cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17487469
title: Global Monthly Mean Burned Area (km², 0.25°) Averaged Across 2019–2024 — Derived from ESA FireCCI Sentinel-3 SYN v1.1

description: This dataset provides global monthly mean burned area (in square kilometers) averaged across the years 2019 to 2024. It is derived from the European Space Agency (ESA) Fire Disturbance Climate Change Initiative (FireCCI) Sentinel-3 SYN Burned Area Grid Product, version 1.1. The FireCCI product (FireCCIS311) combines multispectral reflectance data from the Ocean and Land Color Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) sensors onboard the Sentinel-3A and 3B satellites, complemented by VIIRS thermal anomaly detections, to identify and quantify burned areas globally.

The FireCCIS311 grid product summarizes pixel-level burned area information into a regular global grid at 0.25 × 0.25 degree spatial resolution and monthly temporal resolution. For this derived dataset, all available monthly grids from 2019 to 2024 were processed to calculate the long-term mean burned area for each calendar month (January–December). The resulting layers represent the climatological mean monthly fire activity, smoothing inter-annual variability and highlighting consistent spatial and seasonal patterns in global fire occurrence and extent.

Each GeoTIFF file corresponds to one calendar month and contains the mean burned area per 0.25° grid cell, expressed in km². The dataset is suitable for use in ecological and environmental analyses, including studies of fire-climate interactions, vegetation dynamics, biogeography, ecological niche modeling, and assessments of disturbance regimes.

All rasters cover the global extent (-180° to 180°, -90° to 90°) at 0.25° (~25 km) resolution in the WGS 84 coordinate reference system (EPSG: 4326). Pixel values indicate the mean burned area (km²) per grid cell; zero values correspond to grid cells where no burned area was detected across the 2019–2024 period.

File contents:FireCCI_BurnedArea_MonthlyMean_Global_0.25deg.zip └── 12 GeoTIFF files: FireCCI_BurnedArea_Mean_01.tif – FireCCI_BurnedArea_Mean_12.tif  (one for each calendar month, January–December)

Data source:ESA Fire Climate Change Initiative (FireCCI): Sentinel-3 SYN Burned Area Grid Product, version 1.1Chuvieco E., Pettinari M.L., Lizundia-Loiola J., Khairoun A., Danne O., Boettcher M., Storm T. (2024).ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Grid product, version 1.1.NERC Environmental Data Service (Centre for Environmental Data Analysis).Source URL: catalogue.ceda.ac.uk/uuid/da8e669a74334c82a56e0b470bc4ef04

License:Data derived under the Open Government Licence (OGL, UK) as distributed by the ESA CCI Fire project through the Centre for Environmental Data Analysis (CEDA). Redistribution and derivative works are permitted with proper attribution to the original authors and project.

Chuvieco E. et al. (2024). ESA Fire Climate Change Initiative (FireCCI): Sentinel-3 SYN Burned Area Grid product, version 1.1. NERC EDS CEDA.
DOI: 10.5281/zenodo.17487468
title: Global Monthly Mean Burned Area (km², 0.25°) Averaged Across 2019–2024 — Derived from ESA FireCCI Sentinel-3 SYN v1.1

description: This dataset provides global monthly mean burned area (in square kilometers) averaged across the years 2019 to 2024. It is derived from the European Space Agency (ESA) Fire Disturbance Climate Change Initiative (FireCCI) Sentinel-3 SYN Burned Area Grid Product, version 1.1. The FireCCI product (FireCCIS311) combines multispectral reflectance data from the Ocean and Land Color Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) sensors onboard the Sentinel-3A and 3B satellites, complemented by VIIRS thermal anomaly detections, to identify and quantify burned areas globally.

The FireCCIS311 grid product summarizes pixel-level burned area information into a regular global grid at 0.25 × 0.25 degree spatial resolution and monthly temporal resolution. For this derived dataset, all available monthly grids from 2019 to 2024 were processed to calculate the long-term mean burned area for each calendar month (January–December). The resulting layers represent the climatological mean monthly fire activity, smoothing inter-annual variability and highlighting consistent spatial and seasonal patterns in global fire occurrence and extent.

