cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.10130
title: Brazilian Atmospheric Inventories - BRAIN version 2: meteorology dataset in Southern Brazil
title: Brazilian Atmospheric Inventories - BRAIN version 2: meteorology dataset in Southern Brazil

description: We provide hourly meteorology data derived from Weather and Research Forecasting model from 2020 in Southern Brazil. WRF has been set up to reproduce 36 hours simulations, where the initial 12 hours have been dedicated to model stabilization, which are excluded from the analysis. Thirty-three vertical levels have been employed, spaced at 50 hPa intervals. The parameterizations used in this work are described in SM3. The remaining vertical levels followed a hybrid modeling scheme, accounting for terrain in the lower layers and gradually minimizing its influence in the higher levels. SM4 details all variables in WRF outputs.Global Forecast System (GFS) from the National Center for Atmospheric Research (NCAR) provided inputs with spatial resolution of 0.25° x 0.25° and a temporal resolution of six hours for the WRF simulations (Skamarock et al., 2008). Land use data and classification parameters from the United States Geological Survey's (USGS) Moderate Resolution Imaging Spectroradiometer (MODIS).Details of the modeling domains can be found in SM1. In the present dataset, we provide data from d02, Files are in netCDF format with 4x4km of spatial resolution and hourly temporal resolution, covering the Southern Brazilian territory. Data are divided by day.
description: We provide hourly meteorology data derived from Weather and Research Forecasting model from 2020 in Southern Brazil. WRF has been set up to reproduce 36 hours simulations, where the initial 12 hours have been dedicated to model stabilization, which are excluded from the analysis. Thirty-three vertical levels have been employed, spaced at 50 hPa intervals. The parameterizations used in this work are described in SM3. The remaining vertical levels followed a hybrid modeling scheme, accounting for terrain in the lower layers and gradually minimizing its influence in the higher levels. SM4 details all variables in WRF outputs.Global Forecast System (GFS) from the National Center for Atmospheric Research (NCAR) provided inputs with spatial resolution of 0.25° x 0.25° and a temporal resolution of six hours for the WRF simulations (Skamarock et al., 2008). Land use data and classification parameters from the United States Geological Survey's (USGS) Moderate Resolution Imaging Spectroradiometer (MODIS).Details of the modeling domains can be found in SM1. In the present dataset, we provide data from d02, Files are in netCDF format with 4x4km of spatial resolution and hourly temporal resolution, covering the Southern Brazilian territory. Data are divided by day.
DOI: 10.57760/sciencedb.11463
title: Wild ungulates and cattle have different effects on litter decomposition as revealed by fecal addition in a Northeast Asian temperate forest
title: Wild ungulates and cattle have different effects on litter decomposition as revealed by fecal addition in a Northeast Asian temperate forest

description: We conducted litter decomposition experiments on 30 long-term large herbivore exclusion plots from July 2022 to October 2023 in Northeast Tiger and Leopard National Park(NTLNP), which is situated in the northern section of Jilin Province in China and borders North Korea to the southwest and the southwest-most region of Primorsky Krai in Russia. The rate of decomposition of leaf litter was measured using the litterbag method. We placed 12 litterbags within each enclosure on July 15–17, 2022: 4 bags of leaf litter (10 g of leaves per litterbag), 4 bags of sika deer feces and litter mixture (5 g of deer feces + 5 g of leaves), and 4 bags of cattle feces and litter mixture (5 g of cattle feces + 5 g of leaves).All analyses were performed in R 4.3.2 (R Development Core Team)
description: We conducted litter decomposition experiments on 30 long-term large herbivore exclusion plots from July 2022 to October 2023 in Northeast Tiger and Leopard National Park(NTLNP), which is situated in the northern section of Jilin Province in China and borders North Korea to the southwest and the southwest-most region of Primorsky Krai in Russia. The rate of decomposition of leaf litter was measured using the litterbag method. We placed 12 litterbags within each enclosure on July 15–17, 2022: 4 bags of leaf litter (10 g of leaves per litterbag), 4 bags of sika deer feces and litter mixture (5 g of deer feces + 5 g of leaves), and 4 bags of cattle feces and litter mixture (5 g of cattle feces + 5 g of leaves).All analyses were performed in R 4.3.2 (R Development Core Team)
DOI: 10.15468/dl.zhgdxc
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Plebeia kerri Moure, 1950"
 ]
}

