cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.345490
title: Jingju a cappella singing syllable boundary and duration annotation dataset

description: This dataset is a collection of syllable boundary annotations and syllable duration annotations of a cappella singing performed by jingju (京剧, Beijing opera) professional and amateur singers. This dataset was used as the experimental dataset in the following work: Rong Gong, Nicolas Obin, Georgi Dzhambazov and Xavier Serra, “Score-Informed syllable segmentation for jingju a cappella singing voice with Mel-frequency intensity profiles," in<em> Folk Music Analysis workshop (FMA) 2017, Málaga, Spain</em> <strong>Audio Content</strong> The audio files are the a cappella singing arias recordings, which are stereo or mono, sampled at 44.1 kHz, and stored as wav files. They can be found at this link http://doi.org/10.5281/zenodo.344932 The wav files are recorded by two institutes: those file names ending with ‘qm’ are recorded by C4DM Queen Mary University of London; others file names ending with ‘upf’ or ‘lon’ are recorded by MTG-UPF. If you use the dataset in your work, please cite the following publication. D. A. A. Black, M. Li, and M. Tian, “Automatic Identification of Emotional Cues in Chinese Opera Singing,” in <em>13th Int. Conf. on Music </em><em>Perception and Cognition</em> (ICMPC-2014), 2014, pp. 250–255. <strong>Annotations</strong> The syllable boundary annotation is in Textgrid format (Praat). The annotation is done in both phrase-level and syllable-level. The syllable duration annotation is in cvs format. Please consult Readme text in both folders for further details. The parsing code of the annotation files is provided in ‘pycode’ folder. <strong>Availability of the Dataset</strong> The annotations and codes in this dataset are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. <strong>Contact</strong> If you have any questions or comments about the dataset, please feel free to write to us. Rong Gong: rong&lt;dot&gt;gong&lt;at&gt;upf&lt;dot&gt;edu Rafael Caro Repetto: rafael&lt;dot&gt;caro&lt;at&gt;upf&lt;dot&gt;edu
description: {"references": ["Rong Gong, Nicolas Obin, Georgi Dzhambazov and Xavier Serra, Score-Informed syllable segmentation for jingju a cappella singing voice with Mel-frequency intensity profiles, in\u00a0Folk Music Analysis workshop (FMA) 2017, M\u00e1laga, Spain", "D. A. A. Black, M. Li, and M. Tian, Automatic Identification of\u00a0Emotional Cues in Chinese Opera Singing, in\u00a013th Int. Conf. on Music\u00a0Perception and Cognition\u00a0(ICMPC-2014), 2014, pp. 250\u2013255."]}
DOI: 10.17632/zp93xwnykd.1
title: Data for: Fractional seroprevalence rates in common prey species can cause more than half of feral cats to be exposed to Toxoplasma gondii annually

description: R code to reproduce transmission model/equation and reproduce Figure 1
DOI: 10.6084/m9.figshare.13177163.v1
title: Files for Building the Rust Expression Browser

description: This entry consists of a compressed tar archive containing all the file used to build the initial rust expression browser (www.rust-expression.com).<br>Initial code to provision the software for the browser is available at:https://github.com/JIC-CSB/expvip-ansible<br><br>Code to build the browser using the metadata in this entry is available at:https://github.com/SaundersLab/Rust_Expression_Browser<br>
DOI: 10.25810/558f-c477.30
title: Australian Newspaper Coverage of Climate Change or Global Warming, 2000-2020 - September 2020

description:         The Media and Climate Change Observatory Data monitors 120 sources (across newspapers, radio and TV) in 54 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.17632/tvhtmmjp3m.1
title: Data for: Evaluation of midwifery pelvic floor education and training across the UK and Spain
DOI: 10.17632/hmd87ky8gh.1
title: Data for: Improvements in the Predictive Accuracy of the Hydrophobic Subtraction Model of Reversed-Phase Selectivity

