cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.lcbl.00043
title: Attached Drawing of manuscript LCBL240602
title: LCBL240602稿件附图

description: A Mendelian randomization study on the causal relationship between second-hand smoke and colorectal cancer, and the mediating effect of metabolites （Attached Drawing）
description: A Mendelian randomization study on the causal relationship between second-hand smoke and colorectal cancer, and the mediating effect of metabolites （Attached Drawing）
DOI: 10.57760/sciencedb.15731
title: Seismic landslide hazard map of Wenchuan earthquake area
title: Seismic landslide hazard map of Wenchuan earthquake area

description: The data was obtained by applying the SCM-ANFIS model to the Wenchuan earthquake region, providing a partial representation of the seismic landslide hazard in the area under investigation (Supplemented with seismic landslide hazard results obtained based on the new sampling method - RBS method and SCM-ANFIS model: s,s_8,s_12,s_13,s_15).
description: The data was obtained by applying the SCM-ANFIS model to the Wenchuan earthquake region, providing a partial representation of the seismic landslide hazard in the area under investigation (Supplemented with seismic landslide hazard results obtained based on the new sampling method - RBS method and SCM-ANFIS model: s,s_8,s_12,s_13,s_15).
DOI: 10.57760/sciencedb.19687
title: MuSyQ Global Leaf Chlorophyll Content product with 100m/10 days resolution(2020)
title: MuSyQ全球100m/10天分辨率叶片叶绿素含量产品(2020)

description: Leaf chlorophyll content (LCC) indicates the photosynthetic capacity of green vegetation, which is one of the most important biochemical parameters for ecosystem monitoring. Remote sensing is the only tool for obtaining global-scale LCC information. Over the past five years, researchers have produced several global LCC products. However, the spatial resolutions of existing products range from 300m to 500m, which is insufficient for detailed monitoring needs. This dataset utilizes the Chlorophyll Sensitive Index (CSI) to produce a global LCC product with a 100m/10 days resolution in 2020, based on vegetation type-specific empirical relationships using Sentinel-2 data. Existing research results show that this algorithm demonstrates high accuracy, efficiency, and stability in estimating LCC, making it suitable for the production of global LCC products, and it has the potential to generate higher-resolution global LCC products.
description: Leaf chlorophyll content (LCC) indicates the photosynthetic capacity of green vegetation, which is one of the most important biochemical parameters for ecosystem monitoring. Remote sensing is the only tool for obtaining global-scale LCC information. Over the past five years, researchers have produced several global LCC products. However, the spatial resolutions of existing products range from 300m to 500m, which is insufficient for detailed monitoring needs. This dataset utilizes the Chlorophyll Sensitive Index (CSI) to produce a global LCC product with a 100m/10 days resolution in 2020, based on vegetation type-specific empirical relationships using Sentinel-2 data. Existing research results show that this algorithm demonstrates high accuracy, efficiency, and stability in estimating LCC, making it suitable for the production of global LCC products, and it has the potential to generate higher-resolution global LCC products.
DOI: 10.57760/sciencedb.20135
title: First Proof of Principle Experiment for Muon Production with Ultrashort High Intensity Laser
title: First Proof of Principle Experiment for Muon Production with Ultrashort High Intensity Laser

