cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4624239
title: Global Airborne Observatory: Forest Canopy Height and Carbon Stocks of Panama

description: Two maps are provided from a study of the Republic of Panama. The maps are based on airborne light detection and ranging (lidar) data, combined with satellite-based maps of forest cover and properties, acquired in 2012. The resulting maps are: (1) top of canopy height or TCH; and (2) aboveground carbon density or ACD. Units for TCH are meters above ground. Units for ACD are Mg C per hectare. Maps are provided at 1.0 ha spatial resolution. File format is GeoTIFF. Use of these data require citation of this dataset and the original journal paper that delivered the mapping method. These citations are as follows: Asner, G.P., J. Mascaro, C. Anderson, D.E. Knapp, R.E. Martin, T. Kennedy-Bowdoin, M. van Breugel, S. Davies, J.S. Hall, H.C. Muller-Landau, C. Potvin, W. Sousa, J. Wright and E. Bermingham. 2013. High-fidelity national carbon mapping for resource management and REDD+. <em>Carbon Balance and Management</em> 8:7 (doi:10.1186/1750-0680-8-7) Asner, G.P., J. Mascaro, C. Anderson, D.E. Knapp, and R.E. Martin. 2021. Global Airborne Observatory: Forest canopy height and carbon stocks of Panama (Version 1.0) [Data set]. Zenodo http://doi.org/10.5281/zenodo.4624240
DOI: 10.6084/m9.figshare.14176463.v1
title: RNA-sequencing data

description: Mouse lung ECs were isolated as described previously [8,35]. Purified endothelial cells (EC, CD31<sup>+ </sup>cells) were lysed for RNA isolation with the RNeasy mini kit (Qiagen Inc., Germantown, MD, USA) including DNase I digestion. Equal amounts of RNA from ECs isolated from three individual WT or <i>Egln1<sup>Tie2Cre</sup></i> mice were pooled and sequenced with NovaSeq PE150 at Novogene Corporation Inc. (Sacramento, CA, USA) The original sequencing data were trimmed using FASTX and aligned to the reference genome using TopHat2. The differential expression analysis was performed using Cuffdiff software [36].
DOI: 10.6084/m9.figshare.14256860
title: Additional file 10 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 10.
DOI: 10.6084/m9.figshare.14256860.v1
title: Additional file 10 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 10.
DOI: 10.6084/m9.figshare.14256863
title: Additional file 11 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 11.
DOI: 10.6084/m9.figshare.14256866
title: Additional file 12 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 12.
DOI: 10.6084/m9.figshare.14256869
title: Additional file 13 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 13.
DOI: 10.6084/m9.figshare.14256872
title: Additional file 14 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 14.
DOI: 10.6084/m9.figshare.14256869.v1
title: Additional file 13 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 13.
DOI: 10.6084/m9.figshare.14256872.v1
title: Additional file 14 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 14.
DOI: 10.6084/m9.figshare.14256866.v1
title: Additional file 12 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 12.
DOI: 10.6084/m9.figshare.14256863.v1
title: Additional file 11 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 11.
DOI: 10.6084/m9.figshare.14256878
title: Additional file 2 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 2.
DOI: 10.6084/m9.figshare.14256878.v1
title: Additional file 2 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 2.
DOI: 10.6084/m9.figshare.14256881
title: Additional file 3 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 3.
DOI: 10.6084/m9.figshare.14256881.v1
title: Additional file 3 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 3.
DOI: 10.6084/m9.figshare.14256887.v1
title: Additional file 4 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 4.
DOI: 10.6084/m9.figshare.14256890
title: Additional file 5 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 5.
DOI: 10.6084/m9.figshare.14256902
title: Additional file 8 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 8.
DOI: 10.6084/m9.figshare.14256887
title: Additional file 4 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 4.
DOI: 10.6084/m9.figshare.14256890.v1
title: Additional file 5 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 5.
DOI: 10.6084/m9.figshare.14256896
title: Additional file 6 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 6.
DOI: 10.6084/m9.figshare.14256896.v1
title: Additional file 6 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 6.
DOI: 10.6084/m9.figshare.14256899
title: Additional file 7 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 7.
DOI: 10.6084/m9.figshare.14256905
title: Additional file 9 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 9.
DOI: 10.6084/m9.figshare.14256902.v1
title: Additional file 8 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 8.
DOI: 10.6084/m9.figshare.14256905.v1
title: Additional file 9 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 9.
DOI: 10.6084/m9.figshare.14256899.v1
title: Additional file 7 of Comparative transcriptomic analysis of the different developmental stages of ovary in red swamp crayfish Procambarus clarkii

