cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4xs94489rw.1
title: [68Ga]Ga-Pentixafor PET/CT images of Glioma patients 

description: This dataset contains information showing chemokine receptor-4 (CXCR4) targeting in high-grade glial brain tumors in treatment-naïve adult patients using a novel radiolabeled PET tracer; [68Ga]Ga-CXCR4 PET/CT. 
The enrolled patients received the radiotracer intravenously. After approximately 60 minutes, the PET/CT acquisition was performed with a dedicated scanner and in 10 minutes time per bed position. The images were reconstructed and analyzed with the 3D-OSEM algorithm, applying PSF resolution recovery (TrueX in Syngo ® software, Siemens Medical Solution), 3 iterations, and 21 subsets using a 3 mm Gaussian post-smoothing filter.
These data would be potentially beneficial for automatic tumor delineation machine learning as well as for differentiation between an active viable tumor vs. post-surgery/necrosis in indeterminate cases. The theranostics potential (CXCR4-tageted labeled beta emitters) is one of the most novel areas of interest for future studies.
DOI: 10.14272/hvswcksdickonk-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C26H16N12/c27-35-31-21-9-1-17(2-10-21)25(18-3-11-22(12-4-18)32-36-28)26(19-5-13-23(14-6-19)33-37-29)20-7-15-24(16-8-20)34-38-30/h1-16H

description: dataset for mass spectrometry (MS) MS (EI, 70 eV, 150 °C, C26H16N12), m/z (%): 497 (11) [M + H]+, 496 (40) [M]+, 469 (5) [M – N2 + H]+, 468 (18) [M – N2]+, 455 (100) [M – N3 + H]+, 440 (6) [M – 2 N2]+, 427 (56) [M – N3 – N2 + H]+, 399 (21) [M – 3 N2 + H]+, 371 (19) [M – 3 N3 + H]+, 370 (37) [M – 3 N3]+, 357 (24) [M – 2 N3 – 2 N2 + H]+, 356 (17) [M – 2 N3 – 2 N2]+, 343 (59) [M – 3 N3 – N2 + H]+, 342 (37) [M – 3 N3 – N2]+, 329 (47) [M – 4 N3 + H]+, 328 (30) [M – 4 N3]+.HRMS–EI (m/z): [M]+ calcd for C26H16N12 496.1615; found 496.1616.
DOI: 10.14272/hvswcksdickonk-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C26H16N12/c27-35-31-21-9-1-17(2-10-21)25(18-3-11-22(12-4-18)32-36-28)26(19-5-13-23(14-6-19)33-37-29)20-7-15-24(16-8-20)34-38-30/h1-16H

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, Chloroform-d [7.27 ppm], ppm) δ = 7.00–6.97 (m, 8H, Caromat.H), 6.82–6.78 (m, 8H, Caromat.H).
DOI: 10.14272/hvswcksdickonk-uhfffaoysa-n.1
title: 1,1,2,2-tetrakis(4-azidophenyl)ethene
title: InChI=1S/C26H16N12/c27-35-31-21-9-1-17(2-10-21)25(18-3-11-22(12-4-18)32-36-28)26(19-5-13-23(14-6-19)33-37-29)20-7-15-24(16-8-20)34-38-30/h1-16H

description: This dataset contains experimental data from a sample (InChI=1S/C26H16N12/c27-35-31-21-9-1-17(2-10-21)25(18-3-11-22(12-4-18)32-36-28)26(19-5-13-23(14-6-19)33-37-29)20-7-15-24(16-8-20)34-38-30/h1-16H). The datasets from the following experiments are available: 13C nuclear magnetic resonance spectroscopy (13C NMR) 1H nuclear magnetic resonance spectroscopy (1H NMR) mass spectrometry (MS) infrared absorption spectroscopy (IR)
DOI: 10.14272/hvswcksdickonk-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C26H16N12/c27-35-31-21-9-1-17(2-10-21)25(18-3-11-22(12-4-18)32-36-28)26(19-5-13-23(14-6-19)33-37-29)20-7-15-24(16-8-20)34-38-30/h1-16H

