cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15186326
title: Data set: Uncovering the drivers of vertebra number variation in Australian blindsnakes

description: Repository for "Uncovering the drivers of vertebra number variation in Australian blindsnakes"

---

These data scripts were used to perform analyses included in the research paper "Uncovering the drivers of vertebra number variation in Australian blindsnakes" in The Evolutionary Journal of the Linnean Society.

## Data structure

Contents in the data folder is archived as a zip and can be downloaded from Zenodo (for all versions see https://zenodo.org/doi/10.5281/zenodo.15186327). Once you unzip the zipped files, you will see:

/data/read-only/ - raw measurements from different specimens

/data/script_generated_data/ - A combination of processed data needed to run the analyses. Headshape and body shape data are generated from [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.13743462.svg)](https://doi.org/10.5281/zenodo.13743462)

/data/x-ray/ - files for plotting vertebral profile

/data/radiograph.zip - zip archive with all X-ray images

## Code/Software

All scripts can be run in R Statistical Environment. Scripts should be run in order to create necessary files that will be saved in /data/script_generated_data/ for further scripts.
DOI: 10.5281/zenodo.15186327
title: Data set: Uncovering the drivers of vertebra number variation in Australian blindsnakes

description: Repository for "Uncovering the drivers of vertebra number variation in Australian blindsnakes"

---

These data scripts were used to perform analyses included in the research paper "Uncovering the drivers of vertebra number variation in Australian blindsnakes" in The Evolutionary Journal of the Linnean Society.

## Data structure

Contents in the data folder is archived as a zip and can be downloaded from Zenodo (for all versions see https://zenodo.org/doi/10.5281/zenodo.15186327). Once you unzip the zipped files, you will see:

/data/read-only/ - raw measurements from different specimens

/data/script_generated_data/ - A combination of processed data needed to run the analyses. Headshape and body shape data are generated from [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.13743462.svg)](https://doi.org/10.5281/zenodo.13743462)

/data/x-ray/ - files for plotting vertebral profile

/data/radiograph.zip - zip archive with all X-ray images

## Code/Software

All scripts can be run in R Statistical Environment. Scripts should be run in order to create necessary files that will be saved in /data/script_generated_data/ for further scripts.
DOI: 10.21954/ou.rd.27604914
title: Supplementary materials for the PhD thesis "Chant : forms and functions in five case studies"

description: <i>This dataset</i><i> </i><i>comprises</i><i> </i><i>the files contained on a CD-ROM which was attached to the thesis when it was</i><i> </i><i>submitted</i><i> </i><i>in</i><i> </i><i>2006</i><i>. It was uploaded to ORDO in 2024 for preservation purposes.</i><i> </i><i>For more information, please refer to the thes</i><i>is </i><i>Chant : forms and functions in five case studies</i><i> via ORO.</i>
DOI: 10.21954/ou.rd.27604914.v1
title: Supplementary materials for the PhD thesis "Chant : forms and functions in five case studies"

description: <i>This dataset</i><i> </i><i>comprises</i><i> </i><i>the files contained on a CD-ROM which was attached to the thesis when it was</i><i> </i><i>submitted</i><i> </i><i>in</i><i> </i><i>2006</i><i>. It was uploaded to ORDO in 2024 for preservation purposes.</i><i> </i><i>For more information, please refer to the thes</i><i>is </i><i>Chant : forms and functions in five case studies</i><i> via ORO.</i>
DOI: 10.15468/dl.w8369t
title: Occurrence Download

description: A dataset containing 153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bactrocera dorsalis (Hendel, 1912)",
 "Country is Japan",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 153 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020784-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/ggwyg3
title: Missiemuseum - Herbarium Martin Gusinde

