cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24595638.v1
title: <b>New genus </b><b><i>Valtocarpus</i></b><b> (Myxomycetes = Eumycetozoa): molecular phylogeny and morphological analysis of aethalioid species in the order Stemonitidales</b>

description: <b>The dataset includes:</b><b>Fig. 1</b> with edited three-gene phylogenetic tree in PDFThe <b>Table S1</b> with the list of specimens used for DNA extraction and sequencing and the list of sequences retrieved from GenBankThe <b>File S1</b> with concatenated alignmentPartition file <b>File S2</b> in RAxML formatUnedited three-gene phylogenetic tree <b>File S3</b>
DOI: 10.6084/m9.figshare.24595638
title: <b>New genus </b><b><i>Valtocarpus</i></b><b> (Myxomycetes = Eumycetozoa): molecular phylogeny and morphological analysis of aethalioid species in the order Stemonitidales</b>

description: <b>The dataset includes:</b><b>Fig. 1</b> with edited three-gene phylogenetic tree in PDFThe <b>Table S1</b> with the list of specimens used for DNA extraction and sequencing and the list of sequences retrieved from GenBankThe <b>File S1</b> with concatenated alignmentPartition file <b>File S2</b> in RAxML formatUnedited three-gene phylogenetic tree <b>File S3</b>
DOI: 10.6084/m9.figshare.24591222
title: <b><i>Diachea racemosa</i></b><b> (Myxomycetes = Myxogastrea): a new species with cespitose sporocarps from southern Vietnam and its position within the phylogenetic clade </b><b><i>Diachea</i></b><b> sensu lato (Physarales)</b>

description: <b>The dataset includes:</b><b>Fig. 1</b> and <b>Fig. 2</b> with edited three-gene phylogenetic trees in PDFThe <b>Table S1</b> with the list of specimens used for DNA extraction and sequencing and the list of sequences retrieved from GenBankThe <b>File S1</b> with concatenated alignmentPartition file <b>File S2</b> in RAxML formatUnedited three-gene phylogenetic tree <b>File S3</b><br>
DOI: 10.5281/zenodo.10033362
title: 101223_F1000_datasets
title: From classroom to global goals: A bibliometric analysis of Universitas Indonesia's student projects addressing Sustainable Development Goals (SDG) 3
DOI: 10.5281/zenodo.10033363
title: bibliometricdata_sdgs3
title: From classroom to global goals: A bibliometric analysis of Universitas Indonesia's student projects addressing Sustainable Development Goals (SDG) 3
DOI: 10.5281/zenodo.10336832
title: 101223_F1000_datasets
title: From classroom to global goals: A bibliometric analysis of Universitas Indonesia's student projects addressing Sustainable Development Goals (SDG) 3
DOI: 10.6084/m9.figshare.24783015.v1
title: Masterchart for the 20 landmark data of 60 males and 60 females

description: 120 samples of maxilllary first premolar from dental casts are marked with 20 landmarks each
DOI: 10.6084/m9.figshare.24783015
title: Masterchart for the 20 landmark data of 60 males and 60 females

description: 120 samples of maxilllary first premolar from dental casts are marked with 20 landmarks each
DOI: 10.5517/ccdc.csd.cc25d5pg
title: CCDC 2007705: Experimental Crystal Structure Determination

description: Related Article: Jacqueline C. Calderón, Alberto Herrera, Frank W. Heinemann, Jens Langer, Anthony Linden, Ahmed Chelouan, Alexander Grasruck, Rafael Añez, Timothy Clark, Romano Dorta|2023|J.Org.Chem.|88|16144|doi:10.1021/acs.joc.3c01447
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25kwj5
title: CCDC 2013187: Experimental Crystal Structure Determination

