cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6075691
title: Annotated timeseries from yeast cell lifespans - Training and Test sets - DetecDiv (id03)

description: This dataset represents timeseries lables of cell divisions, to train & test a classifier to detect cell-cycle slowdown.<br> It has been generated by manual annotation from yeast cells lifespans using the DetecDiv software (see below). It is made of 1 file containing : Groundtruth Input data (Xdata): 250 timeseries of classes "1. unbudded", "2. small", "3. large", "4. dead", "5. empty", "6. clog" which are outputs from the doi.org/10.5281/zenodo.5553862 network Groundtruth outputdata (Ydata): 250 timeseries of classes "1. pre-slowdown", "2. post-slowdown", which have been annotated manually. The indexes from the Xdata correspond to that of the Ydata. Timeseries from 1-&gt;200 were used as training while 201-&gt;250 were used as validation. It is related to the trained network doi.org/10.5281/zenodo.5553829 from the software DetecDiv: github.com/gcharvin/DetecDiv biorxiv.org/content/10.1101/2021.10.05.463175v1 <strong>Data type</strong>: Vector timeseries (.mat) (250xF with F the number of frames, between 700 and 1000). <strong>File format</strong>: .mat <strong>Author(s)</strong>: Théo, ASPERT <strong>Contact email</strong>: theo.aspert@gmail.com <strong>Affiliation</strong>: IGBMC, Université de Strasbourg <strong>Funding bodies</strong>: This work was supported by the Agence Nationale pour la Recherche, the grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d'Avenir ANR-10-IDEX-0002-02.
description: {"references": ["DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis Theo Aspert, Didier Hentsch, Gilles Charvin bioRxiv 2021.10.05.463175; doi: https://doi.org/10.1101/2021.10.05.463175", "ASPERT Th\u00e9o. (2021). Trained network for cell-cycle slowdown detection - DetecDiv (id03) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5553829"]}
DOI: 10.5285/86429662-97b8-74fa-e053-6c86abc0a97c
title: An Alternative Framework to Assess Marine Ecosystem Functioning in Shelf Seas (AlterEco) Slocum Glider data, February to October 2018 in the North Sea. Involving units 436 (Stella), 345 (Cabot), 305 (Dolomite) during missions AE2, AE3 and AE4 respectively.

description: As part of the Alternative Framework to Assess Marine Ecosystem Functioning in Shelf Seas (AlterECO) project (NERC grant reference NE/P013902/1), Slocum gliders (units 436, 345 and 305) were deployed in a physically dynamic region of the North Sea, known to undergo seasonal oxygen depletion, over a period of nine months (February to October 2018). These deployments are part of an 18 month observational programme using marine autonomous vehicles. During each deployment the gliders tracked repeat North-South transects close to Dogger Bank and recorded over 6000 hours of data. Each glider carried a standard CTD package measuring temperature and water conductivity (salinity), an oxygen optode sensor and additional optical sensors for chlorophyll fluorescence, turbidity, CDOM fluorescence and PAR (excluding Unit 305), providing high resolution measurements of key hydrographical and biogeochemical parameters. During this 3 year programme and by developing and implementing a novel monitoring framework, AlterEco aims to deliver an improved spatio-temporal understanding of shelf sea function and provide measurements of critical indicators of marine ecosystem health over seasonal timescales.
DOI: 10.5281/zenodo.5553829
title: Trained network for cell-cycle slowdown detection - DetecDiv (id03)

description: <pre>Trained network for cell-cycle slowdown detection. Related to the dataset: doi.org/10.5281/zenodo.5553796</pre> <strong>------------------------------------------</strong> <strong>Author(s)</strong>: Théo, ASPERT <strong>Contact email</strong>: theo.aspert@gmail.com <strong>Affiliation</strong>: IGBMC, Université de Strasbourg <strong>Funding bodies</strong>: This work was supported by the Agence Nationale pour la Recherche, the grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d'Avenir ANR-10-IDEX-0002-02.
description: {"references": ["ASPERT Th\u00e9o. (2021). Annotated timeseries from yeast cell lifespans [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5553796", "ASPERT Th\u00e9o. (2021). Annotated timeseries from yeast cell lifespans - DetecDiv (id03) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5553796"]}
DOI: 10.5281/zenodo.6077125
title: Annotated pixels from brightfield images from yeast cell in microfluidic traps - Training and Test sets - DetecDiv (id02)

