cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5593990
title: Confocal and micro-CT data of Cretakarenni shaoi, holotype, NIGP177331

description: This dataset contains the raw confocal laser scanning microscopy (CLSM) slices and X-ray microtomography (micro-CT) slices for the holotype of <em>Cretakarenni shaoi</em> (NIGP177331) from mid-Cretaceous Burmese amber. Additional confocal data for <em>Cretakarenni birmanicus</em> (QUST-INSECT-0003) are also provided. This dataset is associated with the publication "Minute clubbed beetles with cephalic horns in mid-Cretaceous amber from northern Myanmar (Coleoptera: Monotomidae)" (DOI:10.11865/zs.2022206). Confocal images were obtained with a Zeiss LSM710 confocal laser scanning microscope, using the 488 nm Argon laser excitation line. The original CZI files are provided, which could be opened by the ZEISS ZEN software. Micro-CT data were obtained with a Zeiss Xradia 520 Versa 3D X-ray microscope. Scanning parameters were as follows: isotropic voxel size, 2.0815 μm; power, 4 W; acceleration voltage, 50 kV; exposure time, 3 s; projections, 2801. The TIFF stack is provided.
DOI: 10.5281/zenodo.6390097
title: Confocal data of Bipogonia and Carinibipogonia

description: This dataset contains the raw confocal laser scanning microscopy (CLSM) slices for the holotypes of <em>Bipogonia trivialis</em> (NIGP179428), <em>Bipogonia fortis</em> (NIGP179431), and <em>Carinibipogonia xiai</em> (NIGP179432) from mid-Cretaceous Burmese amber. This dataset is associated with the publication "First Artematopodidae from mid-Cretaceous amber of northern Myanmar (Coleoptera: Elateroidea)" (DOI:10.11646/zootaxa.5129.2.6). Confocal images were obtained with a Zeiss LSM710 confocal laser scanning microscope, using the 561 nm (DPSS 561-10) laser excitation line. The original CZI files are provided, which could be opened by the ZEISS ZEN software.
DOI: 10.5281/zenodo.6390096
title: Confocal data of Bipogonia and Carinibipogonia

description: This dataset contains the raw confocal laser scanning microscopy (CLSM) slices for the holotypes of <em>Bipogonia trivialis</em> (NIGP179428), <em>Bipogonia fortis</em> (NIGP179431), and <em>Carinibipogonia xiai</em> (NIGP179432) from mid-Cretaceous Burmese amber. This dataset is associated with the publication "First Artematopodidae from mid-Cretaceous amber of northern Myanmar (Coleoptera: Elateroidea)" (DOI:10.11646/zootaxa.5129.2.6). Confocal images were obtained with a Zeiss LSM710 confocal laser scanning microscope, using the 561 nm (DPSS 561-10) laser excitation line. The original CZI files are provided, which could be opened by the ZEISS ZEN software.
DOI: 10.6084/m9.figshare.20037389
title: Data_Multimodal_Perception_Cells

description: Single cell data sets containing the measured 4i features from which all analysis presented can be recreated. <br> Check meta header in the corresponding code files from Github for further details.
DOI: 10.6084/m9.figshare.20037389.v1
title: Data_Multimodal_Perception_Cells

description: Single cell data sets containing the measured 4i features from which all analysis presented can be recreated. <br> Check meta header in the corresponding code files from Github for further details.
DOI: 10.5281/zenodo.6632439
title: Supplement file of our database where we have given all the results of our patients diagnosed with a certainty diagnosis

description: Supplement file of our database where we have given all the results of our patients diagnosed with a certainty diagnosis
DOI: 10.5281/zenodo.6632438
title: Supplement file of our database where we have given all the results of our patients diagnosed with a certainty diagnosis

description: Supplement file of our database where we have given all the results of our patients diagnosed with a certainty diagnosis
DOI: 10.23728/b2share.c6b965776b5844fb80046f1b07da971b
title: Impact of PGY-1 Otolaryngology Bootcamp on Procedural Skill Development

