cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13027979.v4
title: Raw data for: Humeral diaphysis structure across mammals

description: File S1. Archive with raw data acquisition for both extant and extinct species, as well as timetree used for phylogenetically informed tests.<br><br>Table S1. Data table comprising the raw data file names for each extant species (LabelHum), species name, lifestyle, body mass (BM), catalogue number (CNum), mean total cross-sectional area (MeanTotArea), p-value associated to the slope of the Cg profile regression (slopeP), as well as its slope and R2. <br><br>Supplementary figures:<br> - Figure S1. Timetree of the extant species sampled. Colours correspond to the specialised lifestyles, i.e., aerial, aquatic, and subterranean; black corresponds to the terrestrial lifestyle. Each doodle represents an independent acquisition of one of the three specialized lifestyle. Abbreviations: Anom., Anomaluromorpha; Lag., Lagomorpha; Xe, Xenarthra.<br><br> - Figure S2. Phenogram of compactness (Cg) profiles slopes (see simplified version in main text, figure 2c).<br><br>
DOI: 10.5281/zenodo.4280859
title: Natural Lake Database in China in 2015 (NLD_China2015)

description: The first database of natural lakes with an area &gt; 0.01 km<sup>2</sup> in China in 2015 (NLD_China2015). The database was manually developed in reference to the existing lake inventories, reservoir datasets, and high-resolution images from Google Earth.
DOI: 10.5281/zenodo.4280858
title: Natural Lake Database in China in 2015 (NLD_China2015)

description: The first database of natural lakes with an area &gt; 0.01 km<sup>2</sup> in China in 2015 (NLD_China2015). The database was manually developed in reference to the existing lake inventories, reservoir datasets, and high-resolution images from Google Earth.
DOI: 10.6084/m9.figshare.13259528
title: Supplemental data

description: <b>Differential microRNA profiles of endothelial progenitor cells in preeclampsia</b>Supplemental documents:Supp Table 1 - 3Supp Methods Supp figure 1
DOI: 10.6084/m9.figshare.13259528.v1
title: Supplemental data

description: <b>Differential microRNA profiles of endothelial progenitor cells in preeclampsia</b>Supplemental documents:Supp Table 1 - 3Supp Methods Supp figure 1
DOI: 10.6084/m9.figshare.13259540.v1
title: OO Centrality and Quality Metrics

description: Dataset and tools for replicating the study titled: Do centrality measures derived from varying dependency types provide similar or useful information about OO software quality?
DOI: 10.6084/m9.figshare.13259540
title: OO Centrality and Quality Metrics

description: Dataset and tools for replicating the study titled: Do centrality measures derived from varying dependency types provide similar or useful information about OO software quality?
DOI: 10.6084/m9.figshare.13259522
title: Table 1.docx

description: Comparison of general information and condition of patients of two groups. N(Number),Time window of operation(The time from patients’cervical cord be injured to received operation treatment),H(Hour),D(Day),W(Week),Damaged segment(The segment of injured cervical vertebra), ASIA (The American Spinal Injury Association). <i></i><sub></sub><sup></sup><b></b><br>
DOI: 10.6084/m9.figshare.13259522.v1
title: Table 1.docx

description: Comparison of general information and condition of patients of two groups. N(Number),Time window of operation(The time from patients’cervical cord be injured to received operation treatment),H(Hour),D(Day),W(Week),Damaged segment(The segment of injured cervical vertebra), ASIA (The American Spinal Injury Association). <i></i><sub></sub><sup></sup><b></b><br>
DOI: 10.6084/m9.figshare.13153457
title: Supplementary information & calculations - Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths

description: PDF contains supplementary information to the paper: Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths.<br>Spreadsheet contains all calculations related to the paper: Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths.
DOI: 10.6084/m9.figshare.13153457.v2
title: Supplementary information & calculations - Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths

description: PDF contains supplementary information to the paper: Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths.<br>Spreadsheet contains all calculations related to the paper: Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths.
DOI: 10.6084/m9.figshare.13153457.v1
title: Calculations - Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths

description: All calculations related to the paper: Mortality displacement: Vulnerable “dry tinder” elders in Sweden prior to COVID-19 may partially account for excess deaths.
DOI: 10.25828/e4wk-9c69
title: Quarterly Labour Force Survey 2020, Quarter 3
DOI: 10.6084/m9.figshare.13259570
title: Table2

description: The pre and post-treatment spinal cord function scores of the two groups.<br>
DOI: 10.6084/m9.figshare.13259570.v2
title: Table2

