cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14284/667
title: Acoustic salient event annotations

description: This repository contains all the data used to produce the results of the publication Parcerisas, C.; Schall, E.; Te Velde, K.; Botteldooren, D.; Devos, P.; Debusschere, E. Machine learning for efficient segregation and labeling of potential biological sounds in long-term underwater recordings (2024). Frontiers in Remote Sensing. doi: 10.3389/frsen.2024.1390687 All the necessary scripts to reproduce the publication results can be found on through github: https://github.com/lifewatch/sound-segregation-and-categorization.
description: Studying marine soundscapes by detecting known sound events and quantifying their spatio-temporal patterns can provide ecologically relevant information. However, the exploration of underwater sound data to find and identify possible sound events of interest can be highly time-intensive for human analysts. To speed up this process, we propose a novel methodology that first detects all the potentially relevant acoustic events and then clusters them in an unsupervised way prior to manual revision. We demonstrate its applicability on a short deployment. To detect acoustic events, a deep learning object detection algorithm from computer vision (YOLOv8) is re-trained to detect any (short) acoustic event. This is done by converting the audio to spectrograms using sliding windows longer than the expected sound events of interest. The model detects any event present on that window and provides their time and frequency limits. With this approach, multiple events happening simultaneously can be detected. To further explore the possibilities to limit the human input needed to create the annotations to train the model, we propose an active learning approach to select the most informative audio files in an iterative manner for subsequent manual annotation. The obtained detection models are trained and tested on a dataset from the Belgian Part of the North Sea, and then further evaluated for robustness on a freshwater dataset from major European rivers. The proposed active learning approach outperforms the random selection of files, both in the marine and the freshwater datasets. Once the events are detected, they are converted to an embedded feature space using the BioLingual model, which is trained to classify different (biological) sounds. The obtained representations are then clustered in an unsupervised way, obtaining different sound classes. These classes are then manually revised. This method can be applied to unseen data as a tool to help bioacousticians identify recurrent sounds and save time when studying their spatio-temporal patterns. This reduces the time researchers need to go through long acoustic recordings and allows to conduct a more targeted analysis. It also provides a framework to monitor soundscapes regardless of whether the sound sources are known or not.
DOI: 10.15468/dl.7vgke5
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Taxillus incanus (Trimen) Wiens"
 ]
}

 The dataset includes 37 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120629-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.24611946.v1
title: Gut Microbiome Characteristics of Hypothyroidism in Early Pregnancy Detected by 16S rRNA Amplicon Sequencing and Shotgun Metagenomics

description: Spearman correlation analysis of gut microbiome, serologic clinical indicators and functional modules in the hypothyroidism group and the control group.
DOI: 10.57745/jte9wg
title: PXDO10012.zip

description: # quantification results associated to the PRIDE PXD010012 dataset

TimsTOF raw data files are available online at https://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD010012


* fasta directory contains protein sequence databases in FASTA format
* fragpipe21.1 contains FragPipe output report files (one directory per experiment, containing the MSstats.csv report)
* i2m contains xpip files (i2MassChroQ xml files)
* masschroq contains masschroqML files and MSstat rdata output files


4 quantification results are given :

* entrapment database search experiment using fragpipe 21.1
* entrapment database search experiment using i2MassChroQ
* i2MassChroQ quantification results on PXD010012 dataset
* Fragpipe 21.1 quantification results on PXD010012 dataset
DOI: 10.57745/f6cbrf
title: PXD014777.zip

description: # PXD014777 benchmark experiment

TimsTOF raw data files are available online at https://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD014777


* fasta directory contains protein sequence databases in FASTA format
* fragpipe21.1 contains FragPipe output report files (one directory per experiment, containing the MSstats.csv report)
* i2m contains xpip files (i2MassChroQ xml files)
* masschroq contains masschroqML files and MSstat rdata output files


10 quantification results are given for each quantification pipeline (i2MassChroQ and Fragpipe21.1) :

* Quantification experiment using identification results calibrated with a 0.1 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.2 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.3 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.4 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.5 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.6 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.7 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.8 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 0.9 % PSM and protein FDR thresholds
* Quantification experiment using identification results calibrated with a 1 % PSM and protein FDR thresholds
DOI: 10.15468/dl.6fvr25
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erysimum canum (Piller & Mitterp.) Polatschek",
 "HasCoordinate is true",
 "Country is Iceland",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "CoordinateUncertaintyInMeters is less than 10000"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120631-240321170329656/datasets/export for details.
DOI: 10.15468/dl.r6b4v8
title: Occurrence Download

description: A dataset containing 65 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tanquana prismatica (Marloth) H.Hartmann & Liede"
 ]
}

