cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30218914.v1
title: EED-Astig

description: We collected data from 640 children aged 3-6 years who underwent routine vision examinations at the outpatient department of Peking University First Hospital between January 1 and June 30, 2025. We present EED-Astig, a new multimodal pediatric dataset for AI-based astigmatism severity prediction.The dataset is released as a single compressed file named `EED-Astig.zip`, which, upon extraction, reveals two main directories: **Images** and **Annotations**, along with an additional file **Parameter.xls**, each containing 3088 files. The Images folder stores all periocular photographs in JPEG format (.jpg), named according to the convention `[group_index].[view_index].jpg`, where `group_index` identifies the subject group and `view_index` (ranging from 1 to 5) specifies the capture perspective—1 for frontal view of both eyes, 2 and 3 for frontal views of the right and left eye respectively, and 4 and 5 for side views of the right and left eye. The Annotations folder contains a corresponding JSON file for every image, sharing the same filename, with annotation content varying by view type: frontal-view images (.1, .2, .3) are annotated with keypoint coordinates (e.g., canthi, lower eyelid points) and corneal segmentation masks, while side-view images (.4, .5) contain keypoints marking the start and end of the eyelash line, all meticulously labeled by professional ophthalmologists and rigorously verified to ensure high data quality and accuracy. The Parameter.xls file provides demographic and clinical metadata, including gender, height, screen time, and birth history, for each subject group, enabling comprehensive supervised learning for astigmatism severity assessment.
DOI: 10.15468/dl.59yw93
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019992-250920141307145/datasets/export for details.
DOI: 10.15468/dl.d9r53u
title: Occurrence Download

description: A dataset containing 2200 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ceiba pentandra"
 ]
}

 The dataset includes 2200 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019990-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26207/df8d-s391
title: Data for "Active Dual-Gated Graphene Transistors for Low-Noise, Drift-Stable, and Tunable Chemical Sensing"

description: Graphene field-effect transistors (GFETs) are among the most promising platforms for ultrasensitive chemical and biological sensing due to their high carrier mobility, large surface area, and low intrinsic noise. However, conventional single-gate GFET sensors in liquid environments suffer from severe limitations, including signal drift, charge trapping, and insufficient signal amplification. Here, we introduce a dual-gate GFET architecture that integrates a high-k hafnium dioxide local back gate with an electrolyte top gate, coupled with real-time feedback biasing. This design enables capacitive signal amplification while simultaneously suppressing gate leakage and low-frequency noise. By systematically evaluating seven distinct operational modes, we identify the Dual Mode Fixed configuration as optimal, achieving up to 20x signal gain, > 15x lower drift compared with gate-swept methods, and up to 7x higher signal to noise ratio across a diverse range of analytes, including neurotransmitters, volatile organic compounds, environmental contaminants, and proteins. We further demonstrate robust, multiplexed detection using a PCB-integrated GFET sensor array, underscoring the scalability and practicality of the platform for portable, high-throughput sensing in complex environments. Together, these advances establish a versatile and stable sensing technology capable of real-time, label-free detection of molecular targets under ambient and physiological conditions, with broad applicability in health monitoring, food safety, agriculture, and environmental screening.
DOI: 10.15468/dl.a65s94
title: Occurrence Download

description: A dataset containing 986 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Protopterus annectens"
 ]
}

 The dataset includes 986 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019993-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5285/3f24651e-2d44-dee3-e063-7086abc0395e
title: Atlantic meridional overturning circulation observed by the RAPID-MOCHA-WBTS (RAPID-Meridional Overturning Circulation and Heatflux Array-Western Boundary Time Series) array at 26N from 2004 to 2024 (v2024.1).

description: The RAPID-MOCHA-WBTS (RAPID-Meridional Overturning Circulation and Heatflux Array-Western Boundary Time Series) programme has produced a continuous time series of the Atlantic Meridional Overturning Circulation (AMOC) at 26N that started in April 2004. This release of the time series covers the period from April 2004 to March 2024. The 26N AMOC time series is derived from measurements of temperature, salinity, pressure and water velocity from an array of moored instruments that extend from the east coast of the Bahamas to the continental shelf off Africa east of the Canary Islands. The AMOC calculation also uses estimates of the transport in the Florida Strait derived from sub-sea cable measurements calibrated by regular hydrographic cruises. The component of the AMOC associated with the wind driven Ekman layer is derived from ERA5 reanalysis. This release of the data includes a document with a brief description of the calculation of the AMOC time series and references to more detailed description in published papers. The 26N AMOC time series and the data from the moored array are curated by the British Oceanographic Data Centre (BODC). The RAPID-MOCHA-WBTS programme is a joint effort between NERC in the UK (Principle Investigator Ben Moat since 2021, Eleanor Frajka-Williams from 2020 to 2021, David Smeed from 2012 to 2020, and Stuart Cunningham from 2004 to 2012), NOAA (PIs Ryan Smith and Denis Volkov) and NSF (PIs Prof. Bill Johns and Prof. Shane Elipot, Uni. Miami) in the USA.
DOI: 10.15468/dl.4xevc5
title: Occurrence Download

