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

description: A dataset containing 1254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Haritalodes derogata Fabricius, 1775"
 ]
}

 The dataset includes 1254 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051982-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bw8s2v
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "OccurrenceStatus is Present",
 "TaxonKey is Zostera caespitosa Miki"
 ]
}

 The dataset includes 16 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054394-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.16attv
title: Occurrence Download

description: A dataset containing 88 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tillandsia dugesii Baker"
 ]
}

 The dataset includes 88 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002594-150615163101818/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cm8xra
title: Occurrence Download

description: A dataset containing 9401 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "License is CC-BY 4.0",
 "TaxonKey is Pelophylax esculentus (Linnaeus, 1758)",
 "Year 2013-2024"
 ]
}

 The dataset includes 9401 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051990-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kpjsnm
title: Occurrence Download

description: A dataset containing 7278 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "HasCoordinate is true",
 "TaxonKey is Bryophyta",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7278 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036622-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mydr2u
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Streptanthus cutleri Cory"
 ]
}

 The dataset includes 68 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192478-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.epgxxb
title: Occurrence Download

description: A dataset containing 59750 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Milvus milvus (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 59750 records from 323 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002594-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.288ump
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rudgea nebulicola Steyerm."
 ]
}

 The dataset includes 23 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192479-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nshx39
title: Occurrence Download

description: A dataset containing 71731 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-135.02437 54.38241,-127.37844 45.27378,-124.05412 33.57218,-111.42171 20.8068,-86.75528 9.96952,-77.94104 3.01285,-78.31858 2.78404,-80.68107 1.0565,-81.72579 -2.10929,-83.3144 -8.04,-74.05535 -23.31143,-77.78302 -55.29727,-61.66985 -58.06296,-61.66985 -44.59524,-37.74061 -22.58995,-30.28525 -3.2301,-58.741 10.785,-60.1352 18.22075,-63.78668 18.95105,-65.84479 11.11696,-71.35521 13.77258,-76.2227 10.58321,-77.8581 9.49887,-81.98216 10.76097,-81.9276 16.28155,-86.60143 22.3212,-91.50843 22.09221,-91.90099 19.63871,-95.56488 19.93313,-94.51798 28.18265,-83.88038 27.38283,-81.29554 25.01329,-80.55338 25.11579,-79.1256 26.89484,-75.83422 35.36721,-75.21432 35.84863,-69.05847 42.27732,-72.75048 57.30252,-101.25704 61.87491,-135.02437 54.38241))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Viperidae"
 ]
}

 The dataset includes 71731 records from 199 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054575-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nuc2nh
title: Occurrence Download

description: A dataset containing 236 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hemiolaus Aurivillius, 1922"
 ]
}

 The dataset includes 236 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036583-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mcnz1f
title: Occurrence Download

description: A dataset containing 92 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cassiopea andromeda (Forskål, 1775)"
 ]
}

 The dataset includes 92 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002594-160430102343922/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cxffby
title: Occurrence Download

description: A dataset containing 123246 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dacnis cayana (Linnaeus, 1766)"
 ]
}

 The dataset includes 123246 records from 204 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0274508-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pjgjnd
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Loxosomella circulare (Harmer, 1915)"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054563-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hx69lw
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dypsis prestoniana Beentje",
 "Country is Madagascar"
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002594-160623103540712/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.un9bec
title: Occurrence Download

description: A dataset containing 661 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Haloxylon Bunge"
 ]
}

 The dataset includes 661 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0192477-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xdy3vh
title: Occurrence Download

description: A dataset containing 4125 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "HasCoordinate is true",
 "TaxonKey is Nymphalidae",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4125 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036626-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p9ybbxiz
title: Sediment deposition and accretion data from a tidal salt marsh in South San Francisco Bay, California 2021-2022

description: The U.S. Geological Survey, Western Ecological Research Center collected sediment and accretion data at a wave-exposed tidal salt marsh in South San Francisco Bay, California. Sediment traps and feldspar marker horizons (MH) were deployed along transects of increasing distance from the sediment source, at primary, secondary and tertiary marsh channels/bay. Data were collected bi-monthly over two month periods in summer 2021 and winter 2021/2022. Included here are trap and MH plot locations, calculated sediment fluxes at each station by deployment period, annual accretion rates, and covariates associated with sediment deposition and accretion including vegetation structure and elevation. This project aimed to assess the temporal and spatial patterns in sediment deposition in order to better understand sediment delivery and marsh resilience to sea-level rise.
DOI: 10.5067/8tdzurgrln9i
title: MODIS Aqua L2 model predicted low cloud types of chopped blocks in which low cloud dominates (block size: 128 pixels x 128 pixels, daytime) V001 at GESDISC
DOI: 10.5281/zenodo.10457005
title: VMGC - Human Vaginal Microbiome Genome Collection

description: The VMGC is a large-scale reference genome resource of the human vaginal microbiome, including over 33,000 genomes derived from 786 prokaryotes, 11 fungi, and 4,263 viruses associated with the human vagina. In terms of representation, the VMGC demonstrates high efficiency in capturing microbial sequences, with a median mapping rate of 91.7% across 4,472 vaginal metagenomic samples obtained from 14 countries.
DOI: 10.5281/zenodo.10530877
title: biVI supporting data

description: Simulated and experimental single cell RNA sequencing datasets analyzed to benchmark biVI and illustrate biVI's ability to infer biophysical parameters are included in data.zip. All data files are described in README_data.md.