description: Excel workbook with HSM2 column and solute parameters.
DOI: 10.25810/es52-xr23.30
title: Canadian Newspaper Coverage of Climate Change or Global Warming, 2000-2020 - September 2020

description:         The Media and Climate Change Observatory Data monitors 120 sources (across newspapers, radio and TV) in 54 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.25345/c5f207
title: MassIVE MSV000086414 - MSU iGEM 2020 Metabolome: Pseudomonas putida
title: The goal of the experiment was to analyze the metabolite profiles of the imidacloprid-degrading soil microbe Pseudomonas putida EM371 ("Cells") (with particular focus on imidacloprid and imidacloprid derivatives) and to fine-tune the ideal imidacloprid concentrations for future imidacloprid-exposure experiments.
DOI: 10.15784/601399
title: South Pole Ice Core Holocene Major Ion Dataset

description: This dataset includes major ion and seasonal sea salt chemistry data from the South Pole Ice Core. Included are the raw major ion data, annually resolved mean, maximum and minimum sea salt sodium concentrations and centennially resolved principal components (discussed in Winski et al. (in review).
DOI: 10.25810/3hvn-ef66.2
title: Danish Newspaper Coverage of Climate Change or Global Warming, 2004-2020 - September 2020

description:         The Media and Climate Change Observatory Data monitors 120 sources (across newspapers, radio and TV) in 54 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.5517/ccdc.csd.cc24nvk7
title: CCDC 1986249: Experimental Crystal Structure Determination

description: Related Article: Marko Rodewald, J. Mikko Rautiainen, Tobias Niksch, Helmar Görls, Raija Oilunkaniemi, Wolfgang Weigand, Risto S. Laitinen|2020|Chem.-Eur.J.|26|13806|doi:10.1002/chem.202002510
DOI: 10.5517/ccdc.csd.cc24nvl8
title: CCDC 1986250: Experimental Crystal Structure Determination

description: Related Article: Marko Rodewald, J. Mikko Rautiainen, Tobias Niksch, Helmar Görls, Raija Oilunkaniemi, Wolfgang Weigand, Risto S. Laitinen|2020|Chem.-Eur.J.|26|13806|doi:10.1002/chem.202002510
DOI: 10.5517/ccdc.csd.cc24nvm9
title: CCDC 1986251: Experimental Crystal Structure Determination

description: Related Article: Marko Rodewald, J. Mikko Rautiainen, Tobias Niksch, Helmar Görls, Raija Oilunkaniemi, Wolfgang Weigand, Risto S. Laitinen|2020|Chem.-Eur.J.|26|13806|doi:10.1002/chem.202002510
DOI: 10.5517/ccdc.csd.cc24nvnb
title: CCDC 1986252: Experimental Crystal Structure Determination

description: Related Article: Marko Rodewald, J. Mikko Rautiainen, Tobias Niksch, Helmar Görls, Raija Oilunkaniemi, Wolfgang Weigand, Risto S. Laitinen|2020|Chem.-Eur.J.|26|13806|doi:10.1002/chem.202002510
DOI: 10.5517/ccdc.csd.cc259blf
title: CCDC 2004974: Experimental Crystal Structure Determination

description: Related Article: Aslam C. Shaikh, Jules Moutet, José M. Veleta, Md Mubarak Hossain, Jan Bloch, Andrei V. Astashkin, Thomas L. Gianetti|2020|Chemical Science|11|11060|doi:10.1039/D0SC04850J
DOI: 10.5517/ccdc.csd.cc259bmg
title: CCDC 2004975: Experimental Crystal Structure Determination

description: Related Article: Aslam C. Shaikh, Jules Moutet, José M. Veleta, Md Mubarak Hossain, Jan Bloch, Andrei V. Astashkin, Thomas L. Gianetti|2020|Chemical Science|11|11060|doi:10.1039/D0SC04850J
DOI: 10.5517/ccdc.csd.cc259bnh
title: CCDC 2004976: Experimental Crystal Structure Determination