description: Additional file 7.
DOI: 10.6084/m9.figshare.14176463.v2
title: RNA-sequencing data

description: Mouse lung ECs were isolated as described previously [8,35]. Purified endothelial cells (EC, CD31<sup>+ </sup>cells) were lysed for RNA isolation with the RNeasy mini kit (Qiagen Inc., Germantown, MD, USA) including DNase I digestion. Equal amounts of RNA from ECs isolated from three individual WT or <i>Egln1<sup>Tie2Cre</sup></i> mice were pooled and sequenced with NovaSeq PE150 at Novogene Corporation Inc. (Sacramento, CA, USA) The original sequencing data were trimmed using FASTX and aligned to the reference genome using TopHat2. The differential expression analysis was performed using Cuffdiff software [36].
DOI: 10.6084/m9.figshare.14176463.v4
title: RNA-sequencing data

description: Please refer our published paper.Yi D, Liu B, Wang T, Liao Q, Zhu MM, Zhao YY, <b>Dai Z</b>. Endothelial Autocrine Signaling through CXCL12/CXCR4/FoxM1 Axis Contributes to Severe Pulmonary Arterial Hypertension. <i>Int. J. Mol. Sci</i>. 2021, 22(6), 3182.
DOI: 10.6084/m9.figshare.14176463.v3
title: RNA-sequencing data

description: Please refer our published paper.Yi D, Liu B, Wang T, Liao Q, Zhu MM, Zhao YY, <b>Dai Z</b>. Endothelial Autocrine Signaling throughCXCL12/CXCR4/FoxM1 Axis Contributes to Severe Pulmonary Arterial Hypertension. <i>Int. J. Mol. Sci</i>. 2021, 22(6), 3182.
DOI: 10.25442/hku.14254403
title: Data for the manuscript "Revealing the Importance of Capillary and Collisional Stresses on Soil Bed Erosion Induced by Debris Flows"

description: These data are generated in the lab and are about the erosion of an unsaturated soil bed by collisional flow.The data uploaded include:(1) Erosion profile - The erosion depth measured by using erosion columns and the calculated erosion rate for each test;(2) Soil bed shear strength - The data compulsory for estimating the shear strength of the unsaturated soil bed;(3) Flow-depth& velocity - Time series data about the flow depth (measured by an ultrasonic sensor) and velocity of the flow (extracted using the PIV technique) at the interface between the non-erodible and erodible beds;(4) Flow depth & pore pressure - Time series data about the flow depth (measured by an ultrasonic sensor) and the pore water pressure (measured by a pore pressure transducer.
DOI: 10.6084/m9.figshare.14176463
title: RNA-sequencing data

description: Please refer our published paper.Yi D, Liu B, Wang T, Liao Q, Zhu MM, Zhao YY, <b>Dai Z</b>. Endothelial Autocrine Signaling through CXCL12/CXCR4/FoxM1 Axis Contributes to Severe Pulmonary Arterial Hypertension. <i>Int. J. Mol. Sci</i>. 2021, 22(6), 3182.
DOI: 10.25442/hku.14254403.v1
title: Data for the manuscript "Revealing the Importance of Capillary and Collisional Stresses on Soil Bed Erosion Induced by Debris Flows"

