cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2967j9
title: CCDC 2121160: Experimental Crystal Structure Determination

description: Related Article: Nicolas NIESSEN, Aurélien Chardon, Nikolay Tumanov, Johan Wouters, Guillaume Berionni|2021|CSD Communication|||
DOI: 10.3886/e164341
title: Music in Dance

description: this is a collection of presentation which is concerning to invitation in facilitating culture and traditional community group. I myself as a speaker and facilitator.
DOI: 10.3886/e164341v1
title: Music in Dance

description: this is a collection of presentation which is concerning to invitation in facilitating culture and traditional community group. I myself as a speaker and facilitator.
DOI: 10.34740/kaggle/dsv/11071
title: Sign Language Digits Dataset
DOI: 10.5517/ccdc.csd.ccxgfzr
title: CCDC 848035: Experimental Crystal Structure Determination

description: Related Article: E. Yamuna|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc296g11
title: CCDC 2121362: Experimental Crystal Structure Determination

description: Related Article: Timofey N. Chmovzh, Mikhail E. Minyaev|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc296h12
title: CCDC 2121393: Experimental Crystal Structure Determination

description: Related Article: Nico Graw|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc296h23
title: CCDC 2121394: Experimental Crystal Structure Determination

description: Related Article: Nico Graw|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc296h34
title: CCDC 2121395: Experimental Crystal Structure Determination

description: Related Article: Nico Graw|2021|CSD Communication|||
DOI: 10.5517/ccdc.csd.cc296h45
title: CCDC 2121396: Experimental Crystal Structure Determination

description: Related Article: Nico Graw|2021|CSD Communication|||
DOI: 10.18112/openneuro.ds004056.v1.0.2
title: GDMotor
DOI: 10.5281/zenodo.6338712
title: Data in support of "Self-adaptive multi-objective climate policies align mitigation and adaptation strategies"

description: The optimization results used for the paper "Self-adaptive multi-objective climate policies align mitigation and adaptation strategies" are reported in this folder. The content should be used together with the GitHub repository hosting the scripts for replication of the results discussed in the paper. In particular, it should be included in the CleanADCDICE folder before running the scripts to produce the figures.
DOI: 10.21227/vmw5-c226
title: RSRPSet_urban: Radio map in dense urban 

description: The experiment is based on the open source RSRP data provided by Huawei Technologies Co., LTD. It measures RSRP of 415,244 signal receiving points in 180 dense urban communication cells.
DOI: 10.6084/m9.figshare.19328630
title: RNA-Seq.xlsx

description: RNA-Seq in ROCK2-null podocytes<br>
DOI: 10.25442/hku.19322327
title: Supporting data for the manuscript "New Paradigm of Unsaturated Erosion Model for Flow-type Landslides: Debunking the Importance of Frictional Shear stress"

description: The spreadsheet contains data obtained in the physical experiments. The experiments are simulation of erosion of unsaturated soil beds caused by flow-type landslides. More specifically, these data are:<br>(1) Time-history of the basal forces generated by dry gravel flows measured by the loadcell. The loadcell is installed on the rigid bed.<br>(2) The probability distribution of basal forces generated by flows with different flow particle size.<br>(3) The probability distribution of basal forces generated by flows with different Froude number.<br>(4) Test program and the properties of the flows and bed material.<br>(5) A summary of the test results.<br>(6) Erosion depth measured by the 14 erosion columns.<br>(7) A summary of the test data obtained by Hsu et al. (2008) in modelling of rock erosion. (Citation: Hsu, L., Dietrich, W. E., & Sklar, L. S. (2008). Experimental study of bedrock erosion by granular flows. <i>Journal of Geophysical Research: Earth Surface</i>, <i>113</i>(F2).)
DOI: 10.25442/hku.19322327.v2
title: Supporting data for the manuscript "New Paradigm of Unsaturated Erosion Model for Flow-type Landslides: Debunking the Importance of Frictional Shear stress"

description: The spreadsheet contains data obtained in the physical experiments. The experiments are simulation of erosion of unsaturated soil beds caused by flow-type landslides. More specifically, these data are:<br>(1) Time-history of the basal forces generated by dry gravel flows measured by the loadcell. The loadcell is installed on the rigid bed.<br>(2) The probability distribution of basal forces generated by flows with different flow particle size.<br>(3) The probability distribution of basal forces generated by flows with different Froude number.<br>(4) Test program and the properties of the flows and bed material.<br>(5) A summary of the test results.<br>(6) Erosion depth measured by the 14 erosion columns.<br>(7) A summary of the test data obtained by Hsu et al. (2008) in modelling of rock erosion. (Citation: Hsu, L., Dietrich, W. E., & Sklar, L. S. (2008). Experimental study of bedrock erosion by granular flows. <i>Journal of Geophysical Research: Earth Surface</i>, <i>113</i>(F2).)
DOI: 10.25442/hku.19322327.v1
title: Supporting data for the manuscript "New Paradigm of Unsaturated Erosion Model for Flow-type Landslides: Debunking the Importance of Frictional Shear stress"

