cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13890040
title: MAGs from Glacier-Fed Streams

description: The biofilm mode of life contributes to the success of microorganisms in extreme environments. Glacier-fed streams feature among Earth’s most extreme aquatic ecosystems because of marked oligotrophy and environmental fluctuations. Here, leveraging 156 metagenomes from the Vanishing Glaciers project, we report thousands of assembled genomes (MAGs) encompassing prokaryotes, algae, fungi, and viruses, and which are involved in biotic interactions within glacier-fed stream biofilms. Bacterial community composition varied regionally and was partially driven by environmental conditions. Bacterial MAGs were characterized by various strategies to exploit inorganic and organic energy sources, functional redundancy and mixotrophy, altogether possible adaptive responses to the glacier-fed stream environment. Our findings suggest that biofilms become more complex and switch from chemoautotrophy to heterotrophy as algal biomass increases in glacier-fed streams owing to glacier shrinkage. Our MAG compendium sheds light on the success of microbial life in glacier-fed streams and provides a resource for future research on a microbiome potentially imperiled by climate change.
DOI: 10.5281/zenodo.14031069
title: Meteorological data of Ali_Tazhong_Minfeng and Potential Source Analysis Code_FEAST

description: Meteorological data of Ali_Tazhong_Minfeng and Potential Source Analysis Code_FEAST
DOI: 10.5281/zenodo.14054836
title: Source data for publication "Bacteria use exogenous peptidoglycan as a danger signal to trigger biofilm formation"

description: This dataset contains the source data for the figures in the following publication: 

Title: Bacteria use exogenous peptidoglycan as a danger signal to trigger biofilm formation

Authors: Sanika Vaidya, Dibya Saha, Daniel K.H. Rode, Gabriel Torrens, Mads F. Hansen, Praveen K. Singh, Eric Jelli, Kazuki Nosho, Hannah Jeckel, Stephan Göttig, Felipe Cava, Knut Drescher

Journal: Nature Microbiology, 2025

 

Description of the dataset: 

The data is organized by figures in the publication receferenced above. For each figure, there is a XLSX-file that contains the processed data and a ZIP-archive that contains the raw image data. The ZIP-archive also contains readme documents with more detailed descriptions for every set of raw image data. 

Example: For Figure 1 in the main text of the publication, there following data are available:



raw data: Figure_01.zip

processed data: Processed_Source_Data_Figure1.xlsx


Similarly, XLSX-files and ZIP-archives are available for the main text Figures 1-6. For the Extended Data (ED) Figures 1-10, there are XLSX-files available that present the data shown in each figure. Only some of the Extended Data Figures present results based on image data - therefore raw image data ZIP-archives are only available for ED Figures 3, 6, 7, 8, 9, 10.
DOI: 10.5281/zenodo.4904800
title: HumBugDB: a large-scale acoustic mosquito dataset

description: <strong>A large-scale multi-species dataset of acoustic recordings</strong> Dataset accompanying code and paper: <em>HumBugDB: a large-scale acoustic mosquito dataset</em>. A large-scale multi-species dataset containing recordings of mosquitoes collected from multiple locations globally, as well as via different collection methods. In total, we present 71,286 seconds (20 hours) of labelled mosquito data with 53,227 seconds (15 hours) of corresponding background noise, recorded at the sites of 8 experiments. Of these, 64,843 seconds contain species metadata, consisting of 36 species (or species complexes). This repository contains: Multi-part zip of audio files to be extracted into the same folder Metadata in csv format: neurips_2021_zenodo_0_0_1.csv This data is supplemented by a GitHub repository, https://github.com/HumBug-Mosquito/HumBugDB, which aids as follows: The multi-part zip is intended to be extracted into the folder:<em> /data/audio/</em> in the repository. Latest metadata is hosted on GitHub to allow the modification of additional metadata as it becomes available in the database or bug-fixing. Documentation for code use, and a complete Datasheet for Datasets also available on GitHub. Example code for data splitting, feature extraction, model training, and evaluation in the top-level notebook <em>main.ipynb</em>. Bayesian Convolutional Neural Network models, in both Keras and PyTorch, trained on this data available at GitHub release v1.0
description: Funding from the 2014 Google Impact Challenge Award, and The Bill and Melinda Gates Foundation (https://www.gatesfoundation.org/about/committed-grants/2019/07/opp1209888)
DOI: 10.5281/zenodo.6478745
title: M2 internal tide modal energy terms from a global HYCOM simulation