description: This dataset has been generated by manual segmentation from timelapse images of yeast cells dividing using the DetecDiv software (see below). It contains ~1950 raw images (folder "images") associated with their mask (folder "labels") with 3 classes of pixels according to their value on the mask image, "1. background", "2. mother", "3. other". A splitSets.mat indicates which images have been used for training or for testing. It is related to the trained network doi.org/10.5281/zenodo.5553851 from the software DetecDiv: github.com/gcharvin/DetecDiv biorxiv.org/content/10.1101/2021.10.05.463175v1 ------------------------------------------------------- <strong>Data type</strong>: 2D microscopy images (brightfield) (.tif) + mask image (.tif) <strong>Microscopy data type</strong>: Brightfield images <strong>Imaging</strong>: 20x 0.45 NA brightfield, 6.5µm*6.5µm sCMOS <strong>Cell type</strong>: Budding yeast wild type cell (BY4742) <strong>File format</strong>: .tif (16-bit RGB, 1 color per z-stack) + .mat <strong>Image size</strong>: Brightfield: 60x60x1 (Pixel size: x,y: 325 nm) // Mask: 60x60x1 (Pixel size: x,y: 325 nm), 3 pixel values (one per class). <strong>Author(s)</strong>: Théo, ASPERT <strong>Contact email</strong>: theo.aspert@gmail.com <strong>Affiliation</strong>: IGBMC, Université de Strasbourg <strong>Funding bodies</strong>: This work was supported by the Agence Nationale pour la Recherche, the grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d'Avenir ANR-10-IDEX-0002-02.
description: {"references": ["DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis Theo Aspert, Didier Hentsch, Gilles Charvin bioRxiv 2021.10.05.463175; doi: https://doi.org/10.1101/2021.10.05.463175", "ASPERT Th\u00e9o. (2021). Trained network for segmentation of yeast cell from brightfield images in microfluidic traps - DetecDiv (id02) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5553851"]}
DOI: 10.17632/hvh44pvfvp.1
title: Metabolomic changes in polyunsaturated fatty acids and eicosanoids as diagnostic biomarkers in Mycobacterium avium ssp. paratuberculosis (MAP)-inoculated Holstein-Friesian heifers

description: Herein, we used experimentally MAP-inoculated heifer calves to identify biomarkers for MAP infections. At 2-weeks of age, 20 Holstein-Friesian (HF) calves were experimentally inoculated with MAP. These calves, along with 20 control calves, were sampled biweekly up to 13-months of age and then monthly up to 19-months of age. Sera were assessed using flow infusion electrospray high-resolution mass spectrometry (FIE-HRMS) on a Q Exactive hybrid quadrupole-Orbitrap mass spectrometer for high throughput, sensitive, non-targeted metabolite fingerprinting
DOI: 10.5281/zenodo.5553851
title: Trained network for segmentation of yeast cell from brightfield images in microfluidic traps - DetecDiv (id02)

description: <pre>Trained network for segmentation of yeast cell from brightfield images in microfluidic traps. Related to the dataset: https://doi.org/10.5281/zenodo.5553771</pre> <strong>------------------------------------------</strong> <strong>Author(s)</strong>: Théo, ASPERT <strong>Contact email</strong>: theo.aspert@gmail.com <strong>Affiliation</strong>: IGBMC, Université de Strasbourg <strong>Funding bodies</strong>: This work was supported by the Agence Nationale pour la Recherche, the grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d'Avenir ANR-10-IDEX-0002-02.
description: {"references": ["DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis Theo Aspert, Didier Hentsch, Gilles Charvin bioRxiv 2021.10.05.463175; doi: https://doi.org/10.1101/2021.10.05.463175", "ASPERT Th\u00e9o. (2021). Annotated brightfield images from yeast cell in microfluidic traps - DetecDiv (id02) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5553771"]}
DOI: 10.5281/zenodo.5553862
title: Trained network for classification of images from yeast cell lifespans - DetecDiv (id01)

description: Trained network for classification of images from yeast cell lifespans. Related to the dataset: doi.org/10.5281/zenodo.5552642 Testset: doi.org/10.5281/zenodo.5866747 <strong>------------------------------------------</strong> <strong>Author(s)</strong>: Théo, ASPERT <strong>Contact email</strong>: theo.aspert@gmail.com <strong>Affiliation</strong>: IGBMC, Université de Strasbourg <strong>Funding bodies</strong>: This work was supported by the Agence Nationale pour la Recherche, the grant ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d'Avenir ANR-10-IDEX-0002-02.
description: {"references": ["DetecDiv, a deep-learning platform for automated cell division tracking and replicative lifespan analysis Theo Aspert, Didier Hentsch, Gilles Charvin bioRxiv 2021.10.05.463175; doi: https://doi.org/10.1101/2021.10.05.463175", "ASPERT Th\u00e9o. (2021). Annotated images from yeast cell lifespans - DetecDiv (id01) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5552642"]}
DOI: 10.5281/zenodo.6862986
title: Intention to utilize telehealth service in Bangladesh