description: Muons, which play a crucial role in both fundamental and applied physics, have traditionally been generated through proton accelerators or from cosmic rays. With the advent of ultra-short high-intensity lasers capable of accelerating electrons to GeV levels, it has become possible to generate muons in laser laboratories. In this work, we show the first proof of principle experiment for novel muon production with an ultra-short, high-intensity laser device through GeV electron beam bombardment on a lead converter target. The muon physical signal is confirmed by measuring its lifetime which is the first clear demonstration of laser-produced muons. Geant4 simulations were employed to investigate the photo-production, electro-production, and Bethe-Heitler processes response for muon generation and their subsequent detection. The results show that the dominant contributions of muons are attributed to the photo-production/electro-production and a significant yield of muons up to 0.01 μ/e- out of the converter target could be achieved. This laser muon source features compact, ultra-short pulse and high flux. Moreover, its implementation in a small laser laboratory is relatively straightforward, significantly reducing the barriers to entry for research in areas such as muonic X-ray elemental analysis, muon spin spectroscopy and so on.
description: Muons, which play a crucial role in both fundamental and applied physics, have traditionally been generated through proton accelerators or from cosmic rays. With the advent of ultra-short high-intensity lasers capable of accelerating electrons to GeV levels, it has become possible to generate muons in laser laboratories. In this work, we show the first proof of principle experiment for novel muon production with an ultra-short, high-intensity laser device through GeV electron beam bombardment on a lead converter target. The muon physical signal is confirmed by measuring its lifetime which is the first clear demonstration of laser-produced muons. Geant4 simulations were employed to investigate the photo-production, electro-production, and Bethe-Heitler processes response for muon generation and their subsequent detection. The results show that the dominant contributions of muons are attributed to the photo-production/electro-production and a significant yield of muons up to 0.01 μ/e- out of the converter target could be achieved. This laser muon source features compact, ultra-short pulse and high flux. Moreover, its implementation in a small laser laboratory is relatively straightforward, significantly reducing the barriers to entry for research in areas such as muonic X-ray elemental analysis, muon spin spectroscopy and so on.
DOI: 10.57760/sciencedb.19256
title: Mowing induced changes in plant diversity and productivity across N addition gradient in a temperate steppe
title: Mowing induced changes in plant diversity and productivity across N addition gradient in a temperate steppe

description: Data were collected from a field experiment in the temperate steppe with different levels of N addition.
description: Data were collected from a field experiment in the temperate steppe with different levels of N addition.
DOI: 10.57760/sciencedb.16692
title: Effects of Different Repetitive Transcranial Magnetic Stimulation Modalities
title: Effects of Different Repetitive Transcranial Magnetic Stimulation Modalities

description: A frequentist network meta-analysis (NMA) using a random-effects model was employed to synthesize both direct and indirect evidence concurrently. All analyses were conducted using Stata statistical software version 16.0 and Review Manager software version 5.331. The effect size for continuous variables was assessed using mean difference (MD) with a 95% confidence interval (CI). In cases where a closed loop existed, statistical inconsistency between direct and indirect evidence was evaluated through local (node-splitting method) and global (design-by-treatment interaction model) approaches32. If the P-value exceeded 0.05, it indicated no statistically significant inconsistency, and the consistency model was applied for further analysis. A network plot was generated to illustrate the relationships among the different interventions, where the size of the nodes represented the sample size of each intervention, and the line thickness indicated the number of randomized controlled trials (RCTs) with direct comparisons. The surface under the cumulative ranking curve (SUCRA) probabilities were calculated to assess the efficacy of various treatment strategies, with higher SUCRA values indicating a more favorable outcome33. Cumulative probability line charts were also produced. Lastly, potential publication bias in the NMA was evaluated using a comparison-adjusted funnel plot.
description: A frequentist network meta-analysis (NMA) using a random-effects model was employed to synthesize both direct and indirect evidence concurrently. All analyses were conducted using Stata statistical software version 16.0 and Review Manager software version 5.331. The effect size for continuous variables was assessed using mean difference (MD) with a 95% confidence interval (CI). In cases where a closed loop existed, statistical inconsistency between direct and indirect evidence was evaluated through local (node-splitting method) and global (design-by-treatment interaction model) approaches32. If the P-value exceeded 0.05, it indicated no statistically significant inconsistency, and the consistency model was applied for further analysis. A network plot was generated to illustrate the relationships among the different interventions, where the size of the nodes represented the sample size of each intervention, and the line thickness indicated the number of randomized controlled trials (RCTs) with direct comparisons. The surface under the cumulative ranking curve (SUCRA) probabilities were calculated to assess the efficacy of various treatment strategies, with higher SUCRA values indicating a more favorable outcome33. Cumulative probability line charts were also produced. Lastly, potential publication bias in the NMA was evaluated using a comparison-adjusted funnel plot.
DOI: 10.57760/sciencedb.10037
title: Thermal Efficiency Dataset Around Cuban Seas (TEDACS)
title: Thermal Efficiency Dataset Around Cuban Seas (TEDACS)