Each GeoTIFF file corresponds to one calendar month and contains the mean burned area per 0.25° grid cell, expressed in km². The dataset is suitable for use in ecological and environmental analyses, including studies of fire-climate interactions, vegetation dynamics, biogeography, ecological niche modeling, and assessments of disturbance regimes.

All rasters cover the global extent (-180° to 180°, -90° to 90°) at 0.25° (~25 km) resolution in the WGS 84 coordinate reference system (EPSG: 4326). Pixel values indicate the mean burned area (km²) per grid cell; zero values correspond to grid cells where no burned area was detected across the 2019–2024 period.

File contents:FireCCI_BurnedArea_MonthlyMean_Global_0.25deg.zip └── 12 GeoTIFF files: FireCCI_BurnedArea_Mean_01.tif – FireCCI_BurnedArea_Mean_12.tif  (one for each calendar month, January–December)

Data source:ESA Fire Climate Change Initiative (FireCCI): Sentinel-3 SYN Burned Area Grid Product, version 1.1Chuvieco E., Pettinari M.L., Lizundia-Loiola J., Khairoun A., Danne O., Boettcher M., Storm T. (2024).ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Grid product, version 1.1.NERC Environmental Data Service (Centre for Environmental Data Analysis).Source URL: catalogue.ceda.ac.uk/uuid/da8e669a74334c82a56e0b470bc4ef04

License:Data derived under the Open Government Licence (OGL, UK) as distributed by the ESA CCI Fire project through the Centre for Environmental Data Analysis (CEDA). Redistribution and derivative works are permitted with proper attribution to the original authors and project.

Chuvieco E. et al. (2024). ESA Fire Climate Change Initiative (FireCCI): Sentinel-3 SYN Burned Area Grid product, version 1.1. NERC EDS CEDA.
DOI: 10.3886/e239460
title: Linking Student Absenteeism on Different Days of the Week to Student Achievement

description: Extensive research has found that when students miss
more school days, they have lower test scores. However, little is known about the
ways in which students miss these days – namely how missing different days of
the week might link differently to test scores. Having this insight, however,
holds important knowledge for building interventions and supporting
instruction. In that vein, this research explored whether accruing absences on
particular days of the week linked differently to student performance on
standardized exams. Relying on school district data for students in elementary
school, there were two key findings. First, missing any amount of school is
negatively associated with lower achievement. That said, our second finding
suggests that missing more Mondays stood out as particularly negative for test
score performance. The results were only present with excused absences,
highlighting that this issue is about missing school, not disengagement
necessarily. The results differed for different student groups, and
implications are thus discussed.
DOI: 10.3886/e239460v1
title: Linking Student Absenteeism on Different Days of the Week to Student Achievement

description: Extensive research has found that when students miss
more school days, they have lower test scores. However, little is known about the
ways in which students miss these days – namely how missing different days of
the week might link differently to test scores. Having this insight, however,
holds important knowledge for building interventions and supporting
instruction. In that vein, this research explored whether accruing absences on
particular days of the week linked differently to student performance on
standardized exams. Relying on school district data for students in elementary
school, there were two key findings. First, missing any amount of school is
negatively associated with lower achievement. That said, our second finding
suggests that missing more Mondays stood out as particularly negative for test
score performance. The results were only present with excused absences,
highlighting that this issue is about missing school, not disengagement
necessarily. The results differed for different student groups, and
implications are thus discussed.
DOI: 10.1285/i26121581n7p255
title: La letteratura di traduzione nel Mezzogiorno medievale fra X e XI secolo: le scuole di Napoli e Amalfi
DOI: 10.15468/dl.esaksw
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gyrodactylus salaris",
 "Country is Russian Federation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 30 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038507-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1285/i26121581n7p263
title: Colophon
DOI: 10.5281/zenodo.14211467
title: Dataset: Impact of plant diversity in potato-ley strip-cropping systems on soil microbial communities

