cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7799725
title: stitches package data

description: This dataset contains the package data for the "stitches" model developed by the GCIMS project. More information about stitches can be found at https://github.com/jgcri/stitches
DOI: 10.5281/zenodo.8367628
title: stitches package data

description: This dataset contains the package data for the "stitches" model developed by the GCIMS project. More information about stitches can be found at https://github.com/jgcri/stitches
DOI: 10.5281/zenodo.8307735
title: Data-set for "Reliability and operation cost of underdamped memories during cyclic erasures" (Research Article, No. apxr.202300074) to Advanced Physics Research.

description: <strong>Dataset for the article: "Reliability and operation cost of underdamped memories during cyclic erasures" (Research Article, No. apxr.202300074) to Advanced Physics Research. </strong> <strong>FigX.fig: </strong>Matlab format figure source used to draw all of the plots of the article, embedding the all data. <strong>evolution_K.m:</strong> Matlab code file that implement the Repeated Erasure model and compute the success rate of the erasure from the temperature evolution computed from the model. <strong>Model_Landauer_enchaine.m:</strong> Matlab code file. Function which uses the SE Model to calculate the evolution of all the energy quantities (average) during step 1 and step 2 starting at an initial temperature CI, and also renders the final temperature conditions to be used iteratively in the RE Model. <strong>Toy_Model.m: </strong>Theoretical toy model for explaning the Landauer repeted erasures temperature evolution. <strong>Analysis_repeated_erasure.m:</strong> Matlab code file to treat raw data .mat files of 45 repeated erasures to compute the energy, work and heat evolution. The average is done on the full raw data samples corresponding to thousands of 45 repeated erasures. <strong>XmsRawData.zip:</strong> Raw data of 45 repeated erasures of duration X ms each. Those Matlab data files are meant to be analysed with the Analysis_repeated_erasure code. Among the usefull variables contained in those files we identifiy : V: applied protocol, position of center of the wells in nm x: position signal in nm sigma_m: calibration of the standard deviation used by the feedback x0: threshold of the virtual potential tau1: duration of step1 tau2: duration of step 2 tau4: half resting time between step1 and step2 X1: initial half distance between the wells dt: acquisition sampling time <br>
DOI: 10.5281/zenodo.8307734
title: Data-set for "Reliability and operation cost of underdamped memories during cyclic erasures" (Research Article, No. apxr.202300074) to Advanced Physics Research.

description: <strong>Dataset for the article: "Reliability and operation cost of underdamped memories during cyclic erasures" (Research Article, No. apxr.202300074) to Advanced Physics Research. </strong> <strong>FigX.fig: </strong>Matlab format figure source used to draw all of the plots of the article, embedding the all data. <strong>evolution_K.m:</strong> Matlab code file that implement the Repeated Erasure model and compute the success rate of the erasure from the temperature evolution computed from the model. <strong>Model_Landauer_enchaine.m:</strong> Matlab code file. Function which uses the SE Model to calculate the evolution of all the energy quantities (average) during step 1 and step 2 starting at an initial temperature CI, and also renders the final temperature conditions to be used iteratively in the RE Model. <strong>Toy_Model.m: </strong>Theoretical toy model for explaning the Landauer repeted erasures temperature evolution. <strong>Analysis_repeated_erasure.m:</strong> Matlab code file to treat raw data .mat files of 45 repeated erasures to compute the energy, work and heat evolution. The average is done on the full raw data samples corresponding to thousands of 45 repeated erasures. <strong>XmsRawData.zip:</strong> Raw data of 45 repeated erasures of duration X ms each. Those Matlab data files are meant to be analysed with the Analysis_repeated_erasure code. Among the usefull variables contained in those files we identifiy : V: applied protocol, position of center of the wells in nm x: position signal in nm sigma_m: calibration of the standard deviation used by the feedback x0: threshold of the virtual potential tau1: duration of step1 tau2: duration of step 2 tau4: half resting time between step1 and step2 X1: initial half distance between the wells dt: acquisition sampling time <br>
DOI: 10.5281/zenodo.8367522
title: Diffraction dataset collected for HeX-2 from T. suis

