cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14724162.v3
title: Research Data

description: Original figure data for the reseach paper of global carbonate weathering carbon sink model
DOI: 10.6084/m9.figshare.14035853
title: Metadata record for the manuscript: Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX)

description: <b>Summary</b><br> This metadata record provides details of the data supporting the claims of the related manuscript: “Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX)”. The related study utilised breast cancer PDX from the Mayo Breast Cancer Genome Guided Therapy Study (BEAUTY) to establish two immortalised, genomically unique breast cancer cell lines. Type of data: whole exome sequencing Subject of data: <i>Mus musculus, </i>breast cancer patient-derived xenografts and matched PDX-derived immortalised human breast cancer cell lines Population characteristics: NSG NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (Stock No: 005557) female mice <b>Data access</b> Whole exome sequencing for each PDX and PDX-derived cell line are openly available in the <i>Sequence Read Archive </i>via accession https://identifiers.org/ncbi/insdc.sra:SRP274166 (BioProject accession: PRJNA649579). The following data are openly available as part of this data record: the histology images, in the zip file ‘Fig4_Histology.zip’; additional data supporting the figures and supplementary figures of the related article, in the Excel spreadsheet ‘Extended_Text_and_Tables.xlsx’. Additionally, Supplementary Tables 1-4 and the raw Western blot images are included with this data record, as well as with the related article. <b>Corresponding author(s) for this study</b> Liewei Wang M.D., Ph.D., Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905 USA. Tel: 507-284-5264; Fax: 507-284-4455; Email: wang.liewei@mayo.edu <br> <b>Study approval </b> All protocols for animal studies have been approved by the IACUC committee of Mayo Clinic.
DOI: 10.6084/m9.figshare.14035853.v1
title: Metadata record for the manuscript: Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX)

description: <b>Summary</b><br> This metadata record provides details of the data supporting the claims of the related manuscript: “Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX)”. The related study utilised breast cancer PDX from the Mayo Breast Cancer Genome Guided Therapy Study (BEAUTY) to establish two immortalised, genomically unique breast cancer cell lines. Type of data: whole exome sequencing Subject of data: <i>Mus musculus, </i>breast cancer patient-derived xenografts and matched PDX-derived immortalised human breast cancer cell lines Population characteristics: NSG NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (Stock No: 005557) female mice <b>Data access</b> Whole exome sequencing for each PDX and PDX-derived cell line are openly available in the <i>Sequence Read Archive </i>via accession https://identifiers.org/ncbi/insdc.sra:SRP274166 (BioProject accession: PRJNA649579). The following data are openly available as part of this data record: the histology images, in the zip file ‘Fig4_Histology.zip’; additional data supporting the figures and supplementary figures of the related article, in the Excel spreadsheet ‘Extended_Text_and_Tables.xlsx’. Additionally, Supplementary Tables 1-4 and the raw Western blot images are included with this data record, as well as with the related article. <b>Corresponding author(s) for this study</b> Liewei Wang M.D., Ph.D., Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905 USA. Tel: 507-284-5264; Fax: 507-284-4455; Email: wang.liewei@mayo.edu <br> <b>Study approval </b> All protocols for animal studies have been approved by the IACUC committee of Mayo Clinic.
DOI: 10.6084/m9.figshare.14169500.v1
title: SARS-COV-2 INFECTION IN CANCER PATIENTS: A POPULATION-BASED STUDY

description: Study population: all the residents in the Veneto and Friuli Venezia Giulia Regions (north-eastern Italy) who were consecutively tested for SARSCoV-2 infection between February 22nd and July 31st, 2020.Study variables: · demographics (age, sex) · comorbidities · history of malignant disease (prevalent diagnosis of malignant cancer, cancer site, interval between diagnosis of cancer and testing for SARS-CoV-2 infection) · clinical outcomes of SARS-CoV-2 infection (admission to hospital; admission to Intensive Care Unit; death)<br>
DOI: 10.34740/kaggle/dsv/2299204
title: UNET Lung Segmentation Weights for Chest X Rays
DOI: 10.5523/bris.25hgq8mkeef6c2flnyon8l1xv4
title: Balloon Data

description: Data from radiosonde launch 27 Aug 2018 and subsequent laboratory tests.
DOI: 10.5281/zenodo.4651477
title: Irish Car Stock Model V 2.4

