cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6275992
title: data set related to article A novel multidimensional questionnaire for the assessment of emotional dysregulation in adolescents: Reactivity, Intensity, Polarity and Stability questionnaire-youth version (RIPoSt-Y)

description: This record contains raw data related to article A novel multidimensional questionnaire for the assessment of emotional dysregulation in adolescents: Reactivity, Intensity, Polarity and Stability questionnaire-youth version (RIPoSt-Y)
DOI: 10.48370/ofd/ttcyjd
title: Plicatura crispa (Pers.) Rea, 298

description: Fungarium Makromycetes
DOI: 10.17632/v9twgk5p4d.2
title: Mao Qigui_Huangshan deformation_2022

description: S Table 1. Zircon U-Pb ages of granitic dike and sediments from the Huangshan area in eastern orogen, NW China.
S Table 2. Apatite U-Pb ages of granitic dike from the Huangshan area in eastern orogen, NW China.
S Table 3 Summary for published geochronological results for the Kangur shear zone
S Table 4 Summary of the structural occurrences in the Huangshan area in eastern orogen, NW China.  
Supplementary Analytical method
DOI: 10.17632/495z7s99zs.2
title: Proteomics and phosphoproteomics datasets of a muscle-specific STIM1 loss-of-function mouse model.

description: STIM1 is an ER/SR transmembrane protein that interacts with ORAI1 to activate store operated Ca2+ entry (SOCE) upon ER/SR depletion of calcium. Normally highly expressed in skeletal muscle, STIM1 deficiency causes significant changes to mitochondrial ultrastructure that do not occur with loss of ORAI1 or other components of SOCE. The datasets in this article are from large-scale proteomics and phosphoproteomics experiments in an inducible mouse model of skeletal muscle-specific STIM1 knock out (KO). These data reveal statistically significant changes in the relative abundance of specific proteins and sites of protein phosphorylation in STIM1 KO gastrocnemius. Protein samples from five biological replicates of each condition (+/- STIM1) were enzymatically digested, the resulting peptides labeled with tandem mass tag (TMT) reagents, mixed, and fractionated.  Phosphopeptides were enriched and a small amount of each input retained for protein abundance analysis. All phosphopeptide and input fractions were analyzed by nano LC-MS/MS on a Q Exactive Plus Orbitrap mass spectrometer, searched with Proteome Discoverer software, and processed with in-house R-scripts for data normalization and statistical analysis.
DOI: 10.17632/vp27db45nm.1
title: FAVORABILIDAD GEOTÉRMICA APLICANDO EL MÉTODO DE ANÀLISIS GEOTHERMAL PLAY FAIRWAY  ÁREA 2, Sierras Subandinas, Cuenca de Tucumán y su extensión en la provincia de Santiago del Estero, Argentina

description: Geospatial data provided in shapefile and GeoTiff formats.
DOI: 10.17632/2zvst4kg2w.1
title: Autonomous fuelled directional rotation about a covalent single bond

description: Experimental data for the article titled "Autonomous fuelled directional rotation about a covalent single bond" by Borsley et al. This work describes a the autonomous chemically fuelled directional rotation of a rotor relative to a stator about a covalent single bond in a small molecule molecular motor.

Includes data for NMR spectroscopy, HPLC, CD spectroscopy, mass spectrometry and computation. Please contact the corresponding author if you require anything else.
DOI: 10.11588/data/t3mib0/fidtr9
title: Covid Ag SR_MA Update.xlsx

description: :unav
DOI: 10.25934/pr00005840.1
title: Available IPD datapackage for study 'A Randomised, Double-blind, Parallel-group, Placebo-controlled, Duloxetine-referenced, Fixed-dose Study Evaluating the Efficacy and Safety of Three Dosages of [Vortioxetine] Lu AA21004, in Acute Treatment of Major Depressive Disorder'