description: This data set contains modal energy terms from a forward global HYCOM simulation (22.1) with realistic tide and atmospheric forcing as discussed in https://doi.org/10.1016/j.ocemod.2020.101656 (On the interplay between horizontal resolution and wave drag and their effect on tidal baroclinic mode waves in realistic global ocean simulations, 2020, MC Buijsman, GR Stephenson, JK Ansong, BK Arbic, JAM Green, ... Ocean Modelling 152, 101656). <strong>Please cite this article when using these data. </strong> This is a 4-km simulation with 41 layers. All data is on the native tripole grid. Data is stored as netcdf4 classic. The 2D data sets are 7055 x 9000 (lat x lon). The data set contains The time-mean and depth-integrated M2 mode 1-5 energy terms: x (eastward) and y (northward) fluxes, KE, APE, conversion, flux divergence, and the intermodal energy conversion (topographic mode coupling) term. The terms are computed for a two-week time series starting on GMT 01-Sep-2016 01:00:00. For details see the paper. Positive seafloor depth, and latitude and longitude coordinates The M2 mode-1 SSH of the same simulation can be found here: https://doi.org/10.5281/zenodo.5514226 https://sites.google.com/site/maartenbuijsman/
DOI: 10.5281/zenodo.7542486
title: Biplane fluoroscopy derived humerus and scapula kinematics during arm elevation and rotation

description: This dataset contains torso, scapula, and humerus kinematics from 20 healthy subjects performing coronal plane abduction, scapular plane abduction, forward elevation, internal external rotation at 90º of abduction, and internal external rotation in adduction. The humerus and scapula were imaged at 100 Hz using a biplane fluoroscopy system. 3D models of the humerus and scapula were constructed from each subject’s CT scan. Model-based markerless tracking ascertained the 3D position and orientation of each bone model by semi-automatically aligning digitally reconstructed radiographs against each frame of the biplane fluoroscopy recordings. The kinematics of the torso were measured using skin marker motion capture.
description: Research reported in this publication was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) of the National Institutes of Health under award number R01 AR067196. The research content herein is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
DOI: 10.60520/ieda/113537
title: Daily time series of matrix glass composition from tephra samples from the 2021 Tajogaite eruption at Cumbre Vieja volcano (La Palma, Canary Islands)

description: Ash and lapilli samples were continuously collected during the 2021 eruption of Cumbre Vieja volcano. This dataset reports the major and volatile (S, Cl) element compositions of matrix glasses from these samples. Data were acquired by electron probe microanalysis at the American Museum of Natural History and are given for 85 samples and 4 duplicates, resulting in a daily time series of erupted melt composition capturing 94% of the eruptive sequence.
description: Longpré, M.-A., S. Tramontano, M. J. Pankhurst, D. C. Roman, M. C. Reiss, F. Cortese, M. R. James, L. Spina, F. Rodríguez, B. Coldwell, A. Martín-Lorenzo, O. Barbee, L. D'Auria, K. J. Chamberlain, J. H. Scarrow, Shifting melt composition linked to volcanic tremor at Cumbre Vieja volcano, in press, Nature Geoscience
DOI: 10.6075/j0rv0m27
title: The JAG inertial confinement fusion simulation dataset for multi-modal scientific deep learning. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative

description: The goal of this project is to build better surrogate models for Inertial Confinement Fusion (ICF) using neural networks. Particularly, we are interested in replicating the behavior of the JAG 1D Semi-analytic simulator for ICF. The JAG model has been designed to give a rapid description of the observables from ICF experiments, which are all generated very late in the implosion. In this way the very complex and computationally expensive transport models needed to describe the capsule drive can be avoided, allowing a single solution in $ ilde$ seconds. The trade-off is that JAG inputs do not relate to actual experimental observables, rather the state of the implosion once the laser drive has switched off. At that point, an analytic description of the spatial profile inside the hotspot can be found [1,2], leaving only a set of coupled ODEs describing the temporal energy balance inside the entire problem which can be solved easily [3]. The various terms in the energy balance equation relate to different physics processes (radiation, electron conduction, heating by alpha particles, etc), making JAG useful for investigating the role of various potentially uncertain physics models. Combined with a thin-shell model describing the 3D hydrodynamic evolution of the hotspot [4], JAG has a detailed description of the spatial and temporal evolution of all thermodynamic variables which can be post-process to predict a full range of experimental observables. References: 1. Betti et al., Physics of Plasmas 9, 2277 (2002) 2. Springer et al., EPJ Web. Conferences 59:04001 (2013) 3. Betti et al., Physical Review Letters 114:255003 (2015) 4. Ott et al., Physical Review letters 29:1429 (1995)
description: A dataset is provided to test/train the models. This is a tarball inside 'data/', which contains .npy files for 10K images, scalars, and the corresponding input parameters. The size of the dataset provided (in 'data/') are as follows: Input: (9984, 5), Output/Scalars: (9984, 22), Output/Images: (9984, 16384). Images are interpreted as (-1,64,64,4). This package was built and tested using Tensorflow 1.8.0. It also depends on standard Python packages such as NumPy, Matplotlib for basic data loading and plotting utilities. We also provide a Python Jupyter Notebook, that is a self-contained script to load, process, and test the dataset described above. In particular, we include a Neural Network designed to act as a surrogate for the JAG 1D Simulator. The neural network is implemented in Tensorflow. The notebook allows a user to load the dataset, load the neural network and train it such that given just the 5 input parameters, it predicts the scalars and images accurately. This can be done directly in the notebook, without any additional modifications. During training, intermediate predictions are also saved to disk (as specified by the user). We hope this serves as a starting point to build, test and play with the ICF-JAG simulation dataset.
DOI: 10.6084/m9.figshare.25762806
title: Emergence of large-scale cell death via trigger waves of ferroptosis

description: This dataset contains the microscopy source data for the article entitled "Emergence of large-scale cell death via trigger waves of ferroptosis".
DOI: 10.6084/m9.figshare.27143571
title: Chrysiptera cyanea genome annotation, transcriptome, proteome, and script for manuscript figure production