description: Results section of manuscript
DOI: 10.6084/m9.figshare.20052380
title: supporting data and RStudio session

description: Supplementary info word file, Rstudio files and respective excel files
DOI: 10.6084/m9.figshare.20052380.v1
title: supporting data and RStudio session

description: Supplementary info word file, Rstudio files and respective excel files
DOI: 10.6084/m9.figshare.19450421.v2
title: Papachatzis_Frontiers_Data Availability

description: The datasets presented in the study “<em>Papachatzis N, Slivka DR, Pipinos II,Schmid KK and Takahashi KZ (2022) Does the Heel’s Dissipative Energetic Behavior Affect Its Thermodynamic Responses During Walking? Front. Bioeng. Biotechnol. 10:908725. doi: 10.3389/fbioe.2022.908725”</em>
DOI: 10.6084/m9.figshare.19450421
title: Papachatzis_Frontiers_Data Availability

description: The datasets presented in the study “<em>Papachatzis N, Slivka DR, Pipinos II,Schmid KK and Takahashi KZ (2022) Does the Heel’s Dissipative Energetic Behavior Affect Its Thermodynamic Responses During Walking? Front. Bioeng. Biotechnol. 10:908725. doi: 10.3389/fbioe.2022.908725”</em>
DOI: 10.6084/m9.figshare.19450421.v1
title: Papachatzis_Frontiers_Data Availability

description: The datasets presented in the study “<em>Papachatzis N, Slivka DR, Pipinos II,Schmid KK and Takahashi KZ (2022) Does the Heel’s Dissipative Energetic Behavior Affect Its Thermodynamic Responses During Walking? Front. Bioeng. Biotechnol. 10:908725. doi: 10.3389/fbioe.2022.908725”</em>
DOI: 10.6084/m9.figshare.20009042
title: Data for Damashek et al. 2022 Upper Oconee ARGs manuscript v2

description: Dataset for Damashek et al. 2022 manuscript on ARGs and fecal source tracking in the Upper Oconee River watershed (GA, USA). Updated from previous version to include volume of water sampled for each DNA sample. <br> Sheet 1: Gene abundances and sampling information for each DNA sample. Gene abundances are calculated as copies µL DNA–1, copies mL–1 site water, and as a ratio to bacterial 16S rRNA gene abundance. Sheet 2: Environmental data at sampling sites. Separate sheets show data and corresponding metadata. Site-linked sewer and septic data are withheld due to privacy concerns. Sheet 3: Correlations between genes. Correlations (Spearman’s<em> r</em>, Benjamini-Hochberg corrected <em>p</em>) between genes across the entire dataset. See Damashek et al. (in review) for analyses. Bibliographic information will be published here upon acceptance.
DOI: 10.5517/ccdc.csd.cc28n627
title: CCDC 2104778: Experimental Crystal Structure Determination

description: Related Article: Tingting Zhou, Anquan Zheng, Wenge Zhang, Xiuxiang Lu, Huiyu Chen, Haibo Tan|2022|Org.Biomol.Chem.|20|4096|doi:10.1039/D2OB00634K
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.cc28w3q0
title: CCDC 2111432: Experimental Crystal Structure Determination

description: Related Article: Zi-Jian Li, Xue Wang, Lin Zhu, Yu Ju, Zeru Wang, Qian Zhao, Zhi-Hui Zhang, Tao Duan, Yuan Qian, Jian-Qiang Wang, Jian Lin|2022|Inorg.Chem.|61|7467|doi:10.1021/acs.inorgchem.2c00545
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.6632584
title: Building fraction map of Germany (Sentinel-1/-2 based, 10m and 100m resolution)