description: The purpose of the study is to evaluate the efficacy and the tolerability of three fixed doses of Vortioxetine in order to establish the appropriate clinical effective dose range in the treatment of Major Depressive Disorder (MDD).
DOI: 10.6084/m9.figshare.17696531.v2
title: Population genomics, gut microbiota, and transcriptional response to heat shock in Hong Kong oyster Magallana hongkongensis

description: The Hong Kong oyster Magallana hongkongensis, previously known as Crassostrea hongkongensis, is a true oyster species that native to the estuary-coast of Pearl River Delta in southern China. The species has long been farmed for hundreds of years, and with scientific, ecological, cultural and nutritional importance. However, there is only limited information on the genetic background and stress adaptation mechanism of M. hongkongensis, restricting the sustainable production and utilisation of the local oyster resources. Here, we presented the population structure analysis on oysters collected from Deep Bay (Shenzhen Bay) and Lantau Island in Hong Kong, the transcriptome analysis on heat shock responses and the gut microbiota profile of M. hongkongensis. A conserved genetic background of local oysters was uncovered by the whole genome resequencing on 49 individuals, and the results indicated a close relationship and adaptation process in local oyster populations. Genetic variants in homeobox and heat shock protein genes were identified and predicted with regulatory function. Oysters had also been incubated under temperate (25 °C) and heat shock (32 °C) conditions for 24 hours to investigate the stress responses. Transcriptome profiles revealed the heat-induced regulation on heat shock protein, protein binding genes and signal transduction genes. We also found the differential expression of two splicing factors might be regulated by alternative splicing, and their expression levels were higher under heat stress. In addition, the gut microbe community were detected by 16S rRNA sequencing, and Cyanobacteria, Proteobacteria and Spirochaetes were the top phyla found in local oysters. Our results provided the knowledge on transcriptomic responses to heat shock in local oyster and implied the molecular basis for the divergent adaptation to the changeable aquatic environment. We also suggested that gut microbiota might participate in the regulation of stress response in M. hongkongensis. These findings give new insights on different mechanisms of local adaptation in Hong Kong oysters and other molluscs.
DOI: 10.5517/ccdc.csd.cc269pcl
title: CCDC 2035099: Experimental Crystal Structure Determination

description: Related Article: Sushila, Swati Dhamija, Moumita Patra, Jacques Pécaut, Ramesh Kataria, Soumyabrata Goswami, Susovan Bhowmik, Ranjan Patra|2022|Inorg.Chim.Acta|535|120852|doi:10.1016/j.ica.2022.120852
DOI: 10.5517/ccdc.csd.cc269pdm
title: CCDC 2035100: Experimental Crystal Structure Determination

description: Related Article: Sushila, Swati Dhamija, Moumita Patra, Jacques Pécaut, Ramesh Kataria, Soumyabrata Goswami, Susovan Bhowmik, Ranjan Patra|2022|Inorg.Chim.Acta|535|120852|doi:10.1016/j.ica.2022.120852
DOI: 10.5517/ccdc.csd.cc269pfn
title: CCDC 2035101: Experimental Crystal Structure Determination

description: Related Article: Sushila, Swati Dhamija, Moumita Patra, Jacques Pécaut, Ramesh Kataria, Soumyabrata Goswami, Susovan Bhowmik, Ranjan Patra|2022|Inorg.Chim.Acta|535|120852|doi:10.1016/j.ica.2022.120852
DOI: 10.5517/ccdc.csd.cc26jzvl
title: CCDC 2042120: Experimental Crystal Structure Determination

description: Related Article: Jianglin Wu, Yao Chen, Jueshan Liu, Zhenguo Pang, Guoping Li, Zhiyun Lu, Yan Huang, Antonio Facchetti, Tobin J. Marks|2022|J.Mater.Chem.C|10|2724|doi:10.1039/D1TC03156B
DOI: 10.5517/ccdc.csd.cc26jzxn
title: CCDC 2042122: Experimental Crystal Structure Determination