description: Diffraction image collected on Eiger detector on proxima 1 on 110/09/2022 to solve the apo structure of Hex-2 from T. suis deposited under PDB code 8QK1. 3600 images 0.1° oscillation at 2.4 ansgtrom on the edge
DOI: 10.5281/zenodo.8367521
title: Diffraction dataset collected for HeX-2 from T. suis

description: Diffraction image collected on Eiger detector on proxima 1 on 110/09/2022 to solve the apo structure of Hex-2 from T. suis deposited under PDB code 8QK1. 3600 images 0.1° oscillation at 2.4 ansgtrom on the edge
DOI: 10.48420/23864202
title: Convection-compensated pure shift NMR

description: This archive contains all raw experimental data files, macros, pulse sequence code, shaped pulse definitions and Mathematica notebooks to support the article "Convection-compensated pure shift NMR: how to stop convection ruining experiments."
DOI: 10.48420/23864202.v1
title: Convection-compensated pure shift NMR

description: This archive contains all raw experimental data files, macros, pulse sequence code, shaped pulse definitions and Mathematica notebooks to support the article "Convection-compensated pure shift NMR: how to stop convection ruining experiments."
DOI: 10.5281/zenodo.8366334
title: FCS and SMLM datasubset from Dibsy et al.

description: Data(sub)set of FCS measurements and SMLM acquisitions used respectively to establish figure 5 and figure 3 of Dibsy et al. FCS zip contains raw data, fitted data (raw data minus excluded data due to photobleaching, large fluctuations, aggregates...) and FCS waist calibration data, to plot FCS diffusion laws (tau1/2=f(w²)). SMLM subset is made of two typical raw images that can be analyzed by any of SMLM reconstructing software to retrieves clusters and clusters (cell) surface density in the presence or absence of a drug modulating branched actin connections (CK666)
DOI: 10.5281/zenodo.8366333
title: FCS and SMLM datasubset from Dibsy et al.

description: Data(sub)set of FCS measurements and SMLM acquisitions used respectively to establish figure 5 and figure 3 of Dibsy et al. FCS zip contains raw data, fitted data (raw data minus excluded data due to photobleaching, large fluctuations, aggregates...) and FCS waist calibration data, to plot FCS diffusion laws (tau1/2=f(w²)). SMLM subset is made of two typical raw images that can be analyzed by any of SMLM reconstructing software to retrieves clusters and clusters (cell) surface density in the presence or absence of a drug modulating branched actin connections (CK666)
DOI: 10.25345/c59z90p1t
title: MassIVE MSV000092923 - Motrpac - Endurance Exercise Training Study In 6 Months Old Rats (Protein Phosphorylation In Heart And Liver)
title: This proteomics dataset focuses on the study of changes in protein phosphorylation in the following tissues: liver and heart. The dataset is a subset of an endurance exercise training study that targets young adult (6-month-old) rats. Specifically, male and female Fischer 344 rats (n = 12) were subjected to progressive treadmill endurance exercise training for 1, 2, 4, or 8 weeks, with tissues collected 48 hours after the last exercise bout. Sex-matched sedentary, untrained rats were used as controls. This study contributes to MoTrPAC's broader mission, which is to identify molecular changes occurring due to exercise. The ultimate goal is to understand how physical activity can improve and sustain health across various ages and fitness levels. The program is supported by the NIH Common Fund. For additional information, visit the MoTrPAC Data Hub at https://motrpac-data.org/.
DOI: 10.5281/zenodo.8367745
title: cfr-data v1.0

description: This repository hosts frequently used datasets for climate field reconstruction (CFR) and supports data remote loading for the Python package cfr. Included datasets <code>PAGES2kv2</code>: PAGES2k Consortium (2017) <code>gistemp1200_ERSSTv4</code>: https://data.giss.nasa.gov/gistemp/ <code>BC09_NINO34</code>: Bunget & Clarke (2009)
DOI: 10.5281/zenodo.8367746
title: cfr-data v1.0