 The dataset includes 65 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120630-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18167/dvn1/sgnsii
title: High resolution map of plant available water content for Senegal, derived from iSDA Africa 30m soil properties maps using USDA Rosetta3 model

description: Purpose: The purpose of this dataset is to provide a high resolution map of available water content for Senegal and Gambia derived from 30m soil properties maps using the iSDA Africa dataset and the USDA Rosetta3 model. The map can be used to notably support spatialized crop simulation models to determine potential crop yields across West Africa. Nature and extent of data: The dataset consists of a high resolution map of plant available water content derived from four soil property datasets from iSDA Africa. The soil properties include sand, clay, silt and fine-earth bulk density, and were predicted at a 30m resolution for 0-20 cm and 20-50cm depth intervals. The USDA Rosetta model was used to compute soil water retention properties from four iSDA layers (sand, clay, silt content, and fine-earth bulk density), including the van Genuchten parameters of residual water content, saturated water content, 'alpha' shape parameter, 'n' shape parameter, and saturated hydraulic conductivity. From these parameters, the volumetric water content at field capacity and permanent wilting point was computed using the van Genuchten-Mualem model. The output map has been filled with nearest neighbor interpolation where NaN values were present. Finally, available water content integrated over the soil profile down to 50cm and to the bedrock depth was calculated. Location and coverage: The dataset covers the countries of Senegal and Gambia in West Africa at a 30m resolution. Temporal scope: The dataset was created using soil property data and models from iSDA Africa and USDA Rosetta3, respectively, and covers the temporal scope of the original datasets. Archive formats / unzipping: Some of the archive files are separated in multiple parts, as indicated by their numeral file extensions (i.e. *.001, *.002, etc). To unzip these files, please consider using an unzipping software such as 7zip, that will manage file concatenation and unzipping given that all parts are stored under the same folder in your file system. Changelog: v1 : first submission v2 : maps have been clipped along the coastline to remove unwanted production artifacts
DOI: 10.15468/dl.9usjhm
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tetragonia herbacea L."
 ]
}

 The dataset includes 110 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120635-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4t6e7r
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Taraxacum ooststroomii Soest"
 ]
}

 The dataset includes 29 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120632-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3n5pqq
title: Occurrence Download

description: A dataset containing 3405 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Bugula flabellata (Thompson, 1848), Bugulina flabellata (Thompson, 1848))"
 ]
}

 The dataset includes 3405 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120633-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bfsbde
title: Occurrence Download

description: A dataset containing 670 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Taraxacum apenninum (Ten.) DC."
 ]
}

 The dataset includes 670 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120634-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5pw3n
title: Occurrence Download

description: A dataset containing 122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Oryzias latipes (Temminck & Schlegel, 1846), Silurus asotus Linnaeus, 1758)"
 ]
}

 The dataset includes 122 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0120636-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21954/ou.rd.24148200
title: Calculated energy and width for resonances in electron_H<sub>2</sub> collisions

description: The energy and width of resonances occurring in electron scattering from H2 have been calculated using the R-matrix method, for bond lengths between 1.1 and 4.0 bohr. This data corresponds to the manuscript <b>Electron scattering from H</b><sub><strong>2</strong></sub><b> </b><b>around the H(2l) + </b><b>H</b><sup><strong>−</strong></sup><b>(1s</b><sup><strong>2</strong></sup><b>) dissociation limit,</b> published in the <i>Journal of Physics B</i>: https://doi.org/10.1088/1361-6455/ad38f3
DOI: 10.21954/ou.rd.24148200.v1
title: Calculated energy and width for resonances in electron_H<sub>2</sub> collisions

description: The energy and width of resonances occurring in electron scattering from H2 have been calculated using the R-matrix method, for bondlengths between 1.1 and 4.0 bohr. This data corresponds to the manuscript <b>Electron scattering from H</b><sub><strong>2</strong></sub><b> </b><b>around the H(2l) + </b><b>H</b><b>−</b><b>(1s</b><sup><strong>2</strong></sup><b>) dissociation limit, </b>to be submitted to the Journal of Physics B.
DOI: 10.21954/ou.rd.24148200.v2
title: Calculated energy and width for resonances in electron_H<sub>2</sub> collisions

description: The energy and width of resonances occurring in electron scattering from H2 have been calculated using the R-matrix method, for bond lengths between 1.1 and 4.0 bohr. This data corresponds to the manuscript <b>Electron scattering from H</b><sub><strong>2</strong></sub><b> </b><b>around the H(2l) + </b><b>H</b><sup><strong>−</strong></sup><b>(1s</b><sup><strong>2</strong></sup><b>) dissociation limit,</b> published in the <i>Journal of Physics B</i>: https://doi.org/10.1088/1361-6455/ad38f3
DOI: 10.5281/zenodo.10656934
title: Data for Abiotic Origin of Organics in the Martian Regolith

description: This is the supplemental data for the muscript (submitted): "Abiotic Origin of Organics in the Martian Regolith", and comprises the following: 

