cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14907843
title: Table 5. Statistically significant values of the correlation coefficient r for all image descriptors, the phenotypic traits of grain and yield per unit area

description: Statistically significant values of the correlation coefficient r for all image descriptors, the phenotypic traits of grain and yield per unit area
DOI: 10.6084/m9.figshare.14907831
title: Table 3. The values of color descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.

description: The values of color descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.
DOI: 10.5281/zenodo.5534433
title: Comprehensive analysis of commercial fragment libraries.

description: <strong>Description of the files</strong> Fragments from libraries: <strong>allFragments_annotations.sdf:</strong> SDF file containing the 3D conformation of all unique 512284 fragments. Descriptors present on the file: Library type (type), Library size (size) and the number of times the fragment is present in the ensemble of libraries (Frequency). <strong>unique_nonbiased_MW_logP_PBF.sdf:</strong> SDF file containing the ensemble of unique fragments from the non-chemically biased libraries. Descriptors present on the file: Canonical Smiles (Canonical_Smiles), Molecular Weight (MW), Partition logarithm (ALogP) and Plane of best fit value (PBF). <strong>unique_nonbiased_principal_descriptors.tsv:</strong> TSV file containing the ensemble of unique fragments from the non-chemically biased libraries with the descriptors that were explicitely used in the article. Descriptors present on the file: Canonical Smiles (Canonical_Smiles), molecular weight (MW), partition logarithm (ALogP) and plane of best fit value (PBF), number of heavy atoms (HAC), number of hydrogen bond acceptors and donors (HBA and HBD), number of rotatable bonds (NRot), number of violations of the rule of three (Ro3_Vio) and quantitative estimate of<strong> </strong>drug-likeness (QED). <strong>unique_nonbiased_descriptors.tsv:</strong> TSV file containing the ensemble of unique fragments from the non-chemically biased libraries with all the calculated descriptors. GTM model: <strong>training_set_GTM.sdf: </strong>SDF file containing the set of 6017 fragments used for training the GTM model. <strong>Model_IIAB2-4_cycle_Freq_05_m301.xml:</strong> xml file of the generated model allowing the generation of GTM landscapes. Scaffold data: <strong>scaffold_data.tsv:</strong> TSV file containing the scaffold data. For an easy exploration of the file please refer to: https://gtmfrag.drugdesign.unistra.fr/
DOI: 10.6084/m9.figshare.14907831.v1
title: Table 3. The values of color descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.

description: The values of color descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.
DOI: 10.6084/m9.figshare.14906853
title: Table 2 The values of shape descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.

description: The values of shape descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.
DOI: 10.6084/m9.figshare.14907840.v1
title: Table 4. Statistically significant values of the Pearson’s correlation coefficient r for the traits related to the technological quality and yield of the analyzed T. durum accessions and reference cultivars.

description: Statistically significant values of the Pearson’s correlation coefficient r for the traits related to the technological quality and yield of the analyzed T. durum accessions and reference cultivars.
DOI: 10.6084/m9.figshare.14906853.v1
title: Table 2 The values of shape descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.

description: The values of shape descriptors in the images of kernels of the analyzed accessions and cultivars of T. durum and Kamut® wheat.
DOI: 10.6084/m9.figshare.14906844
title: Table 1. Accessions and cultivars of T. durum and Kamut® wheat examined in the study

description: Accessions and cultivars of T. durum and Kamut® wheat examined in the study
DOI: 10.6084/m9.figshare.14907840
title: Table 4. Statistically significant values of the Pearson’s correlation coefficient r for the traits related to the technological quality and yield of the analyzed T. durum accessions and reference cultivars.

