cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4382188
title: A studyforrest extension, an annotation of spoken language in the German dubbed movie ``Forrest Gump'' and its audio-description (validation analysis)

description: This component contains the data of the analysis that we ran as a validation of the annotation of speech spoken in the research cut (Hanke et al., 2016) of the movie "Forrest Gump" (Zemeckis, 1994) and its audio-description. The corresponding paper is hosted on github (https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation) and published in f1000research (https://doi.org/10.12688/f1000research.27621.1).
description: Here we present an annotation of speech in the audio-visual movie "Forrest Gump" and its audio-description for a visually impaired audience, as an addition to a large public functional brain imaging dataset (studyforrest.org). The annotation provides information about the exact timing of each of the more than 2500 spoken sentences, 16000 words (including 202 non-speech vocalizations), 66000 phonemes, and their corresponding speaker. Additionally, for every word, we provide lemmatization, a simple part-of-speech-tagging (15 grammatical categories), a detailed part-of-speech tagging (43 grammatical categories), syntactic dependencies, and a semantic analysis based on word embedding which represents each word in a 300-dimensional semantic space. To validate the dataset's quality, we build a model of hemodynamic brain activity based on information drawn from the annotation. Results suggest that the annotation's content and quality enable independent researchers to create models of brain activity correlating with a variety of linguistic aspects under conditions of near-real-life complexity
DOI: 10.5281/zenodo.4382187
title: A studyforrest extension, an annotation of spoken language in the German dubbed movie ``Forrest Gump'' and its audio-description (validation analysis)

description: This component contains the data of the analysis that we ran as a validation of the annotation of speech spoken in the research cut (Hanke et al., 2016) of the movie "Forrest Gump" (Zemeckis, 1994) and its audio-description. The corresponding paper is hosted on github (https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation) and published in f1000research (https://doi.org/10.12688/f1000research.27621.1).
description: Here we present an annotation of speech in the audio-visual movie "Forrest Gump" and its audio-description for a visually impaired audience, as an addition to a large public functional brain imaging dataset (studyforrest.org). The annotation provides information about the exact timing of each of the more than 2500 spoken sentences, 16000 words (including 202 non-speech vocalizations), 66000 phonemes, and their corresponding speaker. Additionally, for every word, we provide lemmatization, a simple part-of-speech-tagging (15 grammatical categories), a detailed part-of-speech tagging (43 grammatical categories), syntactic dependencies, and a semantic analysis based on word embedding which represents each word in a 300-dimensional semantic space. To validate the dataset's quality, we build a model of hemodynamic brain activity based on information drawn from the annotation. Results suggest that the annotation's content and quality enable independent researchers to create models of brain activity correlating with a variety of linguistic aspects under conditions of near-real-life complexity
DOI: 10.5281/zenodo.4382143
title: A studyforrest extension, an annotation of spoken language in the German dubbed movie ``Forrest Gump'' and its audio-description (annotation)

description: This dataset contains the annotation of speech spoken in the research cut (Hanke et al. 2014; Hanke et al., 2016) of the movie "Forrest Gump" (Zemeckis, 1994) and its audio-description that was broadcast as an additional audio track (Koop et al., 2009) for visually impaired listeners on Swiss public television. The corresponding paper is hosted on github (https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation) and published in f1000research (https://doi.org/10.12688/f1000research.27621.1).
description: Here we present an annotation of speech in the audio-visual movie "Forrest Gump" and its audio-description for a visually impaired audience, as an addition to a large public functional brain imaging dataset (studyforrest.org). The annotation provides information about the exact timing of each of the more than 2500 spoken sentences, 16000 words (including 202 non-speech vocalizations), 66000 phonemes, and their corresponding speaker. Additionally, for every word, we provide lemmatization, a simple part-of-speech-tagging (15 grammatical categories), a detailed part-of-speech tagging (43 grammatical categories), syntactic dependencies, and a semantic analysis based on word embedding which represents each word in a 300-dimensional semantic space. To validate the dataset's quality, we build a model of hemodynamic brain activity based on information drawn from the annotation. Results suggest that the annotation's content and quality enable independent researchers to create models of brain activity correlating with a variety of linguistic aspects under conditions of near-real-life complexity
DOI: 10.5281/zenodo.4382142
title: A studyforrest extension, an annotation of spoken language in the German dubbed movie ``Forrest Gump'' and its audio-description (annotation)