description: This dataset features a map of building fractions (as opposed to built-up fractions including other impervious surfaces such as roads) for Germany on a 10m grid based on Sentinel-1A/B and Sentinel-2A/B time series. The data were created by using machine learning regression and spectral unmixing, using synthetically mixed training data. The dataset is completely based on freely accessible satellite imagery, and was validated with freely available building footprint reference data for three federal states. We recommend to use data at an aggregated resolution of 20m, 50m, or 100m, and to clip data at about 20% building fraction when using 10m resolution maps (or roughly the corresponding RMSE at any other resolution). <strong>Temporal extent</strong><br> Used Sentinel-2 data were acquired in 2018, and Sentinel-1 data were acquired in 2017 (see publication). The map is, thus, representative for 2017/2018. Validation results can be affected by building footprint reference data from different years. <strong>Data format</strong><br> The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. Building fraction values are in percent, from 0 to 100. In the original dataset with 10m spatial resolution, fraction values are equivalent to area in m². In the aggregated dataset with 100m spatial resolution, the values must be multiplied with 100 in order to see area in m². <strong>Further information</strong><br> For further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de). A web-visualization of this dataset is available here. <strong>Publication</strong><br> Schug, F.; Frantz, D.; Okujeni, A.; Hostert, P. (2022). Sub-pixel building area mapping based on synthetic training data and regression-based unmixing using Sentinel-1 and -2 data. Remote Sensing Letters. DOI: 10.1080/2150704X.2022.2088253 <strong>Acknowledgements</strong><br> The dataset was generated by FORCE v. 3.6.1 (paper, code), which is freely available software under the terms of the GNU General Public License v. &gt;= 3. Sentinel imagery were obtained from the European Space Agency and the European Commission. Sentinel-1 data were provided by EODC. We thank the providers of the building footprint reference data (see publication). <strong>Funding</strong><br> This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).
DOI: 10.5281/zenodo.6632583
title: Building fraction map of Germany (Sentinel-1/-2 based, 10m and 100m resolution)

description: This dataset features a map of building fractions (as opposed to built-up fractions including other impervious surfaces such as roads) for Germany on a 10m grid based on Sentinel-1A/B and Sentinel-2A/B time series. The data were created by using machine learning regression and spectral unmixing, using synthetically mixed training data. The dataset is completely based on freely accessible satellite imagery, and was validated with freely available building footprint reference data for three federal states. We recommend to use data at an aggregated resolution of 20m, 50m, or 100m, and to clip data at about 20% building fraction when using 10m resolution maps (or roughly the corresponding RMSE at any other resolution). <strong>Temporal extent</strong><br> Used Sentinel-2 data were acquired in 2018, and Sentinel-1 data were acquired in 2017 (see publication). The map is, thus, representative for 2017/2018. Validation results can be affected by building footprint reference data from different years. <strong>Data format</strong><br> The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. Building fraction values are in percent, from 0 to 100. In the original dataset with 10m spatial resolution, fraction values are equivalent to area in m². In the aggregated dataset with 100m spatial resolution, the values must be multiplied with 100 in order to see area in m². <strong>Further information</strong><br> For further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de). A web-visualization of this dataset is available here. <strong>Publication</strong><br> Schug, F.; Frantz, D.; Okujeni, A.; Hostert, P. (2022). Sub-pixel building area mapping based on synthetic training data and regression-based unmixing using Sentinel-1 and -2 data. Remote Sensing Letters. DOI: 10.1080/2150704X.2022.2088253 <strong>Acknowledgements</strong><br> The dataset was generated by FORCE v. 3.6.1 (paper, code), which is freely available software under the terms of the GNU General Public License v. &gt;= 3. Sentinel imagery were obtained from the European Space Agency and the European Commission. Sentinel-1 data were provided by EODC. We thank the providers of the building footprint reference data (see publication). <strong>Funding</strong><br> This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).
DOI: 10.6084/m9.figshare.19982180.v1
title: Data and code from: Encroachment diminishes herbaceous plant diversity in grassy ecosystems worldwide

description: Data and code used in Wieczorkowski, J.D. and Lehmann, C.E.R. (2022) Encroachment diminishes herbaceous plant diversity in grassy ecosystems worldwide. Global Change Biology.
DOI: 10.5281/zenodo.6631246
title: A higher-level nuclear phylogenomic study of the carrot family (Apiaceae)

