cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10008815
title: Focal-TSMP: Deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation

description: This is the preprocessed remote sensing dataset used in the paper "Focal-TSMP: Deep learning for vegetation health prediction and agricultural drought assessment from a regional climate simulation". It contains the preprocessed NOAA data along with the additional files necessary for the TSMP simulation.
description: Check our code on GitHub to see how to download and to do the post-processing with TSMP simulation: https://github.com/HakamShams/Focal_TSMP
description: NOAA remote sensing vegetation products:

Smoothed noise removed normalized difference vegetation index (SMN)
Smoothed noise removed brightness temperature (SMT)
Mask for cold surfaces and invalid pixels
NOAA climatology for the years 1981-1988
NOAA climatology for the years 1989-2016
Mask for the valid pixels over land
Static variables
TSMP statistics
description: Please check the license for NOAA STAR data at (https://www.star.nesdis.noaa.gov/star/productdisclaimer.php). The license for TSMP simulation can be found at Forschungszentrum Juelich Research Center (https://datapub.fz-juelich.de/slts/cordex/index.html) and the license for the static variables can be found at (https://datapub.fz-juelich.de/slts/regional_climate_tsmp_hi-cam/index.html).
DOI: 10.5281/zenodo.1303837
title: Preprocessing scripts and data for study: Pathway-Based Subnetworks Enable Cross-Disease Biomarker Discovery

description: Supplementary File 1 containing preprocessing scripts and data for converting pathway databases into subnetworks.
DOI: 10.5281/zenodo.1303838
title: Preprocessing scripts and data for study: Pathway-Based Subnetworks Enable Cross-Disease Biomarker Discovery

description: Supplementary File 1 containing preprocessing scripts and data for converting pathway databases into subnetworks.
DOI: 10.6084/m9.figshare.24328462
title: The respiratory microbiota of three cohabiting beluga whales (<i>Delphinapterus leucas</i>) under human care

description: We sampled the respiratory mucus from voluntary blowhole exhalations (“blow”) of three healthy beluga whales (<i>Delphinapterus leucas</i>) under professional human care. Blow samples were collected from three resident belugas, one adult male (M1) and two adult females (F1, F2), with voluntary behaviors via non-invasive methods over three days in July 2021 (four days for M1). Samples were weighed and examined microscopically for the enumeration of eukaryotic and prokaryotic microbes, and then were used to evaluate carbon substrate use and taxonomic diversity of prokaryotic communities in the host respiratory sytem. Microscopical observations and 18S rRNA gene sequencing indicated the presence of eukaryotic microbiota, the ciliate genera <i>Planilamina</i> and <i>Kyaroikeus</i> in all three individuals Exposure of samples to different metabolic carbon substrates indicated significant differences in the number of carbon sources usable by the prokaryotic communities of different whales (range: 11-25 sources), as well as a signficantly decreased diversity of carbon sources used by the community in the habitat water (5 sources). Sequencing of the hypervariable V4 region of the 16S rRNA gene revealed 19 amplicon sequence variants (ASVs) that were present in all whale samples. In α-diversity, the oldest female <i>D. leucas</i> (F2) had the lowest overall diversity, and was significantly different from M1 and F1 in taxon composition, including an anomalously low ratio of Baccillota: Bacteroidota (0.01) compared to the other whales. In group pairwise ANOSIM comparisons of microbial community composition, M1 had a significantly higher diversity than F1 and F2. These results suggest that attention should be given to regular microbiome sampling, and indicate a need for the pairing of microbiome and clinical data for animals in aquaria. Overall, these data contribute to the growing database on the core respiratory microbiota in cohabiting cetaceans under professional human care, indicate the utility of non-invasive sampling, and help characterize a baseline for healthy <i>D. leucas.</i>
DOI: 10.6084/m9.figshare.24328462.v1
title: The respiratory microbiota of three cohabiting beluga whales (<i>Delphinapterus leucas</i>) under human care

