cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22189693.v2
title: Location, vegetation, climate, and soils information from global paired eddy covariance towers

description: The name, location, pair number (if applicable), and climate, vegetation, and soils information for global paired ("Appendix A_paired") eddy covariance sites and global ("Appendix B_total") eddy covariance sites. "_ds" refers to climate data obtained through global databases. Climate data from databases was obtained from WorldClim 2.1 (Fick and Hijmans, 2017, https://doi.org/10.1002/joc.5086. Soils data were obtained from the top 0-5 cm depths from the SoilGrid 2.0 database (Poggio et al., 2021, https://doi.org/10.5194/soil-7-217-2021). MAT = mean annual temperature. MAP = mean annual precipitation. SRAD = solar radiation. bdod = bulk density. cec = cation exchange capacity. N = soil nitrogen content. pH = soil pH. soc = soil organic carbon content.
DOI: 10.5517/ccdc.csd.cc2507dv
title: CCDC 1996226: Experimental Crystal Structure Determination

description: Related Article: İlker Avan, İbrahim Kani, Leyla Çalıkuşu|2023|Inorg.Chem.Commun.|150|110518|doi:10.1016/j.inoche.2023.110518
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.cc250d4r
title: CCDC 1996373: Experimental Crystal Structure Determination

description: Related Article: İlker Avan, İbrahim Kani, Leyla Çalıkuşu|2023|Inorg.Chem.Commun.|150|110518|doi:10.1016/j.inoche.2023.110518
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.cc27rr92
title: CCDC 2078404: Experimental Crystal Structure Determination

description: Related Article: Yan He, Qimeng Liu, Tian Gong, Yunfei Liu, Xinying Zhang, Xuesen Fan|2023|Org.Chem.Front.|10|1206|doi:10.1039/D2QO01427K
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.cc28qdq4
title: CCDC 2106906: Experimental Crystal Structure Determination

description: Related Article: Devenderan Ramanathan, Qinglong Shi, Meichen Xu, Rui Chang, Beatriz Peñín, Ignacio Funes-Ardoiz, Juntao Ye|2023|Org.Chem.Front.|10|1182|doi:10.1039/D2QO01979E
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.cc28qdr5
title: CCDC 2106907: Experimental Crystal Structure Determination

description: Related Article: Devenderan Ramanathan, Qinglong Shi, Meichen Xu, Rui Chang, Beatriz Peñín, Ignacio Funes-Ardoiz, Juntao Ye|2023|Org.Chem.Front.|10|1182|doi:10.1039/D2QO01979E
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.cc2b8p0b
title: CCDC 2153291: Experimental Crystal Structure Determination

description: Related Article: Jinyun Luo, Muze Lin, Dengpeng Xia, Guangfen Du, Zhihua Cai, Bin Dai, Lin He|2023|Org.Chem.Front.|10|1224|doi:10.1039/D2QO01855A
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.cc2bmfl0
title: CCDC 2163632: Experimental Crystal Structure Determination

description: Related Article: Ying Zou, Wei Lv, Zhen-Zhen Xue, Jin-Hua Li, Xiao-Yu Li, Guo-Ming Wang|2023|Inorg.Chem.Front.|10|1614|doi:10.1039/D2QI02461F
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.cc2bmfm1
title: CCDC 2163633: Experimental Crystal Structure Determination

description: Related Article: Ying Zou, Wei Lv, Zhen-Zhen Xue, Jin-Hua Li, Xiao-Yu Li, Guo-Ming Wang|2023|Inorg.Chem.Front.|10|1614|doi:10.1039/D2QI02461F
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.cc2bprqj
title: CCDC 2165868: Experimental Crystal Structure Determination

description: Related Article: Muhammad Adnan Bashir, Xuanjie Chen, Tie Wang, Hui Guo, Hongbin Zhai|2023|Org.Chem.Front.|10|1213|doi:10.1039/D2QO01916G
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.cc2brr40
title: CCDC 2167772: Experimental Crystal Structure Determination

