cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7940710
title: Hourly values of an advanced human-biometeorological index for diverse populations from 1991 to 2020

description: The presented human thermal bioclimate dataset was created in the frame of the HEAT-ALARM ("Development of a heat-health warning system in Greece") research project.
It consists of hourly values of population-weighted mPET (modified physiologically equivalent temperature), simulated by the RayMan Pro model for the period 1991-2020 and for six population subsets in 72 regional units and combinations thereof, which are based on the NUTS-3 (Nomenclature of Territorial Units for Statistics-3) classification in Greece, using the Copernicus European Regional Reanalysis (CERRA) at 5.5 km spatial resolution. 
The code used to produce the presented data is available at: https://doi.org/10.5281/zenodo.8009730. It can be used to replicate the dataset not only directly in Greece, but also in any other country included in the CERRA domain after appropriate adjustments.
DOI: 10.15468/dl.2s392k
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Melodinus philippinensis A.DC."
 ]
}

 The dataset includes 10 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054661-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tm3p2s
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Margaritaria luzoniensis (Merr.) Airy Shaw"
 ]
}

 The dataset includes 12 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054662-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mfuvkc
title: Occurrence Download

description: A dataset containing 333 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Moraea lugubris (Salisb.) Goldblatt"
 ]
}

 The dataset includes 333 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054664-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pf9dyx
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Medinilla coursiana H.Perrier"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054663-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tn9mjb
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Millettia ahernii Merr. & Rolfe"
 ]
}

 The dataset includes 45 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054665-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.12763/clwl3a/kowj2j
title: deg_40_09_25-1.txt

description: :unav
DOI: 10.12763/clwl3a/25gtw7
title: deg_40_07_15-1.txt

description: :unav
DOI: 10.12763/clwl3a/8shzff
title: deg_20_06_20-1.txt

description: :unav
DOI: 10.12763/clwl3a/fkehqk
title: winstance_20_05_25-1.txt

description: :unav
DOI: 10.12763/clwl3a/ylg06y
title: deg_50_05_15-1.txt

description: :unav
DOI: 10.12763/clwl3a/wwedga
title: deg_40_05_10-1.txt

description: :unav
DOI: 10.12763/clwl3a/hcegfm
title: winstance_30_09_15-1.txt

description: :unav
DOI: 10.12763/clwl3a/nekrnx
title: deg_20_08_10-1.txt

description: :unav
DOI: 10.12763/clwl3a/8gtntv
title: winstance_50_03_05-1.txt

description: :unav
DOI: 10.12763/clwl3a/aifash
title: winstance_20_06_10-1.txt

description: :unav
DOI: 10.12763/clwl3a/gnbvsr
title: deg_50_08_20-1.txt

description: :unav
DOI: 10.12763/clwl3a/uitw2k
title: deg_40_08_25-1.txt

description: :unav
DOI: 10.12763/clwl3a/4mbvte
title: deg_50_06_20-1.txt

description: :unav
DOI: 10.12763/clwl3a/6j3e1f
title: deg_40_08_20-1.txt

description: :unav
DOI: 10.12763/clwl3a/ohukwh
title: deg_50_08_25-1.txt

description: :unav
DOI: 10.12763/clwl3a/flrd62
title: deg_50_02_20-1.txt

description: :unav
DOI: 10.5281/zenodo.6579817
title: Archive for regression and estimation of the total freeboard of the Arctic using AMSR2 data v2.0

description: This fileset contains data used for generating Tables and Figures in Kim et al. (2022). All file has csv format separated by a comma. In the first line of the individual file, we provide the variable name and unit of each column. The fileset has 6 sub-directories. The name of each directory indicates the figures corresponding to its contents. • Figure 2,7 • Figure 4 (and Table 1-3) • Figure 5 • Figure 6,8 • Figure 6_ICESat2 • Figure A1
DOI: 10.5281/zenodo.6237171
title: Archive for regression and estimation of the total freeboard of the Arctic using AMSR2 data v2.0

