cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/x4ychgbcv7.1
title: Bessa-Gonçalves et al2021_Cytokine array data

description: The hypothesis underlying this data was that modifying Fibrinogen (Fg) scaffolds with Magnesium (Mg) incorporation could modulate macrophage polarisation towards M2 anti-inflammatory phenotype, in vitro and in vivo.
Cytokine array data are provided for:
- Human cytokine array. Cytokines present in conditioned media from macrophages cultured, for 13 days, in Fg and FgMg (10 mM) scaffolds in the presence/absence of M1 stimulation (LPS+INFg) were quantified at Eve Technologies Corp. (Calgary, AB, Canada) using the Human Cytokine Array/Chemokine Array 48-Plex: soluble CD40 ligand (sCD40L), epidermal growth factor (EGF), Eotaxin/CCL11, fibroblast growth factor 2 (FGF-2), FMS-related tyrosine kinase 3 ligand (Flt-3 ligand), Fractalkine/CX3CL1, granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), growth-regulated on alpha protein (GRO-⍺/CXCL1), interferon alpha-2 (IFN⍺2), interferon gamma (IFN𝛄), interleukin (IL)-1⍺, IL-1β, IL-1ra, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17A, IL-17E/IL-25, IL-17F, IL-18, IL-22, IL-27, interferon induced protein 10 (IP-10/CXCL10), monocyte chemoattractant protein (MCP)-1/CCL2, MCP-3/CCL7, macrophage colony-stimulating factor (M-CSF), macrophage-derived chemokine (MDC/CCL22), monokine induced by interferon gamma (MIG/CXCL9), macrophage inflammatory protein -1 alpha (MIP-1⍺/CCL3), macrophage inflammatory protein -1 beta (MIP-1β/CCL4), platelet derived growth factor (PDGF)-AA, PDGF-AB/BB, regulated upon activation, normal T cell expressed, and secreted (RANTES/CCL5), transforming growth factor alpha (TGF⍺), tumor necrosis factor (TNF)⍺, TNFβ and vascular endothelial growth factor A (VEGF-A). The sensitivity of the assay for the analysed markers ranged from 0.14 to 50.78 pg/mL.

- Mouse cytokine array. Cytokines present in inflammatory exudates were quantified at Eve Technologies Corp. (Calgary, AB, Canada) using the using the Mouse Cytokine Array/Chemokine Array 44-Plex: Eotaxin/CCL11, Erythropoietin, 6Ckine/CCL21, Fractalkine/CX3CL1, G-CSF, GM-CSF, interferon beta 1 (IFNB1), IFN𝛄, IL-1⍺, IL-1β, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-11, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-16, IL-17, IL-20, IP-10, keratinocyte chemoattractant (KC), leukemia inhibitor factor (LIF), lipopolysaccharide-induced CXC chemokine (LIX/CXCL5), MCP-1/CCL2, MCP-5/CCL12, M-CSF, MDC/CCL22, MIG/CXCL9, MIP-1⍺/CCL3, MIP-1β/CCL4, MIP-2/CXCL2, MIP-3⍺/CCL20, MIP-3B/CCL19, RANTES, thymus- and activation-regulated chemokine (TARC/CCL17), tissue inhibitor of metalloproteinase (TIMP)-1, TNFα, and VEGF. The sensitivity of the assay for the analysed markers ranged from 0.1 to 33.3 pg/mL.

