cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/z75ccv4cbz.1
title: Optimized NMR-based metabolomic protocol for salivary analysis in clinical practice

description: Saliva remains underexplored in metabolomics compared to widely used biofluids such as blood and urine. However, its non-invasive, rapid, and cost-effective collection, as well as its suitability for self-sampling, make it particularly attractive for clinical and personalized medicine. Moreover, saliva is expected to provide complementary metabolic information to other biofluids. In this context, the present study aims to identify the most suitable sample collection and preparation protocol for maximizing relevant and informative metabolomic data from salivary NMR profiles. Four preparation protocols, selected and adapted from the literature, were systematically compared. Evaluation criteria included the number of identified metabolites, their concentrations, and the intra-day repeatability based on PCA (buckets). The most promising one is an in-house adapted method involving sequential centrifugation, freeze-drying and ultrafiltration (protocol 4). It emerges as the most robust protocol, providing the broadest metabolome coverage with 42 metabolites identified and quantified. This method was further assessed using ANOVA to determine intra- and inter-day precision. Most metabolites demonstrate excellent repeatability (coefficients of variation below 10%) and confirm the reliability of the protocol for quantitative metabolomics analysis. Overall, the optimized approach yields high-quality spectra, wide metabolic coverage and strong analytical precision, making it well suited for reproducible salivary NMR metabolomics. Beyond its methodological contribution, this work highlights saliva as a promising biofluid for diagnostics, disease monitoring and personalized medicine. With appropriate standardization of collection and preparation procedures, saliva could emerge as a biofluid of choice in clinical metabolomics, contributing to advances in preventive and precision healthcare.
DOI: 10.17632/4tdcmmmmtx
title: A Dataset for Classification of Bottle Gourd Leaf Diseases

description: The Dataset for Classification of Bottle Gourd Leaf Diseases includes 1,102 high-quality JPEG images, thoughtfully collected to help identify and classify a range of common diseases found in bottle gourd plants. Captured in natural lighting and real-world settings, the images show leaves in various positions and backgrounds, making the dataset practical for training machine learning models that need to perform well in real farming environments. It features eight clearly labeled categories: Anthracnose is the most common with 491 images, followed by Mosaic Virus (249), Alternaria Leaf Blight (174), Healthy leaves (55), Downy Mildew (46), Early Alternaria Leaf Blight (45), Fungal Damage Leaf (31), and Angular Leaf Spot (11). Each class highlights unique visual symptoms like dark lesions, mosaic patterns, yellowing, or fungal damage. This diverse collection not only captures the visual complexity of leaf diseases but also serves as a reliable foundation for building intelligent, AI-driven tools to support farmers and researchers in early disease detection and plant health management.
DOI: 10.17632/4tdcmmmmtx.1
title: A Dataset for Classification of Bottle Gourd Leaf Diseases

description: The Dataset for Classification of Bottle Gourd Leaf Diseases includes 1,102 high-quality JPEG images, thoughtfully collected to help identify and classify a range of common diseases found in bottle gourd plants. Captured in natural lighting and real-world settings, the images show leaves in various positions and backgrounds, making the dataset practical for training machine learning models that need to perform well in real farming environments. It features eight clearly labeled categories: Anthracnose is the most common with 491 images, followed by Mosaic Virus (249), Alternaria Leaf Blight (174), Healthy leaves (55), Downy Mildew (46), Early Alternaria Leaf Blight (45), Fungal Damage Leaf (31), and Angular Leaf Spot (11). Each class highlights unique visual symptoms like dark lesions, mosaic patterns, yellowing, or fungal damage. This diverse collection not only captures the visual complexity of leaf diseases but also serves as a reliable foundation for building intelligent, AI-driven tools to support farmers and researchers in early disease detection and plant health management.
DOI: 10.17632/wvfgwv6rzt
title: CRISPR Screen in mouse BV2 cells against RVFV

description: STARS file from the original data analysis
DOI: 10.15468/dl.5na7my
title: Occurrence Download

description: A dataset containing 602 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dactylorhiza sambucina)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 602 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007869-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/wvfgwv6rzt.1
title: CRISPR Screen in mouse BV2 cells against RVFV

description: STARS file from the original data analysis
DOI: 10.17632/3p7gjwmsxg
title: Dataset for "Structural controls on non-Fickian and Fickian chemical tracer diffusion in porous media"