description: Statistically significant values of the Pearson’s correlation coefficient r for the traits related to the technological quality and yield of the analyzed T. durum accessions and reference cultivars.
DOI: 10.3886/e134442
title: Perceived social support-giving moderates the association between social relationships and interleukin-6 levels in blood

description: This study aimed to examine whether perceived availability to give support to others moderates associations between social relationships and inflammation. The data from the longitudinal follow-up of the National Survey of Midlife Development in the U.S. (MIDUS 2) were used. Results showed that perceived availability to give support moderated the associations between IL-6 and indicators of positive social relationships, including social integration, perceived support from others, and positive relations with others. Indicators of positive social relationships were associated with lower IL-6 among individuals higher, but not lower, in perceived availability to give support. The moderating effects of giving support held after adjusting for socio-demographic and health-related covariates.<br>
description: Presence of Common Scales: Documentations for the measures, variables, and scales used in the MIDUS 2 and MIDUS 2: Biomarker Project can be found on the following websites. <br><br>Ryff, Carol, Almeida, David M., Ayanian, John, Carr, Deborah S., Cleary, Paul D., Coe, Christopher, … Williams, David. Midlife in the United States (MIDUS 2), 2004-2006. Inter-university Consortium for Political and Social Research [distributor], 2017-11-20. https://doi.org/10.3886/ICPSR04652.v7<br><br>Ryff, Carol D., Seeman, Teresa, and Weinstein, Maxine. Midlife in the United States (MIDUS 2): Biomarker Project, 2004-2009. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-03-27. https://doi.org/10.3886/ICPSR29282.v9
description: This study used the data from the longitudinal follow-up of the National Survey of Midlife Development in the U.S. (MIDUS 2). The baseline sample of MIDUS 2 consisted of individuals from four subsamples, including a national random digit dialing sample, oversamples from five metropolitan areas, siblings of individuals from the random digit dialing sample, and a national random digit dialing sample of twin pairs.
description: English-speaking adults who reside in the United States.
DOI: 10.3886/e134442v6
title: Perceived social support-giving moderates the association between social relationships and interleukin-6 levels in blood

description: This study aimed to examine whether perceived availability to give support to others moderates associations between social relationships and inflammation. The data from the longitudinal follow-up of the National Survey of Midlife Development in the U.S. (MIDUS 2) were used. Results showed that perceived availability to give support moderated the associations between IL-6 and indicators of positive social relationships, including social integration, perceived support from others, and positive relations with others. Indicators of positive social relationships were associated with lower IL-6 among individuals higher, but not lower, in perceived availability to give support. The moderating effects of giving support held after adjusting for socio-demographic and health-related covariates.<br>
description: Presence of Common Scales: Documentations for the measures, variables, and scales used in the MIDUS 2 and MIDUS 2: Biomarker Project can be found on the following websites. <br><br>Ryff, Carol, Almeida, David M., Ayanian, John, Carr, Deborah S., Cleary, Paul D., Coe, Christopher, … Williams, David. Midlife in the United States (MIDUS 2), 2004-2006. Inter-university Consortium for Political and Social Research [distributor], 2017-11-20. https://doi.org/10.3886/ICPSR04652.v7<br><br>Ryff, Carol D., Seeman, Teresa, and Weinstein, Maxine. Midlife in the United States (MIDUS 2): Biomarker Project, 2004-2009. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-03-27. https://doi.org/10.3886/ICPSR29282.v9
description: This study used the data from the longitudinal follow-up of the National Survey of Midlife Development in the U.S. (MIDUS 2). The baseline sample of MIDUS 2 consisted of individuals from four subsamples, including a national random digit dialing sample, oversamples from five metropolitan areas, siblings of individuals from the random digit dialing sample, and a national random digit dialing sample of twin pairs.
description: English-speaking adults who reside in the United States.
DOI: 10.5281/zenodo.5717263
title: Supporting data for boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy

description: This dataset includes the properties necessary to reproduce the analysis of water vapour statistics derived from imaging spectroscopy as in: Richardson et al. (2021a) DOI: 10.5194/amt-14-5555-2021<br> Richardson et al. (2021b) DOI: 10.5194/amt-2021-163 (pre-acceptance DOI, follow links to published version) Files include the retrieval emulator parameters, atmospheric profiles used in the emulator development, column-mean water vapour and cloud water both for the total column water vapour (TCWV) and "effective" TCWV, which accounts for the water vapour integrated along the direct solar path at a range of solar zenith angles, see Richardson 2021b, Eq. (7).
DOI: 10.5281/zenodo.5717262
title: Supporting data for boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy

description: This dataset includes the properties necessary to reproduce the analysis of water vapour statistics derived from imaging spectroscopy as in: Richardson et al. (2021a) DOI: 10.5194/amt-14-5555-2021<br> Richardson et al. (2021b) DOI: 10.5194/amt-2021-163 (pre-acceptance DOI, follow links to published version) Files include the retrieval emulator parameters, atmospheric profiles used in the emulator development, column-mean water vapour and cloud water both for the total column water vapour (TCWV) and "effective" TCWV, which accounts for the water vapour integrated along the direct solar path at a range of solar zenith angles, see Richardson 2021b, Eq. (7).
DOI: 10.6084/m9.figshare.17054372
title: How beliefs about weight malleability and risk perceptions for obesity influence parents’ information seeking and feeding

description: This study surveyed 185 parents to determine whether their perceived risk of their child developing obesity and their implicit theories about the malleability of weight independently and/or interactively predict their child-feeding and pursuit of child-related obesity risk information. Higher risk perceptions were associated with healthier feeding intentions and more information seeking. More incremental (malleable) beliefs predicted healthier feeding intentions and greater pursuit of environmental, but not genetic, information. Contrary to hypotheses, the influence of implicit theories and risk perceptions were primarily independent; however, more incremental beliefs predicted less “junk food” feeding among only parents with lower perceived risk. <b></b>
DOI: 10.5281/zenodo.4680065
title: Semiochemical interaction between Aulacophora foeveicollis andhost plant Cucurbita maxima:SEM and electrophysiological investigation

description: This dataset deals with the investigative SEM and electrophysiological experimental approaches profiling the Semiochemical interaction between <em>Aulacophora foeveicollis</em> and host plant <em>Cucurbita maxima.</em>
DOI: 10.5281/zenodo.4680064
title: Semiochemical interaction between Aulacophora foeveicollis andhost plant Cucurbita maxima:SEM and electrophysiological investigation

description: This dataset deals with the investigative SEM and electrophysiological experimental approaches profiling the Semiochemical interaction between <em>Aulacophora foeveicollis</em> and host plant <em>Cucurbita maxima.</em>
DOI: 10.25345/c59p2z
title: MassIVE MSV000088421 - Proteomic response of Turicibacter bilis MMM721 to chicken bile and its bile acids
title: Bile and its individual components, mainly bile acids, are important for digestion and drive bacteria community dynamics in the upper gastrointestinal tract of chickens. However, specific responses to bile acids have been characterized in only a few commensal bacteria, and it is unclear how other members of the microbiota respond to biliary stress. Here, we used label-free LC-MS/MS to assess the proteomic response of a common inhabitant of the chicken upper intestinal tract, Turicibacter spp. MMM721, to 24 hours of growth in anaerobic growth media supplemented with 0.1% whole chicken bile, 0.1% taurochenodeoxycholic acid, or 0.1% taurocholic acid. 70, 46, and 8 differentially expressed proteins were identified in Turicibacter spp. MMM721 cultured with supplements of whole chicken bile, TCDCA, and TCA, respectively, when compared to unsupplemented controls. Many of the differentially expressed proteins were involved in ribosomal processes, post-translational modifications and chaperones, and modifications to the cell surface. To our knowledge, this work represents the first description of the Turicibacter spp. MMM721 proteomic response to bile and bile acid exposure. Ultimately, the T. bilis MMM721 response to whole bile and bile acids is highly complex, with numerous proteins from a variety of functional categories being induced.
DOI: 10.21227/2vna-ms53
title: EEG data collection experiment software

description: The data collection of the human subjects' brainwaves was performed using a specific experiment of showing a set of pictures that stimulate different emotions on the human subjects. In order to create this kind of experiment, a Java application is developed by us to simulate the visual experiment with the IAPS. It is a simple Java application developed in Eclipse IDE. The main purpose of the application is to collect subjects' credential information and show in sequence the selected set of images from IAPS.
DOI: 10.5281/zenodo.5562482
title: Soil organic matter and plant carbon allocated to nitrogen acquisition simulated by the FUN-BioCROP model

