cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25318/3310026401-fra
title: Probabilité de la mise en œuvre de diverses mesures de protection lorsque cette entreprise retournera au travail sur place, selon les caractéristiques de l'entreprise

description: Probabilité que les entreprises mettent en œuvre diverses mesures de protection lorsque cette entreprise retournera au travail sur place à mesure que les restrictions liées à la COVID-19 seront assouplies, selon le code du Système de classification des industries de l'Amérique du Nord (SCIAN), l'effectif de l'entreprise, le type d'entreprise, activités commerciales et le propriétaire majoritaire.
DOI: 10.5281/zenodo.3985790
title: List of studies on Covid-19 identified in PubMed and excluded from our systematic review

description: In the course of our PubMed searches we identified and screened the title and abstract of a number of studies on Covid-19 that were finally excluded from our systematic review. This file will be updated regularly.
DOI: 10.5281/zenodo.3835784
title: List of studies on Covid-19 identified in PubMed and excluded from our systematic review

description: In the course of our PubMed searches we identified and screened the title and abstract of a number of studies on Covid-19 that were finally excluded from our systematic review. This file will be updated regularly.
DOI: 10.5281/zenodo.3828506
title: Dataset: Random forest models of ultra-low frequency magnetospheric wave power.

description: Predictive models of ground-based ultra-low frequency (ULF, 1-15 mHz) wave power, corresponding to magnetospheric waves. The series of decision tree ensembles (random forests) are dependent on solar wind properties, latitude and azimuthal angle around the Earth (magnetic local time, MLT).
DOI: 10.5281/zenodo.3828505
title: Dataset: Random forest models of ultra-low frequency magnetospheric wave power.

description: Predictive models of ground-based ultra-low frequency (ULF, 1-15 mHz) wave power, corresponding to magnetospheric waves. The series of decision tree ensembles (random forests) are dependent on solar wind properties, latitude and azimuthal angle around the Earth (magnetic local time, MLT).
DOI: 10.5281/zenodo.3985793
title: Chromosight benchmarks and processed data

description: Input data and scripts required to rerun chromosight's benchmarks and associated figures from the manuscript, as well as output results in text format. The record contains 3 tarballs corresponding to two different benchmarks and various processed files. Each tarball contains the scripts, input and output data of its benchmark: <strong>Performance benchmark:</strong> This benchmark is contained in "20200406_benchmark_chromosight_performance.tar.gz" and compares chromosight running time and RAM use with 2 other softwares. This benchmark is run on a real high resolution human Hi-C matrix with different subsampling values. Benchmark scripts are expected to be run on a regular laptop or desktop. <strong>Results benchmark:</strong> This benchmark is contained in "20200406_benchmark_chromosight_results.tar.gz" and assess chromosight's ability to detect chromatin loop patterns on Hi-C contact maps. Chromosight is compared to 4 other softwares. For each software, precision, recall (=sensitivity) and F1 scores are measured using 2000 small synthetic Hi-C matrices with known loop coordinates. Each software is run with a range of 50-200 parameter combinations for all data. Scripts to run this benchmark are written to run as a job array on a SLURM computing cluster to reduce compute time. <strong>Processed data files</strong> Intermediate and output files used throughout the manuscript. This includes contact matrices in cool format, genomic intervals in BED or BED2D format and loop calls from public data for different softwares.
DOI: 10.5517/ccdc.csd.cc21xfbr
title: CCDC 1904154: Experimental Crystal Structure Determination

description: Related Article: Ioan-Andrei Dascalu, Sergiu Shova, Dan George Dumitrescu, Gheorghe Roman, Bogdan-Ionel Bratanovici, Rodinel Ardeleanu, Vasile Lozan|2019|Polyhedron|170|463|doi:10.1016/j.poly.2019.05.066
DOI: 10.5517/ccdc.csd.cc21xfcs
title: CCDC 1904155: Experimental Crystal Structure Determination

