cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11369152
title: Dataset: Predicting relative agronomic efficiency of phosphorus-rich organic residues
DOI: 10.15468/dl.nwyr2n
title: Occurrence Download

description: A dataset containing 870 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mustela sibirica Pallas, 1773"
 ]
}

 The dataset includes 870 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0138589-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11369151
title: Dataset: Predicting relative agronomic efficiency of phosphorus-rich organic residues
DOI: 10.15468/dl.m8gdb4
title: Occurrence Download

description: A dataset containing 362 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ghana",
 "TaxonKey is Elaeis guineensis Jacq."
 ]
}

 The dataset includes 362 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0075280-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.po239p
title: Occurrence Download

description: A dataset containing 6943 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chaoborus A.A.H.Lichtenstein, 1800"
 ]
}

 The dataset includes 6943 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0070031-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.at72te
title: Occurrence Download

description: A dataset containing 65518 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hippophae rhamnoides L."
 ]
}

 The dataset includes 65518 records from 398 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0144207-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ckxwxc
title: Occurrence Download

description: A dataset containing 36247139 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Poaceae"
 ]
}

 The dataset includes 36247139 records from 1937 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002427-171124123535762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w35hw6
title: Occurrence Download

description: A dataset containing 13832746 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-114.60596 -58.89027,-30.60498 -58.89027,-30.60498 24.0715,-114.60596 24.0715,-114.60596 -58.89027))",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 13832746 records from 1072 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059352-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/334wbvg55z
title: Data: Himalayan fir growth in central Bhutan reflects variability in temperature and precipitation

description: This dataset contains the data and R code for the article “Himalayan fir growth in central Bhutan reflects variability in temperature and precipitation” (Lehejček et al., 2025). 

It contains the following data files: 
- TRW: tree-ring widths;
- precipitation: total monthly precipitation (CRU TS v4.08 dataset);
- temperature: average monthly air temperature (CRU TS v4.08 dataset).

Further information can be found in the article:
Lehejček J., Vávrů G., Wangchuk S., Svoboda M., Boonen K. (2025): Himalayan fir growth in central Bhutan reflects variability in temperature and precipitation. J. For. Sci.
DOI: 10.17632/334wbvg55z.1
title: Data: Himalayan fir growth in central Bhutan reflects variability in temperature and precipitation

description: This dataset contains the data and R code for the article “Himalayan fir growth in central Bhutan reflects variability in temperature and precipitation” (Lehejček et al., 2025). 

It contains the following data files: 
- TRW: tree-ring widths;
- precipitation: total monthly precipitation (CRU TS v4.08 dataset);
- temperature: average monthly air temperature (CRU TS v4.08 dataset).

Further information can be found in the article:
Lehejček J., Vávrů G., Wangchuk S., Svoboda M., Boonen K. (2025): Himalayan fir growth in central Bhutan reflects variability in temperature and precipitation. J. For. Sci.
DOI: 10.17632/jgsv28b7ss
title: Tables S1-S3 for the paper on Mg isotope geochemistry in continental flood basalts

description: The data supporting the study of magnesium isotope geochemistry in continental flood basalts, including Table S1 containing Sr-Nd isotope data, Table S2 with trace element and isotopic compositions of the endmembers used in the geochemical modeling, and Table S3 with major-trace element compositions and platinum-group element data for two samples of the SCFBs.
DOI: 10.17632/jgsv28b7ss.1
title: Tables S1-S3 for the paper on Mg isotope geochemistry in continental flood basalts

description: The data supporting the study of magnesium isotope geochemistry in continental flood basalts, including Table S1 containing Sr-Nd isotope data, Table S2 with trace element and isotopic compositions of the endmembers used in the geochemical modeling, and Table S3 with major-trace element compositions and platinum-group element data for two samples of the SCFBs.
DOI: 10.17632/rt8sv9t445.1
title: S2RMCMD

description: it is a plant disease dataset of sugarcane and rice crops. it consist of 16 sugarcane crops disease and 4 rice crops disease.
DOI: 10.15468/dl.pk7cj2
title: Occurrence Download

description: A dataset containing 230 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-42.97334 -22.95203,-42.97014 -22.94878,-42.96325 -22.94615,-42.95719 -22.94041,-42.95349 -22.93096,-42.95046 -22.92601,-42.9508 -22.91826,-42.95736 -22.91981,-42.97048 -22.93143,-42.97502 -22.94119,-42.97334 -22.95203))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 230 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001587-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/nrp7zhm7tx.2
title: Combinatorial and Algebraic Modeling data

