cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19310621
title: Seismic loss dynamics in three Asian megacities using a macro-level approach based on socioeconomic exposure indicators

description: Changes in the Grid-Level Average Annual Loss and Probable Maximum Loss from Present to Future in Jakarta, Metro Manila and Istanbul
DOI: 10.34740/kaggle/dsv/3367548
title: Air Quality Index (by cities)
DOI: 10.5281/zenodo.6387895
title: List of papers

description: We provide the list of papers used to perform the review named:"Plant disease prediction using Deep Learning: A systematic literature review"
DOI: 10.5281/zenodo.5716853
title: List of papers

description: We provide the list of papers used to perform the review named:"Plant disease prediction using Deep Learning: A systematic literature review"
DOI: 10.5281/zenodo.5847508
title: Emoji Gestures in Russian Tweets: Moscow

description: The dataset consists of 48 838 tweets each of them contains one of the 31 gesture emoji (different hand configurations) and its skin tone modifier options (e.g. 🙏🙏🏿🙏🏾🙏🏽🙏🏼🙏🏻), and posted within 50km from Moscow, Russia, in Russian, during May-August 2021. The dataset can be used to investigate the use of gesture emoji by Russian users of the Twitter platform. Python libraries used for collecting tweets and preprocessing: tweepy, re, preprocessor, emoji, regex, string, nltk. The dataset contains 11 columns: preprocessed preprocessed text of the tweet (4 steps) all_emoji lists all emoji in a given tweet hashtags lists all hashtags in a given tweet user_encoded encoded Twitter user name: the first 3 characters of the user name and the first 3 characters of the user's location location_encoded location of the user: "moscow", "moscow_region", or "other" mention_present checks whether each tweet contains mentions url_present checks whether each tweet contains url preprocess_tweet preprocessing step 1: tokenizing mentions, urls, and hashtags lowercase_tweet preprocessing step 2: lowercasing remove_punct_tweet preprocessing step 3: removing punctuation tokenize_tweet preprocessing step 4: tokenizing The further information on the research project can be found here: https://github.com/mzhukovaucsb/emoji_gestures/
DOI: 10.5281/zenodo.5847505
title: Emoji Gestures in English Tweets: California

description: The dataset consists of 479 193 tweets each of them contains one of the 31 gesture emoji (different hand configurations) and its skin tone modifier options (e.g. 🙏🙏🏿🙏🏾🙏🏽🙏🏼🙏🏻), posted within 250km from San Jose, CA and within 200km from Los Angeles, CA, in English, during May-August 2021. The dataset can be used to investigate the use of gesture emoji by English-speaking California Twitter users. Python libraries used for collecting tweets and preprocessing: tweepy, re, preprocessor, emoji, regex, string, nltk. The dataset contains 11 columns: preprocessed preprocessed text of the tweet (4 steps) all_emoji lists all emoji in a given tweet hashtags lists all hashtags in a given tweet user_encoded encoded Twitter user name: the first 3 characters of the user name and the first 3 characters of the user's location location_encoded location of the user: "los_angeles", "san_diego", "san_jose", "san_francisco", "fresno", "long_beach", "sacramento", "oakland", "bakersfield", "anaheim", or "other" mention_present checks whether each tweet contains mentions url_present checks whether each tweet contains url preprocess_tweet preprocessing step 1: tokenizing mentions, urls, and hashtags lowercase_tweet preprocessing step 2: lowercasing remove_punct_tweet preprocessing step 3: removing punctuation tokenize_tweet preprocessing step 4: tokenizing The further information on the research project can be found here: https://github.com/mzhukovaucsb/emoji_gestures/
DOI: 10.5281/zenodo.6387953
title: Outputs of the Jupyter Notebook - Tree crown delineation using detectreeRGB

description: The dataset contains the outputs of the notebook "Tree crown detection using DeepForest" published in The Environmental Data Science Book. <strong>Contributions</strong> <em>Notebook</em> Sebastian H. M. Hickman (author), University of Cambridge, @shmh40 Alejandro Coca-Castro (reviewer), The Alan Turing Institute, @acocac <em>Modelling codebase</em> Sebastian H. M. Hickman (author), University of Cambridge @shmh40 James G. C. Ball (contributor), University of Cambridge @PatBall1 David A. Coomes (contributor), University of Cambridge Toby Jackson (contributor), University of Cambridge
DOI: 10.5281/zenodo.6387952
title: Outputs of the Jupyter Notebook - Tree crown delineation using detectreeRGB

