cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2d8j4c
title: CCDC 2212722: Experimental Crystal Structure Determination

description: Related Article: Jiayu Yan, Shuangliu Zhou, Yukun Wei, Qian Liu, Donghan Wang, Lijun Zhang, Qingbing Yuan, Shaowu Wang|2022|Organometallics|42|81|doi:10.1021/acs.organomet.2c00524
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.cc2d8j5d
title: CCDC 2212723: Experimental Crystal Structure Determination

description: Related Article: Jiayu Yan, Shuangliu Zhou, Yukun Wei, Qian Liu, Donghan Wang, Lijun Zhang, Qingbing Yuan, Shaowu Wang|2022|Organometallics|42|81|doi:10.1021/acs.organomet.2c00524
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.cc2d8j6f
title: CCDC 2212724: Experimental Crystal Structure Determination

description: Related Article: Jiayu Yan, Shuangliu Zhou, Yukun Wei, Qian Liu, Donghan Wang, Lijun Zhang, Qingbing Yuan, Shaowu Wang|2022|Organometallics|42|81|doi:10.1021/acs.organomet.2c00524
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.cc2d8l4f
title: CCDC 2212784: Experimental Crystal Structure Determination

description: Related Article: Tomáš Beránek, Martin Kos, Lubomír Váňa, Ivana Císařová, Jan Sýkora, Jan Storch, Vladimír Církva, Martin Jakubec|2023|Dyes Pigm.|210|111039|doi:10.1016/j.dyepig.2022.111039
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.cc2d8l5g
title: CCDC 2212785: Experimental Crystal Structure Determination

description: Related Article: Tomáš Beránek, Martin Kos, Lubomír Váňa, Ivana Císařová, Jan Sýkora, Jan Storch, Vladimír Církva, Martin Jakubec|2023|Dyes Pigm.|210|111039|doi:10.1016/j.dyepig.2022.111039
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.cc2d8l6h
title: CCDC 2212786: Experimental Crystal Structure Determination

description: Related Article: Tomáš Beránek, Martin Kos, Lubomír Váňa, Ivana Císařová, Jan Sýkora, Jan Storch, Vladimír Církva, Martin Jakubec|2023|Dyes Pigm.|210|111039|doi:10.1016/j.dyepig.2022.111039
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.cc2d9w8w
title: CCDC 2214028: Experimental Crystal Structure Determination

description: Related Article: Ranjeesh Thenarukandiyil, Rohit Kamte, Subhash Garhwal, Philipp Effnert, Natalia Fridman, Graham de Ruiter|2022|Organometallics|42|62|doi:10.1021/acs.organomet.2c00520
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.cc2d9w9x
title: CCDC 2214029: Experimental Crystal Structure Determination

description: Related Article: Ranjeesh Thenarukandiyil, Rohit Kamte, Subhash Garhwal, Philipp Effnert, Natalia Fridman, Graham de Ruiter|2022|Organometallics|42|62|doi:10.1021/acs.organomet.2c00520
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.cc2d9wby
title: CCDC 2214030: Experimental Crystal Structure Determination

description: Related Article: Ranjeesh Thenarukandiyil, Rohit Kamte, Subhash Garhwal, Philipp Effnert, Natalia Fridman, Graham de Ruiter|2022|Organometallics|42|62|doi:10.1021/acs.organomet.2c00520
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.cc2d9wcz
title: CCDC 2214031: Experimental Crystal Structure Determination

description: Related Article: Ranjeesh Thenarukandiyil, Rohit Kamte, Subhash Garhwal, Philipp Effnert, Natalia Fridman, Graham de Ruiter|2022|Organometallics|42|62|doi:10.1021/acs.organomet.2c00520
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.cc2db542
title: CCDC 2214303: Experimental Crystal Structure Determination

description: Related Article: Fortune O. Dzeagu, Jesse D. Carrick|2022|J.Org.Chem.|88|419|doi:10.1021/acs.joc.2c02421
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.21900300
title: MFF-MOE Feature Matrix of Two-photon Abosrption

