cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24064530
title: Global aboveground and belowground Net Primary Productivity grids with 0.05° resolution from 1981 to 2018 using the Deep Learning model

description: Net primary productivity (NPP) in global ecosystems is a critical component of terrestrial carbon cycling and an essential indicator of ecosystem carbon sequestration capacity. However, the size and spatial patterns of NPP across global ecosystems remain uncertain, particularly for the divided estimation of above- and below-ground net primary productivity (ANPP and BNPP), which limits our understanding of global NPP carbon cycling and the sustainability of carbon sequestration. Here, an updated database was compiled with 5,184 filed observations to estimate the spatial patterns of ANPP and BNPP using a modified multilayer perceptron neural network (MLP) method. Based on the 10-fold cross-validation,<i> </i>the model performance<i> </i>of ANPP and BNPP were 0.74 (<i>R</i><sup><em>2</em></sup><i>, RMSE</i>: 138.37 g C m<sup>-2</sup> yr<sup>-1</sup>) and 0.73 (<i>R</i><sup><em>2</em></sup><i>, RMSE</i>: 76.33 g C m<sup>-2</sup> yr<sup>-1</sup>), respectively. The total ANPP and BNPP were 33.4 ± 0.5 and 19.2 ± 0.73 Pg C yr<sup>-1</sup>, respectively. ANPP and BNPP exhibited decreasing trends from low latitudes toward the poles. Over the last 38 years, global 65.38% and 60.83% areas of the ANPP and BNPP showed a growth trend, and annual total ANPP and BNPP were significant positive growth trends (<i>p</i> &lt; 0.01), about 0.02 and 0.05 Pg C yr<sup>-1</sup>, respectively. Our findings suggest that field data-driven prediction of NPP using the MLP model could be a useful approach for obtaining spatially explicit NPP of ecosystems, particularly BNPP. This study contributes to the understanding of the dynamics of terrestrial carbon sequestration in the context of global change and may provide a new method and basis for making climate change response proposals.Filename: ANPP_MLP_1981_2018_0.05.zip; BNPP_MLP_1981_2018_0.05.zipFile information：‘ANPP_MLP_1981_2018_0.05.zip’ is the predicted global ANPP grid with 0.05° spatial resolution from 1981 to 2018; ‘BNPP_MLP_1981_2018_0.05.zip’ is the predicted global BNPP grid with 0.05° spatial resolution from 1981 to 2018. The unit for these data is 'g C m<sup>-2</sup><sup> </sup>a<sup>-1</sup>'. Besides, both zip files contain 38 grid images, and each grid image is named according to the following convention: 'data type' _ 'model type' _ 'year' _ 'spatial resolution'.tif. For example, the ANPP data for the year 1981 would be named:' ANPP_MLP_1981_0.05.tif'.<b>Corresponding author</b>: Xiaolu Tang (lxtt2010@163.com)
DOI: 10.5281/zenodo.8304793
title: Digitalized data for the transient creep of quartz and granulite at high temperature under wet conditions

description: This repository contains the digitalized data from the following original publications and also intermediate results for our manuscript. 1) Gleason, G. C., & Tullis, J. (1995). A flow law for dislocation creep of quartz aggregates determined with the molten salt cell. Tectonophysics, 247(1-4), 1–23. 2) Zhou, Y., Zhang, H., Yao, W., Dang, J., & He, C. (2017). An experimental study on creep of partially molten granulite under high temperature and wet conditions. Journal of Asian Earth Sciences, 139, 15–29.
DOI: 10.5281/zenodo.8304792
title: Digitalized data for the transient creep of quartz and granulite at high temperature under wet conditions

description: This repository contains the digitalized data from the following original publications and also intermediate results for our manuscript. 1) Gleason, G. C., & Tullis, J. (1995). A flow law for dislocation creep of quartz aggregates determined with the molten salt cell. Tectonophysics, 247(1-4), 1–23. 2) Zhou, Y., Zhang, H., Yao, W., Dang, J., & He, C. (2017). An experimental study on creep of partially molten granulite under high temperature and wet conditions. Journal of Asian Earth Sciences, 139, 15–29.
DOI: 10.5281/zenodo.8297064
title: TBT exposure dataset of the manuscript "Assessment of endocrine disruptors effects on zebrafish (Danio rerio) embryos by untargeted LC-HRMS metabolomic analysis"