description: This data consists of information on participants' knowledge, perceived benefit, perceived concerns, and predispositions related to telehealth services in Bangladesh. In the data set, k1 to k5 indicted the items of knowledge. Similarly, pb1 to pb4 indicate perceived benefit, pc indicates the item of perceived concern, and pd1 to pd2 indicates the items of predisposition. This data set also includes information related to the demographic and perceived health status information.
DOI: 10.6084/m9.figshare.19096781
title: WAMRI component C Test results

description: Contiene los resultados de una serie de test sobre el componente C en WAMRI<br>
DOI: 10.5066/p9x3axvj
title: EXPO-CAT: Population exposure to intensity for each Atlas ShakeMap
DOI: 10.17632/m57pyrz8zb.1
title: blockchain-for-uav-networks

description: This is a proof-of-concept implementation for a paper titled: Authenticated Wireless Links between a Drone and Sensors using a Blockchain: Case of Smart Farming by Kahlid S. Alqarni1, Faris A. Almalki, Ben Othman Soufiene, Obaid Ali and Faisal Albalwy
DOI: 10.4119/unibi/2900767
title: Eurace@Unibi Model v1.0 Source Code

description: Eurace@Unibi Model v1.0.1 Source Code is compatible with xparser-0.17.1 (GSL-2.4).
DOI: 10.4119/unibi/2908623
title: Data for the paper: Macroeconomics with Heterogeneous Agent Models: Fostering Transparency, Reproducibility and Replication
DOI: 10.4225/08/5afa18c1d0385
title: Agricultural profit map for Australia for 2010-2011

description: The provided data (the Data) represent a raster map of agricultural profit at full equity (PFE) for Australia for the year 2010/11. Values of PFE are provided in ($/ha) with 2011 $ values. PFE is a measure of profit which is calculated as the revenue from the sale of agricultural commodities minus all fixed and variable costs. This concept is based on the assumption that the land is fully owned (100% equity). The unit of PFE is $/ha.
The Data are provided as raster datasets compatible with ArcGIS. The spatial resolution is ~ 1km. Values provided are not for individual commodities (e.g. wheat, barley etc.) but for a set of commodity classes known as SPREAD classes (e.g. winter cereals, winter oilseeds) and broad land use categories (grazing, natural pastures etc.). Each pixel of the map is linked to agricultural land use but the Data as such do not provide information with regards to individual commodities of commodity groups. To link values of PFE to commodity groups (SPREAD classes) the Data need to be linked to the land use map of the year 2010/11 (Source: National scale land use 2010-11 version 5, Department of Agriculture and Water Resources) which provides the respective commodity class desc riptors.
DOI: 10.5281/zenodo.1451685
title: Geophysical Data From: "A Review Of Geophysical Methods For Soil Structure Characterization"

description: The geophysical data presented herein was collected in the Soil Structure Observatory (see, Keller et. al. 2017) and were used to create Figures 4b, 5a, 5b, 9a and 9b for the manuscript entitled: "A review of geophysical methods for soil structure characterization" submitted to reviews of geophysics. The data set includes:<br>
<br>
GPR data collected from South to North in the bare soil of block C before and after compaction<br>
GPR_800Mhz_BSbeforecompaction.DZW<br>
GPR_800Mhz_BSbeforecompaction.DZT<br>
GPR_800Mhz_BSaftercompaction.DZW<br>
GPR_800Mhz_BSaftercompaction.DZT<br>
<br>
ERT data collected from South to North in the bare soil of block B before and after compaction<br>
ERT_B2_14-03beforecompaction.bin<br>
ERT_B2_14-04aftercompaction.bin<br>
<br>
Time-lapse ERT data collected in block A in September of 2017:<br>
timelapseERT2017.zip<br>
The date and time in the files names indicate the time in which the resistivimeter started collecting data plus two hours.<br>
e.g. for 2017-09-11-18-01-41.bin, the first data point was collected at 14:01 on the 11th of September of 2017.<br>
The first 464 data points correspond to bare soil collected from North to South<br>
The following 464 data points correspond to grassy soil from South to North<br>
<br>
Meteorological data from 2017<br>
meteodata_Reckenholz2017.xls<br>
<br>
Time domain reflectometry data from September of 2017 for block A (10, 20, 40 and 70cm depth). Two land covers (bare soil and grassy soil) and two compaction treatments (full compacted and non compacted) are included.<br>
TDR_A1_Sept2017.xlsx

 