description: Premise The carrot family (Apiaceae) comprises 466 genera, which include many well-known crops (e.g., aniseed, caraway, carrots, celery, coriander, cumin, dill, fennel, parsley, and parsnips). Higher-level phylogenetic relationships among subfamilies, tribes, and other major clades of Apiaceae are not fully resolved. This study aims to address this important knowledge gap. Methods Target sequence capture with the universal Angiosperms353 probe set was used to examine phylogenetic relationships in 234 genera of Apiaceae, representing all four currently recognized subfamilies (Apioideae, Azorelloideae, Mackinlayoideae, and Saniculoideae). Recovered nuclear genes were analyzed using both multispecies coalescent and concatenation approaches. Results We recovered hundreds of nuclear genes even from old and poor-quality herbarium specimens. Of particular note, we placed with strong support three incertae sedis genera (<em>Platysace</em>, <em>Klotzchia</em>, and <em>Hermas</em>); all three occupy isolated positions, with <em>Platysace</em>resolved as sister to all remaining Apiaceae. We placed nine genera (<em>Apodicarpum</em>, <em>Bonannia</em>, <em>Grafia</em>, <em>Haplosciadium</em>, <em>Microsciadium</em>, <em>Physotrichia</em>, <em>Ptychotis</em>, <em>Tricholaser</em>, <em>Xatardia</em>) that have never previously been included in any molecular phylogenetic study. Conclusions We provide support for the maintenance of the four existing subfamilies of Apiaceae, while recognizing that <em>Hermas</em>, <em>Klotzschia</em>, and the <em>Platysace</em> clade may each need to be accommodated in additional subfamilies (pending improved sampling). The placement of the currently apioid genus <em>Phlyctidocarpa</em> can be accommodated by the expansion of subfamily Saniculoideae, although adequate morphological synapomorphies for this grouping are yet to be defined. This is the first phylogenetic study of the Apiaceae using high-throughput sequencing methods and represents an unprecedented evolutionary framework for the group.
DOI: 10.5281/zenodo.6631245
title: A higher-level nuclear phylogenomic study of the carrot family (Apiaceae)

description: Premise The carrot family (Apiaceae) comprises 466 genera, which include many well-known crops (e.g., aniseed, caraway, carrots, celery, coriander, cumin, dill, fennel, parsley, and parsnips). Higher-level phylogenetic relationships among subfamilies, tribes, and other major clades of Apiaceae are not fully resolved. This study aims to address this important knowledge gap. Methods Target sequence capture with the universal Angiosperms353 probe set was used to examine phylogenetic relationships in 234 genera of Apiaceae, representing all four currently recognized subfamilies (Apioideae, Azorelloideae, Mackinlayoideae, and Saniculoideae). Recovered nuclear genes were analyzed using both multispecies coalescent and concatenation approaches. Results We recovered hundreds of nuclear genes even from old and poor-quality herbarium specimens. Of particular note, we placed with strong support three incertae sedis genera (<em>Platysace</em>, <em>Klotzchia</em>, and <em>Hermas</em>); all three occupy isolated positions, with <em>Platysace</em>resolved as sister to all remaining Apiaceae. We placed nine genera (<em>Apodicarpum</em>, <em>Bonannia</em>, <em>Grafia</em>, <em>Haplosciadium</em>, <em>Microsciadium</em>, <em>Physotrichia</em>, <em>Ptychotis</em>, <em>Tricholaser</em>, <em>Xatardia</em>) that have never previously been included in any molecular phylogenetic study. Conclusions We provide support for the maintenance of the four existing subfamilies of Apiaceae, while recognizing that <em>Hermas</em>, <em>Klotzschia</em>, and the <em>Platysace</em> clade may each need to be accommodated in additional subfamilies (pending improved sampling). The placement of the currently apioid genus <em>Phlyctidocarpa</em> can be accommodated by the expansion of subfamily Saniculoideae, although adequate morphological synapomorphies for this grouping are yet to be defined. This is the first phylogenetic study of the Apiaceae using high-throughput sequencing methods and represents an unprecedented evolutionary framework for the group.
DOI: 10.6084/m9.figshare.20054165
title: 11719B_bin3_ANME1

