cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12521918.v1
title: Landsat-spectral-signature-CHEATGRASS

description: Cheatgrass spectral signature from USGS Spectral Library Version 7<br><br>Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., Driscoll, R.L., and Klein, A.J., 2017, USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035, 61 p., https://doi.org/10.3133/ds1035.
DOI: 10.6084/m9.figshare.12521573
title: Raw Data Borowiec et al., 2020 JEB doi:10.1242/jeb.222877

description: Raw data for Borowiec, B.G. and Scott, G.R. (2020). Hypoxia acclimation alters reactive oxygen species homeostasisand oxidative status in estuarine killifish (Fundulus heteroclitus). J. Exp. Biol. 223, jeb222877. doi:10.1242/jeb.222877.<br>Contact B.G.B. if downloading.
DOI: 10.6084/m9.figshare.12521882.v1
title: Landsat-spectral-signature-SAGEBRUSH

description: Sagebrush spectral signature from USGS Spectral Library Version 7<br>Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., Driscoll, R.L., and Klein, A.J., 2017, USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035, 61 p., https://doi.org/10.3133/ds1035<br>
DOI: 10.6084/m9.figshare.12521198
title: JVASP-15391 to JVASP-15977

description: JARVIS-DFT input/output files
DOI: 10.6084/m9.figshare.12521351.v1
title: Robidium dataset

description: A sample UI log for Robidium tool
DOI: 10.6084/m9.figshare.12520778
title: Carbon flux and environmental parameters data from an eddy covariance tower in a mid-succession ecosystem developed on abandoned karst grassland in Slovenia (2012-2019)

description: <b>This data set was used to estimate carbon fluxes by comparing eddy covariance tower (Long = 13.916701, Lat = </b><b>45.543491</b><b>) measurements with vegetation indices based estimates.</b> The data set includes all data required to : - Perform empirical regression of GPP (gross primary production) or NEE (Net ecosystem exchange) with vegetation indices, - Apply the vegetation photosynthesis model, which is a light use efficiency model. <br> This data set includes 4 files, which are 2 *.csv files and 2 *.txt files. The *.csv files have the actual data in tabular format, and the *.txt files, named in the same way as the *.csv files with a prefix "parameters _ metadata", have a complete description of each variable found in the *.csv file, including their units.<br> <br> <b>The first *csv file "1.Halfmonthly_fluxes_vegetation_indices.csv"</b> contains half-monthly aggregated fluxes, environmental parameters and vegetation indices from <b>2012 to 2019</b>. The variables included in the file are: <b>date, NEE, GPP, Reco, Rg, Tair</b><b>_</b><b>midday, Tair, VPD, EVI, SAVI, LSWI, NDVI, GNDVI</b>; and their meanings can be found in the corresponding *.txt file <b>"1.parameters_metadata_Halfmonthly_fluxes_vegetation_indices.txt"</b>.<br> <br> <b>The second *.csv file "2.Halfhourly_LUEmax_calculation_data_2019.csv"</b> contains half-hourly fluxes and environmental parameters for the year 2019, needed to calculate LUE_max, further used in the VPM model. The variables included in the file are: <b>time, incPPFD, bcPPFD_1, bcPPFD_2, naPPFD, frac_grass, frac_trees, frac, VPD, GPP, SWC, Rg, PAR, APAR, uncloudy</b>; and their meanings can be found in the corresponding *.txt file <b>"2.parameters_metadata_Halfhourly_LUEmax_calculation_data_2019.txt"</b>.<b><br></b><b>About the authors of this data set,</b>The original data set was collected by Mitja Ferlan, Klemen Eler, Dominik Vodnik and Primož Simončič. However, the processed data, object of this publication was prepared by Koffi Dodji Noumonvi and Mitja Ferlan.<br><br>P.S. This data set is a research data, that can be used to reproduce the methodology applied in the paper (in review at the moment of publishing this data).
DOI: 10.6084/m9.figshare.12520796
title: source file for skyrmions in WTe2/FGT paper

description: This excel includes the source data for figure 1 and figure 2 in the main text.
DOI: 10.6084/m9.figshare.12520703
title: Scopus_exported_refine_values.csv

description: SCOPUS Search Criteria and Results for investigations dealing with the Theory behind the RFCDC of the Council of Europe.This search was realized on 02/06/2020.
DOI: 10.6084/m9.figshare.12520778.v1
title: Carbon flux and environmental parameters data from an eddy covariance tower in a mid-succession ecosystem developed on abandoned karst grassland in Slovenia (2012-2019)

