cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6973877
title: Data underpinning "Localisation and Sub-Diffusive Transport in Quantum Spin Chains With Dilute Disorder"

description: It is widely believed that many-body localisation in one dimension is fragile and can be easily destroyed by thermal inclusions, however there are still many open questions regarding the stability of the localised phase and under what conditions it breaks down. Here I construct models with dilute disorder, which interpolate between translationally invariant and fully random models, in order to study the breakdown of localisation. This opens up the possibility to controllably increase the density of thermal regions and examine the breakdown of localisation as this density is increased. At strong disorder, the numerical results are consistent with commonly-used diagnostics for localisation even when the concentration of thermalising regions is high. At moderate disorder, I present evidence for slow dynamics and sub-diffusive transport across a large region of the phase diagram, suggestive of a `bad metal' phase. This suggests that dilute disorder may be a useful effective model for studying Griffiths effects in many-body localisation, and perhaps also in a wider class of disordered systems.
description: A README file is available in the .zip archive which explains the subfolders and file structure within. See https://github.com/sjt48/DiluteDisorder for an up-to-date version of the code contained within this dataset, including version history and any bug fixes. Version 2 includes additional data.
DOI: 10.5281/zenodo.6973878
title: Data underpinning "Localisation and Sub-Diffusive Transport in Quantum Spin Chains With Dilute Disorder"

description: It is widely believed that many-body localisation in one dimension is fragile and can be easily destroyed by thermal inclusions, however there are still many open questions regarding the stability of the localised phase and under what conditions it breaks down. Here I construct models with dilute disorder, which interpolate between translationally invariant and fully random models, in order to study the breakdown of localisation. This opens up the possibility to controllably increase the density of thermal regions and examine the breakdown of localisation as this density is increased. At strong disorder, the numerical results are consistent with commonly-used diagnostics for localisation even when the concentration of thermalising regions is high. At moderate disorder, I present evidence for slow dynamics and sub-diffusive transport across a large region of the phase diagram, suggestive of a `bad metal' phase. This suggests that dilute disorder may be a useful effective model for studying Griffiths effects in many-body localisation, and perhaps also in a wider class of disordered systems.
description: A README file is available in the .zip archive which explains the subfolders and file structure within. See https://github.com/sjt48/DiluteDisorder for an up-to-date version of the code contained within this dataset, including version history and any bug fixes.
DOI: 10.5281/zenodo.7547498
title: Data underpinning "Localisation and Sub-Diffusive Transport in Quantum Spin Chains With Dilute Disorder"

description: It is widely believed that many-body localisation in one dimension is fragile and can be easily destroyed by thermal inclusions, however there are still many open questions regarding the stability of the localised phase and under what conditions it breaks down. Here I construct models with dilute disorder, which interpolate between translationally invariant and fully random models, in order to study the breakdown of localisation. This opens up the possibility to controllably increase the density of thermal regions and examine the breakdown of localisation as this density is increased. At strong disorder, the numerical results are consistent with commonly-used diagnostics for localisation even when the concentration of thermalising regions is high. At moderate disorder, I present evidence for slow dynamics and sub-diffusive transport across a large region of the phase diagram, suggestive of a `bad metal' phase. This suggests that dilute disorder may be a useful effective model for studying Griffiths effects in many-body localisation, and perhaps also in a wider class of disordered systems.
description: A README file is available in the .zip archive which explains the subfolders and file structure within. See https://github.com/sjt48/DiluteDisorder for an up-to-date version of the code contained within this dataset, including version history and any bug fixes. Version 2 includes additional data.
DOI: 10.5517/ccdc.csd.cc1z9vns
title: CCDC 1826726: Experimental Crystal Structure Determination

description: Related Article: Ridaphun Nongrum, Ridahunlang Nongkhlaw, Sophie P. Majaw, Jyothi Kumari, Dharmarajan Sriram, Rishanlang Nongkhlaw|2023|Sustainable Chem. Pharm.|32|100967|doi:10.1016/j.scp.2023.100967
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c6hrv
title: CCDC 2180997: Experimental Crystal Structure Determination

description: Related Article: Christopher M. Lemon, David C. Powers, Michael Huynh, Andrew G. Maher, Austin A. Phillips, Brian P. Tripet, Daniel G. Nocera|2022|Inorg.Chem.|62|3|doi:10.1021/acs.inorgchem.2c02285
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c94pj
title: CCDC 2183537: Experimental Crystal Structure Determination

description: Related Article: Rupsa Chanda, Tubai Ghosh, Umasish Jana|2022|J.Org.Chem.|88|658|doi:10.1021/acs.joc.2c01847
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.5256620
title: 20 news group (20ng)

description: 20 Newsgroups (20NG) is a classical and popular dataset for experiments in text applications of machine learning techniques. It contains 18,846 newsgroups documents, partitioned almost evenly across 20 different newsgroups categories. http://qwone.com/~jason/20Newsgroups/ <strong>The files:</strong><br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition. The .zip contains all aforementioned files + the tfidf representation in the CSR matrix format. <strong>Label Definition: (Score File)</strong> 0 atheist resources<br> 1 computer graphics<br> 2 computer os ms windows misc<br> 3 computer system ibm pc hardware<br> 4 computer system mac hardware<br> 5 computer windows x<br> 6 misc miscellaneous for sale<br> 7 rec autos<br> 8 rec motorcycles<br> 9 rec sport baseball<br> 10 rec sport hockey<br> 11 science crypt<br> 12 science electronics<br> 13 science med<br> 14 science space<br> 15 society religion christian<br> 16 talk politics guns<br> 17 talk politics mideast<br> 18 talk politics misc miscellaneous<br> 19 talk religion misc miscellaneous
description: {"references": ["https://doi.org/10.1016/j.ipm.2020.102263", "https://doi.org/10.1016/j.ipm.2020.102481", "Newsweeder: Learning to filter netnews"]}
DOI: 10.5281/zenodo.5256621
title: 20 news group (20ng)

description: 20 Newsgroups (20NG) is a classical and popular dataset for experiments in text applications of machine learning techniques. It contains 18,846 newsgroups documents, partitioned almost evenly across 20 different newsgroups categories. http://qwone.com/~jason/20Newsgroups/ <strong>The files:</strong><br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition. <strong>Label Definition: (Score File)</strong> 0 atheist resources<br> 1 computer graphics<br> 2 computer os ms windows misc<br> 3 computer system ibm pc hardware<br> 4 computer system mac hardware<br> 5 computer windows x<br> 6 misc miscellaneous for sale<br> 7 rec autos<br> 8 rec motorcycles<br> 9 rec sport baseball<br> 10 rec sport hockey<br> 11 science crypt<br> 12 science electronics<br> 13 science med<br> 14 science space<br> 15 society religion christian<br> 16 talk politics guns<br> 17 talk politics mideast<br> 18 talk politics misc miscellaneous<br> 19 talk religion misc miscellaneous
description: {"references": ["https://doi.org/10.1016/j.ipm.2020.102263", "https://doi.org/10.1016/j.ipm.2020.102481", "Newsweeder: Learning to filter netnews"]}
DOI: 10.5281/zenodo.7555237
title: 20 news group (20ng)

description: 20 Newsgroups (20NG) is a classical and popular dataset for experiments in text applications of machine learning techniques. It contains 18,846 newsgroups documents, partitioned almost evenly across 20 different newsgroups categories. http://qwone.com/~jason/20Newsgroups/ <strong>The files:</strong><br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition. The .zip contains all aforementioned files + the tfidf representation in the CSR matrix format. <strong>Label Definition: (Score File)</strong> 0 atheist resources<br> 1 computer graphics<br> 2 computer os ms windows misc<br> 3 computer system ibm pc hardware<br> 4 computer system mac hardware<br> 5 computer windows x<br> 6 misc miscellaneous for sale<br> 7 rec autos<br> 8 rec motorcycles<br> 9 rec sport baseball<br> 10 rec sport hockey<br> 11 science crypt<br> 12 science electronics<br> 13 science med<br> 14 science space<br> 15 society religion christian<br> 16 talk politics guns<br> 17 talk politics mideast<br> 18 talk politics misc miscellaneous<br> 19 talk religion misc miscellaneous
description: {"references": ["https://doi.org/10.1016/j.ipm.2020.102263", "https://doi.org/10.1016/j.ipm.2020.102481", "Newsweeder: Learning to filter netnews"]}
DOI: 10.5281/zenodo.5256658
title: ACM-Digital Library (ACM)

description: ACM-Digital Library (ACM): a subset of the ACM Digital Library with 24, 897 documents containing articles related to Computer Science. We considered only the first level of the taxonomy adopted by ACM, where each document is assigned to one of 11 classes. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition. The .zip contains all aforementioned files + the tfidf representation in the CSR matrix format.
description: {"references": ["https://doi.org/10.1016/j.ipm.2020.102263", "https://doi.org/10.1016/j.ipm.2020.102481"]}
DOI: 10.5281/zenodo.5256659
title: ACM-Digital Library (ACM)

description: ACM-Digital Library (ACM): a subset of the ACM Digital Library with 24, 897 documents containing articles related to Computer Science. We considered only the first level of the taxonomy adopted by ACM, where each document is assigned to one of 11 classes. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
description: {"references": ["https://doi.org/10.1016/j.ipm.2020.102263", "https://doi.org/10.1016/j.ipm.2020.102481"]}
DOI: 10.5281/zenodo.7555249
title: ACM-Digital Library (ACM)

description: ACM-Digital Library (ACM): a subset of the ACM Digital Library with 24, 897 documents containing articles related to Computer Science. We considered only the first level of the taxonomy adopted by ACM, where each document is assigned to one of 11 classes. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition. The .zip contains all aforementioned files + the tfidf representation in the CSR matrix format.
description: {"references": ["https://doi.org/10.1016/j.ipm.2020.102263", "https://doi.org/10.1016/j.ipm.2020.102481"]}
DOI: 10.5281/zenodo.7555245
title: neosilurus_mollespiculum_decontaminated_gx.fasta.gx

description: .
DOI: 10.5281/zenodo.7555244
title: neosilurus_mollespiculum_decontaminated_gx.fasta.gx

description: .
DOI: 10.6073/pasta/abe2eb0ba198d3faf682e0245b5eedaa
title: Weather data for the period 2009 to 2022 from the North Woodlot location at University Farms, Case Western Reserve University

description: Data from the North Woodlot weather station at University Farms of Case Western Reserve University include observations from 2009 to 2022. University Farms is located in Hunting Valley, Ohio. The North Woodlot weather station is at N 41 29.969, W 81 25.234. Data include Date and time (in 15-minute intervals), wind speed, wind gust speed, air temperature, relative humidity, solar radiation, soil moisture, soil temperatures at 0, 2, and 5 cm soil depth, and data logger battery charge.
DOI: 10.5281/zenodo.5256711
title: Books

description: Books dataset is a collection of book descriptions from the Goodreads (https://www.goodreads.com/) website, a famous book review platform. This dataset is composed of 33,594 books descriptions classified into the following 8 genres: children, graphic comics, paranormal fantasy, history & biography, crime & mystery thriller, poetry, romance and young adult. We used as data the title and description of each book. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
description: {"references": ["10.18653/v1/2020.emnlp-main.670"]}
DOI: 10.5281/zenodo.5256710
title: Books

description: Books dataset is a collection of book descriptions from the Goodreads (https://www.goodreads.com/) website, a famous book review platform. This dataset is composed of 33,594 books descriptions classified into the following 8 genres: children, graphic comics, paranormal fantasy, history & biography, crime & mystery thriller, poetry, romance and young adult. We used as data the title and description of each book. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
description: {"references": ["10.18653/v1/2020.emnlp-main.670"]}
DOI: 10.5281/zenodo.7555256
title: Books

description: Books dataset is a collection of book descriptions from the Goodreads (https://www.goodreads.com/) website, a famous book review platform. This dataset is composed of 33,594 books descriptions classified into the following 8 genres: children, graphic comics, paranormal fantasy, history & biography, crime & mystery thriller, poetry, romance and young adult. We used as data the title and description of each book. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
description: {"references": ["10.18653/v1/2020.emnlp-main.670"]}
DOI: 10.5281/zenodo.5256780
title: DBLP

description: DBLPdataset is a set of research papers. This dataset is composed of 38,12$ papers in the computer science field. Each paper is classified into one of the following knowledge subareas: computer vision, computational linguistics, biomedical engineering, software engineering, graphics, data mining, security and cryptography, signal processing, robotics, and theory. We had removed the venue for prevent lack of information about the subarea class. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
description: {"references": ["10.18653/v1/2020.emnlp-main.670"]}
DOI: 10.5281/zenodo.5256781
title: DBLP

description: DBLPdataset is a set of research papers. This dataset is composed of 38,12$ papers in the computer science field. Each paper is classified into one of the following knowledge subareas: computer vision, computational linguistics, biomedical engineering, software engineering, graphics, data mining, security and cryptography, signal processing, robotics, and theory. We had removed the venue for prevent lack of information about the subarea class. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
description: {"references": ["10.18653/v1/2020.emnlp-main.670"]}
DOI: 10.5281/zenodo.7555264
title: DBLP