description: <strong>Raw LC-HRMS data of the TBT exposure of zebrafish embryos (for more details see https://doi.org/10.1016/j.scitotenv.2018.03.369)</strong> The exposure protocol involved zebrafish embryos exposed in groups of 20 to various concentrations of chemical compounds, with five replicates per treatment. The concentrations ranged from the lowest observed effect concentrations (LOECs) to control levels. After exposure, embryos were collected, washed, frozen, and stored. Metabolites were extracted from individual embryo pools using methanol and methionine sulfone. The extraction process included vortexing, sonication, and centrifugation, followed by addition of water and chloroform. The aqueous fraction was dried and reconstituted using acetonitrile-water solution. Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) was used for analysis. Chromatographic separations were carried out on a hydrophilic interaction liquid chromatography (HILIC) column. Mass spectrometry was performed using an Orbitrap mass spectrometer with electrospray ionization in positive and negative modes. The mass spectra were acquired at high resolution, and fragmentation scans were used for metabolite identification. The overall process aimed to analyze the metabolomic profile of zebrafish embryos exposed to different chemical concentrations. <strong>Data files</strong> TBT ESI+ (tbt_pos.rar) - CDF files - QC (4 replicates) - Control (5 replicates) - TBT 3 nM (5 replicates) - TBT 10 nM (5 replicates) - TBT 30 nM (5 replicates) - TBT 100 nM (5 replicates) TBT ESI- (tbt_neg.rar) - CDF files - QC (6 replicates) - Control (5 replicates) - TBT 3 nM (5 replicates) - TBT 10 nM (5 replicates) - TBT 30 nM (5 replicates) - TBT 100 nM (5 replicates)
DOI: 10.5281/zenodo.8297063
title: TBT exposure dataset of the manuscript "Assessment of endocrine disruptors effects on zebrafish (Danio rerio) embryos by untargeted LC-HRMS metabolomic analysis"

description: <strong>Raw LC-HRMS data of the TBT exposure of zebrafish embryos (for more details see https://doi.org/10.1016/j.scitotenv.2018.03.369)</strong> The exposure protocol involved zebrafish embryos exposed in groups of 20 to various concentrations of chemical compounds, with five replicates per treatment. The concentrations ranged from the lowest observed effect concentrations (LOECs) to control levels. After exposure, embryos were collected, washed, frozen, and stored. Metabolites were extracted from individual embryo pools using methanol and methionine sulfone. The extraction process included vortexing, sonication, and centrifugation, followed by addition of water and chloroform. The aqueous fraction was dried and reconstituted using acetonitrile-water solution. Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) was used for analysis. Chromatographic separations were carried out on a hydrophilic interaction liquid chromatography (HILIC) column. Mass spectrometry was performed using an Orbitrap mass spectrometer with electrospray ionization in positive and negative modes. The mass spectra were acquired at high resolution, and fragmentation scans were used for metabolite identification. The overall process aimed to analyze the metabolomic profile of zebrafish embryos exposed to different chemical concentrations. <strong>Data files</strong> TBT ESI+ (tbt_pos.rar) - CDF files - QC (4 replicates) - Control (5 replicates) - TBT 3 nM (5 replicates) - TBT 10 nM (5 replicates) - TBT 30 nM (5 replicates) - TBT 100 nM (5 replicates) TBT ESI- (tbt_neg.rar) - CDF files - QC (6 replicates) - Control (5 replicates) - TBT 3 nM (5 replicates) - TBT 10 nM (5 replicates) - TBT 30 nM (5 replicates) - TBT 100 nM (5 replicates)
DOI: 10.6084/m9.figshare.24064683.v1
title: Arthropod dataset for plantation clear-fell patches

description: The dataset contains and species identified from pitfall trapping in heathland and plantation plots in 2009, together with their abundance in each habitat, species status in the UK (S41=Section 41 priority species, NT=Near Threatened, NR=Nationally Rare, NS=Nationally Scarce) and habitat association.
DOI: 10.6084/m9.figshare.24064683
title: Arthropod dataset for plantation clear-fell patches

description: The dataset contains and species identified from pitfall trapping in heathland and plantation plots in 2009, together with their abundance in each habitat, species status in the UK (S41=Section 41 priority species, NT=Near Threatened, NR=Nationally Rare, NS=Nationally Scarce) and habitat association.
DOI: 10.5258/soton/d2760
title: Dataset supporting the University of Southampton Doctoral thesis "Self-states, attachment and dissociation: relationships and measurement".

description: Dataset supporting the University of Southampton Doctoral thesis "Self-states, attachment and dissociation: relationships and measurement" by Clarissa Lord. This data includes an excel file of collected data created by the author as part of their research.
DOI: 10.18419/darus-3370/1
title: Supporting Information.pdf

description: supporting data
DOI: 10.18419/darus-3370/2
title: 20220209_102057441_Kat_THF_KE100EQ_RT_mod0.2_01_tmp_20C.xml

