cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19820344.v2
title: Dataset with a paper published in Nature Geoscience, titled “Global mapping reveals increase in lacustrine algal blooms over the past decade" https://www.nature.com/articles/s41561-021-00887-x

description: This dataset provides maximum bloom extent (MBE, in km2) and median bloom occurrence (BO, in %) for 21,878 freshwater lakes worldwide in the entire period (1980s-2010s) and three sub-periods (1980–1990s, 2000s, and 2010s), which was generated using Landsat satellite observation between 1982 to 2019. <br> If you have any questions, feel free to contact: houxj_92@163.com
DOI: 10.5281/zenodo.6571777
title: Scoping survey on the state of play of Open Science at SEA-EU universities

description: Survey data that sought to collect information about the state of play on Open Research Data Management practices amongst the SEA-EU Alliance.
DOI: 10.5281/zenodo.6571776
title: Scoping survey on the state of play of Open Science at SEA-EU universities

description: Survey data that sought to collect information about the state of play on Open Research Data Management practices amongst the SEA-EU Alliance.
DOI: 10.21227/6th2-zc61
title: Programming Know-What and Know-How Knowledge Fusion, Semantic Enrichment and Coherent Application

description: "128_dim_word_vector" is the word vector that is used in 2.2.1.  "86 keywords"  is used to extract directive sentences in section 3.1.1. "API-Task KG/ source-of-data" is the data used to construct the API-Task knowledge graph,  and "API-Task KG/KG" is the fusion KG data. ”Experiment RQ_1 and RQ_2" is the experiment data. "Empirical_study" contains the Stack Overflow questions that are used in the empirical study.
DOI: 10.21227/jx6f-nt43
title: Image retrieval

description: The picture shows the operation result of image security retrieval.  The experiment was validated on five common data sets.
DOI: 10.6084/m9.figshare.9637709
title: Bayesian modelling of nonlinear Poisson regression with artificial neural networks

description: Modelling and prediction of count and rate responses have substantial usage in many fields, including health, finance, social, etc. Conventionally, linear Poisson regression models have been widely used to model these responses. However, the linearity assumption of the systematic component of linear Poisson regression models restricts their capability of handling complex data patterns. In this regard, it is important to develop nonlinear Poisson regression models to capture the inherent variability within the count data. In this study, we introduce a probabilistically driven nonlinear Poisson regression model with Bayesian artificial neural networks (ANN) to model count and rate data. This new nonlinear Poisson regression model developed with Bayesian ANN provides higher prediction accuracies over traditional Poisson or negative binomial regression models as revealed in our simulation and real data studies.
DOI: 10.15468/3n8g9t
title: MH_ANTWERPEN - Western marsh harriers (Circus aeruginosus, Accipitridae) breeding near Antwerp (Belgium) [subsampled representation]

description: This animal tracking dataset is derived from Spanoghe et al. (2022, https://doi.org/10.5281/zenodo.6568082) a deposit of Movebank study 938783961. Data have been standardized to Darwin Core using the movepub R package and are downsampled to the first GPS position per hour. The original dataset description follows. <em>MH_ANTWERPEN - Western marsh harriers (Circus aeruginosus, Accipitridae) breeding near Antwerp (Belgium)</em> is a bird tracking dataset published by the Research Institute for Nature and Forest (INBO). It contains animal tracking data collected by the LifeWatch GPS tracking network for large birds (http://lifewatch.be/en/gps-tracking-network-large-birds) for the project/study <strong>MH_ANTWERPEN</strong>, using trackers developed by the University of Amsterdam Bird Tracking System (UvA-BiTS, http://www.uva-bits.nl). The study has been operational since 2018. In total 4 individuals of Western marsh harriers (<em>Circus aeruginosus</em>) have been tagged in their breeding area near the city of Antwerp (Belgium), mainly to study their habitat use and migration behaviour. Data are periodically uploaded from the UvA-BiTS database to Movebank and from there archived on Zenodo (see https://github.com/inbo/bird-tracking). See Milotic et al. (2020, https://doi.org/10.3897/zookeys.947.52570) for a more detailed description of this dataset. This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch.
DOI: 10.48370/ofd/uzhhvl
title: Sarcoscypha coccinea (Jacq.) Sacc., 113

