cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc25yrnk
title: CCDC 2024599: Experimental Crystal Structure Determination

description: Related Article: Güneş Süheyla Kürkçüoğlu, Okan Zafer Yeşilel, Seray Kekeç, Onur Şahin|2022|J.Mol.Struct.|1274|134540|doi:10.1016/j.molstruc.2022.134540
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.cc2c3pjq
title: CCDC 2178293: Experimental Crystal Structure Determination

description: Related Article: Dong HuiYang|2022|CSD Communication|||
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.7295091
title: single-cell RNAseq data (data set 20) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

description: The present dataset (dataset20) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from breast cancer samples downloaded from the GEO website (GSE180286)<strong>. </strong> see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.
DOI: 10.5281/zenodo.7295090
title: single-cell RNAseq data (data set 20) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

description: The present dataset (dataset20) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from breast cancer samples downloaded from the GEO website (GSE180286)<strong>. </strong> see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.
DOI: 10.5281/zenodo.7295118
title: Discretized bulk data by the discretization step of rFASTCORMICS used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

description: Bulk data RNAseq data were downloaded from GEO, GTEX, and other sources (see below) and discretized by the discretization step of rFASTCORMICS (Pacheco et al, 2019) used in the optimization step in scFASTCORMICS: CRC bulk RNAseq data were obtained from Lee et al(2020) <br> CRC control (NM) was downloaded from GSE81861 (GTEX, Healthy colon from) Pancreatic Human islet bulk RNAseq data was downloaded from EBI Expression Atlas (Pancreatic islet cells) Immune cells in pancreatic carcinoma bulk data were obtained from GEO (GSE156278) liver and breast cancer bulk RNAseq data were obtained from the TCGA (GSE62944) rFASTCORMICS and tutorial on rFASTCORMICS can be found: https://github.com/sysbiolux <br>
DOI: 10.5281/zenodo.7295117
title: Discretized bulk data by the discretization step of rFASTCORMICS used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

description: Bulk data RNAseq data were downloaded from GEO, GTEX, and other sources (see below) and discretized by the discretization step of rFASTCORMICS (Pacheco et al, 2019) used in the optimization step in scFASTCORMICS: CRC bulk RNAseq data were obtained from Lee et al(2020) <br> CRC control (NM) was downloaded from GSE81861 (GTEX, Healthy colon from) Pancreatic Human islet bulk RNAseq data was downloaded from EBI Expression Atlas (Pancreatic islet cells) Immune cells in pancreatic carcinoma bulk data were obtained from GEO (GSE156278) liver and breast cancer bulk RNAseq data were obtained from the TCGA (GSE62944) rFASTCORMICS and tutorial on rFASTCORMICS can be found: https://github.com/sysbiolux <br>
DOI: 10.5281/zenodo.7339762
title: Evolución y comparación histórica de precios de la electricidad en España entre el mercado libre y el mercado regulado.

description: Datos obtenidos de la web https://www.esios.ree.es acerca del precio y consumo de la energía por Red Eléctrica Española.
DOI: 10.5281/zenodo.7339763
title: Evolución y comparación histórica de precios de la electricidad en España entre el mercado libre y el mercado regulado.

description: Datos obtenidos de la web https://www.esios.ree.es acerca del precio y consumo de la energía por Red Eléctrica Española.
DOI: 10.5281/zenodo.7342518
title: Evolución y comparación histórica de precios de la electricidad en España entre el mercado libre y el mercado regulado.

description: Datos obtenidos de la web https://www.esios.ree.es acerca del precio y consumo de la energía por Red Eléctrica Española.
DOI: 10.5281/zenodo.7347752
title: Evolución y comparación histórica de precios de la electricidad en España entre el mercado libre y el mercado regulado.