_FTIR hyperspectral map 



↪ FTIR hyperspectral data [combined into single .xlsx file]

↪ FTIR pixel location map

↪ Raman IFORS fitting results


_micro-Raman hyperspectral maps



↪ Raman hyperspectral data [per region]

↪ Raman pixel location map [per region]


_microscopy



↪ Reflected Light (RL) image of entire sample

↪ Reflected Light (RL) [per region]


_mossbauer results

_NanoSIMS



↪ NanoSIMS data [per region]

↪ NanoSIMS data images [per region]

↪ NanoSIMS processed data

↪ NanoSIMS standards


_SEM BSE&EDS images



↪ BSE and EDS images [per region]


 

ABSTRACT

The martian meteorite Northwest Africa (NWA) 11220 and paired stones (notably NWA 7034) are the only group of meteorites that sample a clastic near-surface lithology from Mars. The stones have been recognized as an impact-reworked lithology subjected to an impact-induced hydrothermal system — comparable to the postulated history of Jezero Crater, currently being explored by the NASA Perseverance rover. By applying Mössbauer spectroscopy in combination with several in situ analytical techniques including Raman spectroscopy, FTIR spectroscopy, and NanoSIMS, we show that aliphatic carbon compounds dominate the inventory of insoluble indigenous carbon compounds within NWA 11220. Disordered carbon — present in ~5 μm heterogeneous masses — is preferentially found within porosity where it adjoins the mineral surface of titano-magnetite. This relationship suggests catalytic surfaces have enabled Fischer–Tropsch (FT) synthesis of hydrocarbons. Our in situ micron-scale analytical study indicates that such methods can successfully determine the origin of organic material and, therefore, differentiate abiotic martian organics that exist in the near-surface martian regolith. The multimodal approach will be a key methodology for searching for traces of past life in future samples returned from Mars.
DOI: 10.5281/zenodo.10656933
title: Data for Abiotic Origin of Organics in the Martian Regolith

description: This is the supplemental data for the muscript (submitted): "Abiotic Origin of Organics in the Martian Regolith", and comprises the following: 

_FTIR hyperspectral map 



↪ FTIR hyperspectral data [combined into single .xlsx file]

↪ FTIR pixel location map

↪ Raman IFORS fitting results


_micro-Raman hyperspectral maps



↪ Raman hyperspectral data [per region]

↪ Raman pixel location map [per region]


_microscopy



↪ Reflected Light (RL) image of entire sample

↪ Reflected Light (RL) [per region]


_mossbauer results

_NanoSIMS



↪ NanoSIMS data [per region]

↪ NanoSIMS data images [per region]

↪ NanoSIMS processed data

↪ NanoSIMS standards


_SEM BSE&EDS images



↪ BSE and EDS images [per region]


 

ABSTRACT

The martian meteorite Northwest Africa (NWA) 11220 and paired stones (notably NWA 7034) are the only group of meteorites that sample a clastic near-surface lithology from Mars. The stones have been recognized as an impact-reworked lithology subjected to an impact-induced hydrothermal system — comparable to the postulated history of Jezero Crater, currently being explored by the NASA Perseverance rover. By applying Mössbauer spectroscopy in combination with several in situ analytical techniques including Raman spectroscopy, FTIR spectroscopy, and NanoSIMS, we show that aliphatic carbon compounds dominate the inventory of insoluble indigenous carbon compounds within NWA 11220. Disordered carbon — present in ~5 μm heterogeneous masses — is preferentially found within porosity where it adjoins the mineral surface of titano-magnetite. This relationship suggests catalytic surfaces have enabled Fischer–Tropsch (FT) synthesis of hydrocarbons. Our in situ micron-scale analytical study indicates that such methods can successfully determine the origin of organic material and, therefore, differentiate abiotic martian organics that exist in the near-surface martian regolith. The multimodal approach will be a key methodology for searching for traces of past life in future samples returned from Mars.
DOI: 10.5281/zenodo.10943207
title: Accompanying data - Papyrus - A large scale curated dataset aimed at bioactivity predictions

description: Addition of supporting files:- LICENSE.txt- data_types.json- data_size.json

 

Fixed version of Papyrus++ 05.5:- In the previous 05.5 version data was incorrectly duplicated based on assay type. This resulted in unintended data augmentation.- In this fixed 05.5 version the duplicates have been eliminated, now reporting the correct amount of data per assay type.

