cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15151/esrf-es-1025856318
title: Cryo-electron microscopy EPN BAG

description: At the EPN campus level structural biology work is carried out in all the 4 institutes (IBS, ESRF, ILL and EMBL). Today all structural biology groups are turning to cryo-EM. The EM demand is therefore extremely high and present in the 4 Institutes. In a nutshell, there are more than 45 PIs that could benefit from Krios time on the EPN campus (more than 90 different samples). Around 20 % of the sample are ready for high resolution data collection with already prepared grids that have been pre-screened on Glacios microscopes. Whereas some work could be carried out on Glacios microscopes, for difficult samples the use of a krios is indispensable (heterogeneous sample or limited concentration requiring a large number of images; small protein etc). Only these samples will be selected for Krios time at the BAG level
DOI: 10.5281/zenodo.7598744
title: Dataset related to article "Long Pentraxin 3 as a New Biomarker for Diagnosis of Hip and Knee Periprosthetic Joint Infections".

description: This record contains raw data related to article "Long Pentraxin 3 as a New Biomarker for Diagnosis of Hip and Knee Periprosthetic Joint Infections". Abstract: Background: Preoperative diagnosis of periprosthetic joint infections (PJIs) poses an unmet clinical challenge. The long pentraxin PTX3 is a component of the innate immune system involved in infection immunity. This study evaluated the potential of synovial and plasmatic PTX3 in the diagnosis of hip and knee PJIs. Methods: Consecutive total hip and knee arthroplasty (THA/TKA) revisions were prospectively included and classified as septic or aseptic according to the European Bone and Joint Infection Society (EBJIS) and Musculoskeletal Infection Society (MSIS) criteria. The concentration of PTX3 in plasma and synovial fluid samples was measured with ELISA. The AUC, threshold value, sensitivity, specificity, and positive and negative likelihood ratios were calculated using the ROC (receiver operating characteristic) curve method. Results: The study population included 128 patients (94 THAs; 34 TKAs). The AUC of the synovial PTX3 based on EBJIS criteria was 0.85 (p &lt; 0.0001), with a sensitivity of 81.13% and a specificity of 93.33%. The AUC based on MSIS criteria was 0.95 (p &lt; 0.001), with a sensitivity of 91.43% and a specificity of 89.25%. Plasmatic PTX3 failed to discriminate infected from non-infected patients. Conclusions: Synovial PTX3 demonstrated an excellent diagnostic potential in hip and knee PJIs, with a very high specificity irrespective of the diagnostic criteria for PJI.
DOI: 10.5281/zenodo.7598743
title: Dataset related to article "Long Pentraxin 3 as a New Biomarker for Diagnosis of Hip and Knee Periprosthetic Joint Infections".

description: This record contains raw data related to article "Long Pentraxin 3 as a New Biomarker for Diagnosis of Hip and Knee Periprosthetic Joint Infections". Abstract: Background: Preoperative diagnosis of periprosthetic joint infections (PJIs) poses an unmet clinical challenge. The long pentraxin PTX3 is a component of the innate immune system involved in infection immunity. This study evaluated the potential of synovial and plasmatic PTX3 in the diagnosis of hip and knee PJIs. Methods: Consecutive total hip and knee arthroplasty (THA/TKA) revisions were prospectively included and classified as septic or aseptic according to the European Bone and Joint Infection Society (EBJIS) and Musculoskeletal Infection Society (MSIS) criteria. The concentration of PTX3 in plasma and synovial fluid samples was measured with ELISA. The AUC, threshold value, sensitivity, specificity, and positive and negative likelihood ratios were calculated using the ROC (receiver operating characteristic) curve method. Results: The study population included 128 patients (94 THAs; 34 TKAs). The AUC of the synovial PTX3 based on EBJIS criteria was 0.85 (p &lt; 0.0001), with a sensitivity of 81.13% and a specificity of 93.33%. The AUC based on MSIS criteria was 0.95 (p &lt; 0.001), with a sensitivity of 91.43% and a specificity of 89.25%. Plasmatic PTX3 failed to discriminate infected from non-infected patients. Conclusions: Synovial PTX3 demonstrated an excellent diagnostic potential in hip and knee PJIs, with a very high specificity irrespective of the diagnostic criteria for PJI.
DOI: 10.57745/2fcwkt
title: 230130 - Raw data - Álvarez et al. (2023).tab

