cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.00915
title: Cryogenic perchlorate and chloride datasets
title: Cryogenic perchlorate and chloride datasets

description: The datasets include three zip packages of source data for the article "Cryogenic Origin of Fractionation between Perchlorate and Chloride under Modern Martian Climate" in Communications Earth & Environment. The three zip packages are "Source Data for Figures 1 to 4"（used for plotting Figures 1-4 in the main text）, "Source Data for Supplementary Figures" (used for plotting Supplementary Figures) and "Supplementary Tables" (digital tables of all the Supplementary Table ), respectively.
description: The datasets include three zip packages of source data for the article "Cryogenic Origin of Fractionation between Perchlorate and Chloride under Modern Martian Climate" in Communications Earth & Environment. The three zip packages are "Source Data for Figures 1 to 4"（used for plotting Figures 1-4 in the main text）, "Source Data for Supplementary Figures" (used for plotting Supplementary Figures) and "Supplementary Tables" (digital tables of all the Supplementary Table ), respectively.
DOI: 10.57760/sciencedb.01090
title: Crystal structure dataset of chemical constituents of Traditional Chinese medicines
title: 中药材化学成分的晶体结构数据集

description: The crystal structure dataset of the chemical constituents of Traditional Chinese medicine was collected and recorded from the journal literatures, the crystal structure and chemical constituents were integrated through compounds. In this dataset, 527 kinds of Traditional Chinese medicines, 270 kinds of compounds and 345 crystal structure CIF data were collected, and the corresponding relationships among the three data were established. The crystal structure dataset of chemical components of Traditional Chinese medicines can provide useful help for pharmaceutical chemists and pharmacists in pharmaceutical research.
description: The crystal structure dataset of the chemical constituents of Traditional Chinese medicine was collected and recorded from the journal literatures, the crystal structure and chemical constituents were integrated through compounds. In this dataset, 527 kinds of Traditional Chinese medicines, 270 kinds of compounds and 345 crystal structure CIF data were collected, and the corresponding relationships among the three data were established. The crystal structure dataset of chemical components of Traditional Chinese medicines can provide useful help for pharmaceutical chemists and pharmacists in pharmaceutical research.
DOI: 10.57760/sciencedb.01123
title: Data set of snow cover days in Mongolia from 1981 to 2020
title: 1981-2020年蒙古国积雪日数数据集

description: This data set is the annual grid data set of snow days in Mongolia from 1981 to 2020. The data format is TIF with a resolution of 0.1 ° × 0.1°。 According to the definition of Tejada and Gonzalez scholars, the snow day is the snow day when the snow depth reaches 0.5 cm. Snow days refer to the number of snow days in a year ( Tejada and Gonzalez，2006)。 This data set is processed by the reanalysis data era5 of the European Center for medium range weather forecasting. The long-time series snow days data can provide a reference for revealing the changes of snow cover in Mongolia.
description: This data set is the annual grid data set of snow days in Mongolia from 1981 to 2020. The data format is TIF with a resolution of 0.1 ° × 0.1°。 According to the definition of Tejada and Gonzalez scholars, the snow day is the snow day when the snow depth reaches 0.5 cm. Snow days refer to the number of snow days in a year ( Tejada and Gonzalez，2006)。 This data set is processed by the reanalysis data era5 of the European Center for medium range weather forecasting. The long-time series snow days data can provide a reference for revealing the changes of snow cover in Mongolia.
DOI: 10.57760/sciencedb.01136
title: Oceanographic data collected within the eastern equatorial Indian Ocean by JAMES during December 2019‒February 2020
title: Oceanographic data collected within the eastern equatorial Indian Ocean by JAMES during December 2019‒February 2020