description: Crop diversification enhances agroecosystem productivity, yet underlying mechanisms, particularly those underground, remain unclear. Diversification practices, such as strip-cropping (alternating strips of different crops) and integrating legumes (plant-based fertilization), may improve nutrient uptake and reduce pathogen build-up via soil microbial community shifts. However, most evidence for plant diversity benefits arises from grasslands, and its impact in cropping systems remains underexplored. This study examined microbial communities in organically managed, long-term potato-ley strip-cropping systems, comparing mono-cropping and strip-cropping, and further examined the effect of replacing animal manure by integrating legumes and plant-based fertilization in strip-cropping systems. To assess changes in microbial community composition, bacterial, fungal and arbuscular mycorrhizal fungi (AMF) DNA was sequenced. In addition, AMF and potato fungal pathogens were quantified using quantitative PCR. Strip-cropping increased AMF and soil-borne potato pathogens at the strip edges, where ley and potato interacted, though edge effects were absent in plant-based strip-cropping systems. Despite higher pathogen abundance at the edges, these did not relate to more significant tuber disease symptoms or yield losses. Changes in soil abiotic properties, particularly lower pH, from plant-based management, influenced fungal community structure more than strip-cropping. Bacterial community structure, including N-fixing bacteria, remained unaffected by either practice. Our results indicate that legume legacy in plant-based systems more strongly affected fungal community than strip-cropping, while strip-cropping benefitted AMF abundances. Taken together, our findings suggest that for sustainable agricultural practices aiming to improve soil health and crop productivity, a comprehensive approach that considers crop diversity, soil management, and fertilization practices is necessary.
DOI: 10.5281/zenodo.14211468
title: Dataset: Impact of plant diversity in potato-ley strip-cropping systems on soil microbial communities

description: Crop diversification enhances agroecosystem productivity, yet underlying mechanisms, particularly those underground, remain unclear. Diversification practices, such as strip-cropping (alternating strips of different crops) and integrating legumes (plant-based fertilization), may improve nutrient uptake and reduce pathogen build-up via soil microbial community shifts. However, most evidence for plant diversity benefits arises from grasslands, and its impact in cropping systems remains underexplored. This study examined microbial communities in organically managed, long-term potato-ley strip-cropping systems, comparing mono-cropping and strip-cropping, and further examined the effect of replacing animal manure by integrating legumes and plant-based fertilization in strip-cropping systems. To assess changes in microbial community composition, bacterial, fungal and arbuscular mycorrhizal fungi (AMF) DNA was sequenced. In addition, AMF and potato fungal pathogens were quantified using quantitative PCR. Strip-cropping increased AMF and soil-borne potato pathogens at the strip edges, where ley and potato interacted, though edge effects were absent in plant-based strip-cropping systems. Despite higher pathogen abundance at the edges, these did not relate to more significant tuber disease symptoms or yield losses. Changes in soil abiotic properties, particularly lower pH, from plant-based management, influenced fungal community structure more than strip-cropping. Bacterial community structure, including N-fixing bacteria, remained unaffected by either practice. Our results indicate that legume legacy in plant-based systems more strongly affected fungal community than strip-cropping, while strip-cropping benefitted AMF abundances. Taken together, our findings suggest that for sustainable agricultural practices aiming to improve soil health and crop productivity, a comprehensive approach that considers crop diversity, soil management, and fertilization practices is necessary.
DOI: 10.15468/dl.xf76u5
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Galinsoga parviflora",
 "Country is Rwanda",
 "HasCoordinate is true"
 ]
}

 The dataset includes 17 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038510-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s6agd6
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anoplolepis gracilipes",
 "Country is Vanuatu",
 "HasCoordinate is true"
 ]
}

 The dataset includes 56 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038508-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qbp8k8
title: Occurrence Download

description: A dataset containing 7495 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Galinsoga parviflora",
 "Country is Poland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7495 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038509-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12563912
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.atfvts
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rubus ulmifolius",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 62 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038511-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wh2jk9
title: Occurrence Download

description: A dataset containing 333 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rubus ulmifolius",
 "Country is Chile",
 "HasCoordinate is true"
 ]
}

 The dataset includes 333 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038513-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2h7qnq
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rubus ulmifolius",
 "Country is Canada",
 "HasCoordinate is true"
 ]
}