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title: 20220209_105321931_Kat_THF_KE400EQ_RT_mod0.2_tmp_20C.xml

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title: 20220209_093428489_Kat_THF_KE1EQ_150K_0.2.T_mod_tmp_-123C.xml

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title: 20220209_093308051_Kat_THF_KE1EQ_150K_tmp_-123C.xml

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title: 20220209_141626150_Kat_THF_Product1EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_104338640_Kat_THF_KE200EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_112200128_Kat_KE_KE1000EQ_313K_mod0.2_01.xml

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title: 20220209_144341747_Kat_THF_HFIP100EQ_RT_mod0.2_tmp_20C.xml

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title: 20220209_092749735_Kat_THF_KE1EQ_RT_tmp_20C.xml

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title: 20220209_090935631_Kat_THF_RT_tmp_20C.xml

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title: 20220209_132558073_Kat_THF_MI200EQ_150K_mod0.5_01.xml

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title: 20220209_101131457_Kat_THF_KE50EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_134708345_Kat_THF_Product100EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_102528300_Kat_THF_KE100EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_110024631_Kat_THF_KE400EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_132337956_Kat_THF_MI200EQ_RT_mod0.2_tmp_20C.xml

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title: 20220209_105545666_Kat_THF_KE400EQ_RT_mod0.4_tmp_20C.xml

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title: 20220209_104450657_Kat_THF_KE200EQ_150K_mod0.2_tmp_-123C.xml

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title: 20220209_103838096_Kat_THF_KE200EQ_RT_mod0.2_tmp_20C.xml

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title: 20220209_135724971_Kat_THF_Product50EQ_RT_mod0.2_tmp_20C.xml

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title: 20220209_111613324_Kat_KE_KE1000EQ_RT_mod0.2_tmp_20C.xml

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DOI: 10.18419/darus-3370/24
title: 20220209_114529086_Kat_THF_150K_mod0.5_tmp_-123C.xml

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DOI: 10.18419/darus-3370/25
title: 20220209_094141483_Kat_THF_KE1EQ_RT_3_tmp_20C.xml

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DOI: 10.18419/darus-3370/26
title: 20220209_094033449_Kat_THF_KE1EQ_RT_2_tmp_20C.xml

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DOI: 10.18419/darus-3370/27
title: 20220209_100613121_Kat_THF_KE50EQ_RT_mod0.2_tmp_20C.xml

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DOI: 10.18419/darus-3370/28
title: 20220209_110303660_Kat_THF_KE400EQ_150K_mod0.2_tmp_-123C.xml

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title: 20220209_134221861_Kat_THF_Product100EQ_RT_mod0.5_tmp_20C.xml

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DOI: 10.18419/darus-3370/30
title: 20220209_112739021_Kat_KE_KE1000EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_140142212_Kat_THF_Product50EQ_150K_mod0.5_tmp_-123C.xml

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title: 20220209_095042168_Kat_THF_KE10EQ_RT_tmp_20C.xml

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DOI: 10.18419/darus-3370/33
title: 20220209_142744888_Kat_THF_HFIP400EQ_RT_mod0.5_tmp_20C.xml

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DOI: 10.18419/darus-3370/34
title: 20220209_113914700_Kat_THF_RT_mod0.2_tmp_20C.xml

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DOI: 10.18419/darus-3370/35
title: 20220209_101957394_Kat_THF_KE100EQ_RT_mod0.2.xml

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DOI: 10.18419/darus-3370/36
title: 20220209_134057001_Kat_THF_Product100EQ_RT_mod0.2_tmp_20C.xml

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DOI: 10.18419/darus-3370/37
title: 20220209_111850635_Kat_KE_KE1000EQ_303K_mod0.2_01.xml

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title: 20220209_091455149_Kat_THF_150K_tmp_-123C.xml

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title: 20220209_143515918_Kat_THF_HFIP400EQ_150_mod0.5_01_tmp_-123C.xml

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title: 20220209_143417794_Kat_THF_HFIP400EQ_150_mod0.5_tmp_-123C.xml

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title: 20220209_141157849_Kat_THF_Product1EQ_RT_mod0.2_tmp_20C.xml

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title: 20220209_114127653_Kat_THF_RT_mod0.5_tmp_20C.xml

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title: 20220209_095520486_Kat_THF_KE10EQ_150K_mod0.5_tmp_-123C.xml