description: The dataset contains the outputs of the notebook "Tree crown detection using DeepForest" published in The Environmental Data Science Book. <strong>Contributions</strong> <em>Notebook</em> Sebastian H. M. Hickman (author), University of Cambridge, @shmh40 Alejandro Coca-Castro (reviewer), The Alan Turing Institute, @acocac <em>Modelling codebase</em> Sebastian H. M. Hickman (author), University of Cambridge @shmh40 James G. C. Ball (contributor), University of Cambridge @PatBall1 David A. Coomes (contributor), University of Cambridge Toby Jackson (contributor), University of Cambridge
DOI: 10.5281/zenodo.6115471
title: Dataset: digital photographs of specimens in manuscript entitled Taxonomic revision of the mydas-fly genera Eremohaplomydas Bequaert, 1959, Haplomydas Bezzi, 1924, and Lachnocorynus Hesse, 1969 (Insecta: Diptera: Mydidae)

description: This is the original files containing the information published in digital specimens and photo records here in Zenodo.
DOI: 10.5281/zenodo.6115470
title: Dataset: digital photographs of specimens in manuscript entitled Taxonomic revision of the mydas-fly genera Eremohaplomydas Bequaert, 1959, Haplomydas Bezzi, 1924, and Lachnocorynus Hesse, 1969 (Insecta: Diptera: Mydidae)

description: This is the original files containing the information published in digital specimens and photo records here in Zenodo.
DOI: 10.6084/m9.figshare.19426721.v1
title: Genotype specific PEP - Fasta files

description: Genotype specific protein fasta files
DOI: 10.5281/zenodo.6383513
title: Data from: Lianas decelerate tropical forest thinning during succession

description: The well-established pattern of forest thinning during succession predicts an<br> increase in mean tree biomass with decreasing tree density. The forest thinning<br> pattern is commonly assumed to be driven solely by tree-tree competition. The<br> presence of non-tree competitors could alter thinning trajectories, thus<br> altering the rate of forest succession and carbon uptake. We used a large-scale<br> liana removal experiment over 7 years in a 60-to-70-year-old Panamanian forest<br> to test the hypothesis that lianas reduce the rate of forest thinning during<br> succession. We found that lianas slowed forest thinning by reducing tree growth,<br> not by altering tree recruitment or mortality. Without lianas, trees grew and<br> presumably competed more, ultimately reducing tree density while increasing mean<br> tree biomass. Our findings challenge the assumption that forest thinning is<br> driven solely by tree-tree interactions; instead, they demonstrate that<br> competition from other growth forms, such as lianas, slow forest thinning and<br> ultimately delay forest succession.<br>
description: The file metadata.txt contains the details regarding each dataset and code. Please refer to the corresponding paper published in Ecology Letters for further details. Financial support was provided by NSF-DEB 1019436, NSF-DEB 1822473, NSF-IOS 1558093, and NSF-DEB 2001799.
DOI: 10.21227/mtvm-vd90
title: Robotic Arm in a Mocap System

description: Test of a robotic arm with a revolute joint in a MoCap system
DOI: 10.6084/m9.figshare.19424015.v1
title: Neocortical Localization and Thalamocortical Modulation of Neuronal Hyperexcitability contribute to Fragile X Syndrome: Source Data for Figures

description: Source data for manuscript as requested by publisher.
DOI: 10.6084/m9.figshare.19424015.v2
title: Neocortical Localization and Thalamocortical Modulation of Neuronal Hyperexcitability contribute to Fragile X Syndrome: Source Data for Figures and Statistics

description: Source data for manuscript as requested by publisher.
DOI: 10.5281/zenodo.4479845
title: Arctic maritime cyclone distribution and trends in the ERA5

description: This dataset supplements our paper published in the AMS Journal of Applied Meteorology and Climatology (JAMC) under the same title. The repository includes the cyclone tracks, the HST case study, and the delineation for different Arctic sea sections. For any questions, please contact Zihan Chen (via zihan_chen@alumni.brown.edu).
DOI: 10.5281/zenodo.4479844
title: Arctic maritime cyclone distribution and trends in the ERA5