description: Chrysiptera cyanea is among the most common coral reef fish in shallow coastal zones around the main island of Okinawa. Our team is working to develop this fish as a model organism for environmental monitoring purposes. Generating a genome allowed to investigate biomolecular aspects (notably using RNAseq) of the impact of environmental factors on Chrysiptera cyanea.On NCBI:- Raw genomic reads can be found on NCBI under the BioProject PRJNA1167451: m64150e_221129_182410.hifi_reads.fastq.gz and m64150e_221201_052041.hifi_reads.fastq.gz- Biosample is SAMN44005798: Sesoko_Male1_2022_Liver_for_DNA.- The assembly presented in the manuscript is C.cyanea_contigs.fasta.Genome annotation was notably performed using organ-specific transcriptomic reads from the same individual (Sesoko Male 1): - Eye1_S45_R1_001.fastq.gz and Eye1_S45_R2_001.fastq.gz (Accession number: SRR30849507)- Gill1_S47_R1_001.fastq.gz and Gill1_S47_R2_001.fastq.gz (Accession number: SRR30849506)- Liver1_S44_R1_001.fastq.gz and Liver1_S44_R2_001.fastq.gz (Accession number: SRR30849505)- Muscle1_S46_R1_001.fastq.gz and Muscle1_S46_R2_001.fastq.gz (Accession number: SRR30849504)- Sesoko-B1_S13_R1_001.fastq.gz and Sesoko-B1_S13_R2_001.fastq.gz [The brain from a different fish (Sesoko Male B1) collected at the same site on the same day also used for the annotation] (Accession number: SRR30849503)<br>On FigShare:- C.cyanea_genomeannotation.gff3 : genome annotation - C.cyanea_Final_Codingseq.fasta : coding sequence - C.cyanea_proteome.fasta : proteome - C.cyanea_blastannotation.csv : functional annotation of the coding sequence- All BUSCO files for assemblies performed with various options of Flye and the Improved Phased Assembler can also be found on FigShare (short summary, full table, and missing BUSCO list for 9 different assembly options). The assembly that was used for the final genome is the Improved Phased Assembler, no phase, parental alleles (nophase_p)- Delta files obtained from nucmer aligning the genome assembly to reference Pomacentrid genomes (Amphiprion clarkii, A. ocellaris, A. percula, Acanthochromis polyacanthus, Dascyllus trimaculatus) as well as the number of bases aligning between the C. cyanea contigs and reference genomes (n_bases_Ccy_to_X_nucmer.csv) by filtering to only keep alignments longer than 10,000 bases- The R (v4.3.3) script using the aforementioned files to produce Figure 2 and 3 from the manuscript: dotplot_and_nb_bases_calculation_Rscript.txt
DOI: 10.6084/m9.figshare.27266409
title: Spatial variation of population, density, and composition of mosquitoes in mainland China

description: Mosquitoes pose a significant threat to global health, impacting over 40% of the world's population. Currently, a dearth of large-scale and long-term data on mosquito populations in China hinders related research and public health endeavors. In response, we meticulously compiled and analyzed existing studies to construct a comprehensive dataset illustrating the spatial variation of mosquito populations, density, and composition across mainland China. This dataset furnishes invaluable information to support further research on mosquitoes and mosquito-borne diseases on broader spatial and temporal scales. The primary aim of this research is to contribute to efforts aimed at controlling mosquito transmission and mosquito-borne diseases, ultimately enhancing human well-being.
DOI: 10.6084/m9.figshare.27802734
title: Optimal color sets to represent the colors of natural scenes by k-medoids clustering

description: The Munsell and Natural Color Systems, as well as the World Color Survey, are standard sets of colors used in many practical and scientific applications. However, the colors of natural scenes exhibit a bias in color and do not have a uniform distribution, making it difficult for these sets to represent natural colors accurately. We derived sets of colors with small number of samples that are better at representing natural colors than any of these standard sets. Hyperspectral images of natural scenes and a k-medoids clustering algorithm were used to derive representative colors. For the same number of samples, the set of colors obtained by k-medoids is better at representing natural colors than the standard sets. These optimized sets are important for applications that require precise representation of natural colors.
DOI: 10.6084/m9.figshare.27953982.v1
title: Medium-scale thermospheric gravity waves in the high-resolution Whole Atmosphere Model: Seasonal, local time, and longitudinal variations [Dataset]

description: Gravity waves (GWs) are the buoyancy-driven waves in the Earth's atmosphere with periods ranging from few minutes to a few hours. These waves are generated by various processes and play an important role in coupling different regions and layers of the atmosphere. In this study, we use a global high-resolution whole atmosphere model that spans the Earth's atmosphere from the surface to the thermospheric and ionospheric heights of ~600 km. We investigate the seasonal climatology of GWs in the troposphere, stratosphere and thermosphere generated in the model and find that it agrees with previous knowledge from observations and models. We also find that the thermospheric GW activity in the model depends on local time and longitude signifying its interaction with atmospheric tides. Specifically, we observe a wavenumber-4 in the crests and troughs of GW activity around the equator during daytime, which is a signature of non-migrating tides modulating the propagation of GWs. This hasn't been observed before and elucidates the importance of high-resolution whole atmosphere models in advancing the knowledge of upper atmospheric physics.
DOI: 10.6084/m9.figshare.28040894
title: Data with climate risks and SFRs .xlsx

