cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.s98rcq
title: Occurrence Download

description: A dataset containing 201 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Kappaphycus alvarezii (Doty) Doty ex P.C.Silva",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 201 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030538-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.knnk9t
title: Occurrence Download

description: A dataset containing 432 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Macrosamanea pubiramea var. pubiramea, Pithecellobium longiflorum Benth.)"
 ]
}

 The dataset includes 432 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030539-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/d2wm-c558
title: Tanzania Compact - Mafia Island Airport: Baseline Analysis Report
DOI: 10.3886/kfna-kf12
title: Tanzania Compact - Mafia Island Airport: Baseline Analysis Report
DOI: 10.15468/dl.f4dq6k
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Latissimia ningalooensis Ekins, Benayahu & McFadden, 2022",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030541-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6hfqr5
title: Occurrence Download

description: A dataset containing 178480624 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Canada"
 ]
}

 The dataset includes 178480624 records from 2702 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030493-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vgcry4
title: Occurrence Download

description: A dataset containing 22911718 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Accipiter badius, Accipiter gentilis, Accipiter gularis, Accipiter nisus, Accipiter soloensis, Accipiter trivirgatus, Accipiter virgatus, Aceros nipalensis, Achalinus jinggangensis, Acipenser baerii, Acipenser dabryanus, Acipenser nudiventris, Acipenser ruthenus, Acipenser schrenckii, Acipenser sinensis, Acrocephalus sorghophilus, Acrochordus granulatus, Aegolius funereus, Aegypius monachus, Aerodramus fuciphagus, Ailuropoda melanoleuca, Ailurus fulgens, Aix galericulata, Akrokolioplax bicornis, Alauda arvensis, Alcedo hercules, Alcedo meninting, Alces alces, Alectoris magna, Alligator sinensis, Amolops hainanensis, Amolops hongkongensis, Amphizoa sinica, Anabarilius polylepis, Anabarilius transmontanus, Andrias davidianus, Anguilla marmorata, Anorrhinus austeni, Anser albifrons, Anser erythropus, Anthracoceros albirostris, Aquila chrysaetos, Aquila fasciata, Aquila heliaca, Aquila nipalensis, Arborophila ardens, Arborophila atrogularis, Arborophila brunneopectus, Arborophila crudigularis, Arborophila gingica, Arborophila mandellii, Arborophila rufipectus, Arborophila rufogularis, Arborophila torqueola, Arctictis binturong, Arctogalidia trivirgata, Ardea insignis, Arenaria interpres, Asarcornis scutulata, Asio flammeus, Asio otus, Aspiorhynchus laticeps, Athene brama, Athene noctua, Aviceda jerdoni, Aviceda leuphotes, Axis porcinus, Aythya baeri, Babax koslowi, Babax waddelli, Bagarius bagarius, Bagarius rutilus, Bagarius yarrelli, Bahaba taipingensis, Balaenoptera acutorostrata, Balaenoptera borealis, Balaenoptera edeni, Balaenoptera musculus, Balaenoptera omurai, Balaenoptera physalus, Balanoglossus carnosus, Balanoglossus misakiensis, Batrachostomus hodgsoni, Batrachuperus karlschmidti, Batrachuperus londongensis, Batrachuperus pinchonii, Batrachuperus tibetanus, Batrachuperus yenyuanensis, Berardius bairdii, Bhutanitis lidderdalii, Bhutanitis ludlowi, Bhutanitis mansfieldi, Bhutanitis pulchristriata, Bhutanitis thaidina, Bos javanicus, Branchiostoma belcheri, Branta ruficollis, Bubo blakistoni, Bubo bubo, Bubo nipalensis, Bubo scandiacus, Buceros bicornis, Budorcas taxicolor, Bufo aspinius, Bufo stejnegeri, Butastur indicus, Butastur liventer, Butastur teesa, Buteo buteo)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 22911718 records from 9060 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059796-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/amfjtk
title: Deep-learning-ready RGB-Depth imaging dataset of early-growth plants.