 

This repository contains the version 05.5 of the Papyrus dataset, an aggregated dataset of small molecule bioactivities, as described in the article "Papyrus - A large scale curated dataset aimed at bioactivity predictions" http://doi.org/10.1186/s13321-022-00672-x.

 

With the ongoing rapid growth of publicly available ligand-protein bioactivity data, there is a trove of valuable data that can be used to train a plethora of machine learning algorithms. However, not all data is equal in terms of size and quality and a significant portion of researchers’ time is needed to adapt the data to their needs. On top of that, finding the right data for a research question can often be a challenge on its own. To meet these challenges we have constructed the Papyrus dataset. Papyrus is comprised of around 60 million datapoints. This dataset contains multiple large publicly available datasets such as ChEMBL and ExCAPE-DB combined with several smaller datasets containing high-quality data. The aggregated data has been standardised and normalised in a manner that is suitable for machine learning. We show how data can be filtered in a variety of ways and also perform some example quantitative structure-activity relationship analyses and proteochemometric modelling. Our ambition is that this pruned data collection constitutes a benchmark set that can be used for constructing predictive models, while also providing a solid baseline for related research.
DOI: 10.5281/zenodo.7019873
title: Accompanying data - Papyrus - A large scale curated dataset aimed at bioactivity predictions

description: Addition of supporting files:- LICENSE.txt- data_types.json- data_size.json

 

Fixed version of Papyrus++ 05.5:- In the previous 05.5 version data was incorrectly duplicated based on assay type. This resulted in unintended data augmentation.- In this fixed 05.5 version the duplicates have been eliminated, now reporting the correct amount of data per assay type.

 

This repository contains the version 05.5 of the Papyrus dataset, an aggregated dataset of small molecule bioactivities, as described in the article "Papyrus - A large scale curated dataset aimed at bioactivity predictions" http://doi.org/10.1186/s13321-022-00672-x.

 

With the ongoing rapid growth of publicly available ligand-protein bioactivity data, there is a trove of valuable data that can be used to train a plethora of machine learning algorithms. However, not all data is equal in terms of size and quality and a significant portion of researchers’ time is needed to adapt the data to their needs. On top of that, finding the right data for a research question can often be a challenge on its own. To meet these challenges we have constructed the Papyrus dataset. Papyrus is comprised of around 60 million datapoints. This dataset contains multiple large publicly available datasets such as ChEMBL and ExCAPE-DB combined with several smaller datasets containing high-quality data. The aggregated data has been standardised and normalised in a manner that is suitable for machine learning. We show how data can be filtered in a variety of ways and also perform some example quantitative structure-activity relationship analyses and proteochemometric modelling. Our ambition is that this pruned data collection constitutes a benchmark set that can be used for constructing predictive models, while also providing a solid baseline for related research.
DOI: 10.5281/zenodo.7019874
title: Accompanying data - Papyrus - A large scale curated dataset aimed at bioactivity predictions

description: This repository contains the version 05.5 of the Papyrus dataset, an aggregated dataset of small molecule bioactivities, as described in the preprint "Papyrus - A large scale curated dataset aimed at bioactivity predictions". With the ongoing rapid growth of publicly available ligand-protein bioactivity data, there is a trove of valuable data that can be used to train a plethora of machine learning algorithms. However, not all data is equal in terms of size and quality and a significant portion of researchers’ time is needed to adapt the data to their needs. On top of that, finding the right data for a research question can often be a challenge on its own. To meet these challenges we have constructed the Papyrus dataset. Papyrus is comprised of around 60 million datapoints. This dataset contains multiple large publicly available datasets such as ChEMBL and ExCAPE-DB combined with several smaller datasets containing high-quality data. The aggregated data has been standardised and normalised in a manner that is suitable for machine learning. We show how data can be filtered in a variety of ways and also perform some example quantitative structure-activity relationship analyses and proteochemometric modelling. Our ambition is that this pruned data collection constitutes a benchmark set that can be used for constructing predictive models, while also providing a solid baseline for related research.