description: The pre and post-treatment spinal cord function scores of the two groups.<br>
DOI: 10.6084/m9.figshare.13259570.v1
title: Untitled Item

description: The pre and post-treatment spinal cord function scores of the two groups.<br>
DOI: 10.6084/m9.figshare.13259579
title: List of java GitHub projects

description: List of github projects
DOI: 10.6084/m9.figshare.13259579.v1
title: List of java GitHub projects

description: List of github projects
DOI: 10.5281/zenodo.4280871
title: FUI Water Color product of inland waters in China at 30-m in 2015

description: The first 30-meters FUI water color product of China. The product was developed using time-series Landsat 8 imagery and FUI water color retrieval method. Taking into account the huge amount of computational and storage space required for the national-scale water color mapping, the high-performance Google Earth Engine (GEE) cloud-based platform was introduced to support the computation. First, a cloud-free composite in China for the summer of 2015 was generated using time-series Landsat-8 imagery and the Best-Available-Pixel (BAP) compositing algorithm. Then, the first 30-merters FUI water color product of China was developed using the generated BAP composite and the Google Earth Engine computing platform. The first 30-meters FUI water color product can promote the understanding of the water color of water bodies in China, and provide very important information for preserving and restoring inland water quality.
DOI: 10.5281/zenodo.4280870
title: FUI Water Color product of inland waters in China at 30-m in 2015

description: The first 30-meters FUI water color product of China. The product was developed using time-series Landsat 8 imagery and FUI water color retrieval method. Taking into account the huge amount of computational and storage space required for the national-scale water color mapping, the high-performance Google Earth Engine (GEE) cloud-based platform was introduced to support the computation. First, a cloud-free composite in China for the summer of 2015 was generated using time-series Landsat-8 imagery and the Best-Available-Pixel (BAP) compositing algorithm. Then, the first 30-merters FUI water color product of China was developed using the generated BAP composite and the Google Earth Engine computing platform. The first 30-meters FUI water color product can promote the understanding of the water color of water bodies in China, and provide very important information for preserving and restoring inland water quality.
DOI: 10.5281/zenodo.4279318
title: GLC_FCS30-2020:Global Land Cover with Fine Classification System at 30m in 2020

description: The new GLC_FCS30-2020 products were produced based on Global 30-m land-cover product with fine classification system in 2015 (GLC_FCS30-2015) and combined with the 2019-2020 time series Landsat surface reflectance data, Sentinel-1 SAR data, DEM terrain elevation data, global thematic auxiliary dataset and prior knowledge dataset.
DOI: 10.48372/5t7q-0x08
title: A new approach to assessing the space use behaviour of macroinvertebrates by automated video tracking
DOI: 10.5281/zenodo.4280358
title: FUI Water Color product of inland waters in China at 30-m in 2015

description: The first 30-meters FUI water color product of China. The product was developed using time-series Landsat 8 imagery and FUI water color retrieval method. Taking into account the huge amount of computational and storage space required for the national-scale water color mapping, the high-performance Google Earth Engine (GEE) cloud-based platform was introduced to support the computation. First, a cloud-free composite in China for the summer of 2015 was generated using time-series Landsat-8 imagery and the Best-Available-Pixel (BAP) compositing algorithm. Then, the first 30-merters FUI water color product of China was developed using the generated BAP composite and the Google Earth Engine computing platform. The first 30-meters FUI water color product can promote the understanding of the water color of water bodies in China, and provide very important information for preserving and restoring inland water quality. The details of the product is described in "FUI_WaterColor_2015China_Readme_V1.1.docx".
description: There is some wrong in the Version 1.0. Please use the datasource from this version (V1.1).
DOI: 10.5281/zenodo.4277390
title: FUI Water Color product of inland waters in China at 30-m in 2015

description: The first 30-meters FUI water color product of China. The product was developed using time-series Landsat 8 imagery and FUI water color retrieval method. Taking into account the huge amount of computational and storage space required for the national-scale water color mapping, the high-performance Google Earth Engine (GEE) cloud-based platform was introduced to support the computation. First, a cloud-free composite in China for the summer of 2015 was generated using time-series Landsat-8 imagery and the Best-Available-Pixel (BAP) compositing algorithm. Then, the first 30-merters FUI water color product of China was developed using the generated BAP composite and the Google Earth Engine computing platform. The first 30-meters FUI water color product can promote the understanding of the water color of water bodies in China, and provide very important information for preserving and restoring inland water quality. The details of the product is described in "FUI_WaterColor_2015China_Readme_V1.1.docx".
description: There is some wrong in the Version 1.0. Please use the datasource from this version (V1.1).
DOI: 10.5281/zenodo.4275053
title: An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3

