cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.71870/8e3q-j519
title: Data for: GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems
title: Data för: GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems

description: This dataset contains the samples of the training, validation and test data sets for the two numerical examples of the article ''GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems'' (Stenmark, Rylander, McKelvey & Ludvig-Osipov, 2026). All data is created using the finite element method as described in the article and is stored in the NPZ format which can be opened with the Python library NumPy (https://numpy.org/). The complete descriptions of all variables contained in the data are found in the article.
description: Detta dataset innehåller träning-, validering- och testdata för de två numeriska exemplen i artikeln "GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems" (Stenmark, Rylander, McKelvey & Ludvig-Osipov, 2026). Datat är skapat med hjälp av finita elementmetoden enligt beskrivning i artikeln och är lagrat i formatet NPZ som kan öppnas med Pythonbiblioteket NumPy (https://numpy.org/). Alla variabler i datasetet finns beskrivna i artikeln.
DOI: 10.71870/7bnk-0132
title: Data for: GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems
title: Data för: GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems

description: This dataset contains the samples of the training, validation and test data sets for the two numerical examples of the article ''GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems'' (Stenmark, Rylander, McKelvey & Ludvig-Osipov, 2026). All data is created using the finite element method as described in the article and is stored in the NPZ format which can be opened with the Python library NumPy (https://numpy.org/). The complete descriptions of all variables contained in the data are found in the article.
description: Detta dataset innehåller träning-, validering- och testdata för de två numeriska exemplen i artikeln "GIANT Networks: Very Deep Fully-Connected Neural Networks Applied to Microwave Problems" (Stenmark, Rylander, McKelvey & Ludvig-Osipov, 2026). Datat är skapat med hjälp av finita elementmetoden enligt beskrivning i artikeln och är lagrat i formatet NPZ som kan öppnas med Pythonbiblioteket NumPy (https://numpy.org/). Alla variabler i datasetet finns beskrivna i artikeln.
DOI: 10.17632/6mwgv6ktmj
title: DATA - Intensification of Pasture-Based Animal Production System Has Little Short-Term Effect on Soil Carbon Stock in the Southern Brazilian Highland

description: This dataset contains soil physical and textural data collected from pasture-based livestock systems under different levels of management intensification in the Southern Brazilian Highlands. The data include measurements across multiple soil depths and plots, covering variables such as soil bulk density, total porosity, microporosity, macroporosity, and soil texture fractions (sand, silt, and clay).

The dataset was generated as part of the research supporting the peer-reviewed article: “Intensification of pasture-based animal production system has little short-term effect on soil carbon stock in the Southern Brazilian Highland” by Camacho et al., published in Agronomy (2023, Vol. 13, No. 3, Article 850).

These data were used to evaluate how pasture intensification affects soil physical structure and carbon-related properties in subtropical grassland systems. The dataset provides transparency and reproducibility for the published analyses and may be useful for comparative studies on soil management, pasture intensification, and soil carbon dynamics in similar agroecosystems.
DOI: 10.17632/6mwgv6ktmj.1
title: DATA - Intensification of Pasture-Based Animal Production System Has Little Short-Term Effect on Soil Carbon Stock in the Southern Brazilian Highland

description: This dataset contains soil physical and textural data collected from pasture-based livestock systems under different levels of management intensification in the Southern Brazilian Highlands. The data include measurements across multiple soil depths and plots, covering variables such as soil bulk density, total porosity, microporosity, macroporosity, and soil texture fractions (sand, silt, and clay).

The dataset was generated as part of the research supporting the peer-reviewed article: “Intensification of pasture-based animal production system has little short-term effect on soil carbon stock in the Southern Brazilian Highland” by Camacho et al., published in Agronomy (2023, Vol. 13, No. 3, Article 850).