description: Dataset composed of RGB, Depth, and Infrared images acquired while monitoring the growth of tomatoes, beans and rapeseed. 11 trials were conducted from 14-01-2022 to 13-12-2022.
DOI: 10.57745/c2zgiz
title: MassiveFold data for target H1267 - T300

description: MassiveFold data generated for CASP16, in collaboration with CAPRI . 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from https://predictioncenter.org/) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from https://www.capri-docking.org/assessment/) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
DOI: 10.57745/begc8r
title: Cartes et informations géographiques du réseau d'irrigation au domaine du Merle

description: Ce jeu de données présente la compilation des informations spatiales historiques sur le réseau d'irrigation au domaine du Merle ainsi qu'une mise à jour à la date de réalisation (début 2022).
DOI: 10.57745/bkml1l
title: Impact of a 2-month exercise training program on glycaemic fluctuations on days with and without exercise in adults with type 1 diabetes.

description: In type 1 diabetes (T1D), some few studies have explored the impact of training on glycaemic fluctuations. However, no research aimed to assess glycaemic excursions and their progression throughout a 2-month training program, distinguishing those observed around exercise sessions from those of non-exercising days. Nineteen (13 female) adults with T1D participated in 2-3 supervised exercise (aerobic/strength) 90-min weekly sessions over 2 months. Glycaemic excursions (continuous glucose monitoring) were calculated for specific periods (24-hour, nocturnal; periods before, during, after exercise sessions) and compared between day with and without an exercise session. Linear mixed models or binary/multinomial logistic regressions with random effects were used to assess the effect of weeks of training and type of day, including or not an exercise session, on glycaemic excursions. The data made available on data.gouv corresponds to all the data files used for these analyses. Access to the data can also be requested from Elsa Heyman. During the 2-month training, nights following exercise showed reduced risk of hyperglycaemic (&gt;10.0mmol⋅L-1) compared to non-exercise nights. This difference attenuated with weeks of training, in parallel to a progressive increased risk of time &gt;16.7mmol⋅L-1 during early and late recovery periods after exercise sessions. Overall, independently of exercise session occurrence, level 1 and 2 nocturnal hypoglycaemic risk increased as the training weeks passed. In conclusion, for patients with type 1 diabetes who engage in regular physical activity, it is crucial to be vigilant about post-exercise glycaemic excursions, particularly at night. Although acute exercise (i.e., day with vs. without a training session) reduced nocturnal hyperglycaemia without increasing the risk of hypoglycaemia, this risk of hypoglycaemia progressively increased after several weeks of training, during the nights, even those not subsequent to an acute exercise. Therefore, enhancing glycaemic control, especially at night, using continuous glucose monitoring systems is essential, not only during the first weeks of training, but also after several weeks.
DOI: 10.57745/8z4btr
title: Corrosion Database of the piers of the île de Ré bridge (campain 2015)

description: This DATABASE "CORROSION of the piers of the île de Ré bridge" (in French) gathers the results of the corrosion assessment of the île de Ré bridge performed in 2015 as part of the DéCoF-Ré project. It consists of Microsoft Excel files that provides for 15 piers (among 28) information on: 1. Preparation of concrete 2. Visual inspection 3. Location of the reinforcement 4. Connexion to the reinforcement 5. Resistivity measurements 6. Half-cell potential measurements 7. Corrosion rate measurements
DOI: 10.57745/cgfewi
title: MassiveFold data for target H1227 - T272

description: MassiveFold data generated for CASP16, in collaboration with CAPRI . In this dataset, the LetB sequences were trimmed to 1-279. 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from https://predictioncenter.org/) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from https://www.capri-docking.org/assessment/) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
DOI: 10.57745/ctm9bo
title: Dynamic axial Magnetic Resonance Imaging (MRI) of healthy abdominal wall

description: This dataset contains anonymized axial magnetic resonance imaging (MRI) data of abdominal region of twenty healthy in vivo participants performing three exercises: breathing, coughing and Valsalva. This dataset includes anatomical MRI slices and corresponding segmented masks, providing insights into muscle activity and anatomical structures under different exercise conditions. Please look at the README file for more informations
DOI: 10.57745/aiujz6
title: MassiveFold data for target T1294v1 and T1294v2

description: MassiveFold data generated for CASP16, in collaboration with CAPRI . 8040 predictions were generated in total for both T1294v1 and T1294v2 targets = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from https://predictioncenter.org/)
DOI: 10.57745/apnoh8
title: METABARFOOD - Complementary analyses

description: This report contains complementary analyses performed for the METABARFOOD project.
DOI: 10.57745/ceqvvn
title: Sapin blanc / Abies alba

description: Fichier d'impression 3D d'anatomie du bois file for 3D printer : Wood anatomy
DOI: 10.57745/ch6qn4
title: FRPV - Classification model and training material for the detection of Rooftop Photovoltaic (RPV) systems.

