cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.4dddz7
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oreochromis niloticus (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.5808 -24.13,35.5909 -24.0715,30.5701 -24.0715,30.5701 -28.5786,32.4847 -28.5786,32.55 -28.5222,33.0346 -26.8668,32.9741 -26.7838,33.0415 -26.059,32.9304 -26.0011,32.7994 -26.1281,32.6834 -26.0015,32.813 -25.8728,32.8513 -25.7166,33.3048 -25.3731,35.1489 -24.6699,35.5808 -24.13))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021759-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fds6f4
title: Occurrence Download

description: A dataset containing 65 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 Cinnamomum mairei H.Lév."
 ]
}

 The dataset includes 65 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021760-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/3bhvnsc8bg.1
title: A ketogenic diet mitigates hippocampal astrogliosis in epileptic brain
DOI: 10.17632/pxvtgd82dn
title: Dataset on the analysis of β-galactosidase immobilization efficiency on AMP resin in syringe and column reactors

description: Raw data to on AMP resin covalently immobilized β-Galactosidase using a PDC linker and the determination of enzyme activity. Resin loading was determined by measuring the protein concentration difference between the original lactase solution and the reactor supernatant using a Bradford assay. Enzyme activity of the supernatants was assessed with ONPG as the substrate, and lactose turnover rates were measured using a lactose solution. The dataset provides detailed results for five different approaches with several syringe reactors and two column reactors, enabling comparison of immobilization efficiency and catalytic performance. The dataset may be valuable for industrial applications where stable and efficient immobilized β-galactosidase systems are required, such as lactose-free dairy production.
DOI: 10.17632/pxvtgd82dn.1
title: Dataset on the analysis of β-galactosidase immobilization efficiency on AMP resin in syringe and column reactors

description: Raw data to on AMP resin covalently immobilized β-Galactosidase using a PDC linker and the determination of enzyme activity. Resin loading was determined by measuring the protein concentration difference between the original lactase solution and the reactor supernatant using a Bradford assay. Enzyme activity of the supernatants was assessed with ONPG as the substrate, and lactose turnover rates were measured using a lactose solution. The dataset provides detailed results for five different approaches with several syringe reactors and two column reactors, enabling comparison of immobilization efficiency and catalytic performance. The dataset may be valuable for industrial applications where stable and efficient immobilized β-galactosidase systems are required, such as lactose-free dairy production.
DOI: 10.17632/4f9ptj34nb
title: Dataset for Understanding Accessibility Needs CMS for Blind Users Authors

description: The accompanying dataset provides full transparency and reproducibility of the research presented in the article Understanding Accessibility Needs CMS for Blind Users Authors.
DOI: 10.17632/4f9ptj34nb.3
title: Dataset for Understanding Accessibility Needs CMS for Blind Users Authors

description: The accompanying dataset provides full transparency and reproducibility of the research presented in the article Understanding Accessibility Needs CMS for Blind Users Authors.
DOI: 10.17632/tkkhfj6htf
title: Neurologists’ Readiness for the Updated McDonald’s Criteria in Egypt

description: This excel file contains 16-item questionnaire that assesses neurologists' perspectives on the newly proposed updates to the multiple sclerosis (MS) diagnostic criteria.
DOI: 10.17632/tkkhfj6htf.1
title: Neurologists’ Readiness for the Updated McDonald’s Criteria in Egypt

description: This excel file contains 16-item questionnaire that assesses neurologists' perspectives on the newly proposed updates to the multiple sclerosis (MS) diagnostic criteria.
DOI: 10.15468/dl.wrqdtx
title: Occurrence Download

description: A dataset containing 12010 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Solenopsis geminata",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 12010 records from 87 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026649-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/zg99bnvk3c.1
title: Junior & Collegiate Tennis Ratings & Results

description: The included datasets contain match-level (singles) observations from the 2024 Boys’ 16 & 18 USTA National Indoor Championships, the 2024 Boys’ 16 & 18 USTA National Winter Championships, and the 2024 ITA Men’s All-American Championships. The two boys' tournaments are stored in the Junior_Tennis.csv file, and the observations of the collegiate matches are stored in the College_Tennis.csv file.

Columns included in the datasets contain player names (anonymized for the boys' matches), an indicator of the match outcome (equals 1 if Player 1 won, 0 if Player 1 lost, and RET if Player 1 had to retire from the match), and the two players' WTN (World Tennis Number) and UTR (Ultimate Tennis Rating) ratings going into the observed match. Whether a player appears as Player 1 or Player 2 in the observed match was the result of randomization. There are also columns (Player1Comp and Player2Comp) that have "inverted" the WTN ratings (subtracted them from 40) such that higher values are indicative of a better (stronger) rating.