description: Related Article: Ioan-Andrei Dascalu, Sergiu Shova, Dan George Dumitrescu, Gheorghe Roman, Bogdan-Ionel Bratanovici, Rodinel Ardeleanu, Vasile Lozan|2019|Polyhedron|170|463|doi:10.1016/j.poly.2019.05.066
DOI: 10.5517/ccdc.csd.cc21xfdt
title: CCDC 1904156: Experimental Crystal Structure Determination

description: Related Article: Ioan-Andrei Dascalu, Sergiu Shova, Dan George Dumitrescu, Gheorghe Roman, Bogdan-Ionel Bratanovici, Rodinel Ardeleanu, Vasile Lozan|2019|Polyhedron|170|463|doi:10.1016/j.poly.2019.05.066
DOI: 10.5517/ccdc.csd.cc2241ny
title: CCDC 1910519: Experimental Crystal Structure Determination

description: Related Article: Sandrine Kappler-Gratias, Léo Bucher, Nicolas Desbois, Yoann Rousselin, Kerstin Bystricky, Claude P. Gros, Franck Gallardo|2020|RSC Med. Chem.|11|783|doi:10.1039/D0MD00127A
DOI: 10.5517/ccdc.csd.cc24l788
title: CCDC 1983729: Experimental Crystal Structure Determination

description: Related Article: Chih-Chieh Wang, Jia-Hua Tsai, Szu-Yu Ke, Gene-Hsiang Lee, Yu-Chun Chuang, En-Che Yang|2020|Cryst.Growth Des.|20|5395|doi:10.1021/acs.cgd.0c00608
DOI: 10.5517/ccdc.csd.cc24l799
title: CCDC 1983730: Experimental Crystal Structure Determination

description: Related Article: Chih-Chieh Wang, Jia-Hua Tsai, Szu-Yu Ke, Gene-Hsiang Lee, Yu-Chun Chuang, En-Che Yang|2020|Cryst.Growth Des.|20|5395|doi:10.1021/acs.cgd.0c00608
DOI: 10.5517/ccdc.csd.cc24mzsk
title: CCDC 1985419: Experimental Crystal Structure Determination

description: Related Article: Jian Li, Fang Yang, Weiwei Hu, Bo Ren, Zi-Sheng Chen, Kegong Ji|2020|Chem.Commun.|56|9154|doi:10.1039/D0CC03285A
DOI: 10.5517/ccdc.csd.cc24s188
title: CCDC 1989309: Experimental Crystal Structure Determination

description: Related Article: Xialei Lv, Yaxiong Wang, Nengquan Li, Xiaosong Cao, Guohua Xie, Hong Huang, Cheng Zhong, Lei Wang, Chuluo Yang|2020|Chem.Eng.Journal|402|126173|doi:10.1016/j.cej.2020.126173
DOI: 10.5517/ccdc.csd.cc24s199
title: CCDC 1989310: Experimental Crystal Structure Determination

description: Related Article: Xialei Lv, Yaxiong Wang, Nengquan Li, Xiaosong Cao, Guohua Xie, Hong Huang, Cheng Zhong, Lei Wang, Chuluo Yang|2020|Chem.Eng.Journal|402|126173|doi:10.1016/j.cej.2020.126173
DOI: 10.5281/zenodo.3985568
title: A dataset of media realeases (Twitter, News and Comments, Youtube, Facebook) form Poland related to COVID-19 for open research

