cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23451536.v1
title: Table S3 Traits information.xlsx from Functional traits trade-offs define plant population stability across different biomes

description: Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species' ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability.
DOI: 10.6084/m9.figshare.23451536
title: Table S3 Traits information.xlsx from Functional traits trade-offs define plant population stability across different biomes

description: Ecological theory posits that temporal stability patterns in plant populations are associated with differences in species' ecological strategies. However, empirical evidence is lacking about which traits, or trade-offs, underlie species stability, especially across different biomes. We compiled a worldwide collection of long-term permanent vegetation records (greater than 7000 plots from 78 datasets) from a large range of habitats which we combined with existing trait databases. We tested whether the observed inter-annual variability in species abundance (coefficient of variation) was related to multiple individual traits. We found that populations with greater leaf dry matter content and seed mass were more stable over time. Despite the variability explained by these traits being low, their effect was consistent across different datasets. Other traits played a significant, albeit weaker, role in species stability, and the inclusion of multi-variate axes or phylogeny did not substantially modify nor improve predictions. These results provide empirical evidence and highlight the relevance of specific ecological trade-offs, i.e. in different resource-use and dispersal strategies, for plant populations stability across multiple biomes. Further research is, however, necessary to integrate and evaluate the role of other specific traits, often not available in databases, and intraspecific trait variability in modulating species stability.
DOI: 10.6084/m9.figshare.23299157
title: <strong>Relationships between fault friction, slip time, and physical parameters explored by experiment-based friction model: A Machine Learning Approach Using Recurrent Neural Networks (RNNs)</strong>

description: 1. 'Raw Data (HVR1087)': This dataset contains raw experimental data from the HVR1087 experiment. It includes parameters such as slip velocity, accumulated slip, axial shortening, normal stress, shear stress, temperature, and friction. The units for each parameter are provided within the file. The file is formatted as a CSV (Comma eparated Values) file. <br> 2. 'Analyzed Data (HVR1087)': This file consists of data that has been processed and used for machine learning analysis in the current study. The parameters contained in this file, including Average slip velocity, Average axial shortening, Average normal stress, Average shear stress, Average friction, Average temperature, Rate of temperature, Rate of axial shortening, and Power density, were calculated based on the 'Raw data (HVR1087)'. The units for each parameter are provided within the file. This data is also formatted as a CSV file. <br> 3. 'Constructing Model': This file contains the script or code used to carry out machine learning analysis in this study. It includes procedures such as data preprocessing, data splitting, construction of the training model, plotting of validation and test data, and tracing of gradient importance. Additionally, it provides information regarding the hyperparameters used in the study ('#ref'). The file format for this data is .ipynb, and it is compatible with Jupyter Notebooks.
DOI: 10.6084/m9.figshare.23299157.v2
title: <strong>Relationships between fault friction, slip time, and physical parameters explored by experiment-based friction model: A Machine Learning Approach Using Recurrent Neural Networks (RNNs)</strong>

description: 1. 'Raw Data (HVR1087)': This dataset contains raw experimental data from the HVR1087 experiment. It includes parameters such as slip velocity, accumulated slip, axial shortening, normal stress, shear stress, temperature, and friction. The units for each parameter are provided within the file. The file is formatted as a CSV (Comma eparated Values) file. <br> 2. 'Analyzed Data (HVR1087)': This file consists of data that has been processed and used for machine learning analysis in the current study. The parameters contained in this file, including Average slip velocity, Average axial shortening, Average normal stress, Average shear stress, Average friction, Average temperature, Rate of temperature, Rate of axial shortening, and Power density, were calculated based on the 'Raw data (HVR1087)'. The units for each parameter are provided within the file. This data is also formatted as a CSV file. <br> 3. 'Constructing Model': This file contains the script or code used to carry out machine learning analysis in this study. It includes procedures such as data preprocessing, data splitting, construction of the training model, plotting of validation and test data, and tracing of gradient importance. Additionally, it provides information regarding the hyperparameters used in the study ('#ref'). The file format for this data is .ipynb, and it is compatible with Jupyter Notebooks.
DOI: 10.6084/m9.figshare.23299157.v1
title: <strong>Relationships between fault friction, slip time, and physical parameters explored by experiment-based friction model: A Machine Learning Approach Using Recurrent Neural Networks (RNNs)</strong>

description: The dataset encompasses information pertaining to the physical parameters of the experimental fault slip surface during High Velocity Rotary Shear (HVR) tests. These experiments were conducted on diorite specimens at a consistent slip velocity of 0.004 m/s under a range of normal stress conditions, specifically between 0.3 and 5.8 MPa.
DOI: 10.6084/m9.figshare.23004563.v16
title: <strong>Diurnal versus nocturnal pollination in a subalpine wetland: from network structure to plant reproduction - Dataset</strong>