description: Physical processes within geoscientific models are sometimes described by simplified schemes known as parameterisations. The values of the parameters within these schemes can be poorly constrained by theory or observation. Uncertainty in the parameter values translates into uncertainty in the outputs of the models. Proper quantification of the uncertainty in model predictions therefore requires a systematic approach for sampling parameter space. In this study, we develop a simple and efficient approach to identify regions of multi-dimensional parameter space that are consistent with observations. Using the Parallel Ice Sheet Model to simulate the present-day state of the Antarctic Ice Sheet, we find that co-dependencies between parameters preclude the identification of a single optimal set of parameter values. Approaches such as large ensemble modelling are therefore required in order to generate model predictions that incorporate proper quantification of the uncertainty arising from the parameterisation of physical processes.
DOI: 10.5281/zenodo.4275052
title: An iterative process for efficient optimisation of parameters in geoscientific models: a demonstration using the Parallel Ice Sheet Model (PISM) version 0.7.3

description: Physical processes within geoscientific models are sometimes described by simplified schemes known as parameterisations. The values of the parameters within these schemes can be poorly constrained by theory or observation. Uncertainty in the parameter values translates into uncertainty in the outputs of the models. Proper quantification of the uncertainty in model predictions therefore requires a systematic approach for sampling parameter space. In this study, we develop a simple and efficient approach to identify regions of multi-dimensional parameter space that are consistent with observations. Using the Parallel Ice Sheet Model to simulate the present-day state of the Antarctic Ice Sheet, we find that co-dependencies between parameters preclude the identification of a single optimal set of parameter values. Approaches such as large ensemble modelling are therefore required in order to generate model predictions that incorporate proper quantification of the uncertainty arising from the parameterisation of physical processes.
DOI: 10.6084/m9.figshare.13259660.v1
title: Journal Evaluation.odt

description: This document focusses on evaluation of Journals.
DOI: 10.6084/m9.figshare.13259660
title: Journal Evaluation.odt

description: This document focusses on evaluation of Journals.
DOI: 10.24378/exe.2863
title: Microfluidic devices powered by integrated elasto-magnetic pumps (dataset)

description: This is the dataset used for the Binsley et al. (2020) article "Microfluidic devices powered by elasto-magnetic pumps" published in Lab on a Chip.
description: Microfluidic devices powered by elasto-magnetic pumps dataset. The data is stored in text files and is analysed with the included matlab scripts.
description: The article associated with this dataset is located in ORE at: http://hdl.handle.net/10871/123389
DOI: 10.1285/i22390359v38p1
title: Frontespizio
DOI: 10.5281/zenodo.4280950
title: AI-related patents (WIPO, category G06N) and market capitalisation by companies registering at least 2 new ones in 2019, sorted into four global regions (China, USA, EEA, rest of the world)

description: Datasets and presentations concerning the strength of the EU and "the rest of the world" relative to China and the USA, for the purpose of illustrating and counteracting / better informing narratives concerning a "new AI cold war". The materials authored by us may be freely used under the terms of the MIT License, which appears in its entirety in both the dataset and the presentation. The other materials are only curated by us, taken from Twitter as examples of misinformation pertaining to this concern. Authors: The original analysis was conducted primarily by Malikova in collaboration with Bryson. An associated publication is anticipated where Bryson is the lead author. Contributors: independently followed Malikova's procedures to check her work. Inconsistencies were triple checked and resolved.
description: A linked project contains embargoed versions of screen shots evidencing some numbers appearing in the dataset which are not publicly available.
DOI: 10.1285/i22390359v38p5
title: Table of Contents
DOI: 10.1285/i22390359v38p9
title: Introduction. ELF in specialized domains of intercultural communication
DOI: 10.6084/m9.figshare.12756914.v1
title: Additional file 23 of Integrating GWAS, linkage mapping and gene expression analyses reveals the genetic control of growth period traits in rapeseed (Brassica napus L.)

description: Additional file 23: Table S13. The common QTLs detected by both GWAS and linkage mapping.
DOI: 10.25582/data.2023-01.2709110/2298144
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.12756899
title: Additional file 19 of Integrating GWAS, linkage mapping and gene expression analyses reveals the genetic control of growth period traits in rapeseed (Brassica napus L.)

