cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7884833
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 500m SIN Grid in 2011

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500 m spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500 m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2011. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2010</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2012</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2011 Spatial Resolution: 500 m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7884832
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 500m SIN Grid in 2011

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500 m spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500 m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2011. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2010</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2012</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2011 Spatial Resolution: 500 m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.6456618
title: Code for Atmospheric Research publication - Height correction method based on the Monin–Obukhov similarity theory for better prediction of near-surface wind fields

description: In this repository, we include the source codes for WRF namelist, figures, and height correction used in the Atmospheric Research publication "Height correction method based on the Monin–Obukhov similarity theory for better prediction of near-surface wind fields" The namelist.wps and namelist.input in WRF namelist are using for making input and running simulation, and Fig scripts in Figure scripts are using for plotting the figures in the paper. hgt_corr in Height correction method is a code to correct the disparity of the 10-m height definition between the model and observation by applying the developed the height correction algorithm based on the Monin-Obukhov similarity theory.
DOI: 10.5281/zenodo.6530542
title: Code for Atmospheric Research publication - Height correction method based on the Monin–Obukhov similarity theory for better prediction of near-surface wind fields

description: In this repository, we include the source codes for WRF namelist, figures, and height correction used in the Atmospheric Research publication "Height correction method based on the Monin–Obukhov similarity theory for better prediction of near-surface wind fields" The namelist.wps and namelist.input in WRF namelist are using for making input and running simulation, and Fig scripts in Figure scripts are using for plotting the figures in the paper. hgt_corr in Height correction method is a code to correct the disparity of the 10-m height definition between the model and observation by applying the developed the height correction algorithm based on the Monin-Obukhov similarity theory.
DOI: 10.6084/m9.figshare.12235094.v1
title: Marginal band microtubules are acetylated by αTAT1

description: The discoid shape of resting platelets is maintained by a peripheral, circular bundle of microtubules called marginal band. Marginal band microtubules are acetylated on lysine 40 of the alpha-tubulin subunits. We have previously shown that the deacetylase HDAC6 is responsible for tubulin deacetylation in platelets and that the hyperacetylated state of the microtubules in <i>HDAC6KO</i> platelets correlates with faster activation/spreading kinetics, pointing to a regulatory role of this modification. So far, the question about the reverse enzyme, responsible for tubulin acetylation in platelets, has remained unanswered. Several enzymes have been described as having tubulin acetylation activity. Here we identify αTAT1 as the enzyme responsible for the acetylation of marginal band microtubules. We show that αTAT1 deficiency has only minor consequences for platelet production and function. A residual tubulin acetylation level in αTAT1 deficient platelet lysates suggests the presence of an additional tubulin-acetylating enzyme that is unable to acetylate marginal band microtubules.
DOI: 10.5517/ccdc.csd.cc2d7f36
title: CCDC 2211667: Experimental Crystal Structure Determination

description: Related Article: Mykyta O. Ivanytsya, Olena O. Pariiska, Andrey M. Mishura, Eduard B. Rusanov, Svetlana V. Shishkina, Alina O. Gorlova, Anton S. Lytvynenko, Sergey V. Ryabukhin, Dmitriy M. Volochnyuk, Sergey V. Kolotilov|2023|Inorg.Chem.|62|5906|doi:10.1021/acs.inorgchem.2c03816
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.7885256
title: MUSES Leaf Area Index (LAI) Monthly Global 1km SIN Grid in 2007

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 1 km spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2007. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2006</strong></em>, <em>and <strong>click here</strong> to download the MUSES LAI product <strong>in 2008</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2007 Spatial Resolution: 1 km Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7885255
title: MUSES Leaf Area Index (LAI) Monthly Global 1km SIN Grid in 2007

