cells.<br>
DOI: 10.25909/15132684.v1
title: Dataset_Experiment 1 Functional analysis and Immunophenotyping analysis

description: Functional analysis: CEF and PHAImmunophenotyping analysis: Low density neutrophils, monocytes, lymphocytes, T-cells, NK cells and B cells.<br>
DOI: 10.25909/15132708
title: Dataset_Experiment 2 Impact of cell volume on PBMC quality

description: Impact of cryopreserved cell volume on PBMC quality
DOI: 10.25909/15132708.v1
title: Dataset_Experiment 2 Impact of cell volume on PBMC quality

description: Impact of cryopreserved cell volume on PBMC quality
DOI: 10.25909/15132714
title: Dataset_Experiment 3 Impact of cell concentration on PBMC quality

description: Impact of cryopreserved cell concentration on PBMC quality
DOI: 10.25909/15132714.v1
title: Dataset_Experiment 3 Impact of cell concentration on PBMC quality

description: Impact of cryopreserved cell concentration on PBMC quality
DOI: 10.25909/15982587
title: Jones_et_al_2021_ClimateSmart_mariculture_revised_supp_tables.xlsx

description: Supplementary tables (S1 - S5) and literature review metadata for Jones et al 2021 'Climate-Friendly Seafood: The Potential for Emissions Reduction and Carbon Capture in Marine Aquaculture'
DOI: 10.25909/16391697
title: Solar panel data in max luminous

description: A 3 cell groups solar panel were tested. 22 cells are in one cell group.
DOI: 10.25909/16391697.v2
title: Solar panel data in max luminous

description: A 3 cell groups solar panel were tested. 22 cells are in one cell group.