cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3635402
title: Measurement of Absolute Retinal Blood Flow Using a Laser Doppler Velocimeter Combined with Adaptive Optics

description: <strong>Data set of measurements related to the following:</strong> <strong>Purpose: </strong>Development and validation of an absolute laser Doppler velocimeter (LDV) based on an adaptive optical fundus camera which provides simultaneously high definition images of the fundus vessels and absolute maximal red blood cells (RBCs) velocity in order to calculate the absolute retinal blood flow. <strong>Methods: </strong>This new absolute laser Doppler velocimeter is combined with the adaptive optics fundus camera (rtx1, Imagine Eyes©,Orsay, France) outside its optical wavefront correction path. A 4 seconds recording includes 40 images, each synchronized with two Doppler shift power spectra. Image analysis provides the vessel diameter close to the probing beam and the velocity of the RBCs in the vessels are extracted from the Doppler spectral analysis. Combination of those values gives an average of the absolute retinal blood flow. An in vitro experiment consisting of latex microspheres flowing in water through a glass-capillary to simulate a blood vessel and in vivo measurements on six healthy human retinal venous junctions were done to assess the device. <strong>Results: </strong>In the in vitro experiment, the calculated flow varied between 1.75 μl/min and 25.9 μl/min and was highly correlated (r2 = 0.995) with the imposed flow by a syringe pump. In the in vivo experiment, the error between the flow in the parent vessel and the sum of the flow in the daughter vessels was between −25% and 17% (mean±sd −2 ± 17%). Retinal blood flow in the main temporal retinal veins of healthy subjects varied between 1.3 μL/min and 28.7 μL/min <strong>Conclusion: </strong>This adaptive optics LDV prototype (aoLDV) allows the measurement of absolute retinal blood flow derived from the retinal vessel diameter and the maximum RBCs velocity in that vessel.
description: Data set consists of images done with the rtx1 and simultaneous Doppler spectra of two channel.
DOI: 10.5281/zenodo.3635401
title: Measurement of Absolute Retinal Blood Flow Using a Laser Doppler Velocimeter Combined with Adaptive Optics

description: <strong>Data set of measurements related to the following:</strong> <strong>Purpose: </strong>Development and validation of an absolute laser Doppler velocimeter (LDV) based on an adaptive optical fundus camera which provides simultaneously high definition images of the fundus vessels and absolute maximal red blood cells (RBCs) velocity in order to calculate the absolute retinal blood flow. <strong>Methods: </strong>This new absolute laser Doppler velocimeter is combined with the adaptive optics fundus camera (rtx1, Imagine Eyes©,Orsay, France) outside its optical wavefront correction path. A 4 seconds recording includes 40 images, each synchronized with two Doppler shift power spectra. Image analysis provides the vessel diameter close to the probing beam and the velocity of the RBCs in the vessels are extracted from the Doppler spectral analysis. Combination of those values gives an average of the absolute retinal blood flow. An in vitro experiment consisting of latex microspheres flowing in water through a glass-capillary to simulate a blood vessel and in vivo measurements on six healthy human retinal venous junctions were done to assess the device. <strong>Results: </strong>In the in vitro experiment, the calculated flow varied between 1.75 μl/min and 25.9 μl/min and was highly correlated (r2 = 0.995) with the imposed flow by a syringe pump. In the in vivo experiment, the error between the flow in the parent vessel and the sum of the flow in the daughter vessels was between −25% and 17% (mean±sd −2 ± 17%). Retinal blood flow in the main temporal retinal veins of healthy subjects varied between 1.3 μL/min and 28.7 μL/min <strong>Conclusion: </strong>This adaptive optics LDV prototype (aoLDV) allows the measurement of absolute retinal blood flow derived from the retinal vessel diameter and the maximum RBCs velocity in that vessel.
description: Data set consists of images done with the rtx1 and simultaneous Doppler spectra of two channel.
DOI: 10.5519/qd.loyllnp3
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (253 records)
DOI: 10.5519/qd.4noj3b0g
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (58 records)
DOI: 10.5281/zenodo.3648083
title: GitHub developer behavior and repository evolution dataset