description: Related Article: Romana Mičová, Cyril Rajnák, Ján Titiš, Erika Samoľová, Michal Zalibera, Alina Bieńko, Roman Boča|2023|Chem.Commun.|59|2612|doi:10.1039/D2CC06510J
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.21788666.v1
title: Supplementary_Dataset_S1

description: “Supplementary Dataset S1” contains the results of blastn search using reference transcriptome sequences and registered genomic sequences in NCBI.
DOI: 10.18434/mds2-1902
title: Hestia Fossil Fuel Carbon Dioxide Emissions Inventory for Urban Regions
DOI: 10.6084/m9.figshare.21082441
title: Simulation of 40 Selected German Farm neighborhoods with LoRaWAN-based DTN

description: This archive contains simulation results as well as the raw simulation files, conducted with "The-One" [1]. Results are used to get statistics about DTN based farm neighborhood communication in small-sized clusters up to 116 farms. <br> Data Used for Simulation <br> Base data set consists of 40 cluster of German farms. Each cluster has multiple geographic locations (points), representing a farm building, that has at maximum a distance (euclidean) of 2000m to another farm. <br> There are two scenarios, with each: simulation data: simulation parameter description (.json) configuration and report files for each cluster (0..39) result graphics (.eps) and statistics (.tex) <br> static Scenario <em>static</em> has following relevant parameters: one static agent for each farm position with LoRa and WiFi interface simulation time: 43200s message_interval: 1800s / count of all agents message size (random): 80 - 500 byte lora transmit speed: 7kbps lora transmit range: 2000 wifi transmit speed: 6750k wifi transmit range: 100m routing: Epidemic, PRoPHET mobile Scenario <em>mobile</em> has following relevant parameters: one static agent for each farm position with LoRa and WiFi interface one mobile agent for each farm with WiFi interface, moving on paths simulation time: 43200s message_interval: 3600s / count of all agents message size (random): 80 - 500 bytes lora transmit speed: 7kbps lora transmit range: 2000m wifi transmit speed: 6750k wifi transmit range: 100m routing: Epidemic, PRoPHET movement speed of mobile agents (random): 1.0 - 1.5 m/s <br> Resources [1] http://akeranen.github.io/the-one/ <br>
DOI: 10.6084/m9.figshare.21082441.v1
title: Simulation of 40 Selected German Farm neighborhoods with LoRaWAN-based DTN

description: This archive contains simulation results as well as the raw simulation files, conducted with "The-One" [1]. Results are used to get statistics about DTN based farm neighborhood communication in small-sized clusters up to 116 farms. <br> Data Used for Simulation <br> Base data set consists of 40 cluster of German farms. Each cluster has multiple geographic locations (points), representing a farm building, that has at maximum a distance (euclidean) of 2000m to another farm. <br> There are two scenarios, with each: simulation data: simulation parameter description (.json) configuration and report files for each cluster (0..39) result graphics (.eps) and statistics (.tex) <br> static Scenario <em>static</em> has following relevant parameters: one static agent for each farm position with LoRa and WiFi interface simulation time: 43200s message_interval: 1800s / count of all agents message size (random): 80 - 500 byte lora transmit speed: 7kbps lora transmit range: 2000 wifi transmit speed: 6750k wifi transmit range: 100m routing: Epidemic, PRoPHET mobile Scenario <em>mobile</em> has following relevant parameters: one static agent for each farm position with LoRa and WiFi interface one mobile agent for each farm with WiFi interface, moving on paths simulation time: 43200s message_interval: 3600s / count of all agents message size (random): 80 - 500 bytes lora transmit speed: 7kbps lora transmit range: 2000m wifi transmit speed: 6750k wifi transmit range: 100m routing: Epidemic, PRoPHET movement speed of mobile agents (random): 1.0 - 1.5 m/s <br> Resources [1] http://akeranen.github.io/the-one/ <br>
DOI: 10.25921/04pf-zh25
title: EK60 Water Column Sonar Data Collected During EX2204
DOI: 10.5281/zenodo.7034378
title: Data for "A versatile platform for graphene nanoribbon synthesis, electronic decoupling, and spin polarized measurements"