description: This fileset contains data used for generating Tables and Figures in Kim et al. (2022). All file has csv format separated by a comma. In the first line of the individual file, we provide the variable name and unit of each column. The fileset has 6 sub-directories. The name of each directory indicates the figures corresponding to its contents. • Figure 2,7 • Figure 4 (and Table 1-3) • Figure 5 • Figure 6,8 • Figure 6_ICESat2 • Figure A1
DOI: 10.5281/zenodo.6573900
title: Lagrangian overturning in the eastern subpolar North Atlantic Ocean - ORCA025-GJM189 Particle Trajectory Dataset

description: This dataset contains the output of Lagrangian particle tracking experiments using 5-day mean velocity and hydrographic fields from the ORCA025-GJM189 ocean sea-ice model hindcast configured during the Drakkar project in which numerical particles are initialised along the northward inflows across the Overturning in the Subpolar North Atlantic Program (OSNAP) East section. Particles are advected using a bespoke version of TRACMASS v7.1 Lagrangian particle tracking tool using the regular step-wise stationary advection scheme and an adapted implementation of the vertical turbulent mixing parameterisation created by Paris et al. (2013) for the Connectivity Modelling System Lagrangian particle tracking tool. This vertical turbulent mixing scheme only acts on particles found within the surface mixed layer (as evaluated along particle trajectories) and randomly reshuffles them according to a maximum vertical velocity of 10 cm/s - characteristic of vertical convective plumes. Note, particles cannot be artificially subducted across the base of the mixed layer into the ocean interior using this scheme. Particles are initialised on the first-available day of each month (based on the centre of the model fields 5-day mean windows) between 1976 and 2008 (inclusive) before being advected within the Iceland and Irminger Basins until any one of three termination conditions are met: 1) particles return southward across OSNAP East, 2) particles flow northward across the Greenland-Scotland Ridge, or 3) particles reach the maximum advection time of 7-years. The 7-year maximum advection time ensures &gt;99.1% of all initialised particles meet one of conditions 1) or 2), hence only 0.9% of all particles are terminated between OSNAP East and the Greenland-Scotland Ridge. The number of particles initialised in each model-grid cell scales with the total northward transport through that cell, such that the maximum possible transport conveyed by any single particle is 2.5 mSv (mSv == 1E-3 Sv), enabling the calculation of robust Lagrangian statistics. Particle locations (referenced to the original ORCA025 model grid) and properties (potential temperature, salinity, potential density and local mixed layer depth) are stored in the output files on every model-grid cell crossing. TRACMASS determines particle properties on grid-cell crossings by taking the average of the properties stored at the nearest two T-grid points. In total, four Lagrangian experiments were conducted at the Department of Earth Sciences, University of Oxford. Please see README.md for a full description of all Lagrangian experiments and the accompanying output files. <strong>For a complete description of the ORCA025-GJM189 hindcast configuration see:</strong> https://github.com/meom-configurations/ORCA025.L75-GJM189. <strong>For a complete description of TRACMASS v7.1 see</strong>: https://github.com/TRACMASS/tracmass
DOI: 10.5281/zenodo.6573899
title: Lagrangian overturning in the eastern subpolar North Atlantic Ocean - ORCA025-GJM189 Particle Trajectory Dataset