description: The dataset includes four types of hydrographic data: glider, shipboard CTD, VADCP, and subsurface mooring. The data were obtained from an international corporation cruise, named as JAMES in the eastern equatorial Indian Ocean during December 2019‒February 2020. Hydrographic data from subsurface mooring are obtained by the measurements of mooring-mounted ADCP, CTD, and RBR. The dataset could be used to analyze the characteristics, evolutionary process, and possible origination of a subsurface anticyclonic eddy in the eastern equatorial Indian Ocean.
description: The dataset includes four types of hydrographic data: glider, shipboard CTD, VADCP, and subsurface mooring. The data were obtained from an international corporation cruise, named as JAMES in the eastern equatorial Indian Ocean during December 2019‒February 2020. Hydrographic data from subsurface mooring are obtained by the measurements of mooring-mounted ADCP, CTD, and RBR. The dataset could be used to analyze the characteristics, evolutionary process, and possible origination of a subsurface anticyclonic eddy in the eastern equatorial Indian Ocean.
DOI: 10.57760/sciencedb.01159
title: Raw Metagenomic Sequencing Data of Extracellular Vesicles (EVs) isolated from dust
title: Raw Metagenomic Sequencing Data of Extracellular Vesicles (EVs) isolated from dust

description: This dataset is the raw data of metagenomic sequencing, including dust as well as EVs isolated from dust. Metagenomic shotgun sequencing libraries were sequenced using HiSeq 2000 platform.
description: This dataset is the raw data of metagenomic sequencing, including dust as well as EVs isolated from dust. Metagenomic shotgun sequencing libraries were sequenced using HiSeq 2000 platform.
DOI: 10.57760/sciencedb.01173
title: Whole genome mutation rate profiles for multiple species
title: Whole genome mutation rate profiles for multiple species

description: We developed a deep learning framework 'MuRaL' to learn and predict single-nucleotide mutation rates using genomic sequnence as input. This Dataset provides the whole genome mutation rate profiles for multiple species described in the paper.
description: We developed a deep learning framework 'MuRaL' to learn and predict single-nucleotide mutation rates using genomic sequnence as input. This Dataset provides the whole genome mutation rate profiles for multiple species described in the paper.
DOI: 10.57760/sciencedb.01174
title: A SPEI dataset in China-Pakistan Economic Corridor from 1961 to 2015
title: 1961–2015年中巴经济走廊SPEI干旱指数数据集

description: Drought index data set is the basis of drought research. Drought disasters occur frequently in the China Pakistan Economic Corridor. Making the drought index data set is of great scientific significance for drought monitoring and risk assessment. Based on daily precipitation and temperature gridded data of the China-Pakistan Economic Corridor from 1961 to 2015 and calculated standardized precipitation evapotranspiration index (SPEI) for different time scales (1- 24 months). The verification shows that this dataset has high accuracy and can better reflect the real temporal and spatial distribution characteristics of drought in China-Pakistan Economic Corridor area. The dataset can provide substantial support for climate change research and assessment of drought disaster risk over the China-Pakistan Economic Corridor.
description: Drought index data set is the basis of drought research. Drought disasters occur frequently in the China Pakistan Economic Corridor. Making the drought index data set is of great scientific significance for drought monitoring and risk assessment. Based on daily precipitation and temperature gridded data of the China-Pakistan Economic Corridor from 1961 to 2015 and calculated standardized precipitation evapotranspiration index (SPEI) for different time scales (1- 24 months). The verification shows that this dataset has high accuracy and can better reflect the real temporal and spatial distribution characteristics of drought in China-Pakistan Economic Corridor area. The dataset can provide substantial support for climate change research and assessment of drought disaster risk over the China-Pakistan Economic Corridor.
DOI: 10.57760/sciencedb.00834
title: Spaceborne SAR ocean wave and ocean wind data in the Arctic
title: Spaceborne SAR ocean wave and ocean wind data in the Arctic

