cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4660858
title: ChinaHighPM2.5 (Version 3)

description: ChinaHighPM<sub>2.5</sub> is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from MODIS/Terra+Aqua MAIAC AOD products together with other auxiliary data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. This is the MODIS/Terra+Aqua Level 3 (L3) yearly 0.01 degree (≈ 1 km) gridded ground-level PM<sub>2.5</sub> products in Eastern China (ECHAP_PM2.5_Y1K) from 2000 to 2020, which are averaged from the Level 2 daily products. Note that the data for the year 2000 is averaged from March 2000 to December 2000. The annual PM<sub>2.5</sub> estimates are highly related to ground-based measurements (R<sup>2</sup> = 0.94) with an average root-mean-square error (RMSE) of 5.07 µg m<sup>-3</sup>. <strong>Note that this dataset is closed since a new version is published at </strong>10.5281/zenodo.3539349.
description: CHAP website: https://weijing-rs.github.io/product.html
description: {"references": ["Wei, J., Li, Z., Lyapustin, A., Sun, L., Peng, Y., Xue, W., Su, T., and Cribb, M. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications. Remote Sensing of Environment, 2021, 252, 112136. https://doi.org/10.1016/j.rse.2020.112136", "Wei, J., Li, Z., Cribb, M., Huang, W., Xue, W., Sun, L., Guo, J., Peng, Y., Li, J., Lyapustin, A., Liu, L., Wu, H., and Song, Y. Improved 1 km resolution PM2.5 estimates across China using enhanced space-time extremely randomized trees, Atmospheric Chemistry and Physics, 2020, 20(6), 3273-3289. https://doi.org/10.5194/acp-20-3273-2020"]}
DOI: 10.5281/zenodo.6398971
title: ChinaHighPM₂.₅: Daily Seamless 1 km Ground-Level PM₂.₅ Dataset for China (2000–Present)

description: ChinaHighPM2.5 is part of a series of long-term, seamless, high-resolution, and high-quality datasets of air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution.

Here is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level PM2.5 dataset for China from 2000 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.92, a root-mean-square error (RMSE) of 10.76 µg m-3, and a mean absolute error (MAE) of 6.32 µg m-3 on a daily basis.

If you use the ChinaHighPM2.5 dataset in your scientific research, please cite the following references (Wei et al., RSE, 2021; Wei et al., ACP, 2020):





Wei, J., Li, Z., Lyapustin, A., Sun, L., Peng, Y., Xue, W., Su, T., and Cribb, M. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications. Remote Sensing of Environment, 2021, 252, 112136. https://doi.org/10.1016/j.rse.2020.112136




Wei, J., Li, Z., Cribb, M., Huang, W., Xue, W., Sun, L., Guo, J., Peng, Y., Li, J., Lyapustin, A., Liu, L., Wu, H., and Song, Y. Improved 1 km resolution PM2.5 estimates across China using enhanced space-time extremely randomized trees. Atmospheric Chemistry and Physics, 2020, 20(6), 3273–3289. https://doi.org/10.5194/acp-20-3273-2020



The data is continuously updated, and

        all (including daily) data for the year 2022 is accessible at: ChinaHighPM2.5 (2022)

        all (including daily) data for the year 2023 is accessible at: ChinaHighPM2.5 (2023)

        all (including daily) data for the year 2024 is accessible at: ChinaHighPM2.5 (2024)

        more data is coming soon...

More CHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html
description: Note that the data are recorded in local time (i.e., Beijing time: GMT+8).

This dataset is continuously updated. If you require additional data for related scientific research, please contact us (weijing_rs@163.com or weijing.rs@gmail.com).
DOI: 10.6084/m9.figshare.29133520
title: Additional file 1 of Patient characteristics and pharmacologic treatment patterns in antifibrotic-treated patients with fibrosing interstitial lung diseases: real-world results from a claims database

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.29133520.v1
title: Additional file 1 of Patient characteristics and pharmacologic treatment patterns in antifibrotic-treated patients with fibrosing interstitial lung diseases: real-world results from a claims database

