cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/gfcmdbvw65
title: A Multi-Stage, Pixel-Level Annotated Apple Dataset for Precision Agriculture Research

description: The dataset of apples was collected from September 2017 to October 2019 in an experimental orchard at the College of Horticulture, Northwest A&F University (Yangling, Shaanxi, China). The dataset consists of 1,124 apple images captured under varying natural lighting and weather conditions, covering multiple growth stages—from immature green apples to mature red targets—including transitional color variations. The dataset is classified into three distinct categories: immature (green), semi-mature (transitional), and mature (red). Table 1 gives a detailed description and visualization for each categories. The dataset contains 1,406 annotated images capturing apples across three developmental stages: 532 images with immature (green) apples, 316 with semi-mature (color-transitioning) apples, and 384 with mature (red) apples. The non-additive total reflects natural orchard conditions where individual images frequently contain multiple maturity stages—either three stages simultaneously or two transitional stages coexisting. This indicates that asynchronous fruit development occurs within orchards. Across all images, we annotated 2,573 distinct apple instances: 921 immature (green), 813 semi-mature (green-red color transition), and 839 mature (red) apples.
DOI: 10.15468/dl.hafsx8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Durio zibethinus",
 "Country is Lao People’s Democratic Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036747-250920141307145/datasets/export for details.
DOI: 10.17632/gfcmdbvw65.3
title: A Multi-Stage, Pixel-Level Annotated Apple Dataset for Precision Agriculture Research

description: The dataset of apples was collected from September 2017 to October 2019 in an experimental orchard at the College of Horticulture, Northwest A&F University (Yangling, Shaanxi, China). The dataset consists of 1,124 apple images captured under varying natural lighting and weather conditions, covering multiple growth stages—from immature green apples to mature red targets—including transitional color variations. The dataset is classified into three distinct categories: immature (green), semi-mature (transitional), and mature (red). Table 1 gives a detailed description and visualization for each categories. The dataset contains 1,406 annotated images capturing apples across three developmental stages: 532 images with immature (green) apples, 316 with semi-mature (color-transitioning) apples, and 384 with mature (red) apples. The non-additive total reflects natural orchard conditions where individual images frequently contain multiple maturity stages—either three stages simultaneously or two transitional stages coexisting. This indicates that asynchronous fruit development occurs within orchards. Across all images, we annotated 2,573 distinct apple instances: 921 immature (green), 813 semi-mature (green-red color transition), and 839 mature (red) apples.
DOI: 10.17632/njys4dhgh8
title: LB MRT Inpainting RGB images Dataset

description: Images inpainted by Lattice Boltzmann based anisotropic diffusion method.
This dataset was created to support research in the fields of image inpainting, defect detection, and restoration algorithms. It consists of 10,000 RGB-color images originally selected from a larger public dataset Places*. Synthetic defects were introduced into these images to simulate realistic degradation, and corresponding binary masks were generated to annotate the defect regions. Additionally, the dataset includes the results of applying an image inpainting algorithm to these corrupted images, allowing researchers to evaluate restoration quality.

The dataset is structured into four main folders:

"orig.zip": Contains the original 10,000 RGB images. These were selected from a public dataset, resized and preprocessed uniformly.

"spot.zip": Contains the same images as `orig/`, but with synthetic defects applied.

"mask.zip": Contains binary masks corresponding to the defect locations in the `spot/` images. A value of `1` indicates a defect pixel, and `0` indicates background.

"result.zip": Contains the inpainted images generated from the `spot/` images using a selected inpainting algorithm. These outputs can be used to evaluate inpainting performance using both visual inspection and quantitative metrics.


*Places: A 10 million Image Database for Scene Recognition
B. Zhou, A. Lapedriza, A. Khosla, A. Oliva, and A. Torralba
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
DOI: 10.17632/njys4dhgh8.1
title: LB MRT Inpainting RGB images Dataset

description: Images inpainted by Lattice Boltzmann based anisotropic diffusion method.
This dataset was created to support research in the fields of image inpainting, defect detection, and restoration algorithms. It consists of 10,000 RGB-color images originally selected from a larger public dataset Places*. Synthetic defects were introduced into these images to simulate realistic degradation, and corresponding binary masks were generated to annotate the defect regions. Additionally, the dataset includes the results of applying an image inpainting algorithm to these corrupted images, allowing researchers to evaluate restoration quality.