description: Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19), challenging public health mitigation strategies and possibly the political consensus. The widespread use of the traditional and social media on the Internet provides us with an invaluable source of information on societal dynamics during pandemics. IWith this dataset we aim to understand mechanisms of COVID-19 epidemic-related social behavior in Poland deploying methods of computational social science and digital epidemiology. We have collected and analyzed COVID-19 perception on the Polish language Internet during 15.01-31.07 and labeled data quantitatively (Twitter, Youtube, Articles) and qualitatively (Facebook, Articles and Comments of Article) in the Internet by infomediological approach. - manually coded 1,449 articles / Facebook posts from Lower Silesia (facebook_articles_lower_silesia.zip) and 111 texts from outside this region; -extracted 57,306 representative articles (articles_till_06_08.zip) in Polish using Eventregitry.org tool in language Polish and topic "Coronavirus" in article body; - extracted 1,015,199 (tweets_till_31_07_users.zip and tweets_till_31_07_text.zip) and Tweets from #Koronawirus in language Polish in Twitter. - collected 1,574 videos (youtube_comments_till_31_07.zip and youtube_movie.csv) with keyword: Koronawirus on YouTube and 247,575 comments on them; - We supplemented the media observations with an analysis of 244 social empirical studies on COVID-19 in Poland (empirical_studies.csv). Reports and analyzes and coding books can be found in Polish at: http://www.infodemia-koronawirusa.pl
description: {"references": ["Jarynowski A, W\u00f3jta-Kempa M, Belik V. TRENDS IN PERCEPTION OF COVID-19 IN POLISH INTERNET, Polish Epidemiological Review", "Jarynowski A, W\u00f3jta-Kempa M, P\u0142atek D, Krzowski \u0141, Belik V. Spatial Diversity of COVID-19 Cases in Poland Explained by Mobility Patterns - Preliminary Results 2020; http://dx.doi.org/10.2139/ssrn.3621152"]}
DOI: 10.25387/g3.11829177.v1
title: Supplemental Material for Cui et al., 2020

description: Supplemental material
DOI: 10.25387/g3.11829177
title: Supplemental Material for Cui et al., 2020

description: Supplemental material
DOI: 10.5281/zenodo.3985811
title: Dataset for the paper: "The Gas Accessible Membrane Electrode (GAME): A Versatile Platform for Elucidating Electrocatalytic Processes Using Real Time and In Situ Hyphenated Electrochemical Techniques"

description: The data in this spreadsheet was used to produce the figures in the paper Authors: Guohui Zhang, Anthony Kucernak Title: The Gas Accessible Membrane Electrode (GAME): A Versatile Platform for Elucidating Electrocatalytic Processes Using Real Time and In Situ Hyphenated Electrochemical Techniques Journal: ACS Catalysis, 2020 DOI: 10.1021/acscatal.0c02433 Please cite the above reference if you wish to use this data<br> DOI of data:10.5281/zenodo.3985811
DOI: 10.5281/zenodo.3985810
title: Dataset for the paper: "The Gas Accessible Membrane Electrode (GAME): A Versatile Platform for Elucidating Electrocatalytic Processes Using Real Time and In Situ Hyphenated Electrochemical Techniques"

description: The data in this spreadsheet was used to produce the figures in the paper Authors: Guohui Zhang, Anthony Kucernak Title: The Gas Accessible Membrane Electrode (GAME): A Versatile Platform for Elucidating Electrocatalytic Processes Using Real Time and In Situ Hyphenated Electrochemical Techniques Journal: ACS Catalysis, 2020 DOI: 10.1021/acscatal.0c02433 Please cite the above reference if you wish to use this data<br> DOI of data:10.5281/zenodo.3985811
DOI: 10.5281/zenodo.3954465
title: Shadow-wall lithography of ballistic superconductor-semiconductor quantum devices

description: This repository contains data sets that support the conclusions and figures in the manuscript "Shadow-wall lithography of ballistic superconductor-semiconductor quantum devices". The Jupyter notebook "Manuscript figures.ipynb" contains all the necessary scripts to generate the figures. The measurement data is contained in the "Data" folder.
DOI: 10.6084/m9.figshare.12808310
title: Vrindavani_genotype

description: BovineSNP50K genotypes of 96 crossbred Vrindavani cattle collected from ICAR-IVRI farm at Bareilly, India.
DOI: 10.6084/m9.figshare.12808310.v2
title: Vrindavani_genotype

description: BovineSNP50K genotypes of 96 crossbred Vrindavani cattle collected from ICAR-IVRI farm at Bareilly, India.
DOI: 10.6084/m9.figshare.12808310.v1
title: Vrindavani_genotype

description: BovineSNP50K genotypes of 96 crossbred Vrindavani cattle collected from ICAR-IVRI farm at Bareilly, India.
DOI: 10.5281/zenodo.3985837
title: Models from: Exploring ensemble applications for multi-sequence myocardial pathology segmentation