description: Based on the BP neural network, one kind of method of machine learning, we developed a novel method to retrieve sea significant wave height (SWH) and sea surface wind field (SSW) information from spaceborne SAR data in high spatial resolution. Then we produced the relevant data products based on the ESA Sentinel-1 (S1) SAR data in horizontal-horizontal (HH) polarization acquired in the Arctic using the proposed method.The extra-wide (EW) swath mode data have been extensively acquired in the Arctic since the Sentinel-1A and 1B satellites launched in 2014 and 2016, which have a wide coverage of approximately 400 by 400 km and a pixel size of 40 by 40 m. The twins can acquired approximately 2,500 scenes SAR images each month in the Arctic. Based on the above-mentioned method, we processed each S1 SAR image in the Arctic and generated the SWH data and SSW data, which are in the standard CF-1.7 convention of NetCDF-4 format. Each S1 image corresponds to a NC file. The spatial resolution of S1-retrieved SWH and SSW are 2.56 km and 2 km, respectively.We have finished processing the S1 data acquired between 2017 and 2021 in the pan Arctic ocean (above 60 degrees North) and uploaded the corresponding SWH and SSW data. We are continuing to process the ongoing acquired data. Therefore, the published data will be updated often.
description: Based on the BP neural network, one kind of method of machine learning, we developed a novel method to retrieve sea significant wave height (SWH) and sea surface wind field (SSW) information from spaceborne SAR data in high spatial resolution. Then we produced the relevant data products based on the ESA Sentinel-1 (S1) SAR data in horizontal-horizontal (HH) polarization acquired in the Arctic using the proposed method.The extra-wide (EW) swath mode data have been extensively acquired in the Arctic since the Sentinel-1A and 1B satellites launched in 2014 and 2016, which have a wide coverage of approximately 400 by 400 km and a pixel size of 40 by 40 m. The twins can acquired approximately 2,500 scenes SAR images each month in the Arctic. Based on the above-mentioned method, we processed each S1 SAR image in the Arctic and generated the SWH data and SSW data, which are in the standard CF-1.7 convention of NetCDF-4 format. Each S1 image corresponds to a NC file. The spatial resolution of S1-retrieved SWH and SSW are 2.56 km and 2 km, respectively.We have finished processing the S1 data acquired between 2017 and 2021 in the pan Arctic ocean (above 60 degrees North) and uploaded the corresponding SWH and SSW data. We are continuing to process the ongoing acquired data. Therefore, the published data will be updated often.
DOI: 10.57760/sciencedb.00880
title: China Water Cover Map (2020/10 m)
title: China Water Cover Map (2020/10 m)

description: The China Water Cover Map (2020/10 m) was developed by the wetland remote sensing research team of Aerospace Information Research Institute, Chinese Academy of Sciences. The map was developed based on an automatic shape-based and inundation frequency-based classification method using time series Sentinel-1 and Sentinel-2 images covering the whole China in the year 2020 with the aid of the remote sensing big data cloud platform. The overall accuracy of CWaC is 85.6% and the kappa coefficient is 0.83. The classification accuracy of rivers, reservoirs, lakes, agricultural ponds, and rice fields all exceed 80%, and the classification accuracy of seasonal wetlands exceeds 70%. At the same time, seven prominent water-related data products are chosen to compare with CWaC. The results show that CWaC has a high degree of consistency with existing data, and its unprecedented spatial resolution shows unique advantages. The CWaC is the first effort on water cover type mapping for the whole China at 10-m spatial resolution, which can provide important information for managing water resources and studying the relationship between the transformation of water cover types and human activities.
description: The China Water Cover Map (2020/10 m) was developed by the wetland remote sensing research team of Aerospace Information Research Institute, Chinese Academy of Sciences. The map was developed based on an automatic shape-based and inundation frequency-based classification method using time series Sentinel-1 and Sentinel-2 images covering the whole China in the year 2020 with the aid of the remote sensing big data cloud platform. The overall accuracy of CWaC is 85.6% and the kappa coefficient is 0.83. The classification accuracy of rivers, reservoirs, lakes, agricultural ponds, and rice fields all exceed 80%, and the classification accuracy of seasonal wetlands exceeds 70%. At the same time, seven prominent water-related data products are chosen to compare with CWaC. The results show that CWaC has a high degree of consistency with existing data, and its unprecedented spatial resolution shows unique advantages. The CWaC is the first effort on water cover type mapping for the whole China at 10-m spatial resolution, which can provide important information for managing water resources and studying the relationship between the transformation of water cover types and human activities.
DOI: 10.57760/sciencedb.01064
title: DOM molecular signatures of 22 Chinese reference soils
title: DOM molecular signatures of 22 Chinese reference soils

