cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7490484
title: MUSES Fractional Vegetation Coverage (FVC) 8-Day Global 500m SIN Grid in 2018

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500m spatial resolution and 8-day temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2018. Please <em><strong>click here</strong> to download the MUSES FVC product <strong>in 2017</strong></em>, and <em><strong>click here</strong> to download the MUSES FVC product <strong>in 2019</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global; Temporal Coverage: 2018; Spatial Resolution: 500m; Temporal Resolution: 8 days; Projection: Sinusoidal; Data Format: HDF; Scale: 0.004; Valid Range: 0 – 250. <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7494671
title: postdoc

description: allpostdoc
DOI: 10.5281/zenodo.7494670
title: postdoc

description: allpostdoc
DOI: 10.5519/qd.9co6ju2r
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (8 records)
DOI: 10.21227/xgj7-c707
title: Rea-End Vehicles Collusion Detection in Internet of Vehicles  

description: The dataset for the vehicles collusion detection in internet of vehicles is generated from internet of vehicles enviornment using VSSIM. The detail procedure of the data collection and the preprocessing procedure can be found in the publihsed paper.
DOI: 10.5281/zenodo.7016552
title: The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins

description: Supplementary Dataset for the work entitled "The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins". This dataset includes files for the T3SS2 reconstructed phylogenetic tree (Newick tree and fasta file), hierarchical clustering data analysis file from MORPHEUS, Table S1 with genome accession numbers, and all the data of the absence/presence of T3SS2-related components, Table S2 with the prediction of novel effector proteins.
DOI: 10.5281/zenodo.7016551
title: The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins

description: Supplementary Dataset for the work entitled "The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins". This dataset includes files for the T3SS2 reconstructed phylogenetic tree (Newick tree and fasta file), hierarchical clustering data analysis file from MORPHEUS, Table S1 with genome accession numbers, and all the data of the absence/presence of T3SS2-related components, Table S2 with the prediction of novel effector proteins.
DOI: 10.5281/zenodo.7308526
title: The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins

description: Supplementary Dataset for the work entitled "The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins". This dataset includes files for the T3SS2 reconstructed phylogenetic tree (Newick tree and fasta file), hierarchical clustering data analysis file from MORPHEUS, Table S1 with genome accession numbers, and all the data of the absence/presence of T3SS2-related components, Table S2 with the prediction of novel effector proteins.
DOI: 10.5281/zenodo.7497846
title: The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins

description: Supplementary Dataset for the work entitled "The Vibrio Type III Secretion System 2 is not restricted to the Vibrionaceae and encodes differentially distributed repertoires of effector proteins". This dataset includes files for the T3SS2 reconstructed phylogenetic tree (Newick tree and fasta file), hierarchical clustering data analysis file from MORPHEUS, Table S1 with genome accession numbers, and all the data of the absence/presence of T3SS2-related components, Table S2 with the prediction of novel effector proteins.
DOI: 10.34740/kaggle/dsv/4796209
title: Mahanagar Yatayat Dataset
DOI: 10.5281/zenodo.7078808
title: The TDI data and corresponding PSD files for PyCBC LISA documentation example

description: The TDI data and corresponding PSD files for PyCBC LISA documentation example, generated from LDC-Sangria<em> </em>dataset.
DOI: 10.5281/zenodo.7078835
title: The TDI data and corresponding PSD files for PyCBC LISA documentation example

description: The TDI data and corresponding PSD files for PyCBC LISA documentation example, generated from LDC-Sangria<em> </em>dataset.
DOI: 10.5281/zenodo.7253532
title: The TDI data and corresponding PSD files for PyCBC LISA documentation example

description: The TDI data and corresponding PSD files for PyCBC LISA documentation example, generated from LDC-Sangria<em> </em>dataset.
DOI: 10.5281/zenodo.7255549
title: The TDI data and corresponding PSD files for PyCBC LISA documentation example

description: The TDI data and corresponding PSD files for PyCBC LISA documentation example, generated from LDC-Sangria<em> </em>dataset.
DOI: 10.5281/zenodo.7433487
title: The TDI data and corresponding PSD files for PyCBC LISA documentation example

