cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2f0x4j
title: CCDC 2235197: Experimental Crystal Structure Determination

description: Related Article: Jixing Han, Chaopeng Hu, Qianli Li, Liu Leo Liu, Chen-Ho Tung, Ping Cui, Lingbing Kong|2023|Inorg.Chem.|62|18820|doi:10.1021/acs.inorgchem.3c03232
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.cc2f0x5k
title: CCDC 2235198: Experimental Crystal Structure Determination

description: Related Article: Jixing Han, Chaopeng Hu, Qianli Li, Liu Leo Liu, Chen-Ho Tung, Ping Cui, Lingbing Kong|2023|Inorg.Chem.|62|18820|doi:10.1021/acs.inorgchem.3c03232
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.cc2f0x6l
title: CCDC 2235199: Experimental Crystal Structure Determination

description: Related Article: Jixing Han, Chaopeng Hu, Qianli Li, Liu Leo Liu, Chen-Ho Tung, Ping Cui, Lingbing Kong|2023|Inorg.Chem.|62|18820|doi:10.1021/acs.inorgchem.3c03232
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.cc2f0x7m
title: CCDC 2235200: Experimental Crystal Structure Determination

description: Related Article: Jixing Han, Chaopeng Hu, Qianli Li, Liu Leo Liu, Chen-Ho Tung, Ping Cui, Lingbing Kong|2023|Inorg.Chem.|62|18820|doi:10.1021/acs.inorgchem.3c03232
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.cc2f0x8n
title: CCDC 2235201: Experimental Crystal Structure Determination

description: Related Article: Jixing Han, Chaopeng Hu, Qianli Li, Liu Leo Liu, Chen-Ho Tung, Ping Cui, Lingbing Kong|2023|Inorg.Chem.|62|18820|doi:10.1021/acs.inorgchem.3c03232
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.cc2f0x9p
title: CCDC 2235202: Experimental Crystal Structure Determination

description: Related Article: Jixing Han, Chaopeng Hu, Qianli Li, Liu Leo Liu, Chen-Ho Tung, Ping Cui, Lingbing Kong|2023|Inorg.Chem.|62|18820|doi:10.1021/acs.inorgchem.3c03232
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: 10.5523/bris.3lr5ju5bpvwpp2rei9ckhzwi3q
title: Analytical approximations for magnetic coupling coefficients between adjacent coils
title: K-Model

description: Supplemenatry data for paper "Analytical approximations for magnetic coupling coefficients between adjacent coils" by Hughes, Hernandez, and Mulholland, published in IEEE Magnetics, 2023/2024
DOI: 10.34740/kaggle/ds/4059603
title: YOLO v5 format of the Traffic Signs dataset
DOI: 10.2909/ccda6ecb-9379-48a5-8f80-05cc400cae81
title: Season amplitude 2017-present (raster 10m and 100m), Europe, yearly, Nov. 2022 - adjusted to the HRL grid

description: The Season Amplitude (AMPL), one of the Vegetation Phenology and Productivity (VPP) parameters, is a product of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The Season Amplitude (AMPL) is the difference between the maximum and minimum Plant Phenology Index (PPI) values reached during the season. The Plant Phenology Index (PPI) is a physically based vegetation index, developed for improving the monitoring of the vegetation growth cycle. The PPI index values, with 5-day satellite revisit cycle, are first used in a function fitting to derive the PPI Seasonal Trajectories, which is a filtered time series with regular 10-day time step. From these Seasonal Trajectories, a suite of 13 Vegetation Phenology and Productivity (VPP) parameters are then computed and provided, for up to two seasons each year. The Amplitude is one of the 13 parameters. The full list is available in the table 3 of the Product User Manual in the below link section. A complementary quality indicator (QFLAG) provides a confidence level, that is described in table 4 of the same manual. The AMPL dataset is made available as raster files with 10 x 10m and 100 x 100m resolutions, in ETRS89-LAEA projection corresponding to the HRL grid, for those tiles that cover the EEA38 countries and the United Kingdom and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year.
DOI: 10.2909/2d8ef180-584b-4283-929b-4e3af40c1847
title: Plant Phenology Index Seasonal Trajectories 2017-present (raster 10m and 100m), Europe, 10-daily, Nov. 2022 - adjusted to the HRL grid

