cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.733eh5
title: Occurrence Download

description: A dataset containing 19555 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Neogale Gray, 1865"
 ]
}

 The dataset includes 19555 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001035-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ygtkhh
title: Occurrence Download

description: A dataset containing 123 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Synedrella nodiflora (L.) Gaertn."
 ]
}

 The dataset includes 123 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013596-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/7skswgr2h5.1
title: Gene Expression Analysis of DK210 (EGFR) treatment study in a syngeneic tumor model

description: Transcriptional gene analysis from tumor infiltrating effector memory CD8 T cells in a DK210 (EGFR) study with B16F10 tumor bearing mice
DOI: 10.15468/dl.ejtar5
title: Occurrence Download

description: A dataset containing 5239 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Syrmaticus mikado",
 "Country is Chinese Taipei",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5239 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049099-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15577615
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250602p Initial

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250602p Initial. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15577616
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250602p Initial

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250602p Initial. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.15468/dl.nfpvhk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Epipleoneura susanae",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003020-251120083545085/datasets/export for details.
DOI: 10.25612/837.aye6nm4lxnnr
title: Harris County Parcels 2022

description: Parcel shapefiles from Harris Central Appraisal District (HCAD).
DOI: 10.15468/dl.bwk8y9
title: Occurrence Download

description: A dataset containing 85 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "Geometry POLYGON((3.59348 43.99952,3.53613 43.86548,3.45085 43.69183,3.52586 43.46166,3.72314 43.42365,4.00366 43.56236,3.98825 43.77917,3.88344 43.94358,3.59348 43.99952))",
 "TaxonKey is Euchorthippus chopardi"
 ]
}

 The dataset includes 85 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003021-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25612/837.0m3xjg3egxnz
title: Harris County Parcels (2023)

description: Parcel shapefiles from Harris Central Appraisal District (HCAD).
DOI: 10.6073/pasta/10a1f70ad9418e70bc7907f5ddb5530d
title: Littoral and Pelagic Water Temperatures and Light in Escanaba, McDermott, and Sparkling Lakes, Wisconsin USA 2023-2024

description: This dataset contains high-frequency temperature (°C) and light (lux) measurements from three north-temperate lakes collected during the summers of 2023 and 2024, as well as locations of sensors in each lake. HOBO (HOBO Pendant temp/light®, Onset Brands, MA) sensors recorded at hourly intervals. Measurements were collected at 0.5m and 1m depth in all lakes (McDermott, Escanaba, and Sparkling) and at select 3m sites in Sparkling Lake.
 
 Sampling included pelagic and littoral zones. Each lake contained two pelagic sites instrumented using subsurface buoys. The number of littoral sites varied by lake and year (see Methods). At littoral sites, macrophyte presence or absence was assessed weekly, with presence defined as macrophytes occupying more than 50% of the water column. In Sparkling Lake 3m littoral sites were paired, with sensors placed inside and outside macrophyte beds less than 10m apart.
 
 These data were used to quantify thermal habitat breadth (daily temperature range) and to compare estimates based on (1) pelagic-only measurements and (2) combined pelagic + littoral measurements, allowing evaluation of the littoral zone’s contribution to lake thermal assessments. The dataset also supports analyses of macrophyte effects on thermal habitat in littoral zones. Data collection presented in this data package represents a subset of the larger "Walleye Bright Spots" project data.
DOI: 10.5281/zenodo.17676648
title: A Rigorous Conceptual Framework Linking Self-Rotation to Orbital Stability and Spacetime Curvature in Celestial Bodies: The Role of Frame-Dragging, Geodesic Paths, and Low-Pressure Spacetime Environments

description: This rigorous conceptual paper advances a novel theoretical framework asserting that the self-rotation (spin) of celestial bodies, including planets and stars, plays a critical role in sustaining their orbital paths through the generation of spacetime curvature via frame-dragging effects, as predicted by general relativity. We postulate that the cessation of self-rotation could destabilize these paths, potentially transforming stable orbiting bodies into rogue, free-floating entities. Grounded in the principles of general relativity, this framework integrates the geodesic equations, Kerr metrics, and gravitomagnetic phenomena to model the interplay between spin and orbital dynamics. The analysis is bolstered by precise mathematical derivations, Python-based numerical simulations incorporating verified observational data from missions such as Gravity Probe B and recent rogue planet surveys by JWST and Euclid, advanced sensitivity and uncertainty analyses employing Bayesian inference and quantitative statistics, and explicit falsifiability criteria. High-fidelity TikZ visualizations depict spacetime curvature, geodesic trajectories, and simulation outputs. Additionally, we explore the implications of planetary rotation on habitability, including magnetic field generation, atmospheric circulation, and climate stability. This multidisciplinary integration—spanning general relativity, astrophysics, computational physics, statistical modeling, and astrobiology—provides a deep, multidimensional, and empirically substantiated perspective on orbital stability and planetary habitability, challenging conventional views and offering testable predictions for future observations.
DOI: 10.15468/dl.9hscmk
title: Occurrence Download