description: <b>This data set was used to estimate carbon fluxes by comparing eddy covariance tower (Long = 13.916701, Lat = </b><b>45.543491</b><b>) measurements with vegetation indices based estimates.</b> The data set includes all data required to : - Perform empirical regression of GPP (gross primary production) or NEE (Net ecosystem exchange) with vegetation indices, - Apply the vegetation photosynthesis model, which is a light use efficiency model. <br> This data set includes 4 files, which are 2 *.csv files and 2 *.txt files. The *.csv files have the actual data in tabular format, and the *.txt files, named in the same way as the *.csv files with a prefix "parameters _ metadata", have a complete description of each variable found in the *.csv file, including their units.<br> <br> <b>The first *csv file "1.Halfmonthly_fluxes_vegetation_indices.csv"</b> contains half-monthly aggregated fluxes, environmental parameters and vegetation indices from <b>2012 to 2019</b>. The variables included in the file are: <b>date, NEE, GPP, Reco, Rg, Tair</b><b>_</b><b>midday, Tair, VPD, EVI, SAVI, LSWI, NDVI, GNDVI</b>; and their meanings can be found in the corresponding *.txt file <b>"1.parameters_metadata_Halfmonthly_fluxes_vegetation_indices.txt"</b>.<br> <br> <b>The second *.csv file "2.Halfhourly_LUEmax_calculation_data_2019.csv"</b> contains half-hourly fluxes and environmental parameters for the year 2019, needed to calculate LUE_max, further used in the VPM model. The variables included in the file are: <b>time, incPPFD, bcPPFD_1, bcPPFD_2, naPPFD, frac_grass, frac_trees, frac, VPD, GPP, SWC, Rg, PAR, APAR, uncloudy</b>; and their meanings can be found in the corresponding *.txt file <b>"2.parameters_metadata_Halfhourly_LUEmax_calculation_data_2019.txt"</b>.<br><b>About the authors of this data set,</b>The original data set was collected by Mitja Ferlan, Klemen Eler, Dominik Vodnik and Primož Simončič. However, the processed data, object of this publication was prepared by Koffi Dodji Noumonvi and Mitja Ferlan.<br><br>P.S. This data set is a research data, that can be used to reproduce the methodology applied in the paper (in review at the moment of publishing this data).
DOI: 10.6084/m9.figshare.12520601
title: A internacionalização na formação em Relações Internacionais no Brasil

description: Dados obtidos da plataforma GeoCapes para observar a distribuição de bolsistas no Exterior nas áreas de “Ciência Política e Relações Internacionais”.
DOI: 10.6084/m9.figshare.12520601.v2
title: A internacionalização na formação em Relações Internacionais no Brasil

description: Dados obtidos da plataforma GeoCapes para observar a distribuição de bolsistas no Exterior nas áreas de “Ciência Política e Relações Internacionais”.
DOI: 10.6084/m9.figshare.12520484
title: Calculation of study-wide significance threshold

description: The files Permutation203LeadSNPs.mat.gz and Permutation1000RandomSNPs.mat.gz contain the permutation outcomes from the process described in Supplementary Note 1, for the 203 lead SNPs and 1,000 randomly selected SNPs. These results were used to illustrate that the meta-analysis pipeline does not artificially inflate our p-values (Supplementary Note 1) and to empirically calculate the study-wide significance threshold (Supplementary Note 2). The MatLab script (IndependentTests.m) can be used to replicate the calculations in Supplementary Note 2.
DOI: 10.6084/m9.figshare.12520601.v1
title: A internacionalização na formação em Relações Internacionais no Brasil

description: Dados obtidos da plataforma GeoCapes para observar a distribuição de bolsistas no Exterior nas áreas de “Ciência Política e Relações Internacionais”.
DOI: 10.6084/m9.figshare.12520484.v1
title: Calculation of study-wide significance threshold

description: The files Permutation203LeadSNPs.mat.gz and Permutation1000RandomSNPs.mat.gz contain the permutation outcomes from the process described in Supplementary Note 1, for the 203 lead SNPs and 1,000 randomly selected SNPs. These results were used to illustrate that the meta-analysis pipeline does not artificially inflate our p-values (Supplementary Note 1) and to empirically calculate the study-wide significance threshold (Supplementary Note 2). The MatLab script (IndependentTests.m) can be used to replicate the calculations in Supplementary Note 2.
DOI: 10.6084/m9.figshare.12520451
title: 单侧.xls

description: 数据quality
DOI: 10.6084/m9.figshare.12520448
title: Data_How do hoverflies use their righting reflex?