description: Fungarium Macromycetes
DOI: 10.5517/ccdc.csd.cc267f30
title: CCDC 2032921: Experimental Crystal Structure Determination

description: Related Article: Zhen-Zhu Zhao, Xuan Zhao, Ying-Ying Si, Zhen-Zhen Wang, Yan-Jun Sun, He-Ping Chen, Wei-Sheng Feng, Ji-Kai Liu|2022|Phytochemistry|200|113227|doi:10.1016/j.phytochem.2022.113227
DOI: 10.5517/ccdc.csd.cc267f41
title: CCDC 2032922: Experimental Crystal Structure Determination

description: Related Article: Zhen-Zhu Zhao, Xuan Zhao, Ying-Ying Si, Zhen-Zhen Wang, Yan-Jun Sun, He-Ping Chen, Wei-Sheng Feng, Ji-Kai Liu|2022|Phytochemistry|200|113227|doi:10.1016/j.phytochem.2022.113227
DOI: 10.5517/ccdc.csd.cc28ffpv
title: CCDC 2098287: Experimental Crystal Structure Determination

description: Related Article: Jelte S. Steen, Jules L. Nuismer, Vytautas Eiva, Albert E. T. Wiglema, Nicolas Daub, Johan Hjelm, Edwin Otten|2022|J.Am.Chem.Soc.|144|5051|doi:10.1021/jacs.1c13543
DOI: 10.5517/ccdc.csd.cc28ffqw
title: CCDC 2098288: Experimental Crystal Structure Determination

description: Related Article: Jelte S. Steen, Jules L. Nuismer, Vytautas Eiva, Albert E. T. Wiglema, Nicolas Daub, Johan Hjelm, Edwin Otten|2022|J.Am.Chem.Soc.|144|5051|doi:10.1021/jacs.1c13543
DOI: 10.5517/ccdc.csd.cc28ffrx
title: CCDC 2098289: Experimental Crystal Structure Determination

description: Related Article: Jelte S. Steen, Jules L. Nuismer, Vytautas Eiva, Albert E. T. Wiglema, Nicolas Daub, Johan Hjelm, Edwin Otten|2022|J.Am.Chem.Soc.|144|5051|doi:10.1021/jacs.1c13543
DOI: 10.5517/ccdc.csd.cc28xwkn
title: CCDC 2113132: Experimental Crystal Structure Determination

description: Related Article: Ratchanaporn Chokchaisiri, Teerawut Thothaisong, Warangkana Chunglok, Wanatsanan Chulrik, Bunlawee Yotnoi, Suwadee Chokchaisiri, Lucksagoon Ganranoo, Sarot Cheenpracha, Chutamas Thepmalee, Apichart Suksamrarn|2022|Phytochemistry|200|113225|doi:10.1016/j.phytochem.2022.113225
DOI: 10.5517/ccdc.csd.cc28xwlp
title: CCDC 2113133: Experimental Crystal Structure Determination

description: Related Article: Ratchanaporn Chokchaisiri, Teerawut Thothaisong, Warangkana Chunglok, Wanatsanan Chulrik, Bunlawee Yotnoi, Suwadee Chokchaisiri, Lucksagoon Ganranoo, Sarot Cheenpracha, Chutamas Thepmalee, Apichart Suksamrarn|2022|Phytochemistry|200|113225|doi:10.1016/j.phytochem.2022.113225
DOI: 10.5517/ccdc.csd.cc2bnfct
title: CCDC 2164586: Experimental Crystal Structure Determination