description: This dataset supplements our paper published in the AMS Journal of Applied Meteorology and Climatology (JAMC) under the same title. The repository includes the cyclone tracks, the HST case study, and the delineation for different Arctic sea sections. For any questions, please contact Zihan Chen (via zihan_chen@alumni.brown.edu).
DOI: 10.3886/e113621v1-113440
title: Replication data for: The Impact of Women's Health Clinic Closures on Preventive Care

description: We examine the impact of women's health clinic closures on women's preventive care use in Texas and Wisconsin using a unique policy context, data on clinic street addresses, and confidential respondent ZIP codes from the Behavioral Risk Factor Surveillance System. From a within-ZIP-code analysis, we conclude that an increase of 100 miles to the nearest clinic results in a decrease in the annual utilization rate of a clinical breast exam by 11 percent, a mammogram by 18 percent, and a Pap test by 14 percent. These estimates are generally larger for women of lower educational attainment.
DOI: 10.6084/m9.figshare.3761562.v2170
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.5281/zenodo.6388030
title: Data sets and models for the Deep API Learning Revisited paper

description: Training and test data for the machine learning experiments described in the paper Deep API Learning Revisited paper. Trained models are also included. Deep API Learning Revisited paper: https://doi.org/10.1145/3524610.3527872 GitHub repository: https://github.com/hapsby/deepAPIRevisited
description: {"references": ["Gu et al. (2016) Deep API Learning, https://doi.org/10.1145/2950290.2950334"]}
DOI: 10.5281/zenodo.6388029
title: Data sets and models for the Deep API Learning Revisited paper

description: Training and test data for the machine learning experiments described in the paper Deep API Learning Revisited paper. Trained models are also included. Deep API Learning Revisited paper: https://doi.org/10.1145/3524610.3527872 GitHub repository: https://github.com/hapsby/deepAPIRevisited
description: {"references": ["Gu et al. (2016) Deep API Learning, https://doi.org/10.1145/2950290.2950334"]}
DOI: 10.5281/zenodo.6387471
title: VMP_HP-ext

description: The VML-HP-ext collection contains 715 page images excerpted from 171 different manuscripts covering 14 medieval writing Hebrew styles, accompanied by their hard and soft GT labels. We also provide the official split of the VML-HP-ext into training, typical test, and blind test sets. <br> The typical test set includes unseen pages of the manuscripts from the training set. While training and typical test sets are disjoint on the page level, they do share the same set of manuscripts. Therefore, we also provide the blind test set, which consists of manuscripts that do not appear in the training set. The blind test set imitates a real-life scenario, where scholars would like to obtain a classification for a previously unseen document.
description: For more details, please refer to [1]. When using this dataset in research work, please cite [1]. [1] A.Droby, D. Vasyutinsky Shapira, I. Rabaev, B. Kurar Barakat, and J. El-Sana. Hard and Soft Labeling for Hebrew Paleography: A Case Study. Accepted to the 15th IAPR International Workshop on Document Analysis System (https://das2022.univ-lr.fr/index.php/)
DOI: 10.5281/zenodo.6386398
title: Computer Code; Raw Image_Mangoes

description: Exporting mangoes to foreign countries while maintaining quality is a challenge for distributors. The quality and maturity of mangoes are inhomogeneous, even when mangoes are harvested from the same tree at the same time. While quality affects the product value at the time of harvest, maturity affects the product value over time after harvest. The maturity of mangoes also greatly affects the storage and transport time. This data is collected in Vietnam with many mango cultivars and used to train machine learning models for the automatic classify mango system.
DOI: 10.5281/zenodo.6386397
title: Computer Code; Raw Image_Mangoes

description: Exporting mangoes to foreign countries while maintaining quality is a challenge for distributors. The quality and maturity of mangoes are inhomogeneous, even when mangoes are harvested from the same tree at the same time. While quality affects the product value at the time of harvest, maturity affects the product value over time after harvest. The maturity of mangoes also greatly affects the storage and transport time. This data is collected in Vietnam with many mango cultivars and used to train machine learning models for the automatic classify mango system.
DOI: 10.5281/zenodo.6386592
title: Genetic and immunological evaluation of children with inborn errors of immunity and hypoxemic COVID-19 pneumonia