description: Trained models for the MyoPS2020 challenge http://www.sdspeople.fudan.edu.cn/zhuangxiahai/0/MyoPS20/ As described in the publication: "Exploring ensemble applications for multi-sequence myocardial pathology segmentation" Source code available at: https://github.com/chfc-cmi/miccai2020-myops
DOI: 10.5281/zenodo.3985836
title: Models from: Exploring ensemble applications for multi-sequence myocardial pathology segmentation

description: Trained models for the MyoPS2020 challenge http://www.sdspeople.fudan.edu.cn/zhuangxiahai/0/MyoPS20/ As described in the publication: "Exploring ensemble applications for multi-sequence myocardial pathology segmentation" Source code available at: https://github.com/chfc-cmi/miccai2020-myops
DOI: 10.15468/pjnada
title: Two new species of Liodessus Guignot, 1939 diving beetles from Northern Peru (Coleoptera, Dytiscidae, Hydroporinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Balke, Michael, Megna, Yoandri S., Zenteno, Nilver, Figueroa, Luis, Hendrich, Lars (2020): Two new species of Liodessus Guignot, 1939 diving beetles from Northern Peru (Coleoptera, Dytiscidae, Hydroporinae). Alpine Entomology 4: 173-178, DOI: http://dx.doi.org/10.3897/alpento.4.55139, URL: http://dx.doi.org/10.3897/alpento.4.55139
DOI: 10.5517/ccdc.csd.cc244rwy
title: CCDC 1970790: Experimental Crystal Structure Determination

description: Related Article: Martin Rentschler, Sirma Iglesias, Marie-Ann Schmid, Cunming Liu, Stefanie Tschierlei, Wolfgang Frey, Xiaoyi Zhang, Michael Karnahl, Dooshaye Moonshiram|2020|Chem.-Eur.J.|26|9527|doi:10.1002/chem.201905601
DOI: 10.15468/ahreee
title: A new species of the genus Acanthosaura (Squamata, Agamidae) from Yunnan, China, with comments on its conservation status

description: This dataset contains the digitized treatments in Plazi based on the original journal article Liu, Shuo, Hou, Mian, Mo, Mingzhong, Rao, Dingqi (2020): A new species of the genus Acanthosaura (Squamata, Agamidae) from Yunnan, China, with comments on its conservation status. ZooKeys 959: 113-135, DOI: http://dx.doi.org/10.3897/zookeys.959.54601, URL: http://dx.doi.org/10.3897/zookeys.959.54601
DOI: 10.5517/ccdc.csd.cc247jsq
title: CCDC 1973453: Experimental Crystal Structure Determination

description: Related Article: Ismail Ismail, Zhuoyue Chen, Lu Sun, Xiuru Ji, Haishun Ye, Xueying Kang, Haojie Huang, Haibin Song, Sarah G. Bolton, Zhen Xi, Michael D. Pluth, Long Yi|2020|Chemical Science|11|7823|doi:10.1039/D0SC01518K
DOI: 10.15468/k3rqwc
title: Eidophasia assmanni sp. nov., the first alpine representative of the genus, detected in the Russian Altai Mountains (Lepidoptera, Plutellidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Huemer, Peter, Sohn, Jae-Cheon (2020): Eidophasia assmanni sp. nov., the first alpine representative of the genus, detected in the Russian Altai Mountains (Lepidoptera, Plutellidae). ZooKeys 959: 99-111, DOI: http://dx.doi.org/10.3897/zookeys.959.54259, URL: http://dx.doi.org/10.3897/zookeys.959.54259
DOI: 10.5517/ccdc.csd.cc2492sb
title: CCDC 1974941: Experimental Crystal Structure Determination

description: Related Article: Justin T. Miller, Yixin Ren, Sheng Li, Kui Tan, Gregory McCandless, Christine Jacob, Zheng Wu, Ching-Wu Chu, Bing Lv, Michael C. Biewer, Mihaela C. Stefan|2020|Inorg.Chem.|59|10379|doi:10.1021/acs.inorgchem.0c00234
DOI: 10.5517/ccdc.csd.cc2492tc
title: CCDC 1974942: Experimental Crystal Structure Determination