description: In this work, based on GitHub Archive project and repository mining tools, we process all available data into concise and structured format to generate GitHub developer behavior and repository evolution dataset. With the self-configurable interactive analysis tool provided by us, it will give us a macroscopic view of open source ecosystem evolution.
DOI: 10.5281/zenodo.3648084
title: GitHub developer behavior and repository evolution dataset

description: In this work, based on GitHub Archive project and repository mining tools, we process all available data into concise and structured format to generate GitHub developer behavior and repository evolution dataset. With the self-configurable interactive analysis tool provided by us, it will give us a macroscopic view of open source ecosystem evolution.
DOI: 10.15468/7gua4s
title: The larva of Rhyacophila hartigi Malicky 1971, including a discriminatory matrix to the Italian Rhyacophila larvae with tufted multifilament gills (Rhyacophilidae, Trichoptera)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Waringer, Johann, Malicky, Hans (2020): The larva of Rhyacophila hartigi Malicky 1971, including a discriminatory matrix to the Italian Rhyacophila larvae with tufted multifilament gills (Rhyacophilidae, Trichoptera). Zootaxa 4731 (1): 103-114, DOI: https://doi.org/10.11646/zootaxa.4731.1.7
DOI: 10.5281/zenodo.3634768
title: MD snapshots: Potassium channel blocker crafted by ɑ-hairpinin scaffold engineering

description: Snapshots of molecular dynamics (MD) simulations of 25 complexes of Kv1.3 channel with a series of Tk-hefu peptide analogues (25 different peptides). Each system include solvated lipid bilayer, the channel and the peptide at 0 (before MD) and 110 ns (after MD). Files are in *.gro format. Additionally, this data set includes two excel tables (*.xlsx) with analysis of intermolecular contacts between the channel and the peptides for all systems in dynamics. These are the same supplementary tables that are uploaded as Supplementary information to <em>Frontiers in chemistry</em> website.
DOI: 10.5281/zenodo.3634769
title: MD snapshots: Potassium channel blocker crafted by ɑ-hairpinin scaffold engineering

description: Snapshots of molecular dynamics (MD) simulations of 25 complexes of Kv1.3 channel with a series of Tk-hefu peptide analogues (25 different peptides). Each system include solvated lipid bilayer, the channel and the peptide at 0 (before MD) and 110 ns (after MD). Files are in *.gro format. Additionally, this data set includes two excel tables (*.xlsx) with analysis of intermolecular contacts between the channel and the peptides for all systems in dynamics. These are the same supplementary tables that are uploaded as Supplementary information to <em>Frontiers in chemistry</em> website.
DOI: 10.5281/zenodo.3647655
title: Utah Open Data - D4 Evaluation Datasets

description: State of Utah data used for the evaluation of our data-driven domain discovery algorithm (D4). This repository contains 1766 tables that were downloaded on 2019-09-27 from the Socrata Open Data API.
DOI: 10.5281/zenodo.3647656
title: Utah Open Data - D4 Evaluation Datasets

description: State of Utah data used for the evaluation of our data-driven domain discovery algorithm (D4). This repository contains 1766 tables that were downloaded on 2019-09-27 from the Socrata Open Data API.
DOI: 10.5281/zenodo.3648126
title: Dataset for "Terahertz Absorption-Saturation and Emission in Electron-doped Germanium Quantum Wells"

description: Raw data acquired during beamtime at the FELBE FEL light source discussed in C. Ciano, M. Virgilio, L. Bagolini, L. Baldassarre, A. Pashkin,<sup> </sup>M. Helm, M. Montanari, L. Persichetti, L. Di Gaspare,<sup> </sup>G. Capellini, D. J. Paul, G. Scalari, J. Faist, M. De Seta, and M. Ortolani, "Terahertz Absorption-Saturation and Emission in Electron-doped Germanium Quantum Wells", Optics Express
DOI: 10.5281/zenodo.3647915
title: Multi-Objective Design of Actuators: Pareto fronts

description: These are the best-known Pareto fronts for the 20 MODAct benchmark problems. Files are text files where each row is a point and each column an objective. Associated publication is under review.
DOI: 10.5281/zenodo.3647916
title: Multi-Objective Design of Actuators: Pareto fronts