description: This is the raw Feature matrix of paper entitled "Interpretable machine learning of two-photon abosrption" on Advanced Science. We used ‘Comprehensive_Molecular_Featurizer’ to generated this.
DOI: 10.6084/m9.figshare.21900300.v1
title: MFF-MOE Feature Matrix of Two-photon Abosrption

description: This is the raw Feature matrix of paper entitled "Interpretable machine learning of two-photon abosrption" on Advanced Science. We used ‘Comprehensive_Molecular_Featurizer’ to generated this.
DOI: 10.18434/t4/1433084
title: NIST SAMATE Software Assurance Reference Dataset

description: This dataset provides the NIST Software Assurance Metrics And Tool Evaluation
      (SAMATE) Software Assurance Reference Dataset (SARD) - a set of programs with known security
      flaws. This will allow end users to evaluate tools and tool developers to test their
      methods.
DOI: 10.25828/5sny-n338
title: Quarterly Labour Force Survey 2019, Quarter 1
DOI: 10.25828/kg4n-kz59
title: Quarterly Labour Force Survey 2020, Quarter 2
DOI: 10.25828/kz1a-wk96
title: Quarterly Labour Force Survey 2018, Quarter 4
DOI: 10.25828/vkhb-2j69
title: Quarterly Labour Force Survey 2020, Quarter 1
DOI: 10.3886/e131162v1
title: Code and Public Data for "Targeting In-Kind Transfers through Market Design: A Revealed Preference Analysis of Public Housing Allocation"

description: Code and instructions to reproduce analysis in the article "Targeting In-Kind Transfers through Market Design: A Revealed Preference Analysis of Public Housing Allocation."<br><br>Abstract: "Public housing benefits are rationed through waitlists. Theoretical work on public housing allocation has debated how much choice applicants should have over units, identifying a possible trade-off between efficiency and redistribution. This paper empirically establishes the existence and economic importance of this trade-off using waitlist data from Cambridge, MA. I estimate a model of public housing preferences in a setting where heterogeneous apartments are rationed through waiting time. Eliminating choice would improve targeting but reduce tenant welfare by more than 30 percent. Such a change is only justified on targeting grounds by a strong social preference for redistribution."
description: The CHA data contain applicants for Cambridge Housing Authority programs who were on a waitlist between 2010 and 2015, and program participants during the same period.<br><br>The ACS data contain households living in Massachusetts between 2010 and 2014.
DOI: 10.5291/ill-data.st-17
title: STEREO phase III run cycle 2020-2
DOI: 10.5441/002/icdt.2014.19
title: A Dichotomy on the Complexity of Consistent Query Answering for Atoms with Simple Keys
DOI: 10.6084/m9.figshare.19722013.v1
title: Accelerating OCR-Based Widget Localization for Test Automation of GUI Applications

description: The source code and the datasets used in the experiment.
DOI: 10.1285/i15910725v36p43
title: Tradizioni e saperi attorno ad alcune varietà locali di Cucumis melo L. in Salento (Puglia)

