cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3750493
title: Gradients2-MGL1704-IFCB-ESD_2020-04-01_v1.0

description: Cruise: Gradients 2, MGL1704 Project Name: Simons Foundation, Gradient NPSG Dataset Description: The Imaging FlowCytoBot (IFCB) is an in situ automated imaging flow cytometer that generates images of particles suspended in seawater, in this case from the underway uncontaminated seawater system. The IFCB uses a recycled sheath fluid (0.2 µm filtered seawater) to align and drive particles individually towards a light source (red laser, 4.5 mW) in order to detect and identify single or colonial cells using a combination of optical properties (red fluorescence and light scattering intensities) and high resolution images (3.2 pixels per microns) by a mounted camera. Both optical properties are used to trigger targeted image acquisition of suspended particles in the size range &lt;4 to 100 μm. The instrument continuously samples from ~5 ml aliquots from the intake, and processes all particles contained in that volume for the next 20 minutes. Images corresponding to the "Sample" variable are available on the cruise's dashboard (http://ifcb-data.soest.hawaii.edu/IFCB_NPTZ). This dataset is the size, or equivalent spherical diameter, of imaged cells by genus. Equivalent spherical Diameter (ESD) is converted from the cell's biovolume (BV) assuming a spherical cell, according to the formula: ESD=[(6XBV)/(PI)]^(1/3). We use a series of matlab scripts provided by the H. Sosik (https://github.com/hsosik/ifcb-analysis/wiki) to outline cells and extract their corresponding biovolume using a pixels-distance map algorithm (Moberg and Sosik: 2012, doi:10.4319/lom.2012.10.278) and a fixed conversion factor (3.2 px/µm).
DOI: 10.5281/zenodo.4267140
title: Gradients2-MGL1704-IFCB-Abundance_2020-04-01_v1.0

description: Cruise: Gradients 2, MGL1704 Project Name: Simons Foundation, Gradient NPSG Dataset Description: The Imaging FlowCytoBot (IFCB) is an in situ automated imaging flow cytometer that generates images of particles suspended in seawater, in this case from the underway uncontaminated seawater system aboard the R/V Langseth (intake 5m). The IFCB uses a recycled sheath fluid (0.2 µm filtered seawater) to align and drive particles individually towards a light source (red laser, 4.5 mW) in order to detect and identify single or colonial cells using a combination of optical properties (red fluorescence and light scattering intensities) and high resolution images (3.2 pixels per micron) by a mounted camera. Both optical properties are used to trigger targeted image acquisition of suspended particles in the size range &lt;4 to 100 μm. The instrument continuously samples (few seconds) from ~5 ml aliquots from the intake, and processes all particles contained in that volume for the next 20 mins. Images corresponding to the "Sample" variable are available on the cruise's dashboard (http://ifcb-data.soest.hawaii.edu/IFCB_NPTZ). This dataset is for the abundance of imaged cells by genus. For each sample, the total number of cells classified to the genus-level by a random forest algorithm (Sosik and Olson, 2007 doi:10.4319/lom.2007.5.204) is counted and divided by the corresponding volume analyzed (~5 mL). Note that we used all the images collected during Gradients 2.0 to train the random forest algorithm and that classification is therefore highly accurate for this dataset. Using 7 µm calibration beads, we estimated that the error of cell concentration due to cell detection during sample acquisition averages 11 ± 10 %, independently of concentrations in the range 1-10000 cell/mL.
DOI: 10.5281/zenodo.3750484
title: Gradients2-MGL1704-IFCB-Abundance_2020-04-01_v1.0

description: Cruise: Gradients 2, MGL1704 Project Name: Simons Foundation, Gradient NPSG Dataset Description: The Imaging FlowCytoBot (IFCB) is an in situ automated imaging flow cytometer that generates images of particles suspended in seawater, in this case from the underway uncontaminated seawater system aboard the R/V Langseth (intake 5m). The IFCB uses a recycled sheath fluid (0.2 µm filtered seawater) to align and drive particles individually towards a light source (red laser, 4.5 mW) in order to detect and identify single or colonial cells using a combination of optical properties (red fluorescence and light scattering intensities) and high resolution images (3.2 pixels per micron) by a mounted camera. Both optical properties are used to trigger targeted image acquisition of suspended particles in the size range &lt;4 to 100 μm. The instrument continuously samples (few seconds) from ~5 ml aliquots from the intake, and processes all particles contained in that volume for the next 20 mins. Images corresponding to the "Sample" variable are available on the cruise's dashboard (http://ifcb-data.soest.hawaii.edu/IFCB_NPTZ). This dataset is for the abundance of imaged cells by genus. For each sample, the total number of cells classified to the genus-level by a random forest algorithm (Sosik and Olson, 2007 doi:10.4319/lom.2007.5.204) is counted and divided by the corresponding volume analyzed (~5 mL). Note that we used all the images collected during Gradients 2.0 to train the random forest algorithm and that classification is therefore highly accurate for this dataset. Using 7 µm calibration beads, we estimated that the error of cell concentration due to cell detection during sample acquisition averages 11 ± 10 %, independently of concentrations in the range 1-10000 cell/mL.
DOI: 10.5281/zenodo.4267131
title: SKiYMET Meteor Radar Horizontal Wind at Andes Lidar Observatory 2009-2014