description: We sampled the respiratory mucus from voluntary blowhole exhalations (“blow”) of three healthy beluga whales (<i>Delphinapterus leucas</i>) under professional human care. Blow samples were collected from three resident belugas, one adult male (M1) and two adult females (F1, F2), with voluntary behaviors via non-invasive methods over three days in July 2021 (four days for M1). Samples were weighed and examined microscopically for the enumeration of eukaryotic and prokaryotic microbes, and then were used to evaluate carbon substrate use and taxonomic diversity of prokaryotic communities in the host respiratory sytem. Microscopical observations and 18S rRNA gene sequencing indicated the presence of eukaryotic microbiota, the ciliate genera <i>Planilamina</i> and <i>Kyaroikeus</i> in all three individuals Exposure of samples to different metabolic carbon substrates indicated significant differences in the number of carbon sources usable by the prokaryotic communities of different whales (range: 11-25 sources), as well as a signficantly decreased diversity of carbon sources used by the community in the habitat water (5 sources). Sequencing of the hypervariable V4 region of the 16S rRNA gene revealed 19 amplicon sequence variants (ASVs) that were present in all whale samples. In α-diversity, the oldest female <i>D. leucas</i> (F2) had the lowest overall diversity, and was significantly different from M1 and F1 in taxon composition, including an anomalously low ratio of Baccillota: Bacteroidota (0.01) compared to the other whales. In group pairwise ANOSIM comparisons of microbial community composition, M1 had a significantly higher diversity than F1 and F2. These results suggest that attention should be given to regular microbiome sampling, and indicate a need for the pairing of microbiome and clinical data for animals in aquaria. Overall, these data contribute to the growing database on the core respiratory microbiota in cohabiting cetaceans under professional human care, indicate the utility of non-invasive sampling, and help characterize a baseline for healthy <i>D. leucas.</i>
DOI: 10.5517/ccdc.csd.cc2g8b25
title: CCDC 2272116: Experimental Crystal Structure Determination

description: Related Article: Wang Jie|2023|CSD Communication|||
description: Related Article: Jie Wang, Shan-Shan Wang, Jun Xiao, Yu-Jie He, Xin-Yan Wu, Xingguang Li, Pei-Nian Liu|2023|Chem.Commun.|59|12495|doi:10.1039/D3CC03950A
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.cc2g8b36
title: CCDC 2272117: Experimental Crystal Structure Determination

description: Related Article: Wang Jie|2023|CSD Communication|||
description: Related Article: Jie Wang, Shan-Shan Wang, Jun Xiao, Yu-Jie He, Xin-Yan Wu, Xingguang Li, Pei-Nian Liu|2023|Chem.Commun.|59|12495|doi:10.1039/D3CC03950A
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: 10.15139/s3/l3dtdj
title: God of the good gaps: Prevalence, eliciting situations, and demonstrations of gratitude to god as compared to interpersonal gratitude, 2023

description: Overview: Researchers recruited 1,270 Christian, Jewish, Hindu, and Muslim participants for this online study on how religious individuals express gratitude to God. Procedure: Participants were randomly assigned to one of two priming conditions. Participants in the God-prime condition were prompted to write about their relationship with God for two minutes; participants in the neutral-prime condition observed and wrote about their favorite colors in the surrounding environment. Participants then completed three tasks. First, they were prompted to think about an achievement in their life, write a response that expressed gratitude for that achievement, and complete self-report measures that evaluated to whom they attributed that success. Then, participants were asked to recall a time when they expressed gratitude to God, write about that time, and create a list of 1-7 strategies that they use to show gratitude to God. Finally, participants repeated the same steps in task two, but answered the prompt regarding gratitude to other people. Measures: The survey consisted of open response and multiple-choice questions. Attribution of success was measured using a nine-item assessment that included an Attribution to God scale, an Attribution to Self scale, and an Attribution to Other People scale. An existing scale by Mahoney et. Al (2003) was modified to generate the Attribution to God Scale. The Attribution to Self and Other People scales were developed for the purpose of this study. Three other variables, targets of gratitude, reasons for gratitude, and demonstrations of gratitude, were assessed by coding participants’ open responses. Other measures in the data set which were not reported on include social desirability, plans for Thanksgiving, and names of gods worshipped by Hindu participants. Sample: The sample was diverse in regards to gender and race. White/Caucasian participants accounted for 54% of the sample. Female participants accounted for 60.7% of the sample. Participants were 18 years of age and older, with the median age of the sample being 39.86. This study was approved by Duke Campus IRB and registered as Study 2021-0208.
DOI: 10.25346/s6/5o4lga
title: Pizzagate conspiracy archive

