cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.16322765
title: Penggunaan Frasa "عذاب الانتظار" dalam Media Sosial Arab: Korpus Observasional

description: Dokumen ini merupakan cuplikan observasional data observasional yang merekam penggunaan frasa ‘adzāb al-intizhār (عذاب الانتظار) oleh pengguna media sosial Arab, khususnya di Twitter, selama periode April hingga November 2024. Frasa ini dianalisis sebagai bentuk pergeseran makna leksikal dari domain religius ke fungsi metaforis dan emosional dalam komunikasi digital. Data ini digunakan sebagai bagian dari studi disertasi mengenai perubahan makna dalam bahasa Arab modern di media sosial. Dokumen ini mendukung analisis dalam Bab IV disertasi dengan contoh autentik dari komunitas daring Arab.
DOI: 10.5281/zenodo.16322766
title: Penggunaan Frasa "عذاب الانتظار" dalam Media Sosial Arab: Korpus Observasional

description: Dokumen ini merupakan cuplikan observasional data observasional yang merekam penggunaan frasa ‘adzāb al-intizhār (عذاب الانتظار) oleh pengguna media sosial Arab, khususnya di Twitter, selama periode April hingga November 2024. Frasa ini dianalisis sebagai bentuk pergeseran makna leksikal dari domain religius ke fungsi metaforis dan emosional dalam komunikasi digital. Data ini digunakan sebagai bagian dari studi disertasi mengenai perubahan makna dalam bahasa Arab modern di media sosial. Dokumen ini mendukung analisis dalam Bab IV disertasi dengan contoh autentik dari komunitas daring Arab.
DOI: 10.17632/t4npyttrbf
title: TRuE-AD3 supplemental data and PLS

description: These are supplemental data and a plain-language summary to the article titled "Efficacy and Safety of Ruxolitinib Cream in Children Aged 2 to 11 Years With Atopic Dermatitis: Results From TRuE-AD3, a Phase 3, Randomized Double-Blind Study", which was published in the Journal of the American Academy of Dermatology
DOI: 10.17632/t4npyttrbf.2
title: TRuE-AD3 supplemental data and PLS

description: These are supplemental data and a plain-language summary to the article titled "Efficacy and Safety of Ruxolitinib Cream in Children Aged 2 to 11 Years With Atopic Dermatitis: Results From TRuE-AD3, a Phase 3, Randomized Double-Blind Study", which was published in the Journal of the American Academy of Dermatology
DOI: 10.2909/a03370aa-cf17-42e8-b765-d60576c9909d
title: Reference Land Cover Change in Yangambi 2000-2016 (vector) - version 1, October 2019

description: This metadata refers to the Land Cover Change vector data generated over Yangambi (Africa) in the framework of the Copernicus Global Land Hot Spot Mapping (C-GL-HSM) contract under the coordination of JRC. This area of interest is either mapped with the generic 8 classes dichotomus legend (CAF_99_lcc_a) or the detailed modular legend (CAF_99_lcc_b).

The mapped area of interest (AOI) represents a key landscape for conservation area (KLC). It is situated in the central part of the Democratic Republic of Congo (DRC), along the Congo River, in the thick central African forest. The KLC has a total size of about 727,622 ha (7276.22 km²), while the Yangambi biosphere reserve has a total area of 223,100 ha (2,231 km²). The site is very important from a biodiversity point of view since it hosts about 32,000 tree species. The elephant (Loxodonta Africana Cyclotis), the river hog (Potamochoerus Porcus) and monkeys (Cercopithecusspp) are present in this area, however they are also among the most threatened species (UNESCO).

Reference time: 2000 - 2016
DOI: 10.17632/dnk6839b86.2
title: Climate-Land Cover data used by DeepEcoClimate

description: Sourced and processed from 

- Climate normals: CRU TS v4.06
- Land cover: MCD12C1
- Elevation: GMTED2010

-------------------------------------

climate_data_land.h5 contains 7 datasets with gzip compression

'indices' - shape (66501, 2) - latitude, longitude for all land pixels
'elev' - shape (66501, ) - average elevation (in metre) for each land pixel
'tmp' - shape (66501, 124, 12) - average daily mean temperature of each month during 1901-2024 for each land pixel
'pre' - shape (66501, 124, 12) - precipitation of each month during 1901-2024 for each land pixel
'pet' - shape (66501, 124, 12) - potential evapotranspiration (PET) of each month during 1901-2024 for each land pixel
'tmn' - shape (66501, 124, 12) - average daily minimum temperature of each month during 1901-2024 for each land pixel
'tmx' - shape (66501, 124, 12) - average daily maximum temperature of each month during 1901-2024 for each land pixel

Temperatures are in Celcius, precipitation and PET are in millimeters
'indices', 'elev', 'pet' are not used in the climate classification models, only for plotting