description: <strong>Latest release of the Irish Car Stock Model Version 2.4</strong> The Irish Car Stock Model was first developed by Daly and Ó Gallachoir (2011a), entitled "Modelling private car energy demand using a technological car stock model". It is available at: https://doi.org/10.1016/j.trd.2010.08.009.<br> <br> Future scenarios were explored in Daly and Ó Gallachoir (2011b) entitled "Modelling future private car energy demand in Ireland", and is available at: https://doi.org/10.1016/j.enpol.2011.09.027<br> <br> Further updates to the Irish Car Stock Model were developed by Mulholland et al. (2017), the article entitled "Techno-economic data for a multi-model approach to decarbonisation of the Irish private car sector" is available at: https://doi.org/10.1016/j.dib.2017.10.006. Latest update is led by Vera O'Riordan, Hannah Daly, Fionn Rogan and Brian Ó Gallachóir. Included in this repository is the latest version of the Irish Car Stock Model 2.4, current updates to the Irish Car Stock Model V 2.5 are ongoing. For queries, errors and omissions please contact: vera.oriordan@ucc.ie
description: {"references": ["Daly, H. and \u00d3 Gallach\u00f3ir, B., 2011. Modelling private car energy demand using a technological car stock model. Transportation Research Part D: Transport and Environment, 16(2), pp.93-101.", "Daly, H. and \u00d3 Gallach\u00f3ir, B., 2011. Modelling future private car energy demand in Ireland. Energy Policy, 39(12), pp.7815-7824.", "Mulholland, E., Rogan, F. and Gallach\u00f3ir, B., 2017. Techno-economic data for a multi-model approach to decarbonisation of the Irish private car sector. Data in Brief, 15, pp.922-932."]}
DOI: 10.5281/zenodo.4651476
title: Irish Car Stock Model V 2.4

description: <strong>Latest release of the Irish Car Stock Model Version 2.4</strong> The Irish Car Stock Model was first developed by Daly and Ó Gallachoir (2011a), entitled "Modelling private car energy demand using a technological car stock model". It is available at: https://doi.org/10.1016/j.trd.2010.08.009.<br> <br> Future scenarios were explored in Daly and Ó Gallachoir (2011b) entitled "Modelling future private car energy demand in Ireland", and is available at: https://doi.org/10.1016/j.enpol.2011.09.027<br> <br> Further updates to the Irish Car Stock Model were developed by Mulholland et al. (2017), the article entitled "Techno-economic data for a multi-model approach to decarbonisation of the Irish private car sector" is available at: https://doi.org/10.1016/j.dib.2017.10.006. Latest update is led by Vera O'Riordan, Hannah Daly, Fionn Rogan and Brian Ó Gallachóir. Included in this repository is the latest version of the Irish Car Stock Model 2.4, current updates to the Irish Car Stock Model V 2.5 are ongoing. For queries, errors and omissions please contact: vera.oriordan@ucc.ie
description: {"references": ["Daly, H. and \u00d3 Gallach\u00f3ir, B., 2011. Modelling private car energy demand using a technological car stock model. Transportation Research Part D: Transport and Environment, 16(2), pp.93-101.", "Daly, H. and \u00d3 Gallach\u00f3ir, B., 2011. Modelling future private car energy demand in Ireland. Energy Policy, 39(12), pp.7815-7824.", "Mulholland, E., Rogan, F. and Gallach\u00f3ir, B., 2017. Techno-economic data for a multi-model approach to decarbonisation of the Irish private car sector. Data in Brief, 15, pp.922-932."]}
DOI: 10.5517/ccdc.csd.cc1lw3n7
title: CCDC 1485819: Experimental Crystal Structure Determination

description: Related Article: Rajib Sarkar|2018|J.Indian Chem.Soc.|95|971|
DOI: 10.5517/ccdc.csd.cc237ghb
title: CCDC 1943591: Experimental Crystal Structure Determination

description: Related Article: Wei-Ting Chen, Qiao Wang, Li-Jing Min, Hong-Ke Wu, Jian-Quan Weng, Chen-Xia Tan, Yong-Gang Zhang, Bei-Zhen Hu, Xing-Hai Liu|2019|Ind.J.Heterocycl.Chem.|29|429|
DOI: 10.5517/ccdc.csd.cc22c7h6
title: CCDC 1917427: Experimental Crystal Structure Determination

description: Related Article: Shijiang Yu, Wenxin Lin, Xiajuan Huang, Xiaokang Jin, Shuting Yao, Bing Wang, Hongliang Zhu, Jianjun Chen|2021|Polyhedron|205|115278|doi:10.1016/j.poly.2021.115278
DOI: 10.5517/ccdc.csd.cc138dd5
title: CCDC 1020966: Experimental Crystal Structure Determination

