cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29132717
title: <b>Contribution of range-wide and short-scale chemical soil variation to local adaptation in a tropical montane forest tree</b>

description: Local adaptation is a fundamental process that allows populations to thrive in their native environment, often increasing genetic differentiation with neighboring stands. However, detecting the molecular basis and selective factors responsible for local adaptation remains a challenge, particularly in sessile, non-model species with long life cycles, such as forest trees. Local adaptation in trees is not only modeled by climatic factors, but also by soil variation. Such variation depends on dynamic geological and ecological processes that generate a highly heterogeneous selective mosaic that may differentially condition tree adaptation both at the range-wide and local scales. This could be particularly manifest in species inhabiting mountain ranges that were formed by diverse geological events, like sacred fir (<i>Abies religiosa</i>), a conifer endemic to the mountains of central Mexico. Here, we used landscape genomics approaches to investigate how chemical edaphic variation influences the genetic structure of this species at the range-wide and local scales. After controlling for neutral genetic structure, we performed genotype-environment associations, and identified 49 and 23 candidate SNPs at the range-wide and local scales, respectively, with little overlap between scales. We then developed polygenic models with such candidates, which accounted for ~20% of the range-wide variation in soil <i>Ca</i><sup>2+</sup> concentration, electric conductivity (<i>EC</i>), and <i>pH</i>, and for the local variation in soil <i>EC</i> and organic carbon content (<i>OC</i>). Spatial Principal Component Analyses further highlighted the role of geography and populationsolation in explaining this genetic-soil co-variation. Our findings reveal that local adaptation in trees is the result of an intricate interaction between soil chemical properties and the local population’s genetic makeup, and that the selective factors driving such adaptation greatly vary and are not necessarily predictable across spatial scales. These results highlight the need to consider edaphic variation in forest genetic studies (including common garden experiments), and in conservation, management and assisted migration programs.
DOI: 10.6084/m9.figshare.29132717.v1
title: <b>Contribution of range-wide and short-scale chemical soil variation to local adaptation in a tropical montane forest tree</b>

description: Local adaptation is a fundamental process that allows populations to thrive in their native environment, often increasing genetic differentiation with neighboring stands. However, detecting the molecular basis and selective factors responsible for local adaptation remains a challenge, particularly in sessile, non-model species with long life cycles, such as forest trees. Local adaptation in trees is not only modeled by climatic factors, but also by soil variation. Such variation depends on dynamic geological and ecological processes that generate a highly heterogeneous selective mosaic that may differentially condition tree adaptation both at the range-wide and local scales. This could be particularly manifest in species inhabiting mountain ranges that were formed by diverse geological events, like sacred fir (<i>Abies religiosa</i>), a conifer endemic to the mountains of central Mexico. Here, we used landscape genomics approaches to investigate how chemical edaphic variation influences the genetic structure of this species at the range-wide and local scales. After controlling for neutral genetic structure, we performed genotype-environment associations, and identified 49 and 23 candidate SNPs at the range-wide and local scales, respectively, with little overlap between scales. We then developed polygenic models with such candidates, which accounted for ~20% of the range-wide variation in soil <i>Ca</i><sup>2+</sup> concentration, electric conductivity (<i>EC</i>), and <i>pH</i>, and for the local variation in soil <i>EC</i> and organic carbon content (<i>OC</i>). Spatial Principal Component Analyses further highlighted the role of geography and populationsolation in explaining this genetic-soil co-variation. Our findings reveal that local adaptation in trees is the result of an intricate interaction between soil chemical properties and the local population’s genetic makeup, and that the selective factors driving such adaptation greatly vary and are not necessarily predictable across spatial scales. These results highlight the need to consider edaphic variation in forest genetic studies (including common garden experiments), and in conservation, management and assisted migration programs.
DOI: 10.15468/dl.thsywa
title: Occurrence Download