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DOI: 10.18419/darus-3370/45
title: 3jA.cif

description: :unav
DOI: 10.18419/darus-3370/46
title: 3nA.cif

description: :unav
DOI: 10.18419/darus-3370/47
title: checkcif_report_3aC.pdf

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DOI: 10.18419/darus-3370/48
title: checkcif_report_9.pdf

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DOI: 10.18419/darus-3370/49
title: 3gA.cif

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title: 14b.cif

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title: 3iA.cif

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title: checkcif_report_3aA.pdf

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title: checkcif_report_3gA.pdf

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title: checkcif_report_3oA.pdf

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title: checkcif_report_3fA.pdf

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DOI: 10.18419/darus-3370/56
title: 3aC.cif

description: :unav
DOI: 10.18419/darus-3370/57
title: checkcif_report_3iA.pdf

description: :unav
DOI: 10.18419/darus-3370/58
title: checkcif_report_14b.pdf

description: :unav
DOI: 10.18419/darus-3370/59
title: 9.cif

description: :unav
DOI: 10.18419/darus-3370/60
title: S22.cif

description: :unav
DOI: 10.18419/darus-3370/61
title: checkcif_report_3aG.pdf

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DOI: 10.18419/darus-3370/62
title: checkcif_report_S22.pdf

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title: checkcif_report_C3.pdf

description: :unav
DOI: 10.18419/darus-3370/64
title: 3fA.cif

description: :unav
DOI: 10.18419/darus-3370/65
title: checkcif_report_3nA.pdf

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DOI: 10.18419/darus-3370/66
title: 3oA.cif

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title: checkcif_report_3jA.pdf

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title: 3aG.cif

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title: 3aA.cif

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DOI: 10.5281/zenodo.8304875
title: Bibliometric Analysis of Data Mining Techniques in Human Motion Research: Future Directions

description: bibliometric dataset
DOI: 10.5281/zenodo.8304874
title: Bibliometric Analysis of Data Mining Techniques in Human Motion Research: Future Directions

description: bibliometric dataset
DOI: 10.5281/zenodo.8296894
title: One-point Integral and Turbulent wind Characteristics at the FINO1 Platform (2007-2008)

description: <strong>Dataset</strong>: One-point Integral and Turbulent wind Characteristics at the FINO1 Platform (2007-2008) <strong>Authors:</strong> Cheynet, E. <strong>Description:</strong> This dataset offers a comprehensive collection of wind measurements derived from continuous sonic anemometer recordings at the FINO1 offshore platform during the years 2007 and 2008. The measurements were conducted to investigate the properties and characteristics of wind turbulence in the marine atmospheric boundary layer, especially in relation to atmospheric stability. The data provide insights that have potential implications for the design and safety of offshore structures, particularly wind turbines, as they relate to wind loads. The database includes aggregated mean flow data alongside one-point turbulent characteristics. <strong>Tutorial:</strong> https://se.mathworks.com/matlabcentral/fileexchange/134446-offshore-wind-turbulence-characteristics-at-fino1 <strong>Content Overview:</strong> <strong>Format:</strong> Matlab (.mat) files. <strong>Data Duration:</strong> The dataset spans two years, from 2007 to 2008. <strong>Volume:</strong> 24 separate .mat files, approximately one file for each month of the two-year period. <strong>Measurement Tool:</strong> Sonic anemometer positioned at the FINO1 offshore platform. <strong>Primary Features:</strong> Aggregated mean flow and one-point turbulent characteristics. <strong>Relevance and Applications:</strong> Exploration of the validity of various turbulence models (e.g., Kaimal or Mann spectral models) in offshore environments. Study of the single-point auto-spectral and cross-spectral densities of wind turbulence. Assessment of the applicability of certain standards, such as IEC 61400-1 and IEC 61400-3, especially in the context of the North Sea wind turbines. <strong>Literature Related to the Dataset:</strong> Cheynet, E., Jakobsen, J. B., & Obhrai, C. (2017). Spectral characteristics of surface-layer turbulence in the North Sea. Energy Procedia, 137, 414-427. Elsevier. Cheynet, E., Jakobsen, J. B., & Reuder, J. (2018). Velocity spectra and coherence estimates in the marine atmospheric boundary layer. Boundary-layer meteorology, 169(3), 429-460. Springer Netherlands. Cheynet, E. (2019). Influence of the Measurement Height on the Vertical Coherence of Natural Wind. Lecture Notes in Civil Engineering, 27, 207-221. Springer.
DOI: 10.5281/zenodo.8296893
title: One-point Integral and Turbulent wind Characteristics at the FINO1 Platform (2007-2008)