description: The spreadsheet contains data obtained in the physical experiments. The experiments are simulation of erosion of unsaturated soil beds caused by flow-type landslides. More specifically, these data are:<br>(1) Time-history of the basal forces generated by dry gravel flows measured by the loadcell. The loadcell is installed on the rigid bed.<br>(2) The probability distribution of basal forces generated by flows with different flow particle size.<br>(3) The probability distribution of basal forces generated by flows with different Froude number.
DOI: 10.6084/m9.figshare.19328612.v1
title: node-2001-2019.xlsx

description: 基于时间序列数据的土地覆盖演化时空图分析<br>
DOI: 10.6084/m9.figshare.19328642
title: Supplementary Material for: Endocannabinoid System in Polycystic Kidney Disease

description: <b><i>Introduction:</i></b> Autosomal dominant polycystic kidney disease (ADPKD) is a commonly inherited disorder characterized by renal cyst formation. A major pathological feature of ADPKD is the development of interstitial inflammation. The endocannabinoid (EC) system is present in the kidney and has recently emerged as an important player in inflammation and the pathogenesis of progressive kidney disease. <b><i>Methods:</i></b> Data on ECs were collected using a validated mass spectrometry assay from a well-characterized cohort of 102 ADPKD patients (at baseline and after 2- and 4 years on standard vs. rigorous blood-pressure control) and compared to 100 healthy subjects. <b><i>Results:</i></b> Compared to healthy individuals, we found higher interleukins-6 and -1b as well as reduced plasma levels of anandamide (AEA), 2-arachidonoyl­glycerol (2-AG), and their congeners in ADPKD patients. Baseline AEA concentration negatively associated with the progression of ADPKD as expressed by the yearly percent change in height-corrected total kidney volume and positively with the yearly change in renal function (measured as estimated glomerular filtration rate, ΔeGFR). AEA analog palmitoylethanolamide (PEA) is also associated positively with the yearly change in eGFR. <b><i>Discussion and Conclusion:</i></b> The results of the present study suggest that ADPKD patients present with lower levels of ECs and that reestablishing the normality of the renal EC system via augmentation of AEA, PEA, and 2-AG levels, either through the increase of their synthesis or through a reduction of their degradation, could be beneficial and may present a promising therapeutic target in said patients.
DOI: 10.25919/f66v-q224
title: Parkes pulsar observations with undefined project IDs for 2021OCTS_15

description: Parkes pulsar observations with undefined project IDs for 2021OCTS. This collection contains observations from project ID PX071.
DOI: 10.5281/zenodo.6339952
title: Interaction of Surface Glycoprotein of SARS-CoV-2 Variants of Concern with Potential Drug Candidates: A Molecular Docking Study

description: This dataset contains additional docking images of SARS-CoV-2 Variants of Concern with drugs under study. It also contains a spreadsheet containing binding residues with different types of bonds. Further it includes the raw spike protein sequences, 3D model of spike proteins of VOCs (variant of concern) and potential drugs used in this study.
DOI: 10.5281/zenodo.5955250
title: Interaction of Surface Glycoprotein of SARS-CoV-2 Variants of Concern with Potential Drug Candidates: A Molecular Docking Study

description: This dataset contains additional docking images of SARS-CoV-2 Variants of Concern with drugs under study. It also contains a spreadsheet containing binding residues with different types of bonds. Further it includes the raw spike protein sequences, 3D model of spike proteins of VOCs (variant of concern) and potential drugs used in this study.
DOI: 10.25919/efcg-9x24
title: Parkes observations for project P1050 semester 2021OCTS_24

