cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5618477
title: Reproduction package for the paper "Constraining a neutron star merger origin for localized fast radio bursts"

description: This is a reproduction package for the paper "Constraining a neutron star merger origin for localized fast radio bursts" by Gourdji et al. (2020) and published in MNRAS. This package provides a Jupyter notebook and the necessary information to reproduce the figures and main results of this paper.
DOI: 10.5281/zenodo.5266492
title: Dataset of ipsilateral motor-evoked potentials induced by transcranial magnetic stimulation

description: The dataset includes 2546 trials of EMG recordings after ipsilateral TMS under muscle contraction. This data was used for the evaluation of the DiMEP toolbox https://pypi.org/project/dimep/ All subjects provided written, informed consent before participation and following approval by the local ethics committee. Subjects had no contraindications to TMS. TMS was delivered with a MagVenture MagPro-R30 with MagOption and a MCF-B70 figure 8-coil at an orientation of 45° to the midsagittal plane (see figure 1A). First, the motor hotspot of the contralateral, i.e., right, extensor digitorum communis (EDC) was determined by applying 40 stimuli to the left hemisphere. 40% MSO was used as the starting intensity and increased in steps of 5% MSO in case no MEPs could be elicited. Next, at the locations of the three stimuli that resulted in the greatest MEP, i.e., the largest MEP peak-to-peak amplitude, additional three stimuli were applied. The stimulation location that consistently elicited the largest MEPs in the contralateral EDC was then selected as the hotspot. A neuro-navigation system (TMS Navigator, Localite GmbH, Germany) supported coil positioning throughout the measurements. In order to measure ipsilateral MEPs, TMS pulses were applied to the motor hotspot with 5s ± 1.25 s between pulses (at an intensity of 90% MSO). To increase the likelihood of exhibiting ipsilateral MEPs, subjects were requested to isometrically contract their left biceps brachii (BB) to 30% of its maximum voluntary contraction while receiving visual feedback of the BB activity relative to the required target level of contraction on a computer display. The electromyographical response (EMG) to TMS was recorded with a BrainProducts ExG bipolar amplifier from the ipsilateral EDC. All trials were divided into 1s segments, i.e., 500 ms before and after each TMS pulse, and sampled at 1000 Hz. We removed artifacts due to coil placement with a Heaviside fit removal, a Hampel filter of 20 ms width, and a polynomial detrending of 5<sup>th</sup> order. Trials with remaining artifacts were rejected, resulting in an average of 47 trials per subject.
DOI: 10.15468/mvfkag
title: Novelties in centralAmazonian microcaddisflies: Three new species of Ochrotrichia Mosely (Trichoptera: Hydroptilidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Moreno, Lucas, Desidério, Gleison Robson, Pes, Ana Maria, Hamada, Neusa (2021): Novelties in centralAmazonian microcaddisflies: Three new species of Ochrotrichia Mosely (Trichoptera: Hydroptilidae). Zootaxa 5060 (2): 250-264, DOI: https://doi.org/10.11646/zootaxa.5060.2.6
DOI: 10.15468/pdec2t
title: A new species of the genus Mongoloniscus Verhoeff, 1930 (Crustacea: Isopoda: Agnaridae) from China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Yang, Lina, An, Jianmei (2021): A new species of the genus Mongoloniscus Verhoeff, 1930 (Crustacea: Isopoda: Agnaridae) from China. Zootaxa 5060 (2): 265-274, DOI: https://doi.org/10.11646/zootaxa.5060.2.7
DOI: 10.15468/t99q4y
title: Tachinid flies (Diptera: Tachinidae) reared from deciduous plant-feeding lepidopteran larvae at Hokkaido University Tomakomai Forest (Japan), with descriptions of three new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Shima, Hiroshi, Abe, Tomokazu, Libra, Martin (2021): Tachinid flies (Diptera: Tachinidae) reared from deciduous plant-feeding lepidopteran larvae at Hokkaido University Tomakomai Forest (Japan), with descriptions of three new species. Zootaxa 5060 (2): 275-295, DOI: https://doi.org/10.11646/zootaxa.5060.2.8
DOI: 10.6084/m9.figshare.16906531
title: Chart metadata and snapshots of data from Oct. 29, 2021