description: The TDI data and corresponding PSD files for PyCBC LISA documentation example, generated from LDC-Sangria<em> </em>dataset.
DOI: 10.5281/zenodo.7497853
title: The TDI data and PSD/sensitivity-related files for PyCBC LISA documentation example

description: The TDI data and PSD/sensitivity-related files for PyCBC LISA documentation example, most of them are generated from LDC-Sangria<em> </em>dataset.
DOI: 10.5281/zenodo.7078807
title: The TDI data and PSD/sensitivity-related files for PyCBC LISA documentation example

description: The TDI data and PSD/sensitivity-related files for PyCBC LISA documentation example, most of them are generated from LDC-Sangria<em> </em>dataset.
DOI: 10.5281/zenodo.6033560
title: Data set for "Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2"

description: Data sets for the publication "Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS<sub>2</sub>", doi:10.1021/acsnano.1c07065
description: {"references": ["doi:10.1021/acsnano.1c07065"]}
DOI: 10.5281/zenodo.6033559
title: Data set for "Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2"

description: Data sets for the publication "Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS<sub>2</sub>", doi:10.1021/acsnano.1c07065
description: {"references": ["doi:10.1021/acsnano.1c07065"]}
DOI: 10.5281/zenodo.7497784
title: raw data for a manuscript submitted to Materials and Structures Journal

description: raw data for a manuscript submitted to Materials and Structures Journal. Includes: coating thickness, jointly with economic and environmental calculations
DOI: 10.5281/zenodo.7497783
title: raw data for a manuscript submitted to Materials and Structures Journal

description: raw data for a manuscript submitted to Materials and Structures Journal. Includes: coating thickness, jointly with economic and environmental calculations
DOI: 10.5281/zenodo.7099499
title: Datasets and models about the geophysical characterization of the Mt. Melbourne Volcanic Field (Northern Victoria Land, Antarctica)

description: Supplementary materials about the geophysical characterization of the Mt. Melbourne Volcanic Field
DOI: 10.6084/m9.figshare.21766499
title: Supplementary Dataset for: "Genetic basis for the biodegradation of a polyether-polyurethane-acrylic copolymer by a landfill microbial community inferred by metagenomic deconvolution analysis"

description: This Dataset contains raw data referring to the manuscript: "Genetic basis for the biodegradation of a polyether-polyurethane-acrylic copolymer by a landfill microbial community inferred by metagenomic deconvolution analysis" by Sánchez-Reyes et al.,
DOI: 10.5281/zenodo.6669857
title: BLASTDB NCBI GeneBank viruses complete genomes 2023/01/01

description: Database: NCBI GeneBank Viruses Complete genomes 2023_01_01<br> 86,641 sequences; 2,391,589,518 total bases<br> Date: Jan 1, 2023 4:32 PM<br> BLASTDB Version: 5
description: This database is part of https://bitbucket.org/plyusnin/lazypipe project
description: {"references": ["https://doi.org/10.1093/ve/veaa091"]}
DOI: 10.5281/zenodo.6669858
title: BLASTDB NCBI GeneBank viruses complete genomes 2022/06/19

description: BALSTDB<br> NCBI GeneBank viruses complete genomes, updated 2022/06/19<br> 81,634 sequences; 1,748,075,095bp
description: This database is part of https://bitbucket.org/plyusnin/lazypipe project
DOI: 10.5281/zenodo.7285160
title: BLASTDB NCBI GeneBank viruses complete genomes 2022/11/04

description: Database: NCBI GeneBank Viruses Complete genomes 2022_11_04<br> 86,352 sequences; 2,371,168,247 total bases<br> Date: Nov 4, 2022 5:03 PM<br> BLASTDB Version: 5
description: This database is part of https://bitbucket.org/plyusnin/lazypipe project
description: {"references": ["https://doi.org/10.1093/ve/veaa091"]}
DOI: 10.5281/zenodo.7303045
title: BLASTDB NCBI GeneBank viruses complete genomes 2023/01/01

