cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.4s8b6q5
title: Data from: Phylogenetic relationships and convergent evolution of ocean-shore ground beetles (Coleoptera: Carabidae: Trechinae: Bembidion and relatives)

description: Through phylogenetic analysis of seven genes, we show that there have been
 at least six independent entries into intertidal habitats in the history
 of bembidiine carabids, in the ancestors of: (i) Orzolina Machado, (ii)
 Bembidion (Desarmatocillenus Netolitzky), (iii) Bembidion laticeps
 (LeConte) + palosverdes Kavanaugh & Erwin, (iv) Bembidion laterale
 (Samouelle), (v) Bembidion umi Sasakawa and Bembidion quadriimpressum
 (Motschulsky) (which may represent two separate entries), and (vi) B.
 nigropiceum (Marsham). The following lineages are widely separated within
 the subtribe Bembidiina: Orzolina is sister to the genus Ocys Stephens;
 subgenus Desarmatocillenus appears to be sister to all Bembidion Latreille
 excluding subgenus Phyla Motschulsky; B. laticeps + B. palosverdes is a
 clade in the Bembidion series; B. laterale is a member of the Princidium
 Motschulsky complex; B. umi and B. quadriimpressum are related to the
 Nearctic Clade of the Ocydromus Clairville complex; B. nigropiceum is
 sister to B. praeustum Dejean among sampled species. There are three
 separate lineages of ocean‐shore bembidiines that are known to prey on
 amphipods, and adults of these lineages [Bembidion (Desarmatocillenus), B.
 laterale, and B. mandibulare Solier] have unusually wide heads with long
 mandibles. Also common among independent lineages restricted to ocean
 shores are prominent front angles of the prothorax, larger numbers of
 setae on the elytral disc, a notable sinuation in the margin of each
 elytron near its apex, and short, wide mesotarsi. The reasons for the
 repeated evolution of these features are not evident. Our results also
 suggest that inland species of the Nearctic Clade may have arisen from an
 ocean‐shore ancestor. The close genetic similarities between the gravel
 river shore dwelling B. praeustum and the intertidal specialist B.
 nigropiceum suggest that the striking morphological adaptations of B.
 nigropiceum to the intertidal zone arose rapidly. We make one
 nomenclatural change: we resurrect the subgenus Lymneops Casey to
 accommodate B. palosverdes and B. laticeps.
description: Sequence data and
 phylogenetic treesThis file contains the
 DNA sequence data analyzed plus the inferred phylogenetic trees. It also
 contains a matrix of habitat data, as well as a tree showing (if opened in
 Mesquite) the habitat data mapped onto the phylogeny. It is in NEXUS
 format.MaddisonMaruyamaData.nex
DOI: 10.5061/dryad.n0d07ds
title: Data from: Development of low cost non-contact structural health monitoring system for rotating machinery

description: Condition monitoring systems are increasingly being employed in industrial
 applications to improve the availability of equipment to increase the
 overall equipment efficiency. Condition monitoring of gearboxes, a key
 element of rotating machines, ensures to continuously reduce and eliminate
 costs, unscheduled downtime and unexpected breakdowns. This study
 demonstrates a low cost microcontroller based non-contact data acquisition
 system for condition monitoring of rotating machinery. Experimental
 validation of the proposed system was carried out by performing
 examination tests on a gearbox test-rig. A user friendly Graphical User
 Interface (GUI) was also developed which facilitate user to perform signal
 processing in both real-time and offline mode. With these features the
 proposed system can perform most of the functions available in complex,
 standalone machines. The use of a general purpose PC and standard
 programming language makes the system simple, economical, and adaptable to
 a variety of problems. The tests show the developed system can perform
 properly as proposed.
description: raw_dataThe file contains all the raw data and processed FFT data for all gear running conditions
DOI: 10.15468/dl.7ct8z4
title: Occurrence Download

description: A dataset containing 273 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Ateles fusciceps"
 ]
}

 The dataset includes 273 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005957-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f4at7w
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.60111000000001 24.825288, 88.523742 24.819711, 88.4483 24.803119, 88.37665800000001 24.775923, 88.310596 24.738802, 88.251749 24.692676, 88.20157 24.638691, 88.161289 24.578185, 88.131891 24.512656, 88.11408299999999 24.443723, 88.10828600000001 24.373089, 88.11462299999999 24.302493, 88.132919 24.233672, 88.162705 24.168317, 88.20323399999999 24.108031, 88.25349900000001 24.054289, 88.31225999999999 24.008407, 88.378074 23.971505, 88.44932799999999 23.944484, 88.524283 23.928004, 88.60111000000001 23.922465, 88.677937 23.928004, 88.752892 23.944484, 88.824146 23.971505, 88.88996 24.008407, 88.94872100000001 24.054289, 88.998986 24.108031, 89.03951499999999 24.168317, 89.069301 24.233672, 89.087597 24.302493, 89.093934 24.373089, 89.088137 24.443723, 89.070329 24.512656, 89.040931 24.578185, 89.00064999999999 24.638691, 88.95047099999999 24.692676, 88.89162399999999 24.738802, 88.82556200000001 24.775923, 88.75391999999999 24.803119, 88.678478 24.819711, 88.60111000000001 24.825288))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005956-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18344654
title: Codes and Two datasets used in SaDE-RD for SLP