 The dataset includes 37 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001344-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.j00133.00336
title: Experimental Data for Rumor Detection Model Based on Dynamic Propagation and Neural Hawkes Process
title: Experimental Data for Rumor Detection Model Based on Dynamic Propagation and Neural Hawkes Process

description: This data list includes two real-world social media rumor datasets: Twitter15 and Twitter16. The Twitter15 and Twitter16 datasets contain 1,490 and 818 tweet events respectively. Each tweet event consists of a tweet propagation graph, where the nodes represent tweet posts and the edges represent reply or retweet relationships between tweet posts. Each source tweet is labeled with the corresponding category of the tweet event. Both datasets include four labels: True Rumor (TR), False Rumor (FR), Unverified Rumor (UR), and Non-Rumor (NR). In addition, the core code of the DPNHRD model is provided in this data list.
description: This data list includes two real-world social media rumor datasets: Twitter15 and Twitter16. The Twitter15 and Twitter16 datasets contain 1,490 and 818 tweet events respectively. Each tweet event consists of a tweet propagation graph, where the nodes represent tweet posts and the edges represent reply or retweet relationships between tweet posts. Each source tweet is labeled with the corresponding category of the tweet event. Both datasets include four labels: True Rumor (TR), False Rumor (FR), Unverified Rumor (UR), and Non-Rumor (NR). In addition, the core code of the DPNHRD model is provided in this data list.
DOI: 10.57760/sciencedb.08636
title: The HiC reads of whole genome sequencing in Lycosidae Pardosa_laura
title: The HiC reads of whole genome sequencing in Lycosidae Pardosa_laura

description: The HiC reads of whole genome sequencing in Lycosidae Pardosa_laura,the Illumina HiSeq 2000 platform was performed with paired-end sequencing.
description: The HiC reads of whole genome sequencing in Lycosidae Pardosa_laura,the Illumina HiSeq 2000 platform was performed with paired-end sequencing.
DOI: 10.57760/sciencedb.15628
title: Dataset for Raman spectra of airborne pathogens
title: Dataset for Raman spectra of airborne pathogens

description: This dataset contains Raman spectra of different airborne pathogens, which can be used for rapid identification of real-world airborne pathogens.
description: This dataset contains Raman spectra of different airborne pathogens, which can be used for rapid identification of real-world airborne pathogens.
DOI: 10.15468/dl.meukfq
title: Occurrence Download

description: A dataset containing 10777 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Aneides lugubris (Hallowell, 1849))"
 ]
}

 The dataset includes 10777 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001345-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.08588
title: Satellite-Based Monitoring of Methane Emissions from China's Rice Hub
title: Satellite-Based Monitoring of Methane Emissions from China's Rice Hub