description: Related Article: Aslam C. Shaikh, Jules Moutet, José M. Veleta, Md Mubarak Hossain, Jan Bloch, Andrei V. Astashkin, Thomas L. Gianetti|2020|Chemical Science|11|11060|doi:10.1039/D0SC04850J
DOI: 10.5517/ccdc.csd.cc259bpj
title: CCDC 2004977: Experimental Crystal Structure Determination

description: Related Article: Aslam C. Shaikh, Jules Moutet, José M. Veleta, Md Mubarak Hossain, Jan Bloch, Andrei V. Astashkin, Thomas L. Gianetti|2020|Chemical Science|11|11060|doi:10.1039/D0SC04850J
DOI: 10.5517/ccdc.csd.cc25f0n9
title: CCDC 2008510: Experimental Crystal Structure Determination

description: Related Article: Hua Deng, Tian-Tian Liu, Zheng-Dong Ding, Wu-Lin Yang, Xiaoyan Luo, Wei-Ping Deng|2020|Org.Chem.Front.|7|3247|doi:10.1039/D0QO00789G
DOI: 10.5517/ccdc.csd.cc25fk39
title: CCDC 2009020: Experimental Crystal Structure Determination

description: Related Article: Christoph Zippel, Eduard Spuling, Zahid Hassan, Mika Polamo, Martin Nieger, Stefan Bräse|2020|Chem.-Eur.J.|26|13771|doi:10.1002/chem.202003709
DOI: 10.5517/ccdc.csd.cc25fk4b
title: CCDC 2009021: Experimental Crystal Structure Determination

description: Related Article: Christoph Zippel, Eduard Spuling, Zahid Hassan, Mika Polamo, Martin Nieger, Stefan Bräse|2020|Chem.-Eur.J.|26|13771|doi:10.1002/chem.202003709
DOI: 10.5517/ccdc.csd.cc25fk5c
title: CCDC 2009022: Experimental Crystal Structure Determination

description: Related Article: Christoph Zippel, Eduard Spuling, Zahid Hassan, Mika Polamo, Martin Nieger, Stefan Bräse|2020|Chem.-Eur.J.|26|13771|doi:10.1002/chem.202003709
DOI: 10.5517/ccdc.csd.cc25fk6d
title: CCDC 2009023: Experimental Crystal Structure Determination

description: Related Article: Christoph Zippel, Eduard Spuling, Zahid Hassan, Mika Polamo, Martin Nieger, Stefan Bräse|2020|Chem.-Eur.J.|26|13771|doi:10.1002/chem.202003709
DOI: 10.5517/ccdc.csd.cc24wl5t
title: CCDC 1992716: Experimental Crystal Structure Determination

description: Related Article: Andrey N. Usoltsev, Sergey A. Adonin, Boris A. Kolesov, Alexander S. Novikov, Vladimir P. Fedin, Maxim N. Sokolov|2020|Chem.-Eur.J.|26|13776|doi:10.1002/chem.202002014
DOI: 10.5517/ccdc.csd.cc25hvq8
title: CCDC 2011240: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvr9
title: CCDC 2011241: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvsb
title: CCDC 2011242: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvtc
title: CCDC 2011243: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvvd
title: CCDC 2011244: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvwf
title: CCDC 2011245: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvxg
title: CCDC 2011246: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvyh
title: CCDC 2011247: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hvzj
title: CCDC 2011248: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw0l
title: CCDC 2011249: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw1m
title: CCDC 2011250: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw2n
title: CCDC 2011251: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw3p
title: CCDC 2011252: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw4q
title: CCDC 2011253: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw5r
title: CCDC 2011254: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw6s
title: CCDC 2011255: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw7t
title: CCDC 2011256: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hw8v
title: CCDC 2011257: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5517/ccdc.csd.cc25hwbx
title: CCDC 2011259: Experimental Crystal Structure Determination

description: Related Article: Saray Argibay-Otero, Ana M. Graña, Rosa Carballo, Ezequiel M. Vázquez-López|2020|Inorg.Chem.|59|14101|doi:10.1021/acs.inorgchem.0c01887
DOI: 10.5281/zenodo.4247643
title: Raw data for "Examining the effects of transcranial direct current stimulation on human episodic memory with machine learning"

description: This is the raw dataset for "Examining the effects of transcranial direct current stimulation on human episodic memory with machine learning". Each .xlsx file represents an experimental results of a single participant. Directory description: Eng_sham - the results from experiments without stimulation on English sample from Medvedeva, 2019. Eng_vlPFC - the results from experiments with vLPFC stimulation on English sample from Medvedeva, 2019. enc_off_new - the results from experiments with dLPFC offline encoding stimulation on Russian sample. enc_on_new - the results from experiments with dLPFC online encoding stimulation on Russian sample. sham_no stimulation - the results from experiments without stimulation offline encoding stimulation on Russian sample. vlPFC_stimulation - the results from experiments with vLPFC stimulation on Russian sample. Age.xlsx - the ages of the participants
DOI: 10.5281/zenodo.3837110
title: Raw data for "Examining the effects of transcranial direct current stimulation on human episodic memory with machine learning"

description: This is the raw dataset for "Examining the effects of transcranial direct current stimulation on human episodic memory with machine learning". Each .xlsx file represents an experimental results of a single participant. Directory description: Eng_sham - the results from experiments without stimulation on English sample from Medvedeva, 2019. Eng_vlPFC - the results from experiments with vLPFC stimulation on English sample from Medvedeva, 2019. enc_off_new - the results from experiments with dLPFC offline encoding stimulation on Russian sample. enc_on_new - the results from experiments with dLPFC online encoding stimulation on Russian sample. sham_no stimulation - the results from experiments without stimulation offline encoding stimulation on Russian sample. vlPFC_stimulation - the results from experiments with vLPFC stimulation on Russian sample. Age.xlsx - the ages of the participants
DOI: 10.5281/zenodo.4247638
title: DATASET: Characterization of static and kinetic motor task of forearm and hand in healthy individuals

description: This database resulted from: ZARUZ, Maria Jose Ferreira. Caracterização de tarefa motora estática e cinética de antebraço e mão em indivíduos hígidos. 2016. 80 f. Dissertação (Mestrado em Ciências) - Universidade Federal de Uberlândia, Uberlândia, 2017. Disponível em: http://doi.org/10.14393/ufu.di.2016.592 There are numerous scales in literature to characterize the degree of severity of neuromotor diseases. Among them, we can mention the Unified Parkinson Disease Rating Scale (UPDRS), which is widely used in the clinical practice. The main limitation of scales such as the UPDRS is the subjectivity of evaluation based on the experience of examiners. In this context, the use of objective scales is of great relevance in the process of assessing and monitoring the evolution of neuromotor diseases. In order to contribute to the objective assessment of wrist and forearm static and kinetic motor tasks, this research proposed an index that characterizes normality patterns for healthy individuals. In total, 99 neurologically healthy subjects participated in the study. Inertial and electromyographic signals of the forearm and wrist were detected during the execution of the following tasks: pinch grip, pronation and supination of the forearm, and support of the upper limb against gravity. For visualization and processing of the data, a set of features was estimated and projected onto a two-dimensional space using the T-Distributed Stochastic Neighbor Embedding (t-SNE) method. A normality index was proposed based on the normalized Euclidean distance of the data referring to each type of task. To exemplify the practical application of the proposed index, data were collected from individuals with Parkinson's disease, which is a neurodegenerative illness, very prevalent nowadays. Its clinical symptoms includes tremor, bradykinesia, stiffness and postural disorders, compromising the movements of the upper limb such as forearm and wrist. The estimated values for the index indicated atypical patterns for these individuals when compared to normality patterns. We hope that the proposed index can be used to assess the severity of neuromotor diseases, such as the Parkinson's disease.
DOI: 10.5281/zenodo.4247637
title: DATASET: Characterization of static and kinetic motor task of forearm and hand in healthy individuals