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3227 (w), 3046 (w), 3031 (w), 2961 (w), 2929 (w), 2414 (w), 2113 (vs), 2081 (vs), 1924 (w), 1898 (w), 1803 (w), 1775 (w), 1599 (m), 1567 (w), 1500 (vs), 1443 (w), 1409 (m), 1373 (w), 1290 (vs), 1272 (vs), 1213 (m), 1179 (vs), 1169 (s), 1126 (vs), 1109 (vs), 1086 (m), 1035 (w), 1016 (s), 976 (m), 959 (w), 941 (w), 916 (w), 866 (m), 832 (vs), 812 (vs), 778 (vs), 759 (s), 741 (s), 724 (s), 700 (s), 688 (m), 671 (s), 662 (s), 649 (s), 625 (m), 594 (s), 567 (m), 538 (vs), 530 (vs), 510 (vs), 482 (s), 446 (m), 409 (m), 390 (s) cm–1.
DOI: 10.14272/hvswcksdickonk-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C26H16N12/c27-35-31-21-9-1-17(2-10-21)25(18-3-11-22(12-4-18)32-36-28)26(19-5-13-23(14-6-19)33-37-29)20-7-15-24(16-8-20)34-38-30/h1-16H

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, Chloroform-d [77.0 ppm], ppm) δ = 140.1 (4C, CqN3), 139.6 (2C, Cq), 138.6 (4C,Cq), 132.8 (8C, Caromat.H), 118.8 (8C, Caromat.H).
DOI: 10.6084/m9.figshare.22152056
title: Waller et al_2023_Collateral TB_Source Data.xlsx

description: Source data for figures generated in: https://doi.org/10.1101/2022.10.31.514625
DOI: 10.6084/m9.figshare.22152056.v1
title: Waller et al_2023_Collateral TB_Source Data.xlsx

description: Source data for figures generated in: https://doi.org/10.1101/2022.10.31.514625
DOI: 10.21942/uva.18551108
title: Data and Stata code

description: Data on solar energy foreign investments, described in https://link.springer.com/article/10.1057/s41267-020-00358-2
DOI: 10.21942/uva.18551108.v1
title: Data and Stata code

description: Data on solar energy foreign investments, described in https://link.springer.com/article/10.1057/s41267-020-00358-2
DOI: 10.5281/zenodo.7685508
title: Supplementary data to: Internal anatomy of brachyuran crab from a Late Cretaceous methane seep and an overview of internal soft tissues in fossil decapod crustaceans

description: 001-Secretanella_sp_AAK_072019.zip - µCT scan data, 1.28 GB stack of DICOM images. High-resolution X-ray computed tomography (CT) scans of specimen ALMNH:Paleo:6522 were obtained at the Berkeley Preclinical Imaging Facility (UC Berkeley, California, USA) in July 2019 using a GE Healthcare eXplore Locus Micro CT Scanner. The specimen was scanned using a conebeam energy of 80 kV, a current of 450 µA, 2,000 ms exposure time, and no filter, resulting in a voxel resolution of 20.523 µm. Visualization and three-dimensional reconstruction of the resulting µCT data were performed using the open-source software 3D Slicer v.4.13.0 (Fedorov et al., 2012). Additional_images_gifs_3Dmodel.zip - archive containing 3 folders of additionnal images, video (gifs) and a 3D model (STL file) : - Addendum_Figure_3 : additional images / views to the figure 3 presented in the paper. - Gifs_3d_models : gifs and STL 3d model of the scanned specimen - Images_gifs_inc_gastric_musc : images, gifs and 3d model similar as in the other folders, but displaying potential gastric muscles
DOI: 10.5281/zenodo.7685509
title: Supplementary data to: Internal anatomy of brachyuran crab from a Late Cretaceous methane seep and an overview of internal soft tissues in fossil decapod crustaceans

description: 001-Secretanella_sp_AAK_072019.zip - µCT scan data, 1.28 GB stack of DICOM images. High-resolution X-ray computed tomography (CT) scans of specimen ALMNH:Paleo:6522 were obtained at the Berkeley Preclinical Imaging Facility (UC Berkeley, California, USA) in July 2019 using a GE Healthcare eXplore Locus Micro CT Scanner. The specimen was scanned using a conebeam energy of 80 kV, a current of 450 µA, 2,000 ms exposure time, and no filter, resulting in a voxel resolution of 20.523 µm. Visualization and three-dimensional reconstruction of the resulting µCT data were performed using the open-source software 3D Slicer v.4.13.0 (Fedorov et al., 2012). Additional_images_gifs_3Dmodel.zip - archive containing 3 folders of additionnal images, video (gifs) and a 3D model (STL file) : - Addendum_Figure_3 : additional images / views to the figure 3 presented in the paper. - Gifs_3d_models : gifs and STL 3d model of the scanned specimen - Images_gifs_inc_gastric_musc : images, gifs and 3d model similar as in the other folders, but displaying potential gastric muscles
DOI: 10.5281/zenodo.7687815
title: Supplementary data to: Internal anatomy of brachyuran crab from a Late Cretaceous methane seep and an overview of internal soft tissues in fossil decapod crustaceans