description: <strong><em>Background:</em></strong> SARS-CoV-2 has infected more than 450 million people around the world. In about 10% of cases, the infection leads to hypoxemic pneumonia, which is much rarer in children, while multisystem inflammation is seen almost only in children. <strong><em>Methods:</em></strong> We evluated 31 young patients (0.5-19 years) who had both pre-existing inborn errors of immunity (IEI) and were later diagnosed with COVID-19 complications. Whole-exome sequencing was performed, SARS-CoV-2 specific antibodies and autoantibody against type I interferons were measured and plasma inflammatory factors were profiled. We also reviewed COVID-19 disease severity and outcome in IEI patients in the literature. <strong><em>Results:</em></strong> A potential genetic cause of the IEI was identified in 28 patients (90.3%). The IgM and IgG-specific antibody response against the spike protein of the virus was positive in 14 (66.6%) of the IEI patients tested. Autoantibodies neutralizing type I interferons were identified in the plasma of two patients (6.8% of tested samples). Five patients fulfilled the diagnostic criteria of multisystem inflammatory syndrome in children (MIS-C). Eleven patients (35.4%) died due to COVID-19 complications showing a 3000 fold higher mortality rate compared to normal COVID-19 death rate in children (0.01%). For the additional 696 IEI patients reported till date, severe presentation of COVID-19 was observed in 23.3% of cases. Furthermore, a 5-fold higher mortality rate was observed, when compared with global infection-fatality reports. <strong><em>Conclusions:</em></strong> Elucidating the genetic basis of IEI patients with severe/critical COVID-19 may help to better understand the human innate and adaptive immune response against SARS-CoV-2, which may assist to develop better preventive and therapeutic strategies.
DOI: 10.5281/zenodo.6386591
title: Genetic and immunological evaluation of children with inborn errors of immunity and hypoxemic COVID-19 pneumonia

description: <strong><em>Background:</em></strong> SARS-CoV-2 has infected more than 450 million people around the world. In about 10% of cases, the infection leads to hypoxemic pneumonia, which is much rarer in children, while multisystem inflammation is seen almost only in children. <strong><em>Methods:</em></strong> We evluated 31 young patients (0.5-19 years) who had both pre-existing inborn errors of immunity (IEI) and were later diagnosed with COVID-19 complications. Whole-exome sequencing was performed, SARS-CoV-2 specific antibodies and autoantibody against type I interferons were measured and plasma inflammatory factors were profiled. We also reviewed COVID-19 disease severity and outcome in IEI patients in the literature. <strong><em>Results:</em></strong> A potential genetic cause of the IEI was identified in 28 patients (90.3%). The IgM and IgG-specific antibody response against the spike protein of the virus was positive in 14 (66.6%) of the IEI patients tested. Autoantibodies neutralizing type I interferons were identified in the plasma of two patients (6.8% of tested samples). Five patients fulfilled the diagnostic criteria of multisystem inflammatory syndrome in children (MIS-C). Eleven patients (35.4%) died due to COVID-19 complications showing a 3000 fold higher mortality rate compared to normal COVID-19 death rate in children (0.01%). For the additional 696 IEI patients reported till date, severe presentation of COVID-19 was observed in 23.3% of cases. Furthermore, a 5-fold higher mortality rate was observed, when compared with global infection-fatality reports. <strong><em>Conclusions:</em></strong> Elucidating the genetic basis of IEI patients with severe/critical COVID-19 may help to better understand the human innate and adaptive immune response against SARS-CoV-2, which may assist to develop better preventive and therapeutic strategies.
DOI: 10.5281/zenodo.6385595
title: Comparació Cobertura Autos

description: <pre>El dataset conté informació sobre diferents cobertures i garanties que cobreix cada paquet d'assegurances d'automòbil ofert per cada companyia d'assegurances.</pre>
DOI: 10.5281/zenodo.6385594
title: Comparació Cobertura Autos

description: <pre>El dataset conté informació sobre diferents cobertures i garanties que cobreix cada paquet d'assegurances d'automòbil ofert per cada companyia d'assegurances.</pre>
DOI: 10.5281/zenodo.6385226
title: COVD-19 Pandemic coverage in the Greek media

description: Reasearch conducted by the Laboratory for Social Rearch in the Media, Communication and Media Department, University of Athens. The research was conducted during the spring of 2020 and concerns the coverage of the COVID-19 pandemic first wave by the Greek media (television news bulletins and news sites). Professor George Pleios designed the research, Stamatis Poulakidakos (Laboratory teaching Staff) was responsible for the statistical analysis, while six researchers took part in the project.
DOI: 10.5281/zenodo.6385225
title: COVD-19 Pandemic coverage in the Greek media