description: Angles data of the body, the head and the wings through time of Episyrphus Balteatus during multiples righting reflex. Wings angle for the normal condition and angles data of the body and the head for four conditions : normal (lighting from above). Lum_bas (lighting from below). Halt_ajout (halteres loaded with some glue). HB_colle (head and thorax glued).
DOI: 10.6084/m9.figshare.12520448.v1
title: Data_How do hoverflies use their righting reflex?

description: Angles data of the body, the head and the wings through time of Episyrphus Balteatus during multiples righting reflex. Wings angle for the normal condition and angles data of the body and the head for four conditions : normal (lighting from above). Lum_bas (lighting from below). Halt_ajout (halteres loaded with some glue). HB_colle (head and thorax glued).
DOI: 10.6084/m9.figshare.12520409
title: GASVM and GA k-means

description: Unsupervised clustering (e.g., K-means) and supervised machine learning (e.g., support vector machines (SVMs)) methods can be used in data-driven classification and predictive mapping of mineral prospectivity.<br>
DOI: 10.6084/m9.figshare.12520451.v1
title: 单侧.xls

description: data
DOI: 10.6084/m9.figshare.12520451.v3
title: 单侧.xls

description: 数据quality
DOI: 10.6084/m9.figshare.12520451.v2
title: 单侧.xls

description: 数据 data
DOI: 10.6084/m9.figshare.12520115
title: Fig_figs.zip

description: This is the datasets for the paper submitted to Journal of Physical Oceanography.
DOI: 10.6084/m9.figshare.12520010
title: Different groups of ground-dwelling spiders share similar trophic niches in temperate forests - Data file

description: Different groups of ground-dwelling spiders share similar trophic niches in temperate forests - Data file<br>Column codes clarification:ID, Sample nameOrder - Taxa order for sampleFamily - Taxa family for sampleRegion - southern taiga is indicated by ST and broadleaved forest as BLFire - "fire" for areas, which were exposed to forest fire, "control" for non-treatedPlot - Plot ID Body size, mm - size group of studied predator individualsCollembola Col3F-Col5R - detection of Collembola by GC PCR, binaryLumbricidae 185F-14233R - detection of Lumbricidae by GC PCR, binaryOribatida ORI S14 - ORI A16 - detection of Oribatida by GC PCR, binaryStaphylinidae STA S6 - STA A3- detection of Staphylinidae by GC PCR, binaryDiptera DIP S16 - DIP A17 - detection of Diptera by GC PCR, binaryGamasina GAM S7 - GAM A8 - detection of Gamasina by GC PCR, binaryPCR-name - running sample ID used for PCRsd13C norm - standartized d13C valuesd15N norm - standartized d15N valuesSUMM PRED - the amount of predators detected by GC PCRSUMM HERB - the amount of NON-predators detected by GC PCRTOTAL POSITIVES - the total amount of groups detected by GC PCRLOG(Wet weight) - wet weight of studieв predator individuals, dec.log.(g)Hunting - hunting type of studied individuals, according to spider familyHabitat (Lowest forest tier)Habitat (Highest forest tier)Habitat group - according to the lowest and highest habitat forest tier combinationCollembola - expected feeding on Collembola, binaryDiptera - expected feeding on Diptera, binaryLepidoptera - expected feeding on Lepidoptera, binaryColeoptera - expected feeding on Coleoptera, binaryHemiptera - expected feeding on Hemiptera, binaryEsp.small - expected feeding on small prey (collembola and mites), binaryExpect VS GutContentCollembola - expected to observed feeding on Collembola, binaryDiptera - expected to observed feeding on Diptera, binaryColeoptera - expected to observed feeding on Coleoptera, binaryEsp.small - expected to observed feeding on small prey (collembola and mites), binarySUM of positive hits - expected to observed feeding hits summ
DOI: 10.6084/m9.figshare.12520115.v1
title: Fig_figs.zip

description: This is the datasets for the paper submitted to Journal of Physical Oceanography.
DOI: 10.6084/m9.figshare.12519971
title: Data set, Patients’ involvement in decision-making at Kisenyi Health Center IV, Kampala, Central Uganda