-------------------------------

climate_variables.h5 contains 1 dataset with gzip compression

'res' - shape (66502, 124, 10)
res[-1, :, :] is the global average
Ten climate variables during 1901-2024 for each land pixel

"Coldest Month Mean Temperature": 0,
"Hottest Month Mean Temperature": 1,
"Coldest Month Mean Daily Minimum": 2,
"Hottest Month Mean Daily Maximum": 3,
"Mean Annual Temperature": 4,
"Wettest Month Precipitation": 5,
"Driest Month Precipitation": 6,
"Total Annual Precipitation": 7,
"Thermal Index": 8,
"Aridity Index": 9,

Temperature in Celcius, precipitation in millimeters
These data facilitates plotting in the ClimViz app

-------------------------------------

data.mat contains 4 ndarrays

'inputs' - shape (1411486, 3, 12) - 1411486 observations, tmn, pre, tmx for 12 months
'targets' - shape (1411486, 14) - 1411486 observations, proportions for 14 land cover types
'features' - shape (1411486, 60) - 1411486 observations, 60 features derived from MATLAB-pretrained model
'new_centroid' - shape (26, 60) - 26 centroids of climate types in the feature space, manually merged from a (5, 4, 3) self-organizing map trained in MATLAB

This file is used in TorchModel.py (in the GitHub repo) to migrate (and regularize) the model from MATLAB to PyTorch
Check the GitHub repo (https://github.com/peace-Van/ClimViz) for details
DOI: 10.2909/39d78f16-28df-4c6e-8097-2981a80320d3
title: Reference Land Cover Change in Yangambi 2016-2019 (vector) - version 1, October 2019

description: This metadata refers to the Land Cover Change vector data generated over Yangambi (Africa) in the framework of the Copernicus Global Land Hot Spot Mapping (C-GL-HSM) contract under the coordination of JRC. This area of interest is either mapped with the generic 8 classes dichotomus legend (CAF_99_lcc_a) or the detailed modular legend (CAF_99_lcc_b).

The mapped area of interest (AOI) represents a key landscape for conservation area (KLC). It is situated in the central part of the Democratic Republic of Congo (DRC), along the Congo River, in the thick central African forest. The KLC has a total size of about 727,622 ha (7276.22 km²), while the Yangambi biosphere reserve has a total area of 223,100 ha (2,231 km²). The site is very important from a biodiversity point of view since it hosts about 32,000 tree species. The elephant (Loxodonta Africana Cyclotis), the river hog (Potamochoerus Porcus) and monkeys (Cercopithecusspp) are present in this area, however they are also among the most threatened species (UNESCO).

Reference time: 2016 - 2019
DOI: 10.15468/dl.bnz6kb
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Gyps africanus)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 52 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028823-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k9625n
title: Occurrence Download

description: A dataset containing 6499 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cyclamen repandum"
 ]
}

 The dataset includes 6499 records from 130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028825-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h3n2cg
title: Occurrence Download

description: A dataset containing 10651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Russian Federation, Afghanistan, Armenia, Azerbaijan, Georgia, Iraq, Iran (Islamic Republic of), Palestine, State of, Israel, Kyrgyzstan, Syrian Arab Republic, Uzbekistan, Türkiye, Lebanon, Turkmenistan, Kazakhstan)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lactuca serriola",
 "Year is greater than or equal to 1901"
 ]
}

 The dataset includes 10651 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028826-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t7m856
title: Occurrence Download

description: A dataset containing 210 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cirsium vulgare",
 "Country is Mexico",
 "HasCoordinate is true"
 ]
}

 The dataset includes 210 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028827-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ns3ya5
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Centaurea calcitrapa",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 151 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028828-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.2909/8ba1c9fb-8625-4ae2-a4ba-9d780bedac2b
title: Reference Land Cover in Caribbean 2017-2018 (vector) - version 1, Oct. 2020

description: This metadata refers to the Land Cover vector data generated over Caribbean for 2017 in the framework of the Copernicus Global Land Hot Spot Mapping (C-GL-HSM) contract under the coordination of JRC. 
This area of interest is either mapped with the generic 8 classes dichotomus legend (CAR_01_lc_a) or the detailed modular legend (CAR_01_lc_b).

The mapped area of interest (AOI) represents a key landscape for conservation area (KLC). 

The Caribbean has a long history of establishing protected areas (PA) with the first Caribbean PA’s being established more than 200 years ago. While PA development continued steadily throughout the 1950s to 1980s, there has been a rise in the number of sites declared since the 1990s. This increase resulted mainly from awareness raising and showcasing the benefits provided by PA’s. The objectives for PA development broadened in scope from watershed and wildlife protection to fisheries management, biodiversity protection, attractions for tourism, and education (http://parkscaribbean.net).