description: This repository hosts frequently used datasets for climate field reconstruction (CFR) and supports data remote loading for the Python package cfr. Included datasets <code>PAGES2kv2</code>: PAGES2k Consortium (2017) <code>gistemp1200_ERSSTv4</code>: https://data.giss.nasa.gov/gistemp/ <code>BC09_NINO34</code>: Bunget & Clarke (2009)
DOI: 10.25345/c56688v7c
title: MassIVE MSV000092924 - Motrpac - Endurance Exercise Training Study In 6 Months Old Rats (Protein Acetylation In Heart And Liver)
title: This proteomics dataset focuses on the study of changes in protein acetylation in the following tissues: liver and heart. The dataset is a subset of an endurance exercise training study that targets young adult (6-month-old) rats. Specifically, male and female Fischer 344 rats (n = 12) were subjected to progressive treadmill endurance exercise training for 1, 2, 4, or 8 weeks, with tissues collected 48 hours after the last exercise bout. Sex-matched sedentary, untrained rats were used as controls. This study contributes to MoTrPAC's broader mission, which is to identify molecular changes occurring due to exercise. The ultimate goal is to understand how physical activity can improve and sustain health across various ages and fitness levels. The program is supported by the NIH Common Fund. For additional information, visit the MoTrPAC Data Hub at https://motrpac-data.org/.
DOI: 10.15151/esrf-es-1332880330
title: iNEXT Discovery-Instruct ESRF-ERIC; Structural biology for translational research and discovery.

description: The aim of this proposal is to provide user access to automated protein-to-structure and fragment screening pipelines based on the combination of EMBL HTX lab services and CrystalDirect technology and automated data collection at ESRF’s MX beamlines. Access modalities will include 1) Online-Crystallography (Protein-to-Structure pipeline) 2) Large-Scale ligand and Fragment Screening and 3) new Plate-to-beam data collection modalities enabled by the integration of CrystalDirect at MASSIF1. User access to these modalities will require competitive application and peer-review through the E.C. funded iNEXT Discovery and Instruct-ERIC consortia. Moreover, new approaches for high density ligand screening will be implemented and the experimental opportunities enabled by the Integration of CrystalDirect at the MASSIF-1 station will be further developed. This work will be carried out in the context of international collaborative projects.
DOI: 10.5281/zenodo.8367373
title: Parenting_mouse_demo_model

description: Please see https://www.nature.com/articles/s41592-022-01443-0 for full details on this data and model. Here, as a demo we provide a DLCRNet-50_ms4 trained for 60K iterations, batch size 4. It was trained on 70% of the dataset as presented at: https://benchmark.deeplabcut.org/datasets.html
DOI: 10.5281/zenodo.8367374
title: Parenting_mouse_demo_model

description: Please see https://www.nature.com/articles/s41592-022-01443-0 for full details on this data and model. Here, as a demo we provide a ResNet-50_ms4 trained for 60K iterations, batch size 4.
DOI: 10.5281/zenodo.8367716
title: Parenting_mouse_demo_model

description: Please see https://www.nature.com/articles/s41592-022-01443-0 for full details on this data and model. Here, as a demo we provide a DLCRNet-50_ms4 trained for 60K iterations, batch size 4. It was trained on 70% of the dataset as presented at: https://benchmark.deeplabcut.org/datasets.html
DOI: 10.14469/hpc/12985
title: Endo_TS1_G16_PCM_DCM_def2svp_v_01_reactant

description: Gaussian 16 (C01) calculation
DOI: 10.14469/hpc/12986
title: Endo_TS1_G16_PCM_DCM_def2svp_v_01

description: Kinisot.py command line KIE calculation: "python3 /usr/local/bin/Kinisot.py REACTANT.log TS.log --iso ATOM -t TEMP", where ATOM is number label of transferred proton and TEMP is the temperature (Kelvin)
DOI: 10.23719/1529547
title: SDR2022

description: Qualitative interviews related to experiences with the nutrients solutions-driven research pilot based out of EPA-ORD-ACESD
DOI: 10.14469/hpc/12988
title: Endo_TS1_G16_PCM_DCM_def2svpp_v_01

description: Kinisot.py command line KIE calculation: "python3 /usr/local/bin/Kinisot.py REACTANT.log TS.log --iso ATOM -t TEMP", where ATOM is number label of transferred proton and TEMP is the temperature (Kelvin)
DOI: 10.14469/hpc/12989
title: Endo_TS1_G16_PCM_DCM_def2svpp_v_01_reactant

