cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14363627
title: The bacterial biome of ticks and their wildlife hosts at the sylvatic urban interface

description: Data related to publication "The bacterial biome of ticks and their wildlife hosts at the urban-wildlife interface"
DOI: 10.34740/kaggle/dsv/3780577
title: Contrastive Language Image Pretraining by openai
DOI: 10.5281/zenodo.5760304
title: QReCC - Question Rewriting in Conversational Context

description: QReCC contains 14K conversations with 81K question-answer pairs and a collection of 54M passages. See the README for more information. Additional data used in the SCAI-QReCC 2021 challenge: https://doi.org/10.5281/zenodo.5749472
DOI: 10.5281/zenodo.4748782
title: QReCC - Question Rewriting in Conversational Context

description: QReCC contains 14K conversations with 81K question-answer pairs and a collection of 54M passages. See the README for more information. Additional data used in the SCAI-QReCC 2021 challenge: https://doi.org/10.5281/zenodo.5749472
DOI: 10.6084/m9.figshare.16895001.v3
title: An inducible model for unraveling the effects of advanced glycation end-product accumulation in aging connective tissues

description: In connective tissues there is a clear link between increasing age and degeneration. Advanced glycation end-products (AGEs) are believed to play a central role. AGEs are sugar-induced non-enzymatic crosslinks which accumulate in collagen with age and diabetes, altering tissue mechanics and cellular function. Despite ample correlative evidence linking collagen glycation to tissue degeneration, little is known how AGEs impact cell-matrix interactions, limiting therapeutic options. One reason for this limited understanding is that AGEs are typically induced using high concentrations of ribose which decrease cell viability, making it impossible to investigate cell-matrix interactions. The objective of this study was to develop a system to trigger AGE accumulation while maintaining cell viability. Using cell-seeded high density collagen gels, we investigated the effect of two systems for AGE induction, ribose at low concentrations (30, 100, and 200 mM) over 15 days of culture and riboflavin (0.25 and 0.75 mM) induced with blue light for 40 seconds (riboflavin-465 nm). We found ribose and riboflavin-465 nm treatment produces fluorescent AGE quantities which match and/or exceed human fluorescent AGE levels for various tissues, ages, and diseases, without affecting cell viability or metabolism. Interestingly, a 40 second treatment of riboflavin-465 nm produced similar levels of fluorescent AGEs as 3 days of 100 mM ribose treatment. Riboflavin-465 nm is a promising method to trigger AGEs on demand <i>in vivo</i> or <i>in vitro</i> without impacting cell viability and offers potential for unraveling the mechanism of AGEs in age and diabetes related tissue damage.
DOI: 10.6084/m9.figshare.20055134
title: Sequencing data

description: This dataset provides data files to accompany the article Promoter methylation of <em>QKI</em> as a potential specific biomarker for early detection of colorectal cancer. <br> The data included methylation sequencing data of the <em>QKI </em>gene from our independent validation set, including 271 colorectal cancer tissue samples, 8 adenoma tissue samples, 9 polyp tissue samples, 24 adjacent normal tissue samples, 29 colorectal cancer peripheral blood leukocyte samples, 29 healthy controls peripheral blood leukocyte samples, and the cfDNA samples from 9 patients of colorectal cancer and 5 healthy controls. <br>
DOI: 10.6084/m9.figshare.20055134.v1
title: Sequencing data

description: This dataset provides data files to accompany the article Promoter methylation of <em>QKI</em> as a potential specific biomarker for early detection of colorectal cancer. <br> The data included methylation sequencing data of the <em>QKI </em>gene from our independent validation set, including 271 colorectal cancer tissue samples, 8 adenoma tissue samples, 9 polyp tissue samples, 24 adjacent normal tissue samples, 29 colorectal cancer peripheral blood leukocyte samples, 29 healthy controls peripheral blood leukocyte samples, and the cfDNA samples from 9 patients of colorectal cancer and 5 healthy controls. <br>
DOI: 10.5281/zenodo.3342157
title: PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11)

