cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7635445
title: Amazon and Congo forest moisture recycling 1979-2014

description: Evaporation and precipitation recycling of the rainforests in South America and Africa 1979-2014. Do not use the spin-up years 1979 and 2014.
description: %MATLAB script for loading data for your convenience. Please define the paths. lat150 = ncread([myFolder 'Data\Interim_data\invariants.nc'],'latitude'); % [degrees_north] lon150 = ncread([myFolder 'Data\Interim_data\invariants.nc'],'longitude'); % [degrees_east] lat150 = double(lat150); lon150 = double(lon150); lsm = ncread([myFolder 'Data\Interim_data\invariants.nc'],'lsm'); % [degrees_north] lsm = lsm'; dg = 111089.56; gridcell = abs(lat150(2)-lat150(1)); % grid cell size [degrees] A_gridcell = (gridcell*dg)*(gridcell*cos(lat150*pi/180)*dg); % area size of the grid cell [m2] gridAreaMap = A_gridcell*ones(1,length(lon150)); %gridAreas for each cell of the world years = 1979:2014; load([outputFolder sprintf('Y%d-Y%d-precMYrs.mat',years(1),years(end))],'precMYrs') load([outputFolder sprintf('Y%d-Y%d-pTrackRatioMYrs.mat',years(1),years(end))],'pTrackRatioMYrs') evapMYrs = importdata([outputFolder sprintf('Y%d-Y%d-evapMYrsAmazonFor.mat',years(1),years(end))],'evapMYrsAmazonFor'); load([outputFolder sprintf('Y%d-Y%d-evapTrackMYrsAmazonFor.mat',years(1),years(end))],'evapTrackMYrsAmazonFor') load([outputFolder sprintf('Y%d-Y%d-evapTrackMYrsCongoFor.mat',years(1),years(end))],'evapTrackMYrsCongoFor') % p-shed load([outputFolder sprintf('Y%d-Y%d-precMYrsAmazonFor.mat',years(1),years(end))],'precMYrsAmazonFor') load([outputFolder sprintf('Y%d-Y%d-precTrackMYrsAmazonFor.mat',years(1),years(end))],'precTrackMYrsAmazonFor') % e-shed load([outputFolder sprintf('Y%d-Y%d-precMYrsCongoFor.mat',years(1),years(end))],'precMYrsCongoFor') load([outputFolder sprintf('Y%d-Y%d-precTrackMYrsCongoFor.mat',years(1),years(end))],'precTrackMYrsCongoFor') load([outputFolder sprintf('Y%d-Y%d-amazonRegions.mat',years(1),years(end))],... 'amSource','amazonHotspot','amazonSinkMinorNorth','amazonSinkMinorSouth','amazonSinkMajor') load([outputFolder sprintf('Y%d-Y%d-congoRegions.mat',years(1),years(end))],... 'coSource','congoHotspot','congoSinkMinorNorth','congoSinkMinorSouth','congoSinkMajor') % For calculating evaporation recycling ratios: evapTrackRatioMYrsAmazonFor = evapTrackMYrsAmazonFor./evapMYrs; evapTrackRatioMYrsCongoFor = evapTrackMYrsCongoFor./evapMYrs; % The forest regions are: regionAm = amSource + amazonHotspot; %Rainforest in South America regionCo = coSource + congoHotspot; %Rainforest in Africa
DOI: 10.5281/zenodo.7635444
title: Amazon and Congo forest moisture recycling 1979-2014