description: This is the dataset used to obtain more information via a combinatorial (pairwise) method to compare how energy is partitioned when different additives are supplemented in poultry
DOI: 10.17632/k7npp2smrm
title: Limnocorral greenhouse gases

description: This dataset includes measured surface concentration and emissions data for CO2, CH4, and N2O for limnocorrals installed in 3 ponds at the Ole Miss Field Station in Abbeville, MS USA. The dataset also includes water temperature and oxygen data for all limnocorrals as well as water chemistry.
DOI: 10.17632/k7npp2smrm.1
title: Limnocorral greenhouse gases

description: This dataset includes measured surface concentration and emissions data for CO2, CH4, and N2O for limnocorrals installed in 3 ponds at the Ole Miss Field Station in Abbeville, MS USA. The dataset also includes water temperature and oxygen data for all limnocorrals as well as water chemistry.
DOI: 10.15468/dl.3k75h8
title: Occurrence Download

description: A dataset containing 6361 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corella parallelogramma"
 ]
}

 The dataset includes 6361 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001589-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.awmcrm
title: Occurrence Download

description: A dataset containing 6236 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Conopeum reticulum"
 ]
}

 The dataset includes 6236 records from 108 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001588-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/cg65h3jhf5.3
title: Ecosystem Services Indicators for the Medicinal and Aromatic Potential of poorly studied Plant Taxa: an Application on the Endemic Flora of the Peloponnese, Greece

description: Article's abstract: The interest in new natural products and herbal raw materials increases in a variety of scientific and industrial fields, but many plant taxa of restricted distribution tend to be overlooked as potential assets. Their large number precludes their study and valorization. Therefore, there is a dire need to develop tools for assessing the plant taxa potential as ecosystem service providers, to prioritize the research efforts and to enhance conservation priorities. With the aim to identify taxa of interest as potential medicinal and aromatic plants (MAP), among the taxa of a given flora, we developed a set of indicators. These indicators are based on the available scientific literature and are formulated even for taxa of restricted distribution, based on their closely related species in terms of phylogeny, taxonomy (same species, or same genus within the flora), or in use as approved herbal medicine or edible crop. The developed indicators are herein applied to the endemic flora of the Peloponnese, a floristic region of Greece with high total- and
endemic- species diversity. Even though only 12.5% of the endemic taxa have previously been documented as MAP, the use of indicators suggests 58.3% of the flora as of non-null MAP potential (Indicator I1), while 74.1% of the taxa obtained a non-null value of Study Interest Index (Indicator I2). The results suggest 25 taxa as of high MAP potential, whereas 24 taxa are emphasized as of high-priority for further studies. This is, to our knowledge, the first attempt to establish a systematic literature-based method to assess
potentially significant edible, medicinal and/or aromatic taxa.

This dataset contains:
FULL: The basic dataset of properties and components for the studied flora and its relatives, with calculated variables of use in the calculation of the indicators, and values of indicators, per taxon.
C0: The calculation of the four indices based on the formulas for the endemic flora of the Peloponnese.
C1: The medicinal/aromatic properties of the endemic taxa and the corresponding references.
C2: The medicinal/aromatic properties of the phylogeny and species-level related taxa, the corresponding references, and the correspondences between endemics and related taxa.
C3: The list of 'Outstanding' related taxa with their properties.
C4: The description of the chemical compositions for the extracts of the endemics/relatives, with their correspondences.
C5: The form used to test the indices, and the results of the test.
Review...: The full bibliography related to the properties of the endemic and related taxa.
DOI: 10.17632/zs2mbjv7dn
title: Biased sampling confounds machine learning prediction of antimicrobial resistance

description: Antimicrobial resistance (AMR) poses a growing threat to human health. Increasingly, genome sequencing is being applied for surveillance of bacterial pathogens, producing a wealth of data to train machine learning (ML) applications to predict AMR and identify resistance determinants. However, bacterial populations are highly structured and sampling is biased towards human disease isolates, meaning samples and derived features are not independent. This is rarely considered in applications of ML to AMR. Here, we demonstrate the confounding effects of sample structure by collecting over 24,000 whole genome sequences and AMR phenotypes from five diverse pathogens and constructing realistic pathological training data where resistance is confounded with phylogeny. We show resulting ML models perform poorly, and increasing the training sample size fails to rescue performance. A comprehensive analysis of 6,740 models identifies species- and drug-specific effects on model accuracy. We provide concrete recommendations for evaluating future ML approaches to AMR.
DOI: 10.17632/zs2mbjv7dn.3
title: Biased sampling confounds machine learning prediction of antimicrobial resistance