Both data for a pilot run (performed to determine if sample concentration was appropriate) and a run for all the other samples are provided. The sample identification legend is provided in all the files.
DOI: 10.6084/m9.figshare.17283764.v1
title: Types of Publications in COVID-19 Research

description: The PubMed search was conducted on December 15, 2021, to find out the number of publications in COVID-19 research for each category of publication type defined in PubMed. For example, the number of review papers on COVID-19 was retrieved using the following search terms:<br>(((COVID [Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (SARS-CoV-2[Title/Abstract])) AND (Review[PT])<br><br>
DOI: 10.6084/m9.figshare.17283764.v2
title: Number of COVID-related publications in each publication type according to PubMed

description: The PubMed search was conducted on March 26, 2022, to find out the number of publications in COVID-19 research for each category of publication type defined in PubMed. <br><br>The PubMed search was conducted using the following search terms:(((COVID[Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (SARS-CoV-2[Title/Abstract])) AND (("2020/01"[Date - Publication] : "2020/11"[Date - Publication])) AND X<sup>a</sup>[PT]<br><sup>a</sup>X represents one of seventy-nine publication types in PubMed.<br><br>
DOI: 10.6084/m9.figshare.19425932
title: Energia_e_emissoes_2018.xlsx

description: Cálculo dos coeficientes de energia e carbono para a matriz energética brasileira de 2018.
DOI: 10.6084/m9.figshare.19425932.v1
title: Energia_e_emissoes_2018.xlsx

description: Cálculo dos coeficientes de energia e carbono para a matriz energética brasileira de 2018.
DOI: 10.6084/m9.figshare.17283764.v3
title: Number of COVID-related publications in each publication type according to PubMed

description: The PubMed search was conducted on March 26, 2022, to find out the number of publications in COVID-19 research for each category of publication type defined in PubMed. <br><br>The PubMed search was conducted using the following search terms:(((COVID[Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (SARS-CoV-2[Title/Abstract])) AND (("2020/01"[Date - Publication] : "2020/11"[Date - Publication])) AND X<sup>a</sup>[PT]<br><sup>a</sup>X represents one of seventy-nine publication types in PubMed.<br><br>
DOI: 10.5281/zenodo.6387025
title: Verbascum thapsus decontaminated FSCR

description: .
DOI: 10.5281/zenodo.6387024
title: Verbascum thapsus decontaminated FSCR

description: .
DOI: 10.6084/m9.figshare.17283764
title: Number of COVID-related publications in each publication type according to PubMed

description: The PubMed search was conducted on March 26, 2022, to find out the number of publications in COVID-19 research for each category of publication type defined in PubMed. <br><br>The PubMed search was conducted using the following search terms:(((COVID[Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (SARS-CoV-2[Title/Abstract])) AND (("2020/01"[Date - Publication] : "2020/11"[Date - Publication])) AND X<sup>a</sup>[PT]<br><sup>a</sup>X represents one of seventy-nine publication types in PubMed.<br><br>
DOI: 10.6084/m9.figshare.17283764.v5
title: Number of COVID-related publications in each publication type according to PubMed

description: The PubMed search was conducted on March 26, 2022, to find out the number of publications in COVID-19 research for each category of publication type defined in PubMed. <br><br>The PubMed search was conducted using the following search terms:(((COVID[Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (SARS-CoV-2[Title/Abstract])) AND (("2020/01"[Date - Publication] : "2020/11"[Date - Publication])) AND X<sup>a</sup>[PT]<br><sup>a</sup>X represents one of seventy-nine publication types in PubMed.<br><br>
DOI: 10.6084/m9.figshare.17283764.v4
title: Number of COVID-related publications in each publication type according to PubMed

description: The PubMed search was conducted on March 26, 2022, to find out the number of publications in COVID-19 research for each category of publication type defined in PubMed. <br><br>The PubMed search was conducted using the following search terms:(((COVID[Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (SARS-CoV-2[Title/Abstract])) AND (("2020/01"[Date - Publication] : "2020/11"[Date - Publication])) AND X<sup>a</sup>[PT]<br><sup>a</sup>X represents one of seventy-nine publication types in PubMed.<br><br>
DOI: 10.5281/zenodo.6387001
title: ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type Inference