Keller, T., Colombi, T., Ruiz, S., Manalili, M. P., Rek, J., Stadelmann, V., ... & Schymanski, S. (2017). Long-Term Soil Structure Observatory for Monitoring Post-Compaction Evolution of Soil Structure. <em>Vadose Zone Journal</em>, <em>16</em>(4).
DOI: 10.5281/zenodo.7015077
title: Data supporting "Dispersal of bacteria and stimulation of permafrost decomposition by Collembola"

description: This archive contains the processed sequencing data, processed CO<sub>2</sub> flux data and the script used to generate figures and tables presented in "Dispersal of bacteria and stimulation of permafrost decomposition by Collembola" by Monteux S., Mariën J., and Krab E.J., Biogeosciences 2022, 19, 4089-4105, https://doi.org/10.5194/bg-19-4089-2022 . A more exhaustive repository including bioinformatics processing is found at https://git.bolin.su.se/bolin/monteux-2022-collembola and the raw DNA data is deposited at ENA under accession number PRJEB51992
description: {"references": ["https://doi.org/10.5194/bg-19-4089-2022"]}
DOI: 10.6073/pasta/e8f1f800c4d632a6178ba3a1928bc0b5
title: Small mammal structure cover collected at Team Vole fences near Nome, Toolik Lake, and Utqaigvik, Alaska, summer 2019

description: Percent cover of tundra vole and brown lemming structures collected from within the Team Vole enclosure/exclosure fences near Nome, Toolik, Utqiagvik, AK 2019.
DOI: 10.6084/m9.figshare.19137374
title: Duganella vulcania sp. nov., Rugamonas fusca sp. nov., Rugamonas brunnea sp. nov. and Rugamonas apoptosis sp. nov., isolated from subtropical streams, in China and phylogenomic analyses of the genera Janthinobacterium, Duganella, Rugamonas, Pseudoduganella and Massilia

description: Supplementary Material for ‘<em>Duganella vulcania</em> sp. nov., <em>Rugamonas fusca</em> sp. nov., <em>Rugamonas brunnea</em> sp. nov. and <em>Rugamonas apoptosis</em> sp. nov., isolated from subtropical streams, and phylogenomic analyses of the genera Janthinobacterium, Duganella, Rugamonas, Pseudoduganella and Massilia’, as published in <em>International Journal of Systematic and Evolutionary Microbiology</em>.
DOI: 10.6084/m9.figshare.20927293
title: Supplementary Material for: Statistical Analysis Plan for the INTEnsive Care Bundle with Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial: A Stepped-Wedge Cluster Randomized Controlled Trial

description: The third INTEnsive care bundle with blood pressure Reduction in Acute Cerebral hemorrhage Trial (INTERACT3) is an international, multicenter, stepped-wedge (4 phases/3 steps) cluster randomized trial involving 110 hospitals in mainly low- and middle-income countries during 2017–2022. The aim is to determine the effectiveness of a goal-directed care bundle of intensive blood pressure (BP) lowering, glycemic control, antipyrexia, and anticoagulation reversal treatment versus usual standard of care, in patients with acute intracerebral hemorrhage (ICH). After a “usual care” period, hospitals were randomly allocated to implementing care-bundle protocols for control targets (systolic BP &lt;140 mm Hg; glucose 6.1–7.8/7.8–10.0 mmol/L according to diabetes mellitus status; temperature ≤37.5°C; normalization of anticoagulation). A sample size of 8,360 patients (mean 19 per phase per site) provides 90% power (α = 0.05) for a 5.6% absolute improvement in the primary outcome of scores on the modified Rankin scale at 6 months, analyzed by ordinal logistic regression. A detailed statistical analysis plan (SAP) was developed to prespecify the method of analysis for all outcomes and key variables collected in the trial. The primary analysis will use ordinal logistic regression adjusted for the stepped-wedge design. The SAP also includes planned sensitivity analyses, including covariate adjustments, missing data imputations, and subgroup analysis. This SAP allows transparent, verifiable, and prespecified analyses in consideration of the challenges in conducting the study during the COVID pandemic. It also avoids analysis bias arising from prior knowledge of the findings in determining the benefits and harms of a care bundle in acute ICH.
DOI: 10.6084/m9.figshare.20935468
title: Supplementary Material for: Risk Factors and Outcomes of Stem Cell Mobilization Failure in Multiple Myeloma Patients