description: Datos obtenidos de la web https://www.esios.ree.es acerca del precio y consumo de la energía por Red Eléctrica Española.
DOI: 10.5281/zenodo.7295505
title: Optimization used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

description: OptimizationResults contain the expanded input model for each data set, in the C field are the indices of the core reactions in the expanded input model used to build the multi-cell population for the 121 different parameters, A contains the indices of reaction in the multi-cell population model for the 121 runs, thresh the parameter setting for the cover and REI. The REI is given in %. So 5 REI means 0.05. While A might change because of alternative optimals when run on a different computer, C and the expanded Input model will remain unchanged. Multi_cell_population_CRC and Multi_cell_population_NM are the models obtained by scFASTCORMICS with the optimal setting for Dataset1 and Dataset2, respectively. Please, check the publication (scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data) for more details.
DOI: 10.5281/zenodo.7295504
title: Optimization used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

description: OptimizationResults contain the expanded input model for each data set, in the C field are the indices of the core reactions in the expanded input model used to build the multi-cell population for the 121 different parameters, A contains the indices of reaction in the multi-cell population model for the 121 runs, thresh the parameter setting for the cover and REI. The REI is given in %. So 5 REI means 0.05. While A might change because of alternative optimals when run on a different computer, C and the expanded Input model will remain unchanged. Multi_cell_population_CRC and Multi_cell_population_NM are the models obtained by scFASTCORMICS with the optimal setting for Dataset1 and Dataset2, respectively. Please, check the publication (scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data) for more details.
DOI: 10.5281/zenodo.7347768
title: Ship Wrecks dataset

description: Dataset of shipwrecks around the world. Extracted from wikipedia
DOI: 10.5281/zenodo.7347767
title: Ship Wrecks dataset

description: Dataset of shipwrecks around the world. Extracted from wikipedia
DOI: 10.5281/zenodo.7300150
title: Development of the multi-dimensional Mobility Divide Index as a methodology to assess the accessibility level of public transport systems

description: This paper presents the development of a multi-dimensional Mobility Divide Index (MDI) for assessing the accessibility of public transport developed using a co-design approach, directly involving end-users in the index design process. The index measures the gap that persons with disabilities feel they need to over-come to use public transport in the same way non-disabled citizens do. The MDI covers six accessibility-related dimensions: 1) safety, 2) convenience, 3) comfort, 4) affordability, 5) travel time, 6) autonomy. The method paper describes the step-by-step approach to create the MDI as a set of indicators to be rated by people with different access needs to a) provide evidence of the main criticalities to be addressed through the design and implementation of new inclusive mobility solutions, b) guide the design of new inclusive mobility solutions and measure their impacts and c) inform the transport sector encouraging positive changes in transport by providing recommendations for policy-making, new directions for service innovation, improvements and practical advice or highlighting investment priorities to pave the way for a more inclusive mobility. We present our findings in ways that can inform universal design and provide actionable information to researchers, policymakers, transport and urban planners, operators and stakeholders’ representatives to promote inclusive and equitable mobility solutions for all. Finally, we suggest follow up research and innovation, as well as recommendations for its uptake and utilisation in the pursuit of European accessibility standards and requirements for products and services in the mobility sector.
DOI: 10.5281/zenodo.7074346
title: Development of the multi-dimensional Mobility Divide Index as a methodology to assess the accessibility level of public transport systems

description: This paper presents the development of a multi-dimensional Mobility Divide Index (MDI) for assessing the accessibility of public transport developed using a co-design approach, directly involving end-users in the index design process. The index measures the gap that persons with disabilities feel they need to over-come to use public transport in the same way non-disabled citizens do. The MDI covers six accessibility-related dimensions: 1) safety, 2) convenience, 3) comfort, 4) affordability, 5) travel time, 6) autonomy. The method paper describes the step-by-step approach to create the MDI as a set of indicators to be rated by people with different access needs to a) provide evidence of the main criticalities to be addressed through the design and implementation of new inclusive mobility solutions, b) guide the design of new inclusive mobility solutions and measure their impacts and c) inform the transport sector encouraging positive changes in transport by providing recommendations for policy-making, new directions for service innovation, improvements and practical advice or highlighting investment priorities to pave the way for a more inclusive mobility. We present our findings in ways that can inform universal design and provide actionable information to researchers, policymakers, transport and urban planners, operators and stakeholders’ representatives to promote inclusive and equitable mobility solutions for all. Finally, we suggest follow up research and innovation, as well as recommendations for its uptake and utilisation in the pursuit of European accessibility standards and requirements for products and services in the mobility sector.
DOI: 10.6084/m9.figshare.21526038.v1
title: Subject_S1-S5.csv