description: This dataset contains: A Convolution Neural Network trained to identify rooftop photovoltaic systems The training material, here a set of labelled images of rooftops, based in France, containing or not PV systems. The training dataset is composed of our own data manually labelled as well as the data of Kasmi et al. https://10.1038/s41597-023-01951-4 This dataset is related to the scientific publication "Thebault, Nerot, Govehovitch, Ménézo - A comprehensive building-wise Residential Photovoltaic system detection in heterogeneous urban and rural areas: application to French territories" Applied Energy, 2025, doi.org/10.1016/j.apenergy.2025.125630
DOI: 10.57745/cmf9fc
title: Gut microbiota and Crohn’s disease fastq files

description: Fastq files
DOI: 10.57745/dp1gk8
title: Spatiotemporal reaction dynamics control in two‐photon polymerization for enhancing writing characteristics

description: Videos (supplementary materials) from - Publication : Mao A., Fess S., Kraiem N., Li P., Wu Z., Zhu Q., Huang X., Fan P., Cui B., Silvain J.-F., Hu S., Anthamatten M., Regan S. P., Harding D. J. and Lu Y. Spatiotemporal reaction dynamics control in two‐photon polymerization for enhancing writing characteristics. Adv. Mater. Technol. 2024. DOI : 10.1002/admt.202400077 / HAL : https://https://hal.science/hal-04540424 Dataset production context : Since 2001, three-dimensional microfabrication based on two-photon polymerization (TPP) has drawn extensive attention and interest in biology, optics, photonics, material science, and high-energy physics. The in-volume fabrication capability due to the threshold behavior of two-photon absorption enables TPP higher flexibility compared with other nanofabrication techniques. However, as determined by the in-volume fabrication feature as well as various reaction dynamics, the writing characteristics of TPP, such as throughput, accuracy, surface quality, and fabrication capability, are still limited. Herein, we performed a comprehensive study on the spatiotemporal behavior of reaction dynamics during TPP fabrication, mainly focusing on spatiotemporal characteristics of radical diffusion, photothermal effect, microscale mechanics, and voxel stacking process. Based on the study, a nonsequential fabrication method is established to simultaneously improve key writing characteristics of TPP and realize sharp features, high speeds, large overhang structure, and smooth surfaces. The method established in this work can be applied to improve the performance of functional devices for various fields. Highlighting videos present in supplementary materials For more information see the article
DOI: 10.57745/9ufef9
title: MassiveFold data for target T1234 - T288

description: MassiveFold data generated for CASP16, in collaboration with CAPRI . 8040 predictions were generated for the target = 1005 x 8 sets of parameters. - a description of the setup can be found in `MassiveFold_CASP16_Abstract.pdf` - `README.txt` describes the contents of the main `MassiveFold.tar.gz` file - the main `MassiveFold.tar.gz file contains all the predictions, divided into 8 folders named after the conditions. It contains predictions as well as pickle files, sequence alignments, rankings and plots. The README.txt file describes the contents of this tar.gz. - the `only_pdbs_MassiveFold.tar.gz` is the result of the `gather_runs.py` script, without the pickle files. It contains a list of all the pdb files and ranking files with scores. - `gather_runs.py` allows to gather the runs, to use preferentially to the one included in the main `MassiveFold.tar.gz` at the time of the prediction phase, because it has been updated - `combined_scores.csv` file contains the CASP assessment for the target (from https://predictioncenter.org/) - `CAPRI_assessment.csv` file contains the CAPRI assessment for the target (from https://www.capri-docking.org/assessment/) - `CAPRI_scoring.pdb.gz` is a multi-pdbs containing all the MassiveFold predictions for the target. It was used for the CAPRI scoring phase.
DOI: 10.57745/anhvus
title: Données de réplication pour : Garbage in, garbage out: An industrial perspective on drug absorption modeling