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global LAI product at 1 km spatial resolution and monthly temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao <em>et al</em>., 2014; Xiao <em>et al.</em>, 2016). The MUSES LAI product is spatially complete and temporally continuous. This dataset is the MUSES LAI product in 2007. <em>Please <strong>click here</strong> to download the MUSES LAI product <strong>in 2006</strong></em>, <em>and <strong>click here</strong> to download the MUSES LAI product <strong>in 2008</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2007 Spatial Resolution: 1 km Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 1000 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et al</em>. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 52, 209-223. Xiao Zhiqiang, <em>et al</em>. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. <em>IEEE Transactions on Geoscience and Remote Sensing</em>, 54, 5301-5318. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. <em>International Journal of Remote Sensing</em>, 43(4), 1199-1225. Xiao Zhiqiang, <em>et al</em>. (2017). Evaluation of four long time-series global leaf area index products. <em>Agricultural and Forest Meteorology</em>, 246, 218-230. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.34740/kaggle/dsv/5589540
title: Elon Musk Tweets
DOI: 10.15479/at:ista:12869
title: Research data for: A stochastic cellular automaton model of culture formation

description: We introduce a stochastic cellular automaton as a model for culture and border formation. The model can be conceptualized as a game where the expansion rate of cultures is quantified in terms of their area and perimeter in such a way that approximately round cultures get a competitive advantage. We first analyse the model with periodic boundary conditions, where we study how the model can end up in a fixed state, i.e. freezes. Then we implement the model on the European geography with mountains and rivers. We see how the model reproduces some qualitative features of European culture formation, namely that rivers and mountains are more frequently borders between cultures, mountainous regions tend to have higher cultural diversity and the central European plain has less clear cultural borders.
DOI: 10.5281/zenodo.7357839
title: Resources and datasets for automated high-throughput droplet screening by iSort

description: Contains the design files and source data linked to the following publication in Cell Reports Methods (2023, https://doi.org/10.1016/j.crmeth.2023.100478) <strong><em>iSort </em></strong><strong>enables automated complex microfluidic droplet sorting in an effort to democratize technology.</strong> <strong>Abstract: </strong><br> Fluorescence activated droplet sorting (FADS) is a widely used microfluidic technique for high throughput screening. However, it requires highly trained specialists to determine optimal sorting parameters, resulting in a large combinatorial space that is challenging to optimize systematically. Additionally, there is currently no way to track every single droplet within a screen, leading to compromised sorting and “hidden” false positive events. To overcome all these limitations, we have developed a setup in which the droplet frequency, spacing and trajectory at the sorting junction are monitored in real time using impedance analysis. The resulting data is used to continuously optimize all parameters automatically and to counteract perturbations, resulting in higher throughput, higher reproducibility, increased robustness and a beginner-friendly character. We believe this provides a missing piece for the spreading of phenotypic single-cell analysis methods, similar to what we have seen for single-cell genomics platforms. <strong>To cite:</strong> https://doi.org/10.1016/j.crmeth.2023.100478
DOI: 10.5281/zenodo.7357838
title: Resources and datasets for automated high-throughput droplet screening by iSort

description: Contains the design files and source data linked to the following publication in Cell Reports Methods (2023, https://doi.org/10.1016/j.crmeth.2023.100478) <strong><em>iSort </em></strong><strong>enables automated complex microfluidic droplet sorting in an effort to democratize technology.</strong> <strong>Abstract: </strong><br> Fluorescence activated droplet sorting (FADS) is a widely used microfluidic technique for high throughput screening. However, it requires highly trained specialists to determine optimal sorting parameters, resulting in a large combinatorial space that is challenging to optimize systematically. Additionally, there is currently no way to track every single droplet within a screen, leading to compromised sorting and “hidden” false positive events. To overcome all these limitations, we have developed a setup in which the droplet frequency, spacing and trajectory at the sorting junction are monitored in real time using impedance analysis. The resulting data is used to continuously optimize all parameters automatically and to counteract perturbations, resulting in higher throughput, higher reproducibility, increased robustness and a beginner-friendly character. We believe this provides a missing piece for the spreading of phenotypic single-cell analysis methods, similar to what we have seen for single-cell genomics platforms. <strong>To cite:</strong> https://doi.org/10.1016/j.crmeth.2023.100478
DOI: 10.15468/dl.wsbdmu
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Draba aizoides"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014831-250827131500795/datasets/export for details.
DOI: 10.15468/dl.peev4g
title: Occurrence Download

description: A dataset containing 1115 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Crotalus lepidus klauberi"
 ]
}