description: This is a request for observing time for the timing campaign of new pulsar discoveries from the reprocessing of the low-latitude Galactic plane section of the HTRU survey (P630). We have now completed 90 % of the survey with GPU based coherent acceleration search, template bank and fast folding algorithm pipelines, and now have discovered 92 previously unknown pulsars and 8 "class A" pulsars awaiting confirmation. Interesting science can usually only be derived from a new pulsar after confirmation and a follow-up timing campaign is carried out. One year of initial timing is the minimum timespan required to fully characterise any newly-discovered pulsars, essential for deriving pulsar parameters such as the characteristic age, magnetic field strength, spin-down rate, as well as to detect any unexpected behaviour of the pulsar which might result from emission instabilities. Pulsars on the observing list here have been confirmed in the previous and current 2021APRS semesters, the follow-up timing in OCTS2021 will produce completely new and exciting results. In addition, this timing project will allow us to measure the true Galactic plane pulsar population and the boundaries of pulsar parameter space in the galactic plane.
DOI: 10.6084/m9.figshare.19328612
title: node-2001-2019.xlsx

description: 基于时间序列数据的土地覆盖演化时空图分析<br>
DOI: 10.6084/m9.figshare.19328612.v3
title: node-2001-2019.xlsx

description: 基于时间序列数据的土地覆盖演化时空图分析<br>
DOI: 10.6084/m9.figshare.19328612.v2
title: node-2001-2019.xlsx

description: 基于时间序列数据的土地覆盖演化时空图分析<br>
DOI: 10.18419/darus-2154
title: Supplementary material for 'An atomistic view on the uptake of aromatic compounds by cyclodextrin immobilized on mesoporous silica'

description: This dataset contains simulation input files in GROMACS format accompanying the mentioned publication. Structure, topology, and simulation parameter files are provided for all simulations conducted within the paper. The simulation is divided into three steps, an energy-minimization, an NVT equilibration, and an NVT production simulation run. Provided structure files are of an already equilibrated system. Object files are supplied which can be used to load the generated pores into PoreMS for later alteration and analysis. Additionally, short movies can be viewed for the different systems.
DOI: 10.6084/m9.figshare.19328675
title: Supplementary Material for: Impact of Glucose Tolerance and Its Change on Incident Proteinuria: Analysis of a Nationwide Population-Based Dataset

description: <b><i>Introduction:</i></b> Although diabetes mellitus (DM) increases the risk of proteinuria, the relationship between prediabetes and proteinuria remains not fully understood. Further, whether the change in glucose is associated with the risk for proteinuria is unknown. <b><i>Methods:</i></b> This was a retrospective cohort study that included 1,849,074 participants (median age, 45 years; 59.3% men). No participants were taking glucose-lowering medications, and none had positive proteinuria at the initial health check-up. Each participant was categorized into three groups: normal (hemoglobin A1c [HbA1c] of &lt;5.7%, <i>n</i> = 1,563,121), prediabetes (HbA1c of 5.7–6.4%, <i>n</i> = 253,490), and DM (HbA1c of ≥6.5%, <i>n</i> = 32,463) groups. We investigated the association between each HbA1c category and incident proteinuria using Cox proportional hazards models. We analyzed the association between the annual change in HbA1c and the risk for proteinuria. <b><i>Results:</i></b> A total of 65,954 participants developed proteinuria during the observation period. Not only DM (hazard ratio [HR]: 2.15, 95% confidence interval [CI]: 2.07–2.24) but also prediabetes (HR: 1.14, 95% CI: 1.12–1.17) was associated with a greater risk for proteinuria. The relative risk reduction for proteinuria that was associated with prediabetes and DM was 12.3% and 53.5%, respectively. An annual increase in HbA1c was associated with a greater risk for proteinuria. This association was more pronounced in participants having prediabetes. <b><i>Conclusion:</i></b> Not only DM but also prediabetes increased the risk for proteinuria. The influence of change in HbA1c on incident proteinuria was pronounced in people with prediabetes. Optimizing glucose would provide more benefit to individuals having prediabetes for proteinuria prevention.
DOI: 10.5281/zenodo.6339915
title: Datasets for chromatin hub prediction in six cell lines based on multiple genomic features

description: Tables with features and classes for machine learning prediction of chromatin hubs. Genomic features include CTCF, EP300, H3K27me3, H3K36me3, H3K4me1, H3K4me2, H3K4me3, H3K9ac, H3K9me3, RAD21, RNAPol2, and RNA.Seq, while the classes are Hubs and Non-Hubs. The cell lines featured here are A549, H1ESC, HeLa, IMR90, K562, and MCF7. They happen to be the 6 cell lines out of 8 existing in our integrative database, GREG (https://doi.org/10.1093/database/baz162). The normalized read-coverages from features (variables) are mapped through genomic intervals of 2 Kbs, genome-wide. Such genomic intervals (bins), are classified as Hubs or Non-Hubs. Hubs are those bins with multiple chromatin interactions, including at least one long-range interaction (larger than 1Mb) or an inter-chromosomal interaction (tagged as Inf). Columns per table:<br> chr start end CTCF EP300 H3K27me3 H3K36me3 H3K4me1 H3K4me2 H3K4me3 H3K9ac H3K9me3 RAD21 RNA.Seq RNAPol2 Class Note that features may be inconsistent across different cell types, due to the availability of data. The BAM files have been sourced from ENCODE and NCBI repositories. The analysis following this data can be found at https://github.com/mora-lab/GREG-Hubs.
DOI: 10.5281/zenodo.6339914
title: Datasets for chromatin hub prediction in six cell lines based on multiple genomic features