description: Data for figures of the main and supplemental part of "A versatile platform for graphene nanoribbon synthesis, electronic decoupling, and spin polarized measurements" by Cahlík et al., Nanoscale Advances (2023)
DOI: 10.5281/zenodo.7034377
title: Data for "A versatile platform for graphene nanoribbon synthesis, electronic decoupling, and spin polarized measurements"

description: Data for figures of the main and supplemental part of "A versatile platform for graphene nanoribbon synthesis, electronic decoupling, and spin polarized measurements" by Cahlík et al., Nanoscale Advances (2023)
DOI: 10.21227/vdfg-qj56
title: Graph dataset - LibTiff

description: A comparative, empirical study of state-of-the-art contrastive and generative graph learning models applied to source and binary software fragments drawn from the National Vulnerability Database (NVD) reveals that Graph Masked Auto-Encoders show exceptional promise for detecting security vulnerabilities, outperforming all other baseline models in the study. This fills a key gap in the literature on automated and machine-assisted discovery and patching of software security vulnerabilities, which has become increasingly critical with the dramatic increase in modern software complexity, but for which Graph Neural Network (GNN) approaches are understudied relative to traditional processes, such as manual source code auditing and fuzzing.To conduct the study, a novel dataset is first collected by extracting vulnerable code fragments from six applications with NVD-documented security flaws and converting these codes to five different graph types using specialized tools based on code property graphs and binary semantics lifting. The resulting dataset is applied to GNN-based analyses to determine which algorithm and graph type performs best, followed by an ablation study to determine which combination of parameters maximizes effectiveness of the top-performing detector. The study is the first to train GNN models on a combination of source- and binary-level code features, which is important for helping cyber defenders craft source-level patches that defend against binary-level attacks.
DOI: 10.6084/m9.figshare.21788624
title: Supplementary_Information

description: “Supplementary Information” contains addresses to reference genome information, addresses to web sites, and the data supporting the findings on the ice plant genome function.
DOI: 10.6084/m9.figshare.21788624.v5
title: Supplementary_Information

description: “Supplementary Information” contains addresses to reference genome information, addresses to web sites, and the data supporting the findings on the ice plant genome function.
DOI: 10.6084/m9.figshare.21788624.v4
title: Supplementary_Information

description: “Supplementary Information” contains addresses to reference genome information, addresses to web sites, and the data supporting the findings on the ice plant genome function.
DOI: 10.14272/ndlirbzkzsdgso-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (N-diazo-4-methylbenzenesulfonamide)
title: InChI=1S/C7H7N3O2S/c1-6-2-4-7(5-3-6)13(11,12)10-9-8/h2-5H,1H3

description: dataset for mass spectrometry (MS) MS (EI, 70 eV, 20 °C), m/z (%): 197 (17) [M]+, 155 (74) [M – N3]+, 92 (7) [M – SO2N3 + H]+, 91 (100) [M – SO2N3]+.HRMS–EI (m/z): [M]+ calcd for 197.0254; found 197.0253.
DOI: 10.14272/ndlirbzkzsdgso-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) (N-diazo-4-methylbenzenesulfonamide)
title: InChI=1S/C7H7N3O2S/c1-6-2-4-7(5-3-6)13(11,12)10-9-8/h2-5H,1H3