description: Abstract Lead optimization failures are often linked to poor absorption, compounded by strong efflux transport and low recovery. Here we report a comprehensive analysis and modeling of public and industrial data on adsorption of organic molecules. Comparative analysis of one pharma-industrial chemical space was used to examine the relationship between critical permeability parameters. Our findings highlighted misconceptions in the transport route characterization. We demonstrated the importance of considering recovery, distribution coefficient, and topological polar surface area during Multi-Parameter Optimization. A Multi-Task Learning approach was employed for predictive model development. The models built on the public data were validated on the industrial data, revealing key discrepancies influenced by variation in experimental protocols. Our analysis emphasizes the model building on proprietary data in industrial absorption evaluations, which allows to avoid applicability domain issues and standardized measurement protocols. Finally, the integration of predictive models with Generative Topographic Mapping for chemical space exploration introduces a novel strategy to better understand optimization challenges. This work proposes a visual approach for MPO to improve drug discovery efficiency. The developed public models and curated public datasets are publicly accessible. This repository contains the data collected for this work.
DOI: 10.15468/dl.t3qdmm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Poyntonophrynus fenoulheti (Hewitt & Methuen, 1912)",
 "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 ((20.529 -24.0715,20.509 -24.0455,20.509 -24.0715,20.529 -24.0715))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035115-250525065834625/datasets/export for details.
DOI: 10.57745/d20cfb
title: Experimental gamma-ray data recorded with a LaBr3 and digital acquisition.

description: This package publishes a data set of gamma-ray recorded using an LaBr3 and digital acquisition.
DOI: 10.57745/diilxr
title: Python code for the article "The proportion of resistant hosts in mixtures should be biased towards the resistance with the lowest breaking cost" by Clin et al. 2023 submitted to PLOS Comp Biol

description: These files are code for a Python Streamlit application to reproduce the simulations (disease prevalence as a function of cultivar mixture composition) presented in the referenced article. Parameters can also be varied by the user. Different contexts are presented (no plant priming, plant priming).
DOI: 10.57745/b2oyxv
title: Vegetation resurveys and data on riparian communities along the Upper Rhône and Ain River

description: Floristic data were collected along a reach of the Upper Rhône River and the lower valley of the Ain River, over two periods : betwwen 1980s and 1990s for old, in 2020 and 2021 for recent resurvey. Data on species ecological preferences and strategies were collected for each species from two sources of information : 1) Ellenberg's indicator values (Ellenberg et al., 1992) for light (L), nutrient availability (N) and soil moisture (F) extracted from the Baseflor database (Julve, 1998) and 2) Grime's values (Grime, 1977) for Competitors, Stress tolerators and Ruderals, extracted from the list of species available in Pierce et al. (2017).
DOI: 10.57745/bxjbvh
title: Airborne laser scanning single tree detection NEWFOR benchmark dataset

description: In total 14 different study areas in 4 countries of the Alpine Space are made available. The following data are provided for each study area (number XX): Airborne Laser Scanning data in XX_ALS.laz (LAZ format cf https://laszip.org/) Digital Terrain Model (DTM) in XX_DTM.tif (1x1m or 0.5x0.5m spatial resolution) Forest Inventory (FI) data in XX_ref.shp (ESRI shapefile) Area of Interest in XX_AoI.shp (ESRI shapefile) Metadata in XX_Metadata.pdf Statistical Parameters about the FI data can be found in this publication: Eysn, L.; Hollaus, M.; Lindberg, E.; Berger, F.; Monnet, J.-M.; Dalponte, M.; Kobal, M.; Pellegrini, M.; Lingua, E.; Mongus, D.; Pfeifer, N. A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space. Forests 2015, 6, 1721-1747. DOI:10.3390/f6051721 All study areas used in the publication are present in this dataset, except study areas number 05, 12, 13 and 14 (due to copyright issues).
DOI: 10.57745/bzl832
title: Dataset for an experiment on distributed pair programming

description: Data collected during a distributed pair programming experiment conducted with first year university students in computer science lab sessions. The data (anonymized) consists in students's responses to a System Usability Scale (SUS) survey given after the experiment, responses to a distributed pair programming usability questionnaire, and grades students obtained on the assignement.