The dataset is structured into four main folders:

"orig.zip": Contains the original 10,000 RGB images. These were selected from a public dataset, resized and preprocessed uniformly.

"spot.zip": Contains the same images as `orig/`, but with synthetic defects applied.

"mask.zip": Contains binary masks corresponding to the defect locations in the `spot/` images. A value of `1` indicates a defect pixel, and `0` indicates background.

"result.zip": Contains the inpainted images generated from the `spot/` images using a selected inpainting algorithm. These outputs can be used to evaluate inpainting performance using both visual inspection and quantitative metrics.


*Places: A 10 million Image Database for Scene Recognition
B. Zhou, A. Lapedriza, A. Khosla, A. Oliva, and A. Torralba
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
DOI: 10.17632/2dp7pkyz85
title: Meta Analysis

description: Identifiability to the Recipient Increases Unilateral Giving: A Meta-analysis Informed by Relational Models Theory
DOI: 10.17632/2dp7pkyz85.1
title: Meta Analysis

description: Identifiability to the Recipient Increases Unilateral Giving: A Meta-analysis Informed by Relational Models Theory
DOI: 10.26023/xb43-bsrf-vh04
title: Gan, Addu Atoll, Maldives AMF-2 Surface Meteorology Data. Version 1.0

description: This data set contains the 1 minute surface meteorological data from the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) surface meteorological station was located on Gan during DYNAMO. The data are in NetCDF format.
DOI: 10.15468/dl.7uxn9q
title: Occurrence Download

description: A dataset containing 1909262 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 1909262 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036737-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/f5px9myr2j
title: Preparation of g-C3N4-PEI Quantum Dot Photocatalytic Flower and Its Performance Study for Degrading Tetracycline

description: This paper uses carbon nitride and PEI as precursors to prepare g-C3N4-PEI water-soluble photocatalytic materials and then uses that material and sodium alginate hydrogel to construct photocatalytic flowers. The main research content and conclusions are as follows: 
(1) Five samples of g-C3N4-PEI were prepared using different ratios of both g-C3N4 and PEI materials; the g-C3N4: PEI=1:5 sample has the best degradation performance with a TC removal rate of 73.546%. The UV-Vis, FTIR, fluorescence, and XPS characterizations showed that g-C3N4-PEI had the basic s-triazine ring, carbon, and 
nitrogen atom heterocycle (2p orbitals), graphitic C–N network, amino and hydroxyl groups. The optimal light absorption wavelength is 368(nm), and the quantum yield (λex = 340 nm) was 20.9%, using quinine sulfate as a standard. 
(2) Throughout the experiments, the flower's removal rate of TC was (absorption 50%, photodegradation 66.75%), higher than pure g-C3N4 (6.23% and 52.76%).
DOI: 10.17632/f5px9myr2j.1
title: Preparation of g-C3N4-PEI Quantum Dot Photocatalytic Flower and Its Performance Study for Degrading Tetracycline

description: This paper uses carbon nitride and PEI as precursors to prepare g-C3N4-PEI water-soluble photocatalytic materials and then uses that material and sodium alginate hydrogel to construct photocatalytic flowers. The main research content and conclusions are as follows: 
(1) Five samples of g-C3N4-PEI were prepared using different ratios of both g-C3N4 and PEI materials; the g-C3N4: PEI=1:5 sample has the best degradation performance with a TC removal rate of 73.546%. The UV-Vis, FTIR, fluorescence, and XPS characterizations showed that g-C3N4-PEI had the basic s-triazine ring, carbon, and 
nitrogen atom heterocycle (2p orbitals), graphitic C–N network, amino and hydroxyl groups. The optimal light absorption wavelength is 368(nm), and the quantum yield (λex = 340 nm) was 20.9%, using quinine sulfate as a standard. 
(2) Throughout the experiments, the flower's removal rate of TC was (absorption 50%, photodegradation 66.75%), higher than pure g-C3N4 (6.23% and 52.76%).
DOI: 10.17632/vn59kcyhb3.2
title: Dataset of Soil, Geotechnical, and Mineralogical Data from Ngaoundal, Cameroon