description: In this paper, we present ManyTypes4TypeScript, a very large corpus for training and evaluating machine-learning models for sequence-based type inference in TypeScript. The dataset includes over 9 million type annotations, across 13,953 projects and 539,571 files. The dataset is approximately 10x larger than analogous type inference datasets for Python, and is the largest available for TypeScript. We also provide API access to the dataset, which can be integrated into any tokenizer and used with any state-of-the-art sequence-based model. Finally, we provide analysis and performance results for state-of-the-art code-specific models, for baselining. ManyTypes4TypeScript is available on Huggingface and Zenodo. This dataset was collected on January 22, 2022 and deduplicated with Allamanis code deduplication tool.
DOI: 10.5281/zenodo.6336113
title: ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type Inference

description: In this paper, we present ManyTypes4TypeScript, a very large corpus for training and evaluating machine-learning models for sequence-based type inference in TypeScript. The dataset includes over 9 million type annotations, across 13,953 projects and 539,571 files. The dataset is approximately 10x larger than analogous type inference datasets for Python, and is the largest available for TypeScript. We also provide API access to the dataset, which can be integrated into any tokenizer and used with any state-of-the-art sequence-based model. Finally, we provide analysis and performance results for state-of-the-art code-specific models, for baselining. ManyTypes4TypeScript is available on Huggingface and Zenodo. This dataset was collected on January 22, 2022 and deduplicated with Allamanis code deduplication tool.
DOI: 10.6084/m9.figshare.19425941
title: qoldata_20

description: Dataset of QoL study in Amazon population
DOI: 10.6084/m9.figshare.19425941.v1
title: qoldata_20

description: Dataset of QoL study in Amazon population
DOI: 10.26009/s0gjxjxc
title: TDB-19-1

description: Experiment to explore the impact of flooding on delta surface processes. Two flooding states were imposed: high-intensity flooding, and low-intensity flooding. The system cycled between these states over the experimental runtime. Each flood regime was held constant for a set period to allow surface processes to equilibrate between each transition. Each transition in flooding took place over a planned duration. The water level rise in the basin and the integrated water and sediment flux were held constant over the experimental runtime.
DOI: 10.5517/ccdc.csd.cc26v104
title: CCDC 2050805: Experimental Crystal Structure Determination

description: Related Article: Biao Wang, Xiao Yan, Han Zhong, Qin Ouyang, Xu Tian|2022|Org.Chem.Front.|9|1621|doi:10.1039/D1QO01708J
DOI: 10.5517/ccdc.csd.cc2795b2
title: CCDC 2064393: Experimental Crystal Structure Determination

description: Related Article: Ainur D. Sharapov, Ramil F. Fatykhov, Igor A. Khalymbadzha, Vladimir V. Sharutin, Sougata Santra, Grigory V. Zyryanov, Oleg N. Chupakhin, Brindaban C. Ranu|2022|Green Chemistry|24|2429|doi:10.1039/D1GC04564D
DOI: 10.5517/ccdc.csd.cc27hhmw
title: CCDC 2070478: Experimental Crystal Structure Determination

description: Related Article: Hongfang Li, Ijaz Khan, Qun Li, Yong Jian Zhang|2022|Org.Lett.|24|2081|doi:10.1021/acs.orglett.2c00142
DOI: 10.5517/ccdc.csd.cc21plmz
title: CCDC 1897591: Experimental Crystal Structure Determination

description: Related Article: Wiem Jabeur, Marcus Korb, Jamelah S. Al-Otaibi, Erik Čižmár, Riadh Badraoui, Vladimir Zeleňák, Houcine Naïli|2022|Inorg.Chem.Commun.|139|109279|doi:10.1016/j.inoche.2022.109279
DOI: 10.5517/ccdc.csd.cc27sdfw
title: CCDC 2079028: Experimental Crystal Structure Determination

description: Related Article: Avantika Hasija, Subham Ranjan, Sarah Guerin, S. R. N. Kiran Mangalampalli, Satoshi Takamizawa, Deepak Chopra|2022|J.Mater.Chem.C|10|4257|doi:10.1039/D2TC00076H
DOI: 10.5517/ccdc.csd.cc27sdgx
title: CCDC 2079029: Experimental Crystal Structure Determination

