cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23623950
title: Luecken Cite-seq human bone marrow 2021 preprocessing

description: Dataset published by Luecken et al. 2021 which contains data from human bone marrow measured through joint profiling of single-nucleus RNA and Antibody-Derived Tags (ADTs) using the 10X 3' Single-Cell Gene Expression kit with Feature Barcoding in combination with the BioLegend TotalSeq B Universal Human Panel v1.0.<b>File Description</b><i>cite_quality_control.h5mu</i>: Filtered cell by feature MuData object after quality control.<i>cite_normalization.h5mu</i>: MuData object of normalized data using DSB (denoised and scaled by background) normalization.<i>cite_doublet_removal_xdbt.h5mu:</i> MuData of data after doublet removal based on known cell type markers. Cells were removed if they were double positive for mutually exclusive markers with a DSB value &gt;2.5.<i>cite_dimensionality_reduction.h5mu:</i> MuData of data after dimensionality reduction.<i>cite_batch_correction.h5mu:</i> MuData of data after batch correction.<b>Citation</b>Luecken, M. D. <i>et al.</i> A sandbox for prediction and integration of DNA, RNA, and proteins in single cells. Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2021).<b>Original data link</b>https://openproblems.bio/neurips_docs/data/dataset/
DOI: 10.6084/m9.figshare.23623950.v1
title: Luecken Cite-seq human bone marrow 2021 preprocessing

description: Dataset published by Luecken et al. 2021 which contains data from human bone marrow measured through joint profiling of single-nucleus RNA and Antibody-Derived Tags (ADTs) using the 10X 3' Single-Cell Gene Expression kit with Feature Barcoding in combination with the BioLegend TotalSeq B Universal Human Panel v1.0. <strong>File Description</strong> <em>cite_quality_control.h5mu</em>: Filtered cell by feature MuData object after quality control. <em>cite_normalization.h5mu</em>: MuData object of normalized data using DSB (denoised and scaled by background) normalization. <em>cite_doublet_removal_xdbt.h5mu:</em> MuData of data after doublet removal based on known cell type markers. Cells were removed if they were double positive for mutually exclusive markers with a DSB value &gt;2.5. <strong>Citation</strong> Luecken, M. D. <em>et al.</em> A sandbox for prediction and integration of DNA, RNA, and proteins in single cells. Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (2021). <strong>Original data link</strong> https://openproblems.bio/neurips_docs/data/dataset/
DOI: 10.5281/zenodo.7589087
title: Dataset related to article "Archival skin biopsy specimens as a tool for miRNA-based diagnosis: Technical and post-analytical considerations".

description: microRNA raw data
description: THIS WORK WAS SUPPORTED WITH PAIN-NET PROJECT: MOLECULE-TO-MAN PAIN NETWORK, EU RESEARCH FRAMEWORK PROGRAMME H2020/MARIE SKŁODOWSKA-CURIE ACTIONS, GRANT AGREEMENT NUMBER 721841 AND ITALIAN MINISTRY OF HEALTH (RRC).
DOI: 10.5281/zenodo.7589088
title: Dataset related to article "Archival skin biopsy specimens as a tool for miRNA-based diagnosis: Technical and post-analytical considerations".

description: microRNA raw data
description: THIS WORK WAS SUPPORTED WITH PAIN-NET PROJECT: MOLECULE-TO-MAN PAIN NETWORK, EU RESEARCH FRAMEWORK PROGRAMME H2020/MARIE SKŁODOWSKA-CURIE ACTIONS, GRANT AGREEMENT NUMBER 721841 AND ITALIAN MINISTRY OF HEALTH (RRC).
DOI: 10.34740/kaggle/dsv/6615966
title: COVID Vaccination in World (updated daily)
DOI: 10.25919/m6zd-yg48
title: Parkes observations for project P1186 semester 2023APRS_03