description: This data set contains the computation of thermal efficiency in the seas surrounding Cuba between latitudes 18.5° and 24.0°, and longitudes -73.5° and -85.5°. The objective is to obtain an evaluation of the study area according to the requirements for obtaining maremothermal energy, which must reach values greater than or equal to 0.7 of thermal efficiency. For the computation, 27 years of global ocean reanalysis data from the GLOBAL_MULTIYEAR_PHY_001_030 product of the Copernicus Marine Environmental Monitoring Service (CMEMS) with a spatial resolution of 1/12° have been used.
description: This data set contains the computation of thermal efficiency in the seas surrounding Cuba between latitudes 18.5° and 24.0°, and longitudes -73.5° and -85.5°. The objective is to obtain an evaluation of the study area according to the requirements for obtaining maremothermal energy, which must reach values greater than or equal to 0.7 of thermal efficiency. For the computation, 27 years of global ocean reanalysis data from the GLOBAL_MULTIYEAR_PHY_001_030 product of the Copernicus Marine Environmental Monitoring Service (CMEMS) with a spatial resolution of 1/12° have been used.
DOI: 10.57760/sciencedb.16082
title: Low-Carbon Transition and Firm Value: Based on the Carbon Peaking and Carbon Neutrality Goals
title: 低碳转型与企业价值——基于“双碳”目标视角

description: Paper data and code 
description: Paper data and code
DOI: 10.57760/sciencedb.18789
title: Raw Data for the Impact of Japanese Nuclear Wastewater Discharge Reports on Chinese Consumers' Seafood Purchasing Intentions
title: Raw Data for the Impact of Japanese Nuclear Wastewater Discharge Reports on Chinese Consumers' Seafood Purchasing Intentions

description: Raw Data for the Impact of Japanese Nuclear Wastewater Discharge Reports on Chinese Consumers' Seafood Purchasing Intentions
description: Raw Data for the Impact of Japanese Nuclear Wastewater Discharge Reports on Chinese Consumers' Seafood Purchasing Intentions
DOI: 10.15468/dl.kwja6f
title: Occurrence Download

description: A dataset containing 490 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Ascaphus montanus Mittleman & Myers, 1949)"
 ]
}

 The dataset includes 490 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001366-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.j00206.00048
title: Referral Strategy of Delay Sensitive Patients and Hospital Decision-Making Behavior Under Cooperative and Competitive Modes
title: 合作与竞争模式下延时敏感患者转诊策略与医院决策行为研究

description: The appendix contains the proofs of the propositions and lemmas of the Study of Referral Strategy of Delay Sensitive Patients and Hospital Decision-Making Behavior Under Cooperative and Competitive Modes.
description: The appendix contains the proofs of the propositions and lemmas of the Study of Referral Strategy of Delay Sensitive Patients and Hospital Decision-Making Behavior Under Cooperative and Competitive Modes.
DOI: 10.57760/sciencedb.17446
title: Staphylococcus aureus β-hemolysin
title: Staphylococcus aureus β-hemolysin

description: Staphylococcus aureus β-hemolysin
description: Staphylococcus aureus β-hemolysin
DOI: 10.57760/sciencedb.08560
title: DeepJiandu dataset for character detection and recognition on Jiandu manuscript
title: 简牍文字检测识别数据集

