cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7023445
title: Data collection for article "Regional scale mapping of ecosystem services supply, demand, flow and mismatches in Southern Myanmar"

description: This dataset contains supply, demand, and flow maps from nine ecosystem service models (as layer files in .tif format) underlying the publication "Regional scale mapping of ecosystem services supply, demand, flow and mismatches in Southern Myanmar".
DOI: 10.5281/zenodo.7023261
title: Data collection for article "Local Perspectives on Ecosystem Service Trade-Offs in a Forest Frontier Landscape in Myanmar"

description: This dataset contains 46 transcripts from semi-structured interviews and focus group discussions. An overview of the interviews is additionally provided, as well as information on the encoding. These data underlie the publication "Local Perspectives on Ecosystem Service Trade-Offs in a Forest Frontier Landscape in Myanmar".
DOI: 10.5281/zenodo.7023260
title: Data collection for article "Local Perspectives on Ecosystem Service Trade-Offs in a Forest Frontier Landscape in Myanmar"

description: This dataset contains 46 transcripts from semi-structured interviews and focus group discussions. An overview of the interviews is additionally provided, as well as information on the encoding. These data underlie the publication "Local Perspectives on Ecosystem Service Trade-Offs in a Forest Frontier Landscape in Myanmar".
DOI: 10.5281/zenodo.7064513
title: Explaining Non-Entailment by Model Transformation for the Description Logic EL - IJCKG22 - Resources

description: <strong>resources.zip</strong> contains the experiment data and results, and a README file explaining how to rerun the experiment.
DOI: 10.5517/ccdc.csd.cc2801t5
title: CCDC 2085426: Experimental Crystal Structure Determination

description: Related Article: Kelsey Cairns|2022|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.cc28jdw3
title: CCDC 2101145: Experimental Crystal Structure Determination

description: Related Article: Zihao Zhu, Qixi Mi|2022|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.cc28jdx4
title: CCDC 2101146: Experimental Crystal Structure Determination

description: Related Article: Zihao Zhu, Qixi Mi|2022|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.cc28jdy5
title: CCDC 2101147: Experimental Crystal Structure Determination

description: Related Article: Zihao Zhu, Qixi Mi|2022|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.cc28jdz6
title: CCDC 2101148: Experimental Crystal Structure Determination

description: Related Article: Zihao Zhu, Qixi Mi|2022|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.cc2955th
title: CCDC 2120146: Experimental Crystal Structure Determination

description: Related Article: Fumie Sakurai, Takafumi Yukawa, Asato Kina, Masataka Murakami, Kazuaki Takami, Sachie Morimoto, Masaki Seto, Makoto Kamata, Tohru Yamashita, Kosuke Nakashima, Naohiro Narita, Ezio Bettini, Annarosa Ugolini, Mauro Corsi, Tomoaki Hasui|2022|Bioorg.Med.Chem.|56|116576|doi:10.1016/j.bmc.2021.116576
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.cc2979c7
title: CCDC 2122178: Experimental Crystal Structure Determination

description: Related Article: Jingkai Xu, Meng Chen|2022|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.cc2bs3js
title: CCDC 2168125: Experimental Crystal Structure Determination

description: Related Article: Ari Lehtonen, Reijo Sillanpää|2022|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.cc2btz05
title: CCDC 2169907: Experimental Crystal Structure Determination

description: Related Article: Shiyong Chen|2022|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.cc2btz16
title: CCDC 2169908: Experimental Crystal Structure Determination

description: Related Article: Shiyong Chen|2022|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.cc2cq15b
title: CCDC 2195921: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2022|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.cc2c520n
title: CCDC 2179610: Experimental Crystal Structure Determination

description: Related Article: Rahul Dahiwadkar, A. Murugan, Delna Johnson, Rik Chakraborty, Vijay Thiruvenkatam, Sriram Kanvah|2023|J.Photochem.Photobiol.A:Chem.|434|114227|doi:10.1016/j.jphotochem.2022.114227
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.cc2cw3q3
title: CCDC 2200805: Experimental Crystal Structure Determination

description: Related Article: Frank R. Fronczek|2022|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.cc2cxv27
title: CCDC 2202459: Experimental Crystal Structure Determination

description: Related Article: R.T. Bettinger, P.J. Squattrito, D. Aulakh, C.G. Gianopoulos|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|961|doi:10.1107/S2056989022008295
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.cc2cxv38
title: CCDC 2202460: Experimental Crystal Structure Determination

description: Related Article: R.T. Bettinger, P.J. Squattrito, D. Aulakh, C.G. Gianopoulos|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|961|doi:10.1107/S2056989022008295
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.cc2cxvdk
title: CCDC 2202469: Experimental Crystal Structure Determination

