cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1356072
title: Goldsmiths RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Goldsmiths, University of London from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356069
title: Edinburgh Napier University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Edinburgh Napier University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356069.v1
title: Edinburgh Napier University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Edinburgh Napier University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356070.v1
title: University of Edinburgh RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by the University of Edinburgh from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122 The original version is available here: http://figshare.com/articles/University_of_Edinburgh_RCUK_Gold_Open_Access_APC_data_2013_14_/1146256 This version has been reformatted into Jisc's standard template.
DOI: 10.6084/m9.figshare.1356072.v1
title: Goldsmiths RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Goldsmiths, University of London from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356073.v1
title: Lancaster University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Lancaster University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356066
title: De Monfort University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by De Montfort University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356068
title: University of Cambridge RCUK APCs 2014

description: This dataset contains details of the article processing charges (APCs) paid by the University of Cambridge from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122 See also: http://figshare.com/articles/Cambridge_APC_payments_for_RCUK_2013_14/987118
DOI: 10.6084/m9.figshare.1356065
title: University of Birmingham RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by the University of Birmingham from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356066.v1
title: De Monfort University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by De Montfort University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356067
title: Durham University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Durham University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122 The original version is available at: http://dx.doi.org/10.6084/m9.figshare.1166616 This version has been converted into Jisc's standard template for APC reporting.
DOI: 10.6084/m9.figshare.1356063
title: Aston University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Aston University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356064
title: University of Bristol RCUK APCs 2013-14, v2

description: This dataset contains details of the article processing charges (APCs) paid by the University of Bristol from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122 The original version is available at: http://figshare.com/articles/University_of_Bristol_RCUK_APCs_2013_14/1202158 This version has been converted into Jisc's standard format for APC reporting.
DOI: 10.6084/m9.figshare.1356065.v1
title: University of Birmingham RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by the University of Birmingham from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356068.v1
title: University of Cambridge RCUK APCs 2014

description: This dataset contains details of the article processing charges (APCs) paid by the University of Cambridge from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122 See also: http://figshare.com/articles/Cambridge_APC_payments_for_RCUK_2013_14/987118
DOI: 10.6084/m9.figshare.1356062
title: Analyzing the Descending Flight of the Germanwings A320 4U9525

description: Something (on 2015-03-26, 10:00 still unknown) caused 4U9525 to descent. All the rest is the automatic reaction of a properly functioning Airbus A320 to these initial conditions: The aircraft is disengaging the autopilot automatically at a Mach number of 0.82 as a consequence of High Speed Protection and follows a subsequent descending flight in manual mode (with normal Fly-by-Wire flight control laws) and idle thrust. The pilots probably are neither touching the side sticks nor the thrust levers. At least, it does not need any pilot intervention to explain the cause of the last 9 minutes of the flight and the final tragic effect.
DOI: 10.6084/m9.figshare.1356067.v1
title: Durham University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Durham University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122 The original version is available at: http://dx.doi.org/10.6084/m9.figshare.1166616 This version has been converted into Jisc's standard template for APC reporting.
DOI: 10.6084/m9.figshare.1356061
title: Analyzing the Descending Flight of the Germanwings A320 4U9525

description: Something (on 2015-03-26, 10:00 still unknown) caused 4U9525 to descent. All the rest is the automatic reaction of a properly functioning Airbus A320 to these initial conditions: The aircraft is disengaging the autopilot automatically at a Mach number of 0.82 as a consequence of High Speed Protection and follows a subsequent descending flight in manual mode (with normal Fly-by-Wire flight control laws) and idle thrust. The pilots probably are neither touching the side sticks nor the thrust levers. At least, it does not need any pilot intervention to explain the cause of the last 9 minutes of the flight and the final tragic effect.
DOI: 10.6084/m9.figshare.1356064.v1
title: University of Bristol RCUK APCs 2013-14, v2

description: This dataset contains details of the article processing charges (APCs) paid by the University of Bristol from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122 The original version is available at: http://figshare.com/articles/University_of_Bristol_RCUK_APCs_2013_14/1202158 This version has been converted into Jisc's standard format for APC reporting.
DOI: 10.6084/m9.figshare.1356059
title: Data from 'Linear tuning of gamma amplitude and frequency to luminance contrast: evidence from a continuous mapping paradigm', Perry et al. (2015) PLoS ONE