description: Gaussian 16 (C01) calculation
DOI: 10.6084/m9.figshare.22442785
title: Dataset of networks used in assessing the Bayan algorithm for community detection

description: This dataset contains a wide range of randomly generated networks (random graphs) from a study on community detection. In total there are 1020 network files. This includes 500 ABCD graphs, 500 LFR graphs, 10 Erdos-Renyi graphs, and 10 Barabasi-Albert graphs as described in the article linked below this description. Each network is provided in .gml format.This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as they provide citations to this data repository (https://doi.org/10.6084/m9.figshare.22442785) and the reference article listed below (http://dx.doi.org/10.48550/arXiv.2209.04562), and license the new creations under the identical terms.For more information about the data, one may refer to the articles below:Aref, Samin, Hriday Chheda, and Mahdi Mostajabdaveh. "The Bayan Algorithm: Detecting Communities in Networks Through Exact and Approximate Optimization of Modularity." <i>arXiv preprint arXiv:2209.04562</i> (2022).Aref, S., Mostajabdaveh, M., Chheda, H. (2023). Heuristic Modularity Maximization Algorithms for Community Detection Rarely Return an Optimal Partition or Anything Similar. In: Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2023. ICCS 2023. Lecture Notes in Computer Science, vol 10476. Springer, Cham. https://doi.org/10.1007/978-3-031-36027-5_48
DOI: 10.6084/m9.figshare.22442785.v3
title: Dataset of networks used in assessing the Bayan algorithm for community detection

description: This dataset contains a range of randomly generated networks (random graphs) from a study on community detection. In total there are 920 network files. This includes 400 ABCD graphs, 500 LFR graphs, 10 Erdos-Renyi graphs, and 10 Barabasi-Albert graphs as described in the article linked below this description. Each network is provided in .gml format. <br> This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as they provide citations to this data repository (https://doi.org/10.6084/m9.figshare.22442785) and the reference article listed below (http://dx.doi.org/10.48550/arXiv.2209.04562), and license the new creations under the identical terms. For more information about the data, one may refer to the article below: Aref, Samin, Hriday Chheda, and Mahdi Mostajabdaveh. "The Bayan Algorithm: Detecting Communities in Networks Through Exact and Approximate Optimization of Modularity." <em>arXiv preprint arXiv:2209.04562</em> (2022).
DOI: 10.25810/558f-c477.65
title: Australian Newspaper Coverage of Climate Change or Global Warming, 2000-2023 - August 2023

description: The Media and Climate Change Observatory Data monitors 126 sources (across newspapers, radio and TV) in 58 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.5281/zenodo.8319399
title: Data from: In situ correlation between microplastic and suspended particulate matter concentrations in river-estuary systems support proxies for satellite-derived estimates of microplastic flux

description: Data from Sullivan et al., (in press) In situ correlation between microplastic and suspended particulate matter concentrations in river-estuary systems support proxies for satellite-derived estimates of microplastic flux, <em>Marine Pollution Bulletin. </em> It contains the summary of the in situ measurements of TSM and microplastic counts and concentrations for each site. For more detail on the methods, users are directed to the methods section 2.2 of the open access paper.
description: This work was funded by ESA contract no. 40000123928/18/I-NB 'SIMPLER: SensIng Marine Plastic Litter using Earth observation in River outflows'. Support from EU Horizon 2020 CERTO (Grant Agreement #870349). We express our sincere thanks to Oban Jones, Georgina Ramm and Gaia Gleratti at PML for their support during field sampling.
DOI: 10.5281/zenodo.8319398
title: Data from: In situ correlation between microplastic and suspended particulate matter concentrations in river-estuary systems support proxies for satellite-derived estimates of microplastic flux

