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

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ruellia simplex",
 "Country is Timor-Leste",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046314-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/g1sd-gaae-f612
title: VOCALS: GOES-10 10.7 um BT (T-11) Imagery. Version 1.0

description: This dataset contains GOES-10 10.7 um BT (T-11) Satellite Imagery. The files are GIF images for the period and area of the VOCALS project.
DOI: 10.15468/dl.qkfbtx
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cantinoa mutabilis",
 "Country is El Salvador",
 "HasCoordinate is true"
 ]
}

 The dataset includes 70 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046315-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/rsta-ftjf-2z0g
title: VOCALS: GOES-10 BTD 6.8-10.7um (T3-4) Imagery. Version 1.0

description: This dataset contains GOES-10 BTD 6.8-10.7um (T3-4) Satellite Imagery. The files are GIF images for the period and area of the VOCALS project.
DOI: 10.15468/dl.4m3y44
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cantinoa mutabilis",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046317-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9wjyq2
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cantinoa mutabilis",
 "Country is Honduras",
 "HasCoordinate is true"
 ]
}

 The dataset includes 33 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046316-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/rm3t-m8a6-wn01
title: VOCALS: GOES-10 BTD 10.7-12.0um (T4-5) Imagery. Version 1.0

description: This dataset contains GOES-10 BTD 10.7-12.0 um (T4-5) Satellite Imagery. The files are GIF images for the period and area of the VOCALS project.
DOI: 10.15468/dl.pmda33
title: Occurrence Download

description: A dataset containing 89 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Priva lappulacea",
 "Country is El Salvador",
 "HasCoordinate is true"
 ]
}

 The dataset includes 89 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046318-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.34kpjc
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Priva lappulacea",
 "Country is Guatemala",
 "HasCoordinate is true"
 ]
}

 The dataset includes 50 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046319-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zr9h7e
title: Occurrence Download

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

 The dataset includes 38 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046320-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/tz5m-rgfd-ad02
title: VOCALS: GOES-10 Optical Depth Imagery. Version 1.0

description: This dataset contains GOES-10 Optical Depth Satellite Imagery. The files are GIF images for the period and area of the VOCALS project.
DOI: 10.15468/dl.ztp4mz
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Priva lappulacea",
 "Country is Sao Tome and Principe",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046321-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/7xjh-g0b0-jw0k
title: VOCALS: GOES-10 Effective Cloud Temperature Imagery. Version 1.0

description: This dataset contains GOES-10 Effective Cloud Temperature Satellite Imagery. The files are GIF images for the period and area of the VOCALS project.
DOI: 10.15468/dl.yym5ue
title: Occurrence Download

description: A dataset containing 549831 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is one of (Africa, Europe, Asia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Hirundo rustica",
 "Year 2012-2014"
 ]
}

 The dataset includes 549831 records from 780 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046291-250920141307145/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.26752246.v1
title: Additional file 5 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 5.
DOI: 10.6084/m9.figshare.26752249
title: Additional file 6 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 6.
DOI: 10.6084/m9.figshare.26752249.v1
title: Additional file 6 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 6.
DOI: 10.6084/m9.figshare.26752252
title: Additional file 7 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 7.
DOI: 10.6084/m9.figshare.26752252.v1
title: Additional file 7 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 7.
DOI: 10.6084/m9.figshare.26752255
title: Additional file 8 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 8.
DOI: 10.6084/m9.figshare.26752258
title: Additional file 9 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 9.
DOI: 10.6084/m9.figshare.26752258.v1
title: Additional file 9 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 9.
DOI: 10.6084/m9.figshare.26752255.v1
title: Additional file 8 of The regulatory effect of TiO2 nanotubes loaded with graphene oxide on macrophage polarization in an inflammatory environment

description: Supplementary Material 8.
DOI: 10.6084/m9.figshare.26353235
title: Additional file 1 of Comparison of dynamic compression system versus multiple cancellous screws in the treatment of femoral neck fractures in young adults

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26353235.v1
title: Additional file 1 of Comparison of dynamic compression system versus multiple cancellous screws in the treatment of femoral neck fractures in young adults

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.26752360
title: Additional file 3 of The evaluation of risk factors for prolonged viral shedding during anti-SARS-CoV-2 monoclonal antibodies and long-term administration of antivirals in COVID-19 patients with B-cell lymphoma treated by anti-CD20 antibody