description: This dataset contains the output of Lagrangian particle tracking experiments using 5-day mean velocity and hydrographic fields from the ORCA025-GJM189 ocean sea-ice model hindcast configured during the Drakkar project in which numerical particles are initialised along the northward inflows across the Overturning in the Subpolar North Atlantic Program (OSNAP) East section. Particles are advected using a bespoke version of TRACMASS v7.1 Lagrangian particle tracking tool using the regular step-wise stationary advection scheme and an adapted implementation of the vertical turbulent mixing parameterisation created by Paris et al. (2013) for the Connectivity Modelling System Lagrangian particle tracking tool. This vertical turbulent mixing scheme only acts on particles found within the surface mixed layer (as evaluated along particle trajectories) and randomly reshuffles them according to a maximum vertical velocity of 10 cm/s - characteristic of vertical convective plumes. Note, particles cannot be artificially subducted across the base of the mixed layer into the ocean interior using this scheme. Particles are initialised on the first-available day of each month (based on the centre of the model fields 5-day mean windows) between 1976 and 2008 (inclusive) before being advected within the Iceland and Irminger Basins until any one of three termination conditions are met: 1) particles return southward across OSNAP East, 2) particles flow northward across the Greenland-Scotland Ridge, or 3) particles reach the maximum advection time of 7-years. The 7-year maximum advection time ensures &gt;99.1% of all initialised particles meet one of conditions 1) or 2), hence only 0.9% of all particles are terminated between OSNAP East and the Greenland-Scotland Ridge. The number of particles initialised in each model-grid cell scales with the total northward transport through that cell, such that the maximum possible transport conveyed by any single particle is 2.5 mSv (mSv == 1E-3 Sv), enabling the calculation of robust Lagrangian statistics. Particle locations (referenced to the original ORCA025 model grid) and properties (potential temperature, salinity, potential density and local mixed layer depth) are stored in the output files on every model-grid cell crossing. TRACMASS determines particle properties on grid-cell crossings by taking the average of the properties stored at the nearest two T-grid points. In total, four Lagrangian experiments were conducted at the Department of Earth Sciences, University of Oxford. Please see README.md for a full description of all Lagrangian experiments and the accompanying output files. <strong>For a complete description of the ORCA025-GJM189 hindcast configuration see:</strong> https://github.com/meom-configurations/ORCA025.L75-GJM189. <strong>For a complete description of TRACMASS v7.1 see</strong>: https://github.com/TRACMASS/tracmass
DOI: 10.5281/zenodo.6397722
title: Data from: Olfactory modulation of barrel cortex activity during active whisking and passive whisker stimulation

description: Rodents depend on olfaction and touch to meet many of their fundamental needs. The joint significance of these sensory systems is underscored by an intricate coupling between sniffing and whisking. However, the impact of simultaneous olfactory and tactile inputs on sensory representations in the cortex remains elusive. To study these interactions, we recorded large populations of barrel cortex neurons using 2-photon calcium imaging in head-fixed mice during olfactory and tactile stimulation. We find that odors alter barrel cortex activity in at least two ways, first by enhancing whisking, and second by central cross-talk that persists after whisking is abolished by facial nerve sectioning. Odors can either enhance or suppress barrel cortex neuronal responses, and while odor identity can be decoded from population activity, it does not interfere with the tactile representation. Thus, barrel cortex represents olfactory information which, in the absence of learned associations, is coded independently of tactile information.
DOI: 10.5281/zenodo.6397721
title: Data from: Olfactory modulation of barrel cortex activity during active whisking and passive whisker stimulation

description: Rodents depend on olfaction and touch to meet many of their fundamental needs. The joint significance of these sensory systems is underscored by an intricate coupling between sniffing and whisking. However, the impact of simultaneous olfactory and tactile inputs on sensory representations in the cortex remains elusive. To study these interactions, we recorded large populations of barrel cortex neurons using 2-photon calcium imaging in head-fixed mice during olfactory and tactile stimulation. We find that odors alter barrel cortex activity in at least two ways, first by enhancing whisking, and second by central cross-talk that persists after whisking is abolished by facial nerve sectioning. Odors can either enhance or suppress barrel cortex neuronal responses, and while odor identity can be decoded from population activity, it does not interfere with the tactile representation. Thus, barrel cortex represents olfactory information which, in the absence of learned associations, is coded independently of tactile information.
DOI: 10.5281/zenodo.6579864
title: Supplemental Material for a Systematic Literature Review on Benchmarks for Evaluating Debugging Approaches

