cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7880981
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 500m SIN Grid in 2017

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500 m spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500 m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2017. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2016</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2018</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2017 Spatial Resolution: 500 m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7880980
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 500m SIN Grid in 2017

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 500 m spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 500 m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2017. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2016</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2018</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2017 Spatial Resolution: 500 m Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.6084/m9.figshare.22714480
title: SquashWorkRawData.xlsx

description: Datasets from a companion planting experiment with the use of marigold and cowpea intercropped with squash and the application of an organic insecticidal soap. Data taken in the fall of 2016 & 2017 on 1) arthropods observed in situ, caught on sticky traps and pan traps, and leaf discs (whitefly counts); 2) squash silverleaf disorder; 3) squash marketable yield.
DOI: 10.6084/m9.figshare.22714480.v1
title: SquashWorkRawData.xlsx

description: Datasets from a companion planting experiment with the use of marigold and cowpea intercropped with squash and the application of an organic insecticidal soap. Data taken in the fall of 2016 & 2017 on 1) arthropods observed in situ, caught on sticky traps and pan traps, and leaf discs (whitefly counts); 2) squash silverleaf disorder; 3) squash marketable yield.
DOI: 10.26180/21715979.v2
title: Aspirin in Reducing Events in the Elderly eXTension (ASPREE-XT)

description: ASPREE (ASPirin in Reducing Events in the Elderly) was a joint US/Australian randomized clinical trial aiming to determine whether low-dose aspirin increases healthy life-span, defined as survival free of dementia and disability. ASPREE began in 2010 and completed recruitment in 2014. It was a randomized, double-blind, placebo controlled, primary prevention trial of daily 100 mg of aspirin in older people free of cardiovascular disease, dementia and physical disability in the United States (US) and Australia with a period of follow-up averaging 4.5 years. ASPREE's primary outcome was duration of survival free of dementia and persistent physical disability and had secondary outcomes encompassing the major health issues related to aging. The trial involving 19,114 persons aged 70 and above (65 years and above for US minorities) is distinctive for its large size, methodological rigor and high participant retention rate in both countries. ASPREE-XT is a post-treatment, longitudinal observational follow-up study of ASPREE participants that began in January 2018. This enables the monitoring of possible legacy effects of aspirin treatment, primarily on cancer incidence, metastases and mortality. In addition, the large well-characterized cohort with extended follow-up and a range of health outcomes provides a unique opportunity to study health and resilience in older individuals.
DOI: 10.26180/21715979.v1
title: Aspirin in Reducing Events in the Elderly eXTension (ASPREE-XT)

description: ASPREE (ASPirin in Reducing Events in the Elderly) was a joint US/Australian randomized clinical trial aiming to determine whether low-dose aspirin increases healthy life-span, defined as survival free of dementia and disability. ASPREE began in 2010 and completed recruitment in 2014. It was a randomized, double-blind, placebo controlled, primary prevention trial of daily 100 mg of aspirin in older people free of cardiovascular disease, dementia and physical disability in the United States (US) and Australia with a period of follow-up averaging 4.5 years. ASPREE's primary outcome was duration of survival free of dementia and persistent physical disability and had secondary outcomes encompassing the major health issues related to aging. The trial involving 19,114 persons aged 70 and above (65 years and above for US minorities) is distinctive for its large size, methodological rigor and high participant retention rate in both countries. ASPREE-XT is a post-treatment, longitudinal observational follow-up study of ASPREE participants that began in January 2018. This enables the monitoring of possible legacy effects of aspirin treatment, primarily on cancer incidence, metastases and mortality. In addition, the large well-characterized cohort with extended follow-up and a range of health outcomes provides a unique opportunity to study health and resilience in older individuals.
DOI: 10.26179/yfx6-rn78
title: Casey-Vostok Line, Reduced Radiosonde Data, 1984
DOI: 10.5281/zenodo.7699122
title: evandethier/global-river-mining