description: Related Article: Justin T. Miller, Yixin Ren, Sheng Li, Kui Tan, Gregory McCandless, Christine Jacob, Zheng Wu, Ching-Wu Chu, Bing Lv, Michael C. Biewer, Mihaela C. Stefan|2020|Inorg.Chem.|59|10379|doi:10.1021/acs.inorgchem.0c00234
DOI: 10.5517/ccdc.csd.cc2492vd
title: CCDC 1974943: Experimental Crystal Structure Determination

description: Related Article: Justin T. Miller, Yixin Ren, Sheng Li, Kui Tan, Gregory McCandless, Christine Jacob, Zheng Wu, Ching-Wu Chu, Bing Lv, Michael C. Biewer, Mihaela C. Stefan|2020|Inorg.Chem.|59|10379|doi:10.1021/acs.inorgchem.0c00234
DOI: 10.5517/ccdc.csd.cc24kfgm
title: CCDC 1982960: Experimental Crystal Structure Determination

description: Related Article: Moumita Chakraborty, Antu Mondal, Shyamal Kumar Chattopadhyay|2020|New J.Chem.|44|12916|doi:10.1039/D0NJ00719F
DOI: 10.15468/q7sj4b
title: Blakealtica, a new genus of flea beetles (Coleoptera, Chrysomelidae, Galerucinae, Alticini) from the Dominican Republic

description: This dataset contains the digitized treatments in Plazi based on the original journal article Viswajyothi, Keezhpattillam, Konstantinov, Alexander S. (2020): Blakealtica, a new genus of flea beetles (Coleoptera, Chrysomelidae, Galerucinae, Alticini) from the Dominican Republic. ZooKeys 959: 1-16, DOI: http://dx.doi.org/10.3897/zookeys.959.53415, URL: http://dx.doi.org/10.3897/zookeys.959.53415
DOI: 10.25387/g3.12732782
title: Supplemental Material for Rode, Courtier-Orgogozo and Debarre, 2020

description: Tables S1 - S3, Figures S1 - S8.<br>
DOI: 10.25387/g3.12732782.v2
title: Supplemental Material for Rode, Courtier-Orgogozo and Debarre, 2020

description: Tables S1 - S3, Figures S1 - S8.<br>
DOI: 10.25387/g3.12732782.v1
title: Supplemental Material for Rode, Courtier-Orgogozo and Debarre, 2020

description: Tables S1 - S3, Figures S1 - S8.<br>
DOI: 10.5281/zenodo.3952415
title: SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles

description: This dataset contains the files and annotations for SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles. The task was composed by two subtasks: span identification (SI) and technique classification (TC). This dataset includes the following: The text files for training, development, and testing sets for both the SI and the TC tasks. The gold-standard files for the training sets, for both the SI and the TC task Our propaganda identification initiative remains active. We keep a live leader-board reporting the performance of models submited up to date. <strong>Reference</strong> Giovanni Da San Martino, Alberto Barrón-Cedeño, Henning Wachsmuth, Rostislav Petrov, and Preslav Nakov. 2020. Task 11: Detection of Propaganda Techniques in News Articles. In Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020). Barcelona, Spain (2020) <pre><code>@InProceedings{SemEval20-11-DaSanMartino, author = "Da San Martino, Giovanni and Barr\'{o}n-Cede\~no, Alberto and Wachsmuth, Henning and Petrov, Rostislav and Nakov, Preslav", title = "{SemEval}-2020 Task 11: {D}etection of Propaganda Techniques in News Articles", pages = "", abstract = "We describe the outcome of the SemEval 2020 Task 11 on the detection of propaganda in news articles. We present two tasks. In the first task, systems are asked to identify specific text spans in a free text where propaganda is being applied. In the second task, systems are asked to identify the propaganda technique being applied in a text span. We describe the construction of the evaluation framework (dataset and evaluation metrics) as well as the approaches explored by the different participants. ", crossref = "SemEval20" }</code></pre>
description: {"references": ["Giovanni Da San Martino, Alberto Barr\u00f3n-Cede\u00f1o, Henning Wachsmuth, Rostislav Petrov, and Preslav Nakov. 2020. Task 11: Detection of Propaganda Techniques in News Articles. In Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020). Barcelona, Spain (2020)"]}
DOI: 10.5281/zenodo.3952414
title: SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles

description: This dataset contains the files and annotations for SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles. The task was composed by two subtasks: span identification (SI) and technique classification (TC). This dataset includes the following: The text files for training, development, and testing sets for both the SI and the TC tasks. The gold-standard files for the training sets, for both the SI and the TC task Our propaganda identification initiative remains active. We keep a live leader-board reporting the performance of models submited up to date. <strong>Reference</strong> Giovanni Da San Martino, Alberto Barrón-Cedeño, Henning Wachsmuth, Rostislav Petrov, and Preslav Nakov. 2020. Task 11: Detection of Propaganda Techniques in News Articles. In Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020). Barcelona, Spain (2020) <pre><code>@InProceedings{SemEval20-11-DaSanMartino, author = "Da San Martino, Giovanni and Barr\'{o}n-Cede\~no, Alberto and Wachsmuth, Henning and Petrov, Rostislav and Nakov, Preslav", title = "{SemEval}-2020 Task 11: {D}etection of Propaganda Techniques in News Articles", pages = "", abstract = "We describe the outcome of the SemEval 2020 Task 11 on the detection of propaganda in news articles. We present two tasks. In the first task, systems are asked to identify specific text spans in a free text where propaganda is being applied. In the second task, systems are asked to identify the propaganda technique being applied in a text span. We describe the construction of the evaluation framework (dataset and evaluation metrics) as well as the approaches explored by the different participants. ", crossref = "SemEval20" }</code></pre>
description: {"references": ["Giovanni Da San Martino, Alberto Barr\u00f3n-Cede\u00f1o, Henning Wachsmuth, Rostislav Petrov, and Preslav Nakov. 2020. Task 11: Detection of Propaganda Techniques in News Articles. In Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020). Barcelona, Spain (2020)"]}
DOI: 10.34740/kaggle/dsv/1419367
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.3985848
title: pull-out experiments on small-scale wood logs

description: This data-set contains results from pull-out experiments on small-scale Salix cuttings. The folder "uprooting tests" contains the values of the uprooting force recorded over time. Values of the total root length of each sample are illustrated in an excel file: "max_uprooting_force-root length". The values of the total root surface area of each sample can be found in the folder: "root surface area". Data are divided according to the uprooting time. Data about the above-ground biomass of the samples can be found in the files excel: "cuttings_growth" and "stem_length-volume".
DOI: 10.5281/zenodo.3985847
title: pull-out experiments on small-scale wood logs

description: This data-set contains results from pull-out experiments on small-scale Salix cuttings. The folder "uprooting tests" contains the values of the uprooting force recorded over time. Values of the total root length of each sample are illustrated in an excel file: "max_uprooting_force-root length". The values of the total root surface area of each sample can be found in the folder: "root surface area". Data are divided according to the uprooting time. Data about the above-ground biomass of the samples can be found in the files excel: "cuttings_growth" and "stem_length-volume".
DOI: 10.5281/zenodo.3985882
title: The evaluation dataset of the AI composition recognition competition, CSMT2020

description: The evaluation dataset contains 4000 MIDI files with exact configurations of development dataset with two exceptions: 1) A number of melodies composed by human composers are added, some of which are published, and some of which are composed for this competition. The music style of the human composed melodies are the same as the styles of music in the training set. This was confirmed by musicologists. 2) There are a number of melodies generated by algorithms with minor algorithmic or parameter changes compared to the algorithms in the development dataset. The development dataset: https://zenodo.org/record/3944685#.Xza9DegzY2x The website of the challenge: http://www.csmcw-csmt.cn/data/2020/ai-composition-recognition2020 (Chinese instruction) https://ai-composition-recognition2020.github.io/english.html (English instruction)