description: Evaporation and precipitation recycling of the rainforests in South America and Africa 1979-2014. Do not use the spin-up years 1979 and 2014.
description: %MATLAB script for loading data for your convenience. Please define the paths. lat150 = ncread([myFolder 'Data\Interim_data\invariants.nc'],'latitude'); % [degrees_north] lon150 = ncread([myFolder 'Data\Interim_data\invariants.nc'],'longitude'); % [degrees_east] lat150 = double(lat150); lon150 = double(lon150); lsm = ncread([myFolder 'Data\Interim_data\invariants.nc'],'lsm'); % [degrees_north] lsm = lsm'; dg = 111089.56; gridcell = abs(lat150(2)-lat150(1)); % grid cell size [degrees] A_gridcell = (gridcell*dg)*(gridcell*cos(lat150*pi/180)*dg); % area size of the grid cell [m2] gridAreaMap = A_gridcell*ones(1,length(lon150)); %gridAreas for each cell of the world years = 1979:2014; load([outputFolder sprintf('Y%d-Y%d-precMYrs.mat',years(1),years(end))],'precMYrs') load([outputFolder sprintf('Y%d-Y%d-pTrackRatioMYrs.mat',years(1),years(end))],'pTrackRatioMYrs') evapMYrs = importdata([outputFolder sprintf('Y%d-Y%d-evapMYrsAmazonFor.mat',years(1),years(end))],'evapMYrsAmazonFor'); load([outputFolder sprintf('Y%d-Y%d-evapTrackMYrsAmazonFor.mat',years(1),years(end))],'evapTrackMYrsAmazonFor') load([outputFolder sprintf('Y%d-Y%d-evapTrackMYrsCongoFor.mat',years(1),years(end))],'evapTrackMYrsCongoFor') % p-shed load([outputFolder sprintf('Y%d-Y%d-precMYrsAmazonFor.mat',years(1),years(end))],'precMYrsAmazonFor') load([outputFolder sprintf('Y%d-Y%d-precTrackMYrsAmazonFor.mat',years(1),years(end))],'precTrackMYrsAmazonFor') % e-shed load([outputFolder sprintf('Y%d-Y%d-precMYrsCongoFor.mat',years(1),years(end))],'precMYrsCongoFor') load([outputFolder sprintf('Y%d-Y%d-precTrackMYrsCongoFor.mat',years(1),years(end))],'precTrackMYrsCongoFor') load([outputFolder sprintf('Y%d-Y%d-amazonRegions.mat',years(1),years(end))],... 'amSource','amazonHotspot','amazonSinkMinorNorth','amazonSinkMinorSouth','amazonSinkMajor') load([outputFolder sprintf('Y%d-Y%d-congoRegions.mat',years(1),years(end))],... 'coSource','congoHotspot','congoSinkMinorNorth','congoSinkMinorSouth','congoSinkMajor') % For calculating evaporation recycling ratios: evapTrackRatioMYrsAmazonFor = evapTrackMYrsAmazonFor./evapMYrs; evapTrackRatioMYrsCongoFor = evapTrackMYrsCongoFor./evapMYrs; % The forest regions are: regionAm = amSource + amazonHotspot; %Rainforest in South America regionCo = coSource + congoHotspot; %Rainforest in Africa
DOI: 10.25625/oefalu/n9gpmd
title: EFForTS Landscape Assessment (LA) - B04,B06 Aboveground plant biomass

description: :unav
DOI: 10.6084/m9.figshare.22086071
title: Supplemental Material for Ligang Xiang et al., 2023

description: Gene function prediction of the genomeof Rhizoctonia solani AG-1 ⅠB in the NR, DFVF, TCDB, Swiss-Prot, P450, and Secretory_Protein database
DOI: 10.6084/m9.figshare.22086071.v1
title: Supplemental Material for Ligang Xiang et al., 2023

description: Gene function prediction of the genomeof Rhizoctonia solani AG-1 ⅠB in the NR, DFVF, TCDB, Swiss-Prot, P450, and Secretory_Protein database
DOI: 10.15151/esrf-es-1028462579
title: Quantification and control of 5f versus 6d contributions to spin and orbital angular momenta in early actinide paramagnetism.