description: This repository contains two datasets applicable to the SaDE-RD algorithm. The first consists of six XLSX files, which store the information of 15, 30, 45, 60, 75 and 90 student residential areas respectively, with each file including the longitude, latitude and the number of students in each residential area. The second is the CEC2014 benchmark set file derived from the dataset published by Liang J J et al., which contains various vectors required for running the 30 functions of the CEC2014 benchmark set.
DOI: 10.5281/zenodo.18344655
title: Codes and Two datasets used in SaDE-RD for SLP

description: This repository contains two datasets applicable to the SaDE-RD algorithm. The first consists of six XLSX files, which store the information of 15, 30, 45, 60, 75 and 90 student residential areas respectively, with each file including the longitude, latitude and the number of students in each residential area. The second is the CEC2014 benchmark set file derived from the dataset published by Liang J J et al., which contains various vectors required for running the 30 functions of the CEC2014 benchmark set.
DOI: 10.15468/dl.d5gsxf
title: Occurrence Download

description: A dataset containing 15076 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-90.26707 22.01569,-74.80808 21.95073,-74.48331 37.7345,-90.13716 37.47468,-90.26707 22.01569))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Iguana"
 ]
}

 The dataset includes 15076 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005955-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5xuxn9
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.60111000000001 24.825288, 88.523742 24.819711, 88.4483 24.803119, 88.37665800000001 24.775923, 88.310596 24.738802, 88.251749 24.692676, 88.20157 24.638691, 88.161289 24.578185, 88.131891 24.512656, 88.11408299999999 24.443723, 88.10828600000001 24.373089, 88.11462299999999 24.302493, 88.132919 24.233672, 88.162705 24.168317, 88.20323399999999 24.108031, 88.25349900000001 24.054289, 88.31225999999999 24.008407, 88.378074 23.971505, 88.44932799999999 23.944484, 88.524283 23.928004, 88.60111000000001 23.922465, 88.677937 23.928004, 88.752892 23.944484, 88.824146 23.971505, 88.88996 24.008407, 88.94872100000001 24.054289, 88.998986 24.108031, 89.03951499999999 24.168317, 89.069301 24.233672, 89.087597 24.302493, 89.093934 24.373089, 89.088137 24.443723, 89.070329 24.512656, 89.040931 24.578185, 89.00064999999999 24.638691, 88.95047099999999 24.692676, 88.89162399999999 24.738802, 88.82556200000001 24.775923, 88.75391999999999 24.803119, 88.678478 24.819711, 88.60111000000001 24.825288))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005958-260120142942310/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.30433060
title: Artifacts - Understanding npm Developers’ Practices, Challenges, and Recommendations for Secure Package Development

description: This is the dataset for the paper: <b>Understanding npm Developers’ Practices, Challenges, and Recommendations for Secure Package Development</b>This paper was accepted for publication at the 19th IEEE/ACM International Conference on Cooperative and Human Aspects of Software Engineering (CHASE 2026) - Research TrackOverviewBelow describes the artifacts associated with this study.<code>SurveyResponses.sqlite</code> --- Survey responses in Sqlite database.<code>SurveyQuestionnaire.pdf</code> --- Survey questionnaire, including response options, utilized in the study.<code>Survey_Free_Text_Reponses_Categorized_Thematic_Analysis.xlsx</code> --- Results of the thematic analysis for the free-text questions.<code>Singlechoice-ranking-questions.xlsx</code> --- Results of the single-choice and ranking question types.<code>code/</code><code>MultiChoiceAnalysis.py</code> --- Class that builds frequency tables for single and multi-choice questions, computes average/median number of choices, performs pair/triplet combination analysis, and saves CSV/text outputs to <code>multichoice-questions/</code>.<code>main-npmPackageSecurity.py</code> --- Main orchestration script. Reads <code>SurveyResponses.csv</code>, runs <code>MultiChoiceAnalysis</code>, generates Likert charts (via <code>plot_likert</code>) and saves PDFs to <code>likert-figures/</code>.<code>SurveyResponses.csv</code> --- Survey responses in CSV (input).<code>likert-figures/</code> --- Output folder (created by <code>main-npmPackageSecurity.py</code>) containing generated Likert PDF figures.<code>multichoice-questions/</code> --- Output folder (created by <code>MultiChoiceAnalysis.py</code>) containing:single-choice and multi-choice frequency CSVscombination analysis CSVs for pairs/tripletssummary text files with average/median choicesCode OutputsLikert chart PDFs: saved to <code>likert-figures/</code>Frequency and combination CSVs + stats: saved to <code>multichoice-questions/</code>Code Dependencies<code>pandas</code><code>matplotlib</code><code>plot_likert</code>Code executionPlace <code>SurveyResponses.csv</code> in the project parent directory.From project root run:<code>python code/main-npmPackageSecurity.py</code>This will create <code>likert-figures/</code> and <code>multichoice-questions/</code> and write outputs.NotesVerify column names in <code>SurveyResponses.csv</code> match those referenced in the scripts before running.Output folders are created automatically by the scripts if missing.<br>
DOI: 10.6084/m9.figshare.30433060.v1
title: Artifacts - Understanding npm Developers’ Practices, Challenges, and Recommendations for Secure Package Development