description: <b><i>Introduction:</i></b> Autologous hematopoietic stem cell transplantation (ASCT) is a well-established treatment for patients with multiple myeloma (MM), and adequate stem cell collection must be assured before ASCT. However, prediction of poor mobilizers (PMs) is still difficult despite several risk factors for mobilization failure having been identified. <b><i>Methods:</i></b> We retrospectively analyzed MM patients at Taipei Veterans General Hospital in Taiwan who underwent stem cell collection between October 2006 and August 2020. A CD34<sup>+</sup> cell collection of &lt;1 × 10<sup>6</sup> cells/kg was defined as a mobilization failure. The primary endpoint was mobilization failure. The secondary endpoint was overall survival (OS). Odds ratios (ORs) and 95% confidence intervals (CIs) for mobilization failure were calculated using a logistic regression model. The cumulative incidence of mortality was estimated using the Kaplan-Meier method. <b><i>Results:</i></b> In the multivariate analysis, absolute monocyte count &lt;500/µL (adjusted OR 10.75, 95% CI: 1.82–63.57, <i>p</i> = 0.009), platelet count &lt;150,000/µL (adjusted OR 12.49, 95% CI: 2.65–58.89, <i>p</i> = 0.001) before mobilization, and time interval from diagnosis to stem cell harvest ≥180 days (adjusted OR 7.69, 95% CI: 1.61–36.87, <i>p</i> = 0.011) were risk factors for PMs. PM patients had poorer OS compared to patients with successful stem cell collection in the univariate analysis (log-rank test <i>p</i> = 0.027). The predicted probability of PMs was estimated by the multiple logistic regression model with a sensitivity of 84.6% and a specificity of 84.0%. <b><i>Conclusion:</i></b> Absolute monocyte count &lt;500/µL, platelet count &lt;150,000/µL, and treatment duration more than 180 days before stem cell mobilization are risk factors for unsuccessful stem cell collection. Our prediction models have high sensitivity and specificity for mobilization failure prediction and allow for early interventions for possible PMs.
DOI: 10.17632/wv6kwbmf2h.1
title: seismic dataset of different finite difference method and different absorbing conditions

description: This dataset is a supplement to the paper of ''Second-order scalar wave field modeling with a first-order perfectly matched layer''. It contains two folders. The first folder 'Computational accuracy' describes the forward results of staggered grid finite difference and traditional grid finite difference in different states, which can compare the different grid methods and the forward accuracy under different parameters. The second folder 'Absorption efficiency' describes the absorption effect of four different absorbing boundary conditions.It can be used as a reference for selecting effective absorbing boundary conditions in geophysical research.
DOI: 10.6084/m9.figshare.21069802
title: SPMP BGCs

description: SPMP BGC genbank files from Antismash and DeepBGC
DOI: 10.6084/m9.figshare.21069802.v1
title: SPMP BGCs

description: SPMP BGC genbank files from Antismash and DeepBGC
DOI: 10.25625/ljmxts
title: Whole rock geochemical data for volcanic rocks of the western Cascades, Washington, Oregon, and California

description: Compilation of whole rock geochemical data for volcanic rocks from the Cascade Range incorporating about 4100 samples from 113 sources. Published as USGS Data Series 155 (du Bray et al., 2006).
DOI: 10.25625/ry3brk
title: Global distribution and composition of Neogene-Quaternary intraplate volcanic rocks

description: Global database of &gt;20, 000 geochemical analyses of Neogene-Quaternary intraplate volcanic rocks. The database collates major, trace element and Sr-Nd-Pb isotopic data for whole-rock samples &lt;20 Ma old that were published between 1990 and 2020. Database as published in Ball et al. (2021).
DOI: 10.25625/izszbl
title: Iran and SE Anatolia Meso-Cenozoic igneous rock compositions

description: Compilation of igneous rock compositions from Iran and SE Anatolia Meso-Cenozoic (ISA), including major, trace element and Sr-Nd-Pb isotopic data as published in Lustrino et al. (2021).
DOI: 10.25625/oxuhhc
title: Major and EDXRF Trace Element Chemical Analyses of Volcanic Rocks from Lassen Volcanic National Park and Vicinity, California

description: WDXRF major-element chemical data for late Pliocene to Holocene volcanic rocks collected from Lassen Volcanic National Park and vicinity, California. Data for Rb, Sr, Ba, Y, Zr, Nb, Ni, Cr, Zn and Cu obtained by EDXRF are included for many samples. Published as USGS Open-File Report 2008-1091 (Clynne et al., 2008).
DOI: 10.25625/7wxang
title: Magmatic rock compositions from the Circum-Mediterranean Anorogenic Cenozoic Igneous province

description: Collection of published and new major and trace element and Sr–Nd–Pb isotopic data (more than 7800 samples) for the magmatic rocks from the Circum-Mediterranean Anorogenic Cenozoic Igneous province compiled by Lustrino & Wilson (2007).