cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2g5yd0
title: CCDC 2269832: Experimental Crystal Structure Determination

description: Related Article: Takuya Shimbayashi, Taiyou Ishige, Ken-ichi Fujita|2023|Org.Chem.Front.|10|5559|doi:10.1039/D3QO01269G
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.cc2g5yf1
title: CCDC 2269833: Experimental Crystal Structure Determination

description: Related Article: Takuya Shimbayashi, Taiyou Ishige, Ken-ichi Fujita|2023|Org.Chem.Front.|10|5559|doi:10.1039/D3QO01269G
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.cc2g5yg2
title: CCDC 2269834: Experimental Crystal Structure Determination

description: Related Article: Takuya Shimbayashi, Taiyou Ishige, Ken-ichi Fujita|2023|Org.Chem.Front.|10|5559|doi:10.1039/D3QO01269G
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.cc2g6966
title: CCDC 2270167: Experimental Crystal Structure Determination

description: Related Article: Michał J. Jadwiszczak, Piotr J. Leszczyński, Zoran Mazej, Przemysław J. Malinowski, Ewa K. Nawrocka, Krzysztof Kazimierczuk, Piotr Kwiatkowski, Piotr Połczyński, Magdalena Grochowska-Tatarczak, Karol J. Fijalkowski, Jarosław Sadło, Wojciech Grochala|2023|Org.Chem.Front.|10|5637|doi:10.1039/D3QO00985H
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.cc2g6977
title: CCDC 2270168: Experimental Crystal Structure Determination

description: Related Article: Michał J. Jadwiszczak, Piotr J. Leszczyński, Zoran Mazej, Przemysław J. Malinowski, Ewa K. Nawrocka, Krzysztof Kazimierczuk, Piotr Kwiatkowski, Piotr Połczyński, Magdalena Grochowska-Tatarczak, Karol J. Fijalkowski, Jarosław Sadło, Wojciech Grochala|2023|Org.Chem.Front.|10|5637|doi:10.1039/D3QO00985H
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.cc2g6988
title: CCDC 2270169: Experimental Crystal Structure Determination

description: Related Article: Michał J. Jadwiszczak, Piotr J. Leszczyński, Zoran Mazej, Przemysław J. Malinowski, Ewa K. Nawrocka, Krzysztof Kazimierczuk, Piotr Kwiatkowski, Piotr Połczyński, Magdalena Grochowska-Tatarczak, Karol J. Fijalkowski, Jarosław Sadło, Wojciech Grochala|2023|Org.Chem.Front.|10|5637|doi:10.1039/D3QO00985H
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.cc2g6yqc
title: CCDC 2270803: Experimental Crystal Structure Determination

description: Related Article: tongchang fang|2023|CSD Communication|||
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.cc2gby1t
title: CCDC 2274626: Experimental Crystal Structure Determination

description: Related Article: Sumit Sahoo, Gunasekaran Velmurugan, Peter Comba, Harapriya Rath|2023|Org.Chem.Front.|10|5601|doi:10.1039/D3QO01131C
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.10065705
title: Moderate size diversity of tree roots has largest effect on the carbon loss in tropical soils
DOI: 10.6084/m9.figshare.24456619
title: Diversity Outbred mouse omic data and associated code for manuscripts on glycolysis and ferroptosis in red blood cells

description: This project includes genetic, metabolomic, and lipidomic data from the Diversity Outbred mouse population and code used to generate results for manuscripts on glycolyis and ferroptosis in red blood cells.
DOI: 10.20392/2b58c240-49ce-4a72-800c-a13e978dac00
title: High-resolution measurements of swordfish skin surface roughness

description: Coordinate (x, y, z) data representing the skin surface of a swordfish, measured using an optical coherence tomography system and a gel-based stereo profilometer.
description: ASCII text file containing (x, y, z) coordinate data
description: 1
description: CC-BY
DOI: 10.6084/m9.figshare.24518665.v1
title: Shotgun lipidomics of mouse liver with adenovirus mediated PNPLA3 overexpression in ATGL-/- mice.

description: 10-week-old female C57BL/6J whole-body ATGL-/- mice were maintained on chow diet and infected with Ad-null, Ad-FLAG-PNPLA3-WT virus via retroorbital injection at 5x10^8 PFU/mouse. Four days post-injection, mice were sacrificed following a 12-h fast.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Ad-null group: 1300, 1301, 1338Ad-PNPLA3-WT group: 1261, 1282, 1289
DOI: 10.6084/m9.figshare.24518680
title: Shotgun lipidomics of mouse liver with adenovirus mediated PNPLA3-I148M overexpression in WT mice.