description: This is horizontal wind measured by a SKiYMET Meteor Radar near Andes Lidar Observatory in Cerro Pachón, Chile (30.05 S, 70.82 W) from Sep 2009 to Aug 2014. The radar was previously installed at Maui, Hawaii and is described in the paper Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, <em>J. Geophys. Res.</em>, <em>110</em>, D09S02, doi:10.1029/2003JD004486. The data is in NetCDF format, at 1 hr and 2 km resolution from 80 to 100 km altitude. Time is in UT. Both time and altitude refer to the center of the 1 hr bin. Wind rms errors and numbers of meteor detections used for wind retrieval are also inicluded.
description: {"references": ["Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, J. Geophys. Res., 110, D09S02, doi:10.1029/2003JD004486."]}
DOI: 10.6084/m9.figshare.13218746
title: p62/SQSTM1-droplet serves as a platform for autophagosome formation and anti-oxidative stress response

description: p62/SQSTM1-droplet serves as a platform for autophagosome formation and anti-oxidative stress response
DOI: 10.6084/m9.figshare.13218746.v1
title: p62/SQSTM1-droplet serves as a platform for autophagosome formation and anti-oxidative stress response

description: p62/SQSTM1-droplet serves as a platform for autophagosome formation and anti-oxidative stress response
DOI: 10.5281/zenodo.4267141
title: SKiYMET Meteor Radar Horizontal Wind at Andes Lidar Observatory 2009-2014

description: This is horizontal wind measured by a SKiYMET Meteor Radar near Andes Lidar Observatory in Cerro Pachón, Chile (30.05 S, 70.82 W) from Sep 2009 to Aug 2014. The radar was previously installed at Maui, Hawaii and is described in the paper Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, <em>J. Geophys. Res.</em>, <em>110</em>, D09S02, doi:10.1029/2003JD004486. The data is in NetCDF format, at 1 hr and 2 km resolution from 80 to 100 km altitude. Time is in UT. Both time and altitude refer to the center of the 1 hr bin. Wind rms errors and numbers of meteor detections used for wind retrieval are also inicluded.
description: {"references": ["Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, J. Geophys. Res., 110, D09S02, doi:10.1029/2003JD004486."]}
DOI: 10.5281/zenodo.4267147
title: SKiYMET Meteor Radar Horizontal Wind at Andes Lidar Observatory 2009-2014

description: This is horizontal wind measured by a SKiYMET Meteor Radar near Andes Lidar Observatory in Cerro Pachón, Chile (30.05 S, 70.82 W) from Sep 2009 to Aug 2014. The radar was previously installed at Maui, Hawaii and is described in the paper Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, <em>J. Geophys. Res.</em>, <em>110</em>, D09S02, doi:10.1029/2003JD004486. The data is in NetCDF format, at 1 hr and 2 km resolution from 80 to 100 km altitude. Time is in UT. Both time and altitude refer to the center of the 1 hr bin. Wind rms errors and numbers of meteor detections used for wind retrieval are also inicluded.
description: {"references": ["Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, J. Geophys. Res., 110, D09S02, doi:10.1029/2003JD004486."]}
DOI: 10.5281/zenodo.4267127
title: SKiYMET Meteor Radar Horizontal Wind at Andes Lidar Observatory 2009-2014