description: <strong>Data files for analyzing the effects of gold and precious mineral mining in river systems. </strong>This work is a global-scale application of satellite remote sensing of river water quality, particularly of suspended sediment in rivers. The project is summarized (and version control more rigorously maintained) at https://github.com/evandethier/global-alluvial-mining. All files necessary for producing the results are in the imports.zip file. All R Code to do these analyses are in the R.zip file. <em>If the files in the imports folder are arranged in the correct structure</em>, running the R files in sequence will produce the findings and most figures. All Google Earth Engine code is in the GEE.zip file. However, all the outputs generated by the GEE code are in the imports.zip file. I suggest beginning a new R project. It's important that you put the imports folder in the folder where you create the R project. The imports folder must be called `imports` and all sub-folders must also keep their names. <strong>Note that this code will create new folders and files on your computer. </strong>However, it does not delete pre-existing files. Some help navigating can be provided by the following spreadsheets: Where files are created and imported is given in `global_river_mining_where_files_are_in_code.xlsx` Where figures are created is given in `global_river_mining_where_figs_are_in_code.xlsx` -- Evan Dethier, 1 May 2023 https://github.com/evandethier * * * Related work has been published here: <strong>Applications:</strong> Dethier, E. N., Renshaw, C. E., & Magilligan, F. J. (2022). Rapid changes to global river suspended sediment flux by humans. <em>Science, 376</em>(6600), 1447-1452. DOI: 10.1126/science.abn798 Dethier, E. N., Sartain, S. L., & Lutz, D. A. (2019). Heightened levels and seasonal inversion of riverine suspended sediment in a tropical biodiversity hot spot due to artisanal gold mining. <em>Proceedings of the National Academy of Sciences of the United States of America, 116</em>(48), 23936-23941. doi:10.1073/pnas.1907842116 <strong>Methods: </strong> Dethier, E. N., Renshaw, C. E., & Magilligan, F. J. (2020). Toward Improved Accuracy of Remote Sensing Approaches for Quantifying Suspended Sediment: Implications for Suspended-Sediment Monitoring. <em>Journal of Geophysical Research: Earth Surface, 125</em>(7), e2019JF005033. doi:10.1029/2019jf005033
DOI: 10.5281/zenodo.7699121
title: evandethier/global-river-mining

description: <strong>Data files for analyzing the effects of gold and precious mineral mining in river systems. </strong>This work is a global-scale application of satellite remote sensing of river water quality, particularly of suspended sediment in rivers. The project is summarized (and version control more rigorously maintained) at https://github.com/evandethier/global-alluvial-mining. All files necessary for producing the results are in the imports.zip file. All R Code to do these analyses are in the R.zip file. <em>If the files in the imports folder are arranged in the correct structure</em>, running the R files in sequence will produce the findings and most figures. All Google Earth Engine code is in the GEE.zip file. However, all the outputs generated by the GEE code are in the imports.zip file. I suggest beginning a new R project. It's important that you put the imports folder in the folder where you create the R project. The imports folder must be called `imports` and all sub-folders must also keep their names. <strong>Note that this code will create new folders and files on your computer. </strong>However, it does not delete pre-existing files. Some help navigating can be provided by the following spreadsheets: Where files are created and imported is given in `global_river_mining_where_files_are_in_code.xlsx` Where figures are created is given in `global_river_mining_where_figs_are_in_code.xlsx` -- Evan Dethier, 1 May 2023 https://github.com/evandethier * * * Related work has been published here: <strong>Applications:</strong> Dethier, E. N., Renshaw, C. E., & Magilligan, F. J. (2022). Rapid changes to global river suspended sediment flux by humans. <em>Science, 376</em>(6600), 1447-1452. DOI: 10.1126/science.abn798 Dethier, E. N., Sartain, S. L., & Lutz, D. A. (2019). Heightened levels and seasonal inversion of riverine suspended sediment in a tropical biodiversity hot spot due to artisanal gold mining. <em>Proceedings of the National Academy of Sciences of the United States of America, 116</em>(48), 23936-23941. doi:10.1073/pnas.1907842116 <strong>Methods: </strong> Dethier, E. N., Renshaw, C. E., & Magilligan, F. J. (2020). Toward Improved Accuracy of Remote Sensing Approaches for Quantifying Suspended Sediment: Implications for Suspended-Sediment Monitoring. <em>Journal of Geophysical Research: Earth Surface, 125</em>(7), e2019JF005033. doi:10.1029/2019jf005033
DOI: 10.5281/zenodo.7882360
title: MiniImageNet pickle files for learn2learn library