description: This is the dataset for the paper: <b>Understanding npm Developers’ Practices, Challenges, and Recommendations for Secure Package Development</b>This paper was accepted for publication at the 19th IEEE/ACM International Conference on Cooperative and Human Aspects of Software Engineering (CHASE 2026) - Research TrackOverviewBelow describes the artifacts associated with this study.<code>SurveyResponses.sqlite</code> --- Survey responses in Sqlite database.<code>SurveyQuestionnaire.pdf</code> --- Survey questionnaire, including response options, utilized in the study.<code>Survey_Free_Text_Reponses_Categorized_Thematic_Analysis.xlsx</code> --- Results of the thematic analysis for the free-text questions.<code>Singlechoice-ranking-questions.xlsx</code> --- Results of the single-choice and ranking question types.<code>code/</code><code>MultiChoiceAnalysis.py</code> --- Class that builds frequency tables for single and multi-choice questions, computes average/median number of choices, performs pair/triplet combination analysis, and saves CSV/text outputs to <code>multichoice-questions/</code>.<code>main-npmPackageSecurity.py</code> --- Main orchestration script. Reads <code>SurveyResponses.csv</code>, runs <code>MultiChoiceAnalysis</code>, generates Likert charts (via <code>plot_likert</code>) and saves PDFs to <code>likert-figures/</code>.<code>SurveyResponses.csv</code> --- Survey responses in CSV (input).<code>likert-figures/</code> --- Output folder (created by <code>main-npmPackageSecurity.py</code>) containing generated Likert PDF figures.<code>multichoice-questions/</code> --- Output folder (created by <code>MultiChoiceAnalysis.py</code>) containing:single-choice and multi-choice frequency CSVscombination analysis CSVs for pairs/tripletssummary text files with average/median choicesCode OutputsLikert chart PDFs: saved to <code>likert-figures/</code>Frequency and combination CSVs + stats: saved to <code>multichoice-questions/</code>Code Dependencies<code>pandas</code><code>matplotlib</code><code>plot_likert</code>Code executionPlace <code>SurveyResponses.csv</code> in the project parent directory.From project root run:<code>python code/main-npmPackageSecurity.py</code>This will create <code>likert-figures/</code> and <code>multichoice-questions/</code> and write outputs.NotesVerify column names in <code>SurveyResponses.csv</code> match those referenced in the scripts before running.Output folders are created automatically by the scripts if missing.<br>
DOI: 10.57760/sciencedb.j00207.00051
title: Appendix for “Stand-Alone Tensor Neural Network for Hyperspectral Image Classification”
title: Appendix for “Stand-Alone Tensor Neural Network for Hyperspectral Image Classification”

description: This appendix file contains supporting data tables, comparative experimental results and supporting figures for the main article "Stand-Alone Tensor Neural Network for Hyperspectral Image Classification": Tables S.1 through S.6 and Figures S.1 through S.4.  
description: This appendix file contains supporting data tables, comparative experimental results and supporting figures for the main article "Stand-Alone Tensor Neural Network for Hyperspectral Image Classification": Tables S.1 through S.6 and Figures S.1 through S.4.
DOI: 10.15468/dl.uq48b6
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Telmatobius carrillae"
 ]
}