description: This data set is for the study, <b>Patients’ involvement in decision-making at Kisenyi Health Center IV, Kampala, Central Uganda.</b>
DOI: 10.6084/m9.figshare.12519971.v1
title: Data set, Patients’ involvement in decision-making at Kisenyi Health Center IV, Kampala, Central Uganda

description: This data set is for the study, <b>Patients’ involvement in decision-making at Kisenyi Health Center IV, Kampala, Central Uganda.</b>
DOI: 10.6084/m9.figshare.12519893
title: Video-based Evaluation of Infant Crawling toward Quantitative Assessment of Motor Development

description: Some of the videos and codes used in the analysis.
DOI: 10.6084/m9.figshare.12519893.v1
title: Video-based Evaluation of Infant Crawling toward Quantitative Assessment of Motor Development

description: Some of the videos and codes used in the analysis.
DOI: 10.6084/m9.figshare.12519887
title: data.rar

description: These data are compressed into a compressed package.
DOI: 10.6084/m9.figshare.12519890
title: Kitap (6).xlsx

description: Clinical and laboratory data of 63 patients with Covid-19 pneumonia.
DOI: 10.6084/m9.figshare.12519890.v1
title: Kitap (6).xlsx

description: Clinical and laboratory data of 63 patients with Covid-19 pneumonia.
DOI: 10.6084/m9.figshare.12519809.v1
title: CBMIstudy1predata.xlsx

description: People with high anxiety tend to interpret ambiguous cues negatively, regardless of whether the cues are negative or positive. Cognitive bias modification for interpretation (CBM-I) may reduce such biases. However, CBM-I sessions for social anxiety in previous studies were held either only once or twice a week in the laboratory and did not test the Japanese population. In this study, we developed a Japanese version of CBM-I. The current study investigated the effects of a short, intensive program using two types of the Japanese version of CBM-I procedures. In Study 1, 74 participants were randomly placed into either a one-week program with online sessions of text-based scenarios training or a control condition. In Study 2, 120 participants were randomized into one-week online sessions of text-based scenarios training (four times) and picture-word cue training (three times) or a control condition. In both Study 1 and 2, participants in the control condition completed the same positive interpretation task after a one-week standby. In Study 1, individuals in the positive condition demonstrated significant improvements in depressive symptoms from pre-intervention to post-intervention compared to those in the control condition. Improvements in depressive symptoms and interpretation bias at a one-month follow-up were significant. In Study 2, in the positive condition, there was a significant reduction in negative affect compared to the control condition. In addition, there were greater reductions in negative affect, social evaluative fear, and negative interpretation bias at a one-month follow-up, irrespective of condition. Results suggest that text-based CBM-I affects depressive symptom and interpretation bias, text, and picture-based CBM-I especially affects these emotional characteristics. Depending on the assessment and treatment policy for patients, we might concurrently use two approaches, one with text stimuli when stimulating depressive symptoms and interpretations, and the other with picture stimuli when stimulating emotions.
DOI: 10.6084/m9.figshare.12519479
title: Data and Source.xlsx

description: The data provided in this repository is the datasets of the article “Micro, Small, and Medium Enterprises (MSMEs) and Poverty Reduction: Empirical Evidence from Indonesia”. The raw data are gathered from The Ministry of Cooperatives and SMEs in Indonesia and the Central Bureau of Statistic Indonesia. In addition, this article uses secondary data from the period of 1997-2018 to estimate the effect of MSMEs on poverty reduction in Indonesia both directly and indirectly.
DOI: 10.6084/m9.figshare.12519488
title: Source data for "Defining and predicting transdiagnostic categories of neurodegenerative disease"

description: Source data for Cornblath et al. 2020, "Defining and predicting transdiagnostic categories of neurodegenerative disease."
DOI: 10.6084/m9.figshare.12519809.v2
title: CBMIstudy1predata.xlsx