description: A dataset containing 26761 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anura",
 "GadmGid is IDN",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Occurrence evidence)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 26761 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019988-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17864/1947.001453
title: Dataset supporting the article 'Core-level binding energies describe electrostatic potentials at nuclei for ionic liquids'

description: This compressed file is supplementary to the article cited in the 'Related publication' section found in the README file. Its contents include the input and (some) output files of the ionic liquid [C8C1Im][TfO] studied here computationally. These computational files will allow you to replicate both the Ab Initio Molecular Dynamics (MD) (calculated using CP2K) and the Density Functional Theory (DFT) (calculated using VASP) calculations shown in the article. All XPS experimental data is previously published (as referenced in CONTENTS) and the data for the three other ILs studied computationally is already published as follows: F. K. Towers Tompkins, R. Grau-Crespo and K. R. J. Lovelock, 2024: Dataset supporting the article
'Anion-dependent strength scale of interactions in ionic liquids from x-ray photoelectron spectroscopy, ab initio molecular dynamics, and density functional theory'. University of Reading. Dataset. https://doi.org/10.17864/1947.001317
DOI: 10.21954/ou.rd.30166825
title: Strengthening assessment integrity in the era of generative AI: evidence from a large-scale study

description: The advent of ChatGPT in November 2022 immediately rang alarm bells about the integrity of academic assessment, especially in distance learning. The challenge of detecting generative AI (GenAI) misuse has led some educators to advocate a reversion to in-person exams, proctoring and viva voces, even though these may undermine inclusion; others see a solution in assessment redesign. This large-scale empirical study at a UK university, based on 590 student and 354 AI-generated answers, provides evidence on markers’ ability to detect the GenAI scripts and whether some assessment types are more robust than others against GenAI misuse. Seventeen different assessment types were tested, using 59 example questions spanning 17 disciplines at FHEQ levels 3 to 6. Synthesising quantitative and qualitative analysis, the research found that training improved markers’ ability to detect GenAI answers but also increased false positives. This reinforces the case instead for assessment redesign and the research found that some assessment types were more robust against GenAI, particularly those that rely on higher level skills, align with ‘authentic’ assessment, require application of course materials and are supported by clear and rigorously-applied marking rubrics. The findings suggest evidence-based practical ways to redesign assessment for the GenAI era.
DOI: 10.21954/ou.rd.30166825.v1
title: Strengthening assessment integrity in the era of generative AI: evidence from a large-scale study

description: The advent of ChatGPT in November 2022 immediately rang alarm bells about the integrity of academic assessment, especially in distance learning. The challenge of detecting generative AI (GenAI) misuse has led some educators to advocate a reversion to in-person exams, proctoring and viva voces, even though these may undermine inclusion; others see a solution in assessment redesign. This large-scale empirical study at a UK university, based on 590 student and 354 AI-generated answers, provides evidence on markers’ ability to detect the GenAI scripts and whether some assessment types are more robust than others against GenAI misuse. Seventeen different assessment types were tested, using 59 example questions spanning 17 disciplines at FHEQ levels 3 to 6. Synthesising quantitative and qualitative analysis, the research found that training improved markers’ ability to detect GenAI answers but also increased false positives. This reinforces the case instead for assessment redesign and the research found that some assessment types were more robust against GenAI, particularly those that rely on higher level skills, align with ‘authentic’ assessment, require application of course materials and are supported by clear and rigorously-applied marking rubrics. The findings suggest evidence-based practical ways to redesign assessment for the GenAI era.
DOI: 10.15468/dl.5tgtvn
title: Occurrence Download

description: A dataset containing 313 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Habenaria jaliscana"
 ]
}

 The dataset includes 313 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019994-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.34596.54406
title: XRD Patterns of TiO2 NPs and S. Trilobata leaves
DOI: 10.15468/dl.dg2qxj
title: Occurrence Download

description: A dataset containing 81923 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "StateProvince is Massachusetts",
 "TaxonKey is Asteraceae"
 ]
}