description: Data File 1
DOI: 10.21227/5yz4-8816
title: Intelligent Forecasters: Data Analytical Tools Utilized to Have Financial Investments for Smart Cities Investors

description: This Dataset is related to the data prices of the cryptocurrency "Ethereum" over four years, from 01/01/2018 to 114/22/2022. Also, the new dataset created by the predictions of the intelligent filtered LSTM model is included.
DOI: 10.5281/zenodo.7347824
title: dataset for bioRxiv preprint titled 'Evolution of drug resistance drives progressive destabilizations in functionally conserved molecular dynamics of the flap region of the HIV-1 protease'

description: This data supports the Figures in the preprint titled <strong>Evolution of drug resistance drives progressive destabilizations in functionally conserved molecular dynamics of the flap region of the HIV-1 protease</strong> <strong>working abstract</strong> The HIV-1 protease is one of several common key targets of combination drug therapies for human immunodeficiency virus infection and acquired immunodeficiency syndrome (HIV/AIDS). During the progression of the disease, some individual patients acquire -drug resistance due to mutational hotspots on the viral proteins targeted by combination drug therapies. It has recently been discovered that drug-resistant mutations accumulate on the ‘flap region’ of the HIV-1 protease, which is a critical dynamic region involved in non-specific polypeptide binding during invasion and infection of the host cell. In this study, we utilize machine learning assisted comparative molecular dynamics, conducted at single amino acid site resolution, to investigate the dynamic changes that occur during functional dimerization and polypeptide binding of the main protease. We use a multi-agent machine learning model to identify conserved dynamics of the HIV-1 main protease that are preserved across simian and feline protease orthologs (SIV and FIV). We also investigate changes in dynamics due to common drug-resistant mutations in many patients. We find that a key functional site in the flap region, a solvent-exposed isoleucine (ILE50) and surrounding sites that control flap dynamics is often targeted by drug-resistance mutations, likely leading to malfunctional molecular dynamics affecting the overall flexibility of the flap region. We conclude that better long term patient outcomes may be achieved by designing drugs that target protease regions which are less dependent upon single sites with large functional binding effects.
DOI: 10.5281/zenodo.7347823
title: dataset for bioRxiv preprint titled 'Evolution of drug resistance drives progressive destabilizations in functionally conserved molecular dynamics of the flap region of the HIV-1 protease'

description: This data supports the Figures in the preprint titled <strong>Evolution of drug resistance drives progressive destabilizations in functionally conserved molecular dynamics of the flap region of the HIV-1 protease</strong> <strong>working abstract</strong> The HIV-1 protease is one of several common key targets of combination drug therapies for human immunodeficiency virus infection and acquired immunodeficiency syndrome (HIV/AIDS). During the progression of the disease, some individual patients acquire -drug resistance due to mutational hotspots on the viral proteins targeted by combination drug therapies. It has recently been discovered that drug-resistant mutations accumulate on the ‘flap region’ of the HIV-1 protease, which is a critical dynamic region involved in non-specific polypeptide binding during invasion and infection of the host cell. In this study, we utilize machine learning assisted comparative molecular dynamics, conducted at single amino acid site resolution, to investigate the dynamic changes that occur during functional dimerization and polypeptide binding of the main protease. We use a multi-agent machine learning model to identify conserved dynamics of the HIV-1 main protease that are preserved across simian and feline protease orthologs (SIV and FIV). We also investigate changes in dynamics due to common drug-resistant mutations in many patients. We find that a key functional site in the flap region, a solvent-exposed isoleucine (ILE50) and surrounding sites that control flap dynamics is often targeted by drug-resistance mutations, likely leading to malfunctional molecular dynamics affecting the overall flexibility of the flap region. We conclude that better long term patient outcomes may be achieved by designing drugs that target protease regions which are less dependent upon single sites with large functional binding effects.
DOI: 10.3886/e174501v1-130798
title: Data and Code for: Interaction, Stereotypes and Performance. Evidence from South Africa