description: Tables with features and classes for machine learning prediction of chromatin hubs. Genomic features include CTCF, EP300, H3K27me3, H3K36me3, H3K4me1, H3K4me2, H3K4me3, H3K9ac, H3K9me3, RAD21, RNAPol2, and RNA.Seq, while the classes are Hubs and Non-Hubs. The cell lines featured here are A549, H1ESC, HeLa, IMR90, K562, and MCF7. They happen to be the 6 cell lines out of 8 existing in our integrative database, GREG (https://doi.org/10.1093/database/baz162). The normalized read-coverages from features (variables) are mapped through genomic intervals of 2 Kbs, genome-wide. Such genomic intervals (bins), are classified as Hubs or Non-Hubs. Hubs are those bins with multiple chromatin interactions, including at least one long-range interaction (larger than 1Mb) or an inter-chromosomal interaction (tagged as Inf). Columns per table:<br> chr start end CTCF EP300 H3K27me3 H3K36me3 H3K4me1 H3K4me2 H3K4me3 H3K9ac H3K9me3 RAD21 RNA.Seq RNAPol2 Class Note that features may be inconsistent across different cell types, due to the availability of data. The BAM files have been sourced from ENCODE and NCBI repositories. The analysis following this data can be found at https://github.com/mora-lab/GREG-Hubs.
DOI: 10.6084/m9.figshare.17703107
title: Predicting the risk of severe COVID-19 outcomes in primary care: development and validation of a vulnerability index for equitable allocation of effective vaccines

description: General practitioners (GPs) need a valid, user-friendly tool to identify patients most vulnerable to COVID-19, especially in the hypothesis of a booster vaccine dose. The aim of this study was to develop and validate a GP-friendly prognostic index able to forecast severe COVID-19 outcomes in primary care. Indeed, no such prognostic score is as yet available in Italy. In this retrospective cohort study, a representative sample of 47,868 Italian adults were followed up for 129,000 person–months. The study outcome was COVID-19-related hospitalization and/or death. Candidate predictors were chosen on the basis of systematic evidence and current recommendations. The model was calibrated by using Cox regression. Both internal and external validations were performed. Age, sex and several clinical characteristics were significantly associated with severe outcomes. The final multivariable model explained 60% (95%CI 58–63%) of variance for COVID-19-related hospitalizations and/or deaths. The area under the receiver-operator curve (AUC) was 84% (95% CI: 83–85%). On applying the index to an external cohort, the AUC was 94% (95% CI: 93–95%). This index is a reliable prognostic tool that can help GPs to prioritize their patients for preventive and therapeutic interventions.
DOI: 10.6084/m9.figshare.17703107.v1
title: Predicting the risk of severe COVID-19 outcomes in primary care: development and validation of a vulnerability index for equitable allocation of effective vaccines

description: General practitioners (GPs) need a valid, user-friendly tool to identify patients most vulnerable to COVID-19, especially in the hypothesis of a booster vaccine dose. The aim of this study was to develop and validate a GP-friendly prognostic index able to forecast severe COVID-19 outcomes in primary care. Indeed, no such prognostic score is as yet available in Italy. In this retrospective cohort study, a representative sample of 47,868 Italian adults were followed up for 129,000 person–months. The study outcome was COVID-19-related hospitalization and/or death. Candidate predictors were chosen on the basis of systematic evidence and current recommendations. The model was calibrated by using Cox regression. Both internal and external validations were performed. Age, sex and several clinical characteristics were significantly associated with severe outcomes. The final multivariable model explained 60% (95%CI 58–63%) of variance for COVID-19-related hospitalizations and/or deaths. The area under the receiver-operator curve (AUC) was 84% (95% CI: 83–85%). On applying the index to an external cohort, the AUC was 94% (95% CI: 93–95%). This index is a reliable prognostic tool that can help GPs to prioritize their patients for preventive and therapeutic interventions.
DOI: 10.5281/zenodo.5733564
title: Table of ToxTree Analysis