description: In ancient China, bamboo and wooden slips referred to as "Jiandu" served as primary mediums for documenting historical events prior to the advent of paper. These artifacts are rich in historical data and cultural significance. Accurate identification of characters on Jiandu is essential for deciphering the historical narratives they contain and plays a vital role in processing Jiandu manuscripts. We introduce the DeepJiandu dataset, specifically designed for the detection and recognition of Jiandu characters. Comprising 7,416 images annotated with 99,888 characters across 2,272 categories, this dataset addresses a variety of complex challenges encountered in Jiandu character recognition, including character degradation, diverse layouts, and variable forms and shapes. The authenticity and reliability of the DeepJiandu dataset render it an effective tool for training and evaluating models geared towards Jiandu character recognition.
description: In ancient China, bamboo and wooden slips referred to as "Jiandu" served as primary mediums for documenting historical events prior to the advent of paper. These artifacts are rich in historical data and cultural significance. Accurate identification of characters on Jiandu is essential for deciphering the historical narratives they contain and plays a vital role in processing Jiandu manuscripts. We introduce the DeepJiandu dataset, specifically designed for the detection and recognition of Jiandu characters. Comprising 7,416 images annotated with 99,888 characters across 2,272 categories, this dataset addresses a variety of complex challenges encountered in Jiandu character recognition, including character degradation, diverse layouts, and variable forms and shapes. The authenticity and reliability of the DeepJiandu dataset render it an effective tool for training and evaluating models geared towards Jiandu character recognition.
DOI: 10.57760/sciencedb.19830
title: Anti-UL82_Flag IP-MS
title: Anti-UL82_Flag IP-MS

description: After lysing SW620-UL82 OE cells, use Anti-UL82 to co-precipitate UL82 and analyze its interacting proteins. Use IgG as a negative control.
description: After lysing SW620-UL82 OE cells, use Anti-UL82 to co-precipitate UL82 and analyze its interacting proteins. Use IgG as a negative control.
DOI: 10.57760/sciencedb.19829
title: Metabolomics data of UL82 VS Vector.
title: Metabolomics data of UL82 VS Vector.

description: Transfect UL82 or Vector into SW620 cells and observe the changes in metabolomics.
description: Transfect UL82 or Vector into SW620 cells and observe the changes in metabolomics.
DOI: 10.57760/sciencedb.19828
title: Transcriptome sequencing of shAGR VS shNC
title: Transcriptome sequencing of shAGR VS shNC

description: Transcriptome sequencing data after SW620-UL82 OE was transfected with shAGR2 or shNC
description: Transcriptome sequencing data after SW620-UL82 OE was transfected with shAGR2 or shNC
DOI: 10.57760/sciencedb.19827
title: Transcriptome sequencing data of SW620_Vector versus SW620_UL82.
title: Transcriptome sequencing data of SW620_Vector versus SW620_UL82.

description: Overexpress the UL82 gene in the SW620 cell line and compare it with the empty vector transfection group to observe the changes in the transcriptome.
description: Overexpress the UL82 gene in the SW620 cell line and compare it with the empty vector transfection group to observe the changes in the transcriptome.
DOI: 10.57760/sciencedb.psych.00146
title: Dataset for Pupil Dynamics and Causality Perception: Insights from Pupillometry
title: Dataset for Pupil Dynamics and Causality Perception: Insights from Pupillometry

description: Dataset for Pupil Dynamics and Causality Perception: Insights from Pupillometry. This dataset includes preprocessed data, scripts for further analysis, and summarized data for statistical evaluation.
description: Dataset for Pupil Dynamics and Causality Perception: Insights from Pupillometry. This dataset includes preprocessed data, scripts for further analysis, and summarized data for statistical evaluation.
DOI: 10.57760/sciencedb.18680
title: Dataset of VEX and MHD simulation for manuscript "Unveiling the global characteristics of turbulence in the Venusian space environment"
title: Dataset of VEX and MHD simulation for manuscript "Unveiling the global characteristics of turbulence in the Venusian space environment"

description: Data and codes in the analyses based on the VEX observations and MHD simulation for manuscript "Unveiling the global characteristics of turbulence in the Venusian space environment". This dataset includes analyzing codes, the observation data and simulation data based on a 3D MHD Venus simulation model. The analyzing code are shown in "Fig1.m", "Fig2.m", "Fig3.m", and "Fig4.m", respectively. The observation and simulation data are shown in the "data" dir, including the grid data "grid_eq.mat" and "grid_xz.mat", the VEX data "psd_wake.dat" and "Wakesave.sav", the magnetic field data "Bmag.mat" and "Bmag_t.mat", the power data "power_Aball.mat" and "power_Abxz.mat", the spectral data "slope_ratio.mat".
description: Data and codes in the analyses based on the VEX observations and MHD simulation for manuscript "Unveiling the global characteristics of turbulence in the Venusian space environment". This dataset includes analyzing codes, the observation data and simulation data based on a 3D MHD Venus simulation model. The analyzing code are shown in "Fig1.m", "Fig2.m", "Fig3.m", and "Fig4.m", respectively. The observation and simulation data are shown in the "data" dir, including the grid data "grid_eq.mat" and "grid_xz.mat", the VEX data "psd_wake.dat" and "Wakesave.sav", the magnetic field data "Bmag.mat" and "Bmag_t.mat", the power data "power_Aball.mat" and "power_Abxz.mat", the spectral data "slope_ratio.mat".
DOI: 10.57760/sciencedb.19691
title: MuSyQ Global Leaf Chlorophyll Content product with 100m/10 days resolution(2022)
title: MuSyQ全球100m/10天分辨率叶片叶绿素含量产品(2022)