description: This is horizontal wind measured by a SKiYMET Meteor Radar near Andes Lidar Observatory in Cerro Pachón, Chile (30.05 S, 70.82 W) from Sep 2009 to Aug 2014. The radar was previously installed at Maui, Hawaii and is described in the paper Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, <em>J. Geophys. Res.</em>, <em>110</em>, D09S02, doi:10.1029/2003JD004486. The data is in NetCDF format, at 1 hr and 2 km resolution from 80 to 100 km altitude. Time is in UT. Both time and altitude refer to the center of the 1 hr bin. Wind rms errors and numbers of meteor detections used for wind retrieval are also inicluded.
description: {"references": ["Franke, S. J., X. Chu, A. Z. Liu, W. K. Hocking (2005), Comparison of meteor radar and Na Doppler lidar measurements of winds in the mesopause region above Maui, Hawaii, J. Geophys. Res., 110, D09S02, doi:10.1029/2003JD004486."]}
DOI: 10.25919/5fab494fd8620
title: Parkes observations for project P1041 semester 2020APRS_24

description: We recently discovered five millisecond pulsars (MSPs) in the globular cluster Omega Centauri. This is the first pulsar discovery in this globular cluster. Four of these pulsars are isolated with spin periods of 4.1, 4.2, 4.6 and 6.8ms. The fifth has a spin period of 4.8ms and is in an eclipsing binary system with an orbital period of 2.1 hours. We propose to carry out a timing campaign of these new pulsars in order to study the dynamics in the core of Omega Centauri, to reveal the origin of Gamma-ray emission from the core, and to probe the ionised interstellar medium in Omega Centauri. Our proposed observations will also enable us to carry out deeper searches of pulsars in the cluster.
DOI: 10.6084/m9.figshare.13218806
title: Predictors of Viremia in PLWH in Guatemala_July 2019 to February 2020.sav

description: This is a data set of a prospective cohort of people living with HIV over the age of 18 taking place in Hospital Roosevelt in Guatemala used to determine predictors of viremia and persistent viremia. It includes 664 records consisting of demographic, socioeconomical and clinical variables related to viral non suppresion and persistent viremia plus recoded variables for aspects like excessive alcohol use, smoking and categorization based on viral status. For more information feel free to email me at deanwortizlopez@gmail.com
DOI: 10.6084/m9.figshare.13218806.v1
title: Predictors of Viremia in PLWH in Guatemala_July 2019 to February 2020.sav

description: This is a data set of a prospective cohort of people living with HIV over the age of 18 taking place in Hospital Roosevelt in Guatemala used to determine predictors of viremia and persistent viremia. It includes 664 records consisting of demographic, socioeconomical and clinical variables related to viral non suppresion and persistent viremia plus recoded variables for aspects like excessive alcohol use, smoking and categorization based on viral status. For more information feel free to email me at deanwortizlopez@gmail.com
DOI: 10.21227/ye86-qq22
title: GeoNRW

description: This dataset consists of orthorectified aerial photographs, LiDAR derived digital elevation models and segmentation maps with 10 classes, acquired through the open data program of the German state North Rhine-Westphalia (https://www.opengeodata.nrw.de/produkte/) and refined with OpenStreeMap. Please check the license information (http://www.govdata.de/dl-de/by-2-0). Preprocessing consists of resampling the 0.1m resolution photographs to 1m, taking the first LiDAR return while averaging within 1m² to arrive at the same resolution as the photographs, and rasterizing vector files of the land cover data. In total the dataset consists of 7783 triplets of size 1000x1000 pixels.
DOI: 10.6084/m9.figshare.13218818.v1
title: BFI

description: BFI dataset
DOI: 10.6084/m9.figshare.13218818
title: BFI

description: BFI dataset
DOI: 10.18112/openneuro.ds001787.v1.0.3
title: EEG meditation study
DOI: 10.5517/ccdc.csd.cc21yg3l
title: CCDC 1905139: Experimental Crystal Structure Determination

description: Related Article: Jiao Ji, Xin Chen, Hui Lin, Ai-Quan Jia, Qian-Feng Zhang|2019|Inorg.Chim.Acta|494|105|doi:10.1016/j.ica.2019.05.019
DOI: 10.5517/ccdc.csd.cc21yg5n
title: CCDC 1905141: Experimental Crystal Structure Determination

description: Related Article: Jiao Ji, Xin Chen, Hui Lin, Ai-Quan Jia, Qian-Feng Zhang|2019|Inorg.Chim.Acta|494|105|doi:10.1016/j.ica.2019.05.019
DOI: 10.5517/ccdc.csd.cc21yg6p
title: CCDC 1905142: Experimental Crystal Structure Determination

description: Related Article: Jiao Ji, Xin Chen, Hui Lin, Ai-Quan Jia, Qian-Feng Zhang|2019|Inorg.Chim.Acta|494|105|doi:10.1016/j.ica.2019.05.019
DOI: 10.5517/ccdc.csd.cc21yg8r
title: CCDC 1905144: Experimental Crystal Structure Determination