description: Zip folder contains the data and metadata for all charts shown in the manuscript (DOI TBD). Tabular JSON data represent the results from running a SPARQL query on the public MaterialsMine SPARQL endpoint on Oct. 29, 2021.
DOI: 10.6084/m9.figshare.16906531.v2
title: Chart metadata and snapshots of data from Oct. 29, 2021

description: Zip folder contains the data and metadata for all charts shown in the manuscript (DOI TBD). Tabular JSON data represent the results from running a SPARQL query on the public MaterialsMine SPARQL endpoint on Oct. 29, 2021.
DOI: 10.6084/m9.figshare.16906531.v1
title: Chart metadata and snapshots of data from Oct. 29, 2021

description: Zip folder contains the data and metadata for all charts shown in the manuscript (DOI TBD). Tabular JSON data represent the results from running a SPARQL query on the public MaterialsMine SPARQL endpoint on Oct. 29, 2021.
DOI: 10.5281/zenodo.5619691
title: SMART-Miner

description: Metadata and data set for training the SMART Miner
DOI: 10.6073/pasta/4475d3c99091bc933b1255cee795ad13
title: Dry weight biomass measurements of net-collected mesozooplankton. Samples collected in the CCE-LTER region on Process Cruises from 2006 to the present. Summaries for each Lagrangian Cycle.

description: Mesozooplankton are collected with plankton nets (typically a 71-cm diameter, 202-um mesh Bongo net) and samples flash frozen at sea in liquid N2 for subsequent shore-based measurements of dry weight biomass. Measurements are made by weighing pre-tared Nitex mesh on an analytical balance, for mesozooplankton size-fractionated into 5 different categories (&gt; 0.2 mm, 0.5 mm, 1.0 mm, 2.0 mm, 5.0 mm). Biomass is expressed as dry mass of zooplankton per m3 of water filtered, or when multiplied by the maximum depth of the tow, as integrated dry mass of zooplankton per m2 of sea surface. Samples for dry weight biomass have been collected on CCE-LTER Process Cruises since 2006 and these collections are ongoing.
DOI: 10.15468/3hwqce
title: Integrative description of Mesobiotus anastasiae sp. nov. (Eutardigrada, Macrobiotoidea) and first record of Lobohalacarus (Chelicerata, Trombidiformes) from the Republic of South Africa

description: This dataset contains the digitized treatments in Plazi based on the original journal article Tumanov, Denis V. (2020): Integrative description of Mesobiotus anastasiae sp. nov. (Eutardigrada, Macrobiotoidea) and first record of Lobohalacarus (Chelicerata, Trombidiformes) from the Republic of South Africa. European Journal of Taxonomy 726 (726): 102-131, DOI: https://doi.org/10.5852/ejt.2020.726.1179, URL: http://dx.doi.org/10.5852/ejt.2020.726.1179
DOI: 10.15468/v3g74v
title: The spider family Oecobiidae (Arachnida: Araneae) in Iran, Afghanistan and Turkmenistan

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zamani, Alireza, Bosselaers, Jan (2020): The spider family Oecobiidae (Arachnida: Araneae) in Iran, Afghanistan and Turkmenistan. European Journal of Taxonomy 726: 38-58, DOI: https://doi.org/10.5852/ejt.2020.726.1173
DOI: 10.21231/c3kn-r286
title: Ixodes scapularis density in US temperate forests shaped by deer, earthworms, and other disparate factors at two scales
DOI: 10.34808/53g6-en14
title: MODALITY corpus - SPEAKER 01 - COMMANDS C4