description: IntroductionWe perform a high-resolution inversion of atmospheric methane observations from the TROPOMI satellite observations to infer monthly rice methane emissions for 2021 from Northeast China.Data filesMonthly optimized methane emissions: NortheastChina_CH4Flux_{inversion case}_2021{month}.nc- 9 members of the date sets: SRON-E1(base), SRON-E1-SA-down, SRON-E1-SA-up, SRON-E1-SA-nondiag, SRON-E1-wet, SRON-E2, SRON-E3, WFMD-E1, WFMD-E2Data infomation- Variables: CH4_Flux_{emi_sector} (unit: kg/m2/s) and area (unit: m2). Emission sectors include coal, oil, gas, wastewater, livestock, landfills, rice, wetlands, seeps, termites, biosmass burning, and other anthropogenic- Spatial resolution: 0.5° x 0.625°- Period: the year 2021- Domain: Northeast China (39°N – 54°N, 119°E – 137°E)
description: IntroductionWe perform a high-resolution inversion of atmospheric methane observations from the TROPOMI satellite observations to infer monthly rice methane emissions for 2021 from Northeast China.Data filesMonthly optimized methane emissions: NortheastChina_CH4Flux_{inversion case}_2021{month}.nc- 9 members of the date sets: SRON-E1(base), SRON-E1-SA-down, SRON-E1-SA-up, SRON-E1-SA-nondiag, SRON-E1-wet, SRON-E2, SRON-E3, WFMD-E1, WFMD-E2Data infomation- Variables: CH4_Flux_{emi_sector} (unit: kg/m2/s) and area (unit: m2). Emission sectors include coal, oil, gas, wastewater, livestock, landfills, rice, wetlands, seeps, termites, biosmass burning, and other anthropogenic- Spatial resolution: 0.5° x 0.625°- Period: the year 2021- Domain: Northeast China (39°N – 54°N, 119°E – 137°E)
DOI: 10.57760/sciencedb.09642
title: Batch-to-Batch optimal control for multiple-input multiple-output batch processes based on multiway kernel partial least squares model
title: Batch-to-Batch optimal control for multiple-input multiple-output batch processes based on multiway kernel partial least squares model

description: Simulation Data for Batch-to-Batch optimal control for multiple-input multiple-output batch processes based on multiway kernel partial least squares model
description: Simulation Data for Batch-to-Batch optimal control for multiple-input multiple-output batch processes based on multiway kernel partial least squares model
DOI: 10.57760/sciencedb.11526
title: Music Institutions of Beijing, Shanghai, Guangzhou and Shenzhen
title: 北上广深音乐机构

description: Music institutions of Beijing, Shanghai, Guangzhou and Shenzhen
description: Music institutions of Beijing, Shanghai, Guangzhou and Shenzhen
DOI: 10.15468/dl.np3nzf
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xenia umbellata Lamarck, 1816",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 34 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001346-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.11567
title: Data for the manuscript submitted to ESN
title: Data for the manuscript submitted to ESN

description: Supporting data for the manuscript "Formation of stabilized colloidal vaterite nanoparticles via the introduction of uranyl into groundwater" submitted to ESN.
description: Supporting data for the manuscript "Formation of stabilized colloidal vaterite nanoparticles via the introduction of uranyl into groundwater" submitted to ESN.
DOI: 10.57760/sciencedb.09807
title: Data for photocharging BiVO4
title: Data for photocharging BiVO4

description: The data for XRD, J-V, charge transfer/separation efficiency, IMPS, charge density, log-log plot of dQ/dt~Q, XPS of O1s
description: The data for XRD, J-V, charge transfer/separation efficiency, IMPS, charge density, log-log plot of dQ/dt~Q, XPS of O1s
DOI: 10.57760/sciencedb.agriculture.00115
title: The identification dataset of commercial corn varieties in the summer corn growing area of North China's four provinces in 2021 and 2022
title: 2021-2022年华北四省夏玉米产区玉米商业品种鉴定数据集

description: This dataset offers data information on 27 key characteristics, including growth period, plant height, resistance, and yield, for 188 commercial maize varieties cultivated in the summer maize regions of China’s four provinces. The data are provided with daily time resolution and spans the years 2021 and 2022. The data collection and processing process strictly adheres to measurement instrument data quality control and standards. The data are publicly available at a regional scale, aiming to support the exploration and utilization of superior maize germplasm resources across various maize production regions.
description: This dataset offers data information on 27 key characteristics, including growth period, plant height, resistance, and yield, for 188 commercial maize varieties cultivated in the summer maize regions of China’s four provinces. The data are provided with daily time resolution and spans the years 2021 and 2022. The data collection and processing process strictly adheres to measurement instrument data quality control and standards. The data are publicly available at a regional scale, aiming to support the exploration and utilization of superior maize germplasm resources across various maize production regions.
DOI: 10.57760/sciencedb.11760
title: VGLL4, a promising biomarker, promotes epithelial-mesenchymal transition and cancer stemness via the Wnt pathway in hepatocellular carcinoma
title: VGLL4, a promising biomarker, promotes epithelial-mesenchymal transition and cancer stemness via the Wnt pathway in hepatocellular carcinoma