description: These are the results of particle tracking simulation in 2D stochastic porous media, with Monte Carlo iterations. They are disorder-averaged spatial profiles, MSD, and survival probabilities.
DOI: 10.17632/3p7gjwmsxg.1
title: Dataset for "Structural controls on non-Fickian and Fickian chemical tracer diffusion in porous media"

description: These are the results of particle tracking simulation in 2D stochastic porous media, with Monte Carlo iterations. They are disorder-averaged spatial profiles, MSD, and survival probabilities.
DOI: 10.17632/k7t73ndkxz
title: Dataset Kudriavtseva

description: Датасет содержит значения отраслевых индексов МосБиржи и значения индексов тем новостей.
DOI: 10.17632/k7t73ndkxz.1
title: Dataset Kudriavtseva

description: Датасет содержит значения отраслевых индексов МосБиржи и значения индексов тем новостей.
DOI: 10.15468/dl.wdehna
title: Occurrence Download

description: A dataset containing 3783 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dactylorhiza traunsteineri, Orchis angustifolia, Orchis angustifolia, Orchis angustifolia, Orchis angustifolia, Orchis angustifolia, Orchis angustifolia, Orchis traunsteineri, Orchis traunsteineri, Orchis traunsteineri)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 3783 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007870-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rgj39b
title: Occurrence Download

description: A dataset containing 692 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((3.42924 43.28954,3.42779 43.29244,3.43895 43.29869,3.43895 43.30047,3.44073 43.30204,3.44386 43.31743,3.44207 43.31855,3.44319 43.32469,3.43649 43.32948,3.4327 43.32837,3.41273 43.33294,3.41228 43.33662,3.40626 43.34053,3.38919 43.34031,3.37747 43.33238,3.38986 43.32535,3.40113 43.31152,3.4076 43.28876,3.40815 43.28731,3.42924 43.28954))",
 "TaxonKey is Insecta"
 ]
}

 The dataset includes 692 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007871-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/00eae8d70316abe9b27a18760093d3fb
title: Fisher Meteorological Station at Harvard Forest since 2001

description: The Fisher Meteorological Station became operational on 11 Feb 2001. The station is located in an open field 200 m north of the Shaler Met Station, in a site chosen to minimize the angle of surrounding trees above the horizon (currently 15-25 degrees from the station at breast height). The Fisher Met Station records air temperature, relative humidity, dew point, precipitation (including water equivalent of snow), global solar radiation, PAR radiation, net radiation, barometric pressure, scalar wind speed, vector wind speed, peak gust speed (1-second), vector wind direction, standard deviation of wind direction (wind measurements at 10 m height), and soil temperature (10 cm depth). Instruments are scanned once per second, and 15-minute (hourly before 2005) and daily values are calculated and stored by a datalogger. Data for the current month are available online, updated every 15 minutes, with out-of-range values replaced by NA but values not otherwise checked. Earlier data are checked and archived monthly with missing, questionable, and estimated values flagged, following methods of the LTER ClimbDB project. A log of events affecting station measurements (e.g., instrument repair and recalibration, ice storms, lightning) and selected monthly and annual values are also posted.
 For current data, please see: https://harvardforest.fas.harvard.edu/met-hydro-stations. For a longer climate record that includes adjusted data from the Shaler Met Station, please see dataset HF300.
DOI: 10.15468/dl.mr4aw2
title: Occurrence Download

description: A dataset containing 32406 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Megaceryle torquata"
 ]
}

 The dataset includes 32406 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007873-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2jbtcf
title: Occurrence Download

description: A dataset containing 207 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Castratella piloselloides",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 207 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007874-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rh56wp
title: Occurrence Download

description: A dataset containing 5331 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dactylorhiza viridis, Coeloglossum viride)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 5331 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007876-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fwy7vr
title: Occurrence Download

description: A dataset containing 1295 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Daphne cneorum, Daphne cneorum, Daphne cneorum, Daphne cneorum)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 1295 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007879-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ghh3j6
title: Occurrence Download

description: A dataset containing 14053 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Danthonia decumbens, Triodia decumbens, Sieglingia decumbens)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 14053 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007878-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n98sa2
title: Occurrence Download