description: Tabulation of ToxTree Analysis for Journal Article:<strong>COMPUTATIONAL EXAMINATION </strong><strong>OF FLAVONOID COMPOUNDS: UTILIZATION OF MOLECULAR SIMULATION TO DISCOVER DRUG CANDIDATE FOR COVID-19</strong>
DOI: 10.5281/zenodo.5733563
title: Table of ToxTree Analysis

description: Tabulation of ToxTree Analysis for Journal Article:<strong>COMPUTATIONAL EXAMINATION </strong><strong>OF FLAVONOID COMPOUNDS: UTILIZATION OF MOLECULAR SIMULATION TO DISCOVER DRUG CANDIDATE FOR COVID-19</strong>
DOI: 10.6084/m9.figshare.19328689.v1
title: Table S2 from The <i>yellow</i> gene regulates behavioural plasticity by repressing male courtship in <i>Bicyclus anynana</i> butterflies

description: Differentially expressed genes of male pupal brains comparisons between treatments (Dry season with vehicle - DSV, Wet season with vehicle - WSV and Dry season injected with 20E - DS20E. logFC represents the log-foldchange in the gene expression; logCPM represents the log counts per million; FDR represents the false discovery rate, where values of less than 0.001 are simply represented as &lt;0.001. See excel file sheet 1 for DSV compared to WSV, sheet 2 for DS20E compared to DSV, and sheet 3 for DS20E compared to WSV. Green color indicates down-regulated genes and red indicates upregulated genes.
DOI: 10.6084/m9.figshare.19328689
title: Table S2 from The <i>yellow</i> gene regulates behavioural plasticity by repressing male courtship in <i>Bicyclus anynana</i> butterflies

description: Differentially expressed genes of male pupal brains comparisons between treatments (Dry season with vehicle - DSV, Wet season with vehicle - WSV and Dry season injected with 20E - DS20E. logFC represents the log-foldchange in the gene expression; logCPM represents the log counts per million; FDR represents the false discovery rate, where values of less than 0.001 are simply represented as &lt;0.001. See excel file sheet 1 for DSV compared to WSV, sheet 2 for DS20E compared to DSV, and sheet 3 for DS20E compared to WSV. Green color indicates down-regulated genes and red indicates upregulated genes.
DOI: 10.6084/m9.figshare.19328695
title: Movies from Robust and efficient identification of optimal mixing perturbations using proxy multiscale measures

description: Movies for flows presented in Heffernan & Caulfield
DOI: 10.6084/m9.figshare.19328695.v1
title: Movies from Robust and efficient identification of optimal mixing perturbations using proxy multiscale measures

description: Movies for flows presented in Heffernan & Caulfield
DOI: 10.6084/m9.figshare.19328698
title: Electronic supplementary cls file from Robust and efficient identification of optimal mixing perturbations using proxy multiscale measures

description: Supplementary cls file
DOI: 10.6084/m9.figshare.19328698.v1
title: Electronic supplementary cls file from Robust and efficient identification of optimal mixing perturbations using proxy multiscale measures

description: Supplementary cls file
DOI: 10.6084/m9.figshare.19328701
title: Data from Robust and efficient identification of optimal mixing perturbations using proxy multiscale measures

description: Data and models presented in Heffernan & Caulfield
DOI: 10.6084/m9.figshare.19328701.v1
title: Data from Robust and efficient identification of optimal mixing perturbations using proxy multiscale measures

description: Data and models presented in Heffernan & Caulfield
DOI: 10.5281/zenodo.6334016
title: mFRR market related datasets for HLU9 of the CROSSBOW project

description: Datasets for HLU9 of the CROSSBOW project. What is included? <strong>Cross-Zonal Capacities</strong> - formatted dataset published as a whole CZC data for the years 2018 & 2019 were gathered in HLU9. The CZC values were for the timeframe after the ID market took place (before the mFRR market). Parameters included: Date & Time, CZC value to and from the delivering LFC area. CZC data was collected for borders of TSOs from the CROSSBOW project consortium<strong>.</strong> <strong>mFRR market related data </strong>- formatted dataset published, sensitive data omitted as per the guidelines from TSOs mFRR market data include <strong>BSP bids</strong> (which are comprised of Price, Timestamp, Direction, Quantity, LFC Area…), <strong>TSO demands</strong> (which are comprised of Quantity, Direction, Elasticity, LFC area, Timestamp…). Not all data was made available by the TSOs.