cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21501303.v1
title: Additional file 5 of Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning

description: Additional file 5: Supplementary File S4.
DOI: 10.6084/m9.figshare.21501292
title: Additional file 4 of A simple and efficient method to quantify the cell parameters of the seed coat, embryo and silique wall in rapeseed

description: Additional file 4. Raw data of all the figures.
DOI: 10.6084/m9.figshare.21501292.v1
title: Additional file 4 of A simple and efficient method to quantify the cell parameters of the seed coat, embryo and silique wall in rapeseed

description: Additional file 4. Raw data of all the figures.
DOI: 10.6084/m9.figshare.21501325
title: Additional file 1 of DNA methylome in pancreatic cancer identified novel promoter hyper-methylation in NPY and FAIM2 genes associated with poor prognosis in Indian patient cohort

description: Additional file 1.Details of the PAAD samples in the TCGA cohort (n=185). The red marked samples were excluded from the analysis. Highlighted samples wre used in discovery cohort
DOI: 10.6084/m9.figshare.21501325.v1
title: Additional file 1 of DNA methylome in pancreatic cancer identified novel promoter hyper-methylation in NPY and FAIM2 genes associated with poor prognosis in Indian patient cohort

description: Additional file 1.Details of the PAAD samples in the TCGA cohort (n=185). The red marked samples were excluded from the analysis. Highlighted samples wre used in discovery cohort
DOI: 10.34740/kaggle/dsv/4447574
title: YouTube Daily
DOI: 10.5281/zenodo.7118103
title: Individual tree scans by TLS: the Italian dataset

description: The dataset contains single tree scans collected in different forests, with different forest managment, mainly during leaf off conditions. Forests belong to Italian ecosystems. The objective of this dataset is to publicly share the effort made from the Laboratory of forest geomatics (ForGeoLab) of CREA Research centre for forestry and wood. Such measures can be profitably used to measure tree volume, tree biomass, and tree architectural traits, without tree felling. TLS_SingleTrees_CREA_202209.ods is a metadata file contains some info on evrey single tree of this dataset. The ascii.zip file contains single tree scans as reported in metadata file.
DOI: 10.5281/zenodo.7118104
title: Individual tree scans by TLS: the Italian dataset

description: The dataset contains single tree scans collected in different forests, with different forest managment, mainly during leaf off conditions. Forests belong to Italian ecosystems. The objective of this dataset is to publicly share the effort made from the Laboratory of forest geomatics (ForGeoLab) of CREA Research centre for forestry and wood. Such measures can be profitably used to measure tree volume, tree biomass, and tree architectural traits, without tree felling. TLS_SingleTrees_CREA_202209.ods is a metadata file contains some info on evrey single tree of this dataset. The ascii.zip file contains single tree scans as reported in metadata file.
DOI: 10.5281/zenodo.7285178
title: Individual tree scans by TLS: the Italian dataset

description: The dataset contains single tree scans collected in different forests, with different forest managment, mainly during leaf off conditions. Forests belong to Italian ecosystems. The objective of this dataset is to publicly share the effort made from the Laboratory of forest geomatics (ForGeoLab) of CREA Research centre for forestry and wood. Such measures can be profitably used to measure tree volume, tree biomass, and tree architectural traits, without tree felling. TLS_SingleTrees_CREA_202209.ods is a metadata file contains some info on evrey single tree of this dataset. The ascii.zip file contains single tree scans as reported in metadata file.
DOI: 10.5281/zenodo.6773625
title: Automated Nuclear Pleomorphism Scoring in Breast Cancer: Slide-Study test set