description: This dataset contains the annotation of speech spoken in the research cut (Hanke et al. 2014; Hanke et al., 2016) of the movie "Forrest Gump" (Zemeckis, 1994) and its audio-description that was broadcast as an additional audio track (Koop et al., 2009) for visually impaired listeners on Swiss public television. The corresponding paper is hosted on github (https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation) and published in f1000research (https://doi.org/10.12688/f1000research.27621.1).
description: Here we present an annotation of speech in the audio-visual movie "Forrest Gump" and its audio-description for a visually impaired audience, as an addition to a large public functional brain imaging dataset (studyforrest.org). The annotation provides information about the exact timing of each of the more than 2500 spoken sentences, 16000 words (including 202 non-speech vocalizations), 66000 phonemes, and their corresponding speaker. Additionally, for every word, we provide lemmatization, a simple part-of-speech-tagging (15 grammatical categories), a detailed part-of-speech tagging (43 grammatical categories), syntactic dependencies, and a semantic analysis based on word embedding which represents each word in a 300-dimensional semantic space. To validate the dataset's quality, we build a model of hemodynamic brain activity based on information drawn from the annotation. Results suggest that the annotation's content and quality enable independent researchers to create models of brain activity correlating with a variety of linguistic aspects under conditions of near-real-life complexity
DOI: 10.6084/m9.figshare.13553966.v1
title: Supplementary Material for: Relationship between Apgar Scores and Morbidity and Mortality Outcomes in Preterm Infants: A Single-Centre Cohort Study

description: <b><i>Introduction:</i></b> Apgar scoring in modern practice has extended beyond the original described remit by Virginia Apgar, including prognostication. Prognostic value of Apgar scoring in preterm populations is unsupported by robust evidence. <b><i>Objectives:</i></b> We aimed to identify the association between mortality or a composite mortality/major morbidity outcome in preterm infants with 1-min, 5-min, and sum 1 + 5-min Apgar scores. <b><i>Methods:</i></b> Seven-year retrospective data was analysed on neonates born &lt;32 weeks gestation in a regional neonatal centre. Co-primary outcomes were mortality and composite mortality/major morbidity. Adjusted odds ratios (aOR) were estimated using multivariable logistic regression analysis. <b><i>Results:</i></b> 394 infants were included in the analysis. In neonates born &lt;28 weeks gestation, no significant association was found between Apgar scores and the co-primary outcomes. In neonates born ≥28 weeks, low 1-min (aOR 10.452 [1.273, 85.835] for scores 4–6, 22.173 [2.666, 184.438] for scores 0–3), 5-min (4.724 [1.616, 13.806] for scores 4–6, 11.178 [1.803, 69.299] for scores 0–3), and sum 1 + 5-min Apgar scores (12.447 [2.674, 57.941] for scores 4–6, 55.960 [8.333, 375.804] for scores 0–3) were associated with significantly increased aOR of mortality. Increased aOR of composite mortality/major morbidity were also seen in neonates with moderately low (4–6) Apgar scores (aOR 3.104 [1.522, 6.328] for 1 min, 2.804 [1.406, 5.594] for 5 min, and 3.232 [1.769, 5.905] for 1 + 5 min). <b><i>Conclusions:</i></b> Apgar scoring at 1 and 5 min has limited prognostic accuracy for extremely preterm infants but is prognostic in older infants. Sum Apgar scores, a measure of initial condition and response to resuscitation, may be a better predictor of mortality than individual scores.
DOI: 10.6084/m9.figshare.13553966
title: Supplementary Material for: Relationship between Apgar Scores and Morbidity and Mortality Outcomes in Preterm Infants: A Single-Centre Cohort Study