UTRs were collected from the UTR website (https://app.utrsports.net/home). WTNs were collected directly from the public draw sheets when available; otherwise, WTNs were collected from the WTN website (https://worldtennisnumber.com/eng/player-search/). Match results were collected from the public draw sheets available through the USTA (https://playtennis.usta.com/Competitions/xs-tennis-inc/Tournaments/) and ITA (https://colleges.wearecollegetennis.com/Competitions/ITA/Tournaments/) websites.
DOI: 10.17632/f42hwwrpgn
title: Leaf on Stem Image Dataset Beans (LSID-Beans)

description: The dataset is composed of 6981 images of 612 common bean leaves (Phaseolus vulgaris). Each image contains a leaf accompanied by a fiducial marker. The resolution of the images is 512 x 512 pixels. The dataset provide annotations of the known leaf dimensions (area, perimeter, length, and width), image segmentation, known area uniformly distributed over the leaf region, real area of the marker region, marker pose, capture conditions, and camera calibration. This dataset can be useful for developing deep learning algorithms for leaf dimensioning and related problems. Therefore, there is a potential to contribute to computer vision and plant physiology researchers and specialists.
DOI: 10.17632/f42hwwrpgn.3
title: Leaf on Stem Image Dataset Beans (LSID-Beans)

description: The dataset is composed of 6981 images of 612 common bean leaves (Phaseolus vulgaris). Each image contains a leaf accompanied by a fiducial marker. The resolution of the images is 512 x 512 pixels. The dataset provide annotations of the known leaf dimensions (area, perimeter, length, and width), image segmentation, known area uniformly distributed over the leaf region, real area of the marker region, marker pose, capture conditions, and camera calibration. This dataset can be useful for developing deep learning algorithms for leaf dimensioning and related problems. Therefore, there is a potential to contribute to computer vision and plant physiology researchers and specialists.
DOI: 10.17632/zfrs99j8z6.1
title: Early Detection of Infant Common Illnesses (0–3 Years): Symptom-Based Dataset from Bangladesh

description: The data consists of 2,553 responses obtained through a survey from the parents and primary caregivers of the children under the age of three in Bangladesh. It provides detailed demographic information (like age and gender), symptom reports (including respiratory problems, diarrhea, fever, skin rashes, and ear infections), the concerns of caregivers and final names of illnesses. The survey was also designed to capture early markers of frequent infant illnesses, and to reflect observations made in real-world care.

The dataset aims to advance studies on early detection, monitoring and management of common childhood illness. It is a base for public health research, pediatric health studies and decision support systems both for parents and HCP. Moreover, it can be applied to machine learning purposes, such as symptom-based illness prediction and pattern analysis for the pediatric health records. Based on the provision of trustworthy and well-organized information, this dataset hopes to help in the timely diagnosis, intervention, and care of children outcomes in Bangladesh.
Keywords: Infant health; childhood illnesses; symptom dataset; healthcare dataset; machine learning; ARI; diarrhea; fever; Bangladesh
DOI: 10.17632/6szsnpypdd
title: Orange Fruit Diseases Dataset

description: The dataset contains dominant diseases affecting oranges such as Blacks spot, Canker, Greening, Scab and a Healthy one. The dataset can be used for any artificial intelligence project and any agricultural research for precision Agriculture. This dataset was carefully curated from https://data.mendeley.com/datasets/3f83gxmv57/1 and https://www.kaggle.com/datasets/jonathansilva2020/orange-diseases-dataset repository respectively for the purpose of research works in computer vision. To enhance robustness and generalizability, we gathered these datasets from both repos. This approach allowed us to include images with varying lighting conditions and qualities, thus strengthening the model’s validity across diverse real-world scenarios.
DOI: 10.17632/6szsnpypdd.1
title: Orange Fruit Diseases Dataset

description: The dataset contains dominant diseases affecting oranges such as Blacks spot, Canker, Greening, Scab and a Healthy one. The dataset can be used for any artificial intelligence project and any agricultural research for precision Agriculture. This dataset was carefully curated from https://data.mendeley.com/datasets/3f83gxmv57/1 and https://www.kaggle.com/datasets/jonathansilva2020/orange-diseases-dataset repository respectively for the purpose of research works in computer vision. To enhance robustness and generalizability, we gathered these datasets from both repos. This approach allowed us to include images with varying lighting conditions and qualities, thus strengthening the model’s validity across diverse real-world scenarios.
DOI: 10.17632/dwky3hnt6j.2
title: Raw data and MATLAB codes for Xu et al., 2025, GRL

description: This dataset includes the raw data, the compilation of published data, and the MATLAB codes of the Monte Carlo model used in Xu et al., 2025, GRL.
DOI: 10.15468/dl.su9rab
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026652-250811113504898/datasets/export for details.
DOI: 10.17632/5bnrnhccfs
title: Ong onychomycosis

description: Supplemental for Ong et al. Clinical variations in onychomycosis across Fitzpatrick phototypes: a retrospective cohort study
DOI: 10.17632/5bnrnhccfs.1
title: Ong onychomycosis

description: Supplemental for Ong et al. Clinical variations in onychomycosis across Fitzpatrick phototypes: a retrospective cohort study
DOI: 10.15468/dl.mjumc7
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra hircus",
 "Country is Iraq",
 "HasCoordinate is true"
 ]
}