description: Related Article: Lu Zhang, Xing Liu, Jian Zhou, Chun-Mei Huang, Congrui Ouyang|2022|Dyes Pigm.|203|110384|doi:10.1016/j.dyepig.2022.110384
DOI: 10.5517/ccdc.csd.cc2bnfdv
title: CCDC 2164587: Experimental Crystal Structure Determination

description: Related Article: Lu Zhang, Xing Liu, Jian Zhou, Chun-Mei Huang, Congrui Ouyang|2022|Dyes Pigm.|203|110384|doi:10.1016/j.dyepig.2022.110384
DOI: 10.5517/ccdc.csd.cc2bnffw
title: CCDC 2164588: Experimental Crystal Structure Determination

description: Related Article: Lu Zhang, Xing Liu, Jian Zhou, Chun-Mei Huang, Congrui Ouyang|2022|Dyes Pigm.|203|110384|doi:10.1016/j.dyepig.2022.110384
DOI: 10.5281/zenodo.6572013
title: Pycirk exiobase data

description: A version of EXIOBASE multi-regional SUTs V3.3 for 2011 and that has been: Expanded in labels for all categories (including synonyms, country regions and names in the multiindexes to facilitate slicing). Expanded by including characterization tables (originally developed under DESIRE FP7) The datasets are pickled and are meant to be used with pycirk a modelling software to simulate EEIO structural change due to technological and policy interventions. https://cmlplatform.github.io/pycirk/
DOI: 10.48370/ofd/rcdt2y
title: Schizopora radula (Persoon) Hellenberg, 4654

description: Fungarium Macromycetes
DOI: 10.5281/zenodo.6572178
title: Multi-dimensional hydrodynamic simulations of stellar objects

description: Supplementary material for the ArbeitsgruppenInspirationsMesse event
DOI: 10.5281/zenodo.6572179
title: SocialDisNER corpus: gold standard annotations for detection of disease mentions in Spanish tweets

description: Gold Standard annotations for <strong>SocialDisNER </strong>(SMM4H 2022 – Task 10) shared task. <strong>Introduction:</strong><br> The <strong>SocialDisNER corpus</strong> of the SMM4H 2022 – Task 10 task will focus on the recognition of disease mentions in tweets written in Spanish after selecting primarily<strong><em> first-hand experience of diseases</em></strong> and other health-relevant content (from patient associations, professional healthcare institutions, and through followers of patient association accounts of a <em>diversity of pathologies</em> including rare diseases, mental health, cancer, etc..). The corpus was manually annotated by medical experts following the SMM4H-SocialDisNER guidelines. These guidelines were adapted from previous efforts used to annotate patient clinical records and medical literature. It covers rules for annotating <strong>mentions of diseases</strong> in health-related tweets in Spanish, The training set consists of 5000 tweets written in Spanish, the annotated validation set and the unannotated test set will be published shortly. The structure of the dataset is: socialdisner.zip: <strong><em>train-valid-txt-files</em></strong>: folder with training and validation text files. One text file per tweet, he file name corresponds to the tweet id.. One sub-directory per corpus split (train and valid). Validation tweets have not yet been included. <strong><em>mentions.tsv</em></strong>: This file contains the manually annotated disease mentions. The file has the following fields: <em>tweets_id</em>: This is the id of the tweet, using Twitter API you can query the content of the tweet. <em>Begin</em>: This is the position in the tweet where the annotation was found. <em>End</em>: This is the position of the last character of the annotation in the tweet. <em>Type: </em>This is the type of entity found, in our case "ENFERMEDAD". <em>Extraction</em>: This is the literal extraction, in other words, the fragment of text which refers to the annotation. For further information, please visit https://temu.bsc.es/socialdisner/ Do not share the data with other individuals/teams without permission from the task organizer. Tweets IDs are the primary source of information. Tweet texts are provided as support material. By downloading this resource, you agree to the Twitter Terms of Service, Privacy Policy, Developer Agreement, and Developer Policy.
DOI: 10.48370/ofd/dqn44v
title: Scleroderma areolatum Ehrenb., 1830

description: Fungarium Macromycetes
DOI: 10.6084/m9.figshare.19786959
title: R code for statistical analysis from Personality, sperm traits and a test for their combined dependence on male condition in guppies

description: There is evidence that animal personality can affect sexual selection, with studies reporting that male behavioural types are associated with success during pre- and post-copulatory sexual selection. Given these links between personality and sexual traits, and the accumulating evidence that their expression can depend on an individual's dietary status (i.e. condition), a novel prediction is that changes in a male's diet should alter both the average expression of personality and sexual traits, and their covariance. We tested these predictions using the guppy <i>Poecilia reticulata</i>, a species previously shown to exhibit strong condition dependence in ejaculate traits and a positive correlation between sperm production and individual variation in boldness. Contrary to expectation, we found that dietary restriction—when administered in mature adult males—did not affect the expression of either behavioural (boldness and activity) or ejaculate traits, although we did find that males subjected to dietary stress exhibited a positive association between sperm velocity and boldness that was not apparent in the unrestricted diet group. This latter finding points to possible context-dependent patterns of covariance between sexually selected traits and personalities, which may have implications for patterns of selection and evolutionary processes under fluctuating environmental conditions.
DOI: 10.48370/ofd/8tgeps
title: Scleroderma citrinum Pers., 27

description: Fungarium Macromycetes
DOI: 10.5281/zenodo.6255933
title: Datasets for publication titled "Chiral control of spin-crossover dynamics in Fe(II) complexes"

description: Transient absorption (TA), transient absorption anisotropy (TAA), and time-resolved circular dichroism (TRCD) datasets analyzed and interpreted in the publication titled "Chiral control of spin-crossover dynamics in Fe(II) complexes" published in Nature Chemistry under the DOI 10.1038/s41557-022-00933-0.
DOI: 10.5281/zenodo.6255932
title: Datasets for publication titled "Chiral control of spin-crossover dynamics in Fe(II) complexes"

description: Transient absorption (TA), transient absorption anisotropy (TAA), and time-resolved circular dichroism (TRCD) datasets analyzed and interpreted in the publication titled "Chiral control of spin-crossover dynamics in Fe(II) complexes" published in Nature Chemistry under the DOI 10.1038/s41557-022-00933-0.
DOI: 10.5281/zenodo.6572208
title: Climate Response to ~23% Albedo Reduction in IPSL-CM5A2-LR

description: The dataset consists of IPSL-CM5A2-LR outputs from a present-day control (pdControl, Con) and 23% Arctic sea ice albedo reduction experiment (Alb). Both sets of experiments are annual means for 200 years of simulation. The Con has 12 members from two restarts (7 and 5) and the Alb experiment has 14 members from the same restarts (9 and 5). Annual datasets include: Winter (JFM) and summer (JAS) sea ice area fraction (SIA), Atlantic overturning streamfunction (zomsfatl,msftrho), sea level pressure (SLP), sea surface temperature (TOS), sea surface salinity (SOS), barotropic streamfunction (BSF), zonal windstress (TAUX), and meridional windstress (TAUY). Since there are two restarts from different model years, the time axis has been changed to count years of the experiment (i.e. 1,2,3,...200). The anomalies of the Alb experiment are also provided taking into account the respective control. The missing data is recorded as nan. The datasets are created from the IPSL-CM5A-LR output files, using CDO and Python3 commands to combine and create annual averages.
DOI: 10.5281/zenodo.6036926
title: Climate Response to ~23% Albedo Reduction in IPSL-CM5A2-LR

description: The dataset consists of IPSL-CM5A2-LR outputs from a present-day control (pdControl, Con) and 23% Arctic sea ice albedo reduction experiment (Alb). Both sets of experiments are annual means for 200 years of simulation. The Con has 12 members from two restarts (7 and 5) and the Alb experiment has 14 members from the same restarts (9 and 5). Annual datasets include: Winter (JFM) and summer (JAS) sea ice area fraction (SIA), Atlantic overturning streamfunction (zomsfatl,msftrho), sea level pressure (SLP), sea surface temperature (TOS), sea surface salinity (SOS), barotropic streamfunction (BSF), zonal windstress (TAUX), and meridional windstress (TAUY). Since there are two restarts from different model years, the time axis has been changed to count years of the experiment (i.e. 1,2,3,...200). The anomalies of the Alb experiment are also provided taking into account the respective control. The missing data is recorded as nan. The datasets are created from the IPSL-CM5A-LR output files, using CDO and Python3 commands to combine and create annual averages.
DOI: 10.5281/zenodo.6572350
title: 68c32f9c-bdaa-420c-879c-90b40d8bc4d5

description: These data sets are one of the workflows of ddbj/workflow-registry.
DOI: 10.5281/zenodo.6572349
title: 68c32f9c-bdaa-420c-879c-90b40d8bc4d5

description: These data sets are one of the workflows of ddbj/workflow-registry.
DOI: 10.5519/qd.csznjj3j
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (887740 records)
DOI: 10.48370/ofd/aayxam
title: Scleroderma verrucosum (Bull.): Pers., 1831

description: Fungarium Macromycetes
DOI: 10.5281/zenodo.6572286
title: VolveSynthetic

description: VolveSynthetic -------------- This folder contains the dataset associated to the following [repository](https://github.com/DIG-Kaust/VolveSynthetic). It is organized as follows: * **Original**: directory where to place original field dataset from the Volve village - commands to download the dataset are provided in the following [notebook](https://github.com/DIG-Kaust/VolveSynthetic/blob/main/Inversion/MainInversion.ipynb). * **Velocity**: directory containing the velocity models and acquisition geometry extracted from the field data. * **Modelling**: directory containing modelled synthetic datasets. * **Processing**: directory containing processed synthetic datasets. * **Imaging**: directory containing seismic images created by performing RTM on the modeled and processed data. For more details on how these files have been generated and how to use them, please refer to the README file in the repository.
DOI: 10.5281/zenodo.6572285
title: VolveSynthetic

description: VolveSynthetic -------------- This folder contains the dataset associated to the following [repository](https://github.com/DIG-Kaust/VolveSynthetic). It is organized as follows: * **Original**: directory where to place original field dataset from the Volve village - commands to download the dataset are provided in the following [notebook](https://github.com/DIG-Kaust/VolveSynthetic/blob/main/Inversion/MainInversion.ipynb). * **Velocity**: directory containing the velocity models and acquisition geometry extracted from the field data. * **Modelling**: directory containing modelled synthetic datasets. * **Processing**: directory containing processed synthetic datasets. * **Imaging**: directory containing seismic images created by performing RTM on the modeled and processed data. For more details on how these files have been generated and how to use them, please refer to the README file in the repository.
DOI: 10.6084/m9.figshare.19787428
title: ESM Raw data from Skeletal muscle function underpins muscle spindle abundance

description: Muscle spindle abundance is highly variable within and across species, but we currently lack any clear picture of the mechanistic causes or consequences of this variation. Previous use of spindle abundance as a correlate for muscle function implies a mechanical underpinning to this variation, but these ideas have not been tested. Herein, we use integrated medical imaging and subject-specific musculoskeletal models to investigate the relationship between spindle abundance, muscle architecture and <i>in vivo</i> muscle behaviour in the human locomotor system. These analyses indicate that muscle spindle number is tightly correlated with muscle fascicle length, absolute fascicle length change, velocity of fibre lengthening and active muscle forces during walking. Novel correlations between functional indices and spindle abundance are also recovered, where muscles with a high abundance predominantly function as springs, compared to those with a lower abundance mostly functioning as brakes during walking. These data demonstrate that muscle fibre length, lengthening velocity and fibre force are key physiological signals to the central nervous system and its modulation of locomotion, and that muscle spindle abundance may be tightly correlated to how a muscle generates work. These insights may be combined with neuromechanics and robotic studies of motor control to help further tease apart the functional drivers of muscle spindle composition.
DOI: 10.6084/m9.figshare.19787428.v1
title: ESM Raw data from Skeletal muscle function underpins muscle spindle abundance

description: Muscle spindle abundance is highly variable within and across species, but we currently lack any clear picture of the mechanistic causes or consequences of this variation. Previous use of spindle abundance as a correlate for muscle function implies a mechanical underpinning to this variation, but these ideas have not been tested. Herein, we use integrated medical imaging and subject-specific musculoskeletal models to investigate the relationship between spindle abundance, muscle architecture and <i>in vivo</i> muscle behaviour in the human locomotor system. These analyses indicate that muscle spindle number is tightly correlated with muscle fascicle length, absolute fascicle length change, velocity of fibre lengthening and active muscle forces during walking. Novel correlations between functional indices and spindle abundance are also recovered, where muscles with a high abundance predominantly function as springs, compared to those with a lower abundance mostly functioning as brakes during walking. These data demonstrate that muscle fibre length, lengthening velocity and fibre force are key physiological signals to the central nervous system and its modulation of locomotion, and that muscle spindle abundance may be tightly correlated to how a muscle generates work. These insights may be combined with neuromechanics and robotic studies of motor control to help further tease apart the functional drivers of muscle spindle composition.
DOI: 10.6084/m9.figshare.19822885.v1
title: Raw data of Zhao et al., 2022, Geoderma

description: Raw data associated with Zhao et al., 2022, Geoderma. Any use of the data set should be approved by the corresponding author Kai Yue at "kyleyuechina@163.com".
DOI: 10.6084/m9.figshare.19822885
title: Raw data of Zhao et al., 2022, Geoderma

description: Raw data associated with Zhao et al., 2022, Geoderma. Any use of the data set should be approved by the corresponding author Kai Yue at "kyleyuechina@163.com".
DOI: 10.6084/m9.figshare.19822039.v1
title: GradR-CIFAR10-Model

description: Pretrained SNN models using GradR on CIFAR-10 dataset.
DOI: 10.6084/m9.figshare.19822039
title: GradR-CIFAR10-Model

description: Pretrained SNN models using GradR on CIFAR-10 dataset.
DOI: 10.5281/zenodo.6572527
title: Supporting information for "Diverse P-T-t paths reveal high-grade metamorphosed forearc complexes in NW China"

description: The supporting information includes raw chemical compositions of minerals, bulk-rock major and trace elements of rocks, and SIMS U-Pb isotopic analysis data of metamorphic zircons for "Diverse P-T-t paths reveal high-grade metamorphosed forearc complexes in NW China" by Wang et al.
DOI: 10.5281/zenodo.5568640
title: Supporting information for "Diverse P-T-t paths reveal high-grade metamorphosed forearc complexes in NW China"

description: The supporting information includes raw chemical compositions of minerals, bulk-rock major and trace elements of rocks, and SIMS U-Pb isotopic analysis data of metamorphic zircons for "Diverse P-T-t paths reveal high-grade metamorphosed forearc complexes in NW China" by Wang et al.
DOI: 10.6084/m9.figshare.19822441
title: MS36R1_SEC2B_demo.rar

description: Demo image data for SATINN, a workflow designed to automate analysis of histological images of mouse seminiferous tubules. This is a subset of one of the full sections used in the manuscript Yang et al., 2022, and intended for use in testing and improving the standalone app that is currently in development. Additional information can be found at http://github.com/conradlab/SATINN.