description: Bug benchmarks are used in development and evaluation of debugging approaches. Quantitative performance comparison of different debugging approaches is only possible when they have been evaluated on the same dataset or benchmark. However, benchmarks are often specialized towards usage for certain debugging approaches in their contained data, metrics, and artifacts. Such benchmarks can not be easily used on debugging approaches outside their scope as such approach may rely on specific data such as bug reports or code metrics not included in the dataset. Furthermore, benchmarks vary in their size w.r.t. the number of subject programs and the size of the individual subject programs. For these reasons, we have performed a systematic literature review where we have identified 73 benchmarks that can be used to evaluate debugging approaches. We compare the different benchmarks with respect to their size and the provided information such as bug reports, contained test cases, and other code metrics. Furthermore, we have investigated how well the benchmarks realize the FAIR guiding principles. This comparison is intended to help researchers to quickly identify all suitable benchmarks for evaluating their specific debugging approaches. More information can be found in the publication: Thomas Hirsch and Birgit Hofer: "A Systematic Literature Review on Benchmarks for Evaluating Debugging Approaches", submitted to the Journal of Systems and Software, under review.
DOI: 10.5517/ccdc.csd.cc2929tj
title: CCDC 2117387: Experimental Crystal Structure Determination

description: Related Article: Yuan Gao, Jun-Su Zhou, Hong-Chun Liu, Yan Zhang, Wei-Hang Yin, Qun-Fang Liu, Guan-Wu Wang, Jin-Xin Zhao, Jian-Min Yue|2022|Phytochemistry|198|113142|doi:10.1016/j.phytochem.2022.113142
DOI: 10.5517/ccdc.csd.cc29gr4p
title: CCDC 2129332: Experimental Crystal Structure Determination

description: Related Article: Manan Ahmed, Katrina A Zenere, Natasha F Sciortino, Kasun Sankalpa Athukorala Arachchige, Gemma F Turner, Jace Cruddas, Carol Hua, Jason R Price, Jack K. Clegg, Francisco  Javier Valverde-Muñoz, Jose Antonio Real, Guillaume Chastanet, Stephen A Moggach, Cameron J Kepert, Benjamin J. Powell, Suzanne M. Neville|2022|Inorg.Chem.|61|6641|doi:10.1021/acs.inorgchem.2c00530
DOI: 10.5517/ccdc.csd.cc29gr6r
title: CCDC 2129334: Experimental Crystal Structure Determination

description: Related Article: Manan Ahmed, Katrina A Zenere, Natasha F Sciortino, Kasun Sankalpa Athukorala Arachchige, Gemma F Turner, Jace Cruddas, Carol Hua, Jason R Price, Jack K. Clegg, Francisco  Javier Valverde-Muñoz, Jose Antonio Real, Guillaume Chastanet, Stephen A Moggach, Cameron J Kepert, Benjamin J. Powell, Suzanne M. Neville|2022|Inorg.Chem.|61|6641|doi:10.1021/acs.inorgchem.2c00530
DOI: 10.5517/ccdc.csd.cc29ldx7
title: CCDC 2132859: Experimental Crystal Structure Determination

description: Related Article: Chunmei Chen, Xue Ren, Xiaowei Luo, YongHong Liu|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc29xl4z
title: CCDC 2142631: Experimental Crystal Structure Determination

description: Related Article: Lixia Guo, Xue Han, Yujie Ma, Jiangnan Li, Wanpeng Lu, Weiyao Li, Daniel Lee, Ivan da Silva, Yongqiang Cheng, Svemir Rudić, Pascal Manuel, Mark D. Frogley, Anibal J. Ramirez-Cuesta, Martin Schröder, Sihai Yang|2022|Chem.Commun.|58|5753|doi:10.1039/D2CC01197B
DOI: 10.5517/ccdc.csd.cc2bgcbj
title: CCDC 2158757: Experimental Crystal Structure Determination

description: Related Article: Andreas Lorbach, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bgdbk
title: CCDC 2158788: Experimental Crystal Structure Determination

description: Related Article: Christian Reus, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bgdfn
title: CCDC 2158791: Experimental Crystal Structure Determination