description: 10-week-old female C57BL/6J wildtype mice were maintained on chow diet and infected with Ad-null or Ad-FLAG-PNPLA3-I148M virus via retroorbital injection at 5x10^8 PFU/mouse. Four days post-injection, mice were sacrificed following a 12-h fast.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Ad-null group: 1218, 1219, 1371 [control group data found in "Figure 2" files]Ad-PNPLA3-WT group: 1259 (included as internal reference for comparison of two separate runs)Ad-PNPLA3-I148M group: 1237, 1312, 1354 [experimental group data found in "Figure 7" file]
DOI: 10.6084/m9.figshare.24518680.v1
title: Shotgun lipidomics of mouse liver with adenovirus mediated PNPLA3-I148M overexpression in WT mice.

description: 10-week-old female C57BL/6J wildtype mice were maintained on chow diet and infected with Ad-null or Ad-FLAG-PNPLA3-I148M virus via retroorbital injection at 5x10^8 PFU/mouse. Four days post-injection, mice were sacrificed following a 12-h fast.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Ad-null group: 1218, 1219, 1371 [control group data found in "Figure 2" files]Ad-PNPLA3-WT group: 1259 (included as internal reference for comparison of two separate runs)Ad-PNPLA3-I148M group: 1237, 1312, 1354 [experimental group data found in "Figure 7" file]
DOI: 10.6084/m9.figshare.24518719.v1
title: Shotgun lipidomics of mouse liver with ASO mediated PNPLA3 knockdown in WT mice stimulated with LXR agonist 'T0901317'.

description: 10-week-old female wild-type C57BL/6J mice were ad-libitum fed a corn-oil enriched Western Diet, a modified Western diet with corn oil substituted for butter (D21050712i) matched to D12079B (Research Diets, New Brunswick, NJ). During 3 week feeding time course, mice were administered 10 mg/kg ASO in PBS twice a week via IP injection. For LXR agonist administration, both groups of mice were injected 10 mg/kg T0901317 in 1:1 m-pyrrole: ethanol (5 mg/ml) on day 19 and day 20. Following metabolic synchronization, mice were sacrificed after 6 h of refeeding on day 21.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Control ASO group: 05, 06, 07PNPLA3 ASO group: 08, 09, 10
DOI: 10.6084/m9.figshare.24518665
title: Shotgun lipidomics of mouse liver with adenovirus mediated PNPLA3 overexpression in ATGL-/- mice.

description: 10-week-old female C57BL/6J whole-body ATGL-/- mice were maintained on chow diet and infected with Ad-null, Ad-FLAG-PNPLA3-WT virus via retroorbital injection at 5x10^8 PFU/mouse. Four days post-injection, mice were sacrificed following a 12-h fast.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Ad-null group: 1300, 1301, 1338Ad-PNPLA3-WT group: 1261, 1282, 1289
DOI: 10.6084/m9.figshare.24518644.v1
title: Shotgun lipidomics of mouse liver with adenovirus mediated PNPLA3 overexpression in WT mice.

description: 10-week-old female C57BL/6J wildtype mice were maintained on chow diet and infected with Ad-null, Ad-FLAG-PNPLA3-WT virus via retroorbital injection at 5x10^8 PFU/mouse. Four days post-injection, mice were sacrificed following a 12-h fast.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Ad-null group: 1218, 1219, 1371Ad-PNPLA3-WT group: 1243, 1259, 1291
DOI: 10.6084/m9.figshare.24518719
title: Shotgun lipidomics of mouse liver with ASO mediated PNPLA3 knockdown in WT mice stimulated with LXR agonist 'T0901317'.

description: 10-week-old female wild-type C57BL/6J mice were ad-libitum fed a corn-oil enriched Western Diet, a modified Western diet with corn oil substituted for butter (D21050712i) matched to D12079B (Research Diets, New Brunswick, NJ). During 3 week feeding time course, mice were administered 10 mg/kg ASO in PBS twice a week via IP injection. For LXR agonist administration, both groups of mice were injected 10 mg/kg T0901317 in 1:1 m-pyrrole: ethanol (5 mg/ml) on day 19 and day 20. Following metabolic synchronization, mice were sacrificed after 6 h of refeeding on day 21.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Control ASO group: 05, 06, 07PNPLA3 ASO group: 08, 09, 10
DOI: 10.6084/m9.figshare.24518644
title: Shotgun lipidomics of mouse liver with adenovirus mediated PNPLA3 overexpression in WT mice.

description: 10-week-old female C57BL/6J wildtype mice were maintained on chow diet and infected with Ad-null, Ad-FLAG-PNPLA3-WT virus via retroorbital injection at 5x10^8 PFU/mouse. Four days post-injection, mice were sacrificed following a 12-h fast.Total lipids were extracted from mouse liver tissues and analyzed using multidimensional mass spectrometry (MDMS)-based shotgun lipidomics (MDMS-SL) at the University of Texas Health Science Center at San Antonio, as previously detailed (Yang et al., Anal.Chem., 2009)Ad-null group: 1218, 1219, 1371Ad-PNPLA3-WT group: 1243, 1259, 1291
DOI: 10.57967/hf/1328
title: DoxygenStrings-Long
DOI: 10.5281/zenodo.10079725
title: Scientific Mapping Example with R package `bibliometrix`

description: Example of the use of the R package bibliometrix for bibliometric analysis
DOI: 10.5281/zenodo.10079724
title: Scientific Mapping Example with R package `bibliometrix`

description: Example of the use of the R package bibliometrix for bibliometric analysis
DOI: 10.5281/zenodo.10001790
title: A case study: assessing the efficacy of the revised dosage regimen via prediction model for recurrent event rate using biomarker data
DOI: 10.5281/zenodo.10001791
title: A case study: assessing the efficacy of the revised dosage regimen via prediction model for recurrent event rate using biomarker data
DOI: 10.5281/zenodo.10074392
title: nuScenes Knowledge Graph

description: Ontologies and Knowledge Graphs of the ICCV 2023 workshop paper "nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction".
Content

nSKG (nuScenes Knowledge Graph): knowledge graph for the nuScenes dataset, that models all scene participants and road elements, as well as their semantic and spatial relationships
nSTP (nuScenes Trajectory Prediction Graph): heterogeneous graph of the nuScenes dataset for trajectory prediction in PyTorch Geometric (PyG) format. It extends nSKG for example by transformation into agents' local coordinate systems, relevant agent extraction, semantic relationships between agents.
nuScenes_agent_onto: ontology for the traffic participants (agents)
nuScenes_map_onto: ontology for the extended map
stardog_rules: SPARQL rules for mapping nuScenes concepts to the agent ontology
How to use
nSKG represents the KG created on the basis of the nuScenes ontologies nuScenes_agent_onto.ttl and nuScenes_map_onto.ttl and materializing the nuScenes annotation dataset. It can be used for applications where relational information between entities are important. The ontologies are in Turtle format and can be viewed by ontology editors such as Protege.
nSTP represents the extended version of nSKG, where agents are represented in local coordinate systems to enforce shift- and rotation-invariance. It also includes semantic relationships between agents, e.g. whether agents are on neighboring lanes, the same lane or might intersect. This is done based on the semantic scene graph describe in (Towards Traffic Scene Description: The Semantic Scene Graph). The data is provided in PyTorch Geometric format and directly be used to train graph neural network for trajectory prediction.
Acknowledgements
Special thanks to Motional for the permission to distribute this modified version of the nuScenes dataset.
Citation
If you use this work please cite

@inproceedings{ title={nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction}, author={Leon Mlodzian and Zhigang Sun and Hendrik Berkemeyer and Sebastian Monka and Zixu Wang and Stefan Dietze and Lavdim Halilaj and Juergen Luettin},booktitle={International Conference on Computer Vision (ICCV), Workhsop on Scene Graphs and Graph Representation Learning (SG2RL)}, year={2023} }
DOI: 10.5281/zenodo.10074393
title: nuScenes Knowledge Graph

description: Ontologies and Knowledge Graphs of the ICCV 2023 workshop paper "nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction".
Content

nSKG (nuScenes Knowledge Graph): knowledge graph for the nuScenes dataset, that models all scene participants and road elements, as well as their semantic and spatial relationships
nSTP (nuScenes Trajectory Prediction Graph): heterogeneous graph of the nuScenes dataset for trajectory prediction in PyTorch Geometric (PyG) format. It extends nSKG for example by transformation into agents' local coordinate systems, relevant agent extraction, semantic relationships between agents.
nuScenes_agent_onto: ontology for the traffic participants (agents)
nuScenes_map_onto: ontology for the extended map
stardog_rules: SPARQL rules for mapping nuScenes concepts to the agent ontology
How to use
nSKG represents the KG created on the basis of the nuScenes ontologies nuScenes_agent_onto.ttl and nuScenes_map_onto.ttl and materializing the nuScenes annotation dataset. It can be used for applications where relational information between entities are important. The ontologies are in Turtle format and can be viewed by ontology editors such as Protege.
nSTP represents the extended version of nSKG, where agents are represented in local coordinate systems to enforce shift- and rotation-invariance. It also includes semantic relationships between agents, e.g. whether agents are on neighboring lanes, the same lane or might intersect. This is done based on the semantic scene graph describe in (Towards Traffic Scene Description: The Semantic Scene Graph). The data is provided in PyTorch Geometric format and directly be used to train graph neural network for trajectory prediction.
Acknowledgements
Special thanks to Motional for the permission to distribute this modified version of the nuScenes dataset.
Citation
If you use this work please cite