description: Database: NCBI GeneBank Viruses Complete genomes 2023_01_01<br> 86,641 sequences; 2,391,589,518 total bases<br> Date: Jan 1, 2023 4:32 PM<br> BLASTDB Version: 5
description: This database is part of https://bitbucket.org/plyusnin/lazypipe project
description: {"references": ["https://doi.org/10.1093/ve/veaa091"]}
DOI: 10.4121/21792347
title: List of Withdrawn Proposals - The European Commission's right of withdrawal of proposals

description: Aggregate list of the total OLP proposals lapsed/withdrawn by the European Commission, based on data obtained from the European Parliament’s Legislative Observatory Database. The data is restricted to OLP proposals actually withdrawn (excluding those that simply became lapsed and where the Commission did not effectively use its right of withdrawal), setting the withdrawn proposal as the unit of analysis. The withdrawn proposals are classified by type of procedure or legislative instrument and policy-issue, by the number of years passed between proposal initiation and proposal withdrawal, and by the the reaction of the co-legislators (Council and Parliament) on the withdrawal of the proposal. The generated database includes a total of 261 entries, of which 11 are dropped because they were lapsed, but not withdrawn. The final sample (n) is composed of a total of 250 withdrawn proposals between 1994 and 2020.
DOI: 10.4121/21770006
title: Mapping collaborative housing in Europe [Co-Lab Mapping] project data

description: This dataset is the result of data collection and refinement within the Co-lab mapping project. The purpose of this data collection and refinement is to provide a scientifically-validated categorisation of the different collaborative housing forms in Europe and to create the basis for comparative and quantitative studies on collaborative housing. This promotes mutual learning and communication amongst users across countries and regions. It is being made public to facilitate use by other researchers and professionals in their own work. <br> This dataset contains quantitative data on collaborative housing forms in Sweden, Denmark, United Kingdom, and The Netherlands. Quantitative raw data was collected and refined from primary sources, namely datasets provided by umbrella organisations from the different European countries involved in the project.
DOI: 10.4121/21764192
title: Paddy Rice Mapping using Deep ResU-Net CNN Segmentation

description: The main objective of this study was to develop a workflow for paddy rice field mapping using a combination of high spatial and temporal optical and radar satellite data in a deep-learning residual CNN model.
DOI: 10.4121/21127528.v1
title: Wetland Classification with Deep ResU-Net Convolutional Neural Network and Multitemporal Sentinel-1 & 2 Imagery and ALOS Elevation Data: A Case Study in Alberta Parkland & Grassland Natural Region, Canada

description: The study aimed to develop a Deep Learning (DL) model for a large-scale wetland classification in Alberta's Parkland and Grassland Natural Region (PGNR) using a fusion of multi-temporal Sentinel-2 (S2) optical and Sentinel-1 (S1) radar data and topographic data. A key objective of the study was to compare the performance of the ResNet model with two shallow learning techniques (namely Random Forest (RF) and Support Vector Machine (SVM)). A 25-band multi-seasonal (acquired over the summer/fall months of 2017 to 2020) image stack comprised of S1 (dual-polarization vertical-horizontal (VH) bands) and S2 (near-infrared (band 8) and shortwave infrared (band 11)) images and Advanced Land Observing Satellite (ALOS) derived Topographic Wetness Index as input data in the three models. Comparing the three products' accuracy metrics showed that the CNN model significantly outperformed the shallow machine learning models (SVM and RF). The best performing model was the ResU-Net model, with overall accuracy and overall kappa of 74% and 0.62, followed by SVM (69% and 0.55) and RF (0.68 and 0.54), respectively. The relative F1 scores of the mapped wetlands (marsh, open water, and swamp) using the shallow ML models showed deficiencies in their predictive capabilities. The average F1 score of the ResNet model was 0.77 compared to 0.65 (for SVM) and 0.64 (for RF). Compared to the ResNet CNN predictions, it was evident that this DL technique outperformed the shallow ML techniques evaluated in the study.
DOI: 10.6084/m9.figshare.21801088
title: Table 1.xlsx

description: Table 1 demonstrated sources, short summaries, study constructs, operational definitions, inclusion criteria, and rating codes for exclusion.
DOI: 10.6084/m9.figshare.21801088.v1
title: Table 1.xlsx