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 2122 (vs), 1595 (w), 1494 (w), 1451 (w), 1398 (w), 1367 (vs), 1307 (w), 1296 (w), 1188 (s), 1163 (vs), 1120 (m), 1085 (s), 1041 (w), 1017 (w), 975 (w), 956 (w), 909 (w), 857 (w), 839 (w), 813 (s), 800 (m), 744 (vs), 703 (m), 659 (vs), 591 (vs), 552 (m), 538 (vs), 501 (m), 462 (w), 455 (w), 446 (w), 436 (w), 422 (w), 405 (w), 385 (w) cm–1.
DOI: 10.14272/ndlirbzkzsdgso-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (N-diazo-4-methylbenzenesulfonamide)
title: InChI=1S/C7H7N3O2S/c1-6-2-4-7(5-3-6)13(11,12)10-9-8/h2-5H,1H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, Chloroform-d, ppm) δ = 7.88–7.86 (m, 2H, CHAr), 7.43 (d, J = 8.1 Hz, 2H, CHAr), 2.54–2.47 (s, 3H, CH3).Impurities: Water in CDCl3 (1.54 ppm)
DOI: 10.14272/ndlirbzkzsdgso-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (N-diazo-4-methylbenzenesulfonamide)
title: InChI=1S/C7H7N3O2S/c1-6-2-4-7(5-3-6)13(11,12)10-9-8/h2-5H,1H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, Chloroform-d, ppm) δ = 146.2 (1C, Cq), 135.6 (1C, Cq), 130.3 (2C, CArH), 127.6 (2C, CArH), 21.8 (CH3).
DOI: 10.14272/ndlirbzkzsdgso-uhfffaoysa-n/chmo0000596
title: distortionless enhancement with polarization transfer (DEPT) (N-diazo-4-methylbenzenesulfonamide)
title: InChI=1S/C7H7N3O2S/c1-6-2-4-7(5-3-6)13(11,12)10-9-8/h2-5H,1H3

description: dataset for distortionless enhancement with polarization transfer (DEPT)
DOI: 10.14272/ndlirbzkzsdgso-uhfffaoysa-n.1
title: tosylazid
title: InChI=1S/C7H7N3O2S/c1-6-2-4-7(5-3-6)13(11,12)10-9-8/h2-5H,1H3

description: This dataset contains experimental data from a sample (N-diazo-4-methylbenzenesulfonamide, InChI=1S/C7H7N3O2S/c1-6-2-4-7(5-3-6)13(11,12)10-9-8/h2-5H,1H3). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) mass spectrometry (MS) infrared absorption spectroscopy (IR) distortionless enhancement with polarization transfer (DEPT)
DOI: 10.5066/p9420wxu
title: Total and Dissolved Organic Carbon Data to Support Implementation of Revised Freshwater Aluminum Water-Quality Criteria in Massachusetts

description: This data set contains historical data on concentrations of total and dissolved organic carbon in Massachusetts streams from the U.S. Geological Survey National Water Information System (NWIS) database. The data were compiled from NWIS using site and sample selection criteria to retrieve all publicly available data from surface-water samples that contained analysis of both total and dissolved organic carbon. The data set was screened, as much as possible from the site and sample description information in NWIS, to retain only routine environmental samples from stream sites. The final data set consists of 223 samples from 52 sites and were collected from 1978 to 2007.
DOI: 10.6084/m9.figshare.22190026
title: 6-minRT spreadsheet

description: 6-minRT spreadsheet
DOI: 10.5281/zenodo.7680172
title: IMPROVER: the new probabilistic post processing system at the UK Met Office: BAMS paper Data

description: © Crown Copyright, Met Office This is the data associated with the figures in the IMPROVER BAMS paper 2023: https://doi.org/10.1175/BAMS-D-21-0273.1. Gridded data is in CF-NetCDF with reasonably self explanatory metadata, other data such as for Figure 9's wind speed calibration is in CSV.
description: {"references": ["Roberts, Nigel et al. 2023: IMPROVER: the new probabilistic post processing system at the UK Met Office: BAMS"]}
DOI: 10.5281/zenodo.7680171
title: IMPROVER: the new probabilistic post processing system at the UK Met Office: BAMS paper Data

description: © Crown Copyright, Met Office This is the data associated with the figures in the IMPROVER BAMS paper 2023: https://doi.org/10.1175/BAMS-D-21-0273.1. Gridded data is in CF-NetCDF with reasonably self explanatory metadata, other data such as for Figure 9's wind speed calibration is in CSV.
description: {"references": ["Roberts, Nigel et al. 2023: IMPROVER: the new probabilistic post processing system at the UK Met Office: BAMS"]}
DOI: 10.5066/p9irzl8s
title: CE-QUAL-W2 water-quality model and data for Berlin Lake, Lake Milton, Michael J Kirwan Reservoir, Mosquito Creek Lake, and the Mahoning River, Ohio