description: A dataset containing 146 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Centradenia floribunda",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 146 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007880-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/s2xrjhtbkk
title: Voice Quality, Vocal Fatigue, and Dysphonia Measures in Patients with Multiple Sclerosis
DOI: 10.17632/s2xrjhtbkk.1
title: Voice Quality, Vocal Fatigue, and Dysphonia Measures in Patients with Multiple Sclerosis
DOI: 10.17632/3w42gbzbvb.1
title: Dataset for Master’s Thesis on Innovation and Financial Performance of Chinese EV Public Companies

description: Dataset for Master’s Thesis on Innovation and Financial Performance of Chinese EV Public Companies
DOI: 10.17632/x59cx6ns2h.1
title: JCVI-syn3B FtsZ:mCherry plasmid

description: This plasmid was used for genetic introduction of a second copy of the FtsZ gene fused with mCherry to JCBI-syn3B for fluorescent imaging of cell division. Gibson assembly was used to construct the plasmid. Syn1.0 (GeneBank accession number CP002027) served as the template to amplify fragment 1 using primers 5’-GAATTCGCCAGAACCAGCAGCGGAGCCAGCGGATCCTTTTAAAAATGTCGGAAAGTCATC-3’ and 5’-AGCAAAGTGGGTGATAAATAAATGACAAACGAATTTAAACAAATAGC-3’, and fragment 2 using primers 5’-CGTTTGTCATTTATTTATCACCCACTTTG-3’ and 5’-ATTTGAACGTTGCGAAGCAACAGAAGCATAATAACAATTATTAAT-3’. The vector backbone was amplified using primers 5’-AAGGATCCGCTGGCTCCGCTGCTGGTTCTGGCGAATTCATGGTATCAAAAGGAGAAGAAGATAATATG-3’ and 5’-TAATTGTTATTATGCTTCTGTTGCTTCGCAACGTTCAAATC-3’, with the ptxB-FLAG plasmid (not published) as the template. PrimeSTAR Max DNA polymerase (Takara, #R045A) was used to amplify the fragments. PCR was performed with an initial denaturation at 98 °C for 3 minutes, followed by 30 cycles of 98 °C for 10 seconds, 55 °C for 10 seconds, and 72 °C for 1 minute, with a final extension at 72 °C for 5 minutes. Primers 5’-TCCTCCAGCTCCTAATCCTT-3’ and 5’-TGTTTGTCGGTGAACGCTCT-3’ were used for colony PCR to identify positive clones. The final plasmid was confirmed by sequencing.
DOI: 10.17632/g7jy5s65v7
title: Bat calls dataset for deep learning classification

description: This dataset contains ultrasonic bat call recordings used for CNN-based species classification.

It includes:
- Filtered recordings from the ChiroVox database, processed using an adaptive spectral subtraction method.
- Unfiltered recordings from the Xeno-Canto database.

The dataset focuses on six bat species:
- Rhinolophus hipposideros
- Myotis daubentonii
- Eptesicus serotinus
- Nyctalus noctula
- Pipistrellus pipistrellus
- Pipistrellus pygmaeus

The data were collected and processed in the context of an academic project at INSA Rennes.
DOI: 10.17632/g7jy5s65v7.1
title: Bat calls dataset for deep learning classification

description: This dataset contains ultrasonic bat call recordings used for CNN-based species classification.

It includes:
- Filtered recordings from the ChiroVox database, processed using an adaptive spectral subtraction method.
- Unfiltered recordings from the Xeno-Canto database.

The dataset focuses on six bat species:
- Rhinolophus hipposideros
- Myotis daubentonii
- Eptesicus serotinus
- Nyctalus noctula
- Pipistrellus pipistrellus
- Pipistrellus pygmaeus