description: Additional file 19: Table S11. List of flowering time genes in B. napus from our RNA-sequencing data using Arabidopsis flowering genes as queries.
DOI: 10.25582/data.2023-01.2709907/2298145
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710618/2298146
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.12756905.v1
title: Additional file 20 of Integrating GWAS, linkage mapping and gene expression analyses reveals the genetic control of growth period traits in rapeseed (Brassica napus L.)

description: Additional file 20: Table S12. The detailed information of different haplotypes detected in seven candidate genes.
DOI: 10.6084/m9.figshare.12756974.v1
title: Additional file 11 of SMRT and Illumina RNA sequencing reveal novel insights into the heat stress response and crosstalk with leaf senescence in tall fescue

description: Additional file 11 The differential expression of Hsfs in each comparison.
DOI: 10.6084/m9.figshare.12756977
title: Additional file 12 of SMRT and Illumina RNA sequencing reveal novel insights into the heat stress response and crosstalk with leaf senescence in tall fescue

description: Additional file 12. The differential expression of NAC transcription factors in each comparison.
DOI: 10.25582/data.2023-02.2732319/2298147
title: Data for EMSL Project 51287 from February 2023
DOI: 10.6084/m9.figshare.12756983.v1
title: Additional file 14 of SMRT and Illumina RNA sequencing reveal novel insights into the heat stress response and crosstalk with leaf senescence in tall fescue

description: Additional file 14. All primers used in this study.
DOI: 10.6084/m9.figshare.12756902.v1
title: Additional file 1 of Integrating GWAS, linkage mapping and gene expression analyses reveals the genetic control of growth period traits in rapeseed (Brassica napus L.)

description: Additional file 1: Table S1. ANOVA analysis of five growth period traits in GWAS(a) and linkage mapping(b).
DOI: 10.25582/data.2023-01.2708981/2298148
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709631/2298149
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710897/2298150
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711081/2298151
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2705484/2298152
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2705773/2298153
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2707488/2298154
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2733290/2298155
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2711216/2298156
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710544/2298157
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710499/2298158
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708623/2298159
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710875/2298160
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2733341/2298161
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2710782/2298162
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710926/2298163
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2732391/2298164
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2708651/2298165
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708715/2298166
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709832/2298167
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711126/2298168
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706120/2298169
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709788/2298170
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2706670/2298171
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2707491/2298172
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2733338/2298173
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2706423/2298174
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708825/2298175
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.14329504.v1
title: Additional file 1 of Clinical characteristics and sociodemographic features of psychotic major depression

description: Additional file 1. Data
DOI: 10.25582/data.2023-01.2716489/2298176
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.12756992
title: Additional file 3 of SMRT and Illumina RNA sequencing reveal novel insights into the heat stress response and crosstalk with leaf senescence in tall fescue

description: Additional file 3. The differential expression of DEGs in comparison V4.
DOI: 10.25582/data.2023-02.2732571/2298177
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2711322/2298178
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.12756992.v1
title: Additional file 3 of SMRT and Illumina RNA sequencing reveal novel insights into the heat stress response and crosstalk with leaf senescence in tall fescue

description: Additional file 3. The differential expression of DEGs in comparison V4.
DOI: 10.25582/data.2023-01.2711352/2298179
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.19571987.v1
title: Additional file 4 of Mapping the distributions of blood-sucking mites and mite-borne agents in China: a modeling study

description: Additional file 4. The number of mite species recorded in each county and seven biogeographic regions in China.
DOI: 10.6084/m9.figshare.19571990
title: Additional file 5 of Mapping the distributions of blood-sucking mites and mite-borne agents in China: a modeling study

description: Additional file 5. The code of BRT model.
DOI: 10.25582/data.2023-01.2710001/2298180
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.19571990.v1
title: Additional file 5 of Mapping the distributions of blood-sucking mites and mite-borne agents in China: a modeling study

description: Additional file 5. The code of BRT model.
DOI: 10.25582/data.2023-01.2708357/2298181
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2708894/2298182
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710143/2298183
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2711098/2298184
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-02.2733083/2298185
title: Data for EMSL Project 51287 from February 2023
DOI: 10.25582/data.2023-01.2710793/2298186
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709475/2298187
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2710470/2298188
title: Data for EMSL Project 51287 from January 2023
DOI: 10.25582/data.2023-01.2709691/2298189
title: Data for EMSL Project 51287 from January 2023
DOI: 10.6084/m9.figshare.12756947.v1
title: Additional file 9 of Integrating GWAS, linkage mapping and gene expression analyses reveals the genetic control of growth period traits in rapeseed (Brassica napus L.)

description: Additional file 9: Table S5. QTLs detected for five growth period traits in GH06 × P174 RIL population.