cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7097181
title: Tipologias de Mobilidade para a Região Metropolitana do Vale do Paraíba e Litoral Norte (RMVPLN)

description: Esse conjunto de dados apresenta o shapefile das Tipologias de Mobilidade para a Região Metropolitana do Vale do Paraíba e Litoral Norte (RMVPLN), construídas a partir dos dados do OpenStreetMap (OSM), do ano de 2020. A partir da classificação de Highway (‘highway’ tag) dos dados do OSM, foram estabelecidas sete categorias das Tipologias de Mobilidade, descritas na tabela abaixo. Essas informações refletem em conjunto a potencial circulação que cada Tipologia de Mobilidade permite, desde uma circulação local até uma circulação regional. Tabela 1. Descrição das Tipologias de Mobilidade, sua potencial circulação e a as categorias utilizadas do OSM. <strong>Circulação</strong> <strong>Tipologias</strong> <strong>Categorias OSM </strong> <strong>Descrição</strong> <strong>Tipologia (n)</strong> Circulação regional Mobilidade por vias rápidas entre cidades <em>Motorway, Motorway - Link</em>, <em>Trunk, Trunk - Link, Primary, Primary - Link</em> As vias terrestres rápidas correspondem as rodovias e vias expressas, com velocidade de circulação &gt;=80km/h, reservadas a veículos motorizados e Vias terrestres arteriais, com velocidade de circulação &gt;=60km/h, conectando cidades 1 Circulação municipal Mobilidade por vias coletoras na cidade <em>Secondary, Secondary - Link</em> Vias terrestres coletoras, com velocidade de circulação média &gt;=40km/h, conectando cidades e povoados (Secundárias) 2 Circulação local Mobilidade por vias locais <em>Tertiary</em>, <em>Tertiary -Link, Unclassified</em> Vias terrestres locais, com menor fluxo de veículos, podendo ser vias não classificadas (vias locais sem uso residencial), conectando bairros e/ou permitindo uma rede de circulação secundária em cidades pequenas. 3 Circulação local residencial Mobilidade por vias residenciais <em>Residential</em> Vias locais, de baixo fluxo de veículos, dentro de área residencial 4 Circulação local de serviços e outros Mobilidade por vias de acesso <em>Road</em>, <em>Service, Raceway</em>,<em> Living</em> <em>Street</em>, <em>Track</em> Estradas rústicas (<em>track</em> – vias para uso agrícola, florestal), de caráter de acesso ou o interior de propriedades industriais, acampamentos, estacionamentos (vias de serviço), e pistas de corrida (<em>raceway</em>), vias de preferência de pedestres, e vias de tipo desconhecido (<em>road</em>) 5 Circulação local não motorizado Mobilidade ativa <em>Steps</em>, Path, <em>Cicleway</em>, <em>Pedestrian</em>, <em>Footway</em>, <em>Bridleway</em> Vias terrestres de uso não motorizado, podendo ser do tipo escadas, caminho, ciclovias, calçadão, pista de caminhada e hipovias 6 Circulação potencial futura Mobilidade futura <em>Abandoned, Construction, Proposed</em> Vias terrestres abandonadas, em construção ou propostas 7
DOI: 10.5517/ccdc.csd.cc24f2vj
title: CCDC 1978787: Experimental Crystal Structure Determination

description: Related Article: Juan Sun, Jing Xie, Licun Li, Jean-Pascal Sutter|2020|Inorg.Chem.Front.|7|1949|doi:10.1039/D0QI00098A
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.cc24f2wk
title: CCDC 1978788: Experimental Crystal Structure Determination

description: Related Article: Juan Sun, Jing Xie, Licun Li, Jean-Pascal Sutter|2020|Inorg.Chem.Front.|7|1949|doi:10.1039/D0QI00098A
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.cc24f2th
title: CCDC 1978786: Experimental Crystal Structure Determination

description: Related Article: Juan Sun, Jing Xie, Licun Li, Jean-Pascal Sutter|2020|Inorg.Chem.Front.|7|1949|doi:10.1039/D0QI00098A
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.cc2704yc
title: CCDC 2055732: Experimental Crystal Structure Determination

description: Related Article: Fengli Li, Zhangyan Huang, Shuyuan Mo, Saisai Gu, Sitian Zhang, Beiye Yang, Jianping Wang, Zhengxi Hu, Yonghui Zhang|2022|New J.Chem.|46|17149|doi:10.1039/D2NJ03531F
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.cc247xdq
title: CCDC 1973813: Experimental Crystal Structure Determination

description: Related Article: J. Srividya, D. Reuben Jonathan, B.K. Revathy, V. Sivamadhavi, Anbalagan|2022|J.Mol.Struct.|1271|134080|doi:10.1016/j.molstruc.2022.134080
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.cc27npxj
title: CCDC 2075478: Experimental Crystal Structure Determination

description: Related Article: Raghavender Medishetty, Akansha Ekka, Caroline Evania Mulijanto, Rika Tandiana, Jagadese J. Vittal|2022|CrystEngComm|24|6330|doi:10.1039/D2CE00822J
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.cc27npyk
title: CCDC 2075479: Experimental Crystal Structure Determination

description: Related Article: Raghavender Medishetty, Akansha Ekka, Caroline Evania Mulijanto, Rika Tandiana, Jagadese J. Vittal|2022|CrystEngComm|24|6330|doi:10.1039/D2CE00822J
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.cc27npzl
title: CCDC 2075480: Experimental Crystal Structure Determination

description: Related Article: Raghavender Medishetty, Akansha Ekka, Caroline Evania Mulijanto, Rika Tandiana, Jagadese J. Vittal|2022|CrystEngComm|24|6330|doi:10.1039/D2CE00822J
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.cc27nq0n
title: CCDC 2075481: Experimental Crystal Structure Determination

description: Related Article: Raghavender Medishetty, Akansha Ekka, Caroline Evania Mulijanto, Rika Tandiana, Jagadese J. Vittal|2022|CrystEngComm|24|6330|doi:10.1039/D2CE00822J
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.cc27nq1p
title: CCDC 2075482: Experimental Crystal Structure Determination

description: Related Article: Raghavender Medishetty, Akansha Ekka, Caroline Evania Mulijanto, Rika Tandiana, Jagadese J. Vittal|2022|CrystEngComm|24|6330|doi:10.1039/D2CE00822J
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.cc27nq2q
title: CCDC 2075483: Experimental Crystal Structure Determination

description: Related Article: Raghavender Medishetty, Akansha Ekka, Caroline Evania Mulijanto, Rika Tandiana, Jagadese J. Vittal|2022|CrystEngComm|24|6330|doi:10.1039/D2CE00822J
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.cc28bb43
title: CCDC 2095294: Experimental Crystal Structure Determination

description: Related Article: Anna Broto-Ribas, María Susana Gutiérrez, Inhar Imaz, Arnau Carné-Sánchez, Felipe Gándara, Judith Juanhuix, Daniel Maspoch|2022|Chem.Commun.|58|10480|doi:10.1039/D2CC03220A
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.cc28bb32
title: CCDC 2095293: Experimental Crystal Structure Determination

description: Related Article: Anna Broto-Ribas, María Susana Gutiérrez, Inhar Imaz, Arnau Carné-Sánchez, Felipe Gándara, Judith Juanhuix, Daniel Maspoch|2022|Chem.Commun.|58|10480|doi:10.1039/D2CC03220A
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.cc29bgjn
title: CCDC 2125221: Experimental Crystal Structure Determination

description: Related Article: Pavel S. Gribov, Kyrill Yu. Suponitsky, Aleksei B. Sheremetev|2022|New J.Chem.|46|17548|doi:10.1039/D2NJ03521A
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.cc29bgkp
title: CCDC 2125222: Experimental Crystal Structure Determination

description: Related Article: Pavel S. Gribov, Kyrill Yu. Suponitsky, Aleksei B. Sheremetev|2022|New J.Chem.|46|17548|doi:10.1039/D2NJ03521A
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: 10.6084/m9.figshare.21165454
title: Identification of key genes associated with inflammation in major depressive disorder progression and its effects on peripheric immune cell infiltration

description: Obtained the gene expression data of peripheral blood provided by patients with MDD and normal volunteers from the GEO database, and evaluated the inflammation scores in each sample via single sample gene set enrichment analysis (ssGSEA) algorithm. Then, WGCNA was conducted to analyze the gene modules associated with inflammation score and the MDD state.
DOI: 10.6084/m9.figshare.20310771.v1
title: EEL Mouse 440 genes single cell data