description: A dataset containing 11201624 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Peru",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 11201624 records from 2865 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003016-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jc469m
title: Occurrence Download

description: A dataset containing 241 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Shorea robusta Gaertn.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 241 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009429-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hwmpww97rs.1
title: A deep learning mobile-based image analysis for cervical cancer detection

description: This dataset provides a structured environment for cervical cancer image analysis using machine learning and deep learning. It includes four main experiments:

Risk factor prediction using classical ML models

ROI segmentation using U-Net

Lesion detection using Detectron2

Binary classification of images and Kappa evaluation

The experiments are implemented in Jupyter notebooks. All datasets are reduced 10% samples. The images used are publicly available from the Intel MobileODT dataset. Originally, the project included a private dataset (CAIME), but for privacy reasons, those images were removed and replaced with public samples. Both Intel/ and test/ folders now contain only public data. Segmentation masks (.tif) were also included where filenames matched.

This environment was originally executed in a Docker container with GPU support (NVIDIA QUADRO), but the reduced version can be tested on CPU.
DOI: 10.15468/dl.n5ea8j
title: Occurrence Download

description: A dataset containing 1109320 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium, Germany, Netherlands)",
 "TaxonKey is one of (Ondatra zibethicus, Myocastor coypus)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1109320 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029681-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n8c3jz
title: Occurrence Download

description: A dataset containing 999794 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Plantago amplexicaulis, Plantago argyrea, Sebaea laxa, Gypsophila festucifolia, Gypsophila lurorum, Gypsophila parva, Gypsophila pilosa, Gypsophila pinifolia, Gypsophila silenoides, Actinolema eryngioides, Gilia malior, Wurmbea drummondii, Eriospermum papilliferum, Eriospermum undulatum, Duvalia gracilis, Duvalia pillansii, Calliandra estebanensis, Rumex cordatus, Limonium pseudarticulatum, Limonium battandieri, Limonium merxmuelleri, Limonium pinillense, Limonium pachynense, Limonium gorgonae, Limonium lambinonii, Limonium lobetanicum, Limonium formosum, Plantago dardanae, Hoplophyllum ferox, Pulicaria alveolosa, Gilia ophthalmoides, Ocimum obovatum, Bonamia pilbarensis, Neuontobotrys elloanensis, Rumex suffruticosus, Rumex ogulinensis, Rumex monistrolensis, Rumex tmoleus, Trachymene coerulea, Limonium xerocamposicum, Limonium kirikosicum, Clutia katharinae, Genoplesium citriodorum, Eriospermum appendiculatum, Eriospermum attenuatum, Eriospermum exigium, Triteleia piutensis, Anacampseros affinis, Nototriche pulverulenta, Gleichenia mendellii, Xerochrysum copelandii, Limonium anatolicum, Sebaea amicorum, Gypsophila nana, Isoetes perralderiana, Limonium ginzbergeri, Struthanthus palmeri, Hesperevax caulescens, Ixianthes retzioides, Eriospermum lanuginosum, Oreocarya confertiflora, Sebaea solaris, Chaenactis kyhosii, Rumex dregeanus, Rumex acetosa, Rumex weberi, Sambucus mexicana, Limonium vigoi, Limonium zacynthium, Psoralea keetii, Platymiscium trifoliolatum, Plantago peloritana, Plantago glacialis, Anacampseros prominens, Lactuca aculeata, Lactuca kochiana, Psilocarphus oregonus, Gilia laciniata, Pulicaria paludosa, Bonamia erecta, Pterocephalus bellidifolius, Limonium astypaleanum, Rumex sanninensis, Rumex pictus, Trachymene thysanocarpa, Staavia zeyheri, Plantago cunninghamii, Brunia compacta, Isoetes echinospora, Clutia abyssinica, Clutia natalensis, Eriospermum cervicorne, Duperreya halfordii, Anacampseros scopata, Isoetes aequinoctialis, Spergularia quartzicola, Limonium clupeanum, Limonium cornarianum, Limonium ampuriense, Limonium algusae)",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 999794 records from 3302 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029683-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kaz26e
title: Occurrence Download

description: A dataset containing 1037 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gongolaria abies-marina (S.G.Gmelin) Kuntze"
 ]
}