description: These data are generated in the lab and are about the erosion of an unsaturated soil bed by collisional flow.The data uploaded include:(1) Erosion profile - The erosion depth measured by using erosion columns and the calculated erosion rate for each test;(2) Soil bed shear strength - The data compulsory for estimating the shear strength of the unsaturated soil bed;(3) Flow-depth& velocity - Time series data about the flow depth (measured by an ultrasonic sensor) and velocity of the flow (extracted using the PIV technique) at the interface between the non-erodible and erodible beds;(4) Flow depth & pore pressure - Time series data about the flow depth (measured by an ultrasonic sensor) and the pore water pressure (measured by a pore pressure transducer.
DOI: 10.5281/zenodo.4626347
title: Data set regarding snow algal modeling

description: This is a data set for using the snow algae model (Onuma et al., 2018; 2020). The content is as below. - data: observed algal cell concentration on the surface snow worldwide (CSV files). model input and output data (CSV files). output data simulated with Bio-MATSIRO (netCDF files). - python: programs for the visualization (python scripts) - figure: png files created by the python scripts
description: The uploaded figures and a python script were slightly modified.
DOI: 10.6084/m9.figshare.14247272
title: Table of the systematic review with the articles selected according to the established criteria, and information extracted from the articles from Systematic review of soil ecosystem services in tropical regions

description: Table of the systematic review of soil ecosystem services in tropical regions
DOI: 10.6084/m9.figshare.14247272.v2
title: Table of the systematic review with the articles selected according to the established criteria, and information extracted from the articles from Systematic review of soil ecosystem services in tropical regions

description: Table of the systematic review of soil ecosystem services in tropical regions
DOI: 10.6084/m9.figshare.14247272.v1
title: Table of the systematic review with the articles selected according to the established criteria, and information extracted from the articles from Systematic review of soil ecosystem services in tropical regions

description: Table of the systematic review of soil ecosystem services in tropical regions
DOI: 10.6084/m9.figshare.14247446
title: Table S2. from Protein aggregation and the evolution of stress resistance in clinical yeast

description: <b>Protein abundance in the aggregate fraction of [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>], and [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>] in comparison with total proteomic data and stress granule proteome.</b> Protein abundance (measured in peptide spectra count “PSM” and expressed in parts per million “ppm”) in isolated aggregates from [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>], [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], and [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>] strains are tabulated in Total Protein sheet. The comparison between stress granule and p-body were tabulated in Stress Granule P-body sheet. The ribosomal proteins identified in aggregate from [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>], [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], and [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>] strains were tabulated in Ribosomal Proteins sheet. The known yeast abundance from unified whole proteome quantification was listed for comparison [17]. Both the total proteome dataset and the aggregate isolation described in here were obtained from cells harvested during mid-exponential phase in YPD medium. The abundance in parts per million for [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>], [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], and [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>] strains were calculated by normalizing spectral counts of individual proteins by total spectral counts per samples and multiplying one million. Columns with a “PSM-Sol” suffix was abundance measures for the fraction that was SDS-soluble whereas columns with a “PSM-Res” suffix was the fraction that was SDS-resistant.
DOI: 10.6084/m9.figshare.14247455
title: Table S3. from Protein aggregation and the evolution of stress resistance in clinical yeast

description: <b>Mass-spectrometry data for aggregates isolated in clinical strains and cured derivatives.</b> Each individual sheet contains proteins identified in the aggregate fraction of a particular clinical strain of interest and its cured derivatives. Protein_AC is the uniprot accession number. Protein_MW is the molecular weight of the protein. Description is the description of protein identified. SGD_Alias is the SGD alias. SGD_Id is the SGD id of protein. Protein_Symbol is the protein symbol. Seq_Id is the systematic name of the protein. Gene is the gene name that encoded the protein. FC is the fold change calculated as the ratio between spectral count in the uncured strain over the cured strain normalized by the ratio of the total spectral counts of uncured strain over the cured strain.
DOI: 10.6084/m9.figshare.14247446.v1
title: Table S2. from Protein aggregation and the evolution of stress resistance in clinical yeast