description: :unav
DOI: 10.5517/ccdc.csd.cc2bl6kq
title: CCDC 2162453: Experimental Crystal Structure Determination

description: Related Article: Catalin Maxim, Cristian D. Ene, Ioana Nicolau, Lavinia L. Ruta, Ileana C. Farcasanu|2022|Dalton Trans.|51|18383|doi:10.1039/D2DT02620A
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.cc2c2d40
title: CCDC 2177041: Experimental Crystal Structure Determination

description: Related Article: Youhua Tao|2022|CSD Communication|||
description: Related Article: Yanchao Wang, Yinuo Zhu, Wenxiu Lv, Xianhong Wang, Youhua Tao|2023|J.Am.Chem.Soc.|145|1877|doi:10.1021/jacs.2c11502
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.cc2c2g86
title: CCDC 2177107: Experimental Crystal Structure Determination

description: Related Article: Youhua Tao|2022|CSD Communication|||
description: Related Article: Yanchao Wang, Yinuo Zhu, Wenxiu Lv, Xianhong Wang, Youhua Tao|2023|J.Am.Chem.Soc.|145|1877|doi:10.1021/jacs.2c11502
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.cc2c2m14
title: CCDC 2177255: Experimental Crystal Structure Determination

description: Related Article: Craig Hardy, Gabriele Kociok-Köhn, Antoine Buchard|2023|Polym.Chem.|14|623|doi:10.1039/D2PY01366E
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.cc2c2m25
title: CCDC 2177256: Experimental Crystal Structure Determination

description: Related Article: Craig Hardy, Gabriele Kociok-Köhn, Antoine Buchard|2023|Polym.Chem.|14|623|doi:10.1039/D2PY01366E
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.cc2c2m36
title: CCDC 2177257: Experimental Crystal Structure Determination

description: Related Article: Craig Hardy, Gabriele Kociok-Köhn, Antoine Buchard|2023|Polym.Chem.|14|623|doi:10.1039/D2PY01366E
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.cc2c2yzd
title: CCDC 2177594: Experimental Crystal Structure Determination

description: Related Article: Yanxia Lv, Zhong-Wei Hou, Yi Wang, Pinhua Li, Lei Wang|2023|Org.Biomol.Chem.|21|1014|doi:10.1039/D2OB01883G
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.cc2c3c1x
title: CCDC 2177968: Experimental Crystal Structure Determination

description: Related Article: Mingying Xie, Muxin Yu, Caiping Liu, Yunfang Zhao, Zhijia Li, Shengchang Li, Feilong Jiang, Lian Chen, Maochun Hong|2022|J.Mater.Chem.C|10|16100|doi:10.1039/D2TC02750J
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.cc2c3c2y
title: CCDC 2177969: Experimental Crystal Structure Determination

description: Related Article: Mingying Xie, Muxin Yu, Caiping Liu, Yunfang Zhao, Zhijia Li, Shengchang Li, Feilong Jiang, Lian Chen, Maochun Hong|2022|J.Mater.Chem.C|10|16100|doi:10.1039/D2TC02750J
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.cc2c3c3z
title: CCDC 2177970: Experimental Crystal Structure Determination

description: Related Article: Mingying Xie, Muxin Yu, Caiping Liu, Yunfang Zhao, Zhijia Li, Shengchang Li, Feilong Jiang, Lian Chen, Maochun Hong|2022|J.Mater.Chem.C|10|16100|doi:10.1039/D2TC02750J
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.cc2c3c40
title: CCDC 2177971: Experimental Crystal Structure Determination

description: Related Article: Mingying Xie, Muxin Yu, Caiping Liu, Yunfang Zhao, Zhijia Li, Shengchang Li, Feilong Jiang, Lian Chen, Maochun Hong|2022|J.Mater.Chem.C|10|16100|doi:10.1039/D2TC02750J
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.cc2c3c51
title: CCDC 2177972: Experimental Crystal Structure Determination

description: Related Article: Mingying Xie, Muxin Yu, Caiping Liu, Yunfang Zhao, Zhijia Li, Shengchang Li, Feilong Jiang, Lian Chen, Maochun Hong|2022|J.Mater.Chem.C|10|16100|doi:10.1039/D2TC02750J
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: 10.17632/8bx8zxbdgm.1
title: CF_LnNHC_catal

