cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/spd29yptft.1
title: Energy Theory of value - Correlation between energy inputs and economic output of Italian Economy 2015

description: Questions like “what is the value?” and “how does it form?” have accompanied the debate on political economy since the beginning. Despite the foundational aspect, consulting the more than 5700 articles of the Ecological Economics Journal, only 8 in reference to "theories of value". The paper aims to reconstruct the debate around the theories of the value with particular focus on the energy theory of value. The theory is based on a partially closed Leontief's model to include labor and government into the transaction matrix. The paper discusses the methodological issues connected to these modifications of traditional input-output analysis and proposes some improvements (regarding gross capital formation) with empirical reference to the Italian economy for the year 2015. The correlation between the embedded energy and the economic value emerging from the results demonstrates the interdependence between energy inputs and economic outputs. As claimed by the same author this seriously compromises the possibility of a real decoupling. The emerging correlation rather suggests to consider the energy-work as primary factor of production. Finally, the opportunity of extending the concept of work in a physical sense offers the possibility of linking the classical approach regarding value with the more recent world-ecology conceptual framework.
DOI: 10.17632/hw39d5kxs6.1
title: Supplementary Material for: “A Comparative Study of Item Space  Visualizations for Recommender Systems”

description: This is the supplementary material for the article “A Comparative Study of Item Space  Visualizations for Recommender Systems” as submitted to the International Journal of Human-Computer Studies.
DOI: 10.17632/hw39d5kxs6.2
title: Supplementary Material for: “A Comparative Study of Item Space  Visualizations for Recommender Systems”

description: This is the supplementary material for the article “A Comparative Study of Item Space  Visualizations for Recommender Systems” as submitted to the International Journal of Human-Computer Studies.
DOI: 10.17632/hw39d5kxs6.3
title: Supplementary Material for: A Comparative Study of Item Space  Visualizations for Recommender Systems

description: This is the supplementary material for the article “A Comparative Study of Item Space  Visualizations for Recommender Systems” as submitted to the International Journal of Human-Computer Studies.
DOI: 10.17632/5r89zptx96.1
title: Bitcoin

description: Bitcoin forecast 2018-2021
DOI: 10.17632/cdrrdy2j8w.1
title: Data repository

description: All the research data were taken from the established journals which is available online.
DOI: 10.17632/drwmy4y8f5.1
title: Code Supplement Rapid nuclear deadenylation of mammalian messenger RNA

description: Data for Manuscript Rapid nuclear deadenylation of mammalian messenger RNA
DOI: 10.17632/2889fp4bz7.1
title: Data on the Relationship between Students’ Attitude towards, and Performance in Mathematics Word Problems, mediated by Active Learning Heuristic Problem-Solving Approach

description: Data were collected from 608 11th-grade students. Students in the comparison group learned LP conventionally whereas students from the treatment group were taught using ALHPS strategies. The data were collected between October 2020 and February 2021. The pretest was administered to both groups followed by an intervention and finally, a post-test.
DOI: 10.17632/35d6hhpczp.1
title: Multi-Objective Scheduling Problem With Sequence Dependent Setup Times Data Set

description: GAMS and MATLAB Data for Multi-Objective Scheduling Problem With Sequence Dependent Setup Times Study
DOI: 10.17632/35d6hhpczp.2
title: Simulated Annealing Algorithm For Weaving Loom Scheduling Problem with Sequence-Dependent Setup Times Data Set

description: GAMS and MATLAB Data for Multi-Objective Scheduling Problem With Sequence Dependent Setup Times Study
DOI: 10.17632/zhcw5vr4bx.1
title: Detrital zircon geochronology of modern rivers in the eastern Pamir syntaxis and its implications on formation of the Pamir accompanying growth of the Tibetan Plateau