description: Related Article: Frank R Fronczek|2022|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: 10.6084/m9.figshare.21070381
title: Data.zip

description: Data presented in the article Relation between interfacial shear and friction force in 2D materials
DOI: 10.5281/zenodo.7062952
title: Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 0.5% spike-in contaminant sequences

description: Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision. Simulation Dataset 0.5% contaminant spike-in.
DOI: 10.5281/zenodo.7044728
title: Spekboom UAV imagery and reference data

description: Dataset and products for the publication <strong>Automated mapping of Portulacaria afra canopies for restoration monitoring with convolutional neural networks and heterogeneous unmanned aerial vehicle imagery</strong>.
DOI: 10.5281/zenodo.7044727
title: Spekboom UAV imagery and reference data

description: Dataset and products for the publication <strong>Automated mapping of Portulacaria afra canopies for restoration monitoring with convolutional neural networks and heterogeneous unmanned aerial vehicle imagery</strong>.
DOI: 10.6084/m9.figshare.16783048
title: Dataset for: Risk effects cascade up to an obligate scavenger

description: The file "Occupancy_Data" includes environmental information, details of deployment, and the use by Andean condors (<em>Vultur gryphus</em>) of 86 carrion stations monitored via camera traps in San Guillermo National Park (SGNP, Argentina). The file "Behavioral_Data" provides the composition and behavior of Andean condor foraging groups in a subset of 33 carrion stations; each row represents a camera trap picture.
DOI: 10.6084/m9.figshare.16783048.v1
title: Dataset for: Risk effects cascade up to an obligate scavenger

description: The file "Occupancy_Data" includes environmental information, details of deployment, and the use by Andean condors (<em>Vultur gryphus</em>) of 86 carrion stations monitored via camera traps in San Guillermo National Park (SGNP, Argentina). The file "Behavioral_Data" provides the composition and behavior of Andean condor foraging groups in a subset of 33 carrion stations; each row represents a camera trap picture.
DOI: 10.6084/m9.figshare.20966248
title: Abbasi-Ravasjani et al_Frontiers in Bioengineering and Biotechnology

description: Lack of bioactivity of three-dimensional (3D)-printed poly-є-caprolactone (PCL) scaffolds limits cell-material interactions in bone tissue engineering. This limitation can be overcome using surface-functionalization by glycosaminoglycan-like anionic polysaccharides, e.g. carboxymethyl cellulose (CMC), a plant-based carboxymethylated, unsulfated polysaccharide, and κ-carrageenan, a seaweed-derived sulfated, non-carboxymethylated polysaccharide. Sulfation of CMC and carboxymethylation of κ-carrageenan critically improve their bioactivity. This study showed for the first-time that surface-functionalization by SCMC is superior to CM-к-Car in increasing hydrophilicity and surface charge, as well as pre-osteoblast proliferation, and collagen production. However, CM-к-Car has an important advantage over SCMC in enhancing surface roughness, as well as promoting osteogenic differentiation of pre-osteoblasts. To the best of our knowledge, surface-functionalization by SCMC or CM-к-Car is a novel feasible strategy to enhance osteoblast proliferation and differentiation on biomaterials, which might improve bone regeneration and seamless biomaterial integration into the bone.
DOI: 10.6084/m9.figshare.20966248.v1
title: Abbasi-Ravasjani et al_Frontiers in Bioengineering and Biotechnology

description: Lack of bioactivity of three-dimensional (3D)-printed poly-є-caprolactone (PCL) scaffolds limits cell-material interactions in bone tissue engineering. This limitation can be overcome using surface-functionalization by glycosaminoglycan-like anionic polysaccharides, e.g. carboxymethyl cellulose (CMC), a plant-based carboxymethylated, unsulfated polysaccharide, and κ-carrageenan, a seaweed-derived sulfated, non-carboxymethylated polysaccharide. Sulfation of CMC and carboxymethylation of κ-carrageenan critically improve their bioactivity. This study showed for the first-time that surface-functionalization by SCMC is superior to CM-к-Car in increasing hydrophilicity and surface charge, as well as pre-osteoblast proliferation, and collagen production. However, CM-к-Car has an important advantage over SCMC in enhancing surface roughness, as well as promoting osteogenic differentiation of pre-osteoblasts. To the best of our knowledge, surface-functionalization by SCMC or CM-к-Car is a novel feasible strategy to enhance osteoblast proliferation and differentiation on biomaterials, which might improve bone regeneration and seamless biomaterial integration into the bone.
DOI: 10.34740/kaggle/dsv/4181423
title: Deep Shape From Template Dataset(DSfTD)
DOI: 10.34740/kaggle/dsv/4181517
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.7064649
title: TRUSTONOMY - Pilot 1 (ITS) Dataset