description: The MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system, as every utterance was labelled. Recordings in noisy conditions can be used to test the robustness of speech recognition systems.
The language material was based on a remote control scenario and it includes 231 words -numbers, names of months and days, a set of verbs and nouns related to a computer device control. They were read by speakers as separated words and sequences resulting in a set of 12 recording sessions per speaker. Half of the sessions were recorded in quiet conditions, the other half contained three kinds of intrusive signals (traffic, babble and factory noise).
The corpus includes recordings of 42 speakers (33 male, 9 female). The participants include 20 students and staff of Multimedia Systems Department of the Gdańsk University of Technology, 5 students of the Institute of English and American Studies of the University of Gdańsk, and 17 native English speakers.
The dataset consist of recordings and visual features for SPEAKER 01:
sex: man
native speaker: no
age: 27
The test material: COMMANDS C4
All recordings for all speakers are available at http://www.modality-corpus.org/  Sample still from the corpus(SPEAKER 01) Due to the size of the corpus (approx. 2.5 TB of data), every speaker’s recording was placed in a separate zip file of the size approx. 4-7 GB each.
The recordings were organized according to the speakers’ language skills. The group A (17 speakers) consists of native-speakers. Non-native speakers recordings (Polish nationals) were placed in the Group B (25 speakers).
The audio files use the Waveform Audio File Format (.wav), and contain a single PCM audio stream sampled at 44.1 kSa/s with 16-bit depth. The video files utilize the Matroska Multimedia Container Format (.mkv) in which a video stream in 1080p resolution, captured at 100 fps was placed after being compressed with h.264 codec (using High 4:4:4 profile). The ‘.lab’ files are text files containing the information on word positions in audio files, and follow the HTK label format. Each line of a ‘.lab’ file contains the actual label preceded by start and end times (in 100 ns units) e.g. : 1239620000 1244790000 FIVE which denotes the word “five”, occurring between the 123.962 s and 124.479 s of audio.Word-accurate SNR values calculated for every recording are also included in the ZIP file.
DOI: 10.34808/65ns-sw76
title: MODALITY corpus - SPEAKER 01 - SEQUENCE S4

description: The MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system, as every utterance was labelled. Recordings in noisy conditions can be used to test the robustness of speech recognition systems.
The language material was based on a remote control scenario and it includes 231 words -numbers, names of months and days, a set of verbs and nouns related to a computer device control. They were read by speakers as separated words and sequences resulting in a set of 12 recording sessions per speaker. Half of the sessions were recorded in quiet conditions, the other half contained three kinds of intrusive signals (traffic, babble and factory noise).
The corpus includes recordings of 42 speakers (33 male, 9 female). The participants include 20 students and staff of Multimedia Systems Department of the Gdańsk University of Technology, 5 students of the Institute of English and American Studies of the University of Gdańsk, and 17 native English speakers.
The dataset consist of recordings and visual features for SPEAKER 01:
sex: man
native speaker: no
age: 27
The test material: SEQUENCE S4
All recordings for all speakers are available at http://www.modality-corpus.org/  Sample still from the corpus(SPEAKER 01) Due to the size of the corpus (approx. 2.5 TB of data), every speaker’s recording was placed in a separate zip file of the size approx. 4-7 GB each.
The recordings were organized according to the speakers’ language skills. The group A (17 speakers) consists of native-speakers. Non-native speakers recordings (Polish nationals) were placed in the Group B (25 speakers).
The audio files use the Waveform Audio File Format (.wav), and contain a single PCM audio stream sampled at 44.1 kSa/s with 16-bit depth. The video files utilize the Matroska Multimedia Container Format (.mkv) in which a video stream in 1080p resolution, captured at 100 fps was placed after being compressed with h.264 codec (using High 4:4:4 profile). The ‘.lab’ files are text files containing the information on word positions in audio files, and follow the HTK label format. Each line of a ‘.lab’ file contains the actual label preceded by start and end times (in 100 ns units) e.g. : 1239620000 1244790000 FIVE which denotes the word “five”, occurring between the 123.962 s and 124.479 s of audio.Word-accurate SNR values calculated for every recording are also included in the ZIP file.
DOI: 10.34808/kp6m-yt53
title: MODALITY corpus - SPEAKER 01 - COMMANDS C3

description: The MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system, as every utterance was labelled. Recordings in noisy conditions can be used to test the robustness of speech recognition systems.
The language material was based on a remote control scenario and it includes 231 words -numbers, names of months and days, a set of verbs and nouns related to a computer device control. They were read by speakers as separated words and sequences resulting in a set of 12 recording sessions per speaker. Half of the sessions were recorded in quiet conditions, the other half contained three kinds of intrusive signals (traffic, babble and factory noise).
The corpus includes recordings of 42 speakers (33 male, 9 female). The participants include 20 students and staff of Multimedia Systems Department of the Gdańsk University of Technology, 5 students of the Institute of English and American Studies of the University of Gdańsk, and 17 native English speakers.
The dataset consist of recordings and visual features for SPEAKER 01:
sex: man
native speaker: no
age: 27
The test material: COMMANDS C3
All recordings for all speakers are available at http://www.modality-corpus.org/  Sample still from the corpus(SPEAKER 01) Due to the size of the corpus (approx. 2.5 TB of data), every speaker’s recording was placed in a separate zip file of the size approx. 4-7 GB each.
The recordings were organized according to the speakers’ language skills. The group A (17 speakers) consists of native-speakers. Non-native speakers recordings (Polish nationals) were placed in the Group B (25 speakers).
The audio files use the Waveform Audio File Format (.wav), and contain a single PCM audio stream sampled at 44.1 kSa/s with 16-bit depth. The video files utilize the Matroska Multimedia Container Format (.mkv) in which a video stream in 1080p resolution, captured at 100 fps was placed after being compressed with h.264 codec (using High 4:4:4 profile). The ‘.lab’ files are text files containing the information on word positions in audio files, and follow the HTK label format. Each line of a ‘.lab’ file contains the actual label preceded by start and end times (in 100 ns units) e.g. : 1239620000 1244790000 FIVE which denotes the word “five”, occurring between the 123.962 s and 124.479 s of audio.Word-accurate SNR values calculated for every recording are also included in the ZIP file.
DOI: 10.34808/ynw9-v466
title: MODALITY corpus - SPEAKER 01 - SEQUENCE S3

description: The MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system, as every utterance was labelled. Recordings in noisy conditions can be used to test the robustness of speech recognition systems.
The language material was based on a remote control scenario and it includes 231 words -numbers, names of months and days, a set of verbs and nouns related to a computer device control. They were read by speakers as separated words and sequences resulting in a set of 12 recording sessions per speaker. Half of the sessions were recorded in quiet conditions, the other half contained three kinds of intrusive signals (traffic, babble and factory noise).
The corpus includes recordings of 42 speakers (33 male, 9 female). The participants include 20 students and staff of Multimedia Systems Department of the Gdańsk University of Technology, 5 students of the Institute of English and American Studies of the University of Gdańsk, and 17 native English speakers.
The dataset consist of recordings and visual features for SPEAKER 01:
sex: man
native speaker: no
age: 27
The test material: SEQUENCE S3
All recordings for all speakers are available at http://www.modality-corpus.org/  Sample still from the corpus(SPEAKER 01) Due to the size of the corpus (approx. 2.5 TB of data), every speaker’s recording was placed in a separate zip file of the size approx. 4-7 GB each.
The recordings were organized according to the speakers’ language skills. The group A (17 speakers) consists of native-speakers. Non-native speakers recordings (Polish nationals) were placed in the Group B (25 speakers).
The audio files use the Waveform Audio File Format (.wav), and contain a single PCM audio stream sampled at 44.1 kSa/s with 16-bit depth. The video files utilize the Matroska Multimedia Container Format (.mkv) in which a video stream in 1080p resolution, captured at 100 fps was placed after being compressed with h.264 codec (using High 4:4:4 profile). The ‘.lab’ files are text files containing the information on word positions in audio files, and follow the HTK label format. Each line of a ‘.lab’ file contains the actual label preceded by start and end times (in 100 ns units) e.g. : 1239620000 1244790000 FIVE which denotes the word “five”, occurring between the 123.962 s and 124.479 s of audio.Word-accurate SNR values calculated for every recording are also included in the ZIP file.
DOI: 10.34808/544q-jt75
title: MODALITY corpus - SPEAKER 01 - COMMANDS C2