description: This dataset contains data from the Slide-Study data set used in the paper: [1]<em> C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. M. Horlings, W. Weichert, J. M. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J.-M Bokhorst, J. van der Laak, F. Ciompi, Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. NPJ Breast Cancer, 2022.</em> The dataset consists of n=118 digital pathology whole-slide images (WSI) of breast cancer surgical resections, stained with hematoxylin and eosin (H&E) at Radboud University Medical Centers, Nijmegen (The Netherlands). The WSIs were scanned with a 3DHistech P1000 scanners at 0.25 um/px spacing, originally stored in MRXS file format. However, the WSIs made available here have been converted to TIFF format with a maximum spacing of 0.5 um/px. This was done to make slides broadly accessible (since MRXS files are sometimes not compatible with some digital pathology viewers or APIs), and with the same spacing used in the prediction of the pleomorphism score in the NPJ breast cancer paper. Note that we are solely releasing the Slide-Study test set used in [1]. Together with the data, we have released a web-based evaluation platform via the grand-challenge.org platform, which can be found at this link: https://breastpleomorphism.grand-challenge.org/. In this way, researchers can download the WSI from Zenodo, process them with their algorithm to predict a single pleomorphism score for each slide, compile the predictions as indicated on the grand-challenge.org page, and submit them, to compare the results with the ones presented in the paper and with the opinion of a panel of four pathologists involved in the study. The data is released under CC BY-NC 4.0 license.
DOI: 10.5281/zenodo.6773626
title: Automated Nuclear Pleomorphism Scoring in Breast Cancer: Slide-Study test set

description: This dataset contains data from the Slide-Study data set used in the paper: [1]<em> C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. M. Horlings, W. Weichert, J. M. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J.-M Bokhorst, J. van der Laak, F. Ciompi, Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. NPJ Breast Cancer, 2022.</em> The dataset consists of n=118 digital pathology whole-slide images (WSI) of breast cancer surgical resections, stained with hematoxylin and eosin (H&E) at Radboud University Medical Centers, Nijmegen (The Netherlands). The WSIs were scanned with a 3DHistech P1000 scanners at 0.25 um/px spacing, originally stored in MRXS file format. However, the WSIs made available here have been converted to TIFF format with a maximum spacing of 0.5 um/px. This was done to make slides broadly accessible (since MRXS files are sometimes not compatible with some digital pathology viewers or APIs), and with the same spacing used in the prediction of the pleomorphism score in the NPJ breast cancer paper. Note that we are solely releasing the Slide-Study test set used in [1]. Together with the data, we have released a web-based evaluation platform via the grand-challenge.org platform, which can be found at this link: https://breastpleomorphism.grand-challenge.org/. In this way, researchers can download the WSI from Zenodo, process them with their algorithm to predict a single pleomorphism score for each slide, compile the predictions as indicated on the grand-challenge.org page, and submit them, to compare the results with the ones presented in the paper and with the opinion of a panel of four pathologists involved in the study. The data is released under CC BY-NC 4.0 license.
DOI: 10.5281/zenodo.7285896
title: Automated Nuclear Pleomorphism Scoring in Breast Cancer: Slide-Study test set

description: This dataset contains data from the Slide-Study data set used in the paper: [1]<em> C. Mercan, M. Balkenhol, R. Salgado, M. Sherman, P. Vielh, W. Vreuls, A. Polonia, H. M. Horlings, W. Weichert, J. M. Carter, P. Bult, M. Christgen, C. Denkert, K. van de Vijver, J.-M Bokhorst, J. van der Laak, F. Ciompi, Deep learning for fully-automated nuclear pleomorphism scoring in breast cancer. NPJ Breast Cancer, 2022.</em> The dataset consists of n=118 digital pathology whole-slide images (WSI) of breast cancer surgical resections, stained with hematoxylin and eosin (H&E) at Radboud University Medical Centers, Nijmegen (The Netherlands). The WSIs were scanned with a 3DHistech P1000 scanners at 0.25 um/px spacing, originally stored in MRXS file format. However, the WSIs made available here have been converted to TIFF format with a maximum spacing of 0.5 um/px. This was done to make slides broadly accessible (since MRXS files are sometimes not compatible with some digital pathology viewers or APIs), and with the same spacing used in the prediction of the pleomorphism score in the NPJ breast cancer paper. Note that we are solely releasing the Slide-Study test set used in [1]. Together with the data, we have released a web-based evaluation platform via the grand-challenge.org platform, which can be found at this link: https://breastpleomorphism.grand-challenge.org/. In this way, researchers can download the WSI from Zenodo, process them with their algorithm to predict a single pleomorphism score for each slide, compile the predictions as indicated on the grand-challenge.org page, and submit them, to compare the results with the ones presented in the paper and with the opinion of a panel of four pathologists involved in the study. The data is released under CC BY-NC 4.0 license.
DOI: 10.18154/rwth-2022-09714
title: Corrigendum to "The Aachen gas-database v2021.2"