description: The multi-frequency observation of the subpulse drifting of PSR J0934-5249 with Parkers. the PSR J0934-5249 was observed at a single frequency (325 MHz) using the GMRT. Its single pulse sequence shows clear coherent drifting with some short nulls. 2DFS plot also shows a clear feature confirming that this pulsar is a coherent drifter. The number of nulls were small for us to study any null induced drift rate changes in this pulsar. Arun Naidu et al. 2017 Estimated the drifting and nulling parameters for the first time in this pulsar. The observations using the Giant Meterwave Radio Telescope for PSR J0934-5249, but there was no further explanation of the pulsar (Basu et al. 2021). Both observations were made at low broadband. We propose using the ultra wideband reciver of Parkes to observe these pulsars for a long time, so that to give a detailed analysis of these pulsar on the wide bandwidth.
DOI: 10.6084/m9.figshare.24250339
title: <b>Unilateral interlaminar fenestration on the convex side provides a reliable access for intrathecal administration of nusinersen in spinal muscular atrophy: a retrospective study</b>

description: <b>Unilateral interlaminar fenestration on the convex side provides a reliable access for intrathecal administration of nusinersen in spinal muscular atrophy: a retrospective study</b>
DOI: 10.6084/m9.figshare.24250339.v1
title: <b>Unilateral interlaminar fenestration on the convex side provides a reliable access for intrathecal administration of nusinersen in spinal muscular atrophy: a retrospective study</b>

description: <b>Unilateral interlaminar fenestration on the convex side provides a reliable access for intrathecal administration of nusinersen in spinal muscular atrophy: a retrospective study</b>
DOI: 10.5281/zenodo.1260335
title: Leap Motion Hand Gestures for Interaction with 3D Virtual Music Instruments (LMHGIf3DVMI)

description: The aim of the dataset is to investigate machine learning real-time gesture recognizer captured with a Leap Motion sensor to control the performance of a virtual 3D musical instrument. The dataset includes from 10-15 samples for each of the 8 gesture classes collected from 10 participants (5 female and 5 male) using the Leap Motion sensor.
DOI: 10.5281/zenodo.1260336
title: Leap Motion Hand Gestures for Interaction with 3D Virtual Music Instruments (LMHGIf3DVMI)

description: The aim of the dataset is to investigate machine learning real-time gesture recognizer captured with a Leap Motion sensor to control the performance of a virtual 3D musical instrument. The dataset includes from 10-15 samples for each of the 8 gesture classes collected from 10 participants (5 female and 5 male) using the Leap Motion sensor.
DOI: 10.25405/data.ncl.24106158
title: Simulation data for reproduction of clinical non-invasive blood pressure measurements

description: Blood pressure measurement. Recordings of blood pressure cuff pressures from 7 subjects. All subjects are anonymous. Each file contains repeat measurement of which 10 are identified for analysis. The published paper analyses the repeatability and accuracy of reproduction of the cuff waveforms that have an application for future assessment of different automated devices, of which there are many hundreds of types available.
DOI: 10.25405/data.ncl.24106158.v1
title: Simulation data for reproduction of clinical non-invasive blood pressure measurements

description: Blood pressure measurement. Recordings of blood pressure cuff pressures from 7 subjects. All subjects are anonymous. Each file contains repeat measurement of which 10 are identified for analysis. The published paper analyses the repeatability and accuracy of reproduction of the cuff waveforms that have an application for future assessment of different automated devices, of which there are many hundreds of types available.
DOI: 10.6084/m9.figshare.22718008.v1
title: PET/CT data for PDL auto-segmentation project

description: PET/CT NIfTI data for paper corresponding to: https://www.medrxiv.org/content/10.1101/2023.02.20.23286188v1. This dataset is comprised of 67 (anonymized) head and neck cancer cases from MD Anderson Cancer Center. Each case contains a CT image, PET image, and primary gross tumor volume segmentation (binary mask), all in NIfTI format. These data were used as an independent test set for the deep learning algorithms in our study. The images and masks were cropped to be consistent with the 2021 HECKTOR Challenge data formatting. Notably, these cases were used in part for the MDA contribution to the 2022 edition of the HECKTOR Challenge.
DOI: 10.6084/m9.figshare.24250414
title: PRISMA-ScR-Fillable-Checklist_10Sept2019.docx

description: prisma scr checklist
DOI: 10.5281/zenodo.8410643
title: NabilaKumala/5026211016: Dataset Benchmark Kebijakan Privasi Pengguna Aplikasi Kesehatan