description: MiniImageNet pickle files for learn2learn library - please move these files to ~/data/l2l_data (or whereever your l2l_data directory is) in order for MAML and USL experiments to properly run and recognize MiniImageNet.
DOI: 10.5281/zenodo.7882359
title: MiniImageNet pickle files for learn2learn library

description: MiniImageNet pickle files for learn2learn library - please move these files to ~/data/l2l_data (or whereever your l2l_data directory is) in order for MAML and USL experiments to properly run and recognize MiniImageNet.
DOI: 10.5517/ccdc.csd.cc2bynhg
title: CCDC 2173456: Experimental Crystal Structure Determination

description: Related Article: Si-Hui Tan, Zhao-Hui Chen, Xi Jiang, Guo-Qing Zhong|2023|J.Solid State Chem.|323|124061|doi:10.1016/j.jssc.2023.124061
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.cc2c4c96
title: CCDC 2178937: Experimental Crystal Structure Determination

description: Related Article: Si-Hui Tan, Zhao-Hui Chen, Xi Jiang, Guo-Qing Zhong|2023|J.Solid State Chem.|323|124061|doi:10.1016/j.jssc.2023.124061
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.cc2c6tn2
title: CCDC 2181304: Experimental Crystal Structure Determination

description: Related Article: Xing Cai, Jie Xie, Chenglong Wang, Zhiying Ma, Guangxia Wang, Hua Wang|2023|Dyes Pigm.|216|111309|doi:10.1016/j.dyepig.2023.111309
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.cc2c6tp3
title: CCDC 2181305: Experimental Crystal Structure Determination

description: Related Article: Xing Cai, Jie Xie, Chenglong Wang, Zhiying Ma, Guangxia Wang, Hua Wang|2023|Dyes Pigm.|216|111309|doi:10.1016/j.dyepig.2023.111309
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: 10.26183/4xyj-7930
title: Rediscovering leadership through multiple lenses of leadership in Australia.

description: Qualitative interviews with academics, politicians, not-for-profit CEOs and Corporate executives to understand leadership in crisis, the challenges of leadership and the attributes of effective leaders in crisis. This will lead to the development of a measurement tool for effective leadership in crisis situations. Interview transcripts contain actual data files with questions. However, the identifications of the respondents were removed from the transcripts.  To discuss access to the data contact Ataus Samad at a.samad@westernsydney.edu.au
DOI: 10.6084/m9.figshare.20406168
title: Breastfeeding Perception Attitude Merge Dataset.csv

description: Breastfeeding is the best source of nutrition for infants. Identifying current attitudes is essential in the effort toward normalizing breastfeeding in communities, including university campuses. The study explored campus community knowledge, awareness and attitudes on breastfeeding, including available resources and laws on two university campuses in the southern United States. This cross-sectional, self-reporting study utilized the Iowa Infant Feeding Attitude Scale and an adaptation of the Breastfeeding Behavior Questionnaire to survey a convenience sample. Results revealed time constraints, availability of private lactation space, and insufficient public appreciation of breastfeeding’s unique advantages to lactating parent and infant as barriers to breastfeeding. Study results will help develop additional breastfeeding strategies to improve university campus community breastfeeding initiatives.
DOI: 10.6084/m9.figshare.20406168.v1
title: Breastfeeding Perception Attitude Merge Dataset.csv