These data were used to evaluate how pasture intensification affects soil physical structure and carbon-related properties in subtropical grassland systems. The dataset provides transparency and reproducibility for the published analyses and may be useful for comparative studies on soil management, pasture intensification, and soil carbon dynamics in similar agroecosystems.
DOI: 10.17632/6mcbxsr2nh
title: Article database; Interaction of selenomethionine and zinc-methionine supplements on blood micromineral profiles and seminal characteristics of tropical Katahdin rams

description: Este conjunto de datos contiene la base experimental en crudo que respalda el artículo 
“Interaction of selenomethionine and zinc-methionine supplements on blood micromineral profiles and seminal characteristics of tropical Katahdin rams”.

La base incluye mediciones de características del eyaculado y perfiles minerales de selenio y zinc en semen y sangre de carneros Katahdin tropicales sometidos a suplementación dietaria. Las variables comprenden volumen seminal, parámetros de movilidad, morfología espermática, integridad de membrana, estado acrosomal y concentraciones de microminerales registradas a lo largo de los tiempos de muestreo y tratamientos experimentales.

Estos datos corresponden a observaciones originales sin procesamiento utilizadas en los análisis estadísticos del estudio y se proporcionan con fines de transparencia científica, reproducibilidad y reutilización futura.
DOI: 10.5281/zenodo.17209110
title: Alternative Splicing Directs PMCA2 to Lysosomes and is Linked to Neurodegeneration

description: Datasets

Microscopy images corresponding to Fig. 1a, 4d, Supplementary Fig. 1, 2, and 5 are deposited on Bioimage Archive with permanent identier: DOI 10.6019/S-BIAD2807

Data for Fig. 5a was reused from: Gene Expression Omnibus (accession ID: GSE178146), and for Fig. 5b and 5c from https://ega-archive.org/datasets/EGAD00001007698

Software (HPLC-RS) developed for the analysis of HPLC-GSL data (Fig. 4f) (is deposited on Zenodo with permanent identifier: DOI: 10.5281/zenodo.18172656 and on Github: https://github.com/ArchercatNEO/HPLC/tree/v0.10.0

Code used to analyse transcriptomic data (Fig. 5) is available from: https://github.com/Jbrenton191/RNAseq_splicing_pipeline
DOI: 10.5281/zenodo.18441234
title: Alternative Splicing Directs PMCA2 to Lysosomes and is Linked to Neurodegeneration

description: Datasets

Microscopy images corresponding to Fig. 1a, 4d, Supplementary Fig. 1, 2, and 5 are deposited on Bioimage Archive with permanent identier: DOI 10.6019/S-BIAD2807

Data for Fig. 5a was reused from: Gene Expression Omnibus (accession ID: GSE178146), and for Fig. 5b and 5c from https://ega-archive.org/datasets/EGAD00001007698

Software (HPLC-RS) developed for the analysis of HPLC-GSL data (Fig. 4f) (is deposited on Zenodo with permanent identifier: DOI: 10.5281/zenodo.18172656 and on Github: https://github.com/ArchercatNEO/HPLC/tree/v0.10.0

Code used to analyse transcriptomic data (Fig. 5) is available from: https://github.com/Jbrenton191/RNAseq_splicing_pipeline
DOI: 10.17632/6mcbxsr2nh.1
title: Article database; Interaction of selenomethionine and zinc-methionine supplements on blood micromineral profiles and seminal characteristics of tropical Katahdin rams

description: Este conjunto de datos contiene la base experimental en crudo que respalda el artículo 
“Interaction of selenomethionine and zinc-methionine supplements on blood micromineral profiles and seminal characteristics of tropical Katahdin rams”.

La base incluye mediciones de características del eyaculado y perfiles minerales de selenio y zinc en semen y sangre de carneros Katahdin tropicales sometidos a suplementación dietaria. Las variables comprenden volumen seminal, parámetros de movilidad, morfología espermática, integridad de membrana, estado acrosomal y concentraciones de microminerales registradas a lo largo de los tiempos de muestreo y tratamientos experimentales.