description: The accompanying data is the data created for the study: 'Linear tuning of gamma amplitude and frequency to luminance contrast: evidence from a continuous mapping paradigm', Perry et al. (2015) PloS ONE. For methods used to generate the data see that paper. The file tuning_data.csv contains contrast tuning data for each participant. Row 1 gives Michelson contrast in %. Rows 2-15 give the amplitude of gamma (in % relative to baseline) at the corresponding contrast for each participant (column 1 gives participant number). Rows 16-29 gives the frequency (in Hz) of gamma for the corresponding contrast. These are the data plotted in the central and right-hand panels of Fig. 2. virtual_sensor_participant_x.csv contains the virtual sensor timeseries for participant x (using the same numbering as Fig. 2). Column one gives time (in ms relative to stimulus onset). Subsequenct columns give the virtual sensor data for each trial (trials containing artefacts have been removed). bertogram8_participant_x.csv contains the time-frequency 'bertogram' for participant x. This is the time-frequency data plotted in Fig. 2 and used for analysing the amplitude tuning. Column 1 gives time relative to stimulus onset (in ms), row 1 gives frequency (in Hz), other columns/rows give data at the corresponding time and frequency as % amplitude relative to baseline. Date were generated using an 8Hz bandpass at each frequency. bertogram1_participant_x.csv contains the time-frequency 'bertogram' for participant x generated using 1Hz bandpass at each frequency. This was the data used for analysing frequency tuning. File layout is identical to bertogram8_participant_x.csv.
DOI: 10.6084/m9.figshare.1356063.v1
title: Aston University RCUK APCs 2013-14

description: This dataset contains details of the article processing charges (APCs) paid by Aston University from RCUK funds from 1 April 2013 to 31 July 2014. An aggregated version can be found here: http://figshare.com/articles/RCUK_APC_data_2013_14_/1180122
DOI: 10.6084/m9.figshare.1356062.v1
title: Analyzing the Descending Flight of the Germanwings A320 4U9525

description: Something (on 2015-03-26 still unknown) caused 4U9525 to descent. All the rest is the automatic reaction of a properly functioning Airbus A320 to these initial conditions: The aircraft is disengaging the autopilot automatically at a Mach number of 0.82 as a consequence of High Speed Protection and follows a subsequent descending flight in manual mode (with normal Fly-by-Wire flight control laws) and idle thrust. The pilots probably are neither touching the side sticks nor the thrust levers. At least, it does not need any pilot intervention to explain the cause of the last 9 minutes of the flight and the final tragic effect.
DOI: 10.6084/m9.figshare.1356059.v1
title: Data from Perry et al. (2015) PLoS ONE

description: The file tuning_data.csv contains contrast tuning data for each participant. Row 1 gives contrast. Rows 2-15 give the amplitude of gamma at the corresponding contrast for each participant (column 1 gives participant number). Rows 16-29 gives the frequency fo gamma for the corresponding contrast. Virtual sensor timeseries files contain the virtual sensor timeseries for eac numbered participant. Column one give time (in ms relative to stimulus onset). Subsequenct columns give the virtual sensor data for each trial (excluding trials containing artefacts).
DOI: 10.6084/m9.figshare.1356061.v1
title: Germanwings_4U9525.xls

description: Something (on 2015-03-26 still unknown) caused 4U9525 to descent. All the rest is the automatic reaction of a properly functioning Airbus A320 to these initial conditions: The aircraft is disengaging the autopilot automatically at a Mach number of 0.82 as a consequence of High Speed Protection and follows a subsequent descending flight in manual mode (with normal Fly-by-Wire flight control laws) and idle thrust. The pilots probably do neither touching the side sticks nor the thrust levers. At least, it does not need any pilot intervention to explain the cause of the last 9 minutes of the flight and the final tragic effect.
DOI: 10.6084/m9.figshare.1356059.v3
title: Data from 'Linear tuning of gamma amplitude and frequency to luminance contrast: evidence from a continuous mapping paradigm', Perry et al. (2015) PLoS ONE