description: 22 Chinese national standard soils (GBW 07401-GBW07385) were purchased from https://www.gbw-china.com, and the molecular signatures of soil-derived dissolved organic matter were revealed by Fourier transform ion cyclotron resonance mass spectrometry.
description: 22 Chinese national standard soils (GBW 07401-GBW07385) were purchased from https://www.gbw-china.com, and the molecular signatures of soil-derived dissolved organic matter were revealed by Fourier transform ion cyclotron resonance mass spectrometry.
DOI: 10.57760/sciencedb.01112
title: Data for the article "IL-7 and CCL19-secreting CAR-T cell therapy for tumors with positive glypican-3 or mesothelin"
title: Data for the article "IL-7 and CCL19-secreting CAR-T cell therapy for tumors with positive glypican-3 or mesothelin"

description: The data is the figure and table in the article "IL-7 and CCL19-secreting CAR-T cell therapy for tumors with positive glypican-3 or mesothelin". The data contains in vitro and in vivo experiment of CAR-T function and CT scan picture of CAR-T treatment in patients.
description: The data is the figure and table in the article "IL-7 and CCL19-secreting CAR-T cell therapy for tumors with positive glypican-3 or mesothelin". The data contains in vitro and in vivo experiment of CAR-T function and CT scan picture of CAR-T treatment in patients.
DOI: 10.57760/sciencedb.01180
title: A dataset of the funding inputs and research paper outputs of highly funded scientists in China from 1986-2019
title: A dataset of the funding inputs and research paper outputs of highly funded scientists in China from 1986-2019

description: The dataset includes a series of data regarding highly funded scientists in China; including the funding inputs and research paper outputs of scientists from 1986 to 2019; and the basic information of those scientists. There are 82,383 records about papers, 2,642 records about projects, and 345 records about basic information of highly funded scientists. All data is freely available as four tables in CSV form. The dataset should be useful for understanding the evolution of highly funded scientists in China.
description: The dataset includes a series of data regarding highly funded scientists in China; including the funding inputs and research paper outputs of scientists from 1986 to 2019; and the basic information of those scientists. There are 82,383 records about papers, 2,642 records about projects, and 345 records about basic information of highly funded scientists. All data is freely available as four tables in CSV form. The dataset should be useful for understanding the evolution of highly funded scientists in China.
DOI: 10.57760/sciencedb.00830
title: Network pharmacology of Tetrandra and Poria Decoction in the treatment of lymphedema
title: 防己茯苓汤治疗淋巴水肿的网络药理学研究

description: The data set contains the basic data of network pharmacology research of Tetrandra and Poria Decoction(TPD) in the treatment of lymphedema, with a total of three tables. Table S1. All the potential targets of TPD; Table S2. Lymphedema-related targets searched by Genecards; Table S3. TPD shared 38 potential targets with lymphedema-related targets.
description: The data set contains the basic data of network pharmacology research of Tetrandra and Poria Decoction(TPD) in the treatment of lymphedema, with a total of three tables. Table S1. All the potential targets of TPD; Table S2. Lymphedema-related targets searched by Genecards; Table S3. TPD shared 38 potential targets with lymphedema-related targets.
DOI: 10.57760/sciencedb.00917
title: Visual Working Memory Impairs Visual Detection: A Function of Working Memory Load or Sensory Load?
title: Visual Working Memory Impairs Visual Detection: A Function of Working Memory Load or Sensory Load?