description: 11719B_bin3_ANME1 MAG. ANME-1a
DOI: 10.6084/m9.figshare.20054165.v1
title: 11719B_bin3_ANME1

description: 11719B_bin3_ANME1 MAG. ANME-1a
DOI: 10.6084/m9.figshare.20054168
title: 11719B_bin4_ANME1

description: MAG of 11719B_bin4_ANME1. ANME-1a
DOI: 10.6084/m9.figshare.20054168.v1
title: 11719B_bin4_ANME1

description: MAG of 11719B_bin4_ANME1. ANME-1a
DOI: 10.6084/m9.figshare.20054180.v1
title: 12019_bin1_ANME1.fasta

description: MAG of 12019_bin1_ANME1. ANME-1c
DOI: 10.6084/m9.figshare.20054180
title: 12019_bin1_ANME1.fasta

description: MAG of 12019_bin1_ANME1. ANME-1c
DOI: 10.6084/m9.figshare.20054186
title: 12019_bin3_Syntropho.fasta

description: MAG of 12019_bin3_syntropho. Syntrophoarchaeum
DOI: 10.6084/m9.figshare.20054186.v1
title: 12019_bin3_Syntropho.fasta

description: MAG of 12019_bin3_syntropho. Syntrophoarchaeum
DOI: 10.6084/m9.figshare.20054192
title: 12019_bin9_ANME1

description: 12019_bin9_ANME1. ANME-1a
DOI: 10.6084/m9.figshare.20054198
title: FW4382_bin035.fasta

description: MAG of FW4382_bin035. ANME-1a
DOI: 10.6084/m9.figshare.20054198.v1
title: FW4382_bin035.fasta

description: MAG of FW4382_bin035. ANME-1a
DOI: 10.6084/m9.figshare.20054204.v1
title: FW4382_bin044

description: MAG of FW4382_bin044. ANME-1c
DOI: 10.6084/m9.figshare.20054204
title: FW4382_bin044

description: MAG of FW4382_bin044. ANME-1c
DOI: 10.6084/m9.figshare.20054207
title: FW4382_bin054

description: MAG of FW4382_bin054. ANME-1a
DOI: 10.6084/m9.figshare.20054207.v1
title: FW4382_bin054

description: MAG of FW4382_bin054. ANME-1a
DOI: 10.6084/m9.figshare.20054213
title: FW4382_bin126

description: MAG of FW4382_bin126. ANME-1c
DOI: 10.6084/m9.figshare.20054213.v1
title: FW4382_bin126

description: MAG of FW4382_bin126. ANME-1c
DOI: 10.6084/m9.figshare.20054219
title: FWG146_ANME1.fasta

description: MAG of FWG146_ANME-1. ANME-1a
DOI: 10.6084/m9.figshare.20054219.v1
title: FWG146_ANME1.fasta

description: MAG of FWG146_ANME-1. ANME-1a
DOI: 10.25318/3210024401-eng
title: Succession plan for the agricultural operation, Census of Agriculture, 2021

description: Census of Agriculture, 2021. Farms reporting having a written succession plan for the agricultural operation.
DOI: 10.6084/m9.figshare.20054222
title: FWG147_ANME1

description: MAG of FWG147_ANME-1. ANME-1a
DOI: 10.6084/m9.figshare.20054222.v1
title: FWG147_ANME1

description: MAG of FWG147_ANME-1. ANME-1a
DOI: 10.6084/m9.figshare.20054225.v1
title: FWG148_ANME1

description: MAG of FWG148_ANME-1. ANME-1a
DOI: 10.6084/m9.figshare.20054225
title: FWG148_ANME1