description: Related Article: Jiao Ji, Xin Chen, Hui Lin, Ai-Quan Jia, Qian-Feng Zhang|2019|Inorg.Chim.Acta|494|105|doi:10.1016/j.ica.2019.05.019
DOI: 10.5517/ccdc.csd.cc21yg9s
title: CCDC 1905145: Experimental Crystal Structure Determination

description: Related Article: Jiao Ji, Xin Chen, Hui Lin, Ai-Quan Jia, Qian-Feng Zhang|2019|Inorg.Chim.Acta|494|105|doi:10.1016/j.ica.2019.05.019
DOI: 10.5281/zenodo.4263528
title: Prediction of cardiovascular diseases by integrating multi-modal features with machine learning methods

description: Electrocardiogram (ECG) and Phonocardiogram (PCG) play important roles in early prevention and diagnosis of cardiovascular diseases. As the development of machine learning technique, detection of cardiovascular diseases from ECG and PCG has been attracted much attention. However, current available methods are mostly based on single data resource. It is desirable to develop efficient multi-modal machine learning methods to predict and diagnose cardiovascular diseases. In this study, we propose a novel multi-modal method for predicting cardiovascular diseases based on ECG and PCG features. By building up conventional neural networks, we extract ECG and PCG deep coding features respectively. The genetic algorithm is used to screen the combined features and obtain the best feature subset. Then support vector machine makes classification decision. Experimental results show that compared with using single-modal features ECG and PCG, the performance of this method reaches an AUC value of 0.936 when using multi-modal data resources. This dataset is developed from a real-world dataset which was assembled by PhysioNet/CinC Challenge in 2016. The original dataset can be downloaded from website (http://www.physionet.org/challenge/2016/).
DOI: 10.5281/zenodo.4263527
title: Prediction of cardiovascular diseases by integrating multi-modal features with machine learning methods

description: Electrocardiogram (ECG) and Phonocardiogram (PCG) play important roles in early prevention and diagnosis of cardiovascular diseases. As the development of machine learning technique, detection of cardiovascular diseases from ECG and PCG has been attracted much attention. However, current available methods are mostly based on single data resource. It is desirable to develop efficient multi-modal machine learning methods to predict and diagnose cardiovascular diseases. In this study, we propose a novel multi-modal method for predicting cardiovascular diseases based on ECG and PCG features. By building up conventional neural networks, we extract ECG and PCG deep coding features respectively. The genetic algorithm is used to screen the combined features and obtain the best feature subset. Then support vector machine makes classification decision. Experimental results show that compared with using single-modal features ECG and PCG, the performance of this method reaches an AUC value of 0.936 when using multi-modal data resources. This dataset is developed from a real-world dataset which was assembled by PhysioNet/CinC Challenge in 2016. The original dataset can be downloaded from website (http://www.physionet.org/challenge/2016/).
DOI: 10.6084/m9.figshare.13218827.v1
title: Dataset

description: Contains data on leaf trait, litter structure and flammability per species.
DOI: 10.6084/m9.figshare.12561770
title: Burmese82.map

description: <b>Mapping the genetic basis of diabetes mellitus in the Australian Burmese cat</b><b><br></b>Diabetes mellitus, a common endocrinopathy affecting domestic cats, shares many clinical and pathologic features with type 2 diabetes in humans. In Australia and Europe, diabetes mellitus is almost four times more common among Burmese cats than in other breeds. As a genetically isolated population, the diabetic Australian Burmese cat provides a spontaneous genetic model for studying diabetes mellitus in humans. Studying complex diseases in pedigreed breeds facilitates tighter control of confounding factors including population stratification, allelic frequencies and environmental heterogeneity. We used the feline 63K SNP array and whole genome sequence data to undertake a genome wide-association study in two stages, and runs of homozygosity analysis, of a case-control cohort of Australian and European Burmese cats. Our results identified diabetes-associated haplotypes across chromosomes A3, B1 and E1 and selective sweeps across the Burmese breed on chromosomes B1, B3, D1 and D4. The locus on chromosome B1, common to both analyses, revealed coding and splice region variants in candidate genes, ANK1, EPHX2 and LOX2, associated with diabetes mellitus and lipid dysregulation in Burmese of Australian provenance. Mapping this condition in a disproportionately affected breed has revealed a polygenic spectrum, implicating loci linked to pancreatic beta cell dysfunction, lipid dysregulation and insulin resistance in the pathogenesis of diabetes mellitus in the Burmese cat. <br>
DOI: 10.6084/m9.figshare.12561770.v1
title: Burmese82.map