description: People with high anxiety tend to interpret ambiguous cues negatively, regardless of whether the cues are negative or positive. Cognitive bias modification for interpretation (CBM-I) may reduce such biases. However, CBM-I sessions for social anxiety in previous studies were held either only once or twice a week in the laboratory and did not test the Japanese population. In this study, we developed a Japanese version of CBM-I. The current study investigated the effects of a short, intensive program using two types of the Japanese version of CBM-I procedures. In Study 1, 74 participants were randomly placed into either a one-week program with online sessions of text-based scenarios training or a control condition. In Study 2, 120 participants were randomized into one-week online sessions of text-based scenarios training (four times) and picture-word cue training (three times) or a control condition. In both Study 1 and 2, participants in the control condition completed the same positive interpretation task after a one-week standby. In Study 1, individuals in the positive condition demonstrated significant improvements in depressive symptoms from pre-intervention to post-intervention compared to those in the control condition. Improvements in depressive symptoms and interpretation bias at a one-month follow-up were significant. In Study 2, in the positive condition, there was a significant reduction in negative affect compared to the control condition. In addition, there were greater reductions in negative affect, social evaluative fear, and negative interpretation bias at a one-month follow-up, irrespective of condition. Results suggest that text-based CBM-I affects depressive symptom and interpretation bias, text, and picture-based CBM-I especially affects these emotional characteristics. Depending on the assessment and treatment policy for patients, we might concurrently use two approaches, one with text stimuli when stimulating depressive symptoms and interpretations, and the other with picture stimuli when stimulating emotions.
DOI: 10.6084/m9.figshare.12519809.v3
title: CBMIstudy1predata.xlsx

description: People with high anxiety tend to interpret ambiguous cues negatively, regardless of whether the cues are negative or positive. Cognitive bias modification for interpretation (CBM-I) may reduce such biases. However, CBM-I sessions for social anxiety in previous studies were held either only once or twice a week in the laboratory and did not test the Japanese population. In this study, we developed a Japanese version of CBM-I. The current study investigated the effects of a short, intensive program using two types of the Japanese version of CBM-I procedures. In Study 1, 74 participants were randomly placed into either a one-week program with online sessions of text-based scenarios training or a control condition. In Study 2, 120 participants were randomized into one-week online sessions of text-based scenarios training (four times) and picture-word cue training (three times) or a control condition. In both Study 1 and 2, participants in the control condition completed the same positive interpretation task after a one-week standby. In Study 1, individuals in the positive condition demonstrated significant improvements in depressive symptoms from pre-intervention to post-intervention compared to those in the control condition. Improvements in depressive symptoms and interpretation bias at a one-month follow-up were significant. In Study 2, in the positive condition, there was a significant reduction in negative affect compared to the control condition. In addition, there were greater reductions in negative affect, social evaluative fear, and negative interpretation bias at a one-month follow-up, irrespective of condition. Results suggest that text-based CBM-I affects depressive symptom and interpretation bias, text, and picture-based CBM-I especially affects these emotional characteristics. Depending on the assessment and treatment policy for patients, we might concurrently use two approaches, one with text stimuli when stimulating depressive symptoms and interpretations, and the other with picture stimuli when stimulating emotions.
DOI: 10.6084/m9.figshare.12519809.v4
title: CBMIstudy1predata.xlsx

description: People with high anxiety tend to interpret ambiguous cues negatively, regardless of whether the cues are negative or positive. Cognitive bias modification for interpretation (CBM-I) may reduce such biases. However, CBM-I sessions for social anxiety in previous studies were held either only once or twice a week in the laboratory and did not test the Japanese population. In this study, we developed a Japanese version of CBM-I. The current study investigated the effects of a short, intensive program using two types of the Japanese version of CBM-I procedures. In Study 1, 74 participants were randomly placed into either a one-week program with online sessions of text-based scenarios training or a control condition. In Study 2, 120 participants were randomized into one-week online sessions of text-based scenarios training (four times) and picture-word cue training (three times) or a control condition. In both Study 1 and 2, participants in the control condition completed the same positive interpretation task after a one-week standby. In Study 1, individuals in the positive condition demonstrated significant improvements in depressive symptoms from pre-intervention to post-intervention compared to those in the control condition. Improvements in depressive symptoms and interpretation bias at a one-month follow-up were significant. In Study 2, in the positive condition, there was a significant reduction in negative affect compared to the control condition. In addition, there were greater reductions in negative affect, social evaluative fear, and negative interpretation bias at a one-month follow-up, irrespective of condition. Results suggest that text-based CBM-I affects depressive symptom and interpretation bias, text, and picture-based CBM-I especially affects these emotional characteristics. Depending on the assessment and treatment policy for patients, we might concurrently use two approaches, one with text stimuli when stimulating depressive symptoms and interpretations, and the other with picture stimuli when stimulating emotions.