description: MAG of FWG148_ANME-1. ANME-1a
DOI: 10.6084/m9.figshare.20054228.v1
title: FWG175_ANME1

description: MAG of FWG175_ANME1. ANME-1c.
DOI: 10.6084/m9.figshare.20054228
title: FWG175_ANME1

description: MAG of FWG175_ANME1. ANME-1c.
DOI: 10.25318/3210024401-fra
title: Plan de relève pour l'exploitation agricole, Recensement de l’agriculture, 2021

description: Recensement de l’agriculture, 2021. Exploitations agricoles déclarant avoir un plan de relève pour l'exploitation.
DOI: 10.6084/m9.figshare.20054231
title: NA091.008_bin1_ANME1

description: MAG of NA091.008_bin1_ANME1. ANME-1c
DOI: 10.6084/m9.figshare.20054231.v1
title: NA091.008_bin1_ANME1

description: MAG of NA091.008_bin1_ANME1. ANME-1c
DOI: 10.6084/m9.figshare.20054237
title: NA091.008_bin2_ANME1

description: MAG of NA091.008_bin2_ANME1. ANME-1c
DOI: 10.6084/m9.figshare.20054237.v1
title: NA091.008_bin2_ANME1

description: MAG of NA091.008_bin2_ANME1. ANME-1c
DOI: 10.5067/cpxnapa2wsq8
title: Spatial Statistical Data Fusion (SSDF) Level 3: CONUS Near-Surface Atmospheric Temperature from SNPP CrIMSS and Aqua AIRS, V2
DOI: 10.5281/zenodo.6622085
title: Model run output for Warren & Kite 202x

description: Model run output for oxygen loss modeling and 40Ar degassing modeling for Warren & Kite 202x (in preparation). Full timeseries output for individual runs in zipped file. Summary data in individual csvs. File names with "nomelt" in the title refer to baseline model runs. File names containing "melt" are model runs including runaway greenhouse surface melting. Code for running full model and generating figures from publication available at: https://github.com/aowarren/Venus_O2
description: This project made use of University of Chicago Research Computing Center resources. Grants: NASA NNH19ZDA001N-FINESST (F.I. A.O. Warren).
DOI: 10.5281/zenodo.6622084
title: Model run output for Warren & Kite 202x

description: Model run output for oxygen loss modeling and 40Ar degassing modeling for Warren & Kite 202x (in preparation). Full timeseries output for individual runs in zipped file. Summary data in individual csvs. File names with "nomelt" in the title refer to baseline model runs. File names containing "melt" are model runs including runaway greenhouse surface melting. Code for running full model and generating figures from publication available at: https://github.com/aowarren/Venus_O2
description: This project made use of University of Chicago Research Computing Center resources. Grants: NASA NNH19ZDA001N-FINESST (F.I. A.O. Warren).
DOI: 10.7278/s50d-154b-fppf
title: Large Kraken2 database for Fungi
DOI: 10.25318/3210024901-fra
title: Utilisation des terres, Recensement de l’agriculture, 2021

description: Recensement de l’agriculture, 2021. Terres en culture, terres en jachère (par méthode de désherbage utilisée), pâturages cultivés ou ensemencés, terres naturelles pour le pâturage, terres boisées et terres humides, superficie en arbres de Noël et toutes les autres superficies.
DOI: 10.25318/3210030901-fra
title: Grandes cultures et foin, Recensement de l’agriculture, 2021

description: Recensement de l’agriculture, 2021. Terres en grandes cultures et foin.
DOI: 10.6084/m9.figshare.20054285.v1
title: ECCO-ISE Sample Data

description: -Sample data for ECCO-Interactive-Solution-Evaluatior tool. -Serves as preliminary files to have the application working
DOI: 10.6084/m9.figshare.20054285
title: ECCO-ISE Sample Data

description: -Sample data for ECCO-Interactive-Solution-Evaluatior tool. -Serves as preliminary files to have the application working