description: Antimicrobial resistance (AMR) poses a growing threat to human health. Increasingly, genome sequencing is being applied for surveillance of bacterial pathogens, producing a wealth of data to train machine learning (ML) applications to predict AMR and identify resistance determinants. However, bacterial populations are highly structured and sampling is biased towards human disease isolates, meaning samples and derived features are not independent. This is rarely considered in applications of ML to AMR. Here, we demonstrate the confounding effects of sample structure by collecting over 24,000 whole genome sequences and AMR phenotypes from five diverse pathogens and constructing realistic pathological training data where resistance is confounded with phylogeny. We show resulting ML models perform poorly, and increasing the training sample size fails to rescue performance. A comprehensive analysis of 6,740 models identifies species- and drug-specific effects on model accuracy. We provide concrete recommendations for evaluating future ML approaches to AMR.
DOI: 10.17632/7yxvpbdkjm
title: Features for BIM annotations

description: The current dataset is prepared to feed ML algorithms for door element annotation in buildings. The data are used to annotate 'Exits', 'Apartment Exits' and 'Normal Doors' on BIM model of high rise buildings in Belgium. For each door sample 13 features are defined and automatically extracted from Revit models.
The datasets comprise manually labeled data with 2677 door samples from four high-rise building models, containing 217 'Exit' and 361 'Apartment Exit', and the remainder as 'Normal Doors' each with 13 attributes.
DOI: 10.17632/7yxvpbdkjm.1
title: Features for BIM annotations

description: The current dataset is prepared to feed ML algorithms for door element annotation in buildings. The data are used to annotate 'Exits', 'Apartment Exits' and 'Normal Doors' on BIM model of high rise buildings in Belgium. For each door sample 13 features are defined and automatically extracted from Revit models.
The datasets comprise manually labeled data with 2677 door samples from four high-rise building models, containing 217 'Exit' and 361 'Apartment Exit', and the remainder as 'Normal Doors' each with 13 attributes.
DOI: 10.17632/v4h43wtnyb
title: Incorporating 3D-Printed Polymer Scaffolds onto MEMS Resonant Chemical Sensors for Enhanced Performance

description: For Spray Coated PECH, Gyroid IP-PDMS, and Gyroid PUT, the sensitivity response to various concentrations of ethylbenzene, M-xylene, and toluene was simultaneously recorded. The sensitivity difference between two sensors with different sensing film geometry in the tested concentration range is highlighted by the relative frequency change for a 5-µm height gyroid PUT (Brown) and block PUT (Blue) as a function of the analyte concentration for ethylbenzene, M-xylene, and toluene. relative frequency change as a function of the low analyte concentration for M-xylene and toluene for a 5-µm height gyroid PUT (green) on the topside and gyroid PUT (purple) on both sides. In the tested concentration range, this plot illustrates the sensitivity difference between two sensors with distinct sensing film coating regions.
DOI: 10.17632/v4h43wtnyb.1
title: Incorporating 3D-Printed Polymer Scaffolds onto MEMS Resonant Chemical Sensors for Enhanced Performance

description: For Spray Coated PECH, Gyroid IP-PDMS, and Gyroid PUT, the sensitivity response to various concentrations of ethylbenzene, M-xylene, and toluene was simultaneously recorded. The sensitivity difference between two sensors with different sensing film geometry in the tested concentration range is highlighted by the relative frequency change for a 5-µm height gyroid PUT (Brown) and block PUT (Blue) as a function of the analyte concentration for ethylbenzene, M-xylene, and toluene. relative frequency change as a function of the low analyte concentration for M-xylene and toluene for a 5-µm height gyroid PUT (green) on the topside and gyroid PUT (purple) on both sides. In the tested concentration range, this plot illustrates the sensitivity difference between two sensors with distinct sensing film coating regions.
DOI: 10.17632/6rd6pbd4rb.1
title: PENTEX II