description: We performed four experiments to examine how different types of Load influence visual detection. Experiment 1 manipulated the retention time of the memory array while keeping the VWM load constant, revealing reduced visual detection along with retention time. Experiments 2 and 3 manipulated the VWM load while maintaining a constant sensory load, and visual detection was not affected. Experiment 4 affirmed that the findings in Experiments 1–3 were reliable.
description: We performed four experiments to examine how different types of Load influence visual detection. Experiment 1 manipulated the retention time of the memory array while keeping the VWM load constant, revealing reduced visual detection along with retention time. Experiments 2 and 3 manipulated the VWM load while maintaining a constant sensory load, and visual detection was not affected. Experiment 4 affirmed that the findings in Experiments 1–3 were reliable.
DOI: 10.34820/fk2/dkpgwf/7dmm8f
title: data hotel homann.pdf

description: :unav
DOI: 10.34820/fk2/dkpgwf
title: data dokumentasi adaptasi elemen interior Hotel Savoy Homann

description: data survey untuk penelitian adaptasi elemen interior terhadap signifikasi gaya art deco
DOI: 10.57760/sciencedb.01103
title: Actinolite temperature calculations
title: Actinolite temperature calculations

description: Actinolite temperatures calculated from WDS Mg and Fe maps using Lledo and Jenkins (2008) polynomial regression
description: Actinolite temperatures calculated from WDS Mg and Fe maps using Lledo and Jenkins (2008) polynomial regression
DOI: 10.57760/sciencedb.01134
title: A hierarchical cellular structural model to unravel the universal power-law rheological behavior of living cells
title: A hierarchical cellular structural model to unravel the universal power-law rheological behavior of living cells

description: Living cells are a complex soft material with fascinating mechanical properties. A striking feature is that, regardless of their types or states, cells exhibit a universal power-law rheological behavior which to this date still has not been captured by a single theoretical model. Here, we propose a cellular structural model that accounts for the essential mechanical responses of cell membrane, cytoplasm and cytoskeleton. We demonstrate that this model can naturally reproduce the universal power-law characteristics of cell rheology, as well as how its power-law exponent is related to cellular stiffness. More importantly, the power-law exponent can be quantitatively tuned in the range of 0.1 ~ 0.5, as found in most types of cells, by varying the stiffness or architecture of the cytoskeleton. Based on the structural characteristics, we further develop a self-similar hierarchical model that can spontaneously capture the power-law characteristics of creep compliance over time and complex modulus over frequency. The present model suggests that mechanical responses of cells may depend primarily on their generic architectural mechanism, rather than specific molecular properties.
description: Living cells are a complex soft material with fascinating mechanical properties. A striking feature is that, regardless of their types or states, cells exhibit a universal power-law rheological behavior which to this date still has not been captured by a single theoretical model. Here, we propose a cellular structural model that accounts for the essential mechanical responses of cell membrane, cytoplasm and cytoskeleton. We demonstrate that this model can naturally reproduce the universal power-law characteristics of cell rheology, as well as how its power-law exponent is related to cellular stiffness. More importantly, the power-law exponent can be quantitatively tuned in the range of 0.1 ~ 0.5, as found in most types of cells, by varying the stiffness or architecture of the cytoskeleton. Based on the structural characteristics, we further develop a self-similar hierarchical model that can spontaneously capture the power-law characteristics of creep compliance over time and complex modulus over frequency. The present model suggests that mechanical responses of cells may depend primarily on their generic architectural mechanism, rather than specific molecular properties.
DOI: 10.57760/sciencedb.01121
title: UAV data monitoring plastic waste dataset
title: UAV data monitoring plastic waste dataset

description: Plastic waste is one of the main factors causing marine environmental pollution and affecting biodiversity, and identification and detection of plastic waste is the premise of removal and treatment. Unmanned aerial vehicle (UAV) is gradually applied to the identification and classification of plastic waste because of its advantages of simplicity, convenience and safe operation, but the current visual interpretation method is inefficient and cumbersome. To support the detection of plastic waste, researchers have developed various automatic and semi-automatic algorithms.Dataset is an automatic detection service.
description: Plastic waste is one of the main factors causing marine environmental pollution and affecting biodiversity, and identification and detection of plastic waste is the premise of removal and treatment. Unmanned aerial vehicle (UAV) is gradually applied to the identification and classification of plastic waste because of its advantages of simplicity, convenience and safe operation, but the current visual interpretation method is inefficient and cumbersome. To support the detection of plastic waste, researchers have developed various automatic and semi-automatic algorithms.Dataset is an automatic detection service.