The data were collected and processed in the context of an academic project at INSA Rennes.
DOI: 10.17632/dyrbpmb3mb
title: Synthetic and Campaign-Level Sentiment Datasets for Early Detection of Reputational Risk in Influencer Marketing

description: This dataset supports research on the use of audience sentiment as an early-warning information signal for reputational risk in influencer marketing campaigns. It consists of two complementary components: a large-scale synthetic dataset designed for model training and methodological validation.
The synthetic dataset contains time-series sentiment and emotion trajectories for 12,000 simulated influencer campaigns observed over a 72-hour horizon with hourly resolution (864,000 observations). Campaigns are generated under controlled conditions to represent a range of risk profiles, emotional intensities, and escalation regimes. Variables include sentiment polarity, discrete emotional dimensions (e.g., anger, betrayal, disappointment), rolling sentiment volatility, and campaign-level risk indicators. Ground-truth risk labels are provided by design, enabling supervised learning, benchmarking, and reproducibility. The campaign-level dataset comprises 45 influencer campaigns observed over a seven-day window with hourly aggregation (7,560 observations). These campaigns represent normatively diverse sectors, including fintech, gambling, health and wellness, and consumer brands.
DOI: 10.57967/hf/7711
title: WxC-Bench
DOI: 10.17632/dyrbpmb3mb.1
title: Synthetic and Campaign-Level Sentiment Datasets for Early Detection of Reputational Risk in Influencer Marketing

description: This dataset supports research on the use of audience sentiment as an early-warning information signal for reputational risk in influencer marketing campaigns. It consists of two complementary components: a large-scale synthetic dataset designed for model training and methodological validation.
The synthetic dataset contains time-series sentiment and emotion trajectories for 12,000 simulated influencer campaigns observed over a 72-hour horizon with hourly resolution (864,000 observations). Campaigns are generated under controlled conditions to represent a range of risk profiles, emotional intensities, and escalation regimes. Variables include sentiment polarity, discrete emotional dimensions (e.g., anger, betrayal, disappointment), rolling sentiment volatility, and campaign-level risk indicators. Ground-truth risk labels are provided by design, enabling supervised learning, benchmarking, and reproducibility. The campaign-level dataset comprises 45 influencer campaigns observed over a seven-day window with hourly aggregation (7,560 observations). These campaigns represent normatively diverse sectors, including fintech, gambling, health and wellness, and consumer brands.
DOI: 10.57967/hf/7710
title: WxC-Bench
DOI: 10.17632/8yxrztg233
title: Depression as a Longitudinal Modulator of Physical–Verbal Aggression in Early Adolescence: Trajectories and Sex Comparisons

description: Background:
Depression in early adolescence has been increasingly linked to heightened aggressive behaviour, yet little is known about how depressive symptoms shape the developmental trajectory of physical–verbal aggression during this critical period. Early adolescence (ages 10–14) is marked by the onset of sex differences in depression as well as significant changes in externalising behaviours, making it an essential stage for understanding comorbidity patterns. This study examines whether depressive symptoms function as a chronic and dynamic risk factor for aggression and whether these effects differ by sex.
Objective:
(1) To analyse the longitudinal effect of depression on physical–verbal aggression across early adolescence;
(2) To determine whether sex moderates the developmental trajectory and severity of aggression in adolescents with and without depression.
Method:
A three‑wave longitudinal design was conducted with 251 adolescents (66.5% girls; ages 10–14) recruited through random probability sampling in Madrid, Spain. Depression was assessed using the CDI‑S, and physical–verbal aggression with the PVA. Repeated‑Measures ANOVA tested intra‑ and inter‑individual differences across ages 10.8 (T1), 11.8 (T2), and 12.8 (T3), including sex and depression status as between‑subjects factors.
Results:
Depression exerted a significant longitudinal effect on aggression (F(1,249)=14.54, p&lt;.001, η²=.055), with adolescents with depression consistently scoring above global mean thresholds across all three time points. Aggression followed a quadratic trajectory (increase from 10.8 to 11.8 years, subsequent decrease at 12.8 years), but remained at elevated baseline levels when depression was present. Although boys and girls showed similar developmental curves (non‑significant interaction), boys displayed greater overall severity (F(1,249)=6.05, p=.015, η²=.024). Depression had a stronger impact in boys (η²=.073) than in girls (η²=.050), with depressed boys exhibiting the highest and most persistent aggression levels.
Conclusions:
Depression acts as a chronic and early‑emerging risk factor for physical–verbal aggression during early adolescence. Although trajectories are similar across sexes, boys show greater severity and reduced decline over time, suggesting increased vulnerability. These findings highlight the need for early screening of depressive symptoms in aggressive youth, and underscore the importance of longitudinal assessment for identifying high‑risk profiles and informing sex‑sensitive preventive interventions.