description: <b>Protein abundance in the aggregate fraction of [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>], and [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>] in comparison with total proteomic data and stress granule proteome.</b> Protein abundance (measured in peptide spectra count “PSM” and expressed in parts per million “ppm”) in isolated aggregates from [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>], [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], and [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>] strains are tabulated in Total Protein sheet. The comparison between stress granule and p-body were tabulated in Stress Granule P-body sheet. The ribosomal proteins identified in aggregate from [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>], [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], and [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>] strains were tabulated in Ribosomal Proteins sheet. The known yeast abundance from unified whole proteome quantification was listed for comparison [17]. Both the total proteome dataset and the aggregate isolation described in here were obtained from cells harvested during mid-exponential phase in YPD medium. The abundance in parts per million for [<i>RNQ</i><sup>+</sup>][<i>PSI</i><sup>+</sup>], [<i>RNQ</i><sup>+</sup>][<i>psi</i><sup>−</sup>], and [<i>rnq</i><sup>−</sup>][<i>psi</i><sup>−</sup>] strains were calculated by normalizing spectral counts of individual proteins by total spectral counts per samples and multiplying one million. Columns with a “PSM-Sol” suffix was abundance measures for the fraction that was SDS-soluble whereas columns with a “PSM-Res” suffix was the fraction that was SDS-resistant.
DOI: 10.6084/m9.figshare.14247455.v1
title: Table S3. from Protein aggregation and the evolution of stress resistance in clinical yeast

description: <b>Mass-spectrometry data for aggregates isolated in clinical strains and cured derivatives.</b> Each individual sheet contains proteins identified in the aggregate fraction of a particular clinical strain of interest and its cured derivatives. Protein_AC is the uniprot accession number. Protein_MW is the molecular weight of the protein. Description is the description of protein identified. SGD_Alias is the SGD alias. SGD_Id is the SGD id of protein. Protein_Symbol is the protein symbol. Seq_Id is the systematic name of the protein. Gene is the gene name that encoded the protein. FC is the fold change calculated as the ratio between spectral count in the uncured strain over the cured strain normalized by the ratio of the total spectral counts of uncured strain over the cured strain.
DOI: 10.5281/zenodo.4626030
title: Lexparency.org legislative corpus

description: This dataset contains the transformed and refined versions of EU legislative acts of the type Regulation, Directive, or Decision. The provided format serves as input for the Lexparency.org web application. This dataset is like a sequel (not a new version) to the dataset 10.5281/zenodo.1442400
DOI: 10.5281/zenodo.3552372
title: Lexparency.org legislative corpus

description: This dataset contains the transformed and refined versions of EU legislative acts of the type Regulation, Directive, or Decision. The provided format serves as input for the Lexparency.org web application. This dataset is like a sequel (not a new version) to the dataset 10.5281/zenodo.1442400
DOI: 10.6084/m9.figshare.14257967
title: DEM and watershed boundary for Qinjiang River China

description: This is the dataset for PIHMgis exercise
DOI: 10.6084/m9.figshare.14257967.v1
title: DEM and watershed boundary for Qinjiang River China

description: This is the dataset for PIHMgis exercise
DOI: 10.6084/m9.figshare.14258003
title: Supplementary Material for: Cognitive Impairment after Lacunar Stroke and the Risk of Recurrent Stroke and Death