description: Message board posts and web pages contributed by participants in the "Pizzagate" conspiracy theory during the 2016 United States presidential election campaign.
DOI: 10.25346/s6/5o4lga/olknvx
title: pizzagate.tgz
DOI: 10.18739/a29k45v32
title: Atmospheric methane across the Last Glacial Maximum from the West Antarctic Ice Sheet (WAIS) Divide, North Greenland Eemian Ice Drilling (NEEM), and Greenland Ice Sheet Project Two (GISP2) ice cores.

description: This dataset includes measurements of atmospheric methane from samples from the North Greenland Eemian Ice Drilling (NEEM), Greenland Ice Sheet Project Two (GISP2) and West Antarctic Ice Sheet (WAIS) Divide ice cores. All measurements were made at the Oregon State University Ice Core and Quaternary Geochemistry Laboratory (Corvallis, OR) using an established analytical system. 433 samples from the NEEM ice core were measured between 1420 and 1560 meter depths. A measurement uncertainty ranging from 2.8 to 4.2 parts per billion (ppb), depending on the measurement year, was determined from replicate samples. 340 samples from the GISP2 ice core were measured between 1740 and 2060 meter depths. A measurement uncertainty ranging from 3.1 to 3.4 ppb, depending on the measurement year, was determined from replicate samples. All GISP2 and NEEM data were corrected for excess methane contamination using the established relationship between excess methane and Ca2+ (Lee et al., 2020). Both corrected and uncorrected data are included in the publication. 340 samples from the GISP2 ice core were measured between 1957 and 3081 meter depths. A measurement uncertainty ranging from 3.1 to 3.4 ppb, depending on the measurement year, was determined from replicate samples. Depths reflect the mid-points of the depth range of each samples, which is typically ~8cm. Lee, J. E. et al. Excess methane in Greenland ice cores associated with high dust concentrations. Geochimica et cosmochimica acta 270, 409-430 (2020).
DOI: 10.18739/a25t3g19q
title: Excess methane data from the Greenland Ice Sheet Project Two (GISP2) and North Greenland Eemian Ice Drilling (NEEM) ice cores, 1400-2400 meter depth

description: This dataset includes new measurements of in-situ, non-atmospheric methane release during the melt-refreeze analysis of ice samples for atmospheric methane measurement, also known as excess methane (CH4xs). All measurements were made at the Oregon State University Ice Core Laboratory and followed the methods of Lee et al., 2020 and Mitchell et al., 2013. Measurements were made using ice from the Greenland Ice Sheet Project Two (GISP2) and North Greenland Eemian Ice Drilling (NEEM) ice cores in 2018, 2019, and 2021. In total, 70 new measurements were made on NEEM ice and 406 measurements on GISP2 ice. The Ca2+ content of the ice was calculated using the published Ca2+ concentration records, and the mass and depth ranges of each sample. For GISP2, the year the measurement was made is included. Mitchell, L., Brook, E., Lee, J. E., Buizert, C. &amp;amp;amp;amp; Sowers, T. Constraints on the late Holocene anthropogenic contribution to the atmospheric methane budget. Science 342, 964-966 (2013). Lee, J. E. et al. Excess methane in Greenland ice cores associated with high dust concentrations. Geochimica et cosmochimica acta 270, 409-430 (2020).
DOI: 10.21223/2za5au/5clucd
title: 04_Data_Dictionary.txt