description: In the previous release and for the measurements in this database's subset [HPGMC v2021], a small correction to the electric field strength of ~1.7% was missing. For details see the accompanying pdf. The corrected data is systematically shifted to lower electric field strenghts. All other datasources were not affected.<br> The Institute of Experimental Physics III B at RWTH Aachen University operates the Aachen Gas Database. It consists of a large quantity of simulations and measurements of electron transport parameters in gas mixtures. In-house measurements were done with various detectors of the Gas Monitoring Chamber type (T2K-style Gas Monitoring Chambers and a High Pressure Gas Monitoring Chamber). To date, the simulation data runs were performed with MagBoltz, configured and run through Garfield++ on our local computing cluster, and PyBoltz. Some data was imported from publications, see the run names for the original sources. Currently, the data can be used in two different ways:<br>The Chair of Experimental Physics III B provides a web frontend, available at the link above. Alternatively, the complete database can be downloaded from this page and used locally. Instructions can be found in the accompanying pdf. This version v2021.2 was published in December 2021 and includes the runs up to 26790. The project is still ongoing.
DOI: 10.5517/ccdc.csd.cc2ckd5j
title: CCDC 2191457: Experimental Crystal Structure Determination

description: Related Article: Yu Teng, Rongrong Zhang, Bingbing Yang, Hong Yang, Xiang Li, Dali Yin, Xinchi Feng, Yulin Tian|2022|J.Mater.Chem.B|10|8642|doi:10.1039/D2TB01893D
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.7286032
title: Natural Earth data in Goode's Homolosine projection

description: Produced from NaturalEarth 1:50m Admin0 - Details map sub units cultural vectordata (version 5.1.1) and with Vectors for Goode's Homolosine projection Created with QGIS 3.20.3
description: {"references": ["Lu\u00eds Moreira de Sousa. (2018). Vectors for Goode's Homolosine projection (v1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.1841337", "Patterson, T., Kelso, N.V., 2022. Natural earth. https://www .naturalearthdata.com/"]}
DOI: 10.5281/zenodo.7286031
title: Natural Earth data in Goode's Homolosine projection

description: Produced from NaturalEarth 1:50m Admin0 - Details map sub units cultural vectordata (version 5.1.1) and with Vectors for Goode's Homolosine projection Created with QGIS 3.20.3
description: {"references": ["Lu\u00eds Moreira de Sousa. (2018). Vectors for Goode's Homolosine projection (v1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.1841337", "Patterson, T., Kelso, N.V., 2022. Natural earth. https://www .naturalearthdata.com/"]}
DOI: 10.5281/zenodo.7286376
title: hAMRonization Table Data

description: hAMRonization This repo contains the hAMRonization module and CLI parser tools that combine the outputs of 18 (as of 2022-09-25) disparate antimicrobial resistance gene detection tools into a single unified format. This is an implementation of the hAMRonization AMR detection specification scheme which supports gene presence/absence resistance and mutational resistance (if supported by the underlying tool). This supports a variety of summary options including an interactive summary.
DOI: 10.5281/zenodo.7286375
title: hAMRonization Table Data

description: hAMRonization This repo contains the hAMRonization module and CLI parser tools that combine the outputs of 18 (as of 2022-09-25) disparate antimicrobial resistance gene detection tools into a single unified format. This is an implementation of the hAMRonization AMR detection specification scheme which supports gene presence/absence resistance and mutational resistance (if supported by the underlying tool). This supports a variety of summary options including an interactive summary.
DOI: 10.21227/fh6x-1165
title: DRACO controlled experiment results 2021/2022 fall semester

description: This dataset contains the experiment results for the article named "Influence of Gamification Elements on Explicit Motive Dispositions"
DOI: 10.5281/zenodo.6535324
title: Unravelling the Nature of the Spin Excitations Disentangled from the Charge Contributions in a Doped Cuprate Superconductor