 The dataset includes 1037 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012931-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/jz3z-ha13
title: Maryland BOEM M14AC00018 Raw Audio Data
DOI: 10.15468/dl.xhh85b
title: Occurrence Download

description: A dataset containing 572 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((117.974 5.764142, 117.903383 5.758572, 117.834509 5.741997, 117.769077 5.714827, 117.708701 5.677733, 117.654869 5.63163, 117.608908 5.577654, 117.571948 5.517137, 117.544898 5.45157, 117.528421 5.38257, 117.522918 5.311835, 117.528522 5.241109, 117.545091 5.172131, 117.572214 5.1066, 117.609221 5.046128, 117.655198 4.992202, 117.709013 4.946149, 117.769343 4.909099, 117.834702 4.881966, 117.903485 4.865414, 117.974 4.859851, 118.044515 4.865414, 118.113298 4.881966, 118.178657 4.909099, 118.238987 4.946149, 118.292802 4.992202, 118.338779 5.046128, 118.375786 5.1066, 118.402909 5.172131, 118.419478 5.241109, 118.425082 5.311835, 118.419579 5.38257, 118.403102 5.45157, 118.376052 5.517137, 118.339092 5.577654, 118.293131 5.63163, 118.239299 5.677733, 118.178923 5.714827, 118.113491 5.741997, 118.044617 5.758572, 117.974 5.764142))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 572 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002134-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.352qft
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Geometry POLYGON((73 34,96.4 34,96.4 43.35,73 43.35,73 34))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Haloxylon ammodendron",
 "Year 1970-2019"
 ]
}

 The dataset includes 33 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002135-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/4ghsnx3gpv
title: Digital transformation and earnings downside risk

description: This dataset comprises Shanghai and Shenzhen A-share listed firms from 2015 to 2024. Data on digital transformation are hand-collected from firms’ annual reports, ESG ratings are obtained from Huazheng ESG Ratings, and financial and market data are sourced from the China Stock Market & Accounting Research (CSMAR) Database. Following standard data cleaning procedures, we exclude firms designated as ST or *ST and those in the financial industry, and winsorize all continuous variables at the 1% and 99% levels. The final sample comprises 15,150 firm-year observations.
DOI: 10.17632/4ghsnx3gpv.1
title: Digital transformation and earnings downside risk

description: This dataset comprises Shanghai and Shenzhen A-share listed firms from 2015 to 2024. Data on digital transformation are hand-collected from firms’ annual reports, ESG ratings are obtained from Huazheng ESG Ratings, and financial and market data are sourced from the China Stock Market & Accounting Research (CSMAR) Database. Following standard data cleaning procedures, we exclude firms designated as ST or *ST and those in the financial industry, and winsorize all continuous variables at the 1% and 99% levels. The final sample comprises 15,150 firm-year observations.
DOI: 10.17632/3fz9434bdd
title: Does short selling of customers affect analysts' forecasts for suppliers?

description: This dataset presents the empirical analysis materials from the paper "Does short selling of customers affect analysts' forecasts for suppliers?"
DOI: 10.17632/3fz9434bdd.2
title: Does short selling of customers affect analysts' forecasts for suppliers?