description: Related Article: Jianglin Wu, Yao Chen, Jueshan Liu, Zhenguo Pang, Guoping Li, Zhiyun Lu, Yan Huang, Antonio Facchetti, Tobin J. Marks|2022|J.Mater.Chem.C|10|2724|doi:10.1039/D1TC03156B
DOI: 10.5517/ccdc.csd.cc28hjz9
title: CCDC 2100311: Experimental Crystal Structure Determination

description: Related Article: Xue-Qing Mou, Liang-Chen Ren, Mei Zhang, Min Wang, Yu-Fan Jin, Qing-Xin Guan, Ang Cai, Shi-Min Zhang, Hai Ren, Yun Zhang, Yong-Zheng Chen|2022|Org.Lett.|24|1405|doi:10.1021/acs.orglett.2c00287
DOI: 10.5517/ccdc.csd.cc28hk0c
title: CCDC 2100312: Experimental Crystal Structure Determination

description: Related Article: Xue-Qing Mou, Liang-Chen Ren, Mei Zhang, Min Wang, Yu-Fan Jin, Qing-Xin Guan, Ang Cai, Shi-Min Zhang, Hai Ren, Yun Zhang, Yong-Zheng Chen|2022|Org.Lett.|24|1405|doi:10.1021/acs.orglett.2c00287
DOI: 10.5517/ccdc.csd.cc28hk1d
title: CCDC 2100313: Experimental Crystal Structure Determination

description: Related Article: Xue-Qing Mou, Liang-Chen Ren, Mei Zhang, Min Wang, Yu-Fan Jin, Qing-Xin Guan, Ang Cai, Shi-Min Zhang, Hai Ren, Yun Zhang, Yong-Zheng Chen|2022|Org.Lett.|24|1405|doi:10.1021/acs.orglett.2c00287
DOI: 10.5517/ccdc.csd.cc2938l9
title: CCDC 2118310: Experimental Crystal Structure Determination

description: Related Article: Kexiang Zhao, Ze-Fan Yao, Zi-Yuan Wang, Jing-Cai Zeng, Li Ding, Miao Xiong, Jie-Yu Wang, Jian Pei|2022|J.Am.Chem.Soc.|144|3091|doi:10.1021/jacs.1c11782
DOI: 10.5517/ccdc.csd.cc2938mb
title: CCDC 2118311: Experimental Crystal Structure Determination

description: Related Article: Kexiang Zhao, Ze-Fan Yao, Zi-Yuan Wang, Jing-Cai Zeng, Li Ding, Miao Xiong, Jie-Yu Wang, Jian Pei|2022|J.Am.Chem.Soc.|144|3091|doi:10.1021/jacs.1c11782
DOI: 10.5517/ccdc.csd.cc2938nc
title: CCDC 2118312: Experimental Crystal Structure Determination

description: Related Article: Kexiang Zhao, Ze-Fan Yao, Zi-Yuan Wang, Jing-Cai Zeng, Li Ding, Miao Xiong, Jie-Yu Wang, Jian Pei|2022|J.Am.Chem.Soc.|144|3091|doi:10.1021/jacs.1c11782
DOI: 10.5517/ccdc.csd.cc294bmf
title: CCDC 2119334: Experimental Crystal Structure Determination

description: Related Article: Xiancui Zhu, Yawen Qi, Yuanqing Yang, Dianjun Guo, Zeming Huang, Lijun Zhang, Yun Wei, Shuangliu Zhou, Shaowu Wang|2022|Inorg.Chem.|61|3202|doi:10.1021/acs.inorgchem.1c03673
DOI: 10.5517/ccdc.csd.cc294bng
title: CCDC 2119335: Experimental Crystal Structure Determination

description: Related Article: Xiancui Zhu, Yawen Qi, Yuanqing Yang, Dianjun Guo, Zeming Huang, Lijun Zhang, Yun Wei, Shuangliu Zhou, Shaowu Wang|2022|Inorg.Chem.|61|3202|doi:10.1021/acs.inorgchem.1c03673
DOI: 10.5281/zenodo.6276369
title: data set related to article An Exploratory Study of Emotional Dysregulation Dimensions in Youth With Attention Deficit Hyperactivity Disorder and/or Bipolar Spectrum Disorders