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.26752360.v1
title: Additional file 3 of The evaluation of risk factors for prolonged viral shedding during anti-SARS-CoV-2 monoclonal antibodies and long-term administration of antivirals in COVID-19 patients with B-cell lymphoma treated by anti-CD20 antibody

description: Supplementary Material 3.
DOI: 10.6084/m9.figshare.26353256
title: Additional file 1 of Unraveling the habitat preferences, ecological drivers, potential hosts, and auxiliary metabolism of soil giant viruses across China

description: Supplementary Material 1: Supplementary Table S1. Detailed information of the sampling sites of this study and their corresponding environmental factors. Supplementary Table S2. Information on metagenomics data used in this study. Supplementary Table S3. PolB sequences used to benchmark our phylogenetic mapping approach (as per Kazlauskas et al. [31]). Supplementary Table S4. Selected detailed information on the soil NCLDV phylotypes identified in this study. Supplementary Table S5. Taxonomic affiliations of marine NCLDV phylotypes identified in a previous study (Endo et al. [17]). Supplementary Table S6. Detailed information of soil NCLDV-eukaryote pairs in the co-occurrence networks shown in Supplementary Figure S9. Supplementary Table S7. Detailed information on giant virus metagenome-assembled genomes recovered in this study. Supplementary Table S8. Functional annotation of giant virus metagenome-assembled genomes recovered in this study. Supplementary Table S9. Reported NCLDVs-eukaryotes relationships in the references.
DOI: 10.6084/m9.figshare.26353256.v1
title: Additional file 1 of Unraveling the habitat preferences, ecological drivers, potential hosts, and auxiliary metabolism of soil giant viruses across China

description: Supplementary Material 1: Supplementary Table S1. Detailed information of the sampling sites of this study and their corresponding environmental factors. Supplementary Table S2. Information on metagenomics data used in this study. Supplementary Table S3. PolB sequences used to benchmark our phylogenetic mapping approach (as per Kazlauskas et al. [31]). Supplementary Table S4. Selected detailed information on the soil NCLDV phylotypes identified in this study. Supplementary Table S5. Taxonomic affiliations of marine NCLDV phylotypes identified in a previous study (Endo et al. [17]). Supplementary Table S6. Detailed information of soil NCLDV-eukaryote pairs in the co-occurrence networks shown in Supplementary Figure S9. Supplementary Table S7. Detailed information on giant virus metagenome-assembled genomes recovered in this study. Supplementary Table S8. Functional annotation of giant virus metagenome-assembled genomes recovered in this study. Supplementary Table S9. Reported NCLDVs-eukaryotes relationships in the references.
DOI: 10.6084/m9.figshare.26353412
title: Additional file 2 of Exosomal ssc-miR-1343 targets FAM131C to regulate porcine epidemic diarrhea virus infection in pigs

description: Additional file 2. The comparison of miRNA-seq between this study and others in PEDV infection.
DOI: 10.6084/m9.figshare.26353412.v1
title: Additional file 2 of Exosomal ssc-miR-1343 targets FAM131C to regulate porcine epidemic diarrhea virus infection in pigs

description: Additional file 2. The comparison of miRNA-seq between this study and others in PEDV infection.
DOI: 10.15468/dl.kzywhb
title: Occurrence Download

description: A dataset containing 798 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dendropsophus labialis (Peters, 1863)"
 ]
}

 The dataset includes 798 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0073027-240626123714530/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.26353229
title: Additional file 1 of Classification of African ground pangolin behaviour based on accelerometer readouts: validation of bio-logging methods

description: Additional file 1. Example ground pangolin behaviour used for accelerometer classification.
DOI: 10.6084/m9.figshare.26353229.v1
title: Additional file 1 of Classification of African ground pangolin behaviour based on accelerometer readouts: validation of bio-logging methods

description: Additional file 1. Example ground pangolin behaviour used for accelerometer classification.
DOI: 10.15468/dl.b6cwed
title: Occurrence Download

description: A dataset containing 14729 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "TaxonKey is Polistes metricus Say, 1831"
 ]
}

 The dataset includes 14729 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030580-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mphhe2
title: Occurrence Download

description: A dataset containing 193 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chimaeropsyllidae"
 ]
}

 The dataset includes 193 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030583-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14052989
title: An Empirical Study of Next-Line Prediction in Build Systems Using CodeGen

description: An Empirical Study of Next-Line Prediction in BuildSystems Using CodeGen.

Build systems play a crucial role in software development and are responsible for compiling source code into executable programs. Despite their importance, build systems often receive limited attention because their impact is not directly visible to end users. This oversight can lead to inadequate maintenance, frequent build failures, and disruptions that require additional resources. Recognising and addressing the maintenance needs of build systems is essential to preventing costly disruptions and ensuring efficient software production.