description: The PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11) is a corpus for the evaluation of automatic vandalism detectors for Wikipedia. For research purposes the corpus can be used free of charge. This corpus supplements the PAN-WVC-10, which features only English edits. Both corpora should be used to get more representative results. The corpus compiles 29949 edits on 24351 Wikipedia articles, among which 2813 vandalism edits have been identified. The corpus features 9985 English edits, 9990 German edits, and 9974 Spanish edits. To annotate the corpus we have used Amazon's Mechanical Turk; each edit was presented to a number of annotators who were asked to decide whether it is vandalism or regular, and the agreement of the annotators was analyzed in order to label an edit.
description: {"references": ["Martin Potthast and Teresa Holfeld. Overview of the 2nd International Competition on Wikipedia Vandalism Detection. In Vivien Petras, Pamela Forner, and Paul D. Clough, editors, Notebook Papers of CLEF 2011 Labs and Workshops, September 2011. ISBN 978-88-904810-1-7. ISSN 2038-4963.", "Benno Stein, Martin Potthast, Alberto Barr\u00f3n-Cede\u00f1o, Paolo Rosso, Efstathios Stamatatos, and Moshe Koppel. 4th International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN 2010). SIGIR Forum, 45 (1) : 45-48, June 2011."]}
DOI: 10.5281/zenodo.3342156
title: PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11)

description: The PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11) is a corpus for the evaluation of automatic vandalism detectors for Wikipedia. For research purposes the corpus can be used free of charge. This corpus supplements the PAN-WVC-10, which features only English edits. Both corpora should be used to get more representative results. The corpus compiles 29949 edits on 24351 Wikipedia articles, among which 2813 vandalism edits have been identified. The corpus features 9985 English edits, 9990 German edits, and 9974 Spanish edits. To annotate the corpus we have used Amazon's Mechanical Turk; each edit was presented to a number of annotators who were asked to decide whether it is vandalism or regular, and the agreement of the annotators was analyzed in order to label an edit.
description: {"references": ["Martin Potthast and Teresa Holfeld. Overview of the 2nd International Competition on Wikipedia Vandalism Detection. In Vivien Petras, Pamela Forner, and Paul D. Clough, editors, Notebook Papers of CLEF 2011 Labs and Workshops, September 2011. ISBN 978-88-904810-1-7. ISSN 2038-4963.", "Benno Stein, Martin Potthast, Alberto Barr\u00f3n-Cede\u00f1o, Paolo Rosso, Efstathios Stamatatos, and Moshe Koppel. 4th International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN 2010). SIGIR Forum, 45 (1) : 45-48, June 2011."]}
DOI: 10.5281/zenodo.3251771
title: Webis Crowd Paraphrase Corpus 2011 (Webis-CPC-11)

description: The Webis Crowd Paraphrase Corpus 2011 (Webis-CPC-11) contains 7,859 candidate paraphrases obtained from Mechanical Turk crowdsourcing. The corpus is made up of 4,067 accepted paraphrases, 3,792 rejected non-paraphrases, and the original texts. These samples have formed part of PAN 2010 international plagiarism detection competition, but were not previously available separate to rest of the competition data. We provide the dataset as a single folder in a Zip archive. Each paraphrase is represented by three files, containing the original text (e.g.: "1-original.txt"), the paraphrase text (e.g.: "1-paraphrase.txt"), and a file containing metadata (e.g.: "1-metadata.txt"), with information about the task identifier, task author identifier, time taken, and whether the paraphrase was accepted or rejected.
description: {"references": ["teven Burrows, Martin Potthast, and Benno Stein. Paraphrase Acquisition via Crowdsourcing and Machine Learning. Transactions on Intelligent Systems and Technology (ACM TIST), 4 (3) : 43:1-43:21, June 2013"]}
DOI: 10.5281/zenodo.3251770
title: Webis Crowd Paraphrase Corpus 2011 (Webis-CPC-11)

description: The Webis Crowd Paraphrase Corpus 2011 (Webis-CPC-11) contains 7,859 candidate paraphrases obtained from Mechanical Turk crowdsourcing. The corpus is made up of 4,067 accepted paraphrases, 3,792 rejected non-paraphrases, and the original texts. These samples have formed part of PAN 2010 international plagiarism detection competition, but were not previously available separate to rest of the competition data. We provide the dataset as a single folder in a Zip archive. Each paraphrase is represented by three files, containing the original text (e.g.: "1-original.txt"), the paraphrase text (e.g.: "1-paraphrase.txt"), and a file containing metadata (e.g.: "1-metadata.txt"), with information about the task identifier, task author identifier, time taken, and whether the paraphrase was accepted or rejected.
description: {"references": ["teven Burrows, Martin Potthast, and Benno Stein. Paraphrase Acquisition via Crowdsourcing and Machine Learning. Transactions on Intelligent Systems and Technology (ACM TIST), 4 (3) : 43:1-43:21, June 2013"]}
DOI: 10.5281/zenodo.3250095
title: PAN Plagiarism Corpus 2011 (PAN-PC-11)