description: 001-Secretanella_sp_AAK_072019.zip - µCT scan data, 1.28 GB stack of DICOM images. High-resolution X-ray computed tomography (CT) scans of specimen ALMNH:Paleo:6522 were obtained at the Berkeley Preclinical Imaging Facility (UC Berkeley, California, USA) in July 2019 using a GE Healthcare eXplore Locus Micro CT Scanner. The specimen was scanned using a conebeam energy of 80 kV, a current of 450 µA, 2,000 ms exposure time, and no filter, resulting in a voxel resolution of 20.523 µm. Visualization and three-dimensional reconstruction of the resulting µCT data were performed using the open-source software 3D Slicer v.4.13.0 (Fedorov et al., 2012). Additional_images_gifs_3Dmodel.zip - archive containing 3 folders of additionnal images, video (gifs) and a 3D model (STL file) : - Addendum_Figure_3 : additional images / views to the figure 3 presented in the paper. - Gifs_3d_models : gifs and STL 3d model of the scanned specimen - Images_gifs_inc_gastric_musc : images, gifs and 3d model similar as in the other folders, but displaying potential gastric muscles
DOI: 10.6084/m9.figshare.22188802.v1
title: Test Cases for Reliability Assessment for Large-Scale Offshore Wind Farm Electrical Collector System Considering Post-Fault Network Recovery

description: This is the dataset for paper: Reliability Assessment for Large-Scale Offshore Wind Farm Electrical Collector System Considering Post-Fault Network Recovery
DOI: 10.5281/zenodo.7398402
title: Peer Preference Nominations Questionnaire / Cuestionario de Nominaciones de Preferencias entre Iguales // SOCIOMET-P_Data_IC_T1-Pre

description: Answers given by students in the first grade of Primary Education to the 4 items of the Peer Preference Nominations Questionnaire by García Bacete et al. (2014). Data collected in public schools in Castellón (Spain) in the autumn of the school year 2010-11. Information is provided on: a) positive and negative peer preference nominations, both emitted and received; b) expected positive and negative peer preference nominations, both emitted and received; c) and numerous combinations of dyadic fit and mismatch between all of them. Most of these results are also expressed as percentages over the number of students in the classroom minus one. The sociometric status of each student is one of the most relevant pieces of information. To learn more about our research and access to other datasets of this or other measures, follow the link GREI Longitudinal Project. Respuestas que los alumnos/as de primer curso de Educación Primaria dan a los 4 ítems del Cuestionario de Nominaciones de Preferencias entre Iguales de García Bacete et al. (2014). Datos recogidos en centros públicos de Castellón (España) en otoño del curso escolar 2010-11. Se proporciona información sobre: a) nominaciones positivas y negativas de preferencia de los compañeros, tanto emitidas como recibidas; b) nominaciones positivas y negativas esperadas de preferencia de los compañeros, tanto emitidas como recibidas; c) y numerosas combinaciones de ajuste y desajuste diádico entre todas ellas. La mayoría de estos resultados también se expresan en porcentajes sobre el número de alumnos del aula menos uno. El estatus sociométrico de cada alumno es una de las informaciones más relevantes. . Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace Proyecto Longitudinal GREI.
description: GRANTS / SUBVENCIONES: Ministerio de Economía y Competitividad (EDU2012-35930); Ministerio de Ciencia e Innovación (PSI2008-00541/PSIC); Generalitat Valenciana (11I028); Universitat Jaume I (UJI-B2019-29; P1-1A2012-04; P1-1B2009-33) y Fundación Dávalos-Fletcher REQUEST / RUEGO: Researchers using this dataset are kindly asked to inform the authors / Se agradecería a los investigadores que usen este dataset que informen a los autores.
DOI: 10.5281/zenodo.7398403
title: Peer Preference Nominations Questionnaire / Cuestionario de Nominaciones de Preferencias entre Iguales // SOCIOMET-P_Data_IC_T1-Pre