description: <strong>Loom file containing the cell by gene table of the EEL mouse 440 gene experiment.</strong> <br> Single cell data generated by EEL FISH on a saggital mouse brain section. .loom files can be opened with: http://loompy.org/ <br> Alternatively there is also a .tab file. <br> <strong>Metadata</strong> Age - Age of animal. Codebook - Name of EEL codebook ColorDict - Cell cluster color dictionary. Cycles - Number of barcoding cycles.<br> Expansion - Pixels the nuceli were expanded (pixelsize = 0.27um)<br> Expansion_um - Expansion of nuclei in micrometer.<br> Experiment - Experiment ID<br> ExperimentDate - Date of experiment<br> FOVoverlapPercentage - Overlap between field of view.<br> GenerationDate - Loom file generation date.<br> LOOM_SPEC_VERSION - Loompy version.<br> MaxHammingDist - maximum allowed Hamming distance.<br> Operator - Experiment operator.<br> Orientation - Cutting orientation.<br> Probes - Probe sequences file.<br> Protocol - Protocol used.<br> Quality - Manual evaluation of quality.<br> RNAfile - RNA file used<br> Removal - Method of removal of overlapping RNA in overlapping fields of view.<br> Sample - Sample ID<br> Segmentation - Segmentation algorithm.<br> Species - Species of sample.<br> Stitching - Field of view stitching method.<br> StitchingChannel - Between cycle alignment channel.<br> Strain - Strain of animal.<br> System - Microscope system used.<br> Tissue - Tissue in experiment.<br> TotalMolecules - Total number of molecules assigned to cells. <br> <strong>Column metadata</strong> X - X coordinate in pixels of 0.27um (multiply by 0.27 to get micrometer) X_um - X coordinate in micrometer. Y - Y coordinate in pixels of 0.27um (multiply by 0.27 to get micrometer) Y_um - Y coordinate in micrometer. tSNE_X - tSNE component 1. tSNE_Y - tSNE component 2. Clusters - Cluster label of each cell. TotalMolecules - Total molecules per cell. Cluster colors are saved as individual RGB values: R - Red. G - Green. B - Blue. <br> <strong>Row metadata</strong> Gene - Gene name GeneTotal - Total number of detected molecules per gene.
DOI: 10.34740/kaggle/dsv/4228344
title: Arabic Viral Tweets (عربي)
DOI: 10.6084/m9.figshare.20412501
title: Computational study on the reduction and solvolysis of triplet chlorobenzenes - geometries

description: "Computational study on the reduction and solvolysis of triplet chlorobenzenes"
DOI: 10.6084/m9.figshare.20412501.v2
title: Computational study on the reduction and solvolysis of triplet chlorobenzenes - geometries

description: "Computational study on the reduction and solvolysis of triplet chlorobenzenes"
DOI: 10.6084/m9.figshare.20412501.v1
title: geometries_xyz.zip

description: "Computational study on the reduction and solvolysis of triplet chlorobenzenes"
DOI: 10.21223/wqmmsn/peaxdq
title: 01_Data.tab

description: :unav
DOI: 10.21223/wqmmsn/oskcxh
title: 02_Dictionary.tab

description: :unav
DOI: 10.6084/m9.figshare.21165613.v1
title: ciconia_abdimii_zanfona_1.fasta.gz

description: .......
DOI: 10.6084/m9.figshare.21165613
title: ciconia_abdimii_zanfona_1.fasta.gz

description: .......
DOI: 10.34820/fk2/l0fm7x/ceqf7e
title: ontologicorpus.csv

description: :unav
DOI: 10.34820/fk2/l0fm7x
title: Ontology Corpus for Big Five Personality Measurement

description: Ontology Corpus for Big Five Personality Quantification
DOI: 10.34740/kaggle/dsv/4225387
title: SMART-PDM Dataset
DOI: 10.5281/zenodo.7095100
title: Datasets for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings

description: <strong>Introduction</strong> The datasets for training and evaluating our model for explainable depression detection on Twitter aided by metaphor concept mappings proposed in the following paper: Sooji, Han, Rui Mao, and Erik Cambria. "Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings." In Proceedings of the 29th International Conference on Computational Linguistics (COLING), 2022. in press Source code for our model is available at github.com/soojihan/HAN. These datasets were generated using the dataset proposed in Shen et al., 2017. The original dataset is available at github.com/sunlightsgy/MDDL. <strong>Description</strong> There are three datasets. <strong>1. mdl_HAN: </strong>This dataset contains tweets and metaphor concept mappings (MCMs) for 5,899 positive (i.e. depressed) and 4,469 negative users. Tweets in this dataset are extracted from the original MDDL dataset (Shen et al., 2017). MCMs were extracted using MetaPro (Mao et al., 2022). Please refer to our paper for more details.The name of each subfolder under the 'positive' and 'negative' subfolders is tweet userid. Each user's folder contains one or two json files: [userid].json: This json file contains tweet text objects, each of which is represented by [timestamp, tweet text]. [userid]_cm.json: This json file contains MCMs, each of which is represented by [timestamp, MCM] Note that some users do not have MCMs. There's no [userid]_cm.json file in such users' folders. <strong>2. imdl_HAN: </strong>This dataset has the same contents and structure as mdl_HAN except that explicit linguistic cues for depression (i.e., “I’m/I was/I am/I’ve been diagnosed depression” and words containing “depress”, “diagnos”, “anxiety”, “bipolar” and “disorder”) were removed from all tweets. <strong>3. sampled_training_eval_data: </strong>This dataset contains 5 randomly sampled cross-validation sets. Each of the five set contains train.csv, test,csv and dev.csv. Each csv file contains user ids. <strong>Remarks</strong> If you use the datasets, please cite our paper: Sooji, Han, Rui Mao, and Erik Cambria. "Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings." In Proceedings of the 29th International Conference on Computational Linguistics (COLING), 2022. in press <strong>Contact</strong> If you have any questions about the datasets or source code for our model, please contact Sooji Han. <strong>References</strong> Shen, Guangyao, Jia Jia, Liqiang Nie, Fuli Feng, Cunjun Zhang, Tianrui Hu, Tat-Seng Chua, and Wenwu Zhu. "Depression detection via harvesting social media: A multimodal dictionary learning solution." In <em>IJCAI</em>, pp. 3838-3844. 2017. Rui Mao, Xiao Li, Mengshi Ge, and Erik Cambria. 2022. MetaPro: A computational metaphor pro- cessing model for text pre-processing. Information Fusion, 86-87:30–43.
DOI: 10.5281/zenodo.7095099
title: Datasets for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings

description: <strong>Introduction</strong> The datasets for training and evaluating our model for explainable depression detection on Twitter aided by metaphor concept mappings proposed in the following paper: Sooji, Han, Rui Mao, and Erik Cambria. "Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings." In Proceedings of the 29th International Conference on Computational Linguistics (COLING), 2022. in press Source code for our model is available at github.com/soojihan/HAN. These datasets were generated using the dataset proposed in Shen et al., 2017. The original dataset is available at github.com/sunlightsgy/MDDL. <strong>Description</strong> There are three datasets. <strong>1. mdl_HAN: </strong>This dataset contains tweets and metaphor concept mappings (MCMs) for 5,899 positive (i.e. depressed) and 4,469 negative users. Tweets in this dataset are extracted from the original MDDL dataset (Shen et al., 2017). MCMs were extracted using MetaPro (Mao et al., 2022). Please refer to our paper for more details.The name of each subfolder under the 'positive' and 'negative' subfolders is tweet userid. Each user's folder contains one or two json files: [userid].json: This json file contains tweet text objects, each of which is represented by [timestamp, tweet text]. [userid]_cm.json: This json file contains MCMs, each of which is represented by [timestamp, MCM] Note that some users do not have MCMs. There's no [userid]_cm.json file in such users' folders. <strong>2. imdl_HAN: </strong>This dataset has the same contents and structure as mdl_HAN except that explicit linguistic cues for depression (i.e., “I’m/I was/I am/I’ve been diagnosed depression” and words containing “depress”, “diagnos”, “anxiety”, “bipolar” and “disorder”) were removed from all tweets. <strong>3. sampled_training_eval_data: </strong>This dataset contains 5 randomly sampled cross-validation sets. Each of the five set contains train.csv, test,csv and dev.csv. Each csv file contains user ids. <strong>Remarks</strong> If you use the datasets, please cite our paper: Sooji, Han, Rui Mao, and Erik Cambria. "Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings." In Proceedings of the 29th International Conference on Computational Linguistics (COLING), 2022. in press <strong>Contact</strong> If you have any questions about the datasets or source code for our model, please contact Sooji Han. <strong>References</strong> Shen, Guangyao, Jia Jia, Liqiang Nie, Fuli Feng, Cunjun Zhang, Tianrui Hu, Tat-Seng Chua, and Wenwu Zhu. "Depression detection via harvesting social media: A multimodal dictionary learning solution." In <em>IJCAI</em>, pp. 3838-3844. 2017. Rui Mao, Xiao Li, Mengshi Ge, and Erik Cambria. 2022. MetaPro: A computational metaphor pro- cessing model for text pre-processing. Information Fusion, 86-87:30–43.
DOI: 10.6084/m9.figshare.20324820.v1
title: EEL mouse sagittal 440 gene RNA spatial data

description: <strong>Raw RNA locations of a sagittal mouse brain section produced by EEL FISH for 440 genes.</strong> RNA files are in the .parquet format which can be opened with FISHscale (https://github.com/linnarsson-lab/FISHscale) or any other parquet file reader (https://arrow.apache.org/docs/index.html) <br> <strong>RNA .parquet files</strong> Position and gene label for all RNA molecules. <br> "c_px_microscope_stitched" contains X coordinates. "r_px_microscope_stitched" contians Y coordinates. The unit are pixels with a size of 0.18 micrometer. Multiply by 0.18 to get um scale. <br> "c_transformed" contains X coordinates. "r_transformed" contains Y coordinates. The units are pixels with a size of 0.27 micrometer. Multiply by 0.27 to get um scale. These coordinates match the coordinates in the single cell .loom file. <br> "hamming_distance" is the hamming distance divided by the barcode length (16). The closer to 0 the better the barcode. <br> <strong>Tissue polygon .csv file</strong> The .csv flie contains a polygon of the tissue area to clip RNA molecules outside. The unit size is in micrometer. <br> <strong>Gene colors .pkl file</strong> Pickled Python dictionary with gene colors used in the paper.