description: The PAN plagiarism corpus 2011 (PAN-PC-11) is a corpus for the evaluation of automatic plagiarism detection algorithms. For research purposes the corpus can be used free of charge. The PAN-PC-11 contains documents in which plagiarism has been inserted automatically as well as documents in which plagiarism has been inserted manually. The former have been constructed using a so-called random plagiarist, a computer program which constructs plagiarism according to a number of parameters, while the latter have been obtained with crowdsourcing via Amazon's Mechanical Turk.
description: {"references": ["Benno Stein, Martin Potthast, Alberto Barr\u00f3n-Cede\u00f1o, Paolo Rosso, Efstathios Stamatatos, and Moshe Koppel. 4th International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN 2010). SIGIR Forum, 45 (1) : 45-48, June 2011."]}
DOI: 10.5281/zenodo.3250094
title: PAN Plagiarism Corpus 2011 (PAN-PC-11)

description: The PAN plagiarism corpus 2011 (PAN-PC-11) is a corpus for the evaluation of automatic plagiarism detection algorithms. For research purposes the corpus can be used free of charge. The PAN-PC-11 contains documents in which plagiarism has been inserted automatically as well as documents in which plagiarism has been inserted manually. The former have been constructed using a so-called random plagiarist, a computer program which constructs plagiarism according to a number of parameters, while the latter have been obtained with crowdsourcing via Amazon's Mechanical Turk.
description: {"references": ["Benno Stein, Martin Potthast, Alberto Barr\u00f3n-Cede\u00f1o, Paolo Rosso, Efstathios Stamatatos, and Moshe Koppel. 4th International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN 2010). SIGIR Forum, 45 (1) : 45-48, June 2011."]}
DOI: 10.5281/zenodo.3251557
title: Webis Clickbait Corpus 2016 (Webis-Clickbait-16)

description: The Webis Clickbait Corpus 2016 (Webis-Clickbait-16) comprises 2992 Twitter tweets sampled from top 20 news publishers as per retweets in 2014. The tweets have been manually annotated by three independent annotators with regard to whether they can be considered clickbait. A total of 767 tweets are considered clickbait by the majority of annotators. The majority vote of reviewers can be used as a ground truth to build clickbait detection technology. This corpus is the first of its kind and gives rise to the development of technology to tackle clickbait.
description: {"references": ["Martin Potthast, Sebastian K\u00f6psel, Benno Stein, and Matthias Hagen. Clickbait Detection. In Nicola Ferro et al, editors, Advances in Information Retrieval. 38th European Conference on IR Research (ECIR 2016) volume 9626 of Lecture Notes in Computer Science, pages 810-817, Berlin Heidelberg New York, March 2016. Springer"]}
DOI: 10.5281/zenodo.3251556
title: Webis Clickbait Corpus 2016 (Webis-Clickbait-16)

description: The Webis Clickbait Corpus 2016 (Webis-Clickbait-16) comprises 2992 Twitter tweets sampled from top 20 news publishers as per retweets in 2014. The tweets have been manually annotated by three independent annotators with regard to whether they can be considered clickbait. A total of 767 tweets are considered clickbait by the majority of annotators. The majority vote of reviewers can be used as a ground truth to build clickbait detection technology. This corpus is the first of its kind and gives rise to the development of technology to tackle clickbait.
description: {"references": ["Martin Potthast, Sebastian K\u00f6psel, Benno Stein, and Matthias Hagen. Clickbait Detection. In Nicola Ferro et al, editors, Advances in Information Retrieval. 38th European Conference on IR Research (ECIR 2016) volume 9626 of Lecture Notes in Computer Science, pages 810-817, Berlin Heidelberg New York, March 2016. Springer"]}
DOI: 10.5281/zenodo.3346490
title: Webis Clickbait Corpus 2017 (Webis-Clickbait-17)