description: Edit<b> 0_main.do </b>to adjust the default path to the base replication folder.Add all <b>ado</b> files to the relevant STATA folderRun <b>0_main</b><b>.do</b> to replicate the main and appendix tables and figures of the paper.
DOI: 10.5281/zenodo.7347848
title: Dataset Literatur Review or Cyber Law Helping Behavior

description: Dataset Literatur Review or Cyber Law Helping Behavior
DOI: 10.5281/zenodo.7347847
title: Dataset Literatur Review or Cyber Law Helping Behavior

description: Dataset Literatur Review or Cyber Law Helping Behavior
DOI: 10.24378/exe.4344
title: A survey of the research challenges and training needs in text analysis for political science research

description: This online survey assessed the research challenges, training needs and preferences of researchers and practitioners (of all seniority and skills level) that use or are interested in using text analysis techniques in their research. The survey has been conducted within the context of the Horizon 2020 OPTED project (http://www.opted.eu).
DOI: 10.23729/733c8f99-47ca-4114-b003-3f4e3fce9ceb
title: HITEC EB06-07

description: EB06 and EB07 samples of HITEC. Collective preview dataset at https://doi.org/10.23729/170132f5-ecba-4dc8-b248-001dc5795db5 Preview dataset found at https://doi.org/10.23729/24a57984-d17b-47d3-807a-a7a392859373 . To obtain data, please contact fairdata-pas@gtk.fi .
DOI: 10.5281/zenodo.7347780
title: Keyframe-level Captions for V3C

description: Image captions generated using CLIP-Caption-Reward and CLIP_prefix_caption for every Keyframe in the Vimeo Creative Commons Collection. Captions are grouped by captioning method and dataset shard and provided as CSV.
description: {"references": ["Cho, J., Yoon, S., Kale, A., Dernoncourt, F., Bui, T., & Bansal, M. (2022). Fine-grained image captioning with clip reward. arXiv preprint arXiv:2205.13115.", "Mokady, R., Hertz, A., & Bermano, A. H. (2021). Clipcap: Clip prefix for image captioning. arXiv preprint arXiv:2111.09734.", "Rossetto, L., Schuldt, H., Awad, G., & Butt, A. A. (2019, January). V3C\u2013a research video collection. In International Conference on Multimedia Modeling (pp. 349-360). Springer, Cham."]}
DOI: 10.5281/zenodo.7347779
title: Keyframe-level Captions for V3C

description: Image captions generated using CLIP-Caption-Reward and CLIP_prefix_caption for every Keyframe in the Vimeo Creative Commons Collection. Captions are grouped by captioning method and dataset shard and provided as CSV.
description: {"references": ["Cho, J., Yoon, S., Kale, A., Dernoncourt, F., Bui, T., & Bansal, M. (2022). Fine-grained image captioning with clip reward. arXiv preprint arXiv:2205.13115.", "Mokady, R., Hertz, A., & Bermano, A. H. (2021). Clipcap: Clip prefix for image captioning. arXiv preprint arXiv:2111.09734.", "Rossetto, L., Schuldt, H., Awad, G., & Butt, A. A. (2019, January). V3C\u2013a research video collection. In International Conference on Multimedia Modeling (pp. 349-360). Springer, Cham."]}
DOI: 10.57745/mf3gyi
title: Cartographie des unités typologiques de sol (format shapefile)