description: <b><i>Introduction:</i></b> Apgar scoring in modern practice has extended beyond the original described remit by Virginia Apgar, including prognostication. Prognostic value of Apgar scoring in preterm populations is unsupported by robust evidence. <b><i>Objectives:</i></b> We aimed to identify the association between mortality or a composite mortality/major morbidity outcome in preterm infants with 1-min, 5-min, and sum 1 + 5-min Apgar scores. <b><i>Methods:</i></b> Seven-year retrospective data was analysed on neonates born &lt;32 weeks gestation in a regional neonatal centre. Co-primary outcomes were mortality and composite mortality/major morbidity. Adjusted odds ratios (aOR) were estimated using multivariable logistic regression analysis. <b><i>Results:</i></b> 394 infants were included in the analysis. In neonates born &lt;28 weeks gestation, no significant association was found between Apgar scores and the co-primary outcomes. In neonates born ≥28 weeks, low 1-min (aOR 10.452 [1.273, 85.835] for scores 4–6, 22.173 [2.666, 184.438] for scores 0–3), 5-min (4.724 [1.616, 13.806] for scores 4–6, 11.178 [1.803, 69.299] for scores 0–3), and sum 1 + 5-min Apgar scores (12.447 [2.674, 57.941] for scores 4–6, 55.960 [8.333, 375.804] for scores 0–3) were associated with significantly increased aOR of mortality. Increased aOR of composite mortality/major morbidity were also seen in neonates with moderately low (4–6) Apgar scores (aOR 3.104 [1.522, 6.328] for 1 min, 2.804 [1.406, 5.594] for 5 min, and 3.232 [1.769, 5.905] for 1 + 5 min). <b><i>Conclusions:</i></b> Apgar scoring at 1 and 5 min has limited prognostic accuracy for extremely preterm infants but is prognostic in older infants. Sum Apgar scores, a measure of initial condition and response to resuscitation, may be a better predictor of mortality than individual scores.
DOI: 10.6084/m9.figshare.13191020.v1
title: Peter_MS22_180720_110055_concat.zip

description: Peter_MS22_180720_110055_concat
DOI: 10.6084/m9.figshare.13191020
title: Peter_MS22_180720_110055_concat.zip

description: Peter_MS22_180720_110055_concat
DOI: 10.5519/qd.4bk67o17
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5602 records)
DOI: 10.5281/zenodo.4400212
title: The Secret Life of Software Vulnerabilities: A Large-Scale Empirical Study

description: Online appendix of the paper entitled: "The Secret Life of Software Vulnerabilities: A Large-Scale Empirical Study". It contains all scripts and data required to replicate the four research questions of the study. Abstract: Software vulnerabilities are weaknesses in source code that can be potentially exploited to cause loss or harm. While researchers have been devising a number of methods to deal with vulnerabilities, there is still a noticeable lack of knowledge on their software engineering life cycle, for example how vulnerabilities are introduced and removed by developers. This information can be exploited to design more effective methods for vulnerability prevention and detection, as well as to understand the granularity that these methods should aim at. To investigate the life cycle of software vulnerabilities, we focus on how, when, and under which circumstances vulnerabilities are introduced in software projects, as well as whether, after how long, and how they are removed. We consider 4,097 vulnerabilities with public patches from the National Vulnerability Database—pertaining to 1,163 open-source software projects on GITHUB—and define a six-step process that involves both automated parts (e.g., using the SZZ algorithm to find the vulnerability-inducing commits) and manual analyses (e.g., how vulnerabilities were fixed). The investigated vulnerabilities can be classified in 148 categories, take on average 4.19 commits before being introduced, and remain unfixed for a median of 1,506.50 commits and 691.50 days. Most of them are introduced by developers with high workload, often when doing maintenance activities, and removed with mostly with the addition of new source code aiming at implementing further checks on inputs. We conclude by distilling practical implications on when and how vulnerability detectors should work to better assist developers in early detecting these issues.
DOI: 10.5281/zenodo.4400211
title: The Secret Life of Software Vulnerabilities: A Large-Scale Empirical Study