description: Answers given by students in the first grade of Primary Education to the 4 items of the Peer Preference Nominations Questionnaire by García Bacete et al. (2014). Data collected in public schools in Castellón (Spain) in the autumn of the school year 2010-11. Information is provided on: a) positive and negative peer preference nominations, both emitted and received; b) expected positive and negative peer preference nominations, both emitted and received; c) and numerous combinations of dyadic fit and mismatch between all of them. Most of these results are also expressed as percentages over the number of students in the classroom minus one. The sociometric status of each student is one of the most relevant pieces of information. To learn more about our research and access to other datasets of this or other measures, follow the link GREI Longitudinal Project. Respuestas que los alumnos/as de primer curso de Educación Primaria dan a los 4 ítems del Cuestionario de Nominaciones de Preferencias entre Iguales de García Bacete et al. (2014). Datos recogidos en centros públicos de Castellón (España) en otoño del curso escolar 2010-11. Se proporciona información sobre: a) nominaciones positivas y negativas de preferencia de los compañeros, tanto emitidas como recibidas; b) nominaciones positivas y negativas esperadas de preferencia de los compañeros, tanto emitidas como recibidas; c) y numerosas combinaciones de ajuste y desajuste diádico entre todas ellas. La mayoría de estos resultados también se expresan en porcentajes sobre el número de alumnos del aula menos uno. El estatus sociométrico de cada alumno es una de las informaciones más relevantes. . Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace Proyecto Longitudinal GREI.
description: GRANTS / SUBVENCIONES: Ministerio de Economía y Competitividad (EDU2012-35930); Ministerio de Ciencia e Innovación (PSI2008-00541/PSIC); Generalitat Valenciana (11I028); Universitat Jaume I (UJI-B2019-29; P1-1A2012-04; P1-1B2009-33) y Fundación Dávalos-Fletcher REQUEST / RUEGO: Researchers using this dataset are kindly asked to inform the authors / Se agradecería a los investigadores que usen este dataset que informen a los autores.
DOI: 10.5517/ccdc.csd.cc26rttm
title: CCDC 2048691: Experimental Crystal Structure Determination

description: Related Article:  Ankita Bal, Prasenjit Mal|2021|Chem. Sel.|6|9317|doi:10.1002/slct.202102758
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7545080
title: Replication package for The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review

description: In order to provide reproducibility, we have made all the data collected in the study titled: "The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review" as a replication package. This package includes the following files: A zip file containing the codes used for this Systematic Literature Review from NVIVO software. One separate file for each of the codes in the Zip file. (Code Summary.zip) Data collection form for different rounds of study. (Data_Collection_Form_Final.xlsx) Summary of number of papers retrieved in each round. (Number_of_Retrieved_studies.pdf)
DOI: 10.5281/zenodo.7545081
title: Replication package for The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review

description: In order to provide reproducibility, we have made all the data collected in the study titled: "The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review" as a replication package. This package includes a Zip file containing the code used for this Systematic Literature Review. One separate file for each of the codes.
DOI: 10.5281/zenodo.7548259
title: Replication package for The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review

description: In order to provide reproducibility, we have made all the data collected in the study titled: "The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review" as a replication package. This package includes the following files: A zip file containing the codes used for this Systematic Literature Review from NVIVO software. One separate file for each of the codes in the Zip file. (Code Summary.zip) Data collection form for different rounds of study. (Data_Collection_Form_Final.xlsx) Summary of number of papers retrieved in each round. (Number_of_Retrieved_studies.pdf)
DOI: 10.5281/zenodo.7628571
title: Replication package for The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review

description: In order to provide reproducibility, we have made all the data collected in the study titled: "The Use of Domain-Specific Languages for Visual Analytics: A Systematic Literature Review" as a replication package. This package includes the following files: A zip file containing the codes used for this Systematic Literature Review from NVIVO software. One separate file for each of the codes in the Zip file. (Code Summary.zip) Data collection form for different rounds of study. (Data_Collection_Form_Final.xlsx) Summary of number of papers retrieved in each round. (Number_of_Retrieved_studies.pdf)
DOI: 10.5281/zenodo.7687850
title: Data and scripts for reproducing "Optimisation and Analysis of Streamwise-Varying Wall-Normal Blowing in a Turbulent Boundary Layer"