description: Related Article: Jacqueline C. Calderón, Alberto Herrera, Frank W. Heinemann, Jens Langer, Anthony Linden, Ahmed Chelouan, Alexander Grasruck, Rafael Añez, Timothy Clark, Romano Dorta|2023|J.Org.Chem.|88|16144|doi:10.1021/acs.joc.3c01447
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc25kwk6
title: CCDC 2013188: Experimental Crystal Structure Determination

description: Related Article: Jacqueline C. Calderón, Alberto Herrera, Frank W. Heinemann, Jens Langer, Anthony Linden, Ahmed Chelouan, Alexander Grasruck, Rafael Añez, Timothy Clark, Romano Dorta|2023|J.Org.Chem.|88|16144|doi:10.1021/acs.joc.3c01447
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34740/kaggle/dsv/7167825
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.6084/m9.figshare.24783021
title: Packaging waste generation Q survey data

description: The data set is a conusmer survey on packaging size choice.
DOI: 10.5281/zenodo.10336544
title: Ground truth and raw hyperspectral files of olive trees for plant stress detection

description: This dataset contains raw hyperspectral images from Cubert S-185 collected on 13 May 2021 from an olive field in Halkidiki, Northern Greece. Included is also a matrix containing the id of each recorded olive tree (the samples) that also appears in the hyperspectral images. QGIS (ver.3.28.0) software plugin 'zonal statistics multiband' was used to compute zonal statistics for each of the 138 spectral bands available for each sample. Accompanying each sample is also the ground truthing data recorded, which addresses the present stress of 3 stressors (Verticillium dahliae, Pleospora herbarum and 'other stressors').
DOI: 10.5281/zenodo.10336545
title: Ground truth and raw hyperspectral files of olive trees for plant stress detection

description: This dataset contains raw hyperspectral images from Cubert S-185 collected on 13 May 2021 from an olive field in Halkidiki, Northern Greece. Included is also a matrix containing the id of each recorded olive tree (the samples) that also appears in the hyperspectral images. QGIS (ver.3.28.0) software plugin 'zonal statistics multiband' was used to compute zonal statistics for each of the 138 spectral bands available for each sample. Accompanying each sample is also the ground truthing data recorded, which addresses the present stress of 3 stressors (Verticillium dahliae, Pleospora herbarum and 'other stressors').
DOI: 10.34740/kaggle/dsv/7167935
title: 2021 World Population (updated daily)
DOI: 10.34740/kaggle/dsv/7167938
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.10047383
title: Dexamethasone induces sleep disturbance in a dose-dependent manner in mice

description: This is the data set indicated in Kato et al, 2023, PLOS ONE (DOI: 10.1371/journal.pone.0296028).
DOI: 10.5281/zenodo.10047384
title: Dexamethasone induces sleep disturbance in a dose-dependent manner in mice

description: This is the data set indicated in Kato et al, 2023, PLOS ONE (DOI: 10.1371/journal.pone.0296028).
DOI: 10.6084/m9.figshare.24783033
title: <b>Study of Biofilm, Virulence Genes and Risk Factors in the </b><b>Urinary Catheter-Associated Escherichia coli</b><b> Infections</b>

description: <b>Study of Biofilm, Virulence Genes and Risk Factors in the </b><b>Urinary Catheter-Associated Escherichia coli</b><b> Infections</b>
DOI: 10.6084/m9.figshare.24783033.v1
title: <b>Study of Biofilm, Virulence Genes and Risk Factors in the </b><b>Urinary Catheter-Associated Escherichia coli</b><b> Infections</b>

description: <b>Study of Biofilm, Virulence Genes and Risk Factors in the </b><b>Urinary Catheter-Associated Escherichia coli</b><b> Infections</b>
DOI: 10.5281/zenodo.10201776
title: Data and code: A fast method to distinguish between fermentative and respiratory metabolisms in single yeast cells