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.29133530
title: Additional file 3 of Characteristics of folic acid metabolism-related genes unveil prognosis and treatment strategy in lung adenocarcinoma

description: Supplementary Material 3: Supplementary Table 1. Univariate Cox regression analysis and K-M analysis of 25 DEGs.
DOI: 10.6084/m9.figshare.29133530.v1
title: Additional file 3 of Characteristics of folic acid metabolism-related genes unveil prognosis and treatment strategy in lung adenocarcinoma

description: Supplementary Material 3: Supplementary Table 1. Univariate Cox regression analysis and K-M analysis of 25 DEGs.
DOI: 10.6084/m9.figshare.29133541
title: Additional file 1 of Meiosis-associated expression patterns during starvation-induced cell fusion in the protist Fisculla terrestris

description: Additional file 1: Table S1 DESeq2 expression level of the 41 DEGs showed the raw expression.
DOI: 10.6084/m9.figshare.29133541.v1
title: Additional file 1 of Meiosis-associated expression patterns during starvation-induced cell fusion in the protist Fisculla terrestris

description: Additional file 1: Table S1 DESeq2 expression level of the 41 DEGs showed the raw expression.
DOI: 10.6084/m9.figshare.29133553.v1
title: Additional file 1 of Design and analysis of binaural signal matching with arbitrary microphone arrays and listener head rotations

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.29133553
title: Additional file 1 of Design and analysis of binaural signal matching with arbitrary microphone arrays and listener head rotations

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.6847970
title: Additional file 2 of Functional and genomic analyses reveal therapeutic potential of targeting β-catenin/CBP activity in head and neck cancer

description: Tabular spreadsheet file containing both table of differential gene expression results comparing ICG-001 treatment (n = 3) versus DMSO (vehicle) control (n = 3) in HSC-3 and CAL27 OSCC cell lines, as well as the ICG-001 treatment gene expression signatures derived thereof (see manuscript “Methods”). (XLSX 4246 kb)
DOI: 10.6084/m9.figshare.6847970.v2
title: Additional file 2 of Functional and genomic analyses reveal therapeutic potential of targeting β-catenin/CBP activity in head and neck cancer

description: Tabular spreadsheet file containing both table of differential gene expression results comparing ICG-001 treatment (n = 3) versus DMSO (vehicle) control (n = 3) in HSC-3 and CAL27 OSCC cell lines, as well as the ICG-001 treatment gene expression signatures derived thereof (see manuscript “Methods”). (XLSX 4246 kb)
DOI: 10.6084/m9.figshare.6847988
title: Additional file 3 of Functional and genomic analyses reveal therapeutic potential of targeting β-catenin/CBP activity in head and neck cancer

description: Tabular ranked gene list file (viewable in Excel) pertaining to differential gene expression testing comparing siRNA-mediated knockdown of β-catenin versus scrambled siRNA control in HSC-3 cells used for GSEA. Fields indicate gene symbol and t test statistic of differential expression, respectively, used as input to the pre-ranked GSEA tool. (TXT 289 kb)
DOI: 10.6084/m9.figshare.6847988.v2
title: Additional file 3 of Functional and genomic analyses reveal therapeutic potential of targeting β-catenin/CBP activity in head and neck cancer

description: Tabular ranked gene list file (viewable in Excel) pertaining to differential gene expression testing comparing siRNA-mediated knockdown of β-catenin versus scrambled siRNA control in HSC-3 cells used for GSEA. Fields indicate gene symbol and t test statistic of differential expression, respectively, used as input to the pre-ranked GSEA tool. (TXT 289 kb)
DOI: 10.6084/m9.figshare.6847970.v1
title: Additional file 2: of Functional and genomic analyses reveal therapeutic potential of targeting β-catenin/CBP activity in head and neck cancer

description: Tabular spreadsheet file containing both table of differential gene expression results comparing ICG-001 treatment (n = 3) versus DMSO (vehicle) control (n = 3) in HSC-3 and CAL27 OSCC cell lines, as well as the ICG-001 treatment gene expression signatures derived thereof (see manuscript “Methods”). (XLSX 4246 kb)
DOI: 10.6084/m9.figshare.6847988.v1
title: Additional file 3: of Functional and genomic analyses reveal therapeutic potential of targeting β-catenin/CBP activity in head and neck cancer

description: Tabular ranked gene list file (viewable in Excel) pertaining to differential gene expression testing comparing siRNA-mediated knockdown of β-catenin versus scrambled siRNA control in HSC-3 cells used for GSEA. Fields indicate gene symbol and t test statistic of differential expression, respectively, used as input to the pre-ranked GSEA tool. (TXT 289 kb)
DOI: 10.6084/m9.figshare.29133601
title: Additional file 3 of The first complete genome of Fructilactobacillus vespulae: strain Mu01, isolated from nectar of Musa paradisiaca L.

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.29133601.v1
title: Additional file 3 of The first complete genome of Fructilactobacillus vespulae: strain Mu01, isolated from nectar of Musa paradisiaca L.