description: The following dataset contain information collected during the project TRUSTONOMY: Building Acceptance and Trust in Autonomous Mobility (H2020, MG 3.3 Grant no. 815003, 2018-2022). It presents the results of Pilaot 1 conducted by Motor Transport Institute (ITS) in Warsaw, Poland. The experiment was conducted on a high class passenger car simulator (automation level L4) and it<br> examined 5 of 6 Trustonomy pillars. The following dataset was compressed in order to reflect the data type especially for:<br> 1. HMI (SO2): verification of HMI time-based usability assessment methodology, data collection for ergonomic assessment,<br> 2. DT (SO4): conducting research on the suitability of the newly developed driver training course for human drivers of ADS in passenger cars,<br> 3. DIPA (SO5): data sample preparation, which will be used in tuning of DIPA model parameters and evaluation of the DIPA algorithm, DSM (SO1) and Trust & acceptance (SO6) pillars are extensively described in P3 (SCANIA) and P4 ULEEDS), therefore this dataset cannot be solely used to draw conclusions for those domains.<br> The dataset contains results collected only for 14 randomly chosen participants, while the research group was composed of 86 people. Therefore, the sample cannot be used to draw any conclusions. The results are presented in .csv file named <em>”Trustonomy results_ P1 ITS_open access”</em>. They should<br> be analysed with a particular emphasis on fields description provided in another .csv file <em>“Trustonomy<br> results_ P1 ITS_open access_labels”</em>.
DOI: 10.5281/zenodo.7064648
title: TRUSTONOMY - Pilot 1 (ITS) Dataset

description: The following dataset contain information collected during the project TRUSTONOMY: Building Acceptance and Trust in Autonomous Mobility (H2020, MG 3.3 Grant no. 815003, 2018-2022). It presents the results of Pilaot 1 conducted by Motor Transport Institute (ITS) in Warsaw, Poland. The experiment was conducted on a high class passenger car simulator (automation level L4) and it<br> examined 5 of 6 Trustonomy pillars. The following dataset was compressed in order to reflect the data type especially for:<br> 1. HMI (SO2): verification of HMI time-based usability assessment methodology, data collection for ergonomic assessment,<br> 2. DT (SO4): conducting research on the suitability of the newly developed driver training course for human drivers of ADS in passenger cars,<br> 3. DIPA (SO5): data sample preparation, which will be used in tuning of DIPA model parameters and evaluation of the DIPA algorithm, DSM (SO1) and Trust & acceptance (SO6) pillars are extensively described in P3 (SCANIA) and P4 ULEEDS), therefore this dataset cannot be solely used to draw conclusions for those domains.<br> The dataset contains results collected only for 14 randomly chosen participants, while the research group was composed of 86 people. Therefore, the sample cannot be used to draw any conclusions. The results are presented in .csv file named <em>”Trustonomy results_ P1 ITS_open access”</em>. They should<br> be analysed with a particular emphasis on fields description provided in another .csv file <em>“Trustonomy<br> results_ P1 ITS_open access_labels”</em>.
DOI: 10.5517/ccdc.csd.cc2bvpnk
title: CCDC 2170609: Experimental Crystal Structure Determination

description: Related Article: Ferdinand Belaj, Antoine Dupe, Nadia C. Mösch-Zanetti|2022|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.cc2bvppl
title: CCDC 2170610: Experimental Crystal Structure Determination

description: Related Article: Ferdinand Belaj, Michael Tüchler, Nadia C. Mösch-Zanetti|2022|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.cc2bvpvr
title: CCDC 2170615: Experimental Crystal Structure Determination

description: Related Article: Ferdinand Belaj, Christof Holzer, Nadia C. Mösch-Zanetti|2022|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: 10.5281/zenodo.7002739
title: A key residue of plant ABC transporter modulates access path geometry and phenylpropanoid substrate selectivity

description: The input and main output files used for the paper <em><strong>"A key residue of plant ABC transporter modulates access path geometry and phenylpropanoid substrate selectivity"</strong></em> are separated in the different tar files depending the MD stage they belong to. <strong>Content</strong> 00_AlphaFold2: The models predicted from AlphaFold2 01_build_system: The parameters for ATP and the initial pdb file used to build each system 02_minimization: Minimization input files for each variant 03_equilibration: Equilibration input files for each variant 04_long_equilibration: ATP restrained equilibration input files for each variant 05_free_equilibration: Free equilibration input files for each variant 06_production: Free production input files for each variant 07_caver: Caver calculations for each variant and replica 08_transport_tools: Analysis of tunnel networks using TransportTools software 09_tunnel_selection: Selection of the tunnels with widest bottleneck radius to perform CaverDock experiments 10_caverdock: CaverDock calculations for each variant and for each ligand tested 11_membrane_patch: MD simulations for liquiritigenin and POPC membrane only<br>