description: If you have questions, please contact the first autor via the email lauraluzia@gmail.comLink to the bioRxiv preprint -> https://www.biorxiv.org/content/10.1101/2023.06.23.546324v1
DOI: 10.5281/zenodo.10201777
title: Data and code: A fast method to distinguish between fermentative and respiratory metabolisms in single yeast cells

description: If you have questions, please contact the first autor via the email lauraluzia@gmail.comLink to the bioRxiv preprint -> https://www.biorxiv.org/content/10.1101/2023.06.23.546324v1
DOI: 10.6084/m9.figshare.24783036
title: <b>The Reliability, Sensitivity and Specificity of Fluorescent Oxidation Products for Measuring Global Oxidative Stres</b><b>s </b><b><i>In Vivo</i></b>

description: Introduction To examine the reliability, sensitivity, and specificity of fluorescent oxidation products (FlOPs; markers of global oxidative damage) for measuring global oxidative stress. Methods To improve FlOP measurement reliability, we mixed plasma samples with the extractant at eight ratios and measured FlOPs with a fluorescent microplate reader (excitation/emission wavelengths 320/420 nm denoted FlOP_320; 360/420 nm [FlOP_360]; and 400/475 nm [FlOP_400]). In a human study, we examined the reliability of an improved FlOP measurement. In an animal study, we examined the sensitivity and specificity of FlOPs for measuring D-galactose induced global oxidative stress. Results At a 1:20 (plasma/extractant) mixture ratio, the overall inter-/intra-assay coefficients of variation (CV) for FlOP measurements among healthy and coronary heart disease participants were &lt;3.6%/&lt;2.7% and &lt;4.4%/&lt;2.0%, respectively. On day 30 of the animal experiment, the Pearson correlations (r) of FlOP_320 and FlOP_360 with D-galactose dose were 0.816 and 0.801, respectively, which were 3-12 times higher than those of malondialdehyde (0.183), 8-hydroxyguanosine (0.157), pentosidine (0.254), and nitrotyrosine (0.068) for measuring D-galactose-induced oxidative damage. FlOP_360 (r=0.225, P = 0.045), but not FlOP_320 and FlOP_400, were significantly correlated with c-reactive protein, a marker of inflammation. Conclusions FlOP_320 are reliable, sensitive and specific markers for measuring global oxidative stress.
DOI: 10.6084/m9.figshare.24783036.v1
title: <b>The Reliability, Sensitivity and Specificity of Fluorescent Oxidation Products for Measuring Global Oxidative Stres</b><b>s </b><b><i>In Vivo</i></b>

description: Introduction To examine the reliability, sensitivity, and specificity of fluorescent oxidation products (FlOPs; markers of global oxidative damage) for measuring global oxidative stress. Methods To improve FlOP measurement reliability, we mixed plasma samples with the extractant at eight ratios and measured FlOPs with a fluorescent microplate reader (excitation/emission wavelengths 320/420 nm denoted FlOP_320; 360/420 nm [FlOP_360]; and 400/475 nm [FlOP_400]). In a human study, we examined the reliability of an improved FlOP measurement. In an animal study, we examined the sensitivity and specificity of FlOPs for measuring D-galactose induced global oxidative stress. Results At a 1:20 (plasma/extractant) mixture ratio, the overall inter-/intra-assay coefficients of variation (CV) for FlOP measurements among healthy and coronary heart disease participants were &lt;3.6%/&lt;2.7% and &lt;4.4%/&lt;2.0%, respectively. On day 30 of the animal experiment, the Pearson correlations (r) of FlOP_320 and FlOP_360 with D-galactose dose were 0.816 and 0.801, respectively, which were 3-12 times higher than those of malondialdehyde (0.183), 8-hydroxyguanosine (0.157), pentosidine (0.254), and nitrotyrosine (0.068) for measuring D-galactose-induced oxidative damage. FlOP_360 (r=0.225, P = 0.045), but not FlOP_320 and FlOP_400, were significantly correlated with c-reactive protein, a marker of inflammation. Conclusions FlOP_320 are reliable, sensitive and specific markers for measuring global oxidative stress.
DOI: 10.6084/m9.figshare.22199491.v8
title: <b>From partial to complete: moult sequence and intensity depend on moult completeness in passerines</b>