description: This record contains raw data related to article An Exploratory Study of Emotional Dysregulation Dimensions in Youth With Attention Deficit Hyperactivity Disorder and/or Bipolar Spectrum Disorders
DOI: 10.5285/1115d8946ba74c7f8a9fc3bfee5513a0
title: ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from AATSR (Advanced Along-Track Scanning Radiometer), level 3 collated (L3C) global product (2002-2012), version 3.00

description: This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Advanced Along-Track Scanning Radiometer (AATSR) on Environmental Satellite (Envisat). Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. Daytime and night-time temperatures are provided in separate files corresponding to the morning and evening Envisat equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class. The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. AATSR achieves full Earth coverage in 3 days so the daily files have gaps where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. Dataset coverage starts on 25th July 2002 and ends on 8th April 2012. There is a twelve day gap in the dataset due to Envisat mission extension orbital manoeuvres from 21st October 2010 to 1st November 2010. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods. The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.
DOI: 10.5285/f1445bde2f1249c99bb5a59b71e9a9d7
title: ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from ATSR-2 (Along-Track Scanning Radiometer 2), level 3 collated (L3C) global product (1995-2013), version 3.00

description: This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Along-Track Scanning Radiometer (ATSR-2) on European Remote-sensing Satellite 2 (ERS-2). Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. Daytime and nighttime temperatures are provided in separate files corresponding to the morning and evening ERS-2 equator crossing times which are 10:30 and 22:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class. The dataset coverage is near global over the land surface. Small regions were not covered due to downlinking constraints (most noticeably a track extending southwards across central Asia through India – further details can be found on the ATSR project webpages at http://www.atsr.rl.ac.uk/dataproducts/availability/coverage/atsr-2/index.shtml. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. ATSR-2 achieves full Earth coverage in 3 days so the daily files have gaps where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. Dataset coverage starts on 1st August 1995 and ends on 22nd June 2003. There are two gaps of several months in the dataset: no data were acquired from ATSR-2 between 23 December 1995 and 30 June 1996 due to a scan mirror anomaly; and the ERS-2 gyro failed in January 2001, data quality was less good between 17th Jan 2001 and 5th July 2001 and are not used in this dataset. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods. The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.
DOI: 10.5285/330b7c922a37420fabb3425671d7d7c6
title: ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land surface temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3A, level 3 collated (L3C) global product (2016-2020), version 3.00

description: This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3A. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. Daytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel-3A equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class. The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRA achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. Dataset coverage starts on 1st May 2016 and ends on 31st December 2020. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies. The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.
DOI: 10.5285/5f66a881adf846bfaad58b0e6068f0ea
title: ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land Surface Temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3B, level 3 collated (L3C) global product (2018-2020), version 3.00

description: This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3B. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. Daytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel 3B equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class. The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRB achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. Dataset coverage starts on 17th November 2018 and ends on 31st December 2020. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies. The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.
DOI: 10.5285/58a01734f841466daa1837353aee5ff8
title: ESA Land Surface Temperature Climate Change Initiative (LST_cci): Land Surface Temperature from MODIS (Moderate resolution Infra-red Spectroradiometer) on Terra, level 3 collated (L3C) global product (2000-2018), version 3.00

description: This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Earth Observing System – Terra (Terra). Satellite land surface temperatures are skin temperatures which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water. Daytime and night-time temperatures are provided in separate files corresponding to the morning and evening Terra equator crossing times which are 10:30 and 22:30 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class. The dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. MODIS achieves full Earth coverage nearly twice per day so the daily files have small gaps primarily close to the equator where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface. Dataset coverage starts on 24th February 2000 and ends on 31st December 2018. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods. The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using a generalised split window retrieval algorithm and data were processed in the UoL processing chain. The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.