description: <b>Mapping the genetic basis of diabetes mellitus in the Australian Burmese cat</b><b><br></b>Diabetes mellitus, a common endocrinopathy affecting domestic cats, shares many clinical and pathologic features with type 2 diabetes in humans. In Australia and Europe, diabetes mellitus is almost four times more common among Burmese cats than in other breeds. As a genetically isolated population, the diabetic Australian Burmese cat provides a spontaneous genetic model for studying diabetes mellitus in humans. Studying complex diseases in pedigreed breeds facilitates tighter control of confounding factors including population stratification, allelic frequencies and environmental heterogeneity. We used the feline 63K SNP array and whole genome sequence data to undertake a genome wide-association study in two stages, and runs of homozygosity analysis, of a case-control cohort of Australian and European Burmese cats. Our results identified diabetes-associated haplotypes across chromosomes A3, B1 and E1 and selective sweeps across the Burmese breed on chromosomes B1, B3, D1 and D4. The locus on chromosome B1, common to both analyses, revealed coding and splice region variants in candidate genes, ANK1, EPHX2 and LOX2, associated with diabetes mellitus and lipid dysregulation in Burmese of Australian provenance. Mapping this condition in a disproportionately affected breed has revealed a polygenic spectrum, implicating loci linked to pancreatic beta cell dysfunction, lipid dysregulation and insulin resistance in the pathogenesis of diabetes mellitus in the Burmese cat. <br>
DOI: 10.6084/m9.figshare.12561815
title: Burmese82.ped

description: <b>Mapping the genetic basis of diabetes mellitus in the Australian Burmese cat</b><br>Diabetes mellitus, a common endocrinopathy affecting domestic cats, shares many clinical and pathologic features with type 2 diabetes in humans. In Australia and Europe, diabetes mellitus is almost four times more common among Burmese cats than in other breeds. As a genetically isolated population, the diabetic Australian Burmese cat provides a spontaneous genetic model for studying diabetes mellitus in humans. Studying complex diseases in pedigreed breeds facilitates tighter control of confounding factors including population stratification, allelic frequencies and environmental heterogeneity. We used the feline 63K SNP array and whole genome sequence data to undertake a genome wide-association study in two stages, and runs of homozygosity analysis, of a case-control cohort of Australian and European Burmese cats. Our results identified diabetes-associated haplotypes across chromosomes A3, B1 and E1 and selective sweeps across the Burmese breed on chromosomes B1, B3, D1 and D4. The locus on chromosome B1, common to both analyses, revealed coding and splice region variants in candidate genes, ANK1, EPHX2 and LOX2, associated with diabetes mellitus and lipid dysregulation in Burmese of Australian provenance. Mapping this condition in a disproportionately affected breed has revealed a polygenic spectrum, implicating loci linked to pancreatic beta cell dysfunction, lipid dysregulation and insulin resistance in the pathogenesis of diabetes mellitus in the Burmese cat.
DOI: 10.6084/m9.figshare.12561815.v1
title: Burmese82.ped

description: <b>Mapping the genetic basis of diabetes mellitus in the Australian Burmese cat</b><br>Diabetes mellitus, a common endocrinopathy affecting domestic cats, shares many clinical and pathologic features with type 2 diabetes in humans. In Australia and Europe, diabetes mellitus is almost four times more common among Burmese cats than in other breeds. As a genetically isolated population, the diabetic Australian Burmese cat provides a spontaneous genetic model for studying diabetes mellitus in humans. Studying complex diseases in pedigreed breeds facilitates tighter control of confounding factors including population stratification, allelic frequencies and environmental heterogeneity. We used the feline 63K SNP array and whole genome sequence data to undertake a genome wide-association study in two stages, and runs of homozygosity analysis, of a case-control cohort of Australian and European Burmese cats. Our results identified diabetes-associated haplotypes across chromosomes A3, B1 and E1 and selective sweeps across the Burmese breed on chromosomes B1, B3, D1 and D4. The locus on chromosome B1, common to both analyses, revealed coding and splice region variants in candidate genes, ANK1, EPHX2 and LOX2, associated with diabetes mellitus and lipid dysregulation in Burmese of Australian provenance. Mapping this condition in a disproportionately affected breed has revealed a polygenic spectrum, implicating loci linked to pancreatic beta cell dysfunction, lipid dysregulation and insulin resistance in the pathogenesis of diabetes mellitus in the Burmese cat.