description: This dataset contains pedological, geotechnical, and mineralogical data collected from the Ngaoundal area, Cameroon. 
It includes geographical coordinates of sampling sites, laboratory geotechnical analyses, XRD and XRF results, macrophotographies of soil samples, 
and soil profile descriptions. The dataset has been compiled to support studies on soil characterization, land management, and hydrogeology.
DOI: 10.5281/zenodo.17244869
title: First test
DOI: 10.17632/tpktyk3g58
title: Relevance of multi-target action in the biocontrol mechanisms of Enterobacter pseudoroggenkampii GVv1 against Phytophthora sojae

description: We previously reported that the rhizobacterium Enterobacter pseudoroggenkampii strain GVv1 protects soybeans against Phytophthora root and stem rot (PRSR), caused by Phytophthora sojae. In this study, we explored GVv1’s mode of action by comparing its effects on P. sojae with three bacterial strains showing low or no protective activity against PRSR.
DOI: 10.17632/tpktyk3g58.1
title: Relevance of multi-target action in the biocontrol mechanisms of Enterobacter pseudoroggenkampii GVv1 against Phytophthora sojae

description: We previously reported that the rhizobacterium Enterobacter pseudoroggenkampii strain GVv1 protects soybeans against Phytophthora root and stem rot (PRSR), caused by Phytophthora sojae. In this study, we explored GVv1’s mode of action by comparing its effects on P. sojae with three bacterial strains showing low or no protective activity against PRSR.
DOI: 10.17632/25r5d4vf5p.1
title: Humps in κ-T curves: Evidence for the Stable Single-domain to Superparamagnetic Transition in Magnetite

description: In this dataset, the original data of temperature-dependent thermomagnetic curves (k-T curves and Ms-T curves) and hysteresis data are included, which are related to the article entitled "Humps in κ-T curves: Evidence for the Stable Single-domain to Superparamagnetic Transition in Magnetite".
DOI: 10.17632/v7gdh9prbj
title: mTOR inhibition reprograms cellular lipid homeostasis by inducing alternative lipid uptake and promoting cholesterol transport. Shin et al.

description: Raw data files for the manuscript entitled 'mTOR inhibition reprograms cellular lipid homeostasis by inducing alternative lipid uptake and promoting cholesterol transport.'
DOI: 10.17632/v7gdh9prbj.1
title: mTOR inhibition reprograms cellular lipid homeostasis by inducing alternative lipid uptake and promoting cholesterol transport. Shin et al.

description: Raw data files for the manuscript entitled 'mTOR inhibition reprograms cellular lipid homeostasis by inducing alternative lipid uptake and promoting cholesterol transport.'
DOI: 10.15468/dl.r4hwph
title: Occurrence Download

description: A dataset containing 690 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Specimen)",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Herpailurus yagouaroundi"
 ]
}

 The dataset includes 690 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036748-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/ezw2-men4-cw0b
title: R/V Roger Revelle Flux, Near-Surface Meteorology, and Navigation Data: DYNAMO Legacy Collection. Version 1.0

description: This data set contains the 10 minute surface meteorological data from the R/V Roger Revelle for its four cruises in the Indian Ocean during DYNAMO. The data are in NetCDF format.
DOI: 10.60520/ieda/114172
title: Stable carbon and oxygen isotope compositions of Jurassic aptychi from the Mecsek Mts., southern Hungary