description: Dataset associated with the manuscript "<strong>Diurnal versus nocturnal pollination in a subalpine wetland: from network structure to plant reproduction</strong>" . Our study is the first to compare diurnal and nocturnal pollination networks from both the structural and reproductive perspectives.The results demonstrated that both diurnal and nocturnal pollinators played a significant role in plant reproduction, and the contribution to the reproduction of each plant might be species-specific.
DOI: 10.5281/zenodo.8020069
title: Data for A system design approach toward integrated cryogenic quantum control systems

description: Data for A system design approach toward integrated cryogenic quantum control systems.
DOI: 10.5281/zenodo.8020068
title: Data for A system design approach toward integrated cryogenic quantum control systems

description: Data for A system design approach toward integrated cryogenic quantum control systems.
DOI: 10.5281/zenodo.7781000
title: Low temperature magnetic properties of variably oxidized natural and synthetic siderite Dekkers et al., 2023, G-cubed

description: The data magnetometric measurements performed on natural and synthetic iron carbonates presented in Dekkers et al. (2023) submitted to G-cubed. Details on the samples and methods can be found in the manuscript and the Additional Supporting Information
DOI: 10.24432/c5rw2f
title: Annealing
DOI: 10.24432/c5vs3q
title: Anonymous Microsoft Web Data
DOI: 10.24432/c5303z
title: Artificial Characters
DOI: 10.24432/c5m59m
title: Audiology (Original)
DOI: 10.24432/c5tp4r
title: Audiology (Standardized)
DOI: 10.24432/c5xw3c
title: Badges
DOI: 10.15132/10000211
title: Lighthouse

description: Abstract
Lighthouse laboratories [high-throughput facilities dedicated to COVID-19]
Documentation
ECOSS is a database that holds surveillance data on various microorganisms (e.g. influenza virus, coronavirus) and infections reported from NHS diagnostic and reference laboratories and Pillar 2 facilities/Lighthouse laboratories [high-throughput facilities dedicated to COVID-19 viral Reverse Transcription-Polymerase Chain Reaction (RT-PCR) testing for the National Testing Programme]. Data on laboratory results for all SARS-CoV-2 RT-PCR tests carried out in Scotland are being collated by ECOSS and can be linked to other data sources.
DOI: 10.24432/c5bp4d
title: Balloons
DOI: 10.24432/c5rp5h
title: Pittsburgh Bridges
DOI: 10.24432/c56w2g
title: Chess (King-Rook vs. King-Knight)
DOI: 10.24432/c5dk5c
title: Chess (King-Rook vs. King-Pawn)
DOI: 10.24432/c57w2s
title: Chess (King-Rook vs. King)
DOI: 10.24432/c5ps35
title: Chess (Domain Theories)
DOI: 10.24432/c5gc7p
title: Bach Chorales
DOI: 10.24432/c59p43
title: Connect-4
DOI: 10.24432/c5259n
title: Japanese Credit Screening
DOI: 10.24432/c50c7b
title: Cylinder Bands
DOI: 10.24432/c5p02v
title: DGP2 - The Second Data Generation Program
DOI: 10.24432/c5260k
title: Document Understanding
DOI: 10.24432/c58p6j
title: EBL Domain Theories
DOI: 10.24432/c5qw24
title: Echocardiogram
DOI: 10.24432/c52c7z
title: Flags
DOI: 10.6084/m9.figshare.23451509
title: SP closed form.cif

description: Spirofuran covalent organic framework, Covalent organic framework, spiropyran, photoresponsive, self-assembly, vesicles
DOI: 10.6084/m9.figshare.23451509.v1
title: SP closed form.cif