description: Herbarium with 105 preserved specimens on separate sheets. The specimens were collected by S.V.D. missionary Martin Gusinde (1886 - 1969) between 1922 and 1924, during various research trips to the south of Chile. Locations where he collected specimens from are Canal Smyth (Chile) and in Tierra del Fuego along Canal Beagle (Remolino - Argentina & Navarino - Chile).The formation of the collected specimens into an herbarium dates from a later, unknown, period. This can be concluded from the reference numbers not corresponding with the years in a chronological manner.Gusinde was in contact with many botanists and scientists around the world, especially with Carl Skottsberg (1880-1963). The are multiple herbaria collected by Gusinde around the world.The herbarium was researched in May 2023 by Daniela Salazar Rodríguez (Pontificia Universidad Católica, Chile) in collaboration with Prof. Dr. Tinde van Andel (Naturalis Biodiversity Center, the Netherlands).
DOI: 10.5518/988
title: Impact of the 2019/2020 Australian megafires on Air Quality and Health

description: Dataset used to estimate AQ and health impacts in 'Impact of the 2019/2020 Australian megafires on Air Quality and Health' . Daily mean modelled data for the fires and no fires simulations are provided alongside the fires only contribution (calculated as fires-no_fires) at ~1km resolution (the same latitude, longitude grid as the population data). Individual daily mean files are provided with the date indicating the day of data.
DOI: 10.15468/dl.vznkuy
title: Occurrence Download

description: A dataset containing 179 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Occurrence evidence",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ulva lactuca L."
 ]
}

 The dataset includes 179 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020786-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.byhqnh
title: Occurrence Download

description: A dataset containing 683 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Adenanthera microsperma Teijsm. & Binn."
 ]
}

 The dataset includes 683 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020787-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h7tccm
title: Occurrence Download

description: A dataset containing 31248 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Celastrus orbiculatus Thunb."
 ]
}

 The dataset includes 31248 records from 250 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020785-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rdxaqz
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bos mutus (Przewalski, 1883)"
 ]
}

 The dataset includes 35 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020788-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14034159
title: Data and code for "Aggregation behaviour as an adaptive reproductive strategy in a marine ecosystem engineer".

description: README for data and code for "Aggregation behaviour as an adaptive reproductive strategy in a marine ecosystem engineer".

Contains the data and R script necessary to reproduce the analyses and figures presented in the above-mentioned manuscript. Below is a description of each file and its role in the analysis.

 

Files Included:

Histology.xlsx: This Excel file contains a table, identical to Supporting Information S5, with detailed information about the individuals used to assess the histological stage, including sex, reproductive stages and the total sample sizes used to calculate the mean sexual stage for each month. This data is used to make Figure 1B in the manuscript and Figure 3 in the Supporting Information S5.

 

Aggregation.xlsx: This Excel file dataset contains a dataset that results from behavioural experiments and histological measurements taken from March to December 2021 (excluding October and November). It includes data for both control (C) and microplastic leachate (MP) treatments. This file is used with the accompanying R script (Aggregation_Reproduction_Code.R) to produce the statistical analyses and remaining figures in the manuscript and Supporting Information.

Details of the Aggregation.xlsx dataset

-       treatment = Treatment group: "C" for Control, "MP" for microplastic leachate

-       rep = Replicate number

-       months = Month of the experiment (numerical: e.g. 1 = March, 8 = December)

-       month = Month of the experiment (categorical: e.g. "March", "April")

-       AGG = Proportion of mussels (%) forming aggregates after 2 hours of experiment

-       stage = Mean reproductive stage for each month (obtained from Histology.xlsx file)

 

Aggregation_Reproduction_Code.R: This R script is used with the Aggregation.xlsx dataset to produce the remaining statistical results and figures presented in the manuscript and Supporting Information.

 

Instructions for Use:

Load the Aggregation.xlsx into your R environment.

Run the Aggregation_Reproduction_Code.R script to reproduce the statistical analyses and figures included in the manuscript and Supporting Information.
DOI: 10.5281/zenodo.14034160
title: Data and code for "Aggregation behaviour as an adaptive reproductive strategy in a marine ecosystem engineer".

description: README for data and code for "Aggregation behaviour as an adaptive reproductive strategy in a marine ecosystem engineer".