description: In the last years, demand for typical products and local varieties considerably increased, leading agricultural research institutes at detection and retrieval germoplasm to define the agricultural biodiversity in relevance area. Most of the characteristics of locally grown vegetable varieties do not match the food industry requirements. More over these varieties are old farmers' prerogative, who like to taste the flavor of a past time. The agricultural land abandon risks to induce these varieties to disappear quickly. This paper describes a preliminary investigation carried out to identify the inter-variety diversity of Cucumis melo, a vegetable exclusive of the Bari and Salento area (Apulia), which recently is affecting the market with its production also at national level. The present work tries to estimate how many and what varieties they still continue to be cultivated and preserved by farmers. Regional exploration have been carried out in order to find germoplasm of Cucumis melo in the different districts of Salento but, above all, to learn more about the farmers who are working to keep alive these varieties, renewing annually seed production with techniques environmentally preserving the rural context. The germoplasm collected has allowed us to initiate studies on the morphological characterization of varieties. Already from a morphological examination of the seeds, it was obvious that an incredible diversity of phenotypes and genotypes exist of the same vegetable. For each sample open field cultivation have been carried out to obtain the morphometric characterization of seeds, leaves, stems, flowers and fruit. Production parameters and the quality of fruits from each variety were also evaluated. Finally, the germoplasm found out corresponded to 3 different varieties of sweet melon and 13 meloncelle (2 of which didn’t germinated); the 11 varieties in production corresponded to 6 well distinct cultivars. The loss of intraspecific biodiversity represents a serious risk to the great variety of Cucumis melo, the result of thousands of years of genetic improvement and domestication.
DOI: 10.25828/1f1a-f611
title: Quarterly Labour Force Survey 2019, Quarter 3
DOI: 10.25828/28jb-6t54
title: Quarterly Labour Force Survey 2019, Quarter 4
DOI: 10.25828/kbtj-yx94
title: Quarterly Labour Force Survey 2018, Quarter 3
DOI: 10.25828/mnwq-w661
title: Quarterly Labour Force Survey 2018, Quarter 1
DOI: 10.25828/r7by-fv52
title: Quarterly Labour Force Survey 2018, Quarter 2
DOI: 10.5067/gzjjya7l0yw2
title: OMPS-NPP L2 LP Aerosol Extinction Vertical Profile swath daily 3slit V1.5
DOI: 10.17632/s5yvzkw4k3.1
title: Physical and biogenic complexity mediates ecosystem functions in urban sessile marine communities

description: Dataset associated with the paper "Physical and biogenic complexity mediates ecosystem functions in urban sessile marine communities" (2022) published in Journal of Applied Ecology.

Abstract:
 1 – The influence of habitat complexity on biodiversity is a central theme in ecology, with many studies reporting positive relationships. Reconciliation approaches in urbanised areas, such as eco-engineering, have increasingly focused on ‘re-building’ the complexity of degraded and/or homogenised habitats to support biodiversity. Yet the effects of increasing complexity and biodiversity on ecological functions are rarely measured. 
2 – We assessed how increasing the physical and/or biogenic complexity of habitats affects the net and gross primary productivity (NPP and GPP, respectively), community respiration and nutrient cycling (specifically dissolved inorganic phosphorus and nitrogen) of intertidal sessile marine communities at three sites. We manipulated physical complexity using two types of settlement tiles: ‘complex’, with crevices and ridges, and ‘flat’. We increased biogenic complexity on half the replicates of each tile type by seeding with oysters. 
3 – Increased physical and biogenic complexity resulted in greater sessile species richness at all sites. Although many variables assessed varied with sites and time of measurements, overall, GPP and NPP was greater on flat tiles than on complex ones.  These patterns were not explained by differences in the total surface area of tiles.. 
5 – Daily flux rates of Dissolved inorganic phosphorus had a significant positive relationship with biogenic complexity. There were no effects of biogenic or physical complexity on the net fluxes of dissolved inorganic nitrogen. 
6 – Effects of habitat complexity on the productivity and nutrient cycling of marine sessile communities were largely unrelated to diversity measures, such as richness or abundance of key taxa and functional groups. 

Synthesis and applications: Eco-engineering practices that manipulate habitat complexity might benefit from explicit functional targets that also consider associated ecosystem services, as we found that under some conditions there is a trade-off between biodiversity and functional targets. Our results suggest that increasing habitat complexity has a positive effect on sessile species richness, but not necessarily on productivity (GPP and NPP). The species pool available as well as light availability is likely to mediate effects of complexity on assemblages, so local environment needs to be a key consideration when designing interventions.
DOI: 10.25828/k727-7s59
title: Quarterly Labour Force Survey 2019, Quarter 2
DOI: 10.17632/7d95mm4hpd.1
title: RDLT

description: A large-scale dataset for random dynamics learning from trajectories used in paper "Conv-Transformer for Random Dynamical System Representation Learning".
DOI: 10.17632/bgpzb4nknt.1
title: MS.data