description: This dataset presents the empirical analysis materials from the paper "Does short selling of customers affect analysts' forecasts for suppliers?"
DOI: 10.17632/jz8kfcgdvn
title: Sensor Fusion Data

description: The data contains raw IMU readings, filtered IMU readings, and real-time IMU and GPS readings.
DOI: 10.17632/jz8kfcgdvn.1
title: Sensor Fusion Data

description: The data contains raw IMU readings, filtered IMU readings, and real-time IMU and GPS readings.
DOI: 10.17632/dg9jxk9w8h
title: Dataset for: "Ocean acidification impacts on oxidative stress, immune response, and growth in bivalves: a meta-analysis"

description: This dataset contains the complete compiled data and calculated effect sizes used to generate the forest plots and conduct the meta-analysis presented in the manuscript entitled "Ocean Acidification Impairs Bivalve Physiology: Meta-Analytic Evidence of Oxidative Stress, Immune Suppression, and Growth Reduction".
DOI: 10.34808/s7e8-j376
title: Raw files from digital image correlation analysis of total shrinkage of 3D-printed concrete mixture with magnetite aggregate. Part 4/4

description: Raw image files recorded by the ARAMIS digital image correlation system for 3D-printed concrete mixture with megnetite aggregate (M20M). The files were used for displacement and strain analysis. Sample designation in the files is consistent with the sample designation used in the manuscript associated with the dataset. Part 4/4
M0 - reference sampleM20B - 20% of aggregate replaced with brick aggregateM20M - 20% of aggregate replaced with magnetite aggregate
DOI: 10.17632/dg9jxk9w8h.1
title: Dataset for: "Ocean acidification impacts on oxidative stress, immune response, and growth in bivalves: a meta-analysis"

description: This dataset contains the complete compiled data and calculated effect sizes used to generate the forest plots and conduct the meta-analysis presented in the manuscript entitled "Ocean Acidification Impairs Bivalve Physiology: Meta-Analytic Evidence of Oxidative Stress, Immune Suppression, and Growth Reduction".
DOI: 10.17632/wppb4v39dp
title: Mapping the Landscape of Artificial Intelligence in Biology Education: Trends, Challenges, and Pedagogical Opportunities from a Systematic Literature Review

description: AI for Biology Education
DOI: 10.5281/zenodo.18324421
title: Comparison Of Diadochokinetic Rate Measures In Individuals With Post-Stroke Spastic And Unilateral Upper Motor Neuron Dysarthria

description: De-identified Excel data supporting the findings of this study are available in an open repository. The dataset includes participant-level diadochokinetic (DDK) rate measures (syllables/second) for alternating (/pʌ/, /tʌ/, /kʌ/) and sequential (/pʌtʌkʌ/) tasks, along with basic demographic and clinical grouping variables required to reproduce the reported analyses (healthy vs. dysarthria; SD, right UUMND, left UUMND). To protect participant privacy, the repository does not include raw audio recordings or any direct identifiers; audio files contain personal speech content and are therefore not shared. The repository record provides the permanent link/DOI and file-level metadata needed for reuse.
DOI: 10.17632/wppb4v39dp.1
title: Mapping the Landscape of Artificial Intelligence in Biology Education: Trends, Challenges, and Pedagogical Opportunities from a Systematic Literature Review

description: AI for Biology Education
DOI: 10.5281/zenodo.18323661
title: peer review
DOI: 10.17632/x9nynx5dt8
title: Data and code supporting "Market Professional Performance under Insider Information Leakage"

description: This dataset contains all the necessary files to replicate the findings, tables, and figures presented in the manuscript “Market Professional Performance under Insider Information Leakage.”
1. Data File (dataset.dta): The final, cleaned panel dataset used for all analyses in the study.
Source: The raw data were originally obtained from the CSMAR (China Stock Market & Accounting Research Database) and RESSET databases. This file contains the processed and merged variables as described in the manuscript.

2. Analysis Script (empirical_analysis.do): A Stata *.do file that executes the main econometric analyses and generates the results reported in the manuscript (e.g., regression tables).

3. Visualization Scripts (generate_Figure_1.py): Python scripts used to generate all figures presented in the manuscript.
DOI: 10.17632/x9nynx5dt8.2
title: Data and code supporting "Market Professional Performance under Insider Information Leakage"

description: This dataset contains all the necessary files to replicate the findings, tables, and figures presented in the manuscript “Market Professional Performance under Insider Information Leakage.”
1. Data File (dataset.dta): The final, cleaned panel dataset used for all analyses in the study.
Source: The raw data were originally obtained from the CSMAR (China Stock Market & Accounting Research Database) and RESSET databases. This file contains the processed and merged variables as described in the manuscript.

2. Analysis Script (empirical_analysis.do): A Stata *.do file that executes the main econometric analyses and generates the results reported in the manuscript (e.g., regression tables).

3. Visualization Scripts (generate_Figure_1.py): Python scripts used to generate all figures presented in the manuscript.