description: This metadata refers to the Plant Phenology Index (PPI) Seasonal Trajectories, is one of the products of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The Plant Phenology Index (PPI) is a physically based vegetation index for improved monitoring of plant phenology, that is developed from a simplified solution to the radiative transfer equation by Jin and Eklundh (2014) and that has a linear relationship with green leaf area index. The PPI Seasonal Trajectories (ST) product is derived from a TIMESAT-based function fitting of the time series of the PPI vegetation index and thus provides a filtered time series of Plant Phenology Index (PPI), with regular 10-day time step. The PPI dataset is made available as raster files with 10 x 10m resolution and 100 x 100m resolutions, in ETRS89-LAEA projection corresponding to the HRL grid, for those tiles that cover the EEA38 countries and the United Kingdom and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year. Each file has an associated quality indicator (QFLAG) that provides a confidence level.
DOI: 10.2909/370c65e6-99fd-4b10-acf2-a8342aec39c7
title: End-of-season value 2017-present (raster 10m and 100m), Europe, yearly, Nov. 2022 - adjusted to the HRL grid

description: The End-of-Season Value (EOSV), one of the Vegetation Phenology and Productivity (VPP) parameters, is a product of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The End-of-Season Value (EOSV) provides the value of the Plant Phenology Index (PPI) at the end of the vegetation growing season. The Plant Phenology Index (PPI) is a physically based vegetation index, developed for improving the monitoring of the vegetation growth cycle. The PPI index values, with 5-day satellite revisit cycle, are first used in a function fitting to derive the PPI Seasonal Trajectories, which is a filtered time series with regular 10-day time step. From these Seasonal Trajectories, a suite of 13 Vegetation Phenology and Productivity (VPP) parameters are then computed and provided, for up to two seasons each year. The End-of-Season Value is one of the 13 parameters. The full list is available in the table 3 of the Product User Manual in the below link section. A complementary quality indicator (QFLAG) provides a confidence level, that is described in table 4 of the same manual. The EOSV dataset is made available as raster files with 10 x 10m and 100 x 100m resolutions, in ETRS89-LAEA projection corresponding to the HRL grid, for those tiles that cover the EEA38 countries and the United Kingdom and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year.
DOI: 10.2909/29d8f9a5-f7df-4da9-b9a6-c18e3d40adef
title: End-of-season date 2017-present (raster 10m and 100m), Europe, yearly, Nov. 2022 - adjusted to the HRL grid

description: The End-of-Season Date (EOSD), one of the Vegetation Phenology and Productivity (VPP) parameters, is a product of the pan-European High Resolution Vegetation Phenology and Productivity (HR-VPP) component of the Copernicus Land Monitoring Service (CLMS). The End-of-Season Date (EOSD) marks the date when the vegetation growing season ends in the time profile of the Plant Phenology Index (PPI). The end-of-season occurs, by definition, when the PPI value reaches 15% of the season amplitude during the green-down period. The Plant Phenology Index (PPI) is a physically based vegetation index, developed for improving the monitoring of the vegetation growth cycle. The PPI index values, with 5-day satellite revisit cycle, are first used in a function fitting to derive the PPI Seasonal Trajectories, which is a filtered time series with regular 10-day time step. From these Seasonal Trajectories, a suite of 13 Vegetation Phenology and Productivity (VPP) parameters are then computed and provided, for up to two seasons each year. The End-of-Season Date is one of the 13 parameters. The full list is available in the table 3 of the Product User Manual in the below link section. A complementary quality indicator (QFLAG) provides a confidence level, that is described in table 4 of the same manual. The EOSD dataset is made available as raster files with 10 x 10m and 100 x 100m resolutions, in ETRS89-LAEA projection corresponding to the HRL grid, for those tiles that cover the EEA38 countries and the United Kingdom and for two seasons in each year from 2017 onwards. It is updated in the first quarter of each year.
DOI: 10.24378/exe.4904
title: Non-Polaritonic Effects in Cavity-Modified Photochemistry (dataset)