description: Spirofuran covalent organic framework, Covalent organic framework, spiropyran, photoresponsive, self-assembly, vesicles
DOI: 10.24432/c57w35
title: Function Finding
DOI: 10.24432/c58w23
title: Horse Colic
DOI: 10.24432/c53k7b
title: ICU
DOI: 10.24432/c5gp4n
title: Image Segmentation
DOI: 10.24432/c5v011
title: Internet Advertisements
DOI: 10.24432/c5ws4d
title: Kinship
DOI: 10.24432/c5cp4q
title: Labor Relations
DOI: 10.24432/c5fg61
title: LED Display Domain
DOI: 10.24432/c5k88z
title: Lenses
DOI: 10.24432/c5dg73
title: Logic Theorist
DOI: 10.24432/c5vg74
title: Mechanical Analysis
DOI: 10.24432/c5x31p
title: Meta-data
DOI: 10.24432/c5g881
title: Mobile Robots
DOI: 10.24432/c5sp4f
title: Molecular Biology (Protein Secondary Structure)
DOI: 10.24432/c56w47
title: Moral Reasoner
DOI: 10.24432/c51608
title: Musk (Version 2)
DOI: 10.24432/c58w3g
title: Othello Domain Theory
DOI: 10.24432/c5dg6q
title: Post-Operative Patient
DOI: 10.24432/c5603w
title: Prodigy
DOI: 10.24432/c5tp54
title: Qualitative Structure Activity Relationships
DOI: 10.24432/c5860f
title: Quadruped Mammals
DOI: 10.24432/c57s34
title: Shuttle Landing Control
DOI: 10.24432/c5530g
title: Solar Flare
DOI: 10.24432/c5ds3p
title: Soybean (Small)
DOI: 10.24432/c5pw2t
title: Challenger USA Space Shuttle O-Ring
DOI: 10.24432/c5b02r
title: Low Resolution Spectrometer
DOI: 10.24432/c5330v
title: Sponge
DOI: 10.24432/c5xs3b
title: Statlog Project
DOI: 10.24432/c5cp53
title: Student Loan Relational
DOI: 10.24432/c5m01v
title: Trains
DOI: 10.24432/c5ww32
title: University
DOI: 10.24432/c5cs3c
title: Waveform Database Generator (Version 1)
DOI: 10.24432/c5j619
title: Undocumented
DOI: 10.24432/c59w45
title: Coil 1999 Competition Data
DOI: 10.24432/c5k599
title: Corel Image Features
DOI: 10.24432/c5zc71
title: E. Coli Genes
DOI: 10.24432/c5wg62
title: El Nino
DOI: 10.24432/c5088p
title: Entree Chicago Recommendation Data
DOI: 10.24432/c5jc79
title: CMU Face Images
DOI: 10.24432/c5q60g
title: Internet Usage Data
DOI: 10.24432/c5bg63
title: IPUMS Census Database
DOI: 10.24432/c5rw3t
title: M. Tuberculosis Genes
DOI: 10.24432/c5sw2r
title: Movie
DOI: 10.24432/c5390x
title: MSNBC.com Anonymous Web Data
DOI: 10.24432/c55c9n
title: NSF Research Award Abstracts 1990-2003
DOI: 10.24432/c5bs5t
title: Pioneer-1 Mobile Robot Data
DOI: 10.24432/c5m89n
title: Robot Execution Failures
DOI: 10.24432/c59g75
title: Synthetic Control Chart Time Series
DOI: 10.24432/c5z88c
title: Syskill and Webert Web Page Ratings
DOI: 10.24432/c5302k
title: UNIX User Data
DOI: 10.24432/c5sw34
title: Volcanoes on Venus - JARtool experiment
DOI: 10.24432/c5p01g
title: Statlog (Image Segmentation)
DOI: 10.24432/c5hg6n
title: Statlog (Vehicle Silhouettes)
DOI: 10.24432/c5vp6t
title: Connectionist Bench (Nettalk Corpus)
DOI: 10.24432/c58p4s
title: Connectionist Bench (Vowel Recognition - Deterding Data)
DOI: 10.24432/c5qs3g
title: Economic Sanctions
DOI: 10.24432/c5n88k
title: Protein Data
DOI: 10.24432/c5359z
title: Cloud
DOI: 10.24432/c5ng78
title: CalIt2 Building People Counts
DOI: 10.24432/c5731g
title: UJI Pen Characters
DOI: 10.24432/c5m90k
title: Reuters Transcribed Subset
DOI: 10.24432/c5jc8p
title: Hill-Valley
DOI: 10.24432/c58p55
title: Arcene
DOI: 10.24432/c5p898
title: Dexter
DOI: 10.24432/c5nk6x
title: Dorothea
DOI: 10.24432/c5zk6q
title: Abscisic Acid Signaling Network
DOI: 10.24432/c5fg8s
title: UJI Pen Characters (Version 2)
DOI: 10.24432/c5sc8v
title: Semeion Handwritten Digit
DOI: 10.24432/c5gc82
title: Libras Movement
DOI: 10.24432/c5h89q
title: URL Reputation
DOI: 10.24432/c54899
title: Demospongiae
DOI: 10.24432/c57c8w