description: DBLPdataset is a set of research papers. This dataset is composed of 38,12$ papers in the computer science field. Each paper is classified into one of the following knowledge subareas: computer vision, computational linguistics, biomedical engineering, software engineering, graphics, data mining, security and cryptography, signal processing, robotics, and theory. We had removed the venue for prevent lack of information about the subarea class. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
description: {"references": ["10.18653/v1/2020.emnlp-main.670"]}
DOI: 10.5281/zenodo.5256830
title: Multi-Perspective Question Answering (MPQA)

description: Multi-Perspective Question Answering is an imbalanced dataset of opinion polarity detection task. This dataset contains news documents from many sources and it was classified into positive and negative classes. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.5281/zenodo.5256831
title: Multi-Perspective Question Answering (MPQA)

description: Multi-Perspective Question Answering is an imbalanced dataset of opinion polarity detection task. This dataset contains news documents from many sources and it was classified into positive and negative classes. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.5281/zenodo.7555268
title: Multi-Perspective Question Answering (MPQA)

description: Multi-Perspective Question Answering is an imbalanced dataset of opinion polarity detection task. This dataset contains news documents from many sources and it was classified into positive and negative classes. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.6073/pasta/2716ff680705925ddd5a37a4523f0020
title: GIS00 GIS Coverages Defining the Site Boundary of Konza Prairie (1977-present)

description: This dataset contains the boundary polygon of the Konza Prairie Biological Station (KPBS). Data type one (GIS000) defines the original KPBS boundary used from 1977 until 1982, type two contains the extended boundary from 1982 (GIS001) to 1997, and type three (GIS002) contains the boundary since 1997. These data are available as zipped (.zip) shapefiles (.shp).
DOI: 10.5281/zenodo.5256838
title: Movie review (MR)

description: Movie review (MR) dataset is a binary (positive and negative labels) sentiment polarity composed of movie reviews. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.5281/zenodo.5256839
title: Movie review (MR)

description: Movie review (MR) dataset is a binary (positive and negative labels) sentiment polarity composed of movie reviews. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.5281/zenodo.7555273
title: Movie review (MR)

description: Movie review (MR) dataset is a binary (positive and negative labels) sentiment polarity composed of movie reviews. The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.6084/m9.figshare.21932274
title: Data of Beyer&Kulow et al_cavity-nesting insects biodiversity measures

description: Abundance (i.e. brood cell number) of cavity-nesting bees and wasps as well as the number of parasitized and aborted brood cells; Species richness data of cavity-nesting bees, wasps and natural enemies; Landscape data (i.e. distance of trap nests to different landscape elements)
DOI: 10.5281/zenodo.5256849
title: OHSUMED

description: OHSUMED collection contains medical documents collected in 1991 related to 23 cardiovascular disease categories. The version we used has 18,302 documents, distributed very irregularly among the categories varying from 56 to 2876 documents per category The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.5281/zenodo.7555276
title: OHSUMED

description: OHSUMED collection contains medical documents collected in 1991 related to 23 cardiovascular disease categories. The version we used has 18,302 documents, distributed very irregularly among the categories varying from 56 to 2876 documents per category The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.5281/zenodo.5256848
title: OHSUMED

description: OHSUMED collection contains medical documents collected in 1991 related to 23 cardiovascular disease categories. The version we used has 18,302 documents, distributed very irregularly among the categories varying from 56 to 2876 documents per category The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_&lt;k&gt;.pkl: pandas DataFrame with k-cross validation partition.
DOI: 10.6073/pasta/67e5f60b87c38157f5240a5546ece0af
title: Weather data for the period 2009 to 2022 from the Open Field location at University Farms, Case Western Reserve University

description: Data from the Open Field weather station at University Farms of Case Western Reserve University include observations from 2009 to 2022. University Farms is located in Hunting Valley, Ohio. From 10/20/2009 to 10/30/2014, the weather station was located at N 41.496883, W 81.436117, when it was relocated to N 41.49759, W81.43738. Data include date/time (in 15-minute intervals), wind speed, wind gust speed, wind direction, air temperature, relative humidity, solar radiation, rainfall, soil moisture, soil temperatures at 0, 2, and 5 cm soil depth, and data logger battery charge.