description: The accompanying data is the data created for the study: 'Linear tuning of gamma amplitude and frequency to luminance contrast: evidence from a continuous mapping paradigm', Perry et al. (2015) PloS ONE. For methods used to generate the data see that paper. The file tuning_data.csv contains contrast tuning data for each participant. Row 1 gives Michelson contrast in %. Rows 2-15 give the amplitude of gamma (in % relative to baseline) at the corresponding contrast for each participant (column 1 gives participant number). Rows 16-29 gives the frequency (in Hz) of gamma for the corresponding contrast. These are the data plotted in the central and right-hand panels of Fig. 2. virtual_sensor_participant_x.csv contains the virtual sensor timeseries for participant x (using the same numbering as Fig. 2). Column one gives time (in ms relative to stimulus onset). Subsequenct columns give the virtual sensor data for each trial (trials containing artefacts have been removed). bertogram8_participant_x.csv contains the time-frequency 'bertogram' for participant x. This is the time-frequency data plotted in Fig. 2 and used for analysing the amplitude tuning. Column 1 gives time relative to stimulus onset (in ms), row 1 gives frequency (in Hz), other columns/rows give data at the corresponding time and frequency as % amplitude relative to baseline. Date were generated using an 8Hz bandpass at each frequency. bertogram1_participant_x.csv contains the time-frequency 'bertogram' for participant x generated using 1Hz bandpass at each frequency. This was the data used for analysing frequency tuning. File layout is identical to bertogram8_participant_x.csv.
DOI: 10.6084/m9.figshare.1356059.v2
title: Data from Perry et al. (2015) PLoS ONE

description: The file tuning_data.csv contains contrast tuning data for each participant. Row 1 gives contrast. Rows 2-15 give the amplitude of gamma at the corresponding contrast for each participant (column 1 gives participant number). Rows 16-29 gives the frequency fo gamma for the corresponding contrast. Virtual sensor timeseries files contain the virtual sensor timeseries for eac numbered participant. Column one give time (in ms relative to stimulus onset). Subsequenct columns give the virtual sensor data for each trial (excluding trials containing artefacts).
DOI: 10.6084/m9.figshare.1356061.v2
title: Analyzing the Descending Flight of the Germanwings A320 4U9525

description: Something (on 2015-03-26, 10:00 still unknown) caused 4U9525 to descent. All the rest is the automatic reaction of a properly functioning Airbus A320 to these initial conditions: The aircraft is disengaging the autopilot automatically at a Mach number of 0.82 as a consequence of High Speed Protection and follows a subsequent descending flight in manual mode (with normal Fly-by-Wire flight control laws) and idle thrust. The pilots probably are neither touching the side sticks nor the thrust levers. At least, it does not need any pilot intervention to explain the cause of the last 9 minutes of the flight and the final tragic effect.
DOI: 10.6084/m9.figshare.1356061.v3
title: Analyzing the Descending Flight of the Germanwings A320 4U9525

description: Something (on 2015-03-26, 10:00 still unknown) caused 4U9525 to descent. All the rest is the automatic reaction of a properly functioning Airbus A320 to these initial conditions: The aircraft is disengaging the autopilot automatically at a Mach number of 0.82 as a consequence of High Speed Protection and follows a subsequent descending flight in manual mode (with normal Fly-by-Wire flight control laws) and idle thrust. The pilots probably are neither touching the side sticks nor the thrust levers. At least, it does not need any pilot intervention to explain the cause of the last 9 minutes of the flight and the final tragic effect.
DOI: 10.6084/m9.figshare.1355942
title: Music-to-Color Associations of Single-line Piano Melodies in Non-Synesthetes

description: Prior research has shown that non-synesthetes’ color associations to classical orchestral music are strongly mediated by emotion. The present study examines similar cross-modal music-to-color associations for much better controlled musical stimuli: 64 single-line piano melodies that were generated from four basic melodies by Mozart, whose global musical parameters were manipulated in tempo (slow/fast), note-density (sparse/dense), mode (major/minor) and pitch-height (low/high). Participants first chose the three colors (from 37) that they judged to be most consistent with (and, later, the three that were most inconsistent with) the music they were hearing. They later rated each melody and each color for the strength of its association along four emotional dimensions: happy/sad, agitated/calm, angry/not-angry and strong/weak. The cross-modal choices showed that faster music in the major mode was associated with lighter, more saturated, yellower (warmer) colors than slower music in the minor mode. These results replicate and extend those of Palmer et al. (2013, Proc. Natl. Acad. Sci. 110, 8836–8841) with more precisely controlled musical stimuli. Further results replicated strong evidence for emotional mediation of these cross-modal associations, in that the emotional ratings of the melodies were very highly correlated with the emotional associations of the colors chosen as going best/worst with the melodies (r = 0.92, 0.85, 0.82 and 0.70 for happy/sad, strong/weak, angry/not-angry and agitated/calm, respectively). The results are discussed in terms of common emotional associations forming a cross-modal bridge between highly disparate sensory inputs.
DOI: 10.6084/m9.figshare.1355852
title: Co-authorships of the ACM Turing and IEEE Von Neumann Awardees