 The dataset includes 37 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005959-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jsdj8x
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.60111000000001 24.825288, 88.523742 24.819711, 88.4483 24.803119, 88.37665800000001 24.775923, 88.310596 24.738802, 88.251749 24.692676, 88.20157 24.638691, 88.161289 24.578185, 88.131891 24.512656, 88.11408299999999 24.443723, 88.10828600000001 24.373089, 88.11462299999999 24.302493, 88.132919 24.233672, 88.162705 24.168317, 88.20323399999999 24.108031, 88.25349900000001 24.054289, 88.31225999999999 24.008407, 88.378074 23.971505, 88.44932799999999 23.944484, 88.524283 23.928004, 88.60111000000001 23.922465, 88.677937 23.928004, 88.752892 23.944484, 88.824146 23.971505, 88.88996 24.008407, 88.94872100000001 24.054289, 88.998986 24.108031, 89.03951499999999 24.168317, 89.069301 24.233672, 89.087597 24.302493, 89.093934 24.373089, 89.088137 24.443723, 89.070329 24.512656, 89.040931 24.578185, 89.00064999999999 24.638691, 88.95047099999999 24.692676, 88.89162399999999 24.738802, 88.82556200000001 24.775923, 88.75391999999999 24.803119, 88.678478 24.819711, 88.60111000000001 24.825288))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005960-260120142942310/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.31130527
title: Hybrid GPR-DNN Enhanced NSGA-II

description: 它构建了一个基于高斯过程回归（GPR）增强数据增强的深度学习优化框架。该方法利用GPR的贝叶斯推断能力在稀疏样本间插值，从而使神经网络能够捕捉传统方法可能忽略的复杂物理特征
DOI: 10.6084/m9.figshare.31130527.v1
title: Hybrid GPR-DNN Enhanced NSGA-II

description: 它构建了一个基于高斯过程回归（GPR）增强数据增强的深度学习优化框架。该方法利用GPR的贝叶斯推断能力在稀疏样本间插值，从而使神经网络能够捕捉传统方法可能忽略的复杂物理特征
DOI: 10.5281/zenodo.18327357
title: Rapid outer-size expansion of typhoon Hinnamnor (2022): Role of merger with a tropical depression

description: Data for figures in paper and support information, including the simulated and observed tropical cyclone track, intensity, and size in two experiments. 

The data of surface wind field, AAM budget terms, vorticity, rada reflectivity, etc.
DOI: 10.5281/zenodo.18327358
title: Rapid outer-size expansion of typhoon Hinnamnor (2022): Role of merger with a tropical depression

description: Data for figures in paper and support information, including the simulated and observed tropical cyclone track, intensity, and size in two experiments. 

The data of surface wind field, AAM budget terms, vorticity, rada reflectivity, etc.
DOI: 10.15468/dl.eaha69
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.60111000000001 24.825288, 88.523742 24.819711, 88.4483 24.803119, 88.37665800000001 24.775923, 88.310596 24.738802, 88.251749 24.692676, 88.20157 24.638691, 88.161289 24.578185, 88.131891 24.512656, 88.11408299999999 24.443723, 88.10828600000001 24.373089, 88.11462299999999 24.302493, 88.132919 24.233672, 88.162705 24.168317, 88.20323399999999 24.108031, 88.25349900000001 24.054289, 88.31225999999999 24.008407, 88.378074 23.971505, 88.44932799999999 23.944484, 88.524283 23.928004, 88.60111000000001 23.922465, 88.677937 23.928004, 88.752892 23.944484, 88.824146 23.971505, 88.88996 24.008407, 88.94872100000001 24.054289, 88.998986 24.108031, 89.03951499999999 24.168317, 89.069301 24.233672, 89.087597 24.302493, 89.093934 24.373089, 89.088137 24.443723, 89.070329 24.512656, 89.040931 24.578185, 89.00064999999999 24.638691, 88.95047099999999 24.692676, 88.89162399999999 24.738802, 88.82556200000001 24.775923, 88.75391999999999 24.803119, 88.678478 24.819711, 88.60111000000001 24.825288))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005962-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dmg7nd
title: Occurrence Download

description: A dataset containing 65 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euroscaptor",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation)"
 ]
}

 The dataset includes 65 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005963-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qpeg9m
title: Occurrence Download

description: A dataset containing 189 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Geometry POLYGON((108.21 29.05,116.07 29.05,116.07 33.2,108.21 33.2,108.21 29.05))",
 "TaxonKey is Forsythia suspensa"
 ]
}

 The dataset includes 189 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005964-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eaefht
title: Occurrence Download

description: A dataset containing 345859 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Danaus plexippus",
 "Year 2015-2026"
 ]
}

 The dataset includes 345859 records from 132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005911-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.38fef3
title: Occurrence Download

description: A dataset containing 317898 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (United States of America, Canada, Mexico)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Danaus plexippus",
 "Year 2015-2026"
 ]
}

 The dataset includes 317898 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005918-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.