description: The Webis Clickbait Corpus 2017 (Webis-Clickbait-17) comprises a total of 38,517 Twitter posts from 27 major US news publishers. In addition to the posts, information about the articles linked in the posts are included. The posts had been published between November 2016 and June 2017. To avoid publisher and topical biases, a maximum of ten posts per day and publisher were sampled. All posts were annotated on a 4-point scale [not click baiting (0.0), slightly click baiting (0.33), considerably click baiting (0.66), heavily click baiting (1.0)] by five annotators from Amazon Mechanical Turk. A total of 9,276 posts are considered clickbait by the majority of annotators. In terms of its size, this corpus outranges the Webis Clickbait Corpus 2016 by one order of magnitude. The corpus is divided into two logical parts, a training and a test dataset. The training dataset has been released in the course of the Clickbait Challenge and a download link is provided below. To allow for an objective evaulatuion of clickbait detection systems, the test dataset is available only through the Evaluation-as-a-Service platform TIRA at the moment. On TIRA, developers can deploy clickbait detection systems and execute them against the test dataset. The performance of the submitted systems can be viewed on the TIRA page of the Clickbait Challenge. To make working with the Webis Clickbait Corpus 2017 convenient, and to allow for its validation and replication, we are developing and sharing a number of software tags: Corpus Viewer. Our Django web service for exploring corpora. For importing the Webis Clickbait Corpus 2017 into the corpus viewer, we provide an appropriate configuration file. MTurk Manager. Our Django web service for conducting sophisticated crowd sourcing tasks on Amazon Mechanical Turk. The service allows to manage projects, upload batches of HITS, apply custom reviewing interfaces, and more. To make the clickbait crowd-sourcing task replicable, we share the worker template that we used to instruct the workers and to display the tweets. Also shared is a reviewing template that can be used to accept/reject assignments and to assess the quality of the received annotations quickly. Web Archiver. Software for archiving web pages as WARC files and reproducing them later on. This software can be used to open the WARC archives provided above. In addition to the corpus "clickbait17-train-170630.zip", we provide the original WARC archives of the articles that are linked in the posts. They are split in 5 archives that can be extracted separately.
DOI: 10.5281/zenodo.3254618
title: Webis Plagiarism Corpus 2008 (Webis-PC-08)

description: This corpus is outdated. Please use its successor PAN-PC-11: https://doi.org/10.5281/zenodo.3250095 The Webis plagiarism corpus 2008 (Webis-PC-08) is a corpus for the evaluation of automatic plagiarism detection algorithms. For research purposes the corpus can be used free of charge, however, since the documents in the corpus are not free of copyrights we need assurance that you have legal access to the ACM digital library.
DOI: 10.5281/zenodo.3254617
title: Webis Plagiarism Corpus 2008 (Webis-PC-08)

description: This corpus is outdated. Please use its successor PAN-PC-11: https://doi.org/10.5281/zenodo.3250095 The Webis plagiarism corpus 2008 (Webis-PC-08) is a corpus for the evaluation of automatic plagiarism detection algorithms. For research purposes the corpus can be used free of charge, however, since the documents in the corpus are not free of copyrights we need assurance that you have legal access to the ACM digital library.
DOI: 10.6084/m9.figshare.20055128
title: Longhorn beetles and predatory clerid beetles attracted to a blend of longhorn beetle pheromone compounds in a Central European oak forest (Coleoptera: Cerambycidae, Cleridae)

description: A blend of longhorn beetle pheromones was tested as a generic attractant for multiple longhorn beetle species in a Central European oak forest. Overall, 21 cerambycid species totalling 1,250 specimens were captured using two trap types. Panel traps captured more beetles than funnel traps. Significantly more adults of <em>Phymatodes testaceus</em> (L.) (Cerambycinae) and <em>Leiopus nebulosus</em> <em>nebulosus </em>(L.) (Lamiinae) were caught in baited traps compared to controls. Significant numbers of four other species were caught in panel traps but not funnel traps. For the cerambycine <em>Pyrrhidium sanguineum </em>(L.), significantly more beetles were caught in treatment traps than controls. For the cerambycine <em>Anaglyptus mysticus </em>(L.), and lepturines <em>Cortodera humeralis </em>(Schaller) and <em>Rhagium sycophanta </em>(Schrank), the numbers of beetles caught in treatment or control traps were similar, indicating no attraction to the lure blend. Adults of a predatory clerid beetle <em>Clerus mutillarius</em> F. were caught in significantly larger numbers by both baited trap types in comparison to controls, totalling 1,514 specimens. Antennae of both sexes of <em>C. mutillarius</em> showed significant responses to 3-hydroxyhexan-2-one and 2-methylbutan-1-ol compared to solvent controls, and antennae from males also responded significantly to <em>syn</em>-2,3-hexanediol. Strong attraction of <em>C. mutillarius</em> suggests eavesdropping on the pheromones of cerambycids and that such attractant baits, without traps, might be used to manipulate the local population density of predators in a push-pull biological control program targeting wood-boring insects.
DOI: 10.6084/m9.figshare.20055128.v2
title: Longhorn beetles and predatory clerid beetles attracted to a blend of longhorn beetle pheromone compounds in a Central European oak forest (Coleoptera: Cerambycidae, Cleridae)