Estos datos corresponden a observaciones originales sin procesamiento utilizadas en los análisis estadísticos del estudio y se proporcionan con fines de transparencia científica, reproducibilidad y reutilización futura.
DOI: 10.15468/dl.yqa2my
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Jupiaba paranatinga",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 22 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005219-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18593011
title: LINF_320041200

description: Chloride channel protein | VCL3; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18593012
title: LINF_320041200

description: Chloride channel protein | VCL3; Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.6sx6tp
title: Occurrence Download

description: A dataset containing 16889 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aegithalos caudatus)",
 "Geometry POLYGON((55.000000 4.000000, 157.000000 4.000000, 157.000000 73.000000, 55.000000 73.000000, 55.000000 4.000000))",
 "Month is one of (March, April, May)",
 "Year is greater than or equal to 2014",
 "Year is less than or equal to 2024",
 "HasCoordinate is true",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is null",
 "CoordinateUncertaintyInMeters is less than or equal to 5000"
 ]
 },
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation, Specimen)"
 ]
}

 The dataset includes 16889 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005217-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vyz9mn
title: Occurrence Download

description: A dataset containing 35742 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Living Specimen",
 "Month is February",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 35742 records from 131 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005218-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29892113
title: <b>Pre-trained Graph Learning Model </b><b>with Spatial-aware Attention Mechanism </b><b>for Road Network Pattern</b><b>s</b><b> Recognition</b>

description: This repository contains the official implementation for the paper: "Pre-trained Graph Learning Model with Spatial-aware Attention Mechanism for Road Network Patterns Recognition". It aims to classify the input road networks into six road network patterns: Gridiron, Organic, Radial, Tributary, Linear, and Chaotic. We represent road networks as graphs and employ a pre-training strategy on a large corpus of unlabeled road network data. Our work introduces a novel pre-trained graph learning model that leverages a spatial-aware attention mechanism that allows the model to focus on salient geometric and topological features, leading to superior performance in pattern recognition tasks.
DOI: 10.6084/m9.figshare.29892113.v3
title: <b>Pre-trained Graph Learning Model </b><b>with Spatial-aware Attention Mechanism </b><b>for Road Network Pattern</b><b>s</b><b> Recognition</b>

description: This repository contains the official implementation for the paper: "Pre-trained Graph Learning Model with Spatial-aware Attention Mechanism for Road Network Patterns Recognition". It aims to classify the input road networks into six road network patterns: Gridiron, Organic, Radial, Tributary, Linear, and Chaotic. We represent road networks as graphs and employ a pre-training strategy on a large corpus of unlabeled road network data. Our work introduces a novel pre-trained graph learning model that leverages a spatial-aware attention mechanism that allows the model to focus on salient geometric and topological features, leading to superior performance in pattern recognition tasks.
DOI: 10.6084/m9.figshare.29892113.v2
title: <b>Pre-trained Graph Learning Model </b><b>with Spatial-aware Attention Mechanism </b><b>for Road Network Pattern</b><b>s</b><b> Recognition</b>

description: This repository contains the official implementation for the paper: "Pre-trained Graph Learning Model with Spatial-aware Attention Mechanism for Road Network Patterns Recognition". It aims to classify the input road networks into six road network patterns: Gridiron, Organic, Radial, Tributary, Linear, and Chaotic. We represent road networks as graphs and employ a pre-training strategy on a large corpus of unlabeled road network data. Our work introduces a novel pre-trained graph learning model that leverages a spatial-aware attention mechanism that allows the model to focus on salient geometric and topological features, leading to superior performance in pattern recognition tasks.
DOI: 10.15468/dl.c8xvcq
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-180 24,180 24,180 90,-180 90,-180 24))",
 {
 "or" : [
 "Month is April",
 "Month is May",
 "Month is June",
 "Month is July"
 ]
 },
 "OccurrenceStatus is Present",
 "TaxonKey is Numenius americanus Bechstein, 1812",
 "Year 1960-2000"
 ]
}

 The dataset includes 91 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0250424-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ase3ke
title: Occurrence Download

description: A dataset containing 501 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epidendrum fulgens Brongn."
 ]
}

 The dataset includes 501 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0265722-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z7rz2t
title: Occurrence Download

description: A dataset containing 51258 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Empetrum hermaphroditum Hagerup",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 51258 records from 229 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0183845-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.waeest
title: Occurrence Download

description: A dataset listing the 3 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epidendrum fulgens Brongn."
 ]
}