description: This is the dataset used for the Thomas et al. (2023) article "Non-Polaritonic Effects in Cavity-Modified Photochemistry" published in Advanced Materials.
description: This is the dataset (all in .csv format) for the manuscript "Non-Polaritonic Effects in Cavity-Modified Photochemistry" published in Advanced Materials in 2023.
DOI: 10.6084/m9.figshare.24552466
title: <i>Trypanosoma brucei</i> infection study - cattle blood and faecal data

description: Data set to accompany project 'Consistent detection of <i>Trypanosoma brucei</i> but not <i>T. congolense</i> DNA in faeces of experimentally-infected cattle'Preprint:https://www.researchsquare.com/article/rs-3628035/v1
DOI: 10.6084/m9.figshare.24552508
title: <i>Trypanosoma congolense</i> infection study - cattle blood and faecal data

description: Data set to accompany project 'Consistent detection of <i>Trypanosoma brucei</i> but not <i>T. congolense</i> DNA in faeces of experimentally-infected cattle'Preprint:https://www.researchsquare.com/article/rs-3628035/v1<br>
DOI: 10.5281/zenodo.2553066
title: Support Assets for Figs and Tabs in gmd-2018-292 (Geosci. Model Dev. Discussions)

description: Source data for Figures and Tables in "VISIR-I.b: waves and ocean currents for energy efficient navigation", by G. Mannarini and L. Carelli, gmd-2018-292 (Geosci. Model Dev. Discussions)

(11 Figures, 7 Tables)
DOI: 10.5281/zenodo.3236401
title: Support Assets for Figs and Tabs in gmd-2018-292 (Geosci. Model Dev. Discussions)

description: Support assets for  "VISIR-I.b: waves and ocean currents for energy efficient navigation", by G. Mannarini and L. Carelli, gmd-2018-292 (Geosci. Model Dev. Discussions):

<strong>-graphs_gmd-2018-292.tar.gz</strong>

Graphs for running VISIR computations  

<strong>- figTab_DATA_v2.tar.gz:</strong>

Source data for Figures and Tables

 

Please refer to https://doi.org/10.5281/zenodo.2563074 for the full release of VISIR-1.b source code.
description: Contact info: gianandrea.mannarini@cmcc.it
DOI: 10.5281/zenodo.3258177
title: Support Data Assets for Figures and Tables in gmd-12-3449-2019 (Geosci. Model Dev.)

description: Support datasets for "VISIR-1.b: ocean surface gravity waves and currents for energy-efficient navigation", by G. Mannarini and L. Carelli (Geosci. Model Dev. paper, https://doi.org/10.5194/gmd-12-3449-2019):

 graphs_gmd-2018-292.tar.gz
Graphs for running VISIR computations  

figTab_DATA_v3.tar.gz:
Source data for Figures and Tables
description: VISIR-1.b source code: https://doi.org/10.5281/zenodo.2563074
DOI: 10.5281/zenodo.1493167
title: Support Data Assets for Figures and Tables in gmd-12-3449-2019 (Geosci. Model Dev.)

description: Support datasets for "VISIR-1.b: ocean surface gravity waves and currents for energy-efficient navigation", by G. Mannarini and L. Carelli (Geosci. Model Dev. paper, https://doi.org/10.5194/gmd-12-3449-2019):

 graphs_gmd-2018-292.tar.gz
Graphs for running VISIR computations  

figTab_DATA_v3.tar.gz:
Source data for Figures and Tables
description: VISIR-1.b source code: https://doi.org/10.5281/zenodo.2563074
DOI: 10.5281/zenodo.1493168
title: Support Assets for Figs and Tabs in gmd-2018-292

description: Source data for Figures and Tables in "VISIR-I.b: waves and ocean currents for energy efficient navigation", by G. Mannarini and L. Carelli, gmd-2018-292 (Geosci. Model Dev. Discussions)

(11 Figures, 7 Tables)
DOI: 10.5281/zenodo.2556801
title: Support Assets for Figs and Tabs in gmd-2018-292 (Geosci. Model Dev. Discussions)

description: Support assets for  "VISIR-I.b: waves and ocean currents for energy efficient navigation", by G. Mannarini and L. Carelli, gmd-2018-292 (Geosci. Model Dev. Discussions):