description: <br><br>There is a dataset including climate physical risk (CPR), climate transition risk (CTR), climate policy uncertainty (CPU), and systemic financial risks (SFRs) indices,where CPR10, CTR10 and CPU10 represent these indicators are constructed by ten newspapers, and CPR3, CTR3 and CPU3 represent these indicators are constructed by three newspapers. Systemic financial risks (SFRs) indicators can be constructed using the approach in our article. These indicators in this dataset are calculated by the author and are not raw data. Since copyright issues with raw data, we do not provide it here. If necessary, you can use the <i>Wind</i> and <i>Wisers Information Portal</i> database to download.
DOI: 10.15468/dl.bnn8pb
title: Occurrence Download

description: A dataset containing 2975 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, November, December)",
 "TaxonKey is Capsicum annuum L.",
 "Year 1995-2024"
 ]
}

 The dataset includes 2975 records from 217 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064450-241126133413365/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.28188791
title: dataset

description: K-Means-RD
DOI: 10.6084/m9.figshare.28188791.v1
title: dataset

description: K-Means-RD
DOI: 10.15468/dl.zn6hvr
title: Occurrence Download

description: A dataset containing 179 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fumaria melillaica Pugsley"
 ]
}

 The dataset includes 179 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064452-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dfbq43
title: Occurrence Download

description: A dataset containing 5079 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, November, December)",
 "TaxonKey is Solanum lycopersicum L.",
 "Year 1994-2024"
 ]
}

 The dataset includes 5079 records from 201 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064451-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3bjm5g
title: Occurrence Download

description: A dataset containing 1192 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, November, December)",
 "TaxonKey is Nicotiana tabacum L.",
 "Year 1994-2024"
 ]
}

 The dataset includes 1192 records from 163 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064453-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14631349
title: Stellate Ganglion Irradiation Alleviates Airway Inflammation in Asthmatic Mice via Activating SIRT1 Signaling Pathway
DOI: 10.5281/zenodo.14631350
title: Stellate Ganglion Irradiation Alleviates Airway Inflammation in Asthmatic Mice via Activating SIRT1 Signaling Pathway
DOI: 10.15468/dl.sbqwfe
title: Occurrence Download

description: A dataset containing 519 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, November, December)",
 "TaxonKey is Solanum melongena L.",
 "Year 1994-2024"
 ]
}

 The dataset includes 519 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064454-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kqvz5c
title: Occurrence Download

description: A dataset containing 4446 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, November, December)",
 "TaxonKey is Solanum sisymbriifolium Lam.",
 "Year 1994-2024"
 ]
}

 The dataset includes 4446 records from 182 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064455-241126133413365/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.28188896
title: <b>Neoadjuvant Immunotherapy Combined with Chemotherapy</b>

description: Neoadjuvant Immunotherapy Combined with Chemotherapy
DOI: 10.15468/dl.ahejzm
title: Occurrence Download

description: A dataset containing 1617 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, December, November)",
 "TaxonKey is Solanum tuberosum L.",
 "Year 1994-2024"
 ]
}

 The dataset includes 1617 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064456-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yhrm6n
title: Occurrence Download

description: A dataset containing 3320 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (January, February, March, April, November, December)",
 "TaxonKey is Talinum paniculatum (Jacq.) Gaertn.",
 "Year 1994-2024"
 ]
}

 The dataset includes 3320 records from 211 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064457-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wyy689
title: Occurrence Download

description: A dataset containing 493 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cinclodes palliatus (Tschudi, 1844)"
 ]
}

 The dataset includes 493 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048500-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-251258
title: Annual Holy Convocation, COGIC (49th: 1956), program

description: [description english/roman)] Program for the 49th Annual Holy Convocation of the Church of God in Christ (COGIC), Mason Temple, Memphis, Tennessee, 1946 November 27 - December 15.