Reference time: 2017 - 2018
DOI: 10.15468/dl.dsk8u9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Centaurea calcitrapa",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028829-250717081556266/datasets/export for details.
DOI: 10.2909/3760a654-6d0d-454d-8a3b-4b8f0bc1e4ad
title: Reference Land Cover in Comoe-Mole 2015-2018 (vector) - version 1, June 2018

description: This metadata refers to the Land Cover vector data generated over Comoe-Mole (Africa) for 2015 in the framework of the Copernicus Global Land Hot Spot Mapping (C-GL-HSM) contract under the coordination of JRC. This area of interest is mapped with the generic 8 classes dichotomus legend (WAF_05_lc_a file).

The mapped area of interest (AOI) represents a Key Landscape for Conservation area (KLC). The KLC has a total size of 4 million ha (40,000 km²) and is located in the northern part of the countries of Ghana and Côte d’Ivoire. The Comoe National Park with a size of 1,149,150 ha (11,491.5 km²) has been designated in 1968 and recognized as UNESCO World heritage site in 1983. The Mole National Park has an area of 484,040 ha (4,840.4 km²) and has been established in 1971. The parks are within the Guinean forest-savanna mosaic (only Comoe) and west Sudanian savanna eco-region. 

Reference time: 2015 - 2018
DOI: 10.57745/eqp24r
title: 199_4_50_1440.json

description: :unav
DOI: 10.57745/lhiziu
title: 187_4_50_1440.json

description: :unav
DOI: 10.17632/29hpr3nrrv.1
title: Mating status-dependent dopaminergic modulation of auditory sensory neurons in Drosophila

description: This dataset supports the findings of the article titled "Mating status-dependent dopaminergic modulation of auditory sensory neurons in Drosophila"
DOI: 10.57745/7edgep
title: 795_2_26_2880.json

description: :unav
DOI: 10.57745/dmxumi
title: 187_2_26_2880.json

description: :unav
DOI: 10.57745/wuozcw
title: 795_4_50_1440.json

description: :unav
DOI: 10.57745/4oaat3
title: 199_2_26_2880.json

description: :unav
DOI: 10.57745/lgfa15
title: readme.txt

description: :unav
DOI: 10.57745/ebdn5w
title: Dataset for the Assembly Line Balancing Problem with Learning Effect

description: This dataset contains aeronautical benchmarks used for experimenting solving approaches of the Assembly Line Balancing Problem with Learning Effect. These benchmarks originate from the industry. However, the learning rate and task learning duration are randomly generated within realistic ranges, based on industrial data.
DOI: 10.2909/450107d1-d7a8-4a7f-8edf-b941468ea698
title: Reference Land Cover in Cross River-Takamanda-Mt Cameroon-Korup 2015-2019 (vector) - version 1, Feb. 2020

description: This metadata refers to the Land Cover vector data generated over Cross River-Takamanda-Mt Cameroon-Korup (Africa) for 2016 in the framework of the Copernicus Global Land Hot Spot Mapping (C-GL-HSM) contract under the coordination of JRC. 
This area of interest is either mapped with the generic 8 classes dichotomus legend (CAF_01_lc_a) or the detailed modular legend (CAF_01_lc_b).

The mapped area of interest (AOI) represents a key landscape for conservation area (KLC). 

This transboundary KLC has a total size of almost 8 million ha (80,000 km²) and is situated between the border of Nigeria and Cameroon. It includes several areas under protection including:
In the north-eastern sector the National Parks of Faro, Gashaka-Gumti and Tchabal Mbabo. This area is characterised mainly by savannah grassland and some very mountainous regions with mountain forests. Gashaka-Gumti is Nigeria’s largest National Park (6730 km²) established for the conservation of biodiversity and for the support of rural development and traditional livelihood.

Reference time: 2015 - 2019
DOI: 10.17632/hcdd4jz4jr
title: Supplemental Table and Figure

description: Supplemental Table 1. HLH-2004 and HLH-2009 diagnostic criteria.
Supplemental Figure 1. PRISMA flowchart detailing the study selection process.
DOI: 10.15468/dl.uyr3pw
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Centaurea calcitrapa",
 "Country is Chile",
 "HasCoordinate is true"
 ]
}

 The dataset includes 29 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028830-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hcdd4jz4jr.1
title: Supplemental Table and Figure

description: Supplemental Table 1. HLH-2004 and HLH-2009 diagnostic criteria.
Supplemental Figure 1. PRISMA flowchart detailing the study selection process.
DOI: 10.15468/dl.pukc3s
title: Occurrence Download

description: A dataset containing 335 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Symphytum uplandicum",
 "Country is Russian Federation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 335 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028833-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d26d4f
title: Occurrence Download

description: A dataset containing 2446709 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 2446709 records from 4573 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028800-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0167339.10fu
title: SH0167339.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0167340.10fu
title: SH0167340.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0167341.10fu
title: SH0167341.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0167342.10fu
title: SH0167342.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0167343.10fu
title: SH0167343.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.