description: Related Article: Christian Reus, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bgdks
title: CCDC 2158795: Experimental Crystal Structure Determination

description: Related Article: Christian Reus, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bgn0h
title: CCDC 2159026: Experimental Crystal Structure Determination

description: Related Article: Steffen Pospiech, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc2bgn2k
title: CCDC 2159028: Experimental Crystal Structure Determination

description: Related Article: Steffen Pospiech, Michael Bolte, Matthias Wagner|2022|CSD Communication|||
DOI: 10.5281/zenodo.6393085
title: Radical Right On Twitter (ROT)

description: We collected the Radical Right On Twitter dataset (ROT7) to advance research into radical right activity online. The resource addresses a lack of data in this field, particularly data that relates to the activity of radical right actors. The dataset was funded without commercial support. ROT follows six months of Twitter activity (8th July 2020 to 9th January 2021) from 35 radical right actors. We follow the advice given by Williams, Burnap, and Sloan (2017) for publishing Twitter data on sensitive topics. ROT includes: It contains: Actors' content: all content produced by the actors, including posts (n = 22,131), replies (n = 19,947), quotes (n = 11,314), and retweets (n = 37,283). Actors' profiles: Twitter profile information for all 35 actors. Actors' followers: a list of each actor's followers, collected each day (combined n = 6,592,056). Actors' friends: a list of each actor's friends, collected each day (combined n = 262,856). Direct engagement: all tweets which engage with actors, including replies, quotes and retweets (n = 31,443,828). Engagers’ followers: List of followers of every user who replied, quoted or retweeted actors' content. We only collected users' list of followers once, even if they engaged with the actors multiple times during the period studied. Other engagement: all other tweets collected through Twitter API that mentions an actor (n = 10,939,868).
DOI: 10.5281/zenodo.6393084
title: Radical Right On Twitter (ROT)

description: We collected the Radical Right On Twitter dataset (ROT7) to advance research into radical right activity online. The resource addresses a lack of data in this field, particularly data that relates to the activity of radical right actors. The dataset was funded without commercial support. ROT follows six months of Twitter activity (8th July 2020 to 9th January 2021) from 35 radical right actors. We follow the advice given by Williams, Burnap, and Sloan (2017) for publishing Twitter data on sensitive topics. ROT includes: It contains: Actors' content: all content produced by the actors, including posts (n = 22,131), replies (n = 19,947), quotes (n = 11,314), and retweets (n = 37,283). Actors' profiles: Twitter profile information for all 35 actors. Actors' followers: a list of each actor's followers, collected each day (combined n = 6,592,056). Actors' friends: a list of each actor's friends, collected each day (combined n = 262,856). Direct engagement: all tweets which engage with actors, including replies, quotes and retweets (n = 31,443,828). Engagers’ followers: List of followers of every user who replied, quoted or retweeted actors' content. We only collected users' list of followers once, even if they engaged with the actors multiple times during the period studied. Other engagement: all other tweets collected through Twitter API that mentions an actor (n = 10,939,868).
DOI: 10.15468/3qmedr
title: LBBG_JUVENILE - Juvenile lesser black-backed gulls (Larus fuscus, Laridae) hatched in Zeebrugge (Belgium) [subsampled representation]

description: This animal tracking dataset is derived from Stienen et al. (2022, https://doi.org/10.5281/zenodo.6579643) a deposit of Movebank study 1259686571. 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>LBBG_JUVENILE - Juvenile lesser black-backed gulls (Larus fuscus, Laridae) hatched in Zeebrugge (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 LBBG_JUVENILE, using trackers developed by Ornitela (https://www.ornitela.com). The study has been operational since 2020. In total 92 individuals of Lesser black-backed gull (<em>Larus fuscus</em>) have been tagged shortly after fledging in the colony of Zeebrugge, mainly to study their habitat use and migration behaviour. Data are automatically synced with Movebank and from there periodically archived on Zenodo (see https://github.com/inbo/bird-tracking). This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch.