cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3956134
title: The path from schizotypy to depression and aggression and the role of family stress

description: These data accompany the article, Premkumar, P., Kuipers, E., Kumari, V. (2020). The path from schizotypy to depression and aggression and the role of family stress. European Psychiatry. The file titled 'Schizotypy, depression, aggression and perceived EE - data sharing.xls' contains the numerical values of the raw data and the aggregate scores of the following scales, Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE), Depression, Anxiety, and Stress Scale (DASS-21), Level of Expressed Emotion (LEE), Buss and Perry Aggression Questionnaire (BPAQ). The file also contains the median scores of the Affective evaluation of standard criticism and standard praise task and participant demographics. The file titled, 'Schizotypy, depression, aggression and perceived EE - data sharing-labels.xlsx' contains the same data, but presents the value labels instead of the numerical values of the raw data for each scale. The file titled 'Schizotypy, depression, aggression and perceived EE - data sharing.sav' is the same data in an SPSS-compatible format.
DOI: 10.5281/zenodo.3956133
title: The path from schizotypy to depression and aggression and the role of family stress

description: These data accompany the article, Premkumar, P., Kuipers, E., Kumari, V. (2020). The path from schizotypy to depression and aggression and the role of family stress. European Psychiatry. The file titled 'Schizotypy, depression, aggression and perceived EE - data sharing.xls' contains the numerical values of the raw data and the aggregate scores of the following scales, Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE), Depression, Anxiety, and Stress Scale (DASS-21), Level of Expressed Emotion (LEE), Buss and Perry Aggression Questionnaire (BPAQ). The file also contains the median scores of the Affective evaluation of standard criticism and standard praise task and participant demographics. The file titled, 'Schizotypy, depression, aggression and perceived EE - data sharing-labels.xlsx' contains the same data, but presents the value labels instead of the numerical values of the raw data for each scale. The file titled 'Schizotypy, depression, aggression and perceived EE - data sharing.sav' is the same data in an SPSS-compatible format.
DOI: 10.5258/soton/d1354
title: Dataset for: Lensless imaging of pollen grains at three-wavelength using deep learning

description: Data supports the paper: Grant-Jacob, J., Praeger, M., Loxham, M., Eason, R. W., & Mills, B. (2020). Lensless imaging of pollen grains at three-wavelength using deep learning. Environmental Research Communications. DOI: 10.1088/2515-7620/aba6d1
DOI: 10.21227/q163-w472
title: Drivers' Activity Tracking With JINS MEME Smart Glasses

description: This dataset contains the signal recording acquired on vehicle (car) drivers (ten experienced drivers and ten learner drivers) on the same 28.7 km route in the Silesian Voivodeship (in Polish województwo śląskie) in southern Poland. Experienced drivers performed the tasks in their own cars whereas the learner drivers performed the tasks under a supervison of a driving instructor in a specially marked cars (with L sign). The tasks include driving through a freeway (motorway), city traffic in Bytom, Radzionków, Piekary Śląskie, Tarnowskie Góry, driving in residential areas, driving on a roundabout, parking and driving through an intersection.
DOI: 10.21227/y32a-dd44
title: Drivers' Activity Tracking With JINS MEME Smart Glasses

description: This dataset contains the signal recording acquired on vehicle (car) drivers (ten experienced drivers and ten learner drivers) on the same 28.7 km route in the Silesian Voivodeship (in Polish województwo śląskie) in southern Poland. Experienced drivers performed the tasks in their own cars whereas the learner drivers performed the tasks under a supervison of a driving instructor in a specially marked cars (with L sign). The tasks include driving through a freeway (motorway), city traffic in Bytom, Radzionków, Piekary Śląskie, Tarnowskie Góry, driving in residential areas, driving on a roundabout, parking and driving through an intersection.
DOI: 10.5281/zenodo.3560365
title: Large-scale analysis of grooming in modern social networks

description: We provide a large-scale dataset of the messages exchanged publicly by the streamers and viewers during the live broadcasts of users identified as adult content producers from the LiveMe platform, a major Social Live Streaming Service (SLSS). The dataset comprises 39,382,838 chat messages exchanged by 1,428,284 users, in the context of 293,271 live broadcasts during a period of approximately two years, from July 2016 to June 2018. The analysis of this dataset can be found in our paper <strong><em>"Large-scale analysis of grooming in modern social networks" </em></strong>(arXiv:2004.08205 [cs.SI]).
DOI: 10.17029/b36d66d7-67ff-4d70-bf48-0891939806d0
title: Dataset: 'Railway Work, Life & Death: ASRS legal book 1901-1905.'

description: Transcription of the Amalgamated Society of Railway Servants legal case book, covering 1901-1905 and held at the Modern Records Centre, University of Warwick. Produced as part of the Railway Work, Life & Death project, in collaboration with the Modern Records Centre.
DOI: 10.17632/8tdnhhm592
title: Data for: A longitudinal study of blockchain diffusion

description: Interview transcripts
DOI: 10.15132/10000151
title: Using a same-different matching task to determine the viability of parallel lexical processing: Measuring reaction time and error rates.

description: Reaction time and error rate means for each experimental condition averaged over the set of items within the condition (for the by-subjects analysis) and over the subjects tested on that condition (for the by-items analysis). The initial sheet of this Excel document provides instruction on how to read and interpret the layout of the following sheets.
DOI: 10.5281/zenodo.3956090
title: WSCC 9 bus system data set

description: WSCC 9 bus system data set High quality data set for data-driven power system assessment.
DOI: 10.5281/zenodo.3956089
title: WSCC 9 bus system data set

description: WSCC 9 bus system data set High quality data set for data-driven power system assessment.
DOI: 10.21227/mkbr-tb67
title: Data for: "Optimum Device and Modulation Scheme Selection for Optical Wireless Communications"

description: There has been extensive modelling of the optical wireless channel, and the optimum modulation scheme for a particular channel is well-understood. However, this modelling has not taken into account the trade-offs that transmitter and receiver selection usually involve. For a particular type of transmitter, the modulation bandwidth and available power are closely related, as are receiver bandwidth, active area and sensitivity. In this paper, we present a design approach that takes this device selection into account. The paper details a general design method for an optical wireless communication system using a holistic design approach (i.e. considering channel, modulation schemes and device constraints). The paper shows results for particular examples, showing a substantial increase in margin (or data-rate) is available using this approach.For instance, by using this approach, it is found that for an optimally chosen Gallium Nitride micro-LED and a commercial photo receiver pair, a 20 dB SNR margin (or ~3 times data-rate improvement) can be obtained compared with a more standard approach.
DOI: 10.21227/n4at-tc59
title: Data for: "Optimum Device and Modulation Scheme Selection for Optical Wireless Communications"

description: There has been extensive modelling of the optical wireless channel, and the optimum modulation scheme for a particular channel is well-understood. However, this modelling has not taken into account the trade-offs that transmitter and receiver selection usually involve. For a particular type of transmitter, the modulation bandwidth and available power are closely related, as are receiver bandwidth, active area and sensitivity. In this paper, we present a design approach that takes this device selection into account. The paper details a general design method for an optical wireless communication system using a holistic design approach (i.e. considering channel, modulation schemes and device constraints). The paper shows results for particular examples, showing a substantial increase in margin (or data-rate) is available using this approach.For instance, by using this approach, it is found that for an optimally chosen Gallium Nitride micro-LED and a commercial photo receiver pair, a 20 dB SNR margin (or ~3 times data-rate improvement) can be obtained compared with a more standard approach.
DOI: 10.5255/ukda-sn-853374
title: Carers' talk to children with language difficulties during shared book reading and play 2016-2018

description: The aim of this research was to explore whether the advantages of shared book reading (the joint attention and high quality adult language input) remain true where children have language difficulties. We compared parents' input to their young children with language difficulties during shared reading and play activities. Sharing books with young children is potentially an excellent opportunity for language development. The children and adults are jointly focused on the same words and pictures, and the text in children’s books tends to have a more varied vocabulary and more accurate and complex grammar than child-directed speech during play. However, in shared reading interventions, the best results have been shown for children who are already progressing well with spoken communication. Children who are at risk for language development (for example because of a slow start to talking, a family history of problems, or socio-economic disadvantage) have benefited less.
DOI: 10.21227/t9s7-2795
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.+-------------------+--------------------------------------------------+
DOI: 10.21227/8qse-9569
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.-------------------------------------------------------------------------Number of Tweets: 329,834,758 — Global (English)-------------------------------------------------------------------------Coronavirus (COVID-19) Geo-tagged Tweets Dataset(tweets with location information; ongoing collection)------------------------------------------------------------------------- | Number of tweets : 329,834,758 tweets |
DOI: 10.21227/m9ja-ee59
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.Dataset Overview| Number of tweets : 329,834,758 tweets
DOI: 10.5258/soton/d1478
title: Dataset for Sparse Space-Time-Frequency-Domain Spreading for Large-Scale Non-Orthogonal Multiple Access

description: Research data for the paper: Liu, Y., Yang & Hanzo, L., 'Sparse Space-Time-Frequency-Domain Spreading for Large-Scale Non-Orthogonal Multiple Access' in IEEE Transactions on Vehicular Technology
DOI: 10.21227/tn4f-h104
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.Dataset Overview| Number of tweets : 329,834,758 tweets
DOI: 10.21227/whhv-tn56
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.Dataset Overview| Number of tweets : 329,834,758 tweets
DOI: 10.5258/soton/d1461
title: Data and COMSOL files supporting a PhD thesis in multiphysics finite element modelling of superconducting cables

description: The reader will find two types of files - .xlsx (Excel) and .mph (COMSOL versions 5.3-5.5), sorted in folders depending on the section they are relevant to. The names of the files should be self-explanatory. Occasionally there are .mphbin files which contain pre-created geometries for some of the models. These can only be used within COMSOL. The .xlsx files contain all numerical data that can be seen in the Figures throughout the thesis. The COMSOL files are set up and ready to run in order to produce the results that were obtained during the research. Due to the size of the completed simulations, it would have been impractical to retain the solutions - a user should be able to re-simulate with minimal modification to each file. Data must be used and understood in conjunction with the contents of the thesis.
DOI: 10.21227/hanm-kq95
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.Dataset Overview| Number of tweets : 329,834,758 tweets
DOI: 10.21227/v7pf-v956
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).Dataset Overview:| Number of tweets : 148,848 tweets
DOI: 10.17632/jwhgvwdrhf.1
title: Publishing via pipeline

description: An analysis of publishing pipelines
DOI: 10.21227/qnfb-wb45
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).Dataset Overview:| Number of tweets : 148,848 tweets
DOI: 10.21227/qfg1-df54
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.Dataset Overview| Number of tweets : 329,834,758 tweets
DOI: 10.21227/apfc-vg62
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page). Below is the quick overview of this dataset.| Number of tweets : 148,848 tweets
DOI: 10.21227/9hb5-5411
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.5258/soton/d1477
title: Dataset for: Microphone array processing for sparse equivalent source representations of tyre noise

description: Data supports the PhD thesis entitled "Microphone array processing for sparse equivalent source representations of tyre noise", awarded to A Papaioanou, 2020 by the University of Southampton. The data in this file are the raw and post-processed measured data which form the basis of the PhD thesis and were obtained by performing a number of measurements at the Southampton University Signal Processing and Control Lab, the semi-anechoic chamber in Applus IDIADA, Barcelona, Spain and the anechoic chamber in Siemens Digital Industries Software, Leuven, Belgium. To view and use the data, you will need the Matlab Software.
DOI: 10.21227/n6zv-cw60
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.21227/gwtj-3g73
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page). Below is the quick overview of this dataset.| Number of tweets : 148,848 tweets
DOI: 10.21227/sk24-vx82
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets
DOI: 10.5281/zenodo.3956394
title: Journal articles containing the compound term marketer behavior/behaviour

description: This file contains a list of all journal articles found at September 2019 that contain the compound term 'marketer behavior' or 'marketer behaviour'.
DOI: 10.5281/zenodo.3956393
title: Journal articles containing the compound term marketer behavior/behaviour

description: This file contains a list of all journal articles found at September 2019 that contain the compound term 'marketer behavior' or 'marketer behaviour'.
DOI: 10.21227/fray-mk55
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page). Below is the quick overview of this dataset.| Number of tweets : 148,848 tweets
DOI: 10.21227/6fet-9z10
title: Coronavirus (COVID-19) Tweets Dataset

description: This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The tweets have been collected by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using more than 40+ keywords used while referencing the pandemic. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Below is the quick overview of this dataset.| Number of tweets : 329,834,758 tweets