<strong>-graphs_gmd-2018-292.tar.gz</strong>

Graphs for running VISIR computations  

<strong>- figTab_DATA.tar.gz:</strong>

Source data for Figures and Tables

 

Please refer to https://doi.org/10.5281/zenodo.2563074 for the full release of VISIR-1.b source code.
description: Contact info: gianandrea.mannarini@cmcc.it
DOI: 10.5281/zenodo.10056900
title: Experiment-based DNN approach for power allocation with a metasurface
DOI: 10.5281/zenodo.10056901
title: Experiment-based DNN approach for power allocation
DOI: 10.5281/zenodo.10210090
title: Experiment-based DNN approach for power allocation with a metasurface
DOI: 10.5281/zenodo.10213819
title: Search strategies for screening for abdominal aortic aneurysm (AAA) in men: a health technology assessment

description: The dataset includes the complete, reproducible search strategies for all literature databases searched during this project. The search strategies address the following research question: 
What is the clinical effectiveness and safety of population-based ultrasound screening for AAA in men compared with no systematic screening?
DOI: 10.5281/zenodo.10213791
title: Dataset from Lagrangian bio-optical drifters during four experiments in coastal and open ocean waters
DOI: 10.5281/zenodo.10213792
title: Dataset from Lagrangian bio-optical drifters during four experiments in coastal and open ocean waters
DOI: 10.5281/zenodo.10210414
title: Detecting and stabilizing measurement-induced symmetry-protected topological phases in generalized cluster models

description: This dataset contains the code and the data used for the corresponding publication.
DOI: 10.5281/zenodo.7684247
title: Detecting and stabilizing measurement-induced symmetry-protected topological phases in generalized cluster models

description: This dataset contains the code and the data used for the corresponding publication.
DOI: 10.5281/zenodo.7684248
title: Detecting and stabilizing measurement-induced symmetry-protected topological phases in generalized cluster models

description: This dataset contains the code and the data used for the corresponding publication.
DOI: 10.57745/aezyog
title: Rockwool support.stl

description: Rockwool support plan
DOI: 10.6084/m9.figshare.24649041
title: <b>Influence of temperature on the population size of </b><b><i>Aceria litchii </i></b><b>(Acari: Eriophyidae) and the development of its galls</b>

description: <b>Data related to the manuscript: Influence of temperature on the population size of </b><b><i>Aceria litchii </i></b><b>(Acari: Eriophyidae) and the development of its galls</b>
DOI: 10.6084/m9.figshare.24649041.v1
title: <b>Influence of temperature on the population size of </b><b><i>Aceria litchii </i></b><b>(Acari: Eriophyidae) and the development of its galls</b>

description: <b>Data related to the manuscript: Influence of temperature on the population size of </b><b><i>Aceria litchii </i></b><b>(Acari: Eriophyidae) and the development of its galls</b>
DOI: 10.5281/zenodo.10213880
title: ENCUESTA A LOS USUARIOS CHINOS SOBRE LOS HÁBITOS DE USO DE LOS AGREGADORES DE NOTICIAS CHINOS
DOI: 10.5281/zenodo.10213881
title: ENCUESTA A LOS USUARIOS CHINOS SOBRE LOS HÁBITOS DE USO DE LOS AGREGADORES DE NOTICIAS CHINOS
DOI: 10.6084/m9.figshare.24649086
title: scaleModel.py

description: The output of the scaleModel.py program is threefold: (1) measured IPC for the scale models; (2) predicted IPC for<br>the target system(s); and (3) a graph showing performance as a function of system size for the four prediction methods
DOI: 10.6084/m9.figshare.24649086.v1
title: scaleModel.py

description: The output of the scaleModel.py program is threefold: (1) measured IPC for the scale models; (2) predicted IPC for<br>the target system(s); and (3) a graph showing performance as a function of system size for the four prediction methods
DOI: 10.6084/m9.figshare.24649107
title: scale_model_data.xlsx

description: This file contains the performance results for the scale-models as well as the miss rate curves for all benchmarks<br>such that the target-system performance predictions can be reproduced without having to re-simulate the scale models.
DOI: 10.6084/m9.figshare.24649107.v1
title: scale_model_data.xlsx