description: The nature of the spin excitations in superconducting cuprates is a key question toward a unified understanding of the cuprate physics from long-range antiferromagnetism to superconductivity. The intense spin excitations up to the over-doped regime revealed by resonant inelastic X-ray scattering bring new insights as well as problems—like understanding their persistence or their relation to the collective excitations in ordered magnets (magnons). Here, we study the evolution of the spin excitations upon hole-doping the superconducting cuprate Bi<sub>2</sub>Sr<sub>2</sub>CaCu<sub>2</sub>O<sub>8+δ</sub> by disentangling the spin from the charge excitations in the experimental cross section. We compare our experimental results against density matrix renormalization group calculations for a <em>t-J</em>-like model on a square lattice. Our results unambiguously confirm the persistence of the spin excitations, which are closely connected to the persistence of short-range magnetic correlations up to high doping. This suggests that the spin excitations in hole-doped cuprates are related to magnons—albeit short-ranged.
description: The experiments were performed at the ADRESS beamline of the Swiss Light Source at the Paul Scherrer Institut (PSI). The experimental work at PSI is supported by the Swiss National Science Foundation through project no. 200021_178867, and the Sinergia network Mott Physics Beyond the Heisenberg Model (MPBH) (SNSF Research Grants CRSII2 160765/1 and CRSII2 141962). The theoretical work is supported by the Narodowe Centrum Nauki (NCN, Poland) under Project Nos. 2016/22/E/ST3/00560 (C.E.A. and K.W.), 2021/40/C/ST3/00177 (C.E.A.) and 2016/23/B/ST3/00839 (K.W.). We acknowledge sup- port by the Interdisciplinary Centre for Mathematical and Computational Modeling (ICM), University of Warsaw (UW), within grant no G81-4. S.N. acknowledges support from SFB 1143 project A05 (project-id 247310070) of the Deutsche Forschungsgemeinschaft. T.C.A. acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 701647 (PSI-FELLOW-II-3i program).
DOI: 10.5281/zenodo.7081488
title: Unravelling the Nature of the Spin Excitations Disentangled from the Charge Contributions in a Doped Cuprate Superconductor

description: The nature of the spin excitations in superconducting cuprates is a key question toward a unified understanding of the cuprate physics from long-range antiferromagnetism to superconductivity. The intense spin excitations up to the over-doped regime revealed by resonant inelastic X-ray scattering bring new insights as well as problems—like understanding their persistence or their relation to the collective excitations in ordered magnets (magnons). Here, we study the evolution of the spin excitations upon hole-doping the superconducting cuprate Bi<sub>2</sub>Sr<sub>2</sub>CaCu<sub>2</sub>O<sub>8+δ</sub> by disentangling the spin from the charge excitations in the experimental cross section. We compare our experimental results against density matrix renormalization group calculations for a <em>t-J</em>-like model on a square lattice. Our results unambiguously confirm the persistence of the spin excitations, which are closely connected to the persistence of short-range magnetic correlations up to high doping. This suggests that the spin excitations in hole-doped cuprates are related to magnons—albeit short-ranged.
description: The experiments were performed at the ADRESS beamline of the Swiss Light Source at the Paul Scherrer Institut (PSI). The experimental work at PSI is supported by the Swiss National Science Foundation through project no. 200021_178867, and the Sinergia network Mott Physics Beyond the Heisenberg Model (MPBH) (SNSF Research Grants CRSII2 160765/1 and CRSII2 141962). The theoretical work is supported by the Narodowe Centrum Nauki (NCN, Poland) under Project Nos. 2016/22/E/ST3/00560 (C.E.A. and K.W.), 2021/40/C/ST3/00177 (C.E.A.) and 2016/23/B/ST3/00839 (K.W.). We acknowledge sup- port by the Interdisciplinary Centre for Mathematical and Computational Modeling (ICM), University of Warsaw (UW), within grant no G81-4. S.N. acknowledges support from SFB 1143 project A05 (project-id 247310070) of the Deutsche Forschungsgemeinschaft. T.C.A. acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 701647 (PSI-FELLOW-II-3i program).
DOI: 10.5281/zenodo.6535323
title: Unravelling the Nature of the Spin Excitations Disentangled from the Charge Contributions in a Doped Cuprate Superconductor