description: Online appendix of the paper entitled: "The Secret Life of Software Vulnerabilities: A Large-Scale Empirical Study". It contains all scripts and data required to replicate the four research questions of the study. Abstract: Software vulnerabilities are weaknesses in source code that can be potentially exploited to cause loss or harm. While researchers have been devising a number of methods to deal with vulnerabilities, there is still a noticeable lack of knowledge on their software engineering life cycle, for example how vulnerabilities are introduced and removed by developers. This information can be exploited to design more effective methods for vulnerability prevention and detection, as well as to understand the granularity that these methods should aim at. To investigate the life cycle of software vulnerabilities, we focus on how, when, and under which circumstances vulnerabilities are introduced in software projects, as well as whether, after how long, and how they are removed. We consider 4,097 vulnerabilities with public patches from the National Vulnerability Database—pertaining to 1,163 open-source software projects on GITHUB—and define a six-step process that involves both automated parts (e.g., using the SZZ algorithm to find the vulnerability-inducing commits) and manual analyses (e.g., how vulnerabilities were fixed). The investigated vulnerabilities can be classified in 148 categories, take on average 4.19 commits before being introduced, and remain unfixed for a median of 1,506.50 commits and 691.50 days. Most of them are introduced by developers with high workload, often when doing maintenance activities, and removed with mostly with the addition of new source code aiming at implementing further checks on inputs. We conclude by distilling practical implications on when and how vulnerability detectors should work to better assist developers in early detecting these issues.
DOI: 10.5281/zenodo.4399225
title: Using Code Reviews to Automatically Configure Static Analysis Tools

description: Working dataset (check traceability oracle) used in the paper
DOI: 10.5281/zenodo.4399224
title: Using Code Reviews to Automatically Configure Static Analysis Tools

description: Working dataset (check traceability oracle) used in the paper
DOI: 10.5281/zenodo.4139498
title: The repository of the SANER'21 paper titled "On the Impact of Flaky Tests in Automated Program Repair"

description: This repository contains the artefact of the paper “On the Impact of Flaky Tests in Automated Program Repair” under review by SANER2021. results: <strong>RQ1:</strong> This table contains all the statistical data of flaky tests we find out from Defects4J benchmark where each line illustrates the commit date, commit id, java file name, as well as all the flaky methods in this test file. Note that the commit id is empty if there is no update about the java file in that line since last version. flaky_methods.xlsx <strong>RQ2:</strong> Here are the execution results of 10 times running of flaky tests under 4 different environment. Detailed execution log of each running are classified by project and named in the format <strong><em>test_log_[project_name].txt</em></strong>,the summarized data of each project are named in the format <strong><em>Flaky_test_[project_name].xlsx</em></strong>. The <strong><em>Flaky_test_all.xlsx</em></strong> contain the summarized data for all projects. jdk1.7 + ubuntu16.04 jdk1.7 + ubuntu18.04 jdk1.8 + ubuntu16.04 jdk1.8 + ubuntu18.04 <strong>RQ3:</strong> This folder contains execution results of the fault localization tool GZoltar-V1.7 under two jdk versions. Result of each bug is named in the format <strong><em>[project_name]_[bug_id].csv</em></strong>. gzoltar_reuslt_flaky_jdk1.7 gzoltar_reuslt_flaky_jdk1.8 gzoltar_reuslt_noFlaky_jdk1.7 gzoltar_reuslt_noFlaky_jdk1.8 <strong>RQ4:</strong> This folder contains repair results of different APR tools. For the 10 tools from RepairThemAll framework, each result is named in format <strong><em>validation_result_[APR_name].txt</em></strong> which indicates whether the previous patch can be generated this time. For TBar, we release all the generated patches including <em>fixed</em> and <em>partially fixed</em>. RepairThemAll TBar
DOI: 10.5281/zenodo.4139497
title: The repository of the SANER'21 paper titled "On the Impact of Flaky Tests in Automated Program Repair"