description: MSCA project PENTEX
DOI: 10.17632/c9kv89yknn
title: Experimental results dataset on two-storey balloon-framed CLT shear wall structures

description: This dataset provides information on the performance of balloon-framed CLT shear walls, tested under reversed cyclic loading considering different hold-down and vertical joint configurations. The dataset provides the detailed input to develop and validate analytical and numerical models for balloon-framed CLT shear walls. The dataset consists of nine Excel files, corresponding to the nine test structures. Each Excel file has one sheet labelled “data” where all recorded loads and displacements are listed and one sheet labelled “plots”, were all displacements are plotted.
DOI: 10.17632/c9kv89yknn.1
title: Experimental results dataset on two-storey balloon-framed CLT shear wall structures

description: This dataset provides information on the performance of balloon-framed CLT shear walls, tested under reversed cyclic loading considering different hold-down and vertical joint configurations. The dataset provides the detailed input to develop and validate analytical and numerical models for balloon-framed CLT shear walls. The dataset consists of nine Excel files, corresponding to the nine test structures. Each Excel file has one sheet labelled “data” where all recorded loads and displacements are listed and one sheet labelled “plots”, were all displacements are plotted.
DOI: 10.17632/2w7f7vb3bj
title: A multicenter clinical evaluation of polymerase chain reaction coupled with quantum dot fluorescence analysis and quantitative real-time reverse transcription polymerase chain reaction in the diagnosis of pathogens

description: This multi-center clinical study evaluated 17 common pathogens in 1,922 pharyngeal swab samples, comparing the diagnostic performance of polymerase chain reaction coupled with quantum dot fluorescence analysis (PCR-QDFA) with that of clinically routine quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). The results were validated using Sanger sequencing as the gold standard. Our results showed that among the samples with single-pathogen infections (1037 cases, 53.95%), the three most frequently detected pathogen were influenza A virus (IAV) (296 cases, 15.40%), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (164 cases, 8.53%), and Mycoplasma pneumoniae (94 cases, 4.89%). Similarly, among the samples with co-infections of two or more pathogens (382 cases, 19.88%), the three most frequently detected pathogens were IAV (148 cases, 7.70%), SARS-CoV-2 (107 cases, 5.57%), and M. pneumoniae (67 cases, 3.49%). In the comprehensive evaluation of 17 respiratory pathogens, PCR-QDFA demonstrated comparable diagnostic performance to qRT-PCR, with an overall sensitivity of 99.78% (99.44–99.92%) (vs. qRT-PCR: 99.82% [99.48–99.94%]) and specificity of 99.94% (99.90–99.96%) (vs. qRT-PCR: 99.95% [99.91–99.97%]). PCR-QDFA offers significant operational advantages, including high-throughput capacity (96 samples per run) and lower cost.
DOI: 10.17632/2w7f7vb3bj.1
title: A multicenter clinical evaluation of polymerase chain reaction coupled with quantum dot fluorescence analysis and quantitative real-time reverse transcription polymerase chain reaction in the diagnosis of pathogens

description: This multi-center clinical study evaluated 17 common pathogens in 1,922 pharyngeal swab samples, comparing the diagnostic performance of polymerase chain reaction coupled with quantum dot fluorescence analysis (PCR-QDFA) with that of clinically routine quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). The results were validated using Sanger sequencing as the gold standard. Our results showed that among the samples with single-pathogen infections (1037 cases, 53.95%), the three most frequently detected pathogen were influenza A virus (IAV) (296 cases, 15.40%), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (164 cases, 8.53%), and Mycoplasma pneumoniae (94 cases, 4.89%). Similarly, among the samples with co-infections of two or more pathogens (382 cases, 19.88%), the three most frequently detected pathogens were IAV (148 cases, 7.70%), SARS-CoV-2 (107 cases, 5.57%), and M. pneumoniae (67 cases, 3.49%). In the comprehensive evaluation of 17 respiratory pathogens, PCR-QDFA demonstrated comparable diagnostic performance to qRT-PCR, with an overall sensitivity of 99.78% (99.44–99.92%) (vs. qRT-PCR: 99.82% [99.48–99.94%]) and specificity of 99.94% (99.90–99.96%) (vs. qRT-PCR: 99.95% [99.91–99.97%]). PCR-QDFA offers significant operational advantages, including high-throughput capacity (96 samples per run) and lower cost.