description: Breastfeeding is the best source of nutrition for infants. Identifying current attitudes is essential in the effort toward normalizing breastfeeding in communities, including university campuses. The study explored campus community knowledge, awareness and attitudes on breastfeeding, including available resources and laws on two university campuses in the southern United States. This cross-sectional, self-reporting study utilized the Iowa Infant Feeding Attitude Scale and an adaptation of the Breastfeeding Behavior Questionnaire to survey a convenience sample. Results revealed time constraints, availability of private lactation space, and insufficient public appreciation of breastfeeding’s unique advantages to lactating parent and infant as barriers to breastfeeding. Study results will help develop additional breastfeeding strategies to improve university campus community breastfeeding initiatives.
DOI: 10.5281/zenodo.7882404
title: Processed dataset used to train models in the study "Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention"

description: The processed dataset used to train models in the study "Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention".
DOI: 10.5281/zenodo.7882403
title: Processed dataset used to train models in the study "Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention"

description: The processed dataset used to train models in the study "Integrative modeling of lncRNA-chromatin interaction maps reveals diverse mechanisms of nuclear retention".
DOI: 10.25345/c5348gs2x
title: MassIVE MSV000091829 - GNPS 230501_0428_MVs_D. acidovorans
title: MS/MS spectrum of small molecules in Membrane vesicles collected from D. acidovorans.
DOI: 10.5281/zenodo.7882451
title: Soil temperature measurements at Gobabeb in December 2017

description: Dataset containing the measurements at 1 min interval of the soil temperature at different depths (5,10,20,30,50,100 cm) in the Gobabeb site in Namibia (-23.56N 15.04E).
DOI: 10.5281/zenodo.7882450
title: Soil temperature measurements at Gobabeb in December 2017

description: Dataset containing the measurements at 1 min interval of the soil temperature at different depths (5,10,20,30,50,100 cm) in the Gobabeb site in Namibia (-23.56N 15.04E).
DOI: 10.7910/dvn/yz8xfy
title: Replication Data for: 'Welcoming' Guests: The Role of Ideational and Contextual Factors in Public Perceptions About Refugees and Attitudes about Their Integration

description: Data and do file to replicate the analyses made in the article
DOI: 10.6084/m9.figshare.22724648
title: NO at low concentration can enhance the formation of highly oxygenated biogenic molecules in the atmosphere

description: The data used to support plotting the main figures in the manuscript of " NO at low concentration can enhance the formation of highly oxygenated biogenic molecules in the atmosphere".
DOI: 10.5517/ccdc.csd.cc2dr5zb
title: CCDC 2226822: Experimental Crystal Structure Determination

description: Related Article: Laxmi Devkota, Daniel J. SantaLucia, Amelia M. Wheaton, Alexander J. Pienkos, Sergey V. Lindeman, J. Krzystek, Mykhaylo Ozerov, John F. Berry, Joshua Telser, Adam T. Fiedler|2023|Inorg.Chem.|62|5984|doi:10.1021/acs.inorgchem.2c04468
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.cc2dr60d
title: CCDC 2226823: Experimental Crystal Structure Determination

description: Related Article: Laxmi Devkota, Daniel J. SantaLucia, Amelia M. Wheaton, Alexander J. Pienkos, Sergey V. Lindeman, J. Krzystek, Mykhaylo Ozerov, John F. Berry, Joshua Telser, Adam T. Fiedler|2023|Inorg.Chem.|62|5984|doi:10.1021/acs.inorgchem.2c04468
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.cc2dr61f
title: CCDC 2226824: Experimental Crystal Structure Determination

description: Related Article: Laxmi Devkota, Daniel J. SantaLucia, Amelia M. Wheaton, Alexander J. Pienkos, Sergey V. Lindeman, J. Krzystek, Mykhaylo Ozerov, John F. Berry, Joshua Telser, Adam T. Fiedler|2023|Inorg.Chem.|62|5984|doi:10.1021/acs.inorgchem.2c04468
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.cc2dr62g
title: CCDC 2226825: Experimental Crystal Structure Determination

description: Related Article: Laxmi Devkota, Daniel J. SantaLucia, Amelia M. Wheaton, Alexander J. Pienkos, Sergey V. Lindeman, J. Krzystek, Mykhaylo Ozerov, John F. Berry, Joshua Telser, Adam T. Fiedler|2023|Inorg.Chem.|62|5984|doi:10.1021/acs.inorgchem.2c04468
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.