description: These data include data collected on a study that aimed to evaluate the effect of non-dominant hand training on motor function and the dual-task cost (DTC)  in MS patients. The results showed that non-dominant hand training improves motor function in both upper limbs and reduces the DTC in MS patients.
DOI: 10.21227/3x45-5d33
title: Transformer internal image

description: In order to evaluate the positioning performance of this algorithm in the transformer, The robot was demonstrated in the Mitsubishi transformer of Shuibei Power Supply Station in Shenzhen. The image frame sequence was obtained during the experiment.
DOI: 10.6084/m9.figshare.21900321
title: Publish or Perish (basic report) Google Scholar Profil Jurnal Manajemen Stratejik dan Simulasi Bisnis

description: <strong>Jurnal Manajemen Stratejik dan Simulasi Bisnis (JMASSBI) - Magister Manajemen FE - UNAND</strong> <em>Publish or Perish 8.8.4275.8412 (basic report)</em><br> <em> WinPosix (x64) edition, running on WinPosix 10.0.19045 (x64)</em> <strong>Search terms</strong> <strong>Data retrieval</strong> <strong>Metrics</strong> <strong>Results</strong>
DOI: 10.34740/kaggle/dsv/4850453
title: 10000Jobshop Problem data
DOI: 10.5517/ccdc.csd.cc2bjssg
title: CCDC 2161096: Experimental Crystal Structure Determination

description: Related Article: Yu. V. Manakin, V. S. Mironov, T. A. Bazhenova, I. A. Yakushev, I. F. Gilmutdinov, S. V. Simonov, E. B. Yagubskii|2022|Chem.Commun.|59|643|doi:10.1039/D2CC05998C
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.cc2dfg6j
title: CCDC 2217467: Experimental Crystal Structure Determination

description: Related Article: Yu. V. Manakin, V. S. Mironov, T. A. Bazhenova, I. A. Yakushev, I. F. Gilmutdinov, S. V. Simonov, E. B. Yagubskii|2022|Chem.Commun.|59|643|doi:10.1039/D2CC05998C
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: 10.34740/kaggle/dsv/4850506
title: Elon Musk Tweets
DOI: 10.5281/zenodo.7533423
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 250m SIN Grid in 2010 (185–361)

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 250m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 250m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2010 (185–361). <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2010 (001–177)</strong> and <em><strong>click here</strong> to download the MUSES FVC produ</em>ct <strong>in 2011 (001–177)</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2010 (185–361) Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 100 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7533422
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 250m SIN Grid in 2010 (185–361)

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 250m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 250m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2010 (185–361). <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2010 (001–177)</strong> and <em><strong>click here</strong> to download the MUSES FVC produ</em>ct <strong>in 2011 (001–177)</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2010 (185–361) Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.01 Valid Range: 0 – 100 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7512560
title: Targeted sensors for glutamatergic neurotransmission

description: Raw and derived data for Figure 9 and supplements
DOI: 10.5281/zenodo.7536473
title: Tandem Observations of Nighttime Mid-latitude Topside Ionospheric Perturbations

description: Dataset from Swarm satellite data for "Tandem Observations of Nighttime Mid-latitude Topside Ionospheric Perturbations".
DOI: 10.5281/zenodo.7536472
title: Tandem Observations of Nighttime Mid-latitude Topside Ionospheric Perturbations

description: Dataset from Swarm satellite data for "Tandem Observations of Nighttime Mid-latitude Topside Ionospheric Perturbations".
DOI: 10.6084/m9.figshare.21900327
title: Publish or Perish Crossref of Jurnal Manajemen Stratejik dan Simulasi Bisnis, ISSN 2746-6868

description: <strong>Jurnal Manajemen Stratejik dan Simulasi Bisnis, ISSN 2746-6868</strong> <strong>Search terms</strong> <strong>Publication name:</strong> Jurnal Manajemen Stratejik dan Simulasi Bisnis<br> <strong>ISSN:</strong> 2746-6868<br> <strong>Years:</strong> all<br> <br> <strong>Data retrieval</strong> <strong>Data source:</strong> Crossref<br> <br> <strong>Metrics</strong> <strong>Results</strong>