cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5573779
title: PsPM-FSS6B: SCR and PSR measurements in a delay fear conditioning task with somatosensory CS and electrical US

description: This dataset includes skin conductance response (SCR) and pupil size response (PSR) measurements. Also included are CS and US information, keypress responses, keypress response times and key correctness for each of 18 healthy unmedicated participants (10 males and 8 females aged 25.7+/-5.0 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. Simple and complex CS are delivered to the intermediate phalanges of the index and middle fingers of the non-dominant hand. Simple stimuli are stimulations to either index or middle finger, complex stimuli are stimulations of different temporal structure to both index and middle fingers. CS intensity is set to a perceivable but not unpleasant level. US is a train of electric square pulses delivered with a constant current stimulator (Digitimer DS7A, Digitimer, Welwyn Garden City, UK) on participants' dominant forearm through a pin-cathode/ring-anode configuration. SOA between the CS and US is 3.5 s. The ITI is randomly determined on each trial to be 7, 9, or 11 s.
description: Raw data are contained in data.zip and described in readme.txt. Pre-processed data are contained in data_pp.zip and described in readme_pp.txt. Data are stored as .mat files for use with MATLAB (The MathWorks Inc., Natick, USA) in a format readable by the PsPM toolbox (bachlab.org/pspm). All raw data files are saved in MATLAB 9.2 (R2017a) format, and all pre-processed data files are saved in MATLAB 9.6 (R2019a) format. This research was supported by Wellcome Trust grant 091593/Z/10/Z, and Swiss National Science Foundation grant 320030_149586/1. Data pre-processing was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. ERC-2018 CoG-816564 ActionContraThreat).
DOI: 10.5281/zenodo.7108317
title: Dimensionality reduction of local structure in glassy binary mixtures

description: This dataset is associated with "<em>Dimensionality reduction of local structure in glassy binary mixtures</em>", by D. Coslovich, R. L. Jack, J. Paret. It includes data and workflow to allow for the replication of the analysis and figures of the manuscript. To reproduce the workflow and the figures, download and extract the package sprouts.tar.gz, then execute <pre><code class="language-bash">./make all</code></pre> This will create the figures under plots/paper and recompile project.pdf. If the workflow fails because of missing dependencies, read the project.pdf file below and check the requirements, or download the docker image sprouts-docker.tar.gz, load the image and execute the same command within the container. <em>Make sure you have at least 20 Gb of free space on your disk if you use the package, and 22 Gb if you use the docker image.</em> To speed up the execution of the workflow, download the data cache (cache.tar) and extract it at the root of the project folder. See project.pdf below for full details about the workflow. <strong>Changelog</strong>: 1.0.0: initial submission
DOI: 10.6084/m9.figshare.12452615
title: Data used to quantify the life cycle cost, primary energy and greenhouse gas emissions of a net zero life cycle primary energy and greenhouse gas emissions apartment building in a Mediterranean climate

description: This datasets contains all relevant data used to calculate the life cycle cost, primary energy use, and greenhouse gas emissions of a net zero life cycle primary energy and greenhouse gas emissions apartment building in Sehaileh, Lebanon.<br>These data include:<br>→The detailed bill of material quantities of the base case;<br>→The detailed bill of assemblies quantities of the base case;<br>→The detailed life cycle cost calculations for each measure and the net zero life cycle primary energy and greenhouse gas emissions building;<br>→The detailed calculations related to the sensitivity analysis; and<br>→Other relevant data and information.
DOI: 10.5281/zenodo.321641
title: PsPM-HRA1: Skin conductance responses in fear conditioning with visual CS and electrical US

description: This dataset includes skin conductance response (SCR) measurements, CS and US information, keypress responses, keypress response times, key correctness and shock ratings for each of 20 healthy unmedicated participants (10 males and 10 females aged 22.2+/-4.0 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS is a visual stimulus appearing in the middle of the screen with variation in color. US is an electric shock as a 500 Hz current pulses train (individual pulse width: 0.5ms, varying current amplitudes (0.90+/-0.63 mA) train width:500 ms). SOA between the CS and US is 3.5 s. The ITI is randomly determined on each trial to be 7, 8, 9, 10 or 11 s. (This was correctly stated in Staib et al. (2015) but wrongly described in Bach et al. (2010).)
description: See the readme file for more detail. Data are stored as .mat files for use with MATLAB in a format readable by the PsPM toolbox (pspm.sourceforge.net). This research was supported by Wellcome Trust grants 098362/Z/12/Z and 098362/Z/12/Z, and Swiss National Science Foundation grant PA00A-117384.
DOI: 10.5281/zenodo.291445
title: PsPM-SCRV5: Skin conductance responses to auditory oddballs

description: This dataset includes skin conductance response (SCR) measurements, keypress responses and keypress response times for each of 20 healthy unmedicated participants (10 males and 10 females aged 21.8+/-3.3 years) participating in an auditory oddball task with 10 oddballs. The stimuli are delivered every second via headphones as one of two sine tones (50ms length; 10ms ramp; ~75dB; 440 or 660 Hz). Subjects are instructed to press a computer key on hearing the oddball. Oddball tone is balanced across participants. ITI is selected randomly on each trial from 29s, 34s or 39s.
description: See the readme file for more detail. Data are stored as .mat files for use with MATLAB in a format readable by the PsPM toolbox (pspm.sourceforge.net). This research was supported by Wellcome Trust grants 098362/Z/12/Z and 098362/Z/12/Z, and Swiss National Science Foundation grant PA00A-117384.
DOI: 10.5281/zenodo.291448
title: PsPM-SCRV7: Skin conductance responses to white noise sounds in quick succession

description: This dataset includes skin conductance response (SCR) measurements for each of 22 healthy unmedicated participants (11 males and 11 females aged 24.7+/-4.5 years) in response to white noise stimulation (1s length; 10ms ramp; ~85dB) under 5 experimental conditions: single stimuli, double stimuli with ISI of 2.5s, 5.5s or 9s and triple stimuli with ISIs randomly determined to be 2s, 5.5s or 9s.
description: See the readme file for more detail. Data are stored as .mat files for use with MATLAB in a format readable by the PsPM toolbox (pspm.sourceforge.net). This research was supported by Wellcome Trust grants 098362/Z/12/Z and 098362/Z/12/Z, and Swiss National Science Foundation grant PA00A-117384.
DOI: 10.5281/zenodo.291465
title: PsPM-SCRV10: Skin conductance responses to loud sounds, simultanously recorded from palm, fingers and foot

description: This dataset includes skin conductance response (SCR) measurements recorded from 3 locations (see section 'Data files' below) for each of 26 healthy unmedicated participants (12 males and 14 females aged 24.4+/-4.9 years) in response to an auditory stimulus (single white noise bursts, 1s length; 10ms ramp; ~85dB). Participants are asked to press a foot pedal upon hearing a stimulus.
description: See the readme file for more detail. Data are stored as .mat files for use with MATLAB in a format readable by the PsPM toolbox (pspm.sourceforge.net). This research was supported by Wellcome Trust grants 098362/Z/12/Z and 098362/Z/12/Z, and Swiss National Science Foundation grant PA00A-117384.
DOI: 10.5281/zenodo.3233557
title: Data for the study: Comparison of beamformer implementations for MEG source localization

description: This data set is a part of the study 'Comparison of beamformers implementations for MEG source localization'. The dataset includes 64 phantom datasets, 2 human datasets, and 50 simulated datasets. The data also include segmented MRI files from FreeSurfer for MEG phantom (Megin Oy, Helsinki, Finland) and a human subject MRI. It also includes the used versions of the four beamforming packages (MNE-Python, FieldTrip, SPM12(DAiSS), and Brainstorm) and codes used for the analysis.
DOI: 10.5281/zenodo.3885797
title: PsPM-trSP2: SCR measurement in response to neutral IAPS pictures while subjected to auditory distractors

description: This dataset includes skin conductance response (SCR) measurements for each of 61 healthy unmedicated participants (30 males and 31 females, misprinted in Bach et al. 2015, aged 25.7 +/- 4.5 years) in response to the 45 least arousing neutral IAPS pictures, presented for 1 s each in 3 blocks, while listening to regular or random distractor sounds, as described in Bach et al. (2015). Inter stimulus interval was randomly determined as 7.65 s, 9 s, or 10.35 s. Each recording starts with a 2-minute baseline interval.
description: See the readme file for more detail. This work was supported by the Wellcome Trust [RJD, Senior Investigator Award 098362/Z/12/Z] and the Senate of Berlin [RJD, Einstein Fellowship]. The Wellcome Trust Centre for Neuroimaging is supported by core funding from the Wellcome Trust 091593/Z/10/Z.
DOI: 10.5281/zenodo.4000539
title: TweetBLM: A Hate Speech Dataset and Analysis of BlackLivesMatter-related Microblogs on Twitter

description: Collection of BLM related tweets and their corresponding labels of hate speech.
DOI: 10.5281/zenodo.4716840
title: Monthly average air-sea fluxes of O2, CO2, and N2 from Earth System Models

description: Each file contains the monthly average air-sea flux of O2, CO2, or N2. The model and species are specified in the file name. Units are all Tmol/m2 timestep. Latitude and longitude are given as degrees North and East, respectively.
DOI: 10.5281/zenodo.5573723
title: PsPM-DoxMemP: SCR, ECG and respiration measurements in a delay fear conditioning task with visual CS and electrical US.

description: This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times for 20 healthy unmedicated participants (7 males and 13 females aged 26.15+/-4.15 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. CS were a red and a blue rectangle. US consisted of 0.5 s square electric pulses with 0.2 ms duration and 10 Hz frequency. SOA between the CS onset and US was 3.5 s. CS and US co-terminated. The ITI was randomly determined on each trial to be 7, 9, or 11 s.
description: Raw data are contained in data.zip and described in readme.txt. Pre-processed data are contained in data_pp.zip and described in readme_pp.txt. Data are stored as .mat files for use with MATLAB (The MathWorks Inc., Natick, USA) in a format readable by the PsPM toolbox (bachlab.org/pspm). All raw data files are saved in MATLAB 9.2 (R2017a) format, and all pre-processed data files are saved in MATLAB 9.6 (R2019a) format. This research was supported by Wellcome Trust grant 091593/Z/10/Z, and Swiss National Science Foundation grant 320030_149586/1. Data pre-processing was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. ERC-2018 CoG-816564 ActionContraThreat).
DOI: 10.5281/zenodo.5573820
title: PsPM-TC: SCR, ECG, EMG and respiration measurements in a discriminant trace fear conditioning task with visual CS and electrical US.

description: This dataset includes skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information, keypress responses and keypress response times from 18 healthy unmedicated participants (8 males and 10 females aged 23.89+/-2.52 years) participating in a classical (Pavlovian) discriminant trace fear conditioning task. CS were a red and a blue rectangle presented for 3 seconds. US consisted of 0.5 s square electric pulses with 0.2 ms duration and 10 Hz frequency. SOA between the CS onset and US was 4 s. The ITI was randomly determined on each trial to be 7, 9, or 11 s.
description: Raw data are contained in data.zip and described in readme.txt. Pre-processed data are contained in data_pp.zip and described in readme_pp.txt. Data are stored as .mat files for use with MATLAB (The MathWorks Inc., Natick, USA) in a format readable by the PsPM toolbox (bachlab.org/pspm). All raw data files are saved in MATLAB 9.2 (R2017a) format, and all pre-processed data files are saved in MATLAB 9.6 (R2019a) format. This research was supported by Wellcome Trust grant 091593/Z/10/Z, and Swiss National Science Foundation grant 320030_149586/1. Data pre-processing was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. ERC-2018 CoG-816564 ActionContraThreat).
DOI: 10.5281/zenodo.5650832
title: PsPM-FER01: PSR, SCR, ECG and respiration measurements from a discriminant delay fear conditioning task with visual CS and electrical US.

description: This dataset includes pupil size response (PSR), skin conductance response (SCR), electrocardiogram (ECG) and respiration measurements. Also included are CS and US information and shock expectancy ratings at the end of the experiment for 30 healthy unmedicated participants (12 males and 18 females aged 23.9+/-4.4 years) participating in a classical (Pavlovian) discriminant delay fear conditioning task. Fear acquisition consisted of 10 CS- and 32 CS+ trials (16 CSa+/16 CSb+). Half of the CS+ trials were paired with an electric shock. CS were colored triangles (yellow/red/blue). US consisted of a 500 ms train of 250 square pulses with individual pulse width of 0.2 ms. SOA between the CS onset and US was 3.5 seconds. CS and US co-terminated. The ITI was randomly determined as discrete values between 7-11 seconds (mean 9 seconds).
description: Raw data are contained in data.zip and described in readme.txt. Pre-processed data are contained in data_pp.zip and described in readme_pp.txt. Data are stored as .mat files for use with MATLAB (The MathWorks Inc., Natick, USA) in a format readable by the PsPM toolbox (bachlab.org/pspm). All raw data files are saved in MATLAB 9.2 (R2017a) format, and all pre-processed data files are saved in MATLAB 9.6 (R2019a) format. This research was supported by Wellcome Trust grant 091593/Z/10/Z. Data pre-processing was supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No. ERC-2018 CoG-816564 ActionContraThreat)
DOI: 10.5281/zenodo.6635559
title: MonkeyPox2022Tweets: The First Public Twitter Dataset on the 2022 MonkeyPox Outbreak

description: <strong>Please cite the following paper when using this dataset:</strong> Nirmalya Thakur, "MonkeyPox2022Tweets: The First Public Twitter Dataset on the 2022 MonkeyPox Outbreak", Journal of Data (Paper Submitted). The preprint of this paper is available at: https://www.preprints.org/manuscript/202206.0172/v1 <strong>Abstract</strong> The world is currently facing an outbreak of the monkeypox virus, and confirmed cases have been reported from 28 countries. Following a recent “emergency meeting”, the World Health Organization is considering whether the outbreak should be assessed as a “potential public health emergency of international concern” or PHEIC, as was done for the COVID-19 and Ebola outbreaks in the past. During this time, people from all over the world are using social media platforms, such as Twitter, for information seeking and sharing related to the outbreak, as well as for familiarizing themselves with the guidelines and protocols that are being recommended by various policy-making bodies to reduce the spread of the virus. This is resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. Mining this Big Data and compiling it in the form of a dataset can serve a wide range of use-cases and applications such as analysis of public opinions, interests, views, perspectives, attitudes, and sentiment towards this outbreak. Therefore, this work presents MonkeyPox2022Tweets, an open-access dataset of Tweets related to the 2022 monkeypox outbreak that were posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management. <strong>Data Description</strong> The dataset consists of a total of 68,934 tweet IDs of the same number of tweets about monkeypox that were posted on Twitter from 7<sup>th</sup> May 2022 to 11<sup>th</sup> June 2022 (the most recent date at the time of dataset upload). The Tweet IDs are presented in 4 different .txt files based on the timelines of the associated tweets. The following table provides the details of these dataset files. <strong>Filename</strong> <strong>No. of Tweet IDs</strong> <strong>Date Range of the Tweet IDs</strong> TweetIDs_Part1.txt 19718 June 11, 2022 to June 5, 2022 TweetIDs_Part2.txt 17585 June 5, 2022 to May 27, 2022 TweetIDs_Part3.txt 17705 May 27, 2022 to May 21, 2022 TweetIDs_Part4.txt 13926 May 21, 2022 to May 7, 2022 The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used. For hydrating this dataset the Hydrator application (link to download and a step-by-step tutorial on how to use Hydrator) may be used.
DOI: 10.5281/zenodo.6802781
title: Data from: Transcriptomic meta-analysis reveals unannotated long non-coding RNAs related to the immune response in sheep

description: This dataset contains additional files from the manuscript: "Transcriptomic meta-analysis reveals unannotated long non-coding RNAs related to the immune response in sheep". The files included are: - All novel lncRNA transcript annotation GTF file ( lncrnas.gtf ) - High-confidence lncRNA gene annotation GTF file ( lncrnas_evidence.gtf ) - All novel lncRNA transcript annotation GTF file remapped to the ARS-UI_Ramb_v2.0 genome ( lncrnas_remapped_v2.gtf ) - Raw count estimates of the extended annotation ( rawcounts.csv ) - TPM values of the extended annotation ( tpmcounts.csv ) - Supplementary data to the published article (.xlsx, .pdf)
DOI: 10.6084/m9.figshare.13190834
title: Metadata record for: ClimateEU, Scale-free climate normals, historical time series, and future projections for Europe

description: This dataset contains key characteristics about the data described in the Data Descriptor ClimateEU, Scale-free climate normals, historical time series, and future projections for Europe. <br> Contents: <br> 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format <br> <br> <br>
DOI: 10.3886/e144903v1
title: Axios-Ipsos Coronavirus Index, waves 34-48

description: Since the COVID-19 pandemic began, Ipsos has partnered with Axios to release a weekly Coronavirus Index survey. The survey examines Americans' behaviors, perceptions of risk, and attitudes around COVID-19. The data in this project is part of the ongoing Axios-Ipsos Coronavirus Index research project. The first batch of data were uploaded to https://doi.org/10.3886/E129181V1. <br><br> All data is publicly available here: https://www.ipsos.com/en-us/news-polls/axios-ipsos-coronavirus-index
DOI: 10.5281/zenodo.3648686
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: 10.5281/zenodo.4485871
title: Supplementary data for the article: Parental age does not influence offspring telomeres during early life in common gulls (Larus canus)

description: R code and data for generating supplementary figures and tables for the article "Parental age does not influence offspring telomeres during early life in common gulls (Larus canus)"
DOI: 10.5281/zenodo.6628824
title: Microwave-activated gates between a fluxonium and a transmon qubit

description: Numerical data and figures generators for the paper A. Ciani, B. Varbanov, N. Jolly, C. Andersen, B. Terhal "Microwave-activated gates between a fluxonium and a transmon qubit"
DOI: 10.17861/b17e30f3-a063-433d-802f-16fb5496af4b
title: Time-division technique for quantum optical receivers utilizing single-photon detector array technology and spatial-multiplexing
DOI: 10.21227/4zdn-qe46
title: Synthetic dataset for mobile wireless networks with SUMO -- individual files

description: This dataset contains individual traces of a published synthetic dataset generator for wireless mobile networks using SUMO. The generated dataset is done with the map of the city of Berlin as base. The dataset has 21 cells of 7 base stations. Separate files were generated for traffic and radio signal quality, but can be joined by using the UE identifier.
DOI: 10.5281/zenodo.1227272
title: Amber Lipid17 Simulations Of Popc/Pops Membranes With Nacl

description: <strong>System: </strong>Simulations of POPC/POPS (5:1, 144 lipids in total) membranes with 500, 1000, 2000, 3000, and 4000 mM of NaCl.

<strong>Number of POPS:</strong> 24.

<strong>Number of POPC</strong> 120.

<strong>Number of waters:</strong> 5760.

<strong>Lipid model:</strong> Amber Lipid 17 [IR Gould, AA Skjevik, CJ Dickson, BD Madej, RC Walker: "Lipid17: A Comprehensive AMBER Force Field for the Simulation of Zwitterionic and Anionic Lipids" in prep. (2018)].

<strong>Ion models: </strong> Amber ff99 [J Åqvist <em>J. Phys. Chem.</em> <strong>94</strong> 8021 (1990)].

<strong>Water model:</strong> TIP3P [WL Jorgensen, J Chandrasekhar, JD Madura, RW Impey, ML Klein <em>J. Chem. Phys.</em> <strong>79</strong> 926 (1983)].

<strong>Simulation engine:</strong> Amber16 [DA Case et al. <em>AMBER 2017</em> UCSF (2017)].

<strong>Number of independent repeats per setup: </strong>1.<br>
<strong>Trajectory lengths per repeat:</strong> 200 ns.<br>
<strong>Previously equilibrated for:</strong> 100 ns.<br>
<strong>Sampling rate:</strong> every 10 ps.

<strong>Time integration step:</strong> 2 fs.

<strong>Thermodynamic ensemble:</strong> NpT. <br>
<strong>Temperature coupling:</strong> 'Langevin' at T = 298 K.<br>
<strong>Pressure coupling: '</strong>Berendsen' [<em>J. Chem. Phys.</em> <strong>81</strong> 3684 (1984); <em>J. Chem. Phys.</em> <strong>103</strong> 10252 (1995)] with xy and z coupled separately at p = 1.0 bar with no surface tension.

<strong>Electrostatics: </strong>PME [<em>J. Chem. Phys.</em> <strong>98</strong> 10089 (1993);<em> J. Chem. Theory Comput.</em> <strong>9</strong> 3878 (2013)].<br>
<strong>Van der Waals:</strong> Turned off between 1.0 nm and 1.5 nm.

<strong>Constraints: </strong>Lengths of covalent bonds involving Hydrogens in lipids using SHAKE [<em>J. Comput. Phys.</em> <strong>23</strong> 327 (1977)], in water using SETTLE [<em>J. Comput. Chem. </em><strong>13</strong> 952 (1992)].

<strong>Used in publications: </strong>OHS Ollila et al. "NMRlipids IV: Headgroup & glycerol backbone structures, and cation binding in bilayers with PS lipids" in prep (2018).
description: B.K acknowledges financial support from International Max Planck Research School on Multiscale Bio-Systems