description: This data package contains the model input, results, and validation data from Juice et al (citation below). The FUN-BioCROP model (Fixation and Uptake of Nitrogen- Bioenergy Carbon, Rhizosphere, Organisms, and Protection) advances the field of bioenergy modeling by integrating new empirical paradigms of the role of belowground processes in shaping coupled carbon (C) and nitrogen (N) cycles. It was developed by modifying the FUN-CORPSE model (Fixation and Uptake of Nitrogen- Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment, Sulman et al. 2017 Ecology Letters) for use in bioenergy systems by including mechanistic tillage, organic matter addition, nitrogen fertilization, harvest, and feedstock-specific parameters, and to be driven by DayCent plant productivity and biomass data.
description: {"references": ["Sulman, B. N., E. R. Brzostek, C. Medici, E. Shevliakova, D. N. L. Menge, and R. P. Phillips. 2017. Feedbacks between plant N demand and rhizosphere priming depend on type of mycorrhizal association. Ecology Letters 20:1043-1053."]}
DOI: 10.5281/zenodo.5562481
title: Soil organic matter and plant carbon allocated to nitrogen acquisition simulated by the FUN-BioCROP model

description: This data package contains the model input, results, and validation data from Juice et al (citation below). The FUN-BioCROP model (Fixation and Uptake of Nitrogen- Bioenergy Carbon, Rhizosphere, Organisms, and Protection) advances the field of bioenergy modeling by integrating new empirical paradigms of the role of belowground processes in shaping coupled carbon (C) and nitrogen (N) cycles. It was developed by modifying the FUN-CORPSE model (Fixation and Uptake of Nitrogen- Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment, Sulman et al. 2017 Ecology Letters) for use in bioenergy systems by including mechanistic tillage, organic matter addition, nitrogen fertilization, harvest, and feedstock-specific parameters, and to be driven by DayCent plant productivity and biomass data.
description: {"references": ["Sulman, B. N., E. R. Brzostek, C. Medici, E. Shevliakova, D. N. L. Menge, and R. P. Phillips. 2017. Feedbacks between plant N demand and rhizosphere priming depend on type of mycorrhizal association. Ecology Letters 20:1043-1053."]}
DOI: 10.6084/m9.figshare.12947189.v1
title: Framing the Discourses on Kurdish & Foreign Women Fighters in Three Types of Western Media.xlsx

description: Framing analysis sample (N=125), graphs, lexical/coding pad + Full list of articles used.
DOI: 10.5281/zenodo.5717349
title: Data on Laboratory bioassay of box tree moth, Cydalima perspectalis

description: Data on Laboratory bioassay of box tree moth with <em>Bacillus thuringiensis, </em>Bio1<sup>® ,</sup> Matrine<sup>®</sup> , chlorfluazuron, chromafenozide and diflubenzuron
DOI: 10.5281/zenodo.5717348
title: Data on Laboratory bioassay of box tree moth, Cydalima perspectalis

description: Data on Laboratory bioassay of box tree moth with <em>Bacillus thuringiensis, </em>Bio1<sup>® ,</sup> Matrine<sup>®</sup> , chlorfluazuron, chromafenozide and diflubenzuron
DOI: 10.6084/m9.figshare.17057801.v1
title: File_S2_BSA_commands

description: File S2, RUN_BSA1.02.py commands using File S1 as input.
DOI: 10.21227/w4ty-1k77
title: Original measured data and matlab code for "Motion Artifact Removal for Ambulatory Electrocardiography"

description: We upload the orig.inal measured ecg and impedance data, in xlxs forms, the 1st column is sampling time,the second is amplitude. We use these files and OriginPro to verify the correctness of the model. And use matlab to verify the algorithm's effectiveness.. More information if you needed,, pls connect the following email: 17112020021@fudan.edu.cn
DOI: 10.5281/zenodo.4584078
title: Simulations of Contrails Under COVID-19 Effects

description: Data in support of a manuscript under review. Tar file with model code that modifies the community atmosphere model: contrail_covid_weekly_mods.tar Base model code is: https://github.com/ESCOMP/CAM/tree/cam6_2_020 The *.nc files are netCDF files with mostly Climate and Forecast (CF) convention model output. They should be mostly self describing in the meta data: subset2_cam6220_sd_2020fullair.1.nc : 12 months with full aviation emissions, 2020 subset2_cam6220_sd_2019fullair.1.nc : 12 months with full aviation emissions, 2019 subset2_cam6220_sd_2020fullairT.1.nc: with full aviation emissions, 2020, with Temperature Nudging. subset2_cam6220_sd_2019noair.1.nc : 12 months with no aviation emissions, 2019 subset2_cam6220_sd_2020noair.1.nc: : 12 months with covid affected aviation emissions, 2020 subset2_cam6220_sd_2020covidair.1.nc : 12 months with covid aviation emissions, 2020 subset2_cam6220_sd_2020noairT.1.nc: : 12 months with covid affected aviation emissions, 2020, with temperature nudging. weekly_flight_fraction_2020all.nc : scaling for 2020 aviation emissions
DOI: 10.5281/zenodo.4584077
title: Simulations of Contrails Under COVID-19 Effects