description: This repository contains the artefact of the paper “On the Impact of Flaky Tests in Automated Program Repair” under review by SANER2021. results: <strong>RQ1:</strong> This table contains all the statistical data of flaky tests we find out from Defects4J benchmark where each line illustrates the commit date, commit id, java file name, as well as all the flaky methods in this test file. Note that the commit id is empty if there is no update about the java file in that line since last version. flaky_methods.xlsx <strong>RQ2:</strong> Here are the execution results of 10 times running of flaky tests under 4 different environment. Detailed execution log of each running are classified by project and named in the format <strong><em>test_log_[project_name].txt</em></strong>,the summarized data of each project are named in the format <strong><em>Flaky_test_[project_name].xlsx</em></strong>. The <strong><em>Flaky_test_all.xlsx</em></strong> contain the summarized data for all projects. jdk1.7 + ubuntu16.04 jdk1.7 + ubuntu18.04 jdk1.8 + ubuntu16.04 jdk1.8 + ubuntu18.04 <strong>RQ3:</strong> This folder contains execution results of the fault localization tool GZoltar-V1.7 under two jdk versions. Result of each bug is named in the format <strong><em>[project_name]_[bug_id].csv</em></strong>. gzoltar_reuslt_flaky_jdk1.7 gzoltar_reuslt_flaky_jdk1.8 gzoltar_reuslt_noFlaky_jdk1.7 gzoltar_reuslt_noFlaky_jdk1.8 <strong>RQ4:</strong> This folder contains repair results of different APR tools. For the 10 tools from RepairThemAll framework, each result is named in format <strong><em>validation_result_[APR_name].txt</em></strong> which indicates whether the previous patch can be generated this time. For TBar, we release all the generated patches including <em>fixed</em> and <em>partially fixed</em>. RepairThemAll TBar
DOI: 10.15468/skevpc
title: Description of Hypocambala zizhongi sp. nov. and the new combination, Glyphiulus polytrichus (Golovatch et al., 2011) comb. nov., based on morphological and molecular data (Spirostreptida: Cambalidea: Cambalopsidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Jiang, Xuan-Kong, Zhang, Zu-Xu, Chen, Hui-Ming, Xie, Zhi-Cai (2021): Description of Hypocambala zizhongi sp. nov. and the new combination, Glyphiulus polytrichus (Golovatch et al., 2011) comb. nov., based on morphological and molecular data (Spirostreptida: Cambalidea: Cambalopsidae). Zootaxa 4903 (3): 405-418, DOI: https://doi.org/10.11646/zootaxa.4903.3.6
DOI: 10.15468/8f7abw
title: Three new leafhopper species of Macropsis Lewis (Hemiptera: Cicadellidae Eurymelinae: Macropsini) with a key to species from the Indian subcontinent

description: This dataset contains the digitized treatments in Plazi based on the original journal article Viraktamath, C. A., Yeshwanth, H. M. (2021): Three new leafhopper species of Macropsis Lewis (Hemiptera: Cicadellidae Eurymelinae: Macropsini) with a key to species from the Indian subcontinent. Zootaxa 4903 (3): 353-372, DOI: https://doi.org/10.11646/zootaxa.4903.3.3
DOI: 10.6084/m9.figshare.12667256
title: Number of underway vessels in the Western Mediterranean (2016/01-2020/11)

description: Terrestrial AIS (T-AIS) data from the Western Mediterranean were collated by the Balearic Islands Coastal Observing and Forecasting System (SOCIB) using a real-time operational system connected to a web-service provided by MarineTraffic (https://www.marinetraffic.com/). The database used in this study contained AIS data from 1st January 2016 until 30th November 2020 at 5 minute intervals (&gt; 545 million AIS messages). In addition to the vessel tracks, the database also included information associated with each vessel, such as the vessel type or length. A first pre-processing of the raw data included the removal of duplicates, invalid identification numbers (i.e. Maritime Mobile Service Identity -MMSI- codes without 9 digits) and codes outside the correct numerical range (i.e. MMSI codes with first digits between 2 and 7 are those intended for individual ships). In order to address inconsistencies in the vessel and MMSI combinations (e.g., changes of MMSI across years), we selected the more frequent combination of MMSI and vessel characteristics (e.g. vessel name and vessel type) for each calendar year. We used a similar vessel categorization as the S-AIS dataset, but were able to derive a sixth category from the AIS metadata, separating “recreational” vessels from “other” vessels. Therefore, vessels were classified into six categories: cargo, tanker, passenger (included high speed crafts and passenger vessels), fishing, recreational (included sailing vessels and pleasure crafts), and others (included all other ship types). We excluded ship type codes 20 to 29 (i.e. wing-in-ground-effect and search and rescue aircraft), as well as codes that had an invalid value (i.e. empty or null) or the value was not listed in the previous type codes. We calculated the number of vessels per day taking into account only those that were underway, thus removing moored vessels inside ports that were inactive. T-AIS coverage was not homogenous in the study area (Holmes et al. 2020) due to a non-uniformly distribution of antennas (i.e. few antennas in north Africa, see www.marinetraffic.com). Based on a previous analysis of the AIS coverage (Holmes et al 2020), we filtered vessels within the coastal zone (44.4 km, ~24 nautical miles) of EU countries (i.e. a total area of 164,318.2 km2 comprised by Spain, France and Italy), thus reducing potential bias due to temporal gaps in signal reception.<br>