description: These are the best-known Pareto fronts for the 20 MODAct benchmark problems. Files are text files where each row is a point and each column an objective. Associated publication is under review.
DOI: 10.5281/zenodo.3648125
title: Dataset for "Terahertz Absorption-Saturation and Emission in Electron-doped Germanium Quantum Wells"

description: Raw data acquired during beamtime at the FELBE FEL light source discussed in C. Ciano, M. Virgilio, L. Bagolini, L. Baldassarre, A. Pashkin,<sup> </sup>M. Helm, M. Montanari, L. Persichetti, L. Di Gaspare,<sup> </sup>G. Capellini, D. J. Paul, G. Scalari, J. Faist, M. De Seta, and M. Ortolani, "Terahertz Absorption-Saturation and Emission in Electron-doped Germanium Quantum Wells", Optics Express
DOI: 10.15468/0qy1ii
title: Review of Parachinavia ROCHE (Hemiptera, Pentatomidae, Pentatominae)

description: This dataset contains the digitized treatments in Plazi based on the original book chapter Grazia, J., Schwertner, C. F. (2008): Review of Parachinavia ROCHE (Hemiptera, Pentatomidae, Pentatominae). In: Grozeva, S., Simov, N. (Eds): Advances in Heteroptera Research. Moscow: Pensoft Publishers: 111-121, DOI: http://doi.org/10.5281/zenodo.3648246
DOI: 10.5519/qd.kr1ocf9t
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4504231 records)
DOI: 10.15129/71c49b70-5e93-4413-b769-44fa1b304547
title: Replication data for: "Trigger Happy?: Military Regimes and the Timing of Conflict"

description: Replication data for: Trigger Happy: Military Regimes and the Timing of Conflict
DOI: 10.15129/90018b58-ef89-4a39-94e8-68e1824605f5
title: Replication data for: "Human Rights and Democratic Arms Transfers: Rhetoric Versus Reality with Different Types of Major Weapon Systems"

description: Replication data for: Human Rights and Democratic Arms Transfers: Rhetoric Versus Reality with Different Types of Major Weapon Systems
DOI: 10.6084/m9.figshare.9124070
title: Data from Kärkkäinen et al. 2020 J Avian Biol 'Correlation in telomere lengths between feathers and blood cells in pied flycatchers'

description: Dataset used in 'Kärkkäinen et al. 2020 'Correlation in telomere lengths between feathers and blood cells<br>in pied flycatchers'. Info on Age class, Sex, bird ID, tissue type (blood vs. feathers) and relative telomere length (T/S ratio) measured using qPCR<br>
DOI: 10.6084/m9.figshare.9124070.v1
title: Data from Kärkkäinen et al. 2020 J Avian Biol 'Correlation in telomere lengths between feathers and blood cells in pied flycatchers'

description: Dataset used in 'Kärkkäinen et al. 2020 'Correlation in telomere lengths between feathers and blood cells<br>in pied flycatchers'. Info on Age class, Sex, bird ID, tissue type (blood vs. feathers) and relative telomere length (T/S ratio) measured using qPCR<br>
DOI: 10.15129/389a80f5-094d-4346-b6be-a503b3f7c55d
title: Replication data for: "Politics and Parasite: The Contribution of Corruption to Human Misery"

description: Replication data for: Politics and Parasite: The Contribution of Corruption to Human Misery
DOI: 10.25573/data.11774589
title: Color Rocks North East and South of Lander Sol 14 D_LRGB_0014_RAS030100CYL_R__SCIPANQM1.jpg

description: InSight Mosaics and Rock Classification and Figures
DOI: 10.5281/zenodo.3648280
title: A comparison of compiler strategies for serverless functions written in Kotlin - dataset

description: The result from the reaseach one for the thesis paper "A comparison of compiler strategies for serverless functions written in Kotlin".
DOI: 10.5281/zenodo.3648281
title: A comparison of compiler strategies for serverless functions written in Kotlin - dataset

description: The result from the reaseach one for the thesis paper "A comparison of compiler strategies for serverless functions written in Kotlin".
DOI: 10.25573/data.11774589.v1
title: Color Rocks North East and South of Lander Sol 14 D_LRGB_0014_RAS030100CYL_R__SCIPANQM1.jpg