description: Data in support of a manuscript under review. Tar file with model code that modifies the community atmosphere model: contrail_covid_weekly_mods.tar Base model code is: https://github.com/ESCOMP/CAM/tree/cam6_2_020 The *.nc files are netCDF files with mostly Climate and Forecast (CF) convention model output. They should be mostly self describing in the meta data: subset2_cam6220_sd_2020fullair.1.nc : 12 months with full aviation emissions, 2020 subset2_cam6220_sd_2019fullair.1.nc : 12 months with full aviation emissions, 2019 subset2_cam6220_sd_2020fullairT.1.nc: with full aviation emissions, 2020, with Temperature Nudging. subset2_cam6220_sd_2019noair.1.nc : 12 months with no aviation emissions, 2019 subset2_cam6220_sd_2020noair.1.nc: : 12 months with covid affected aviation emissions, 2020 subset2_cam6220_sd_2020covidair.1.nc : 12 months with covid aviation emissions, 2020 subset2_cam6220_sd_2020noairT.1.nc: : 12 months with covid affected aviation emissions, 2020, with temperature nudging. weekly_flight_fraction_2020all.nc : scaling for 2020 aviation emissions
DOI: 10.6084/m9.figshare.17057819
title: Data_BYP-A.xlsx

description: Pre and post tests data of a study exploring the effects of the BYP-A, an 8-weeks yoga program, on psychological state of Circus Artist.
DOI: 10.6084/m9.figshare.17057819.v1
title: Data_BYP-A.xlsx

description: Pre and post tests data of a study exploring the effects of the BYP-A, an 8-weeks yoga program, on psychological state of Circus Artist.
DOI: 10.6084/m9.figshare.3761562.v2049
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5281/zenodo.5675427
title: GHADA

description: GHADA is a Geo-Harmonized Atmospheric Dataset for Aerosol optical depth at 550 nm. It contains daily estimations of AOD<sub>550</sub> over Europe with 1km spatial resolution. GHADA was built based on the MODIS MCD19A2 product with 1km spatial resolution which was used as the target variable in the ML models and modelled AOD data from Copernicus Atmosphere Monitoring Service (CAMS) with 80km spatial resolution that used to overcome the high percentage of gaps found in the prementioned product. Three stages were applied to generate GHADA: first, we applied a simple average for all available pixels that passed the quality assurance criteria (QACloudMask = Clear and QAAdjacencyMask = Clear) of the MCD19A2 product. Second, we created an Extra-trees machine learning model for every year between 2018-2020 to predict the missing AOD values in the MCD19A2 using modelled AOD with enhanced spatiotemporal information. Finally, we filled MODIS MCD19A2 gaps with the predicted AOD by merging the outputs from stages one and two. Daily AOD data for each year between 2018 – 2020 during the MODIS satellite overpassing (10:30 a.m. – 1:30 p.m.) are included in this dataset. <strong>Table 1.</strong> Results of the space-time extremely randomized models used to predict the missing AOD in the MODIS MCD19A2 product for each year of the study period. <strong>Year</strong> <strong>R-squared (%)</strong> <strong>RMSE</strong> <strong>MAE</strong> 2018 92.5 0.02 0.012 2019 92.9 0.019 0.012 2020 94.1 0.016 0.010 GHADA was validate using AERONET observations and showed a good result with ~84% of the samples falling within the expected error envelopes defined for AOD products.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union.
description: {"references": ["Ibrahim, S.; Landa, M.; Pe\u0161ek, O.; Pavelka, K.; Halounova, L. Space-Time Machine Learning Models to Analyze COVID-19 Pandemic Lockdown Effects on Aerosol Optical Depth over Europe. Remote Sens. 2021, 13, 3027. https://doi.org/10.3390/rs13153027"]}