 The dataset includes 28 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026650-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/ctbrfc3wx4.2
title: Bioactivities of Polyphenols, Polysaccharides, and Oligosaccharides Derived from Two Wild West African Ganoderma Species

description: This dataset has been updated to include only raw experimental data. Final tables and figures are available in related article.
This dataset contains the raw experimental data associated with the above manuscript. Data are organized in a single excel file (Ganoderma species RawData.xlsx) with the following sheets:
1. Yield of Extracts – Raw weight and percentage yields of extracts obtained from Ganoderma enigmaticum and G. mbrekobenum (3 replicates)
2. Extract Types and Concentrations- List of extract types/fractions (Polyphenols, polysaccharides and oligosaccharides, showing their total phenolic and carbohydrate contents (3 replicates)
3. Antioxidant Activity- Percentage Inhibition of Different Concentrations of the extracts (25-100 µg/ml) (3 replicates)
4. Antibacterial activity showing percentage inhibition values and replicates data, mean and SD of Escherichia coli and Staphylococcus aureus
5. Anticancer activity – Percentage inhibition of cancer cell lines proliferation (HepG2, HCT116 and MDA-MB231 model cell lines) from XTT assay with replicates, mean and SD values
6. Sequences for Phylogenetic Analysis- Details of taxon, voucher number, Country of origin and GenBank Accession numbers of sequences downloaded from the GenBank used for phylogenetic analysis, including sequences used in the study and submitted to the NCBI data repository.
File Formats
• Ganoderma species RawData.xlsx (primary dataset, raw experimental values)
 How to Use
• Open excel file and navigate between sheets for different data categories
• Data are unprocessed, except for basic calculations (means and standard deviations)
DOI: 10.15468/dl.7n7kmh
title: Occurrence Download

description: A dataset containing 268 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capra hircus",
 "Country is Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 268 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026651-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/m77yzby64n
title: Experimental data set of a pneumatic levitator, PWM vs. level

description: The dataset used to train the GRU model was collected from the pneumatic levitation system under controlled experimental conditions. The data acquisition process involved applying a pseudo-random binary sequence (PRBS) to the fan's PWM control signal, which excited the system and generated observable variations in the levitated object's height. The dataset consists of 8,912 samples, recorded at a frequency of 10 Hz, spanning approximately 15 minutes of continuous operation.
Each sample includes two key variables: the PWM control signal (ranging from 0 to 255) and the corresponding height of the levitated object (measured in centimeters).
DOI: 10.17632/m77yzby64n.1
title: Experimental data set of a pneumatic levitator, PWM vs. level

description: The dataset used to train the GRU model was collected from the pneumatic levitation system under controlled experimental conditions. The data acquisition process involved applying a pseudo-random binary sequence (PRBS) to the fan's PWM control signal, which excited the system and generated observable variations in the levitated object's height. The dataset consists of 8,912 samples, recorded at a frequency of 10 Hz, spanning approximately 15 minutes of continuous operation.
Each sample includes two key variables: the PWM control signal (ranging from 0 to 255) and the corresponding height of the levitated object (measured in centimeters).
DOI: 10.17632/wcbh5c4d8g
title: Supplementary Figures for 'Sub-ultraviolet Reflectance Dermoscopy Reveals Hidden Pigment Network in Reed Nevi'

description: Supplementary Figures and Figure Legends
DOI: 10.15468/dl.y6a7kt
title: Occurrence Download

description: A dataset containing 40918 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Catherpes mexicanus"
 ]
}

 The dataset includes 40918 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026654-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/wcbh5c4d8g.1
title: Supplementary Figures for 'Sub-ultraviolet Reflectance Dermoscopy Reveals Hidden Pigment Network in Reed Nevi'

description: Supplementary Figures and Figure Legends
DOI: 10.17632/r9zvpc4xf5
title: Survey Data

description: This data is collected from a survey that was sent to university students about their experience with Generative AI
DOI: 10.17632/r9zvpc4xf5.1
title: Survey Data

description: This data is collected from a survey that was sent to university students about their experience with Generative AI
DOI: 10.17632/fppcb7wsxm
title: Spatio-temporal forecasting of dengue in the Americas -A data set

description: This dataset accompanies the systematic review and meta-analysis entitled “Spatio-temporal forecasting of dengue in the Americas through hybrid mechanistic and data-driven models: Systematic review and meta-analysis.” It provides a comprehensive synthesis of dengue modeling efforts across the Americas from 2016 to 2025, integrating mechanistic, statistical, machine learning, and phylogenetic approaches.