Contains the data and R script necessary to reproduce the analyses and figures presented in the above-mentioned manuscript. Below is a description of each file and its role in the analysis.

 

Files Included:

Histology.xlsx: This Excel file contains a table, identical to Supporting Information S5, with detailed information about the individuals used to assess the histological stage, including sex, reproductive stages and the total sample sizes used to calculate the mean sexual stage for each month. This data is used to make Figure 1B in the manuscript and Figure 3 in the Supporting Information S5.

 

Aggregation.xlsx: This Excel file dataset contains a dataset that results from behavioural experiments and histological measurements taken from March to December 2021 (excluding October and November). It includes data for both control (C) and microplastic leachate (MP) treatments. This file is used with the accompanying R script (Aggregation_Reproduction_Code.R) to produce the statistical analyses and remaining figures in the manuscript and Supporting Information.

Details of the Aggregation.xlsx dataset

-       treatment = Treatment group: "C" for Control, "MP" for microplastic leachate

-       rep = Replicate number

-       months = Month of the experiment (numerical: e.g. 1 = March, 8 = December)

-       month = Month of the experiment (categorical: e.g. "March", "April")

-       AGG = Proportion of mussels (%) forming aggregates after 2 hours of experiment

-       stage = Mean reproductive stage for each month (obtained from Histology.xlsx file)

 

Aggregation_Reproduction_Code.R: This R script is used with the Aggregation.xlsx dataset to produce the remaining statistical results and figures presented in the manuscript and Supporting Information.

 

Instructions for Use:

Load the Aggregation.xlsx into your R environment.

Run the Aggregation_Reproduction_Code.R script to reproduce the statistical analyses and figures included in the manuscript and Supporting Information.
DOI: 10.5281/zenodo.14000405
title: Interlaminar fracture behaviour of emerging laminated-pultruded CFRP plates for wind turbine blades

description: The present work investigates the interlaminar fracture behaviour of pultruded composite plates bonded by resin infusion to form thick CFRP structures. Mode I, II and mixed mode (I/II) tests were performed to obtain fracture properties at different mixed mode ratios.  This publication provides the data set for quasi-static delamination under Mode I (DCB), Mode II (ELS) and Mixed Mode (MMB), including raw data, crack length images and post-processing data. For each data we provide the CHADA for metadata.

 

The research was funded by the European Union under GA No. 101091409 (D-STANDART). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.
DOI: 10.5281/zenodo.14000406
title: Interlaminar fracture behaviour of emerging laminated-pultruded CFRP plates for wind turbine blades

description: The present work investigates the interlaminar fracture behaviour of pultruded composite plates bonded by resin infusion to form thick CFRP structures. Mode I, II and mixed mode (I/II) tests were performed to obtain fracture properties at different mixed mode ratios.  This publication provides the data set for quasi-static delamination under Mode I (DCB), Mode II (ELS) and Mixed Mode (MMB), including raw data, crack length images and post-processing data. For each data we provide the CHADA for metadata.

 

The research was funded by the European Union under GA No. 101091409 (D-STANDART). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.
DOI: 10.5281/zenodo.14034467
title: Cell Viability Assay

description: MTT Cell Viability Assay Data
DOI: 10.5281/zenodo.14034468
title: Cell Viability Assay

description: MTT Cell Viability Assay Data
DOI: 10.5281/zenodo.14006835
title: Mutually validated Tilt Angle Dataset

description: Mutually-Validated Tilt Angle Dataset

This dataset provides reliable sunspot group/active region(AR) tilt angle data and several other parameters from 1996 to 2018.