 The dataset includes 81923 records from 187 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019875-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xub2h6
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Archachatina marginata)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 129 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019995-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3esrjw
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Archachatina marginata)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 129 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019996-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2pchnq
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lycium barbarum",
 "Country is Moldova, Republic of",
 "HasCoordinate is true"
 ]
}

 The dataset includes 19 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019998-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-08.2867004/2428806
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866765/2428807
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2867003/2428808
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866732/2428809
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866733/2428810
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866597/2428811
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866996/2428812
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866892/2428813
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866982/2428814
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866887/2428815
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866644/2428816
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866510/2428817
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866692/2428818
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866829/2428819
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866614/2428820
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866689/2428821
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866834/2428822
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866936/2428823
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866860/2428824
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866931/2428825
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866754/2428826
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866843/2428827
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866561/2428828
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866570/2428829
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866637/2428830
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866893/2428831
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866757/2428832
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866685/2428833
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866674/2428834
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866574/2428835
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866696/2428836
title: Data for EMSL Project 51287 from August 2023
DOI: 10.15468/dl.96ybpm
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((142.862803 -37.276304, 142.862803 -37.283041, 142.871786 -37.283041, 142.871786 -37.27855, 142.876277 -37.27855, 142.876277 -37.276304, 142.862803 -37.276304))"
 ]
}

 The dataset includes 110 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063370-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-08.2866805/2428837
title: Data for EMSL Project 51287 from August 2023
DOI: 10.15468/dl.s7ehc2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.604691 -32.162619, 149.604691 -32.167111, 149.602445 -32.167111, 149.602445 -32.169357, 149.606937 -32.169357, 149.606937 -32.162619, 149.604691 -32.162619))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063371-240626123714530/datasets/export for details.
DOI: 10.25582/data.2023-08.2866816/2428838
title: Data for EMSL Project 51287 from August 2023
DOI: 10.25582/data.2023-08.2866856/2428839
title: Data for EMSL Project 51287 from August 2023
DOI: 10.14457/tu.the.2023.357
title: Identification of genes involved in spikelet fertility in rice using RNA sequencing

description: The identification of genes controlling spikelet fertility is directly important for the yield and quality of rice. This study developed two groups of genetically stable Recombinant Inbred Lines (RILs) with significantly different seed set rates. One group had a high seed set rate (≥ 70%) and the other had a low seed set rate (≤ 25%). These populations were created by crossing the Japanese rice variety Nipponbare with the Thai rice variety Khao Dawk Mali 105. To identify genes, the study examined the stages and tissues affecting the different seed set rates in the two groups. In the F5 generation, the populations with different seed set rates still had complete pollen but varied significantly in seed set rates. The study further observed differences in pollen adhesion and pollen tube growth abnormalities in the low seed set population 4-5 hours after pollination. Samples were collected, and RNA sequencing was conducted at this stage in the F6 generation. Analysis of the differentially expressed genes (DEGs) between the high and low seed set populations identified 249 DEGs in the high seed set group, with 118 up-regulated and 131 down-regulated genes. The low seed set group had 473 DEGs, with 214 up-regulated and 259 down-regulated genes. Validation of 10 DEGs using qRT-PCR showed consistent results with the RNA sequencing data. GO ontology analysis of DEGs in the high seed set group identified 18 GO terms, while the low seed set group had 16 GO terms. KEGG pathway analysis revealed that 11 DEGs in the high seed set group were involved in metabolic pathways, whereas 6 DEGs in the low seed set group were related to pentose and glucuronate interconversions and flavonoid biosynthesis pathways. Further study of DEGs interaction with other genes involved in pollen development, using rice databases, found several interactions, including some previously reported genes related to spikelet fertility. This study discovered new genes and gene functions associated with spikelet fertility, such as Os02g0467600 (cinnamate 4-hydroxylase, CYP73), which is involved in flavonoid synthesis and is expressed more in the high seed set group post-pollination. Additionally, OsPME35 and OsPLL9, which control pectin methylesterase (PME) and pectate lyase (PLL) respectively, showed higher expression in the ovary before pollination in the high seed set group compared to the low seed set group. This indicates their necessity for cell wall formation of the pistil during the interaction between pistil and pollen. The DEGs identified were also located near QTLs related to pollen tube growth and yield components, as previously reported. These findings are valuable as they provide new knowledge about the genetic control of spikelet fertility and can be utilized for developing high-yield rice varieties.