description: A blend of longhorn beetle pheromones was tested as a generic attractant for multiple longhorn beetle species in a Central European oak forest. Overall, 21 cerambycid species totalling 1,250 specimens were captured using two trap types. Panel traps captured more beetles than funnel traps. Significantly more adults of <em>Phymatodes testaceus</em> (L.) (Cerambycinae) and <em>Leiopus nebulosus</em> <em>nebulosus </em>(L.) (Lamiinae) were caught in baited traps compared to controls. Significant numbers of four other species were caught in panel traps but not funnel traps. For the cerambycine <em>Pyrrhidium sanguineum </em>(L.), significantly more beetles were caught in treatment traps than controls. For the cerambycine <em>Anaglyptus mysticus </em>(L.), and lepturines <em>Cortodera humeralis </em>(Schaller) and <em>Rhagium sycophanta </em>(Schrank), the numbers of beetles caught in treatment or control traps were similar, indicating no attraction to the lure blend. Adults of a predatory clerid beetle <em>Clerus mutillarius</em> F. were caught in significantly larger numbers by both baited trap types in comparison to controls, totalling 1,514 specimens. Antennae of both sexes of <em>C. mutillarius</em> showed significant responses to 3-hydroxyhexan-2-one and 2-methylbutan-1-ol compared to solvent controls, and antennae from males also responded significantly to <em>syn</em>-2,3-hexanediol. Strong attraction of <em>C. mutillarius</em> suggests eavesdropping on the pheromones of cerambycids and that such attractant baits, without traps, might be used to manipulate the local population density of predators in a push-pull biological control program targeting wood-boring insects.
DOI: 10.6084/m9.figshare.20055128.v1
title: Untitled ItemLonghorn beetles and predatory clerid beetles attracted to a blend of longhorn beetle pheromone compounds in a Central European oak forest (Coleoptera: Cerambycidae, Cleridae)

description: A blend of longhorn beetle pheromones was tested as a generic attractant for multiple longhorn beetle species in a Central European oak forest. Overall, 21 cerambycid species totalling 1,250 specimens were captured using two trap types. Panel traps captured more beetles than funnel traps. Significantly more adults of <em>Phymatodes testaceus</em> (L.) (Cerambycinae) and <em>Leiopus nebulosus</em> <em>nebulosus </em>(L.) (Lamiinae) were caught in baited traps compared to controls. Significant numbers of four other species were caught in panel traps but not funnel traps. For the cerambycine <em>Pyrrhidium sanguineum </em>(L.), significantly more beetles were caught in treatment traps than controls. For the cerambycine <em>Anaglyptus mysticus </em>(L.), and lepturines <em>Cortodera humeralis </em>(Schaller) and <em>Rhagium sycophanta </em>(Schrank), the numbers of beetles caught in treatment or control traps were similar, indicating no attraction to the lure blend. Adults of a predatory clerid beetle <em>Clerus mutillarius</em> F. were caught in significantly larger numbers by both baited trap types in comparison to controls, totalling 1,514 specimens. Antennae of both sexes of <em>C. mutillarius</em> showed significant responses to 3-hydroxyhexan-2-one and 2-methylbutan-1-ol compared to solvent controls, and antennae from males also responded significantly to <em>syn</em>-2,3-hexanediol. Strong attraction of <em>C. mutillarius</em> suggests eavesdropping on the pheromones of cerambycids and that such attractant baits, without traps, might be used to manipulate the local population density of predators in a push-pull biological control program targeting wood-boring insects.
DOI: 10.25921/d4ea-ag75
title: EK80 Water Column Sonar Data Collected During SH2106
DOI: 10.6084/m9.figshare.20055179
title: Rumen cytochrome bd

description: cytochrome bd-related genes
DOI: 10.6084/m9.figshare.20055179.v1
title: Rumen cytochrome bd

description: cytochrome bd-related genes
DOI: 10.6084/m9.figshare.20055185.v1
title: 国界.shp

description: The data set is mainly the soil bulk density described
DOI: 10.6084/m9.figshare.20055185.v2
title: 国界.shp

description: The data set is mainly the soil bulk density described
DOI: 10.5281/zenodo.6634155
title: Semen and covid

description: The study was performed in Al-Hussein Teaching Hospital , during the September to November, 2021 and its involved 318 patients. The patients info including age, address, and vaccination. The sperm count, activity and morphology were detected by using Computer-assisted semen analysis CASA (Microptic-Spain) according to WHO manual.
DOI: 10.5281/zenodo.6634154
title: Semen and covid

description: The study was performed in Al-Hussein Teaching Hospital , during the September to November, 2021 and its involved 318 patients. The patients info including age, address, and vaccination. The sperm count, activity and morphology were detected by using Computer-assisted semen analysis CASA (Microptic-Spain) according to WHO manual.
DOI: 10.6084/m9.figshare.20051870
title: cho2021microscopic_seq-scope

description: cho2021microscopic_seq-scope