description: open data for the Chem Sci paper "Controlled defluorination and alkylation of C(sp3)-F Bonds by Lanthanide Photocatalysts: Importance of Metal – Ligand Cooperativity"
DOI: 10.18112/openneuro.ds003216.v3.0.9
title: Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset
DOI: 10.25403/upresearchdata.21976025
title: Analysis of the use of the Senior South African Individual Scale-Revised (SSAIS-R) for South African children

description: These datasets were collected through semi-structured interviews. They consist of some of the challenges, advantages and benefits experienced by educational psychologists when using the Senior South African Individual Scale- Revised with South African children. A conceptual framework aided in understanding of this study and was guided by a pschometric approach and provided insight into the usefulness of the SSAIS-R. <br> <br>
DOI: 10.25403/upresearchdata.21976025.v1
title: Analysis of the use of the Senior South African Individual Scale-Revised (SSAIS-R) for South African children

description: These datasets were collected through semi-structured interviews. They consist of some of the challenges, advantages and benefits experienced by educational psychologists when using the Senior South African Individual Scale- Revised with South African children. A conceptual framework aided in understanding of this study and was guided by a pschometric approach and provided insight into the usefulness of the SSAIS-R. <br> <br>
DOI: 10.5281/zenodo.7602231
title: Coversion model and dataset of pressure sensors from voltage to pressure in SocketSense Project WP3

description: This is the conversion model to convert data from voltage to pressure in SocketSense Project WP3
description: Uploaded by Yizhi CHEN(yizhic@kth.se). Please contact yizhic@kth.se if you have any further questions.
DOI: 10.5281/zenodo.5574521
title: Coversion model and dataset of pressure sensors from voltage to pressure in SocketSense Project WP3

description: This is the conversion model to convert data from voltage to pressure in SocketSense Project WP3
description: Uploaded by Yizhi CHEN(yizhic@kth.se). Please contact yizhic@kth.se if you have any further questions.
DOI: 10.34740/kaggle/dsv/4938794
title: Nigerian Presidential Election 2023 Tweets
DOI: 10.6084/m9.figshare.17711108
title: SSM_mon_1950-2014.nc

description: Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °. This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.
DOI: 10.6084/m9.figshare.17711108.v1
title: SSM_mon_1950-2014.nc

description: fusion & downscaling dataset
DOI: 10.5281/zenodo.7602139
title: LLZO Simulation Trajectories

description: Simulation trajectories (in xyz/gro/xtc format) at a range of temperatures of LLZO (from 500 K to 800 K and 1000 K), produced using MetalWalls (doi: 10.21105/joss.02373) and converted to gro format.
DOI: 10.6084/m9.figshare.17711075
title: SSM_mon_ssp370_2015-2100.nc

description: Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °. This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.
DOI: 10.6084/m9.figshare.17711075.v2
title: SSM_mon_ssp370_2015-2100.nc

description: Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °. This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.
DOI: 10.6084/m9.figshare.17711075.v1
title: SSM_mon_ssp370_2015-2100.nc

description: fusion & downscaling dataset
DOI: 10.6084/m9.figshare.17711081
title: SSM_mon_ssp126_2015-2100.nc

description: Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °. This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.
DOI: 10.6084/m9.figshare.17711081.v1
title: SSM_mon_ssp126_2015-2100.nc

description: fusion & downscaling dataset
DOI: 10.6084/m9.figshare.17711084
title: SSM_mon_ssp585_2015-2100.nc

description: Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °. This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.
DOI: 10.6084/m9.figshare.17711084.v2
title: SSM_mon_ssp585_2015-2100.nc

description: Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °. This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.
DOI: 10.6084/m9.figshare.17711084.v1
title: SSM_mon_ssp585_2015-2100.nc

description: fusion & downscaling dataset
DOI: 10.6084/m9.figshare.17711078
title: SSM_mon_ssp245_2015-2100.nc

description: Monthly data of 7cm soil moisture in the surface layer of China. The time range includes the historical period 1850-2014 and the future period 2015-2100 (the future period includes four different shared socio-economic paths: ssp1-2.6, ssp2-4.5, ssp3-7.0 and ssp5-8.5). The spatial resolution is 0.25 °. This data is based on the deep learning method, taking the 7cm surface soil moisture data of era5 land as a reference, and integrating the surface soil moisture data of 25 scaled down cmip6 models. In the context of climate change, data can be used for drought and vegetation correlation analysis.
DOI: 10.6084/m9.figshare.17711078.v1
title: SSM_mon_ssp245_2015-2100.nc