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.29133604
title: Additional file 4 of The first complete genome of Fructilactobacillus vespulae: strain Mu01, isolated from nectar of Musa paradisiaca L.

description: Supplementary Material 4.
DOI: 10.6084/m9.figshare.29133604.v1
title: Additional file 4 of The first complete genome of Fructilactobacillus vespulae: strain Mu01, isolated from nectar of Musa paradisiaca L.

description: Supplementary Material 4.
DOI: 10.6084/m9.figshare.29133634
title: Additional file 1 of Integrated omics reveal the mechanisms underlying softening and aroma changes in pear during postharvest storage and the role of melatonin

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.29133634.v1
title: Additional file 1 of Integrated omics reveal the mechanisms underlying softening and aroma changes in pear during postharvest storage and the role of melatonin

description: Supplementary Material 1.
DOI: 10.15468/dl.5yr3q3
title: Occurrence Download

description: A dataset containing 11523 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudemoia Fuhn, 1967",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "Year is greater than or equal to 1975"
 ]
}

 The dataset includes 11523 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015129-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29133649
title: Additional file 2 of Metabolomic biomarkers in vitreous humor: unveiling the molecular landscape of diabetic retinopathy progression

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.29133649.v1
title: Additional file 2 of Metabolomic biomarkers in vitreous humor: unveiling the molecular landscape of diabetic retinopathy progression

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.29133665
title: Additional file 2 of The Effect of Probiotic Supplementation on Cytokine Modulation in Athletes After a Bout of Exercise: A Systematic Review and Meta-Analysis

description: Supplementary Material 2.
DOI: 10.6084/m9.figshare.29133665.v1
title: Additional file 2 of The Effect of Probiotic Supplementation on Cytokine Modulation in Athletes After a Bout of Exercise: A Systematic Review and Meta-Analysis

description: Supplementary Material 2.
DOI: 10.6084/m9.figshare.29133667
title: Additional file 3 of Enhanced serum-based seed amplification assay for detecting propagative α-synuclein seeds in Parkinson’s disease

description: Additional file 3. Table S1. Identification of proteins in the &gt;100 kDa fraction of human serum by liquid chromatography-mass spectrometry.
DOI: 10.6084/m9.figshare.29133667.v1
title: Additional file 3 of Enhanced serum-based seed amplification assay for detecting propagative α-synuclein seeds in Parkinson’s disease

description: Additional file 3. Table S1. Identification of proteins in the &gt;100 kDa fraction of human serum by liquid chromatography-mass spectrometry.
DOI: 10.6084/m9.figshare.29133431
title: LFP-defined RF remapping

description: LFP-defined RF remapping
DOI: 10.5281/zenodo.10477126
title: ChinaHighO3: Big Data Seamless 1 km Ground-level MDA8 O3 Dataset for China

description: ChinaHighO3 is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from the big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. 

This is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D10K, M10K, and Y10K) ground-level maximum 8-hour average (MDA8) O3 dataset in China from 2000 to present. This dataset yields a high quality with a cross-validation coefficient of determination (CV-R2) of 0.89, a root-mean-square error (RMSE) of 15.77 µg m-3, and a mean absolute error (MAE) of 10.48 µg m-3 on a daily basis.

If you use the ChinaHighO3 dataset for related scientific research, please cite the corresponding reference (Wei et al., RSE, 2022; He et al., 2022) first, and the reference will be updated once our new paper is accepted:





Wei, J., Li, Z., Li, K., Dickerson, R., Pinker, R., Wang, J., Liu, X., Sun, L., Xue, W., and Cribb, M. Full-coverage mapping and spatiotemporal variations of ground-level ozone (O3) pollution from 2013 to 2020 across China. Remote Sensing of Environment, 2022, 270, 112775. https://doi.org/10.1016/j.rse.2021.112775




He, L., Wei, J., Wang, Y., Shang, Q., Liu, J., Yin, Y., Frankerberg, C., Jiang, J., Li, Z., and Yung, Y. Marked impacts of pollution mitigation on crop yields in China. Earth's Future, 2022, 10, e2022EF002936. https://doi.org/10.1029/2022EF002936



More CHAP datasets of different air pollutants can be found at: https://weijing-rs.github.io/product.html
description: Note that the data are recorded in local time (i.e., Beijing time: GMT+8), and measured at the standard condition (i.e., 273 K and 1013 hPa). The concentrations can be converted to the room condition (i.e., 298 K and 1013 hPa) by dividing by a factor of 1.09375 (MEE, 2018).