description: Computational studies indicate that both the 5f and 6d valence orbitals can actively participate in thorium and uranium bonding, and in certain ligand field environments, both 5f and 6d orbitals can carry unpaired electrons. Using M2,3-edge and M4,5-edge XMCD, it is possible to selectively probe 6d and 5f paramagnetism. We propose XMCD studies to investigate how spin-orbit coupling and 6d-5f spin-exchange can be tailored by the ligand-field environment. We specifically target linear and C3 symmetry U/Th molecules due to their propensity to support a 6dz21 ground-state electron occupation. By comparing references that support 6dz20 ground-states, we will be able to unravel the complex contributions to the paramagnetism of molecules with open-shell 6d and 5f orbitals. The results of this study will bring new and important insights into how oxidation state and coordination symmetry influence the paramagnetism of the early actinides.
DOI: 10.5281/zenodo.7635015
title: mtKO_nucleoids dataset 02 - COXII KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>COXII loss of function</strong> mutations from the following acquisition dates:<br> 20221022<br> 20221026<br> 20221029 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.5281/zenodo.7635014
title: mtKO_nucleoids dataset 02 - COXII KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>COXII loss of function</strong> mutations from the following acquisition dates:<br> 20221022<br> 20221026<br> 20221029 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.5281/zenodo.7635050
title: mtKO_nucleoids dataset 03 - ATP8 KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>ATP8 loss of function</strong> mutations from the following acquisition dates:<br> 20221210<br> 20221211<br> 20221212 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.5281/zenodo.7635049
title: mtKO_nucleoids dataset 03 - ATP8 KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>ATP8 loss of function</strong> mutations from the following acquisition dates:<br> 20221210<br> 20221211<br> 20221212 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.5281/zenodo.7635070
title: mtKO_nucleoids dataset 04 - ND3 KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>ND3 loss of function</strong> mutations from the following acquisition dates:<br> 20221110<br> 20221111<br> 20221122 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.5281/zenodo.7635069
title: mtKO_nucleoids dataset 04 - ND3 KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>ND3 loss of function</strong> mutations from the following acquisition dates:<br> 20221110<br> 20221111<br> 20221122 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.5281/zenodo.7635078
title: mtKO_nucleoids dataset 05 - CYTB KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>CYTB loss of function</strong> mutations from the following acquisition dates:<br> 20221217<br> 20221220<br> 20221221 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.5281/zenodo.7635077
title: mtKO_nucleoids dataset 05 - CYTB KO

description: This is one of five imaging datasets to compare mtDNA mutant cell lines with isogenic wild-type cell lines by mtFociCounter. Images are <strong>Spinning Disk Confocal </strong>Images of unsorted 3t3 NIH mouse fibroblasts stably expressing <strong>mitochondrially</strong>targeted dsRed, immunofluorescence against dsDNA (mitochondrial <strong>nucleoids</strong>) and AlexaFluor 647, and stained <strong>nuclei</strong>with Hoechst.<br> Samples from the same day are 13mm coverslips processed in parallel (seeding of cells, fixation, immunofluorescence, microscopy) and mounted on the same glass slide (#1 on left, #2 centre, #3 right). This dataset contains data from <strong>WT</strong> cells and <strong>CYTB loss of function</strong> mutations from the following acquisition dates:<br> 20221217<br> 20221220<br> 20221221 For further details, please do not hesitate to contact the author, timorey AT hotmail DOT com.<br> A preprint with experimental details and analysis will be available soon.
DOI: 10.6084/m9.figshare.22067063
title: Near-anoxia induces immobilization and sustains viability of sperm in ant queens

description: This is a dataset which was used in the study "Near-anoxia induces immobilization and sustains viability of sperm in ant queens" by Gotoh et al. (2023) (doi: 10.1038/s41598-023-29705-7).
DOI: 10.5519/qd.rz4d1ji3
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (384 records)
DOI: 10.34740/kaggle/dsv/4991233
title: Survey on Employment Trends
DOI: 10.5519/qd.ma3jarep
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.22086164
title: report data.spv

description: report data in Study 1
DOI: 10.6084/m9.figshare.22086164.v1
title: report data.spv

description: report data in Study 1
DOI: 10.34740/kaggle/dsv/4991285
title: YouTube Daily
DOI: 10.5281/zenodo.7635563
title: 3dStool

description: The 3D surgical tool dataset (3dStool) has been constructed with the aim of assisting the development of computer vision techniques that address the operating room. Note, functions for visualisation, processing, and splitting the dataset can be found in the relevant github repository. Specifically, even though laparoscopic scenes have received a lot of attention in terms of labelled images, surgical tools that are used at initial stages of an operation, such as scalpels and scissors, have not had any such datasets developed. 3dStool includes 5370 images, accompanied by manually drawn polygon labels, as well as information on the 3D pose of these tools in operation. The tools were recorded while operating on a cadaveric knee. A RealSense D415 was used for image collection, while an optical tracker was employed for the purpose of 3D pose recording. Four surgical tools have been collected for now: Scalpel Scissors Forceps Electric Burr An annotation json file (in the format of COCO) exists for the images, containing the masks, boxes, and other relevant information. Furthermore, pose information is provided in two different manners. Firstly, a csv in the following format: CSV Structure Column 1 2 3 4 5 6 7 8 9 Value X (m) Y (m) Z (m) q<sub>i</sub> q<sub>j</sub> q<sub>k</sub> q<sub>l</sub> Class Image Name Position and orientation are both provided in the coordinate axes of the camera used to obtain the data (Realsense D415, Intel, USA). Pose is provided in the form of quaternions, however it is possible to convert this format into other available notations. The pose data can also be combined with the masks in the form of a final json file, in order to obtain a final COCO-format json with object poses as well. In the data provided, each of the test, train and validation subsets have their own COCO-like json files with the poses fused within, although the "orignal_jsons" only provide the image masks. The files and directories are structured as follows. Note that this example is based on the "train" directory, but a similar structure has been created for the test and val sets: Train manual_json - Contains the json created when manually annotating, the images, therefore <strong>no pose data</strong> included pose - Contains the CSV file with the poses of the relevant images, explained in the table above pose_json - Contains the fused json that includes both the annotations and the pose data for each image surgical2020 - Contains the images in jpg format
DOI: 10.5281/zenodo.7635562
title: 3dStool