description: Stable carbon and oxygen isotope compositions (δ13C and δ18O values, respectively, in ‰ relative to V-PDB) of samples OxAM-1064 (least altered part of the laminated layer in the sample) and H1. The samples are Jurassic aptychi from the Mecsek Mts., southern Hungary. See Bujtor and Albrecht (2021, DOI: 10.7306/VJ.19.3), and Demény et al. (2025, Communications Earth and Environment, under revision).
description: Bujtor, L., Albrecht, R. (2021) Latest Oxfordian – earliest Kimmeridgian ammonite dominated fauna and microfacies from the ammonitico rosso-type Fonyászó Limestone Formation at Zengővárkony (Mecsek Mountains, Hungary). Volumina Jurassica XIX, 61-94; 12.; 
Bujtor, L., Demény, A., Németh, P., Bajnóczi, B. (2024) Laevaptychi as reliable paleotemperature archives: high-resolution stable isotope compositions of Kimmeridgian (Jurassic) lamellar structured aspidoceratid lower mandibles from Zengővárkony (Mecsek Mountains, Hungary). Int. J. Earth Sci. 113, 353–367.
DOI: 10.17632/92jxfc48gg
title: Liquid Chromatography-Mass Spectrometry Method Validation for β-Hydroxythiofentanyl

description: This dataset corresponds to the method validation process of a Liquid Chromatography-Mass Spectrometry (LC-MS) analytical approach developed for the detection and quantification of β-Hydroxythiofentanyl—a synthetic opioid with high pharmacological activity and potential forensic/toxicological relevance. The dataset encompasses key validation parameters, including linearity (calibration curve data across relevant concentration ranges), accuracy (recovery rates from matrix-matched samples such as plasma, urine, or tissue homogenates), precision (intra-day and inter-day repeatability with relative standard deviations), selectivity (peak purity data and interference testing against structurally similar opioids), limit of detection (LOD) and limit of quantification (LOQ), matrix effect (ion suppression/enhancement assessment), and stability (data on short-term, long-term, freeze-thaw, and post-preparation stability of β-Hydroxythiofentanyl in matrices). Additionally, the dataset includes critical experimental details: LC conditions (column type, mobile phase composition, flow rate, injection volume), MS parameters (ionization mode, collision energy), sample preparation protocols (extraction method, cleanup steps), and replicate measurement data for quality control (QC) samples. This dataset serves as a foundational resource for researchers in forensic toxicology, clinical chemistry, or analytical chemistry seeking to adopt, verify, or optimize LC-MS methods for β-Hydroxythiofentanyl analysis, and supports reproducibility in studies involving this synthetic opioid.
DOI: 10.17632/92jxfc48gg.1
title: Liquid Chromatography-Mass Spectrometry Method Validation for β-Hydroxythiofentanyl

description: This dataset corresponds to the method validation process of a Liquid Chromatography-Mass Spectrometry (LC-MS) analytical approach developed for the detection and quantification of β-Hydroxythiofentanyl—a synthetic opioid with high pharmacological activity and potential forensic/toxicological relevance. The dataset encompasses key validation parameters, including linearity (calibration curve data across relevant concentration ranges), accuracy (recovery rates from matrix-matched samples such as plasma, urine, or tissue homogenates), precision (intra-day and inter-day repeatability with relative standard deviations), selectivity (peak purity data and interference testing against structurally similar opioids), limit of detection (LOD) and limit of quantification (LOQ), matrix effect (ion suppression/enhancement assessment), and stability (data on short-term, long-term, freeze-thaw, and post-preparation stability of β-Hydroxythiofentanyl in matrices). Additionally, the dataset includes critical experimental details: LC conditions (column type, mobile phase composition, flow rate, injection volume), MS parameters (ionization mode, collision energy), sample preparation protocols (extraction method, cleanup steps), and replicate measurement data for quality control (QC) samples. This dataset serves as a foundational resource for researchers in forensic toxicology, clinical chemistry, or analytical chemistry seeking to adopt, verify, or optimize LC-MS methods for β-Hydroxythiofentanyl analysis, and supports reproducibility in studies involving this synthetic opioid.
DOI: 10.17632/x3kn2dw7bp
title: Ants3 toolkit: Front-end for Geant4 with interactive GUI and Python scripting