description: This is the accompanying data and Python scripts to reproduce the figures in "Optimisation and Analysis of Streamwise-Varying Wall-Normal Blowing in a Turbulent Boundary Layer", submitted to Flow, Turbulence and Combustion.
DOI: 10.5281/zenodo.7687849
title: Data and scripts for reproducing "Optimisation and Analysis of Streamwise-Varying Wall-Normal Blowing in a Turbulent Boundary Layer"

description: This is the accompanying data and Python scripts to reproduce the figures in "Optimisation and Analysis of Streamwise-Varying Wall-Normal Blowing in a Turbulent Boundary Layer", submitted to Flow, Turbulence and Combustion.
DOI: 10.6084/m9.figshare.20054378
title: EVO10 dataset dictionnary with SMILES and ECFP4 connectivity score

description: 676 875 SMILES generated by EvoMol during enumeration experiments of the chemical spaces as defined by the ECFP4 of either ChEMBL or ZINC+ChEMBL. <br> JSON file of python dictionnary. Key: SMILES, value: dict {'HAC' # number of heavy atoms up to 10, 'swscore_ChEMBL' # % of ECFP4 of the molecule that belong to ChEMBL, 'swscore_ZINC' # % of ECFP4 of the molecule that belong to ZINC or ChEMBL} Only neutral singlet molecule without any atomic charges (formal or real) composed of H, C, N, O, F and S.
DOI: 10.6084/m9.figshare.20054378.v3
title: EVO10 dataset dictionnary with SMILES and ECFP4 connectivity score

description: 676 875 SMILES generated by EvoMol during enumeration experiments of the chemical spaces as defined by the ECFP4 of either ChEMBL or ZINC+ChEMBL. <br> JSON file of python dictionnary. Key: SMILES, value: dict {'HAC' # number of heavy atoms up to 10, 'swscore_ChEMBL' # % of ECFP4 of the molecule that belong to ChEMBL, 'swscore_ZINC' # % of ECFP4 of the molecule that belong to ZINC or ChEMBL} Only neutral singlet molecule without any atomic charges (formal or real) composed of H, C, N, O, F and S.
DOI: 10.6084/m9.figshare.20054378.v2
title: EVO10 dataset dictionnary with SMILES and sillywalk score

description: SMILES generated by EvoMol during enumeration experiments of the chemical spaces as defined by the ECFP4 of either ChEMBL or ZINC+ChEMBL. <br> JSON file of python dictionnary. Key: SMILES, value: dict {'HAC' # number of heavy atoms up to 10, 'swscore_ChEMBL' # % of ECFP4 of the molecule that belong to ChEMBL, 'swscore_ZINC' # % of ECFP4 of the molecule that belong to ZINC or ChEMBL} Only neutral singlet molecule without any atomic charges (formal or real) composed of H, C, N, O, F and S.
DOI: 10.21227/5g7f-hz40
title: ECG Signal Quality in Intermittent Long-Term Dry Electrode Recordings with Controlled Movement Artifacts

description: Wearable long-term monitoring applications are becoming more and more popular in both consumer and medical markets. In wearable ECG monitoring the data quality is dependent on the properties of the electrodes and how they contact the skin. Dry electrodes do not require any action from the user. They usually do not irritate the skin and they provide sufficiently high-quality data for ECG monitoring purposes during low user activity. We investigated prospective movement artifact resistant dry electrode materials for wearable ECG monitoring.The tested materials were 1) porous: conductive polymer, conductive silver fabric, conductive silver fabric with moisture retaining membrane and 2) solid: stainless steel, silver, and platinum. ECG was acquired from test subjects in a 10-minute continuous settling test and in a 48-hour intermittent long-term test. In the settling test the electrodes were stationary, whereas in the long-term test both stationary and controlled movement artifact tests were included. Signal-to-noise ratio (SNR) was used as a figure of merit to quantify the results.The SNR increased in all the electrode types during the settling test. In the long-term test the SNR was in general elevated further. The introduction of electrode movement reduced the SNR markedly. Solid electrodes had higher SNR than the porous electrodes. In the stationary testing stainless steel showed the highest SNR followed by platinum, silver, conductive polymer and conductive fabric. In the movement testing the platinum and stainless steel changed places and the rest of the order was the same.