title: Wall-Following Robot Navigation Data
DOI: 10.24432/c52c9q
title: Spoken Arabic Digit
DOI: 10.24432/c57g8x
title: Localization Data for Person Activity
DOI: 10.24432/c5690v
title: AutoUniv
DOI: 10.24432/c5j88n
title: Steel Plates Faults
DOI: 10.24432/c5qc87
title: MiniBooNE particle identification
DOI: 10.24432/c5qw4w
title: OpinRank Review Dataset
DOI: 10.24432/c5cp6g
title: Relative location of CT slices on axial axis
DOI: 10.24432/c50c8q
title: Online Handwritten Assamese Characters Dataset
DOI: 10.24432/c5fk62
title: PubChem Bioassay Data
DOI: 10.24432/c51k6b
title: Record Linkage Comparison Patterns
DOI: 10.24432/c5mg7z
title: Vicon Physical Action Data Set
DOI: 10.24432/c5ds42
title: Reuter_50_50
DOI: 10.24432/c5zc8d
title: Farm Ads
DOI: 10.24432/c5589m
title: DBWorld e-mails
DOI: 10.24432/c5ck52
title: KEGG Metabolic Relation Network (Directed)
DOI: 10.24432/c5g609
title: KEGG Metabolic Reaction Network (Undirected)
DOI: 10.24432/c5102z
title: YouTube Comedy Slam Preference Data
DOI: 10.24432/c53g79
title: Nomao
DOI: 10.24432/c5t023
title: Planning Relax
DOI: 10.24432/c5dp41
title: Restaurant & consumer data
DOI: 10.24432/c51g7p
title: CNAE-9
DOI: 10.24432/c5m60j
title: Northix
DOI: 10.24432/c5zs41
title: Legal Case Reports
DOI: 10.24432/c5rg76
title: One-hundred plant species leaves data set
DOI: 10.24432/c56k78
title: Daphnet Freezing of Gait
DOI: 10.24432/c56g6v
title: Buzz in social media
DOI: 10.24432/c5rc9x
title: First-order theorem proving
DOI: 10.24432/c54w37
title: Wearable Computing: Classification of Body Postures and Movements (PUC-Rio)
DOI: 10.24432/c5jp5n
title: Gas sensor arrays in open sampling settings
DOI: 10.24432/c5hg71
title: Climate Model Simulation Crashes
DOI: 10.24432/c5t61s
title: MicroMass
DOI: 10.24432/c5h60m
title: QSAR biodegradation
DOI: 10.24432/c5hk6p
title: BLOGGER
DOI: 10.24432/c5c59f
title: Daily and Sports Activities
DOI: 10.24432/c5231x
title: User Knowledge Modeling
DOI: 10.24432/c5fs5r
title: Reuters RCV1 RCV2 Multilingual, Multiview Text Categorization Test collection
DOI: 10.24432/c56c8k
title: NYSK
DOI: 10.24432/c5s02s
title: Turkiye Student Evaluation
DOI: 10.24432/c5w033
title: ser Knowledge Modeling Data (Students' Knowledge Levels on DC Electrical Machines)
DOI: 10.24432/c5w902
title: seismic-bumps
DOI: 10.24432/c5bp5s
title: USPTO Algorithm Challenge, run by NASA-Harvard Tournament Lab and TopCoder Problem: Pat
DOI: 10.24432/c5mc7x
title: YouTube Multiview Video Games Dataset
DOI: 10.24432/c5j02m
title: Activities of Daily Living (ADLs) Recognition Using Binary Sensors
DOI: 10.24432/c5161n
title: SkillCraft1 Master Table Dataset
DOI: 10.24432/c5wk63
title: Weight Lifting Exercises monitored with Inertial Measurement Units
DOI: 10.24432/c5w31c
title: Predict keywords activities in a online social media
DOI: 10.24432/c5zw3p
title: EMG dataset in Lower Limb
DOI: 10.24432/c52889
title: Qualitative_Bankruptcy
DOI: 10.24432/c52s4z
title: LSVT Voice Rehabilitation
DOI: 10.24432/c5pc99
title: Dataset for ADL Recognition with Wrist-worn Accelerometer
DOI: 10.24432/c5ks4m
title: Wilt
DOI: 10.24432/c5wc8s
title: User Identification From Walking Activity
DOI: 10.24432/c56p5j
title: Activity Recognition from Single Chest-Mounted Accelerometer
DOI: 10.24432/c56w3v
title: Dresses_Attribute_Sales
DOI: 10.24432/c5kp4k
title: Tamilnadu Electricity Board Hourly Readings
DOI: 10.24432/c5030x
title: Wholesale customers
DOI: 10.24432/c5f31b
title: Twitter Data set for Arabic Sentiment Analysis
DOI: 10.5281/zenodo.8014430
title: Validation of a new global irrigation scheme in the ORCHIDEE land surface model - Dataset