description: Leaf chlorophyll content (LCC) indicates the photosynthetic capacity of green vegetation, which is one of the most important biochemical parameters for ecosystem monitoring. Remote sensing is the only tool for obtaining global-scale LCC information. Over the past five years, researchers have produced several global LCC products. However, the spatial resolutions of existing products range from 300m to 500m, which is insufficient for detailed monitoring needs. This dataset utilizes the Chlorophyll Sensitive Index (CSI) to produce a global LCC product with a 100m/10 days resolution in 2022, based on vegetation type-specific empirical relationships using Sentinel-2 data. Existing research results show that this algorithm demonstrates high accuracy, efficiency, and stability in estimating LCC, making it suitable for the production of global LCC products, and it has the potential to generate higher-resolution global LCC products.
description: Leaf chlorophyll content (LCC) indicates the photosynthetic capacity of green vegetation, which is one of the most important biochemical parameters for ecosystem monitoring. Remote sensing is the only tool for obtaining global-scale LCC information. Over the past five years, researchers have produced several global LCC products. However, the spatial resolutions of existing products range from 300m to 500m, which is insufficient for detailed monitoring needs. This dataset utilizes the Chlorophyll Sensitive Index (CSI) to produce a global LCC product with a 100m/10 days resolution in 2022, based on vegetation type-specific empirical relationships using Sentinel-2 data. Existing research results show that this algorithm demonstrates high accuracy, efficiency, and stability in estimating LCC, making it suitable for the production of global LCC products, and it has the potential to generate higher-resolution global LCC products.
DOI: 10.57760/sciencedb.19595
title: MuSyQ Global Leaf Chlorophyll Content product with 100m/10 days resolution(2019)
title: MuSyQ全球100m/10天分辨率叶片叶绿素含量产品(2019)

description: Leaf chlorophyll content (LCC) indicates the photosynthetic capacity of green vegetation, which is one of the most important biochemical parameters for ecosystem monitoring. Remote sensing is the only tool for obtaining global-scale LCC information. Over the past five years, researchers have produced several global LCC products. However, the spatial resolutions of existing products range from 300m to 500m, which is insufficient for detailed monitoring needs. This dataset utilizes the Chlorophyll Sensitive Index (CSI) to produce a global LCC product with a 100m/10 days resolution in 2019, based on vegetation type-specific empirical relationships using Sentinel-2 data. Existing research results show that this algorithm demonstrates high accuracy, efficiency, and stability in estimating LCC, making it suitable for the production of global LCC products, and it has the potential to generate higher-resolution global LCC products.
description: Leaf chlorophyll content (LCC) indicates the photosynthetic capacity of green vegetation, which is one of the most important biochemical parameters for ecosystem monitoring. Remote sensing is the only tool for obtaining global-scale LCC information. Over the past five years, researchers have produced several global LCC products. However, the spatial resolutions of existing products range from 300m to 500m, which is insufficient for detailed monitoring needs. This dataset utilizes the Chlorophyll Sensitive Index (CSI) to produce a global LCC product with a 100m/10 days resolution in 2019, based on vegetation type-specific empirical relationships using Sentinel-2 data. Existing research results show that this algorithm demonstrates high accuracy, efficiency, and stability in estimating LCC, making it suitable for the production of global LCC products, and it has the potential to generate higher-resolution global LCC products.