description: This database resulted from: ZARUZ, Maria Jose Ferreira. Caracterização de tarefa motora estática e cinética de antebraço e mão em indivíduos hígidos. 2016. 80 f. Dissertação (Mestrado em Ciências) - Universidade Federal de Uberlândia, Uberlândia, 2017. Disponível em: http://doi.org/10.14393/ufu.di.2016.592 There are numerous scales in literature to characterize the degree of severity of neuromotor diseases. Among them, we can mention the Unified Parkinson Disease Rating Scale (UPDRS), which is widely used in the clinical practice. The main limitation of scales such as the UPDRS is the subjectivity of evaluation based on the experience of examiners. In this context, the use of objective scales is of great relevance in the process of assessing and monitoring the evolution of neuromotor diseases. In order to contribute to the objective assessment of wrist and forearm static and kinetic motor tasks, this research proposed an index that characterizes normality patterns for healthy individuals. In total, 99 neurologically healthy subjects participated in the study. Inertial and electromyographic signals of the forearm and wrist were detected during the execution of the following tasks: pinch grip, pronation and supination of the forearm, and support of the upper limb against gravity. For visualization and processing of the data, a set of features was estimated and projected onto a two-dimensional space using the T-Distributed Stochastic Neighbor Embedding (t-SNE) method. A normality index was proposed based on the normalized Euclidean distance of the data referring to each type of task. To exemplify the practical application of the proposed index, data were collected from individuals with Parkinson's disease, which is a neurodegenerative illness, very prevalent nowadays. Its clinical symptoms includes tremor, bradykinesia, stiffness and postural disorders, compromising the movements of the upper limb such as forearm and wrist. The estimated values for the index indicated atypical patterns for these individuals when compared to normality patterns. We hope that the proposed index can be used to assess the severity of neuromotor diseases, such as the Parkinson's disease.
DOI: 10.21227/kgs3-6406
title: Model 8

description: lgb + temp + group
DOI: 10.5281/zenodo.4243260
title: EMG-EPN-612 Dataset

description: EMG-EPN-612 Dataset This dataset, called EMG-EPN-612, contains EMG signals of 612 people for benchmarking of hand gesture recognition systems. This dataset has been created by the Artificial Intelligence and Computer Vision Research Lab from the Escuela Politécnica Nacional, Quito-Ecuador. The data was obtained by recording, with the Myo armband, EMG signals on the forearm while users were performing five hand gestures: wave-in, wave-out, pinch, open and fist. EMGs of the hand relaxed are also included. The dataset is divided into two groups of 306 people each. One group is for training or designing hand gesture recognition models and the other is intended for testing the classification and recognition accuracy of hand gesture recognition models. In each of these two groups, each person has 50 EMGs for each of the 5 gesture recorded and also 50 EMGs for the hand relaxed. More information about this dataset can be found at: https://laboratorio-ia.epn.edu.ec/en/resources/dataset/2020_emg_dataset_612
DOI: 10.21227/bfje-6f14
title: Heart Disease Dataset (Comprehensive)

description: This heart disease dataset is curated by combining 5 popular heart disease datasets already available independently but not combined before. In this dataset, 5 heart datasets are combined over 11 common features which makes it the largest heart disease dataset available so far for research purposes. The five datasets used for its curation are:ClevelandHungarianSwitzerlandLong Beach VAStatlog (Heart) Data Set.This dataset consists of 1190 instances with 11 features. These datasets were collected and combined at one place to help advance research on CAD-related machine learning and data mining algorithms, and hopefully to ultimately advance clinical diagnosis and early treatment.
DOI: 10.5281/zenodo.4247660
title: Multilevel Text Alignment with Cross-Document Attention

description: This benchmark belongs to our EMNLP2020 paper: Multilevel Text Alignment with Cross-Document Attention.