description: Table 1 demonstrated sources, short summaries, study constructs, operational definitions, inclusion criteria, and rating codes for exclusion.
DOI: 10.6084/m9.figshare.21801085
title: Table 3.xlsx

description: Table 3 raised issues related to the use of three raters' independent ratings to compute the <strong>IRR of </strong>instruments, sub-constructs, demographic variables, item screening, and item evaluation.
DOI: 10.6084/m9.figshare.21801085.v3
title: Table 3.xlsx

description: Table 3 raised issues related to the use of three raters' independent ratings to compute the <strong>IRR of </strong>instruments, sub-constructs, demographic variables, item screening, and item evaluation.
DOI: 10.6084/m9.figshare.21801082
title: Table 2.xlsx

description: Table 2 lists the instrument, subjects, instrument description, conceptual framework, scoring method, reliability, and validity.
DOI: 10.6084/m9.figshare.21801082.v4
title: Table 2.xlsx

description: Table 2 lists the instrument, subjects, instrument description, conceptual framework, scoring method, reliability, and validity.
DOI: 10.34740/kaggle/dsv/4793815
title: Egypt Gold Prices | Daily Updated
DOI: 10.34740/kaggle/dsv/4796599
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.7497935
title: load deflection data of beams

description: load deflection data of corroded beams that strengthened with various method by using GFRP bars
DOI: 10.5281/zenodo.7497934
title: load deflection data of beams

description: load deflection data of corroded beams that strengthened with various method by using GFRP bars
DOI: 10.5281/zenodo.7497947
title: Gene datasets

description: Gene datasets associated with let-7g-5p
DOI: 10.5281/zenodo.7497946
title: Gene datasets

description: Gene datasets associated with let-7g-5p
DOI: 10.25919/d43x-rx64
title: Parkes observations for project P1166 semester 2022OCTS_03

description: Observationally, there are two basic types of Fast Radio Bursts (FRBs): repeating and non-repeating ones. In the southern sky, there are very limited number of repeaters we can monitor unless more are confirmed to repeat. Large sample of FRBs released by the CHIME telescope seems to tell us the morphology difference between repeater and non-repeaters, that is, repeating FRBs tend to exhibit more complex pulse profile but more narrowband radio emission. Using this dichotomy, we may be able to find more repeaters from the known sample. In this project, we select FRB 20180923B, which has not been followed up to date, as the target of this proposed observation. The source has a quite broad pulse width of 20 ms and its brightness is close with most repeaters of with similar dispersion. We request 16-hour observing with the Parkes ultra-wide-bandwidth receiver (UWL) to search for possible repeating events. Even non-detection can still constrain that most of FRBs are not active repeaters.
DOI: 10.25919/ejva-pq37
title: Parkes observations for project P1021 semester 2022OCTS_03

description: We propose to observe PSR J1812-15 and PSR J1831-04, a pair of long spin-period binary pulsars which both show degrees of orbitally-dependent variability. Binary pulsars are valuable objects of scientific study, allowing for multiple applications including tests of gravity, probes of the neutron star equation of state, and fossil records of stellar evolution. Long spin-period pulsars in binary systems are generally much rarer than faster-spinning `recycled’ pulsars, and represent an underexplored region of pulsar binary evolution. This is particularly true of PSR J1812-15, for which only one other pulsar (B1718-19) seems remotely comparable, while PSR J1831-04 may yet turn out to be a third member of this class Our objectives differ for each pulsar. For PSR J1812-15, a minimal low-cadence timing campaign is still required to address ongoing problems with phase connection, which may be caused by an undiagnosed glitch or other un-modelled timing effect. Beyond this, the utter uniqueness of the source warrants further monitoring in the event it displays further undocumented behaviour. For PSR J1831-04 (to date detected only once), our campaign is designed to provide the optimal chance of redetecting the pulsar through a randomised observing schedule, thereby characterising the pulsar and its binary system. If confirmed as similar to PSRs J1812 and B1718, it would contribute significantly to our understanding of this rare class of binary pulsar.
DOI: 10.6084/m9.figshare.21106453
title: Example Microscopy Images