description: This study sorted out the expression of VGLL4 in hepatocellular carcinoma in TCGA, analyzed its differential expression and survival differences, and plotted the ROC curves of VGLL4 and AFP in hepatocellular carcinoma. Construct HepG2 cells with differential expression of VGLL4 and conduct phenotype and WB experiments. Data Fig1A-F show the differential expression of VGLL4 in HCC; Data Fig2A-E demonstrate that VGLL4 is an independent biomarker for poor prognosis in HCC patients; Data Fig3A-B shows the ROC curves of AFP and VGLL4 in liver cancer patients; Data Fig5 shows the correlation between VGLL4 expression and immune cell infiltration in HCC; The data related expression refers to the phenotype experiment and WB experiment data after constructing differentially expressed VGLL4 
description: This study sorted out the expression of VGLL4 in hepatocellular carcinoma in TCGA, analyzed its differential expression and survival differences, and plotted the ROC curves of VGLL4 and AFP in hepatocellular carcinoma. Construct HepG2 cells with differential expression of VGLL4 and conduct phenotype and WB experiments. Data Fig1A-F show the differential expression of VGLL4 in HCC; Data Fig2A-E demonstrate that VGLL4 is an independent biomarker for poor prognosis in HCC patients; Data Fig3A-B shows the ROC curves of AFP and VGLL4 in liver cancer patients; Data Fig5 shows the correlation between VGLL4 expression and immune cell infiltration in HCC; The data related expression refers to the phenotype experiment and WB experiment data after constructing differentially expressed VGLL4
DOI: 10.57760/sciencedb.17702
title: CloudSEN12+: The largest collection of expert-labeled pixels for cloud and cloud shadow detection in Sentinel-2
title: CloudSEN12+: The largest collection of expert-labeled pixels for cloud and cloud shadow detection in Sentinel-2

description: Detecting and screening clouds is the first step in any optical remote sensing (RS) analysis. Cloud formation is diverse, presenting many shapes, thicknesses, and altitudes. This variety poses a significant challenge to developing effective cloud detection algorithms since most datasets shortfall an unbiased representation. To address this issue, we have built CloudSEN12+, a significant expansion of the CloudSEN12 dataset. This new dataset doubles the expert-labeled pixels, making it the largest cloud detection dataset for Sentinel-2 imagery up to date. We have carefully reviewed and refined previous human labels in this new release to ensure maximum trustworthiness. We hope CloudSEN12+ will be a valuable resource for the cloud detection research community.
description: Detecting and screening clouds is the first step in any optical remote sensing (RS) analysis. Cloud formation is diverse, presenting many shapes, thicknesses, and altitudes. This variety poses a significant challenge to developing effective cloud detection algorithms since most datasets shortfall an unbiased representation. To address this issue, we have built CloudSEN12+, a significant expansion of the CloudSEN12 dataset. This new dataset doubles the expert-labeled pixels, making it the largest cloud detection dataset for Sentinel-2 imagery up to date. We have carefully reviewed and refined previous human labels in this new release to ensure maximum trustworthiness. We hope CloudSEN12+ will be a valuable resource for the cloud detection research community.
DOI: 10.57760/sciencedb.18011
title: Ancient Yi Script Handwriting Sample Repository
title: Ancient Yi Script Handwriting Sample Repository