 The dataset's 3 records were derived from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0265715-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xrtk65
title: Occurrence Download

description: A dataset containing 44219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ranunculus aquatilis L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 44219 records from 411 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0292349-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.za2mum
title: Occurrence Download

description: A dataset containing 4720 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bidens subalternans DC.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4720 records from 128 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0289458-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yedqg8
title: Occurrence Download

description: A dataset containing 3446 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lysimachia ephemerum L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3446 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0299821-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48366/r689242
title: Application of machine learning in soil management

description: A comparison of four different studies employing machine learning in soil management shows diverse focuses, from evaluating soil drying to predicting crucial soil properties like organic carbon, moisture content, and temperature. Through various methodologies, these studies aim to provide precise estimations of soil properties to optimize agricultural practices and facilitate decision-making.
DOI: 10.15468/dl.yqkt6s
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scrophularia lateriflora Trautv.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 26 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0416585-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/37thhj
title: Long-term monitoring of primate, bird, and ungulate populations 2010-2022 for protected area management, Keo Seima Wildlife Sanctuary, Cambodia

description: Observations of 13 key species over 12 years in Keo Seima Wildlife Sanctuary, Cambodia, recorded during standardized line transect surveys. Distance sampling and density surface models are used to analyze this data and produce population estimates.
DOI: 10.15468/dl.3y9gfq
title: Occurrence Download

description: A dataset containing 4170 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pseudorchis albida subsp. straminea (Fernald) Á.Löve & D.Löve"
 ]
}

 The dataset includes 4170 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080641-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9cgua5
title: Occurrence Download

description: A dataset containing 475441 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Sweden",
 "OccurrenceStatus is Present",
 {
 "or" : [
 "TaxonKey is Gasterosteus aculeatus Linnaeus, 1758",
 "TaxonKey is Gasterosteus gymnurus Denys, Geiger, Persat, Keith & Dettai, 2015",
 "TaxonKey is Gobio gobio (Linnaeus, 1758)",
 "TaxonKey is Gobius microps Krøyer, 1838",
 "TaxonKey is Gobius minutus Pallas, 1770",
 "TaxonKey is Gymnocephalus cernua (Linnaeus, 1758)",
 "TaxonKey is Huso huso (Linnaeus, 1758)",
 "TaxonKey is Lampetra fluviatilis (Linnaeus, 1758)",
 "TaxonKey is Lampetra planeri (Bloch, 1784)",
 "TaxonKey is Leucaspius delineatus (Heckel, 1843)",
 "TaxonKey is Leuciscus cephalus (Linnaeus, 1758)",
 "TaxonKey is Leuciscus idus (Linnaeus, 1758)",
 "TaxonKey is Leuciscus leuciscus (Linnaeus, 1758)",
 "TaxonKey is Liza aurata (Risso, 1810)",
 "TaxonKey is Liza ramada (Risso, 1827)",
 "TaxonKey is Lota lota (Linnaeus, 1758)",
 "TaxonKey is Lota vulgaris Jenyns, 1835"
 ]
 }
 ]
}

 The dataset includes 475441 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0302264-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8qs6mq
title: Occurrence Download

description: A dataset containing 1214 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Atherina boyeri Risso, 1810",
 "Year 2000-2021"
 ]
}

 The dataset includes 1214 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0270054-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6wn9f7
title: Occurrence Download

description: A dataset containing 1953 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Neocrex erythrops (P.L.Sclater, 1867)"
 ]
}

 The dataset includes 1953 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0426692-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wrywjw
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Begonia hainanensis Chun & F.Chun"
 ]
}

 The dataset includes 17 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0084192-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z2jc26
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Moricandia foetida Bourg."
 ]
}

 The dataset includes 78 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0417976-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vyms4v
title: Occurrence Download

description: A dataset containing 24138 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carduus acanthoides L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 24138 records from 280 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0257724-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b3n98e
title: Occurrence Download

description: A dataset containing 765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Spain, Portugal, Morocco)",
 "Month is one of (December, January, February)",
 "TaxonKey is Phylloscopus inornatus (Blyth, 1842)",
 "Year 1960-2021"
 ]
}

 The dataset includes 765 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000278-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.