description: Images for TDA-Microscopy pipeline example.
DOI: 10.6084/m9.figshare.21106453.v1
title: Example Microscopy Images

description: Images for TDA-Microscopy pipeline example.
DOI: 10.6084/m9.figshare.21106453.v2
title: Example Microscopy Images

description: Images for TDA-Microscopy pipeline example.
DOI: 10.6084/m9.figshare.21106567
title: Full Microscopy Image Set

description: All images used for TDA-Microscopy pipeline.
DOI: 10.6084/m9.figshare.21106567.v1
title: Full Microscopy Image Set

description: All images used in pipeline analysis.
DOI: 10.6084/m9.figshare.21106567.v2
title: Full Microscopy Image Set

description: All images used for TDA-Microscopy pipeline.
DOI: 10.25919/kpra-yp38
title: Parkes observations for project P595 semester 2022OCTS_02

description: We propose to continue the PULSE@Parkes project in which high school students from Australia and around the World use the Parkes radio telescope in a remote observing model to observe and analyse pulsar data. The data from some PULSE@Parkes observations are used to support the space missions, other observations supplement the P456 Pulsar Timing Array project and the remainder were chosen in order to make a detailed analysis of pulsar timing irregularities and intermittency.
DOI: 10.22008/fk2/e0ipc9
title: Supplementary files for: "Delivering seabed geodiversity information through multidisciplinary mapping initiatives: experiences from Norway"

description: Geology is a core component of two major multidisciplinary seabed-mapping initiatives in Norway (MAREANO, Marine Base Maps for the Coastal Zone). Helped by Norway’s Nature Diversity Act, which acknowledges geological and landscape diversity alongside biodiversity, geological information has gained recognition nationally as part of an essential foundation for knowledge-based management, both in the coastal zone and offshore. Recently, international focus on the United Nations Sustainable Development Goals has led to the proposal of Essential Geodiversity Variables, a framework for geological (geodiversity) information, intended to stand alongside Essential Variables already defined for climate, biodiversity and oceans (limited to ocean physics, biochemistry, biology, and ecosystems). Here we examine to what extent map products from the Geological Survey of Norway generated under these multidisciplinary mapping initiatives fit within this framework of Essential Geodiversity Variables and how well it is suited to information on marine geodiversity. Although we conclude that the framework is generally a good fit for the marine-relevant Essential Geodiversity Variable classes (geology and geomorphology), we examine opportunities for further highlighting quantitative geodiversity information. We present preliminary examples of substrate diversity and morphological diversity and discuss our experience of geological mapping as part of multidisciplinary initiatives. We highlight many benefits, which far outweigh any perceived or real compromises of this approach in monetary, practical and scientific terms.
DOI: 10.22008/fk2/e0ipc9/d83bz7
title: Supplementary File S1.docx

description: Lookup table for sediment grain size classes – Supplementary File S1.
DOI: 10.5519/qd.7w4cymmk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.6802221
title: Supplementary_files_CS

description: Supplementary files for the manuscript "Contrast Subgraphs Allow Comparing Homogeneous and Heterogeneous Networks Derived from Omics Data"
DOI: 10.5281/zenodo.7323560
title: Supplementary_files_CS

description: Supplementary files for the manuscript "Contrast Subgraphs Allow Comparing Homogeneous and Heterogeneous Networks Derived from Omics Data"
DOI: 10.5281/zenodo.7323764
title: Supplementary_files_CS

description: Supplementary files for the manuscript "Contrast Subgraphs Allow Comparing Homogeneous and Heterogeneous Networks Derived from Omics Data"
DOI: 10.5281/zenodo.7334174
title: Supplementary_files_CS

description: Supplementary files for the manuscript "Contrast Subgraphs Allow Comparing Homogeneous and Heterogeneous Networks Derived from Omics Data"
DOI: 10.5281/zenodo.6802220
title: Supplementary_files_CS

description: Supplementary files for the manuscript "Contrast Subgraphs Allow Comparing Homogeneous and Heterogeneous Networks Derived from Omics Data"