description: <strong>Co-authorships of the <em>ACM</em> Turing and <em>IEEE</em> Von Neumann Awardees</strong> This map shows the co-authorships of scientists who received: - The <em>ACM</em> A.M. Turing Award - The <em>IEEE</em> John von Neumann Medal - Both of these Nodes were coloured to distinguish Turing (in green) and Von Neumann (in blue) awardees. Red nodes show the recipients of both awards. Node size reflects the "writing efforts": sum 1/n for all papers with n co-authors. Edges in dark grey link two co-authors. Edges in light grey link two awardees who never co-authored a paper but they share at least one co-author (these are opportunities for collaborations). Edge width reflects the strength of collaborations: sum 2 / (n * (n - 1)) for all papers co-authored by two given authors (n co-authors in total). The source data were extracted from the DBLP (http://dblp.uni-trier.de) in February 2015. Peer reviewed conference and journal papers were considered and ArXiv CoRR papers were discarded. For more details about source data processing see (Cabanac et al., 2015). The map was generated with Gephi (http://gephi.github.io). This co-authorship map suggests that the community of CS awardees is a small world with tightly connected scientists. Due to the limited coverage of DBLP (i.e., computer science and frontiers), this map does not show the connections to other disciplines. For a study of the CS awardees as brokers to other disciplines see (Fields, forthcoming). <em>Acknowledgements</em> Thanks go to the DBLP team for maintaining such a valuable service and releasing their data. I am also grateful to my research assistant, Clara Belair, who contributed to this study. <em>References</em> Cabanac, G., Hubert, G., & Milard, B. (2015). Academic careers in Computer Science: continuance and transience of lifetime co-authorships. Scientometrics, 102, 1, 135–150. doi:10.1007/s11192-014-1426-0 Fields, C. (forthcoming). Co-authorship proximity of A. M. Turing Award and John von Neumann Medal winners to the disciplinary boundaries of computer science. Scientometrics. <em>Links</em> http://amturing.acm.org http://www.ieee.org/about/awards/medals/vonneumann.html
DOI: 10.6084/m9.figshare.1355942.v1
title: Music-to-Color Associations of Single-line Piano Melodies in Non-Synesthetes

description: Prior research has shown that non-synesthetes’ color associations to classical orchestral music are strongly mediated by emotion. The present study examines similar cross-modal music-to-color associations for much better controlled musical stimuli: 64 single-line piano melodies that were generated from four basic melodies by Mozart, whose global musical parameters were manipulated in tempo (slow/fast), note-density (sparse/dense), mode (major/minor) and pitch-height (low/high). Participants first chose the three colors (from 37) that they judged to be most consistent with (and, later, the three that were most inconsistent with) the music they were hearing. They later rated each melody and each color for the strength of its association along four emotional dimensions: happy/sad, agitated/calm, angry/not-angry and strong/weak. The cross-modal choices showed that faster music in the major mode was associated with lighter, more saturated, yellower (warmer) colors than slower music in the minor mode. These results replicate and extend those of Palmer et al. (2013, Proc. Natl. Acad. Sci. 110, 8836–8841) with more precisely controlled musical stimuli. Further results replicated strong evidence for emotional mediation of these cross-modal associations, in that the emotional ratings of the melodies were very highly correlated with the emotional associations of the colors chosen as going best/worst with the melodies (r = 0.92, 0.85, 0.82 and 0.70 for happy/sad, strong/weak, angry/not-angry and agitated/calm, respectively). The results are discussed in terms of common emotional associations forming a cross-modal bridge between highly disparate sensory inputs.