@inproceedings{ title={nuScenes Knowledge Graph - A comprehensive semantic representation of traffic scenes for trajectory prediction}, author={Leon Mlodzian and Zhigang Sun and Hendrik Berkemeyer and Sebastian Monka and Zixu Wang and Stefan Dietze and Lavdim Halilaj and Juergen Luettin},booktitle={International Conference on Computer Vision (ICCV), Workhsop on Scene Graphs and Graph Representation Learning (SG2RL)}, year={2023} }
DOI: 10.5281/zenodo.10079005
title: Non-methane volatile organic compound emissions over China estimated using TROPOMI HCHO retrievals

description: We used the Regional multi-Air Pollutant Assimilation System (RAPAS) with the EnKF algorithm to optimize daily NMVOC emissions in China by assimilating TROPOMI HCHO retrievals.  
airqual.qc.csv includes assimilated and verified surface NO2 observations.
HCHO.tar.gz includes assimilated TROPOMI HCHO retrievals.
posterior_emission_27km.nc and  posterior_emission_mg_27km.nc includes inferred daily posterior anthropogenic and biogenic NMVOC emissions respectively for August 2022.
DOI: 10.5281/zenodo.10079768
title: TRANSLATION IN SPORTS CONTEXTS
DOI: 10.5281/zenodo.10079769
title: TRANSLATION IN SPORTS CONTEXTS
DOI: 10.6084/m9.figshare.24518350
title: CINEMA-OT PBMC Immune dataset

description: The full integrated subset of PBMC immune cells used in the CINEMA-OT paper.See: https://www.nature.com/articles/s41592-023-02040-5
DOI: 10.6084/m9.figshare.24518350.v1
title: CINEMA-OT PBMC Immune dataset

description: The full integrated subset of PBMC immune cells used in the CINEMA-OT paper.See: https://www.nature.com/articles/s41592-023-02040-5
DOI: 10.5281/zenodo.10079804
title: EXTRA LINGUISTIC ISSUES IN CROSS CULTURAL COMMUNICATION: BODY LANGUAGE AND TABOOS
DOI: 10.5281/zenodo.10079805
title: EXTRA LINGUISTIC ISSUES IN CROSS CULTURAL COMMUNICATION: BODY LANGUAGE AND TABOOS
DOI: 10.6084/m9.figshare.24354901.v1
title: Data for "Self-Attention ConvLSTM for Short-term Arctic Sea Ice Motion Prediction Using AMSR-E 36.5 GHz Data"

description: The project includes the 2018 AMSR-E images and mask images that we have used.
DOI: 10.5281/zenodo.10079810
title: TRANSLATION PROBLEMS OF SLANGISMS IN ENGLISH AND UZBEKI IN DIFFERENT DISCOURSES
DOI: 10.5281/zenodo.10079811
title: TRANSLATION PROBLEMS OF SLANGISMS IN ENGLISH AND UZBEKI IN DIFFERENT DISCOURSES
DOI: 10.6084/m9.figshare.24518812
title: Supplementary Material for: Ayurveda for a type 1 diabetes patient with peripheral arterial occlusive disease (PAOD)

description: Introduction: The effect of Ayurvedic therapy in type 2 diabetes (t2d) is well documented. For people with type 1 diabetes (t1d), there is little evidence on the applicability of Ayurvedic therapy. This case illustrates the course of Ayurvedic treatment in a person with t1d accompanied by peripheral arterial occlusive disease (PAOD). Case presentation: The patient had insulin-dependent t1d since the age of 6 years. At 39 years of age, he developed progressive bilateral peripheral arterial occlusive disease (PAOD) of the femoral arteries. He presented claudication symptoms at a walking distance of 150m. 10 surgical interventions for recanalization have been performed. The PAOD put heavy psychological strains on the patient. He developed moderate depression with anxiety and complains of tinnitus and sleep disturbances. Through an initial outpatient Ayurvedic treatment focused on dietary and lifestyle changes, phytotherapeutics and a subsequent 6-week inpatient Ayurvedic treatment in India, a weight reduction of 12 kg, a reduction in insulin requirement to 65% of baseline, as well as a walking performance without restriction at medium load could be achieved. The depression and inner tension completely retreated, one-sided tinnitus, and existing sleep disturbances dissolved completely. The lasting effect was still perceptible 5 months after the inpatient stay. Conclusions: For this person with t1d with PAOD, outpatient and inpatient Ayurvedic therapy could generate a significant improvement of his situation. The case demonstrates that people with t1d can benefit from individualized Ayurvedic therapy. This case motivates to invest in Ayurvedic research for people with t1d and complications.