description: fusion & downscaling dataset
DOI: 10.21942/uva.21696134
title: Datafiles: Local Shearing Force Measurement during Frictional Sliding Using Fluorogenic Mechanophores

description: The raw data and the Matlab code for the publication : Chao-Chun Hsu, Feng-Chun Hsia, Bart Weber, Matthijn B. de Rooij, Daniel Bonn, and Albert M. Brouwer, Local Shearing Force Measurement during Frictional Sliding Using Fluorogenic Mechanophores, The Journal of Physical Chemistry Letters <strong>2022</strong> <em>13</em> (38), 8840-8844 10.1021/acs.jpclett.2c02010 <br> Citation: DOI: 10.1021/acs.jpclett.2c02010 <br> Please find more details in the Readme file at each archive file.
DOI: 10.21942/uva.21696134.v2
title: Datafiles: Local Shearing Force Measurement during Frictional Sliding Using Fluorogenic Mechanophores

description: The raw data and the Matlab code for the publication : Chao-Chun Hsu, Feng-Chun Hsia, Bart Weber, Matthijn B. de Rooij, Daniel Bonn, and Albert M. Brouwer, Local Shearing Force Measurement during Frictional Sliding Using Fluorogenic Mechanophores, The Journal of Physical Chemistry Letters <strong>2022</strong> <em>13</em> (38), 8840-8844 10.1021/acs.jpclett.2c02010 <br> Citation: DOI: 10.1021/acs.jpclett.2c02010 <br> Please find more details in the Readme file at each archive file.
DOI: 10.21942/uva.21696134.v1
title: Datafiles: Local Shearing Force Measurement during Frictional Sliding Using Fluorogenic Mechanophores

description: The raw data and the Matlab code for the publication : Chao-Chun Hsu, Feng-Chun Hsia, Bart Weber, Matthijn B. de Rooij, Daniel Bonn, and Albert M. Brouwer, Local Shearing Force Measurement during Frictional Sliding Using Fluorogenic Mechanophores, The Journal of Physical Chemistry Letters <strong>2022</strong> <em>13</em> (38), 8840-8844 10.1021/acs.jpclett.2c02010 <br> Citation: DOI: 10.1021/acs.jpclett.2c02010 <br> Please find more details in the Readme file at each archive file.
DOI: 10.6084/m9.figshare.22004483
title: Visium DLPFC raw

description: Raw data from https://github.com/LieberInstitute/spatialLIBD used for the benchmarking of the spatial clustering methods in CellCharter.
DOI: 10.6084/m9.figshare.22004504
title: China regional multimodal fusion gross primary productivity data (1850-2100),

description: China regional gross primary productivity value data. Time range 1850-2014, including historical period in the future period 2015-2100 (contains four different Shared future period of social and economic path: SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5).The spatial resolution of 0.25 °.This data is based on the deep learning method, adopt the GPP data for reference, the data fusion of 23 CMIP6 downscaling model GPP. Under the background of climate change, the data can be used in the vegetation correlation analysis.
DOI: 10.5281/zenodo.7533554
title: Dimerization the ACE-2 with Different RBD Mounts: A Dynamic Simulation Perspective on SARS-Cov-2 Infecting Details

description: The system construction and dynamic simulation data of paper "Dimerization the ACE-2 with Different RBD Mounts: A Dynamic Simulation Perspective on SARS-Cov-2 Infecting Details"(manuscript, ci-2023-00041c) are prepared.
DOI: 10.5281/zenodo.7533553
title: Dimerization the ACE-2 with Different RBD Mounts: A Dynamic Simulation Perspective on SARS-Cov-2 Infecting Details

description: The system construction and dynamic simulation data of paper "Dimerization the ACE-2 with Different RBD Mounts: A Dynamic Simulation Perspective on SARS-Cov-2 Infecting Details"(manuscript, ci-2023-00041c) are prepared.
DOI: 10.34740/kaggle/dsv/4941044
title: IMDB Movies - All Categories
DOI: 10.6084/m9.figshare.22004273
title: Visium DLPFC preprocessed .h5ad

description: Preprocessed .h5ad data from https://github.com/LieberInstitute/spatialLIBD used for the benchmarking of the spatial clustering methods in CellCharter. <br> <br>