 The dataset includes 16 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038512-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/dans-2xq-nrd5
title: Trauma & Resilience: 32InterviewI2G1
title: Trauma & Resilience: Intergenerational Holocaust research from an existential perspective

description: &lt;p&gt;Respondent I2G1 is zoon van respondenten I1G1 en I1G2. De oorlog heeft met name zijn blik op de wereld beïnvloed: hij heeft een afkeer tegen elke vorm van extremisme. Therapie heeft hem inzicht gegeven in de relatie tussen het verleden van zijn ouders en zijn huidige gedrag.&lt;/p&gt;
DOI: 10.15468/dl.y8a9a8
title: Occurrence Download

description: A dataset containing 481 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linepithema humile",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 481 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038515-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ge7k3k
title: Occurrence Download

description: A dataset containing 137 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linepithema humile",
 "Country is Ecuador",
 "HasCoordinate is true"
 ]
}

 The dataset includes 137 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038516-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vkkvwr
title: Occurrence Download

description: A dataset containing 242 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linepithema humile",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 242 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038517-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6ykxys
title: Occurrence Download

description: A dataset containing 29541 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Leycesteria formosa"
 ]
}

 The dataset includes 29541 records from 173 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038514-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wqm9mz
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rubus ulmifolius",
 "Country is Uruguay",
 "HasCoordinate is true"
 ]
}

 The dataset includes 38 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038521-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.prgvv7
title: Occurrence Download

description: A dataset containing 403 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rubus ulmifolius",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 403 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038519-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xb2wtp
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Melampsoridium hiratsukanum",
 "Country is Russian Federation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038522-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rehg6u
title: Occurrence Download

description: A dataset containing 560 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Galinsoga parviflora",
 "Country is Saudi Arabia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 560 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038523-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16408490
title: Flood magnitude and Annual Maximum Flow simulations for the  Karnali River catchment for an ensemble of CMIP6 climate projections

description: Simulated datasets with Annual Maximum (AMAX) discharge simulations and Flood Frequecy Analysis (FFA) predictions for the Karnali River in Nepal. The ensemble consists of 12 CMIP6 models and 64 hydrological parametersets. The scripts (R Version 4.4.2) analyse the results and generate figures for an article that is currently under review.
DOI: 10.15468/dl.u922em
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Linepithema humile",
 "Country is Japan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 96 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038526-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16410239
title: MetaPromptMH

description: # MetaPromptMH: Context-Aware Mental Health Prediction via Adaptive Prompt Tuning

**MetaPromptMH** is a context-aware and efficient prompt-based framework for mental health prediction on social media. It leverages meta-learning and soft prompt adaptation to improve generalization across diverse platforms and user communities, especially in low-resource and domain-shift settings.

---

## 🧠 Overview

This repository provides the official implementation of the method described in:

> **"Context-Aware Mental Health Prediction from Social Media via Meta-Learned Adaptive Prompt Tuning"**

The proposed method combines:

- **MetaPrompt**: A meta-learned prompt initialization strategy that enhances cross-domain generalization  - **Context-Aware Prompt Fusion (CPF)**: A dynamic prompt selection module based on post-level and user-level signals  - **Lightweight Adaptation**: Only prompt vectors are tuned, keeping the PLM backbone frozen

---

## 🌟 Key Features

- 🚀 Efficient few-shot mental health detection with minimal task-specific tuning- 🌐 Robust generalization across platforms (Reddit, Twitter, etc.)- 📚 Compatible with BERT, RoBERTa, and other Transformer-based PLMs- ⚙️ Domain-aware and context-sensitive prompt fusion- 💡 Applicable to depression, anxiety, stress, and suicidal ideation detection tasks

---

## 📁 Project Structure

```bash.├── models/                  # MetaPrompt and CPF implementation├── data/                    # Preprocessed mental health datasets├── configs/                 # YAML configuration files├── scripts/                 # Training and evaluation scripts├── utils/                   # Metrics, logging, and helpers├── checkpoints/             # Saved prompt encoders└── README.md