This dataset is continuously updated, and if you want to apply for more data or have any questions, please contact me (Email: weijing_rs@163.com; weijing@umd.edu).
DOI: 10.5281/zenodo.10208187
title: GlobalHighO₃: Global Daily Seamless 10 km Ground-Level O₃ Dataset over Land (2000–Present)

description: GlobalHighO3 is part of a series of long-term, seamless, global, high-resolution, and high-quality datasets of air pollutants over land (i.e., GlobalHighAirPollutants, GHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution.

Here is the first big data-derived gapless (spatial coverage = 100%) daily, monthly, and yearly 10 km (i.e., D10K, M10K, and Y10K) global ground-level maximum daily 8-hour average (MDA8) O3 dataset over land from 2000 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.86 and a root-mean-square error (RMSE) of 6.25 ppb on a daily basis.

More GHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html
description: Note that the data are recorded in UTC time (i.e., GMT+0), and all data will be made publicly available online once our paper is accepted.

This dataset is continuously updated. If you require additional data for related scientific research, please contact us (weijing_rs@163.com or weijing.rs@gmail.com).
DOI: 10.5281/zenodo.10208188
title: GlobalHighO₃: Global Daily Seamless 10 km Ground-Level O₃ Dataset over Land (2000–Present)

description: GlobalHighO3 is part of a series of long-term, seamless, global, high-resolution, and high-quality datasets of air pollutants over land (i.e., GlobalHighAirPollutants, GHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution.

Here is the first big data-derived gapless (spatial coverage = 100%) daily, monthly, and yearly 10 km (i.e., D10K, M10K, and Y10K) global ground-level maximum daily 8-hour average (MDA8) O3 dataset over land from 2000 to the present. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R2) of 0.86 and a root-mean-square error (RMSE) of 6.25 ppb on a daily basis.

More GHAP datasets for different air pollutants are available at: https://weijing-rs.github.io/product.html
description: Note that the data are recorded in UTC time (i.e., GMT+0), and all data will be made publicly available online once our paper is accepted.

This dataset is continuously updated. If you require additional data for related scientific research, please contact us (weijing_rs@163.com or weijing.rs@gmail.com).
DOI: 10.15468/dl.pzh87j
title: Occurrence Download

description: A dataset listing the 1421 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation)",
 "Continent is North America",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia",
 "Year 2020-2025"
 ]
}

 The dataset's 1421 records were derived from 179 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015132-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qshhy7
title: Occurrence Download

description: A dataset containing 47 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Craigia yunnanensis W.W.Sm. & W.E.Evans"
 ]
}

 The dataset includes 47 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015133-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2dahds
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "GadmGid is one of (USA.10_1, USA.11_1, USA.41_1, USA.1_1, USA.34_1, USA.25_1, USA.43_1)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ribes echinellum (Coville) Rehder",
 "Year 1980-2025"
 ]
}

 The dataset includes 96 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015130-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7jravm
title: Occurrence Download

description: A dataset containing 1158 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Terminalia sericea Burch. ex DC.",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Occurrence evidence)"
 ]
}

 The dataset includes 1158 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015134-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15493047
title: FormulationMM: a universal computer-driven drug formulation platform

description: a dataset for the case study in FormulationMM including input file, trajectory, results
DOI: 10.34740/kaggle/dsv/11916413
title: Layline Shareholder activism dataset
DOI: 10.1594/pangaea.975980
title: Coarse fraction of sediment core PS115/2_2

description: Sediment Core PS115/2-2 was recovered from the Amundsen Basin in 3600 m water depth at the eastern flank of the Gakkel Ridge during Polarstern Expedition PS115/2 in 2018 (Stein, 2019). The well-dated core is used to reconstruct in detail the interrelationship between ice-sheet dynamics and organic carbon burial in the central Eurasian Basin during the last 430 kyr, and to correlate marine and terrestrial records of the Eurasian Ice Sheet (EIS) history. For separation of the coarse fraction, large-sized samples of about 100 ml volume were taken every 5 cm, freeze-dried, weighed, and then sieved using a 63 µm sieve. The fraction &gt;63 µm has been used for qualitative coarse-fraction analysis (e.g., determination of occurrences of foraminifers, coal fragments, detrital minerals etc.). For details and methods, we refer to Stein et al. (this paper).
DOI: 10.6084/m9.figshare.29133182
title: <b>Supplementary material S</b><b>3</b>

description: <b>Molecular Insight into RACGAP1-Mediated Cell Cycle Arrest</b>The expression levels of CDK4, CDK6, cyclin D1, p21, and p27were examined to clarify whether RACGAP1 influences the cell cycle through CDK-cyclin activation or checkpoint regulation. Using Western blot, we systematically analyzed the expression changes of these key molecules following RACGAP1 knockdown.