description: The U.S. Army Corps of Engineers is considering changing the operations of Berlin Lake, Lake Milton, Michael J Kirwan Reservoir, and Mosquito Creek Lake. The lakes in this study are all reservoirs, formed by dams. These models were constructed to simulate those operations and document possible water-quality effects in the lakes, the lake outflows, and the Mahoning River downstream of the lakes. This data release includes U.S. Army Corps of Engineers water-quality data and the input and output files from the mechanistic water-quality models (CE-QUAL-W2).
DOI: 10.25345/c5gm81z6z
title: MassIVE MSV000091378 - (glyco)-HSP27 binding partners
title: Semisynthetic HSP27 with or without O-GlcNacylation was used as bait to enrich for binding partners. Following enrichment, proteins were separated by SDS-PAGE and subjected to reduction/alkylation followed by trypsin digestion. Samples were desalted using C18 resin and purified peptides subjected to LC-MS/MS analysis over a 90 min gradient.
DOI: 10.7924/r4v40x41n
title: Data from: Chiral perovskite nanoplatelets with tunable circularly polarized luminescence in the strong confinement regime

description: Chiral perovskite nanocrystals have emerged as an interesting chiral excitonic platform that combines both structural flexibility and superior optoelectronic properties. Despite several recent demonstrations of optical activity in various chiral perovskite nanocrystals, efficient circularly polarized luminescence (CPL) with tunable energies remains a challenge. The chirality imprinting mechanism as a function of perovskite nanocrystal dimensionality remains elusive. Here, atomically thin inorganic perovskite nanoplatelets (NPLs) are synthesized with precise control of layer thickness and are functionalized by chiral surface ligands, serving as a unique platform to probe the chirality transfer mechanism at the organic/perovskite interface. It is found that chirality is successfully imprinted into mono-, bi-‚ and tri-layer inorganic perovskite NPLs, exhibiting tunable circular dichroism (CD) and CPL responses. However, chirality transfer decreases in thicker NPLs, resulting in decreased CD and CPL dissymmetry factors for thicker NPLs. Aided by large-scale first-principles calculations, it is proposed that chirality transfer is mainly mediated through a surface distortion rather than a hybridization of electronic states, giving rise to symmetry breaking in the perovskite lattice and spin-split conduction bands. The findings described here provide an in-depth understanding of chirality transfer and design principles for distorted-surface perovskites for chiral photonic applications.
DOI: 10.6084/m9.figshare.22190053
title: AJP-renal supplemental 4

description: Statistical correlation analysis for submitted Amerian Journal of Physiology paper
DOI: 10.6084/m9.figshare.22190053.v1
title: AJP-renal supplemental 4

description: Statistical correlation analysis for submitted Amerian Journal of Physiology paper
DOI: 10.6084/m9.figshare.22190116
title: Totoaba reference transcriptome assembly statistics

description: Totoaba reference transcriptome assembly statistics
DOI: 10.6084/m9.figshare.22190116.v1
title: Totoaba reference transcriptome assembly statistics

description: Totoaba reference transcriptome assembly statistics
DOI: 10.5281/zenodo.7683242
title: Data for Cooper et al., 2023, 4D tomography reveals a complex relationship between wormhole advancement and permeability variation in dissolving rocks, Advances in Water Resources

description: Tomography dataset associated with Cooper, et al. (2023), "4D tomography reveals a complex relationship between wormhole advancement and permeability variation in dissolving rocks" in Advances in Water Resources.
description: Total unzipped file size is ~150GB. Files should be unzipped in a directory if running processing code.
DOI: 10.5281/zenodo.7683240
title: Data for Cooper et al., 2023, 4D tomography reveals a complex relationship between wormhole advancement and permeability variation in dissolving rocks, Advances in Water Resources

description: Tomography dataset associated with Cooper, et al. (2023), "4D tomography reveals a complex relationship between wormhole advancement and permeability variation in dissolving rocks" in Advances in Water Resources.
description: Total unzipped file size is ~150GB. Files should be unzipped in a directory if running processing code.