description: Ce fichier contient les données relatives à la cartographie des types de sols sur le domaine au 1/5000ème. Le fichier au format shapefile contient les polygones correspondants aux plages cartographiques des unités de sols identifiées. Les plages cartographiques ont été construites à partir des observations réalisées sur les sols au cours des levés de terrain (sondages pédologiques et observation du paysage) et lors de l’examen des fosses pédologiques ainsi que les analyses de sol. Les types de sol décrivant les unités typologiques ont été définis selon la nomenclature du référentiel pédologique 2008 (Baize et al., 2008). Le positionnement des sondages a été raisonné à partir des variations de la résistivité électrique. Les fosses pédologiques ont été positionnées à partir de l’esquisse cartographique réalisée sur la base des observations des sondages pédologiques de manière à caractériser le solum type de chaque unité de sol décrite. Les contours des unités ont été affinées à l'aide d’une carte de résistivité électrique.
DOI: 10.57745/ydmkhq
title: Notice synthétique des Unités Typologiques de Sols (format docx)

description: Le fichier au format texte est la notice synthétique des unités typologiques de sols (UTS). Il s’agit de la description littérale des grands traits pédologiques des différents typologies de sols présents sur le site.
DOI: 10.57745/dbzlfr
title: Table UTS

description: Le fichier « table-UTS » décrit des variables relatives aux unités typologiques de sol (UTS) : codification selon le Référentiel pédologique 2008, matériau parental, géologique, nombre d'observations par UTS, régime hydrique. Les champs utilisés sont décrits dans le dictionnaire de données Donesol (https://dw3.gissol.fr/fichiers/dictionnaire_donesol_igcs_3-15_31-03-2021.pdf).
DOI: 10.57745/hyktsb
title: Teneurs en eau à la capacité au champ et au point de flétrissement permanent

description: Cette table contient les résultats des mesures de teneurs en eau g.kg-1 à des valeurs de potentiels particuliers : 10 kPa (pF2) et 1500 kPa (pF4.2) selon le protocole Afnor NF (1994). Ces mesures ont été réalisées sur des échantillons de sol non remaniés de type « mottes ». Pour chaque horizon caractérisé, 8 répétitions ont été réalisées. Les résultats présents dans le fichier correspondent à la moyenne et l’écart-type. Ces valeurs permettent d’accéder au calcul du réservoir en eau utilisable en considérant la teneur en eau à pF2 comme la capacité au champ et la teneur en eau à pF4.2 comme le point de flétrissement permanent.
DOI: 10.57745/inb3zi
title: Table description profil

description: Cette table contient la description synthétique du profil de sol, qu’il s’agisse d’une fosse ou d’un sondage réalisé à la tarière. Elle décrit pour chaque profil son environnement, sa situation géomorphologique, l’organisation géologique, les différentes origines de la différenciation des horizons, les caractéristiques hydriques et la classification. Les champs utilisés font références à ceux du dictionnaire de données Donesol (https://dw3.gissol.fr/fichiers/dictionnaire_donesol_igcs_3-15_31-03-2021.pdf).
DOI: 10.57745/vk5fs1
title: Résistivité électrique (format grid)

description: Mesures des résistivités électriques spatialisées réalisées en sur la période du 6 au 21 octobre 2011, par la société Geocarta (outils ARP, Panissod et al. 1997) selon les trois voies de mesures. Chaque mesure est géoréférencée par un GPS différentiel (John Deere, Modèle StarFire ITC, précision planimétrique de l’ordre de 10 cm). Les mesures sont réalisées le long de profils avec un enregistrement tous les 10 cm. Les parcelles sont parcourues en réalisant des profils parallèles et régulièrement espacés (6 m ou 12 m). Les données sont fournies sous forme de grille (shapefile) et ont été interpolées (spline cubique) selon une maille de 3mx3m.