description: The 3D surgical tool dataset (3dStool) has been constructed with the aim of assisting the development of computer vision techniques that address the operating room. Note, functions for visualisation, processing, and splitting the dataset can be found in the relevant github repository. Specifically, even though laparoscopic scenes have received a lot of attention in terms of labelled images, surgical tools that are used at initial stages of an operation, such as scalpels and scissors, have not had any such datasets developed. 3dStool includes 5370 images, accompanied by manually drawn polygon labels, as well as information on the 3D pose of these tools in operation. The tools were recorded while operating on a cadaveric knee. A RealSense D415 was used for image collection, while an optical tracker was employed for the purpose of 3D pose recording. Four surgical tools have been collected for now: Scalpel Scissors Forceps Electric Burr An annotation json file (in the format of COCO) exists for the images, containing the masks, boxes, and other relevant information. Furthermore, pose information is provided in two different manners. Firstly, a csv in the following format: CSV Structure Column 1 2 3 4 5 6 7 8 9 Value X (m) Y (m) Z (m) q<sub>i</sub> q<sub>j</sub> q<sub>k</sub> q<sub>l</sub> Class Image Name Position and orientation are both provided in the coordinate axes of the camera used to obtain the data (Realsense D415, Intel, USA). Pose is provided in the form of quaternions, however it is possible to convert this format into other available notations. The pose data can also be combined with the masks in the form of a final json file, in order to obtain a final COCO-format json with object poses as well. In the data provided, each of the test, train and validation subsets have their own COCO-like json files with the poses fused within, although the "orignal_jsons" only provide the image masks. The files and directories are structured as follows. Note that this example is based on the "train" directory, but a similar structure has been created for the test and val sets: Train manual_json - Contains the json created when manually annotating, the images, therefore <strong>no pose data</strong> included pose - Contains the CSV file with the poses of the relevant images, explained in the table above pose_json - Contains the fused json that includes both the annotations and the pose data for each image surgical2020 - Contains the images in jpg format
DOI: 10.5281/zenodo.7634530
title: Additional Files for "Standing genetic variation fuels rapid evolution of herbicide resistance in blackgrass"

description: This dataset contains additional supporting files referenced by the following publication: • Kersten S, Chang J, Huber CD, Voichek Y, Lanz C, Hagmaier T, Lang P, Lutz U, Hirschberg I, Lerchl J, Porri A, Van de Peer Y, Schmid K, Weigel D, Rabanal FA. <strong>Standing genetic variation fuels rapid evolution of herbicide resistance in blackgrass. </strong><em>Proc Natl Acad Sci USA</em>. Directory structure: <strong>Haplotypes_ACCase</strong>: this directory contains the two haplotypes (fasta format) inferred by pbaa (https://github.com/PacificBiosciences/pbAA ) for each of the 1,046 individuals for which it was possible to analyse the ACCase locus. <strong>Haplotypes_ALS</strong>: his directory contains the two haplotypes (fasta format) inferred by pbaa (https://github.com/PacificBiosciences/pbAA ) for each of the 842 individuals for which it was possible to analyse the ALS1 locus. <strong>Reference_genome</strong>: this directory contains the Pacbio CLR+Hi-C based chromosome level assembly (fasta file) of an <em>Alopecurus myosuroides</em> individual from the German herbicide-sensitive population DE01087 (Appels Wilde Samen GmbH, Darmstadt). In addition, it includes annotation files (gff format) for transposable elements and protein-coding genes. <strong>SNP_matrix</strong>: this directory contains the SNP matrix (vcf format) for the population study carried out with ddRAD-sequencing data.