description: A dataset containing 360384 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Colias fieldii Ménétriès, 1855, Eristalinus taeniops (Wiedemann, 1818), Eoanthidium salemense (Cockerell, 1919), Leades rufina Jacobi, 1928, Phaethornis longuemareus (R.Lesson, 1832), Saucerottia tobaci (J.F.Gmelin, 1788), Zosterops novaeguineae Salvadori, 1878, Oreocharis arfaki (A.B.Meyer, 1875), Melanocharis longicauda Salvadori, 1876, Ailuroedus melanotis (G.R.Gray, 1858), Pycnopygius cinereus (P.L.Sclater, 1874), Melipotes fumigatus A.B.Meyer, 1886, Gymnophaps albertisii Salvadori, 1874, Phonygammus keraudrenii (Lesson & Garnot, 1826), Treron apicauda Blyth, 1846, Treron sphenurus (Vigors, 1832), Treron curvirostra (J.F.Gmelin, 1789), Ducula badia (Raffles, 1822), Rhabdornis mystacalis (Temminck, 1825), Rhabdotorrhinus waldeni (Sharpe, 1877), Zosterops nigrorum Tweeddale, 1878, Ptenochirus jagorii (Peters, 1861), Ducula poliocephala (G.R.Gray, 1844), Hypsipetes philippinus (J.R.Forster, 1795), Penelopides panini (Boddaert, 1783), Presbytis thomasi (Collett, 1893), Sus cebifrons Heude, 1888, Treron pompadora (J.F.Gmelin, 1789), Phapitreron leucotis (Temminck, 1823), Ptilinopus rivoli (Prévost, 1843), Lophorina superba (J.R.Forster, 1781), Paradisaea rudolphi (Finsch & A.B.Meyer, 1885), Hylobates lar (Linnaeus, 1771), Parotia lawesii E.P.Ramsay, 1885, Sarcops calvus (Linnaeus, 1766), Diphyllodes magnificus (J.R.Forster, 1781), Chalcophaps indica (Linnaeus, 1758), Ptilinopus occipitalis G.R.Gray, 1844, Macropygia tenuirostris Bonaparte, 1854, Amyema fasciculata (Blume) Danser, Trabala vishnou (Lefèbvre, 1827), Ecpatia longinquua, Coloana arcuata Dworakowska, 1981, Plumosa nigrimaculata Song & Li, 2008, Thaia subrufa (Motschulsky, 1863), Coloana bischofiae Sohi, 1977, Dryadomorpha pallida Kirkaldy, 1906, Histia flabellicornis ultima Hering, 1922, Histia flabellicornis (Fabricius, 1775), Actias ningpoana Felder, 1862)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 360384 records from 292 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014921-250515123054153/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.25254592
title: Data and code from: Effectiveness of temporal matching in ecological niche models: Insights for a low-dispersing species

description: This repository contains the data and R scripts used in the study "Effectiveness of temporal matching in ecological niche models: Insights for a low-dispersing species."The study focuses on the Mexican small-eared shrew (Cryptotis mexicanus) and compares the performance of ENMs built with environmental data averaged over different temporal resolutions (one-, five-, and ten-year periods, aligned with occurrence dates) against the standard approach using 30-year climatic averages.<br>
DOI: 10.6084/m9.figshare.28645046
title: What does colonisation tell us? Revisiting the functional outcomes of root colonisation by arbuscular mycorrhizal

description: Data associated with study exploring relationships between colonisation of roots by arbuscular mycorrhizal (AM) fungi and the host plant growth, phosphorus, and phenolic responses to the symbiosis.<br><b>Data.csv</b> file contains plant growth, phosphorus, phenolic data alongside root-length colonised data.<b>colonisation_plots.R</b> file contains script for generating plots in R.
DOI: 10.15468/dl.sukeze
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peromyscus hooperi Lee & Schmidly, 1977",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014928-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15492847
title: Barriers to Use: Perspectives on Research Software data

description: Data, code, and figures for quality-in-use survey evalution of research software.
DOI: 10.5281/zenodo.15492848
title: Barriers to Use: Perspectives on Research Software data

description: Data, code, and figures for quality-in-use survey evalution of research software.
DOI: 10.5281/zenodo.15486736
title: eSIG-Net(Edgetic Mutation Sequence based interaction grammar)

description: datasets for eSIG-Net model training and evaluation.
DOI: 10.5281/zenodo.15486737
title: eSIG-Net(Edgetic Mutation Sequence based interaction grammar)

description: datasets for eSIG-Net model training and evaluation.
DOI: 10.15468/dl.hcem6e
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peromyscus hylocetes Merriam, 1898",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 15 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014934-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w72ry8
title: Occurrence Download

description: A dataset containing 9991 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chelostoma campanularum (Kirby, 1802)"
 ]
}

 The dataset includes 9991 records from 154 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014933-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ew7r4f
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Caudofoveata)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((90 60,120 60,120 90,90 90,90 60))"
 ]
}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012228-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qcpbh7
title: Occurrence Download

description: A dataset containing 1053 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scleria microcarpa Nees ex Kunth)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1053 records from 119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089540-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hxujct
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scleria corymbosa Roxb.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 14 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089541-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w5axt3
title: Occurrence Download

description: A dataset containing 17707 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chaerephon pumilus (Cretzschmar, 1826)"
 ]
}

 The dataset includes 17707 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089542-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nkhjkx
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scleria sieberi Nees)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089543-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/19934783
title: Acceptance of a Virtual Coach for Quitting Smoking and Becoming Physically Active: Dataset

description: <strong>Study</strong>The data was gathered during a longitudinal study on the online crowdsourcing platform Prolific between 20 May 2021 and 30 June 2021. The Human Research Ethics Committee of Delft University of Technology granted ethical approval for the research (Letter of Approval number: 1523). In this study, smokers who were contemplating or preparing to quit smoking interacted with the text-based virtual coach Sam in up to five conversational sessions. In each session, participants were assigned a new preparatory activity for quitting smoking, such as thinking of and writing down reasons for quitting smoking. After the five sessions, participants filled in a post-questionnaire in which they were asked about their acceptance of Sam. Participants answered six acceptance questions, and provided a rating and a free-text response for each of them.The study was pre-registered in the Open Science Framework (OSF): https://osf.io/k2uac. This pre-registration describes the study design, measures, etc. Note that this dataset contains only part of the collected data, namely, the data related to studying the acceptance of the virtual coach.The implementation of the virtual coach Sam can be found here: https://doi.org/10.5281/zenodo.6319356. There you can also find a list of the 24 preparatory activities used in the study (Activities.xlsx).<br><strong>Data</strong>This dataset contains four types of data:<strong>Data from participants' Prolific profiles</strong>. This includes data on demographics (e.g., age range, household size) as well as smoking and physical activity behavior (e.g., weekly exercise amount).<strong>Data from a pre-screening questionnaire</strong>. This includes, for example, the responses to informed consent questions.<strong>Data from a pre-questionnaire</strong>. This includes data on smoking and physical activity behavior, as well as personality and need for cognition.<strong>Data from a post-questionnaire</strong>. This includes data on the acceptance of the virtual coach as well as doing the preparatory activities.There is a separate data file for each type of data.<br><strong>Analysis</strong>Parts of the dataset have been used to study the acceptance of the virtual coach. Examples include: Examining people's relationship and willingness to continue working with a virtual smoking cessation coach (see this peer-reviewed paper: https://doi.org/10.1007/978-3-031-30933-5_17), andInvestigating the acceptance of a virtual coach as a guided intervention for quitting smoking (see the bachelor's thesis by Jaap Dechering: http://resolver.tudelft.nl/uuid:71038d25-9a5a-4068-b22f-fa37b0be23aa).
DOI: 10.4121/19936487
title: Data and results for the bachelor thesis: Reasons to continue or stop using a virtual coach for quitting smoking and increasing physical activity: A mixed-methods analysis.

description: This dataset contains data and results from the analysis conducted for the bachelor thesis, "Reasons to continue or stop using a virtual coach for quitting smoking and increasing physical activity: A mixed-methods analysis.". In this study, a mixed-methods analysis (thematic analysis, quantitative analysis, and a literature study) was carried out to find out what the reasons are for wanting to stop or continue using a virtual coach. By using triangulation, themes were found. Based on these themes, recommendations have been given on how to improve the virtual coach.
DOI: 10.4121/20066186
title: Acceptance of a Virtual Coach as Guided Intervention for Smoking Cessation: Dataset