The files included present structured evidence on dengue dynamics, model structures, and analytical frameworks:

Detailed Overview of Sub-model Structures: Comparative representation of vector–host and within-host modeling frameworks.

Table 1. Data Extraction Matrix: Summary of key variables, parameters, and outcomes derived from the 19 included studies.

Table 2. Comparative Summary: Model calibration, validation techniques, and analytical frameworks applied across studies.

Table 3. Model Characteristics: Overview of dengue transmission model types, associated datasets, and contextual applications.

Figure 1. PRISMA Flow Diagram: Study identification and selection process for the review.

Figure 2. Geographical and Temporal Distribution: Mapping of dengue modeling studies across the Americas (2016–2025).

Figure 3. Heatmap of Risk of Bias: Horizontal representation of quality assessment across the 19 studies.

Figure 4. Forest Plot of Model Complexity: Comparative evaluation of mechanistic, statistical, ML/niche, and phylogenetic approaches.

Figure 5. Compartmental Variables and Interventions: Forest plot synthesis of transmission model compartments and intervention strategies.

Figure 6. Temperature Effects: Quantitative impact of temperature on dengue transmission risk in the Americas.

Figure 7. Model Performance and Predictive Accuracy: ROC curve analysis across different modeling frameworks.

Figure 8. General Compartmental Model: Conceptual diagram of dengue transmission in host–vector populations.

Together, these materials support transparency, reproducibility, and meta-analytical comparison of dengue modeling strategies, offering a valuable reference for researchers, public health practitioners, and policymakers addressing vector-borne disease forecasting in the Americas.
DOI: 10.17632/fppcb7wsxm.1
title: Spatio-temporal forecasting of dengue in the Americas -A data set

description: This dataset accompanies the systematic review and meta-analysis entitled “Spatio-temporal forecasting of dengue in the Americas through hybrid mechanistic and data-driven models: Systematic review and meta-analysis.” It provides a comprehensive synthesis of dengue modeling efforts across the Americas from 2016 to 2025, integrating mechanistic, statistical, machine learning, and phylogenetic approaches.

The files included present structured evidence on dengue dynamics, model structures, and analytical frameworks:

Detailed Overview of Sub-model Structures: Comparative representation of vector–host and within-host modeling frameworks.

Table 1. Data Extraction Matrix: Summary of key variables, parameters, and outcomes derived from the 19 included studies.

Table 2. Comparative Summary: Model calibration, validation techniques, and analytical frameworks applied across studies.

Table 3. Model Characteristics: Overview of dengue transmission model types, associated datasets, and contextual applications.

Figure 1. PRISMA Flow Diagram: Study identification and selection process for the review.

Figure 2. Geographical and Temporal Distribution: Mapping of dengue modeling studies across the Americas (2016–2025).

Figure 3. Heatmap of Risk of Bias: Horizontal representation of quality assessment across the 19 studies.

Figure 4. Forest Plot of Model Complexity: Comparative evaluation of mechanistic, statistical, ML/niche, and phylogenetic approaches.

Figure 5. Compartmental Variables and Interventions: Forest plot synthesis of transmission model compartments and intervention strategies.

Figure 6. Temperature Effects: Quantitative impact of temperature on dengue transmission risk in the Americas.

Figure 7. Model Performance and Predictive Accuracy: ROC curve analysis across different modeling frameworks.

Figure 8. General Compartmental Model: Conceptual diagram of dengue transmission in host–vector populations.

Together, these materials support transparency, reproducibility, and meta-analytical comparison of dengue modeling strategies, offering a valuable reference for researchers, public health practitioners, and policymakers addressing vector-borne disease forecasting in the Americas.
DOI: 10.15468/dl.u5y69w
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-73.24673 10.42469,-73.24754 10.42465,-73.24896 10.42458,-73.25016 10.42449,-73.25142 10.42449,-73.25272 10.42435,-73.25321 10.42428,-73.2532 10.42343,-73.25502 10.42326,-73.25531 10.42226,-73.25627 10.42217,-73.25639 10.42214,-73.2574 10.41988,-73.25525 10.41705,-73.25578 10.41698,-73.25572 10.41528,-73.25491 10.41354,-73.25139 10.41393,-73.24677 10.41474,-73.24318 10.41536,-73.24334 10.41756,-73.2411 10.4175,-73.24142 10.42464,-73.24673 10.42469))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026655-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.