description: The MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system, as every utterance was labelled. Recordings in noisy conditions can be used to test the robustness of speech recognition systems.
The language material was based on a remote control scenario and it includes 231 words -numbers, names of months and days, a set of verbs and nouns related to a computer device control. They were read by speakers as separated words and sequences resulting in a set of 12 recording sessions per speaker. Half of the sessions were recorded in quiet conditions, the other half contained three kinds of intrusive signals (traffic, babble and factory noise).
The corpus includes recordings of 42 speakers (33 male, 9 female). The participants include 20 students and staff of Multimedia Systems Department of the Gdańsk University of Technology, 5 students of the Institute of English and American Studies of the University of Gdańsk, and 17 native English speakers.
The dataset consist of recordings and visual features for SPEAKER 01:
sex: man
native speaker: no
age: 27
The test material: COMMANDS C2
All recordings for all speakers are available at http://www.modality-corpus.org/  Sample still from the corpus(SPEAKER 01) Due to the size of the corpus (approx. 2.5 TB of data), every speaker’s recording was placed in a separate zip file of the size approx. 4-7 GB each.
The recordings were organized according to the speakers’ language skills. The group A (17 speakers) consists of native-speakers. Non-native speakers recordings (Polish nationals) were placed in the Group B (25 speakers).
The audio files use the Waveform Audio File Format (.wav), and contain a single PCM audio stream sampled at 44.1 kSa/s with 16-bit depth. The video files utilize the Matroska Multimedia Container Format (.mkv) in which a video stream in 1080p resolution, captured at 100 fps was placed after being compressed with h.264 codec (using High 4:4:4 profile). The ‘.lab’ files are text files containing the information on word positions in audio files, and follow the HTK label format. Each line of a ‘.lab’ file contains the actual label preceded by start and end times (in 100 ns units) e.g. : 1239620000 1244790000 FIVE which denotes the word “five”, occurring between the 123.962 s and 124.479 s of audio.Word-accurate SNR values calculated for every recording are also included in the ZIP file.
DOI: 10.34808/410c-vz34
title: MODALITY corpus - SPEAKER 01 - SEQUENCE S2

description: The MODALITY corpus is one of the multimodal database of word recordings in English. It consists of over 30 hours of multimodal recordings. The database contains high-resolution, high-framerate stereoscopic video streams and audio signals obtained from a microphone array and a laptop microphone. The corpus can be employed to develop an AVSR system, as every utterance was labelled. Recordings in noisy conditions can be used to test the robustness of speech recognition systems.
The language material was based on a remote control scenario and it includes 231 words -numbers, names of months and days, a set of verbs and nouns related to a computer device control. They were read by speakers as separated words and sequences resulting in a set of 12 recording sessions per speaker. Half of the sessions were recorded in quiet conditions, the other half contained three kinds of intrusive signals (traffic, babble and factory noise).
The corpus includes recordings of 42 speakers (33 male, 9 female). The participants include 20 students and staff of Multimedia Systems Department of the Gdańsk University of Technology, 5 students of the Institute of English and American Studies of the University of Gdańsk, and 17 native English speakers.
The dataset consist of recordings and visual features for SPEAKER 01:
sex: man
native speaker: no
age: 27
The test material: SEQUENCE S2
All recordings for all speakers are available at http://www.modality-corpus.org/  Sample still from the corpus(SPEAKER 01) Due to the size of the corpus (approx. 2.5 TB of data), every speaker’s recording was placed in a separate zip file of the size approx. 4-7 GB each.
The recordings were organized according to the speakers’ language skills. The group A (17 speakers) consists of native-speakers. Non-native speakers recordings (Polish nationals) were placed in the Group B (25 speakers).
The audio files use the Waveform Audio File Format (.wav), and contain a single PCM audio stream sampled at 44.1 kSa/s with 16-bit depth. The video files utilize the Matroska Multimedia Container Format (.mkv) in which a video stream in 1080p resolution, captured at 100 fps was placed after being compressed with h.264 codec (using High 4:4:4 profile). The ‘.lab’ files are text files containing the information on word positions in audio files, and follow the HTK label format. Each line of a ‘.lab’ file contains the actual label preceded by start and end times (in 100 ns units) e.g. : 1239620000 1244790000 FIVE which denotes the word “five”, occurring between the 123.962 s and 124.479 s of audio.Word-accurate SNR values calculated for every recording are also included in the ZIP file.