description: <b><i>Introduction:</i></b> Patients with poststroke cognitive impairment appear to be at higher risk of recurrent stroke and death. However, whether cognitive impairment after lacunar stroke is associated with recurrent stroke and death remains unclear. We assessed whether global or domain-specific cognitive impairment after lacunar stroke is associated with recurrent stroke and death. <b><i>Methods:</i></b> We considered patients from the Secondary Prevention of Small Subcortical Strokes (SPS3) trial with a baseline cognitive exam administered in English by certified SPS3 personnel, 14–180 days after qualifying lacunar stroke. We considered a baseline score of ≤86 on the Cognitive Assessment Screening Instrument to indicate global cognitive impairment, &lt;10 on the Clock Drawing on Command test to indicate executive function impairment, and domain-specific summary scores in the lowest quartile to indicate memory and nonmemory impairment. We used Cox proportional hazards models to estimate the association between poststroke cognitive impairment and subsequent risk of recurrent stroke and death. <b><i>Results:</i></b> The study included 1,528 participants with a median enrollment time of 62 days after qualifying stroke. During a mean follow-up of 3.9 years, 11.4% of participants had recurrent stroke and 8.2% died. In the fully adjusted models, memory impairment was independently associated with an increased risk of recurrent stroke (hazard ratio, 1.48; 95% confidence interval [95% CI]: 1.04–2.09) and death (hazard ratio, 1.87; 95% CI: 1.25–2.79). Global impairment (hazard ratio, 1.66; 95% CI: 1.06–2.59) and nonmemory impairment (hazard ratio, 1.74; 95% CI: 1.14–2.67) were associated with an increased risk of death. <b><i>Discussion/Conclusion:</i></b> After lacunar stroke, memory impairment was an independent predictor of recurrent stroke and death, while global and nonmemory impairment were associated with death. Cognitive screening in lacunar stroke may help identify populations at higher risk of recurrent stroke and death.
DOI: 10.6084/m9.figshare.14258003.v1
title: Supplementary Material for: Cognitive Impairment after Lacunar Stroke and the Risk of Recurrent Stroke and Death

description: <b><i>Introduction:</i></b> Patients with poststroke cognitive impairment appear to be at higher risk of recurrent stroke and death. However, whether cognitive impairment after lacunar stroke is associated with recurrent stroke and death remains unclear. We assessed whether global or domain-specific cognitive impairment after lacunar stroke is associated with recurrent stroke and death. <b><i>Methods:</i></b> We considered patients from the Secondary Prevention of Small Subcortical Strokes (SPS3) trial with a baseline cognitive exam administered in English by certified SPS3 personnel, 14–180 days after qualifying lacunar stroke. We considered a baseline score of ≤86 on the Cognitive Assessment Screening Instrument to indicate global cognitive impairment, &lt;10 on the Clock Drawing on Command test to indicate executive function impairment, and domain-specific summary scores in the lowest quartile to indicate memory and nonmemory impairment. We used Cox proportional hazards models to estimate the association between poststroke cognitive impairment and subsequent risk of recurrent stroke and death. <b><i>Results:</i></b> The study included 1,528 participants with a median enrollment time of 62 days after qualifying stroke. During a mean follow-up of 3.9 years, 11.4% of participants had recurrent stroke and 8.2% died. In the fully adjusted models, memory impairment was independently associated with an increased risk of recurrent stroke (hazard ratio, 1.48; 95% confidence interval [95% CI]: 1.04–2.09) and death (hazard ratio, 1.87; 95% CI: 1.25–2.79). Global impairment (hazard ratio, 1.66; 95% CI: 1.06–2.59) and nonmemory impairment (hazard ratio, 1.74; 95% CI: 1.14–2.67) were associated with an increased risk of death. <b><i>Discussion/Conclusion:</i></b> After lacunar stroke, memory impairment was an independent predictor of recurrent stroke and death, while global and nonmemory impairment were associated with death. Cognitive screening in lacunar stroke may help identify populations at higher risk of recurrent stroke and death.
DOI: 10.6084/m9.figshare.14257979
title: Urban groundwater system

description: We develop an analytical solution for the transit time distribution in an unconfined aquifer accounting for the construction-induced consolidation.