description: Ants3 is a toolkit that serves as a front-end for particle simulations in Geant4 and offers a custom simulator for optical photons. It features a fully interactive Graphical User Interface and an extensive scripting system based on general-purpose scripting languages (Python and JavaScript). Ants3 covers the entire detector simulation/optimization cycle, providing an intuitive approach for configuration of the geometry and simulation conditions, the possibility to automatically distribute workload over local and network resources, and giving a suite of versatile tools based on CERN ROOT for the analysis of the results. The intended application area is the development of new detectors and readout methods. The toolkit has been designed to be user-friendly for those with little experience in simulations and programming.
DOI: 10.17632/x3kn2dw7bp.1
title: Ants3 toolkit: Front-end for Geant4 with interactive GUI and Python scripting

description: Ants3 is a toolkit that serves as a front-end for particle simulations in Geant4 and offers a custom simulator for optical photons. It features a fully interactive Graphical User Interface and an extensive scripting system based on general-purpose scripting languages (Python and JavaScript). Ants3 covers the entire detector simulation/optimization cycle, providing an intuitive approach for configuration of the geometry and simulation conditions, the possibility to automatically distribute workload over local and network resources, and giving a suite of versatile tools based on CERN ROOT for the analysis of the results. The intended application area is the development of new detectors and readout methods. The toolkit has been designed to be user-friendly for those with little experience in simulations and programming.
DOI: 10.15468/dl.j334c6
title: Occurrence Download

description: A dataset containing 38300 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Griselinia littoralis)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 38300 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036749-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2vbk4fcrsz
title: Content freebooting

description: This dataset accompanies the study on content freebooting in social media advertising and its exploitation by counterfeit and dupe brands. The dataset captures advertising activity around a case study product (a floral corset sundress) across TikTok and linked e-commerce domains. It integrates ad-level metadata, creator provenance, network diffusion structures, product inspections, fulfillment outcomes, and detection pipeline results. The dataset is designed to support research and teaching in areas such as multimedia forensics, adversarial content manipulation, e-commerce fraud detection, and network diffusion analysis. It is suitable for both computational modeling (e.g., duplicate detection, network clustering) and qualitative case-based learning.

Data Collection and Methodology
Source Platforms: TikTok ads, linked e-commerce domains, review widgets, and transparency archives.
Observation Period: Four weeks.
Ad Corpus: 54 unique ads linking to 32 domains.
Captured Assets: 180 landing pages, 3,000 extracted frames, 100+ review images.
Purchases: Three advertiser domains, one AliExpress dupe, one control (House of CB).
Analysis Methods: multimodal similarity detection (pHash, dHash, audio fingerprints, vision embeddings, NLP), network diffusion metrics, and product inspections.
DOI: 10.17632/2vbk4fcrsz.1
title: Content freebooting

description: This dataset accompanies the study on content freebooting in social media advertising and its exploitation by counterfeit and dupe brands. The dataset captures advertising activity around a case study product (a floral corset sundress) across TikTok and linked e-commerce domains. It integrates ad-level metadata, creator provenance, network diffusion structures, product inspections, fulfillment outcomes, and detection pipeline results. The dataset is designed to support research and teaching in areas such as multimedia forensics, adversarial content manipulation, e-commerce fraud detection, and network diffusion analysis. It is suitable for both computational modeling (e.g., duplicate detection, network clustering) and qualitative case-based learning.

Data Collection and Methodology
Source Platforms: TikTok ads, linked e-commerce domains, review widgets, and transparency archives.
Observation Period: Four weeks.
Ad Corpus: 54 unique ads linking to 32 domains.
Captured Assets: 180 landing pages, 3,000 extracted frames, 100+ review images.
Purchases: Three advertiser domains, one AliExpress dupe, one control (House of CB).
Analysis Methods: multimodal similarity detection (pHash, dHash, audio fingerprints, vision embeddings, NLP), network diffusion metrics, and product inspections.
DOI: 10.13140/rg.2.2.28577.88164
title: The Role of Experience and the Scientific Method in the Learning Process in Secondary Schools in the Municipality of Prishtina, Kosovo