Parameter inference results and figures are found in results.zip. All results included in results.zip are described in README_results.md.

 

The associated project GitHub can be found at https://github.com/pachterlab/CGCCP_2023.
DOI: 10.5281/zenodo.10554724
title: Dataset for article "Ultraviolet pulse compression via cross-phase modulation in a hollow-core fibre"

description: Data and figures for the paper & supplemental material:

Ultraviolet pulse compression via cross-phase modulation in a hollow-core fibre

Abstract:

Cross-phase modulation induced by an intense near-IR pulse propagating in gas-filled hollow-core fibre is used to spectrally broaden and temporally compress a co-propagating high-energy ultraviolet (UV) pulse, spanning the 260-320 nm region. The central wavelength, bandwidth and sign of the chirp of the output UV pulse can be controlled by tuning the initial delay among the two pulses, allowing us to demonstrate UV pulses with >10 μJ of energy which self-compress down to 6 fs after some propagation in air. This technique opens a way towards the realisation of few-fs ultraviolet pulses with tunable spectrum and high energy.

 

Extracting Figure Sources

execute the follwing substituting {filename}

tar -zxf {filename}.tar.gz
DOI: 10.5281/zenodo.2635543
title: Don't count, predict!  Semantic vectors

description: Semantic vectors associated with the paper "Don't count, predict! A systematic comparison of context-counting vs context-predicting semantics vectors"

<strong>Abstract:</strong> context-predicting models (more commonly known as embeddings or neural language models) are the new kids on the distributional semantics block. Despite the buzz surrounding these models, the literature is still lacking a systematic comparison of the predictive models with classic, count-vector-based distributional semantic approaches. In this paper, we perform such an extensive evaluation, on a wide range of lexical semantics tasks and across many parameter settings. The results, to our own surprise, show that the buzz is fully justified, as the context-predicting models obtain a thorough and resounding victory against their count-based counterparts.
DOI: 10.5281/zenodo.3950528
title: Encuesta Nacional sobre los Efectos del COVID-19 en el Bienestar de los Hogares Mexicanos (ENCOVID-19-ABRIL)

description: Amid the COVID-19 outbreak, the ENCOVID-19 provides information on the well-being of Mexican households in four main domains: labor, income, mental health, and food insecurity. It offers timely information to understand the social consequences of the pandemic and the lockdown measures. It is a project consisting of a series of cross-sectional telephone surveys collected once a month for one year. In addition to the four main domains and a set of COVID19-related questions, the survey includes new key indicators every month to capture the impact of the pandemic on issues like education, social programs, and crime. This is the first dataset of the project, corresponding to April 2020, collected one month after the lockdown began in Mexico.
description: Funded by Universidad Iberoamericana, Mexico City
DOI: 10.5281/zenodo.7596946
title: Lunar Observation Imaging Spectrometer Data

description: This dataset is the raw data observed by the Lunar Observation Imaging Spectrometer (LOIS).
DOI: 10.6084/m9.figshare.24100428.v1
title: CSd - DA Linking File (csv)

description: This file contains the summarized CSD and DA linkage based on the PCCF 2021
DOI: 10.6084/m9.figshare.25201991.v2
title: Summer monsoon drying accelerates India's groundwater depletion under climate change

description: Datasets to prepare the main and supplementary figures for the article submitted in Earth's Future journal.The Main folder contains datasets to plot the 5 main figures in each folder.The Supp folder contains all the other datasets to plot the supplementary figures.
DOI: 10.6084/m9.figshare.26057305
title: Supplementary Material for: Exploring Smartphone App use in older adults with a chronic respiratory disease: ‘The biggest problem I have is I don't understand my phone at all.’

description: Introduction: In older people with a chronic respiratory disease, we explored; (i) usual Smartphone Application (App) use, (ii) the time taken to download and use an App and (iii) changes in self-efficacy for downloading an App after a single practice session. 
Methods: Participants were invited to attend one or two separate assessment sessions (Part A and B). Those who attended Part A had data pertaining to their App usage over the previous week extracted from their Smartphone. Those who attended Part B were asked to download and use a pedometer App and ‘think out loud’ during the task. Before and after the task, participants rated their self-efficacy for downloading an App using a Visual Analogue Scale (0-10). 
Results: Twenty-seven participants (mean±SD 74±5 years) completed Part A. Commonly used Apps related to communication (e.g. texting; median [interquartile range] 15 [9 to 25] min/day) and interest (e.g. news; 14 [4 to 50] min/day). Fifteen participants completed Part B (mean±SD 73±7 years). The median time taken to download and use the App was 24 [22 to 37] min. The ‘think out loud’ data converged into four domains: (i) low self-efficacy for using and learning Apps; (ii) reliance on others for help; (iii) unpleasant emotional responses and (iv) challenges due to changes associated with longevity. Self-efficacy increased by 4 (95% CI 3 to 6). 
Conclusion: This population used Apps mainly to facilitate social connection. It took participants almost half an hour to download and use an App, but a single practice session improved self-efficacy.
DOI: 10.15156/bio/sh0957491.10fu
title: SH0957491.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957492.10fu
title: SH0957492.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957493.10fu
title: SH0957493.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957494.10fu
title: SH0957494.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957495.10fu
title: SH0957495.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0957496.10fu
title: SH0957496.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.