description: :unav
DOI: 10.21223/2za5au/elaone
title: 02_Fieldbook_TPHEN200512_LAVICT_GxE.txt

description: :unav
DOI: 10.21223/2za5au/amu8fm
title: 03_Material_list.txt

description: :unav
DOI: 10.21223/2za5au/hzw2gq
title: TPHEN200512_LAVICT_GxE.xls

description: :unav
DOI: 10.21223/2za5au/zsse4t
title: 01_Fieldbook_TPHEN200512_AYMARA_GxE.txt

description: :unav
DOI: 10.21223/2za5au
title: Dataset for: Study of environmental effect on phenolic compound concentrations in Junin and Huancavelica, 2005

description: The objective of this study was to assess variations in polyphenolic compounds among a total of forty native potato varieties. The experiment employed a randomized complete design (CRD) with three replications. These varieties were cultivated in both Huancayo, Junin, and Aymara, Huancavelica
DOI: 10.21223/2za5au/jggxjs
title: TPHEN200512_AYMARA_GxE.xls

description: :unav
DOI: 10.6084/m9.figshare.24328507
title: Untitled Item

description: Data for manuscript "<b>Palmitic Acid Promotes Atherosclerotic Plaque Vulnerability in Type 2 Diabetes Mellitus through Macrophage Dll4 Signaling-Induced VSMCs Senescence</b>"
DOI: 10.6084/m9.figshare.24328507.v1
title: Untitled Item

description: Data for manuscript "<b>Palmitic Acid Promotes Atherosclerotic Plaque Vulnerability in Type 2 Diabetes Mellitus through Macrophage Dll4 Signaling-Induced VSMCs Senescence</b>"
DOI: 10.18739/a2222r75w
title: Atmospheric methane interpolar difference, four-box troposphere modeled sources, last glacial maximum and deglaciation, Greenland and Antarctica

description: This dataset includes estimates of the atmospheric methane relative interpolar difference (rIPD) across the Last Glacial Maximum and Deglaciation. The rIPD was calculated using discrete, high-resolution methane measurements from the Western Antarctic Ice Sheet (WAIS) Divide, Northern Greenland Eemian (NEEM) and Greenland Ice Sheet Project Two (GISP2) ice cores. Two independent interpolar difference (IPD) records were determined: One using NEEM and WAIS and one using GISP2 and WAIS. The dataset includes rIPD values calculated using both Greenland methane data both corrected and uncorrected for excess methane (Lee et al., 2020). The rIPD was calculated by smoothing each methane record and synchronizing them to the WD2014 gas age scale. 1-sigma rIPD uncertainties are included. This dataset also includes the output of the four-box troposphere model used to interpret the rIPD. For both excess methane-corrected records, the model output and 1-sigma uncertainty is provided for northern extratropical (30N - 90N) and total tropical (30S - 30N) sources in teragrams per year (Tg yr-1). For the NEEM-derived rIPD, sections of the rIPD where atmospheric methane changed rapidly were deemed untrustworthy were removed from the dataset. Lee, J. E. et al. Excess methane in Greenland ice cores associated with high dust concentrations. Geochimica et cosmochimica acta 270, 409-430 (2020).
DOI: 10.6084/m9.figshare.24328528.v1
title: database.xlsx

description: Life cycle inventory for PV applications
DOI: 10.6084/m9.figshare.24328528
title: database.xlsx

description: Life cycle inventory for PV applications
DOI: 10.5517/ccdc.csd.cc2bvfh4
title: CCDC 2170356: Experimental Crystal Structure Determination

description: Related Article: Shuai Zhang, Lei Wang, Yilan Wang, Xiaoming Wang, Shi Ye|2023|J.Phys.Chem.Lett.|14|7773|doi:10.1021/acs.jpclett.3c02139
description: Related Article: Shuai Zhang, Lei Wang, Yilan Wang, Xiaoming Wang, Shi Ye|2023|CSD Communication|||
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.cc2fr8dw
title: CCDC 2256688: Experimental Crystal Structure Determination