description: Dataset Benchmark Kebijakan Aplikasi Telemedisin.xlsx
DOI: 10.5281/zenodo.8410662
title: NabilaKumala/5026211016: Dataset Benchmark Kebijakan Privasi Pengguna Aplikasi Kesehatan

description: Dataset Benchmark Kebijakan Aplikasi Telemedisin.xlsx
DOI: 10.6084/m9.figshare.11342390
title: CLASSnmat: a global Night Marine Air Temperature dataset

description: This is a 5-degree resolution, monthly, global dataset of marine air temperature. The temperature values are obtained from ship observations extracted from the ICOADS dataset (v3).
DOI: 10.6084/m9.figshare.11342390.v1
title: CLASSnmat: a global Night Marine Air Temperature dataset

description: This is a 5-degree resolution, monthly, global dataset of marine air temperature. The temperature values are obtained from ship observations extracted from the ICOADS dataset (v3).
DOI: 10.6084/m9.figshare.22147964
title: An Empirical Investigation into the Influence of Software Communities’ Cultural and Geographical Dispersion on Productivity – Online Appendix

description: This is the online appendix for the research paper titled “An Empirical Investigation into the Influence of Software Communities’ Cultural and Geographical Dispersion on Productivity.”<b>Abstract</b>Estimating and understanding software development productivity represent crucial tasks for researchers and practitioners. Although different works focused on evaluating the impact of human factors on productivity, a few explored the influence of cultural/geographical diversity in software development communities. More particularly, all previous treatise addresses cultural aspects as abstract concepts without providing a quantitative representation. Improved knowledge of these matters might help project managers to assemble more productive teams and tool vendors to design software analytics toolkits that may better estimate productivity. This paper has the goal of enlarging the existing body of knowledge on the factors affecting productivity by focusing on cultural and geographical dispersion of a development community—namely, how diverse a community is in terms of cultural attitudes and geographical collocation of the members who belong to it. To reach this goal, we performed a mixed-method empirical study. First, we built a statistical model relating dispersion metrics with the productivity of 25 open-source communities on Github. Then, we performed a confirmatory survey with 140 practitioners. The key results of our study indicate that cultural and geographical dispersion considerably impact productivity, thus encouraging managers and practitioners to consider such aspects during all the phases of the software development lifecycle. We conclude our paper by elaborating on the main insights from our analyses and instilling implications that may drive further research.
DOI: 10.5281/zenodo.8264468
title: Magnetic Bloch point and vortex configurations

description: This dataset is associated to the arxiv publication "Energetics and Dynamics of a stable Bloch point" by Winkler et al., arxiv:2303.10091 (2023). Link: https://arxiv.org/abs/2303.10091 The set contains stable Bloch point and vortex configurations in various discretizations, disk shapes and models (Heisenberg or micromagnetic), as well as snapshots of dynamics after shifting the structures out of equilibrium. One jupyter notebook is added to plot the data directly within this repository. The github repsitory to produce this states and to verify the results of the study can be found here: https://github.com/WinklerTB/BP_paper_2023 The simulation code (MicMag2) can be found here: https://github.com/WinklerTB/MicMag2 Also the ubermag framework was partly used to evaluate the data: https://ubermag.github.io/
DOI: 10.5281/zenodo.8264467
title: Magnetic Bloch point and vortex configurations

description: This dataset is associated to the arxiv publication "Energetics and Dynamics of a stable Bloch point" by Winkler et al., arxiv:2303.10091 (2023). Link: https://arxiv.org/abs/2303.10091 The set contains stable Bloch point and vortex configurations in various discretizations, disk shapes and models (Heisenberg or micromagnetic), as well as snapshots of dynamics after shifting the structures out of equilibrium. One jupyter notebook is added to plot the data directly within this repository. The github repsitory to produce this states and to verify the results of the study can be found here: https://github.com/WinklerTB/BP_paper_2023 The simulation code (MicMag2) can be found here: https://github.com/WinklerTB/MicMag2 Also the ubermag framework was partly used to evaluate the data: https://ubermag.github.io/
DOI: 10.5281/zenodo.8410729
title: EMAC/MESSy v2.54.0 model (EMAC) aviation emission inventories as calculated by AirTraf 2.0

description: The data provided is a ASCII file which contains an aviation emission inventories for one year of a traffic sample over Europe (85 flights) as calculated by AirTraf submodel within the global modelling system EMAC. The submodel AirTraf enabling aircraft trajectory planning is implemented in the chemistry-climate model EMAC with the coupling to the submodel AirTraf. EMAC is a numerical chemistry and climate simulation system that includes submodels describing tropospheric and middle atmosphere processes and their interaction with oceans, land, and influences coming from anthropogenic emissions. It comprises the second version of the Modular Earth Submodel System (MESSy2) to link multi-institutional computer codes, in which the core atmospheric model is the fifth generation European Center Hamburg general circulation model (ECHAM5). We use a horizontal resolution of T42, with 31 hybrid vertical pressure levels up to 10 hPa (~30 km, T42L31ECMWF) and a time step of 20 minutes, with meteorology nudged to ERA5 reanalysis data as boundary conditions. AirTraf allows to calculate aircraft trajectories for given city-pairs with respect to dedicated routing strategies, considering meteorological conditions calculated by ECHAM5 online. Associated with these identified aircraft trajectories, the climate effect from aviation emissions along these trajectories is calculated from the submodel ACCF version 1.0 of EMAC. ACCF employs the aCCFs, that provide spatially and temporally resolved information on the climate effects of aviation emissions to quantify CO<sub>2</sub> and non-CO<sub>2</sub> effects. Specifically, they allow identifying regions of the atmosphere where aviation emissions induce a strong climate effect, e.g. via the formation of warming contrails or the production of radiatively active species like ozone. Thus, using these aCCFs, the estimated climate effect of aviation emissions and their spatial and temporal variability is available for the model domain: Subsequently, this is provided to AirTraf in order to enable not only estimating climate effects for calculated aircraft trajectories, but also planning of climate-optimized flight trajectories. The combination of EMAC/AirTraf/ACCF is applied here to simulate flight trajectories as great circle routes between city pairs (equal to AirClim), considering the variability of synoptic weather patterns in a continuous representation of the global atmosphere, and to quantitatively assess total climate effect and overall performance of flights.
DOI: 10.5281/zenodo.8410728
title: EMAC/MESSy v2.54.0 model (EMAC) aviation emission inventories as calculated by AirTraf 2.0

description: The data provided is a ASCII file which contains an aviation emission inventories for one year of a traffic sample over Europe (85 flights) as calculated by AirTraf submodel within the global modelling system EMAC. The submodel AirTraf enabling aircraft trajectory planning is implemented in the chemistry-climate model EMAC with the coupling to the submodel AirTraf. EMAC is a numerical chemistry and climate simulation system that includes submodels describing tropospheric and middle atmosphere processes and their interaction with oceans, land, and influences coming from anthropogenic emissions. It comprises the second version of the Modular Earth Submodel System (MESSy2) to link multi-institutional computer codes, in which the core atmospheric model is the fifth generation European Center Hamburg general circulation model (ECHAM5). We use a horizontal resolution of T42, with 31 hybrid vertical pressure levels up to 10 hPa (~30 km, T42L31ECMWF) and a time step of 20 minutes, with meteorology nudged to ERA5 reanalysis data as boundary conditions. AirTraf allows to calculate aircraft trajectories for given city-pairs with respect to dedicated routing strategies, considering meteorological conditions calculated by ECHAM5 online. Associated with these identified aircraft trajectories, the climate effect from aviation emissions along these trajectories is calculated from the submodel ACCF version 1.0 of EMAC. ACCF employs the aCCFs, that provide spatially and temporally resolved information on the climate effects of aviation emissions to quantify CO<sub>2</sub> and non-CO<sub>2</sub> effects. Specifically, they allow identifying regions of the atmosphere where aviation emissions induce a strong climate effect, e.g. via the formation of warming contrails or the production of radiatively active species like ozone. Thus, using these aCCFs, the estimated climate effect of aviation emissions and their spatial and temporal variability is available for the model domain: Subsequently, this is provided to AirTraf in order to enable not only estimating climate effects for calculated aircraft trajectories, but also planning of climate-optimized flight trajectories. The combination of EMAC/AirTraf/ACCF is applied here to simulate flight trajectories as great circle routes between city pairs (equal to AirClim), considering the variability of synoptic weather patterns in a continuous representation of the global atmosphere, and to quantitatively assess total climate effect and overall performance of flights.
DOI: 10.5281/zenodo.8407512
title: Data deposition for "Nanoscale organization of the endogenous ASC speck"

description: dSTORM localizations of manuscript "Nanoscale organization of the endogenous ASC speck" (DOI: https://doi.org/10.1101/2021.09.17.460822)
DOI: 10.5281/zenodo.8399325
title: Data deposition for "Nanoscale organization of the endogenous ASC speck"

description: dSTORM localizations of manuscript "Nanoscale organization of the endogenous ASC speck" (DOI: https://doi.org/10.1101/2021.09.17.460822)
DOI: 10.48366/r642596
title: Overview of clustering ship trajectories based on AIS data using machine learning methods

description: The table shows an overview and comparison of research on different trajectory clustering methods in water transport based on Automatic Identification System (AIS) data using machine learning. Trajectory clustering is a process of grouping similar trajectories together based on their spatial and temporal characteristics. In the context of maritime traffic, trajectory clustering involves grouping vessel trajectories that have similar movement patterns, such as speed, direction, and location. This process helps to identify common traffic patterns and can be used to extract traffic routes between ports, route planning, traffic management and anomaly detection. Trajectory clustering is achieved by different methods such as K-means clustering, Hierarchical clustering, DBSCAN, OPTICS, Mean-shift clustering, spectral clustering, fuzzy clustering, Douglas and Peucker algorithm etc. The choice of method depends on the specific problem and the characteristics of the data.
DOI: 10.5517/ccdc.csd.cc29kbrz
title: CCDC 2131831: Experimental Crystal Structure Determination

description: Related Article: Chun Mao Yuan|2023|CSD Communication|||
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.cc2bm729
title: CCDC 2163430: Experimental Crystal Structure Determination

description: Related Article: Xingxing Yan|2023|CSD Communication|||
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.cc2bsc9t
title: CCDC 2168366: Experimental Crystal Structure Determination

description: Related Article: Valentyna Slyusarchuk, Barnaby O'Brien, Chris Hawes|2023|CSD Communication|||
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.cc2by41h
title: CCDC 2172946: Experimental Crystal Structure Determination

description: Related Article: Yan Zhang, Liji Gu|2023|CSD Communication|||
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.24240007
title: AJP Figures data updated

description: ATP promoted the migration of vascular wall resident CD34+ cells through activating STIM1/MAPK signaling pathway to participate in angiogenesis and vascular repair.
DOI: 10.6084/m9.figshare.24240007.v1
title: AJP Figures data updated

description: ATP promoted the migration of vascular wall resident CD34+ cells through activating STIM1/MAPK signaling pathway to participate in angiogenesis and vascular repair.
DOI: 10.5281/zenodo.3618452
title: EU Lighting Efficacy Policy History Tool

description: As of 2020, the EU has published three regulations on lighting efficiency. This Excel tool can be used to calculate the corresponding luminous efficacy [lm/W] for each regulation. Compiled as part of the research project "What factors drive innovation in energy technologies? The role of technology spillovers and government investment", funded by the Alfred P. Sloan Foundation.
description: {"references": ["http://data.europa.eu/eli/reg/2009/244/oj", "https://ec.europa.eu/energy/sites/ener/files/documents/Implementation%20Guide%20Lighting.pdf", "http://data.europa.eu/eli/reg/2012/1194/oj", "http://data.europa.eu/eli/reg/2019/2020/oj"]}
DOI: 10.5281/zenodo.3618453
title: EU Lighting Efficacy Policy History Tool

description: As of 2020, the EU has published three regulations on lighting efficiency. This Excel tool can be used to calculate the corresponding luminous efficacy [lm/W] for each regulation. Compiled as part of the research project "What factors drive innovation in energy technologies? The role of technology spillovers and government investment", funded by the Alfred P. Sloan Foundation.
description: {"references": ["http://data.europa.eu/eli/reg/2009/244/oj", "https://ec.europa.eu/energy/sites/ener/files/documents/Implementation%20Guide%20Lighting.pdf", "http://data.europa.eu/eli/reg/2012/1194/oj", "http://data.europa.eu/eli/reg/2019/2020/oj"]}