description: InSight Mosaics and Rock Classification and Figures
DOI: 10.18112/openneuro.ds002158.v1.0.1
title: Simultaneous eeg-fmri for a speeded discrimination task with confidence
DOI: 10.5284/1059008
title: East Berkshire Historic Landscape Characterisation (HLC)

description: The East Berkshire Historic Landscape Characterisation (HLC) project, was funded by Historic England and undertaken by Berkshire Archaeology. The database and linked GIS form part of the Berkshire Archaeology Historic Environment Record, and the project report, which discusses the methodology used and presents the results and conclusions, is available for download. The project covers the unitary authorities of Reading, Windsor & Maidenhead, Bracknell Forest, Slough and Wokingham, and was completed in 2019.
DOI: 10.25790/bml0cm.59
title: An in vivo 7T Probabilistic Atlas of the Human Locus Coeruleus
DOI: 10.5281/zenodo.3648094
title: Jira Monitoring Data February 2017

description: This is the first of four datasets that our research "Comparing Static and Dynamic Weighted Software Coupling Metrics" published in https://doi.org/10.1007/978-3-030-30275-7_22 is based on. This dataset contains the monitoring data from our installation of Atlassian Jira, from February 2017.
DOI: 10.5281/zenodo.3648243
title: MAC Dataset

description: This dataset consist prediction of many models of the RSNA Intracranial Hemorrhage Detection Kaggle challenge. These predictions are used as a test case for the MAC framework. There are two files:<br> train.tar.gz: prediction of 310 models on the stage 2 training dataset of the challenge. <br> test.tar.gz: prediction of 460 models on the stage 2 test dataset of the challenge. The labels of the train dataset are located on the Kaggle challenge page.
DOI: 10.5281/zenodo.3648244
title: MAC Dataset

description: This dataset consist prediction of many models of the RSNA Intracranial Hemorrhage Detection Kaggle challenge. These predictions are used as a test case for the MAC framework. There are two files:<br> train.tar.gz: prediction of 310 models on the stage 2 training dataset of the challenge. <br> test.tar.gz: prediction of 460 models on the stage 2 test dataset of the challenge. The labels of the train dataset are located on the Kaggle challenge page.
DOI: 10.5281/zenodo.3618204
title: Selective auditory attention in normal-hearing and hearing-impaired listeners

description: This repository contains the EEG and behavioral data described in: Fuglsang, S A, Märcher-Rørsted, J, Dau, T, Hjortkjær, J (2020). Effects of sensorineural hearing loss on cortical synchronization to competing speech during selective attention. Journal of Neuroscience, 40(12):2562–2572, https://doi.org/10.1523/JNEUROSCI.1936-19.2020 Please cite this paper when using the data The data set consists of response data for 22 hearing-impaired and 22 normal-hearing participants. It includes:<br> - EEG data: responses to two-talker and single-talker speech stimuli<br> - Envelopes of the corresponding speech audio<br> - EEG data: responses to 1 kHz tone beeps for ERPs<br> - EEG data: responses to periodic tone sequences for Envelope-following responses (EFRs)<br> - EEG resting-state data recorded with eyes-open and eyes-closed<br> - inEar EEG data for 19 of the 44 subjects (EEG recorded inside the ear canals)<br> - Behavioral data: speech comprehension scores, task difficulty ratings, speech-in-noise scores (SRTs), tone-in-noise scores, digit span working memory scores, SSQ questionnaire ratings<br> - Pure-tone audiograms For more information, see the README and 'dataset_description.json' file. <br> Format<br> ------<br> The dataset is formatted according to BIDS version 1.3.0 and the BIDS standard extension for EEG (BEP006) that has been merged in the main body of the specification. For more details, see https://bids-specification.readthedocs.io/en/latest/06-extensions.html Behavioural data are stored in the 'participants.tsv' file. Task-difficulty ratings and multiple choice questionnaire data from the selective attention experiment are stored in the events files (see 'task-selectiveattention_events.json'). Code<br> ------<br> Code for analyzing the data is available at: https://gitlab.com/sfugl/snhl Audio<br> ------<br> Envelopes of the audio signals are included in the data set. For inquiries regarding the raw audio data, please send an email to jensh@drcmr.dk with the subject line "ds-eeg-snhl audio". Acknowledgments<br> ----------<br> This work was supported by the EU H2020-ICT grant number 644732 (COCOHA: Cognitive Control of a Hearing Aid) and by the Novo Nordisk Foundation synergy grant NNF17OC0027872 (UHeal). The EarEEG were kindly provided by Eriksholm Research Centre.
description: This work was supported by the EU H2020-ICT grant number 644732 (COCOHA: Cognitive Control of a Hearing Aid) and by the Novo Nordisk Foundation synergy grant NNF17OC0027872 (UHeal).
DOI: 10.5281/zenodo.3648093
title: Jira Monitoring Data February 2017

description: This is the first of four datasets that our research "Comparing Static and Dynamic Weighted Software Coupling Metrics" published in https://doi.org/10.1007/978-3-030-30275-7_22 is based on. This dataset contains the monitoring data from our installation of Atlassian Jira, from February 2017.
DOI: 10.5281/zenodo.3648685
title: Dataset: Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

description: This package contains the instance data used for the experiments presented in the paper <em>Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems</em>, by Alinson S. Xavier, Feng Qiu and Shabbir Ahmed.
DOI: 10.5519/qd.z8pb50y9
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1572732 records)
DOI: 10.25345/c52t25
title: MassIVE MSV000084913 - GC_GNPS_ICL_turorial_20_files_subset
title: Test dataset comprises of 20 files of ICL study of breath metabolites of OGC
DOI: 10.25345/c56h42
title: MassIVE MSV000084912 - GC_GNPS_workshop_test_data_breath_samples_cancer_patients
title: Toy dataset for a workshop on GNPS at Imperial College London, UK. Breadth samples for early diagnose of gastric/oesophageal cancer
DOI: 10.25345/c5b97c
title: MassIVE MSV000084910 - GC_GNPS_ICL_tutorial_20_files_subset_of_the_full_dataset
title: Test dataset comprised of 20 files from ICL study of breathomics of OGC.
DOI: 10.25345/c5g106
title: MassIVE MSV000084911 - GC_GNPS_CL _tutorial FILES_SUBSET
title: Test dataset comprised of 20 files from ICL of breathomics of OGC.
DOI: 10.5281/zenodo.3648227
title: Jira Monitoring Data September 2017

description: <pre>This is the second of four datasets that our research "Comparing Static and Dynamic Weighted Software Coupling Metrics" published in https://doi.org/10.1007/978-3-030-30275-7_22 is based on. This dataset contains the monitoring data from our installation of Atlassian Jira, from September 2017. </pre>
DOI: 10.5281/zenodo.3648228
title: Jira Monitoring Data September 2017

description: <pre>This is the second of four datasets that our research "Comparing Static and Dynamic Weighted Software Coupling Metrics" published in https://doi.org/10.1007/978-3-030-30275-7_22 is based on. This dataset contains the monitoring data from our installation of Atlassian Jira, from September 2017. </pre>
DOI: 10.25345/c5jt48
title: MassIVE MSV000084917 - GC_GNPS_ICL_tutorial_20_files_submit_of_the_full_dataset
title: Test dataset of GC-MS breath analysis in cancer OGC in ICL
DOI: 10.25345/c5ph4d
title: MassIVE MSV000084915 - GC_GNPS_ICL_tutorial_20_files_subset_of_full_dataset
title: Test dataset of 20 files from ICL study of breathomics of OGC
DOI: 10.25345/c5t983
title: MassIVE MSV000084916 - GC_GNPS_ICL_tutorial_20_files_subset_of_the_full_dataset
title: Test dataset comprised of 20 files from ICL study of breathomics of OGC.
DOI: 10.25345/c5z09m
title: MassIVE MSV000084914 - GC_GNPS_TUTORIAL_20Files_Subset
title: Test data set comprised of 20 files from Imperial College London study of breathonomics of OG cancer.
DOI: 10.5281/zenodo.3648239
title: Jira Monitoring Data February 2018

description: <pre>This is the third of four datasets that our research "Comparing Static and Dynamic Weighted Software Coupling Metrics" published in https://doi.org/10.1007/978-3-030-30275-7_22 is based on. This dataset contains the monitoring data from our installation of Atlassian Jira, from February 2018.</pre>
DOI: 10.5281/zenodo.3648240
title: Jira Monitoring Data February 2018

description: <pre>This is the third of four datasets that our research "Comparing Static and Dynamic Weighted Software Coupling Metrics" published in https://doi.org/10.1007/978-3-030-30275-7_22 is based on. This dataset contains the monitoring data from our installation of Atlassian Jira, from February 2018.</pre>
DOI: 10.25345/c51t37
title: MassIVE MSV000084921 - GC_GNPS_ICL_tutorial_files_subset_of_the_full_dataset
title: Test dataset comprised of 20 files from ICL study of breahomics of OGC
DOI: 10.25345/c55h54
title: MassIVE MSV000084922 - GC_GNPS_ICL_tutorial_Workshop_06Feb2020
title: Test dataset- GNPS workshop ICL 6th Feb 2020. Breath VOCs of OG Cancer
DOI: 10.25345/c5998f
title: MassIVE MSV000084920 - GC_GNPS_ICL_tutorial_GengpingLin06Feb2020
title: Demo dataset this is for GNPS workshop use only. further data analysis would be required for COBRA data
DOI: 10.25345/c5f10w
title: MassIVE MSV000084918 - GC_GNPS_ICL_tutorial_cris_wtflooooong
title: Test dataset comprised of 20 files from ICL study of breathomics of OGC.
DOI: 10.25345/c5ht26
title: MassIVE MSV000084919 - Sara data 06022020 why cant i dothis crap
title: Sara Dataset of 20 files from GC-MS analysismorecharachtersmorecharactercsetccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
DOI: 10.25345/c5nh5g
title: MassIVE MSV000084925 - GNPSworkshop_IC_GCMSdataset_20files_06022020
title: test dataset compried of 20 files from ICL study of breathomics of OGC
DOI: 10.25345/c5s97d
title: MassIVE MSV000084924 - Workshop-2020-Febr6-set111111111111111111111
title: miko', thi si where you would put your descriotion if you have real data
DOI: 10.25345/c5x11m
title: MassIVE MSV000084923 - GC_GNPS_ICL_tutorialPT_files_subset_of_ullll
title: test dataset of 20 files from ICL, std of breathomics of OGC PT.
DOI: 10.25345/c50t2j
title: MassIVE MSV000084929 - GC_breathomics_ImperialCollegeLondon_tutorial
title: Test datasets of 20 breath samples analysed by breathomics GC-MS.
DOI: 10.25345/c54m5v
title: MassIVE MSV000084926 - GC_GNPS_ICL_tutorial_20_files_subset_of_the_full_dataset
title: Test dataset comprised of 20 files from ICL study of breathomics of OGC.
DOI: 10.25345/c5896c
title: MassIVE MSV000084927 - GC_GNPS_ICL_DemoData_Jan2020_moreStuff50Charactersplus
title: Demo data for GC-MS GNPS tutorial January 2020 further description of dataset etc etc
DOI: 10.25345/c5d39p
title: MassIVE MSV000084928 - GC_GNPS_ICL_tutorial_HK_blah_blah
title: test data set test data set test data set test data set test data set test data set test data set
DOI: 10.25850/nioz/7b.b.x/40qy9j
title: Weiss et al. Table 1.csv
DOI: 10.25850/nioz/7b.b.x/kwxsl1
title: Weiss et al. (2020) - G. Cubed.txt
DOI: 10.25850/nioz/7b.b.x/sg3bwb
title: Weiss et al. Supp. Table 1.csv
DOI: 10.25850/nioz/7b.b.w/eknwcw
title: config_Cascabel.yaml
DOI: 10.25850/nioz/7b.b.w/iwjghp
title: generate_OTUs.sh
DOI: 10.25850/nioz/7b.b.w/jin4ir
title: vis12S_NIOZ_eDNA.arb
DOI: 10.25850/nioz/7b.b.w/jjj0c7
title: vis12S_NIOZ_eDNA.ARF