description: Related Article: Avantika Hasija, Subham Ranjan, Sarah Guerin, S. R. N. Kiran Mangalampalli, Satoshi Takamizawa, Deepak Chopra|2022|J.Mater.Chem.C|10|4257|doi:10.1039/D2TC00076H
DOI: 10.5517/ccdc.csd.cc27sdhy
title: CCDC 2079030: Experimental Crystal Structure Determination

description: Related Article: Avantika Hasija, Subham Ranjan, Sarah Guerin, S. R. N. Kiran Mangalampalli, Satoshi Takamizawa, Deepak Chopra|2022|J.Mater.Chem.C|10|4257|doi:10.1039/D2TC00076H
DOI: 10.5517/ccdc.csd.cc28dt1k
title: CCDC 2097678: Experimental Crystal Structure Determination

description: Related Article: Hongfang Li, Ijaz Khan, Qun Li, Yong Jian Zhang|2022|Org.Lett.|24|2081|doi:10.1021/acs.orglett.2c00142
DOI: 10.5517/ccdc.csd.cc28z3w8
title: CCDC 2114320: Experimental Crystal Structure Determination

description: Related Article: Ze-Le Chen, Claire Empel, Kun Wang, Pan-Pan Wu, Bao-Gui Cai, Lei Li, Rene M. Koenigs, Jun Xuan|2022|Org.Lett.|24|2232|doi:10.1021/acs.orglett.2c00609
DOI: 10.5517/ccdc.csd.cc28z3x9
title: CCDC 2114321: Experimental Crystal Structure Determination

description: Related Article: Ze-Le Chen, Claire Empel, Kun Wang, Pan-Pan Wu, Bao-Gui Cai, Lei Li, Rene M. Koenigs, Jun Xuan|2022|Org.Lett.|24|2232|doi:10.1021/acs.orglett.2c00609
DOI: 10.5517/ccdc.csd.cc2923k2
title: CCDC 2117193: Experimental Crystal Structure Determination

description: Related Article: Xiao-Dong Tao, Zhuangzhuang Wei, Lingyi Meng, Xu-Lin Chen, Mingxue Yang, Yan-Yun Jing, Dong-Hai Zhang, Can-Zhong Lu|2022|Mater. Chem. Front.|6|748|doi:10.1039/D1QM01660A
DOI: 10.5517/ccdc.csd.cc295pck
title: CCDC 2120628: Experimental Crystal Structure Determination

description: Related Article: M. S. S. Vinod Mouli, Ashutosh Kumar Mishra|2022|CrystEngComm|24|2221|doi:10.1039/D2CE00071G
DOI: 10.5517/ccdc.csd.cc295pdl
title: CCDC 2120629: Experimental Crystal Structure Determination

description: Related Article: M. S. S. Vinod Mouli, Ashutosh Kumar Mishra|2022|CrystEngComm|24|2221|doi:10.1039/D2CE00071G
DOI: 10.5517/ccdc.csd.cc28pk9v
title: CCDC 2106087: Experimental Crystal Structure Determination

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DOI: 10.15156/bio/sh1446518.08fu
title: SH1446518.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1595108.08fu
title: SH1595108.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1595109.08fu
title: SH1595109.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1446519.08fu
title: SH1446519.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1446520.08fu
title: SH1446520.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1595110.08fu
title: SH1595110.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1595111.08fu
title: SH1595111.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1595112.08fu
title: SH1595112.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.25549/one-c4-28956
title: Leslie Akers, letters (1969/1985)

description: Leslie Akers, greeting card, forms, layouts, fliers, letters, postcard, responses from W. Dorr Legg (1969/1985)
DOI: 10.15156/bio/sh1446521.08fu
title: SH1446521.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.