description: Data from Sullivan et al., (in press) In situ correlation between microplastic and suspended particulate matter concentrations in river-estuary systems support proxies for satellite-derived estimates of microplastic flux, <em>Marine Pollution Bulletin. </em> It contains the summary of the in situ measurements of TSM and microplastic counts and concentrations for each site. For more detail on the methods, users are directed to the methods section 2.2 of the open access paper.
description: This work was funded by ESA contract no. 40000123928/18/I-NB 'SIMPLER: SensIng Marine Plastic Litter using Earth observation in River outflows'. Support from EU Horizon 2020 CERTO (Grant Agreement #870349). We express our sincere thanks to Oban Jones, Georgina Ramm and Gaia Gleratti at PML for their support during field sampling.
DOI: 10.5281/zenodo.8367825
title: Initial Conditions for ATOM-COBALT dynamic N:P model simulations in GBC paper

description: Adjustment of standard initial conditions file for COBALT simulations to add dynamic phytoplankton P fields.
DOI: 10.5281/zenodo.8367824
title: Initial Conditions for ATOM-COBALT dynamic N:P model simulations in GBC paper

description: Adjustment of standard initial conditions file for COBALT simulations to add dynamic phytoplankton P fields.
DOI: 10.3886/e183461
title: Data-set - retirement planning

description: This data-set consists of 387 responses
DOI: 10.3886/e183461v1
title: Data-set - retirement planning

description: This data-set consists of 387 responses
DOI: 10.3886/e183461v2
title: Data-set - retirement planning

description: This data-set consists of 387 responses
DOI: 10.15129/d8b31125-23cb-4325-b136-38073dd6a4a6
title: Data for: "Surface Functionalisation of Self-Assembled Quantum Dot Microlasers with a DNA Aptamer"

description: This data relates to an article to be published in the International Journal of Molecular Science. Surface functionalisation of self-assembled colloidal quantum dot supraparticle lasers with a Thrombin Binding Aptamer (TBA-15) has been demonstrated. Data used for creating figures and tables in the manuscript has been compiled into an Excel spreadsheet with separate sheets for each type of data: Size measurements, Fourier Transform Infrared Spectroscopy, Photoluminescence and data for Laser transfer function plots, and Zeta Potential measurements.
DOI: 10.6084/m9.figshare.24171573
title: HistoCAT_Session_Export

description: .csv files exported from HistoCAT
DOI: 10.6084/m9.figshare.24171573.v2
title: HistoCAT_Session_Export

description: .csv files exported from HistoCAT
DOI: 10.6084/m9.figshare.24171573.v1
title: HistoCAT_Session_Export

description: .csv files exported from HistoCAT
DOI: 10.25810/es52-xr23.65
title: Canadian Newspaper Coverage of Climate Change or Global Warming, 2000-2023 - August 2023

description: The Media and Climate Change Observatory Data monitors 126 sources (across newspapers, radio and TV) in 58 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.6084/m9.figshare.24081327
title: Updated readme file for the ALFI dataset

description: Updated readme file for the ALFI dataset; it should substitute the one already uploaded.
DOI: 10.6084/m9.figshare.24081327.v1
title: Updated readme file for the ALFI dataset

description: Updated readme file for the ALFI dataset; it should substitute the one already uploaded.
DOI: 10.25810/3hvn-ef66.35
title: Danish Newspaper Coverage of Climate Change or Global Warming, 2004-2023 - August 2023

description: The Media and Climate Change Observatory Data monitors 126 sources (across newspapers, radio and TV) in 58 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.5517/ccdc.csd.cc284r4b
title: CCDC 2089931: Experimental Crystal Structure Determination

description: Related Article: Sanjit Das,  Fengrui Qu, Elizabeth T. Papish|2021|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fx3q6
title: CCDC 2261348: Experimental Crystal Structure Determination

description: Related Article: Xinyi Song, Min Wang, Wei Liu, Heng Zheng, Carl Redshaw, Xing Feng, Zujin Zhao, Ben Zhong Tang|2023|Dyes Pigm.|219|111532|doi:10.1016/j.dyepig.2023.111532
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fx3r7
title: CCDC 2261349: Experimental Crystal Structure Determination

description: Related Article: Xinyi Song, Min Wang, Wei Liu, Heng Zheng, Carl Redshaw, Xing Feng, Zujin Zhao, Ben Zhong Tang|2023|Dyes Pigm.|219|111532|doi:10.1016/j.dyepig.2023.111532
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34740/kaggle/dsv/6513149
title: Cristiano Ronaldo | All Club Goals