In this paper, we explore whether applying a Large Language Model (LLM) can reduce the burden of maintaining build systems. We aim to determine whether the prior content in build specifications provides sufficient context for an LLM to generate subsequent lines accurately. We conduct an empirical study on CodeGen, a state-of-the-art Large Language Model (LLM), using a dataset of 13,343 Maven build files. The dataset consists of the Expert dataset from the Apache Software Foundation (ASF) for fine-tuning (9,426 build files) and the Generalised dataset from GitHub for testing (3,917 build files). We observe that (i) fine-tuning on a small portion of data (i.e., 11\% of the fine-tuning dataset) provides the largest improvement in performance by 13.93\% (ii) When applied to the Generalised dataset, our fine-tuned model retains 83.86\% of its performance, indicating that it is not overfitted. Upon further investigation, we classify build code content into functional and metadata subgroups based on enclosing tags. Our fine-tuned model performs substantially better in suggesting functional than metadata build code. Our findings highlight the potential of leveraging LLMs like CodeGen to relieve the maintenance challenges associated with build systems, particularly in functional content. The study highlights the limitations of large language models in suggesting the metadata components of build code. Future research should focus on developing approaches to enhance the accuracy and effectiveness of metadata generation.

 

Replication Package Structure:

dataset.zip: Contains dataset for Expert and Generalised dataset.
DOI: 10.5281/zenodo.14052990
title: An Empirical Study of Next-Line Prediction in Build Systems Using CodeGen

description: An Empirical Study of Next-Line Prediction in BuildSystems Using CodeGen.

Build systems play a crucial role in software development and are responsible for compiling source code into executable programs. Despite their importance, build systems often receive limited attention because their impact is not directly visible to end users. This oversight can lead to inadequate maintenance, frequent build failures, and disruptions that require additional resources. Recognising and addressing the maintenance needs of build systems is essential to preventing costly disruptions and ensuring efficient software production.

In this paper, we explore whether applying a Large Language Model (LLM) can reduce the burden of maintaining build systems. We aim to determine whether the prior content in build specifications provides sufficient context for an LLM to generate subsequent lines accurately. We conduct an empirical study on CodeGen, a state-of-the-art Large Language Model (LLM), using a dataset of 13,343 Maven build files. The dataset consists of the Expert dataset from the Apache Software Foundation (ASF) for fine-tuning (9,426 build files) and the Generalised dataset from GitHub for testing (3,917 build files). We observe that (i) fine-tuning on a small portion of data (i.e., 11\% of the fine-tuning dataset) provides the largest improvement in performance by 13.93\% (ii) When applied to the Generalised dataset, our fine-tuned model retains 83.86\% of its performance, indicating that it is not overfitted. Upon further investigation, we classify build code content into functional and metadata subgroups based on enclosing tags. Our fine-tuned model performs substantially better in suggesting functional than metadata build code. Our findings highlight the potential of leveraging LLMs like CodeGen to relieve the maintenance challenges associated with build systems, particularly in functional content. The study highlights the limitations of large language models in suggesting the metadata components of build code. Future research should focus on developing approaches to enhance the accuracy and effectiveness of metadata generation.

 

Replication Package Structure:

dataset.zip: Contains dataset for Expert and Generalised dataset.
DOI: 10.15468/dl.fbaeck
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coptopsyllidae"
 ]
}

 The dataset includes 19 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030584-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive8276.20241212.9.2
title: Mycobacterium peregrinum (ex Bojalil et al. 1962) Kusunoki and Ezaki 1992 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8280.20241212.9.2
title: Mycobacterium phlei Lehmann and Neumann 1899 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8281.20241212.9.2
title: Mycobacterium phlei Lehmann and Neumann 1899 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8282.20241212.9.2
title: Mycobacterium phlei Lehmann and Neumann 1899 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8285.20241212.9.2
title: Mycobacterium phlei Lehmann and Neumann 1899 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8289.20241212.9.2
title: Nocardia beijingensis Wang et al. 2001

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8291.20241212.9.2
title: Mycobacterium salmoniphilum (ex Ross 1960) Whipps et al. 2007 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8299.20241212.9.2
title: Mycobacterium senegalense (Chamoiseau 1973) Chamoiseau 1979

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8309.20241212.9.2
title: Mycobacterium smegmatis (Trevisan 1889) Lehmann and Neumann 1899 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8324.20241212.9.2
title: Mycobacterium smegmatis (Trevisan 1889) Lehmann and Neumann 1899 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8330.20241212.9.2
title: Mycobacterium sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8339.20241212.9.2
title: Mycobacterium lehmannii Nouioui et al. 2017

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8344.20241212.9.2
title: Mycobacterium paraterrae Lee et al. 2016

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8346.20241212.9.2
title: Mycobacterium longobardum Tortoli et al. 2013 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8347.20241212.9.2
title: Mycobacterium iranicum Shojaei et al. 2013 emend. Nouioui et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive8348.20241212.9.2
title: Mycobacterium parakoreense Kim et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15468/dl.uk2xv6
title: Occurrence Download

description: A dataset containing 35703327 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 35703327 records from 7650 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085404-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.