description: Datasets used in the paper 'Validation of a new global irrigation scheme in the ORCHIDEE land surface model', submitted to GMD
DOI: 10.24432/c53s48
title: Urban Land Cover
DOI: 10.5281/zenodo.8014429
title: Validation of a new global irrigation scheme in the ORCHIDEE land surface model - Dataset

description: Datasets used in the paper 'Validation of a new global irrigation scheme in the ORCHIDEE land surface model', submitted to GMD
DOI: 10.24432/c5b61f
title: Bach Choral Harmony
DOI: 10.24432/c5gw3b
title: StoneFlakes
DOI: 10.24432/c54c7k
title: Tennis Major Tournament Match Statistics
DOI: 10.5517/ccdc.csd.ccwcbxg
title: CCDC 815266: Experimental Crystal Structure Determination

description: Related Article: N. Burcu Arslan, Fatma Aydın, Canan Kazak|2021|Phosphorus,Sulfur,Silicon,Relat.Elem.|196|1084|doi:10.1080/10426507.2021.1970550
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: 10.24432/c5z32c
title: Gesture Phase Segmentation
DOI: 10.5517/ccdc.csd.cc27fbfg
title: CCDC 2068395: Experimental Crystal Structure Determination

description: Related Article: Sutthida Wongsuwan, Jaruwan Chatwichien, Weekit Sirisaksoontorn, Kittipong Chainok, Apisit Songsasen, Ratanon Chotima|2023|New J.Chem.|47|10624|doi:10.1039/D3NJ00458A
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.cc2c31zj
title: CCDC 2177687: Experimental Crystal Structure Determination

description: Related Article: Venkata Sai Sashankh Penki, Yu-Lun Chang, Hsing-Yin Chen, Yu-Ting Chu, Yu-Ting Kuo, Dorothy Priyanka Dorairaj, Sri Sudewi, Shang-Wu Ding, Sodio C. N. Hsu|2023|Dalton Trans.|52|7652|doi:10.1039/D3DT00474K
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: 10.24432/c5mp4w
title: Perfume Data
DOI: 10.5517/ccdc.csd.cc2c325r
title: CCDC 2177693: Experimental Crystal Structure Determination

description: Related Article: Venkata Sai Sashankh Penki, Yu-Lun Chang, Hsing-Yin Chen, Yu-Ting Chu, Yu-Ting Kuo, Dorothy Priyanka Dorairaj, Sri Sudewi, Shang-Wu Ding, Sodio C. N. Hsu|2023|Dalton Trans.|52|7652|doi:10.1039/D3DT00474K
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.cc2c329w
title: CCDC 2177697: Experimental Crystal Structure Determination

description: Related Article: Venkata Sai Sashankh Penki, Yu-Lun Chang, Hsing-Yin Chen, Yu-Ting Chu, Yu-Ting Kuo, Dorothy Priyanka Dorairaj, Sri Sudewi, Shang-Wu Ding, Sodio C. N. Hsu|2023|Dalton Trans.|52|7652|doi:10.1039/D3DT00474K
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.cc2c32bx
title: CCDC 2177698: Experimental Crystal Structure Determination

description: Related Article: Venkata Sai Sashankh Penki, Yu-Lun Chang, Hsing-Yin Chen, Yu-Ting Chu, Yu-Ting Kuo, Dorothy Priyanka Dorairaj, Sri Sudewi, Shang-Wu Ding, Sodio C. N. Hsu|2023|Dalton Trans.|52|7652|doi:10.1039/D3DT00474K
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: 10.24432/c58s3f
title: BlogFeedback
DOI: 10.5517/ccdc.csd.cc2dd689
title: CCDC 2216260: Experimental Crystal Structure Determination

description: Related Article: Kaspars Leduskrasts, Artis Kinens, Edgars Suna|2023|Chem.Commun.|59|6905|doi:10.1039/D3CC01674A
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.cc2dd69b
title: CCDC 2216261: Experimental Crystal Structure Determination

description: Related Article: Kaspars Leduskrasts, Artis Kinens, Edgars Suna|2023|Chem.Commun.|59|6905|doi:10.1039/D3CC01674A
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: 10.24432/c5n60v
title: Newspaper and magazine images segmentation dataset
DOI: 10.24432/c5s31f
title: AAAI 2014 Accepted Papers