Overview

The dataset is generated by mutually validating two existing datasets: (1) A-live-homogeneous-database-of-solar-active-regions by Ruihui Wang, Jie Jiang and Yukun Luo (WJL), and (2) Debrecen Photoheliographic Data sunspot catalogue by Baranyi, T., Győri, L. and Ludmány, A. (DPD). The original datasets can be downloaded via their websites: A-live-homogeneous-database-of-solar-active-regions and Debrecen Photoheliographic Data

The mutual validation is automatically accomplished by Python. The code, mutual_validation.py, is attached. For a more detailed description of the mutual validation method, see Lang Qin, Jie Jiang, Ruihui Wang, Mutual Validation of Datasets for Analyzing Tilt Angles in Solar Active Regions(APJ under review)



Data Description


The mutually validated datset is in the file mutually_validated_tilt_angle_dataset.xlsx. There are 14 columns, each contains a type of parameter. The meanings of each header are as follows:



date_dpd: date of observation in DPD dataset

lat_dpd: heliographic latitude of the sunspot group

lon_dpd: (Carrington) heliographic longitude of the sunspot group

area_dpd: the total area of the sunspot group in μMSH

tilt_dpd: the tilt angle of the sunspot group

date_wjl: date of observation in WJL dataset

lat_wjl: heliographic latitude of the active region

lon_wjl: (Carrington) heliographic longitude of the active region

area_wjl: the total area of the active region in μMSH

flux_wjl: the total unsigned magnetic flux of the active region in Mx

tilt_wjl: the tilt angle of the active region

number: the NOAA number

CR: the Carrington rotation number of the sunspot group/active region

consistency: the marker of whether the two tilt angle values are close enough to be considered consistent. "1" means consistent and "0" means inconsistent




Author


Lang Qin, Jie Jiang, Yukun Luo
DOI: 10.5281/zenodo.14006983
title: Mutually validated Tilt Angle Dataset

description: Mutually-Validated Tilt Angle Dataset

This dataset provides reliable sunspot group/active region(AR) tilt angle data and several other parameters from 1996 to 2018.

Overview

The dataset is generated by mutually validating two existing datasets: (1) A-live-homogeneous-database-of-solar-active-regions by Ruihui Wang, Jie Jiang and Yukun Luo (WJL), and (2) Debrecen Photoheliographic Data sunspot catalogue by Baranyi, T., Győri, L. and Ludmány, A. (DPD). The original datasets can be downloaded via their websites: A-live-homogeneous-database-of-solar-active-regions and Debrecen Photoheliographic Data

The mutual validation is automatically accomplished by Python. The code, mutual_validation.py, is attached. For a more detailed description of the mutual validation method, see Lang Qin, Jie Jiang, Ruihui Wang, Mutual Validation of Datasets for Analyzing Tilt Angles in Solar Active Regions(APJ under review)



Data Description


The mutually validated datset is in the file mutually_validated_tilt_angle_dataset.xlsx. There are 14 columns, each contains a type of parameter. The meanings of each header are as follows:



date_dpd: date of observation in DPD dataset

lat_dpd: heliographic latitude of the sunspot group

lon_dpd: (Carrington) heliographic longitude of the sunspot group

area_dpd: the total area of the sunspot group in μMSH

tilt_dpd: the tilt angle of the sunspot group

date_wjl: date of observation in WJL dataset

lat_wjl: heliographic latitude of the active region

lon_wjl: (Carrington) heliographic longitude of the active region

area_wjl: the total area of the active region in μMSH

flux_wjl: the total unsigned magnetic flux of the active region in Mx

tilt_wjl: the tilt angle of the active region

number: the NOAA number

CR: the Carrington rotation number of the sunspot group/active region

consistency: the marker of whether the two tilt angle values are close enough to be considered consistent. "1" means consistent and "0" means inconsistent