description: <strong>Dataset</strong>: One-point Integral and Turbulent wind Characteristics at the FINO1 Platform (2007-2008) <strong>Authors:</strong> Cheynet, E. <strong>Description:</strong> This dataset offers a comprehensive collection of wind measurements derived from continuous sonic anemometer recordings at the FINO1 offshore platform during the years 2007 and 2008. The measurements were conducted to investigate the properties and characteristics of wind turbulence in the marine atmospheric boundary layer, especially in relation to atmospheric stability. The data provide insights that have potential implications for the design and safety of offshore structures, particularly wind turbines, as they relate to wind loads. The database includes aggregated mean flow data alongside one-point turbulent characteristics. <strong>Tutorial:</strong> https://se.mathworks.com/matlabcentral/fileexchange/134446-offshore-wind-turbulence-characteristics-at-fino1 <strong>Content Overview:</strong> <strong>Format:</strong> Matlab (.mat) files. <strong>Data Duration:</strong> The dataset spans two years, from 2007 to 2008. <strong>Volume:</strong> 24 separate .mat files, approximately one file for each month of the two-year period. <strong>Measurement Tool:</strong> Sonic anemometer positioned at the FINO1 offshore platform. <strong>Primary Features:</strong> Aggregated mean flow and one-point turbulent characteristics. <strong>Relevance and Applications:</strong> Exploration of the validity of various turbulence models (e.g., Kaimal or Mann spectral models) in offshore environments. Study of the single-point auto-spectral and cross-spectral densities of wind turbulence. Assessment of the applicability of certain standards, such as IEC 61400-1 and IEC 61400-3, especially in the context of the North Sea wind turbines. <strong>Literature Related to the Dataset:</strong> Cheynet, E., Jakobsen, J. B., & Obhrai, C. (2017). Spectral characteristics of surface-layer turbulence in the North Sea. Energy Procedia, 137, 414-427. Elsevier. Cheynet, E., Jakobsen, J. B., & Reuder, J. (2018). Velocity spectra and coherence estimates in the marine atmospheric boundary layer. Boundary-layer meteorology, 169(3), 429-460. Springer Netherlands. Cheynet, E. (2019). Influence of the Measurement Height on the Vertical Coherence of Natural Wind. Lecture Notes in Civil Engineering, 27, 207-221. Springer.
DOI: 10.5281/zenodo.7573784
title: BriTROC-1 study: genomic landscape of recurrent ovarian high grade serous carcinoma - pre processed data

description: Dataset containing pre-processed data files required to replicate analysis performed in the publication "<strong>The genomic landscape of recurrent ovarian high grade serous carcinoma: the BriTROC-1 study</strong>" (Smith & Bradley et al. 2023).
DOI: 10.5281/zenodo.8304868
title: BriTROC-1 study: genomic landscape of recurrent ovarian high grade serous carcinoma - pre processed data

description: Dataset containing pre-processed data files required to replicate analysis performed in the publication "<strong>The genomic landscape of recurrent ovarian high grade serous carcinoma: the BriTROC-1 study</strong>" (Smith & Bradley et al. 2023).
DOI: 10.5281/zenodo.7573783
title: BriTROC-1 study: genomic landscape of recurrent ovarian high grade serous carcinoma - pre processed data

description: Dataset containing pre-processed data files required to replicate analysis performed in the publication "<strong>The genomic landscape of recurrent ovarian high grade serous carcinoma: the BriTROC-1 study</strong>" (Smith & Bradley et al. 2023).
DOI: 10.6084/m9.figshare.24064689
title: TME3-100004

description: 100004 contig TME3
DOI: 10.6084/m9.figshare.24064689.v2
title: TME3-100004

description: 100004 contig TME3
DOI: 10.6084/m9.figshare.24064689.v1
title: Untitled Item

description: 100004 contig TME3
DOI: 10.5517/cc4fs1c
title: CCDC 132402: Experimental Crystal Structure Determination

description: Related Article: S.A.Pogozhikh, Yu.E.Ovchinnikov, V.N.Khrustalev, M.Yu.Antipin, R.G.Karpenko, S.P.Kolesnikov|1999|Izv.Akad.Nauk SSSR,Ser.Khim.||116|
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f0s3c
title: CCDC 2235072: Experimental Crystal Structure Determination

description: Related Article: Mahendra A. Wagh, Dinesh R. Shinde, Rama Krishna Gamidi, Gangadhar J. Sanjayan|2023|Org.Biomol.Chem.|21|6914|doi:10.1039/D3OB01174G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.8304900
title: GPUB

description: The German Public Building Section Dataset contains multi-modal datasources (RGB,IR,DSM) along with single roof-level annotations of buildings.