description: Related Article: Jett T. Janetzki, Maxim G. Chegerev, Gemma K. Gransbury, Robert W. Gable, Jack K. Clegg, Roger J. Mulder, Guy N. L. Jameson, Alyona A. Starikova, Colette Boskovic|2023|Inorg.Chem.|62|15719|doi:10.1021/acs.inorgchem.3c02598
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.cc2fr8fx
title: CCDC 2256689: Experimental Crystal Structure Determination

description: Related Article: Jett T. Janetzki, Maxim G. Chegerev, Gemma K. Gransbury, Robert W. Gable, Jack K. Clegg, Roger J. Mulder, Guy N. L. Jameson, Alyona A. Starikova, Colette Boskovic|2023|Inorg.Chem.|62|15719|doi:10.1021/acs.inorgchem.3c02598
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.cc2fr8hz
title: CCDC 2256691: Experimental Crystal Structure Determination

description: Related Article: Jett T. Janetzki, Maxim G. Chegerev, Gemma K. Gransbury, Robert W. Gable, Jack K. Clegg, Roger J. Mulder, Guy N. L. Jameson, Alyona A. Starikova, Colette Boskovic|2023|Inorg.Chem.|62|15719|doi:10.1021/acs.inorgchem.3c02598
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.cc2fr8j0
title: CCDC 2256692: Experimental Crystal Structure Determination

description: Related Article: Jett T. Janetzki, Maxim G. Chegerev, Gemma K. Gransbury, Robert W. Gable, Jack K. Clegg, Roger J. Mulder, Guy N. L. Jameson, Alyona A. Starikova, Colette Boskovic|2023|Inorg.Chem.|62|15719|doi:10.1021/acs.inorgchem.3c02598
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.cc2fr8k1
title: CCDC 2256693: Experimental Crystal Structure Determination

description: Related Article: Jett T. Janetzki, Maxim G. Chegerev, Gemma K. Gransbury, Robert W. Gable, Jack K. Clegg, Roger J. Mulder, Guy N. L. Jameson, Alyona A. Starikova, Colette Boskovic|2023|Inorg.Chem.|62|15719|doi:10.1021/acs.inorgchem.3c02598
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.cc2fr8l2
title: CCDC 2256694: Experimental Crystal Structure Determination

description: Related Article: Jett T. Janetzki, Maxim G. Chegerev, Gemma K. Gransbury, Robert W. Gable, Jack K. Clegg, Roger J. Mulder, Guy N. L. Jameson, Alyona A. Starikova, Colette Boskovic|2023|Inorg.Chem.|62|15719|doi:10.1021/acs.inorgchem.3c02598
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.cc2gkg4n
title: CCDC 2280891: Experimental Crystal Structure Determination

description: Related Article: Samuel L. Powley, Charlotte Riley, Hwan-Hee Cho, Nguyen Le Phuoc, Mikko Linnolahti, Neil Greenham, Alexander S. Romanov|2023|Chem.Commun.|59|12035|doi:10.1039/D3CC04091G
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.cc2gkg5p
title: CCDC 2280892: Experimental Crystal Structure Determination

description: Related Article: Samuel L. Powley, Charlotte Riley, Hwan-Hee Cho, Nguyen Le Phuoc, Mikko Linnolahti, Neil Greenham, Alexander S. Romanov|2023|Chem.Commun.|59|12035|doi:10.1039/D3CC04091G
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.cc2gkg6q
title: CCDC 2280893: Experimental Crystal Structure Determination

description: Related Article: Samuel L. Powley, Charlotte Riley, Hwan-Hee Cho, Nguyen Le Phuoc, Mikko Linnolahti, Neil Greenham, Alexander S. Romanov|2023|Chem.Commun.|59|12035|doi:10.1039/D3CC04091G
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.