description: Related Article: Y. Sun, Z. Chen, X. Wang, L. Wang, X. Yang, X. Liang, S. Fan, P. Zhang|2021|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|77|291|doi:10.1107/S2053229621005143
DOI: 10.5517/ccdc.csd.cc138df6
title: CCDC 1020967: Experimental Crystal Structure Determination

description: Related Article: Y. Sun, Z. Chen, X. Wang, L. Wang, X. Yang, X. Liang, S. Fan, P. Zhang|2021|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|77|291|doi:10.1107/S2053229621005143
DOI: 10.5517/ccdc.csd.cc1zc66r
title: CCDC 1828014: Experimental Crystal Structure Determination

description: Related Article: S. Bargavi, S. Gouthaman, M. Sugunalakshmi, S. Lakshmi|2021|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|77|299|doi:10.1107/S2053229621004940
DOI: 10.5517/ccdc.csd.cc1zcgzs
title: CCDC 1828286: Experimental Crystal Structure Determination

description: Related Article: S. Bargavi, S. Gouthaman, M. Sugunalakshmi, S. Lakshmi|2021|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|77|299|doi:10.1107/S2053229621004940
DOI: 10.5517/ccdc.csd.cc1zcpfg
title: CCDC 1828486: Experimental Crystal Structure Determination

description: Related Article: S. Bargavi, S. Gouthaman, M. Sugunalakshmi, S. Lakshmi|2021|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|77|299|doi:10.1107/S2053229621004940
DOI: 10.25646/8583
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.5281/zenodo.4896714
title: Groundwater flow rate prediction from geo-electrical features using Support Vector Machines: Bagoue dataset, Cote d'Ivoire

description: We implemented a support vector machines to predict groundwater flow before drilling using electrical resistivity profiling, vertical electrical sounding. We used the data from Cote d’Ivoire, west part of Africa and we tested the composite estimator in region of Bagoue, north part of CIV. Data are composed on electrical resistivity profile, vertical electrical sounding and borehole data. The coordinates of different boreholes are also mentioned.
DOI: 10.5281/zenodo.4894498
title: AutoMCL_Repository

description: AutoMCL
DOI: 10.5281/zenodo.4894497
title: AutoMCL_Repository

description: AutoMCL
DOI: 10.5281/zenodo.4896758
title: Groundwater flow rate prediction from geo-electrical features using Support Vector Machines: Bagoue dataset, Cote d'Ivoire

description: We implemented a support vector machines to predict groundwater flow before drilling using electrical resistivity profiling, vertical electrical sounding. We used the data from Cote d’Ivoire, west part of Africa and we tested the composite estimator in region of Bagoue, north part of CIV. Data are composed on electrical resistivity profile, vertical electrical sounding and borehole data. The coordinates of different boreholes are also mentioned.
DOI: 10.5281/zenodo.4896724
title: tempset v0.1.0 Example Data

description: Example data for tempset v0.1.0 found here: https://github.com/IMMM-SFA/tempset This dataset represents the gas outputs from 2997 EnergyPlus v9 simulations corresponding to a diverse set of stochastic heating temperature setpoint schedules on weekdays, for a DOE Small Office Prototype model. The space heating in the building is provided by a gas furnace. Each CSV output has been compressed as a GZ file following this format: "gas_&lt;simulation&gt;_&lt;type if applicable&gt;.csv.gz" These files are used by the `<strong><code>aggregate_data()`</code></strong> function which aggregates EnergyPlus outputs at an hourly/sub-hourly resolution per day. Reference: EnergyPlus reference: U.S. Department of Energy. (2020). <em>EnergyPlus</em>. Retrieved on 2021-05-04 from https://www.energyplus.net/
description: {"references": ["EnergyPlus reference: U.S. Department of Energy. (2020). EnergyPlus. Retrieved on 2021-05-04 from https://www.energyplus.net/"]}
DOI: 10.5281/zenodo.4896723
title: tempset v0.1.0 Example Data