 The dataset includes 1115 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014830-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xjrbew
title: Occurrence Download

description: A dataset containing 462 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is New Caledonia",
 "DatasetKey is one of (The vascular plants collection (P) at the Herbarium of the Muséum national d'Histoire Naturelle (MNHN - Paris), Herbarium specimens of Université de Montpellier 2, Institut de Botanique (MPU)), Herbier de Nouvelle-Calédonie, Naturalis Biodiversity Center (NL) - Botany, Royal Botanic Gardens, Kew - Herbarium Specimens, National Herbarium of Victoria (MEL) AVH data, Tropicos Specimens Non-MO)",
 "Geometry POLYGON((165.50653 -21.51216,165.50015 -21.50406,165.45605 -21.49964,165.4423 -21.50283,165.41357 -21.50406,165.3652 -21.49276,165.33917 -21.4881,165.29252 -21.48196,165.28687 -21.48515,165.29136 -21.51248,165.29824 -21.52672,165.30339 -21.54047,165.3286 -21.55667,165.34309 -21.56183,165.35217 -21.56969,165.36469 -21.58221,165.38017 -21.59315,165.39687 -21.6015,165.41283 -21.60543,165.42413 -21.60715,165.4511 -21.60446,165.46718 -21.59174,165.48192 -21.591,165.50254 -21.59297,165.51605 -21.58216,165.51343 -21.52263,165.50653 -21.51216))",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 462 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0107207-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17615/eyxs-fy90
title: Amplification of disease by nutrient addition: Testing mechanisms from individual to community levels 

description: Nutrient supply can amplify disease epidemics through mechanisms from individual to community levels. Within host individuals, nutrient addition can drive pathogen replication or growth. Across a host population, nutrient addition can drive disease transmission by increasing host growth and abundance relative to defense. Furthermore, such effects may be influenced by pathogen species interactions. Understanding how nutrients impact disease epidemics requires a framework that integrates these mechanisms across biological levels. To build such a framework, we conducted a field experiment in an old field on tall fescue, Lolium arundinaceum, and used structural equation models to integrate multiple hypothesized mechanisms. Nutrient addition (NPK fertilizer) increased brown patch disease but was best modeled as a direct path and not mediated by host abundance. To expand our framework, we also re-analyzed a previous experiment. That experiment reproduced the direct path from nutrients to disease, and added an indirect path mediated by host population abundance. Nutrient addition also increased foliar nitrogen, consistent with individual-level mechanism, but this did not increase disease. Brown patch decreased with burden of another disease, anthracnose, independently of nutrients. These results partially support both individual- and population-level hypotheses, emphasizing the importance of considering multiple biological levels underlying impacts of abiotic change.
DOI: 10.15468/dl.rgmrmc
title: Occurrence Download

description: A dataset containing 68778 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Cotoneaster Medik."
 ]
}

 The dataset includes 68778 records from 523 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0107205-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fuv836
title: Occurrence Download

description: A dataset containing 61921 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Sorbus L."
 ]
}

 The dataset includes 61921 records from 600 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0107208-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/408021f9-8576-4175-924f-9ad81866b8cf
title: Data underlying the publication: "Salt marshes for nature-based flood defense: sediment type, drainage, and vegetation drive the development of strong sediment beds"

description: We aimed to determine how fast sediment strength develops in marshes restored or created for nature-based flood defense. Therefore, this study investigated how 1) sediment type, 2) tidal drainage depth and duration, and 3) pioneer vegetation species drive the development rate of sediment strength. A controlled experiment was set up with pots filled with two sediment types, which were either left bare or planted with Spartina anglica or Scirpus maritimus, two dominant salt marsh pioneers in NW Europe. All treatments were subjected to four different tidal regimes with different tidal drainage depth and duration. After the growing season of 2021 (October) and before and after the growing season of 2022 (April and October, respectively), sediment strength proxies (i.e., compaction, penetration resistance, bulk density, and shear strength) and vegetation variables (i.e., above- and belowground biomass) were measured in five pots per treatment. This dataset contains all data of these variables at the three moments in time.