description: Reasearch conducted by the Laboratory for Social Rearch in the Media, Communication and Media Department, University of Athens. The research was conducted during the spring of 2020 and concerns the coverage of the COVID-19 pandemic first wave by the Greek media (television news bulletins and news sites). Professor George Pleios designed the research, Stamatis Poulakidakos (Laboratory teaching Staff) was responsible for the statistical analysis, while six researchers took part in the project.
DOI: 10.5281/zenodo.6383935
title: Raw Data of Mangoes; Computer Code

description: Exporting mangoes to foreign countries while maintaining quality is a challenge for distributors. The quality and maturity of mangoes are inhomogeneous, even when mangoes are harvested from the same tree at the same time. While quality affects the product value at the time of harvest, maturity affects the product value over time after harvest. The maturity of mangoes also greatly affects the storage and transport time. This data is collected in Vietnam with many mango cultivars and used to train machine learning models for the automatic classify mango system.
DOI: 10.5281/zenodo.6383934
title: Raw Data of Mangoes; Computer Code

description: Exporting mangoes to foreign countries while maintaining quality is a challenge for distributors. The quality and maturity of mangoes are inhomogeneous, even when mangoes are harvested from the same tree at the same time. While quality affects the product value at the time of harvest, maturity affects the product value over time after harvest. The maturity of mangoes also greatly affects the storage and transport time. This data is collected in Vietnam with many mango cultivars and used to train machine learning models for the automatic classify mango system.
DOI: 10.6084/m9.figshare.19426766
title: dataset_duplicate_satd.csv

description: This dataset contains the 500 duplicate SATD comments with corresponding commit information.
DOI: 10.6084/m9.figshare.19426766.v1
title: dataset_duplicate_satd.csv

description: This dataset contains the 500 duplicate SATD comments with corresponding commit information.
DOI: 10.34740/kaggle/dsv/3368206
title: BBC News
DOI: 10.6084/m9.figshare.19426772
title: MatDeepLearn DOS data

description: Surface and SrTiO3 DOS data
DOI: 10.3886/e100510v2-113460
title: MacArthur Mental Health Court Study

description: The MacArthur Mental Health Court (MHC) project is a longitudinal study examining the effectiveness of these specialty courts in reducing recidivism, reducing the number of jail days and stays, and increasing access to community mental health and substance use treatment. The study included four data collection sites (two in CA, one in MN, and one in IN), two samples (newly enrolled MHC clients and a comparison sample of offenders with mental illness in the traditional criminal justice system), two interview time points (baseline and 6-month follow-up), and the collection of objective criminal justice and court data up to 18 months post-enrollment in the MHC/post-arrest. This comprehensive project was funded by the John D. and Catherine T. MacArthur Network on Community Mandated Treatment, led by Professor John Monahan, and was conducted by Policy Research Associates (Principal Investigator: Dr. Henry J. Steadman).
description: Presence of Common Scales: Several Likert scales were used.<br>Colorado Symptoms Inventory<br>Insight and Treatment Attitudes Questionnaire
description: There were two samples: MHC and TAU (treatment as usual) samples.<br>The MHC sample were newly enrolled clients in the four participating courts who provided informed consent to participate.<br>The TAU sample were newly arrested offenders with mental health problems in the jails of the same four cities as the courts, who also provided informed consent. In addition, the TAU sample had to be eligible for the MHC (criteria relating to criminal charges and mental health) but could not have been referred to, or rejected from the MHC. <br><br><br>
description: Newly enrolled mental health court (MHC) participants in four locations<br>Newly arrested offenders with mental health issues in four locations<br><br><br>.
description: face-to-face interview; Survey data at baseline (entry into MHC or criminal justice system)<br>Survey data at 6-month follow-up<br>Administrative data from courts
DOI: 10.6084/m9.figshare.19401221
title: Basesdedatos_Cap3_TesisDocCordone

description: Base de datos del capítulo 3 de mi tesis doctoral.<br>
DOI: 10.6084/m9.figshare.19401221.v1
title: Basesdedatos_Cap3_TesisDocCordone

description: Base de datos del capítulo 3 de mi tesis doctoral.<br>
DOI: 10.6084/m9.figshare.19401227
title: Basesdedatos_Cap5_TesisDocCordone

description: Base de datos del capítulo 5 de mi tesis doctoral.<br>