description: Data used for analyses of partial moult sequence and intensity in 61 passerine species from Europe, North and Central America
DOI: 10.5281/zenodo.10337604
title: Pulsed dosing and extended daily dosing of oral vancomycin do not facilitate clearance of Clostridioides difficile colonization in mice

description: Raw fastq files from 16S rRNA amplicon sequencing.
DOI: 10.5281/zenodo.10337605
title: Pulsed dosing and extended daily dosing of oral vancomycin do not facilitate clearance of Clostridioides difficile colonization in mice

description: Raw fastq files from 16S rRNA amplicon sequencing.
DOI: 10.6084/m9.figshare.24783048
title: <b>Sulfate formation driven by wintertime fog processing and a hydroxymethanesulfonate complex with iron: observations from single-particle measurements in Hong Kong</b>

description: Fog processing has a significant impact on sulfur chemistry in the atmosphere. This study analyzed three winter fog events in Hong Kong using single-particle aerosol mass spectrometry (SPAMS) and a Monitor for AeRosols and GAses in ambient air (MARGA). Black carbon (BC)-related carbonaceous particles with substantial sulfate amounts comprised the largest particle number fraction (56.7%). Sulfate mass concentration decreased during fog due to the cloud’s effective scavenging, but fog processing notably promoted sulfate formation at the single-particle level (average peak area increases of 31.2%). Hydroxymethanesulfonate (HMS), an important S(IV) compound and fog tracer, was identified accounting for up to 12% by particle number fraction. Although pH showed a positive correlation (r = 0.53–0.69) with HMS particles in each fog scenario, a negative overall correlation (r = -0.51) was observed. Further analysis revealed that the higher aerosol acidity (pH 0.65–3.11), promoted Fe dissolution, leading to 49% of HMS particles being mixed with Fe, which potentially facilitated sulfate formation via the Fenton reaction. Additionally, around 40% of HMS-Fe particles are mixed with oxalate, thereby warranting further attention for their potential to cause more intricate sulfur oxidation processes. This study reveals the initial identification of a high mixed-state of HMS-Fe, which could potentially serve as a crucial avenue for the formation of sulfate on individual particulate matter. Considering the persistent augmentation of aerosol acidity in the Asian region, this phenomenon necessitates further investigation and attention.
DOI: 10.34740/kaggle/dsv/7168260
title: COVID Vaccination in World (updated daily)
DOI: 10.34740/kaggle/dsv/7168103
title: Oil Spill Incidents Dataset
DOI: 10.5281/zenodo.7725969
title: Image dataset for training of an insect classification model

description:  
This version is deprecated! Please use the updated Insect Detect - insect classification dataset v2 with more images and classes.
 
This dataset contains images of various insects and some other arthropods, sitting on or flying above an artificial flower platform. All images were automatically recorded with the Insect Detect DIY camera trap, a hardware combination of the Luxonis OAK-1, Raspberry Pi Zero 2 W and PiJuice Zero pHAT for automated insect monitoring (bioRxiv preprint).
This classification dataset contains the cropped bounding boxes, exported from the Insect_Detect_detection dataset together with 290 new images of Episyrphus balteatus.
Classes
The following classes were annotated in this dataset:

wasp (mostly Vespula sp.)
hbee (Apis mellifera)
fly (mostly Brachycera)
hovfly (various Syrphidae, e.g. Eupeodes corollae, Scaeva pyrastri)
episyr_balt (Episyrphus balteatus)
other (all Arthropods with insufficient occurences, e.g. various Hymenoptera, true bugs, beetles)
shadow (shadows of the recorded insects)
View the Health Check for more info on class balance.
Deployment
You can use this dataset as starting point to train your own insect classification models. Check the model training instructions for more information.
To deploy the image classification model (ONNX format) on your PC for fast CPU inference, follow the provided Step by Step instructions. Open source Python scripts to deploy the trained model can be found at the insect-detect-ml GitHub repo.
description: If you use this dataset, please cite it as below.
DOI: 10.5281/zenodo.7725970
title: Image dataset for training of an insect classification model

description:  
This version is deprecated! Please use the updated Insect Detect - insect classification dataset v2 with more images and classes.
 