description: This file contains the performance results for the scale-models as well as the miss rate curves for all benchmarks<br>such that the target-system performance predictions can be reproduced without having to re-simulate the scale models.
DOI: 10.6084/m9.figshare.24649083.v1
title: config_files.zip

description: The compressed file contains the AccelSim configuration files of the scale models and the target systems
DOI: 10.6084/m9.figshare.24649083
title: config_files.zip

description: The compressed file contains the AccelSim configuration files of the scale models and the target systems
DOI: 10.60619/7rza-fj14
title: 3D model of the VC haloscope for the lineal y-axis misalignment
DOI: 10.60534/ba7e0-h6c66
title: Co-action of COP1, SPA and cryptochrome in light signal transduction and photomorphogenesis of the moss Physcomitrium patens

description: hosted on: https://git.nfdi4plants.org/projects/719
DOI: 10.60619/pyh4-k949
title: 3D model of the VC haloscope for the y-axis misalignment
DOI: 10.6084/m9.figshare.24649260
title: Dataset for "How to teach the anatomy of the inguinal canal? A multimodal approach"

description: N.A.
DOI: 10.60619/f7wp-cp90
title: 3D model of the VC haloscope for the z-axis misalignment
DOI: 10.18465/07d36386-c2ed-49bb-a2ee-15c8c1a0a5c1
title: MNS Pont-Mahé 2022

description: Modèle Numérique de Surface obtenu par LiDAR sur la côte ligérienne au niveau de Pont-Mahé
DOI: 10.18465/c7e9a745-4df3-42e2-840d-b0d88a22d067
title: MNT Pont-Mahé 2022

description: Modèle Numérique de Terrain obtenu par LiDAR sur la côte ligérienne au niveau de Pont-Mahé
DOI: 10.15151/esrf-es-1298372446
title: New instrument for nano-XRD and nano-XRF at extreme conditions at ID27

description: A new, unique nano-focus instrumentation for rapid parallel XRF and XRD as well as X-ray imaging measurements at extreme pT conditions will be constructed on ID27. Funding for this project was partially obtained from German authorities in the framework of a BMBF project by M. Wilke (Potsdam), S. Jahn (Cologne) and D. Andrault (Clermont-Ferrand). The planned work is outlined in a collaboration contract between ESRF, University Potsdam and Cologne University (CL 0309). The instrument benefits from the very small beam size and the ultimate brilliance provided by the new diffraction-limited synchrotron radiation source at ESRF. During the LTP the new instrument will be benchmarked and employed to perform cutting-edge experiments for understanding materials relevant to processes of the deep Earth. Additionally, this unique setup offers the possibility for applications ranging from materials sciences in the field of superhard or superdense materials to high-pressure solid-state physics.
DOI: 10.5281/zenodo.10066796
title: Growth of Merocyanine Dye J-Aggregate Nanosheets by Living Supramolecular Polymerization

description: Data to report https://doi.org/10.1002/ange.202314667:
J-aggregates are highly desired dye aggregates but so far there has been no general concept how to accomplish the required slip-stacked packing arrangement for dipolar merocyanine (MC) dyes whose aggregation commonly affords one-dimensional aggregates composed of antiparallel, co-facially stacked MCs with H-type coupling. Herein we describe a strategy for MC J-aggregates based on our results for an amphiphilic MC dye bearing alkyl and oligo(ethylene glycol) side chains. In an aqueous solvent mixture, we observe the formation of two supramolecular polymorphs for this MC dye, a metastable off-pathway nanoparticle showing H-type coupling and a thermodynamically favored nanosheet showing J-type coupling. Detailed studies concerning the self-assembly mechanism by UV-Vis spectroscopy and the packing structure by atomic force microscopy and wide-angle X-ray scattering show how the packing arrangement of such amphiphilic MC dyes can afford slip-stacked two-dimensional nanosheets whose macrodipole is compensated by the formation of a bilayer structure. As an additional feature we demonstrate how the size of the nanosheets can be controlled by seeded living supramolecular polymerization.
description: Original spectroscopic data to report: https://doi.org/10.1002/ange.202314667