description: The ancient Yi script has been used for over 8000 years, which can be ranked with Oracle,Sumerian,Egyptian,Mayan and Harappan,and is one of the six ancient scripts in the world. In this article, we collected 2922 handwritten single word samples of commonly used ancient Yi characters. Each character was written by 310 people respectively, with a total of 427,939 valid characters. We completed continuous handwritten text sampling, written by 250 people, with 5 texts per person, covering topics such as Yi astronomy, geography, rituals, and agriculture. In the process of data collection, we proposed an automatic sampling method for ancient Yi script, and completed the automatic cutting and labeling of handwritten samples. Furthermore, we tested the recognition performance of the sorted data set under different deep learning network models. The results show that ancient Yi script has diverse shape structures and rich writing styles, which can be used as a benchmark data set in related ffelds such as handwritten text recognition and handwritten text generation. 
description: The ancient Yi script has been used for over 8000 years, which can be ranked with Oracle,Sumerian,Egyptian,Mayan and Harappan,and is one of the six ancient scripts in the world. In this article, we collected 2922 handwritten single word samples of commonly used ancient Yi characters. Each character was written by 310 people respectively, with a total of 427,939 valid characters. We completed continuous handwritten text sampling, written by 250 people, with 5 texts per person, covering topics such as Yi astronomy, geography, rituals, and agriculture. In the process of data collection, we proposed an automatic sampling method for ancient Yi script, and completed the automatic cutting and labeling of handwritten samples. Furthermore, we tested the recognition performance of the sorted data set under different deep learning network models. The results show that ancient Yi script has diverse shape structures and rich writing styles, which can be used as a benchmark data set in related ffelds such as handwritten text recognition and handwritten text generation.
DOI: 10.57760/sciencedb.10342
title: Genome assembly and annotation results of Phytolacca icosandra L.
title: Genome assembly and annotation results of Phytolacca icosandra L.

description: Chromosome-level genome assembly and annotation results of Phytolacca icosandra L.
description: Chromosome-level genome assembly and annotation results of Phytolacca icosandra L.
DOI: 10.57760/sciencedb.09872
title: RNA sequencing raw data for Phytolacca icosandra under Cd stress
title: RNA sequencing raw data for Phytolacca icosandra under Cd stress

description: RNA sequencing raw data for Phytolacca icosandra roots under 0 (Cd0), 25 (Cd25), and 100 μM (Cd100) Cd treatments.
description: RNA sequencing raw data for Phytolacca icosandra roots under 0 (Cd0), 25 (Cd25), and 100 μM (Cd100) Cd treatments.
DOI: 10.57760/sciencedb.j00001.01054
title: Growing season dynamics dataset of plant communities on different slopes positions at the Yinshanbeilu Station , 2019-2022
title: 2019—2022 年阴山北麓站不同坡位植物群落生长季动态数据集

description: The desert steppe in Yinshanbeil has a special geographic location, which is both a transition zone from the Yinshan Mountains of China to the Mongolian Plateau, and a transition zone from a semi-arid zone to an arid zone climate. It belongs to the important ecological security barrier area in the northern part of the national ecological security pattern. Understanding the characteristics of plant communities in the region is of great significance for exploring the biodiversity of desert steppe, grassland productivity, and the recovery of degraded grassland. In this paper, we collated the field survey data of plant communities in different slope positions of the long-term enclosure sample site at the northern foot of Yinshanbeilu National Field Research Station during the growing season from 2019 to 2022. The data include plant species composition, height, coverage, density and aboveground biomass. The collection and processing of the dataset strictly followed the quality control and specifications of the grassland plant community survey.. This dataset will provide scientific basis and data support for the management and restoration of desert steppe.
description: The desert steppe in Yinshanbeil has a special geographic location, which is both a transition zone from the Yinshan Mountains of China to the Mongolian Plateau, and a transition zone from a semi-arid zone to an arid zone climate. It belongs to the important ecological security barrier area in the northern part of the national ecological security pattern. Understanding the characteristics of plant communities in the region is of great significance for exploring the biodiversity of desert steppe, grassland productivity, and the recovery of degraded grassland. In this paper, we collated the field survey data of plant communities in different slope positions of the long-term enclosure sample site at the northern foot of Yinshanbeilu National Field Research Station during the growing season from 2019 to 2022. The data include plant species composition, height, coverage, density and aboveground biomass. The collection and processing of the dataset strictly followed the quality control and specifications of the grassland plant community survey.. This dataset will provide scientific basis and data support for the management and restoration of desert steppe.