description: Example data for tempset v0.1.0 found here: https://github.com/IMMM-SFA/tempset This dataset represents the gas outputs from 2997 EnergyPlus v9 simulations corresponding to a diverse set of stochastic heating temperature setpoint schedules on weekdays, for a DOE Small Office Prototype model. The space heating in the building is provided by a gas furnace. Each CSV output has been compressed as a GZ file following this format: "gas_&lt;simulation&gt;_&lt;type if applicable&gt;.csv.gz" These files are used by the `<strong><code>aggregate_data()`</code></strong> function which aggregates EnergyPlus outputs at an hourly/sub-hourly resolution per day. Reference: EnergyPlus reference: U.S. Department of Energy. (2020). <em>EnergyPlus</em>. Retrieved on 2021-05-04 from https://www.energyplus.net/
description: {"references": ["EnergyPlus reference: U.S. Department of Energy. (2020). EnergyPlus. Retrieved on 2021-05-04 from https://www.energyplus.net/"]}
DOI: 10.21227/cwhs-t440
title: Bento Packaging Activity Recognition Challenge

description: Human activity recognition (HAR) has been one of the most prevailing and persuasive research topics in different fields for the past few decades. The main idea is to comprehend individuals’ regular activities by looking at bits of knowledge accumulated from people and their encompassing living environments based on sensor observations. HAR has a great impact on human-robot collaborative work, especially in industrial works. In compliance with this idea, we have organized this year’s Bento Packaging Activity Recognition Challenge. In this challenge, participants will have to design methods to identify different activities done during Bento-box packaging from MOCAP data. The data has been collected during the Bento-box packaging sessions inside the lab. We will organize a workshop at ABC Conference to discuss the pros and cons of the different approaches shared by the participants of the challenge and future perspectives of this topic.
DOI: 10.5281/zenodo.4896763
title: Covid-19 global Meditators data

description: Covid 19 global Meditators data
DOI: 10.5281/zenodo.4896762
title: Covid-19 global Meditators data

description: Covid 19 global Meditators data
DOI: 10.17638/datacat.liverpool.ac.uk/1309
title: Data for "Trapped interfacial redox introduces reversibility in the oxygen reduction reaction in a non-aqueous Ca2+ electrolyte"
DOI: 10.5281/zenodo.4896775
title: Groundwater flow rate prediction from geo-electrical features using Support Vector Machines: Bagoue dataset, Cote d'Ivoire

description: We implemented a support vector machines to predict groundwater flow before drilling using electrical resistivity profiling, vertical electrical sounding. We used the data from Cote d’Ivoire, west part of Africa and we tested the composite estimator in region of Bagoue, north part of CIV. Data are composed on electrical resistivity profile, vertical electrical sounding and borehole data. The coordinates of different boreholes are also mentioned.
DOI: 10.5281/zenodo.4762212
title: Evolutionary rescue can be impeded by temporary environmental amelioration - Dataset

description: Rapid evolutionary adaptation has the potential to rescue from extinction populations experienc- ing environmental changes. Little is known, however, about the impact of short-term environmen- tal fluctuations during long-term environmental deterioration, an intrinsic property of realistic environmental changes. Temporary environmental amelioration arising from such fluctuations could either facilitate evolutionary rescue by allowing population recovery (a positive demo- graphic effect) or impede it by relaxing selection for beneficial mutations required for future sur- vival (a negative population genetic effect). We address this uncertainty in an experiment with populations of a bacteriophage virus that evolved under deteriorating conditions (gradually increasing temperature). Periodic environmental amelioration (short periods of reduced tempera- ture) caused demographic recovery during the early phase of the experiment, but ultimately reduced the frequency of evolutionary rescue. These experimental results suggest that environmen- tal fluctuations could reduce the potential of evolutionary rescue.
description: {"references": ["Hao, Y.-Q., Brockhurst, M.A., Petchey, O.L. and Zhang, Q.-G. (2015), Evolutionary rescue can be impeded by temporary environmental amelioration. Ecol Lett, 18: 892-898. https://doi.org/10.1111/ele.12465"]}
DOI: 10.5281/zenodo.4762211
title: Evolutionary rescue can be impeded by temporary environmental amelioration - Dataset

description: Rapid evolutionary adaptation has the potential to rescue from extinction populations experienc- ing environmental changes. Little is known, however, about the impact of short-term environmen- tal fluctuations during long-term environmental deterioration, an intrinsic property of realistic environmental changes. Temporary environmental amelioration arising from such fluctuations could either facilitate evolutionary rescue by allowing population recovery (a positive demo- graphic effect) or impede it by relaxing selection for beneficial mutations required for future sur- vival (a negative population genetic effect). We address this uncertainty in an experiment with populations of a bacteriophage virus that evolved under deteriorating conditions (gradually increasing temperature). Periodic environmental amelioration (short periods of reduced tempera- ture) caused demographic recovery during the early phase of the experiment, but ultimately reduced the frequency of evolutionary rescue. These experimental results suggest that environmen- tal fluctuations could reduce the potential of evolutionary rescue.
description: {"references": ["Hao, Y.-Q., Brockhurst, M.A., Petchey, O.L. and Zhang, Q.-G. (2015), Evolutionary rescue can be impeded by temporary environmental amelioration. Ecol Lett, 18: 892-898. https://doi.org/10.1111/ele.12465"]}
DOI: 10.6084/m9.figshare.14724231
title: A survey on the willingness to take covid-19 vaccine amongst Nigerian youths and associated attitudes and perceptions