description: This dataset contains data and analysis that was used during a study into the acceptance of a virtual coach as guided intervention for smoking cessation. This study aimed to discover why people might or might not accept a virtual coach for smoking cessation. This study was conducted as a bachelor thesis and made use of the original dataset https://doi.org/10.4121/19934783.v1. The study is part of the Perfect Fit project which is funded by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), with project number 628.011.211.
DOI: 10.4121/20099102
title: Data and code underlying the bachelor thesis: Traits for a virtual coach to be a ”friend”

description: This dataset contains data and code snippets from the analysis performed during the thesis, "Traits for a virtual coach to be a friend". Here, an investigation has taken place to what characteristics the virtual coach must possess to establish this friendly relationship. Thus, the main research question is: <strong>What are the reasons for seeing the virtual coach as a stranger or friend?</strong> This research has been based on a retrospective study performed by Albers and Brinkman. Here, five hundred participants interacted with the text-based virtual coach Sam - developed for the Perfect Fit project to convince smokers to quit by performing small activities - in five separate sessions. Afterwards, each participant rated the relationship with the virtual coach, followed by an explanatory free-text response to which thematic analysis was applied. The quality of the thematic analysis has been ensured by researcher and method triangulation. Researcher triangulation, where multiple researchers were involved, determined the reliability of the coding scheme generated during thematic analysis. Method triangulation, which supported the findings, was executed with the free-text responses, literature, and quantitative data, containing demographic and smoke-related characteristics.
DOI: 10.15468/dl.b8r442
title: Occurrence Download

description: A dataset containing 2785 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyperus distans L.f.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2785 records from 228 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089546-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3z9try
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyperus elatus L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 56 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089548-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12446058
title: Deep Gradient Reinforcement learning for Music Improvisation in cloud computing framework

description: The improvised music is further rendered in the MIDI format. The Bach Chorales dataset with six different attributes relevant to musical compositions is employed in implementing the present research. The model was set up in a containerised cloud environment and controlled for smooth load distribution. Five different parameters, such as pitch frequency (PF), standard pitch delay (SPD), average distance between peaks (ADP), note duration gradient (NDG) and pitch class gradient (PCG) are leveraged to assess the quality of the improvised music.
DOI: 10.6084/m9.figshare.26074140
title: Additional file 1 of Liquid-based cytology specimens for next-generation sequencing in lung adenocarcinoma: challenges and evaluation of targeted therapy

description: Supplementary Material 1
DOI: 10.48366/r701133
title: Detection approaches in astronomical images

description: In this comparision , we examine the detection strategies employed in different works, highlighting variations in approaches and methodologies. This comparison sheds light on the effectiveness and versatility of various detection strategies in locating astronomical objects within images.
DOI: 10.15468/dl.kwy5a4
title: Occurrence Download

description: A dataset containing 3460 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyperus compressus L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3460 records from 292 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089549-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12446057
title: Deep Gradient Reinforcement learning for Music Improvisation in cloud computing framework

description: The improvised music is further rendered in the MIDI format. The Bach Chorales dataset with six different attributes relevant to musical compositions is employed in implementing the present research. The model was set up in a containerised cloud environment and controlled for smooth load distribution. Five different parameters, such as pitch frequency (PF), standard pitch delay (SPD), average distance between peaks (ADP), note duration gradient (NDG) and pitch class gradient (PCG) are leveraged to assess the quality of the improvised music.
DOI: 10.5281/zenodo.12446277
title: Deep Gradient Reinforcement learning for Music Improvisation in cloud computing framework

description: The improvised music is further rendered in the MIDI format. The Bach Chorales dataset with six different attributes relevant to musical compositions is employed in implementing the present research. The model was set up in a containerised cloud environment and controlled for smooth load distribution. Five different parameters, such as pitch frequency (PF), standard pitch delay (SPD), average distance between peaks (ADP), note duration gradient (NDG) and pitch class gradient (PCG) are leveraged to assess the quality of the improvised music.
DOI: 10.15468/dl.9hxsjy
title: Occurrence Download

description: A dataset containing 23653 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Puma concolor (Linnaeus, 1771)"
 ]
}

 The dataset includes 23653 records from 373 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089550-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.