This dataset contains images of various insects and some other arthropods, sitting on or flying above an artificial flower platform. All images were automatically recorded with the Insect Detect DIY camera trap, a hardware combination of the Luxonis OAK-1, Raspberry Pi Zero 2 W and PiJuice Zero pHAT for automated insect monitoring (bioRxiv preprint).
This classification dataset contains the cropped bounding boxes, exported from the Insect_Detect_detection dataset together with 290 new images of Episyrphus balteatus.
Classes
The following classes were annotated in this dataset:

wasp (mostly Vespula sp.)
hbee (Apis mellifera)
fly (mostly Brachycera)
hovfly (various Syrphidae, e.g. Eupeodes corollae, Scaeva pyrastri)
episyr_balt (Episyrphus balteatus)
other (all Arthropods with insufficient occurences, e.g. various Hymenoptera, true bugs, beetles)
shadow (shadows of the recorded insects)
View the Health Check for more info on class balance.
Deployment
You can use this dataset as starting point to train your own insect classification models. Check the model training instructions for more information.
To deploy the image classification model (ONNX format) on your PC for fast CPU inference, follow the provided Step by Step instructions. Open source Python scripts to deploy the trained model can be found at the insect-detect-ml GitHub repo.
description: If you use this dataset, please cite it as below.
DOI: 10.5281/zenodo.7725940
title: Image dataset for training of an insect detection model for the Insect Detect DIY camera trap

description: This dataset contains images of an artifical flower platform with different insects sitting on it or flying above it. All images were automatically recorded with the Insect Detect DIY camera trap, a hardware combination of the Luxonis OAK-1, Raspberry Pi Zero 2 W and PiJuice Zero pHAT for automated insect monitoring (bioRxiv preprint).
Classes
The following object classes were annotated in this dataset:

wasp (mostly Vespula sp.)
hbee (Apis mellifera)
fly (mostly Brachycera)
hovfly (various Syrphidae, e.g. Episyrphus balteatus)
other (all Arthropods with insufficient occurences, e.g. various Hymenoptera, true bugs, beetles)
shadow (shadows of the recorded insects)
View the Health Check for more info on class balance.
Versions

v4 insect_detect_416_1class

squashed to square (aspect ratio 1:1)
downscaled to 416x416 pixel
all classes merged into one class ("insect")
v5 insect_detect_raw_4K

original images in 4K resolution (3840x2160 pixel)
v7 insect_detect_320_1class

squashed to square (aspect ratio 1:1)
downscaled to 320x320 pixel
all classes merged into one class ("insect")
Deployment
You can use this dataset as starting point to train your own insect detection models. Check the model training instructions for more information.
Open source Python scripts to deploy the trained models can be found at the insect-detect GitHub repo.
description: If you use this dataset, please cite it as below.
DOI: 10.5281/zenodo.7725941
title: Image dataset for training of an insect detection model for the Insect Detect DIY camera trap

description: This dataset contains images of an artifical flower platform with different insects sitting on it or flying above it. All images were automatically recorded with the Insect Detect DIY camera trap, a hardware combination of the Luxonis OAK-1, Raspberry Pi Zero 2 W and PiJuice Zero pHAT for automated insect monitoring (bioRxiv preprint).
Classes
The following object classes were annotated in this dataset:

wasp (mostly Vespula sp.)
hbee (Apis mellifera)
fly (mostly Brachycera)
hovfly (various Syrphidae, e.g. Episyrphus balteatus)
other (all Arthropods with insufficient occurences, e.g. various Hymenoptera, true bugs, beetles)
shadow (shadows of the recorded insects)
View the Health Check for more info on class balance.
Versions

v4 insect_detect_416_1class

squashed to square (aspect ratio 1:1)
downscaled to 416x416 pixel
all classes merged into one class ("insect")
v5 insect_detect_raw_4K

original images in 4K resolution (3840x2160 pixel)
v7 insect_detect_320_1class

squashed to square (aspect ratio 1:1)
downscaled to 320x320 pixel
all classes merged into one class ("insect")
Deployment
You can use this dataset as starting point to train your own insect detection models. Check the model training instructions for more information.
Open source Python scripts to deploy the trained models can be found at the insect-detect GitHub repo.
description: If you use this dataset, please cite it as below.
DOI: 10.5281/zenodo.10337412
title: Coleta de Dados de Pesquisa de Doutorado: Estresse de Minoria e Violência entre Parceiros Íntimos na População LGBTIQ+

description: A planilha de Excel anexa contém 219 colunas ou variáveis. As 133 primeiras foram numeradas sequencialmente (001 a 133). As restantes foram numeradas de acordo com a escala original para facilitar o cálculo. Todas as colunas contêm o rótulo original por extenso. As opções de resposta estão como originalmente baixadas do Google Forms ao final da coleta. O documento em PDF contém os nomes das variáveis, seu significado, a forma como foram coletadas no questionário online e as escalas correspondentes. 
Período da coleta: 13/09/19 a 05/01/20
Dados pertencentes ao projeto de pesquisa aprovado pelo Comitê de Ética em Pesquisa da Universidade do Vale do Rio dos Sinos (CAAE: 03693218.2.0000.5344). Pesquisador responsável: Icaro Bonamigo Gaspodini. Orientadora: Denise Falcke. 
Nenhum dado contido nestes arquivos é capaz de identificar participantes da pesquisa. 
Tese publicada: http://repositorio.jesuita.org.br/handle/UNISINOS/10227
Este banco de dados está disponível para pesquisadores mediante citação da fonte:
Gaspodini, I. B. (2023). Coleta de dados de pesquisa de doutorado: Estresse de minoria e violência entre parceiros íntimos na população LGBTIQ+ [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10337413
DOI: 10.5281/zenodo.10337413
title: Coleta de Dados de Pesquisa de Doutorado: Estresse de Minoria e Violência entre Parceiros Íntimos na População LGBTIQ+

description: A planilha de Excel anexa contém 219 colunas ou variáveis. As 133 primeiras foram numeradas sequencialmente (001 a 133). As restantes foram numeradas de acordo com a escala original para facilitar o cálculo. Todas as colunas contêm o rótulo original por extenso. As opções de resposta estão como originalmente baixadas do Google Forms ao final da coleta. O documento em PDF contém os nomes das variáveis, seu significado, a forma como foram coletadas no questionário online e as escalas correspondentes. 
Período da coleta: 13/09/19 a 05/01/20
Dados pertencentes ao projeto de pesquisa aprovado pelo Comitê de Ética em Pesquisa da Universidade do Vale do Rio dos Sinos (CAAE: 03693218.2.0000.5344). Pesquisador responsável: Icaro Bonamigo Gaspodini. Orientadora: Denise Falcke. 
Nenhum dado contido nestes arquivos é capaz de identificar participantes da pesquisa. 
Tese publicada: http://repositorio.jesuita.org.br/handle/UNISINOS/10227
Este banco de dados está disponível para pesquisadores mediante citação da fonte:
Gaspodini, I. B. (2023). Coleta de dados de pesquisa de doutorado: Estresse de minoria e violência entre parceiros íntimos na população LGBTIQ+ [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10337413