description: <b>Abstract</b> <b>Background</b> The quick roll out and access to covid-19 will flatten the infection and death rate only when a high level of vaccine uptake is achieved. This study investigated the acceptability of covid-19 vaccine by the Nigerian Youth. <b>Methods</b> This is a cross-sectional study of 631 youths (343 females and 270 males) aged between 15-44 years who were randomly recruited through a questionnaire, conducted from 10 February through 15 March 2021. Each participant had access to an anonymous questionnaire only after getting informed on the objectives of the study and consented to the same. The questionnaire consisted of two parts: demographics and ‘knowledge, attitudes and perceptions’ (KAPs) with 6 and 11 questions respectively. Chi-square test and Cramer’s V Statistic to determine the relative strength of association (at p&lt;0.05) between independent variables and the primary outcomes (willingness to receive a COVID-19 vaccine). <b>Results</b> 44 % of the respondents are not willing to take the vaccine, 22% are willing while 34% are not decisive. Only 10% of those willing to take the vaccine agreed to take it if becomes compulsory while 64% will not change their stand. The willingness to take covid-19 vaccine is associated to age (p=0.008, χ2 =23.027, V=0.139), occupation (p=0.026, χ2=17.455, V=0.119), level of knowledge (p=0.007, χ2=21.026, V=0.131), major source of information for covid-19 (p=0.004, χ2 =31.798, V=0.161), belief in the reality of Covid-19 (p&lt;0.00, χ2=32.477, V=0.163), and compulsion for covid-19 vaccination (p&lt;0.001, χ<sup>2 </sup>=364.973, V=0.546). <b>Conclusion</b> There is an anticipated high level of hesitancy for the uptake of covid-19 vaccine amongst Nigerian youths. Covid-19 uptake advocacy strategies must be developed and focus should be on reinstating trust in the vaccine programs and should be through the most valued source of information for the youths – social media.
DOI: 10.6084/m9.figshare.14724231.v2
title: A survey on the willingness to take covid-19 vaccine amongst Nigerian youths and associated attitudes and perceptions

description: <b>Abstract</b> <b>Background</b> The quick roll out and access to covid-19 will flatten the infection and death rate only when a high level of vaccine uptake is achieved. This study investigated the acceptability of covid-19 vaccine by the Nigerian Youth. <b>Methods</b> This is a cross-sectional study of 631 youths (343 females and 270 males) aged between 15-44 years who were randomly recruited through a questionnaire, conducted from 10 February through 15 March 2021. Each participant had access to an anonymous questionnaire only after getting informed on the objectives of the study and consented to the same. The questionnaire consisted of two parts: demographics and ‘knowledge, attitudes and perceptions’ (KAPs) with 6 and 11 questions respectively. Chi-square test and Cramer’s V Statistic to determine the relative strength of association (at p&lt;0.05) between independent variables and the primary outcomes (willingness to receive a COVID-19 vaccine). <b>Results</b> 44 % of the respondents are not willing to take the vaccine, 22% are willing while 34% are not decisive. Only 10% of those willing to take the vaccine agreed to take it if becomes compulsory while 64% will not change their stand. The willingness to take covid-19 vaccine is associated to age (p=0.008, χ2 =23.027, V=0.139), occupation (p=0.026, χ2=17.455, V=0.119), level of knowledge (p=0.007, χ2=21.026, V=0.131), major source of information for covid-19 (p=0.004, χ2 =31.798, V=0.161), belief in the reality of Covid-19 (p&lt;0.00, χ2=32.477, V=0.163), and compulsion for covid-19 vaccination (p&lt;0.001, χ<sup>2 </sup>=364.973, V=0.546). <b>Conclusion</b> There is an anticipated high level of hesitancy for the uptake of covid-19 vaccine amongst Nigerian youths. Covid-19 uptake advocacy strategies must be developed and focus should be on reinstating trust in the vaccine programs and should be through the most valued source of information for the youths – social media.