Author


Lang Qin, Jie Jiang, Yukun Luo
DOI: 10.6084/m9.figshare.27604839
title: <b>Long</b><b> </b><b>history paddy rice mapping</b><b> </b><b>across Northeast</b><b> </b><b>China with</b><b> </b><b>deep</b><b> </b><b>learning</b><b> </b><b>and </b><b>a</b><b>nnual</b><b> r</b><b>esult</b><b> e</b><b>nhancement</b><b> </b><b>method</b>

description: We utilized multi-sensor Landsat data and a deep learning model to conduct the first annual mapping of paddy rice in Northeast China from 1985 to 2023. We employed the Annual Result Enhancement (ARE) method, which accounts for differences in category probabilities produced by the deep learning model at various stages. This approach helps mitigate the impact of limited training samples when mapping paddy rice on a large scale and across different sensors. Compared to traditional rice mapping methods, the results obtained using the ARE method demonstrated a 6% increase in the F1 score.
DOI: 10.5518/996
title: Intermediate structural hierarchy in biological networks modulates the fractal dimension and force distribution of percolating clusters - Simulation Data

description: We computationally investigated the effect of intermediate (polymeric) nanoscale structure on the formation of protein hydrogels, and found that pre-assembled intermediate structure provides a novel structural coordinate for the hierarchical modulation of macroscopic network properties, as well as furthering our understanding of the general dynamics of network formation. This is the computational dataset comprising our results.
DOI: 10.3886/e210202
title: Analysing the factor structure of the MAIA scale for pregnant women: Development of the MAIA-Preg.

description: During
pregnancy many elements of the bodily experience change, suggesting that
measuring these constructs may require different instruments to those validated
in the general population. This study reports an exploratory and confirmatory
factor analysis exploration of the Multidimensional Assessment of Interoceptive
Awareness (MAIA) in 716 pregnant women (mean gestation 26.4 weeks), from six different
datasets who completed the MAIA online. Exploratory factor
analysis condensed the questionnaire from a 32- to a 19- item scale, with five
factor structure, which best fitted the data. Key subscales of Trust, Attention
Regulation, Self-Regulation and Not Distracting remained robust. The one
remaining item from the Noticing subscale loaded heavily with the Emotional
Awareness subscale. Subscales of Body Listening, Not Worrying and Noticing did
not load and therefore were excluded as factors. This led to the development of
the scale referred to as the MAIA-Preg, which demonstrated a good fit with a
confirmatory factor analysis along with good subscale reliability (ω= 0.73 - .92), and measurement invariance for
second and third trimesters. The MAIA-Preg was also found to be a good fit for
separate non-pregnant (N = 396) and postnatal (N = 174) samples and thus
provides a reliable and valid measure, providing nuanced information about the
bodily experience in perinatal populations, allowing comparisons of changes to
interoceptive sensibility the perinatal period. 

Across
DOI: 10.3886/e210202v1
title: Analysing the factor structure of the MAIA scale for pregnant women: Development of the MAIA-Preg.

description: During
pregnancy many elements of the bodily experience change, suggesting that
measuring these constructs may require different instruments to those validated
in the general population. This study reports an exploratory and confirmatory
factor analysis exploration of the Multidimensional Assessment of Interoceptive
Awareness (MAIA) in 716 pregnant women (mean gestation 26.4 weeks), from six different
datasets who completed the MAIA online. Exploratory factor
analysis condensed the questionnaire from a 32- to a 19- item scale, with five
factor structure, which best fitted the data. Key subscales of Trust, Attention
Regulation, Self-Regulation and Not Distracting remained robust. The one
remaining item from the Noticing subscale loaded heavily with the Emotional
Awareness subscale. Subscales of Body Listening, Not Worrying and Noticing did
not load and therefore were excluded as factors. This led to the development of
the scale referred to as the MAIA-Preg, which demonstrated a good fit with a
confirmatory factor analysis along with good subscale reliability (ω= 0.73 - .92), and measurement invariance for
second and third trimesters. The MAIA-Preg was also found to be a good fit for
separate non-pregnant (N = 396) and postnatal (N = 174) samples and thus
provides a reliable and valid measure, providing nuanced information about the
bodily experience in perinatal populations, allowing comparisons of changes to
interoceptive sensibility the perinatal period. 

Across
DOI: 10.15468/dl.2yvweu
title: Occurrence Download

description: A dataset containing 3729 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acer ukurunduense Trautv. & C.A.Mey."
 ]
}

 The dataset includes 3729 records from 130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020791-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.