description: The nature of the spin excitations in superconducting cuprates is a key question toward a unified understanding of the cuprate physics from long-range antiferromagnetism to superconductivity. The intense spin excitations up to the over-doped regime revealed by resonant inelastic X-ray scattering bring new insights as well as problems—like understanding their persistence or their relation to the collective excitations in ordered magnets (magnons). Here, we study the evolution of the spin excitations upon hole-doping the superconducting cuprate Bi<sub>2</sub>Sr<sub>2</sub>CaCu<sub>2</sub>O<sub>8+δ</sub> by disentangling the spin from the charge excitations in the experimental cross section. We compare our experimental results against density matrix renormalization group calculations for a <em>t-J</em>-like model on a square lattice. Our results unambiguously confirm the persistence of the spin excitations, which are closely connected to the persistence of short-range magnetic correlations up to high doping. This suggests that the spin excitations in hole-doped cuprates are related to magnons—albeit short-ranged.
description: The experiments were performed at the ADRESS beamline of the Swiss Light Source at the Paul Scherrer Institut (PSI). The experimental work at PSI is supported by the Swiss National Science Foundation through project no. 200021_178867, and the Sinergia network Mott Physics Beyond the Heisenberg Model (MPBH) (SNSF Research Grants CRSII2 160765/1 and CRSII2 141962). The theoretical work is supported by the Narodowe Centrum Nauki (NCN, Poland) under Project Nos. 2016/22/E/ST3/00560 (C.E.A. and K.W.), 2021/40/C/ST3/00177 (C.E.A.) and 2016/23/B/ST3/00839 (K.W.). We acknowledge sup- port by the Interdisciplinary Centre for Mathematical and Computational Modeling (ICM), University of Warsaw (UW), within grant no G81-4. S.N. acknowledges support from SFB 1143 project A05 (project-id 247310070) of the Deutsche Forschungsgemeinschaft. T.C.A. acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 701647 (PSI-FELLOW-II-3i program).
DOI: 10.6084/m9.figshare.21501390
title: A high-resolution gridded grazing dataset of grassland ecosystem on the Qinghai–Tibet Plateau in 1982–2015_V2

description: The gridded grazing dataset of the grassland ecosystem on the Qinghai–Tibet Plateau for 1982–2015 was named according to the year corresponding to the grazing data and stored in GeoTIFF format in SU per pixel per year. The spatial resolution was 0.083°, with an annual temporal resolution. The geographic coordinate system of the dataset was GCS_WGS_1984. The dataset has the potential to elucidate the spatiotemporal variation in human activities, clarify the mechanisms of ecological processes, and guide the sustainable management of grassland ecosystems
DOI: 10.5281/zenodo.7286364
title: MLC supervised signature files for the 1st and 2nd cycles of the Q-XRMA analytical runs

description: At this link we make available all the MLC supervised signature files for the 1st and 2nd cycles of the Q-XRMA analytical runs applied to volcanic products of the July 3 and August 28, 2019 paroxysmal eruptions occurred at Stromboli volcano.
DOI: 10.5281/zenodo.7286363
title: MLC supervised signature files for the 1st and 2nd cycles of the Q-XRMA analytical runs

description: At this link we make available all the MLC supervised signature files for the 1st and 2nd cycles of the Q-XRMA analytical runs applied to volcanic products of the July 3 and August 28, 2019 paroxysmal eruptions occurred at Stromboli volcano.
DOI: 10.6084/m9.figshare.21501426
title: Quality of herbal systematic reviews and references OPENDATA Nov22.xlsx

description: Quality assessment of a sample of herbal systematic reviews, adding to previous dataset, this time with references to publications.
DOI: 10.6084/m9.figshare.21501441
title: S2: Zircon U–Pb, oxygen and hafnium isotopic characteristics of the Neoarchaean–Palaeoproterozoic Betsiboka Suite, Madagascar: tracing source to sink pathways in Proterozoic and Phanerozoic provenance studies

description: Summary of zircon characteristics
DOI: 10.6084/m9.figshare.21501441.v1
title: S2: Zircon U–Pb, oxygen and hafnium isotopic characteristics of the Neoarchaean–Palaeoproterozoic Betsiboka Suite, Madagascar: tracing source to sink pathways in Proterozoic and Phanerozoic provenance studies

description: Summary of zircon characteristics
DOI: 10.6084/m9.figshare.21501444
title: S4: Zircon U–Pb, oxygen and hafnium isotopic characteristics of the Neoarchaean–Palaeoproterozoic Betsiboka Suite, Madagascar: tracing source to sink pathways in Proterozoic and Phanerozoic provenance studies

description: SHRIMP SI oxygen isotopic data collected from zircon
DOI: 10.6084/m9.figshare.21501444.v1
title: S4: Zircon U–Pb, oxygen and hafnium isotopic characteristics of the Neoarchaean–Palaeoproterozoic Betsiboka Suite, Madagascar: tracing source to sink pathways in Proterozoic and Phanerozoic provenance studies

description: SHRIMP SI oxygen isotopic data collected from zircon