description: We have collected three new sand samples from Taxkorgan River in eastern Pamir syntaxis . Zircon separation was carried out from ~10 kg samples using conventional magnetic and density techniques to concentrate the non-magnetic, heavy fractions. Representative selections of zircons were then extracted by handpicking under a binocular microscope. Then, ~300 zircon grains were randomly selected and then cast into an epoxy mount and polished to obtain an even surface. And the mount was sanded down, polished and cleaned prior to isotopic analysis.
U‐Pb geochronology of zircons was conducted by laser ablation multicollector inductively coupled plasma mass spectrometry (LA–MC–ICPMS) at the State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration. The analyses involve ablation of zircon with Resolution M50-LR ArF excimer laser ablation system using a spot diameter of 28 microns, and it is necessary to set the integration time of isotopes to be measured, including 15 ms for 204Pb, 206Pb and 208Pb, 30 ms for 207Pb, 10 ms for 232Th and 238U, and 6 ms for other trace elements using Agilent 7900 quadrupole inductively coupled plasma mass spectrometer (Li et al., 2019). Every set of ten samples analyses was followed by analysis of two zircons standard 91,500 and one zircon standard GJ-1, and the glass standard (Jackson et al., 2004). Common Pb was corrected using the method proposed by Andersen (2002). The experimental results were tuned by the standard program Glitter 4.0, and U‐Pb geochronology with concordance less than 90% were excluded. U‐Pb geochronology were output used by 206Pb/238U and 1σ if less than 1.2 Ga, unless use 207Pb/206Pb and 1σ (Nemchin and Cawood, 2005).
DOI: 10.25438/wes02.21603825
title: Touching the fingerprinting API surface

description: Data collected for Is touching the fingerprinting API surface enough?. <br> See the GitLab repo for information about how this data was collected and an explanation of the data files. <br>
DOI: 10.25438/wes02.21603825.v1
title: Touching the fingerprinting API surface

description: Data collected for Is touching the fingerprinting API surface enough?. <br> See the GitLab repo for information about how this data was collected and an explanation of the data files. <br>
DOI: 10.6084/m9.figshare.21632180
title: snp dataset of medicago

description: snp dataset of two closely related medicago species
DOI: 10.5281/zenodo.7373971
title: Sequences of oat metallothioneins

description: Sequences of oat (Avena sativa L.) metallothioneins.
DOI: 10.5281/zenodo.7373970
title: Sequences of oat metallothioneins

description: Sequences of oat (Avena sativa L.) metallothioneins.
DOI: 10.5281/zenodo.7373705
title: Barott Lab/Heron pHi

description: This release contains all of the data and code associated with the manuscript "Environmental memory gained from exposure to extreme pCO2 variability promotes coral acid-base homeostasis".
DOI: 10.5281/zenodo.7373704
title: Barott Lab/Heron pHi

description: This release contains all of the data and code associated with the manuscript "Environmental memory gained from exposure to extreme pCO2 variability promotes coral acid-base homeostasis".
DOI: 10.5281/zenodo.7310400
title: Identifying learning dimensions in CS project descriptions

description: For this study, we conducted a qualitative content analysis of a random sample of 94 English-language project descriptions stored in the CS Track database with the goal of determining which dimensions of learning are reflected most prominently in these texts. Using a slightly modified version of the model of individual learning outcomes developed by Phillips et al. in 2018 as a coding rubric, two members of the research team independently coded all project descriptions by manually assigning phrases, sentences and short paragraphs to eight main categories and 21 subcategories. From these text snippets, distinctive and frequently occurring keywords were extracted, which have since been used in follow-up studies. Our analysis revealed that some learning dimensions (such as data collection or using technology) are very prominently discussed in the project descriptions we studied, while others (e.g. experimenting, study design, community action) are clearly underrepresented. In other words, the project descriptions analysed only partially reflect the educational potential of participation in CS. Based on these findings, we suggested possible explanations and ways in which the issue could be addressed on the level of both project design and project communication. This study profited immensely from the kind support of Tina Phillips and her colleagues, who agreed to share parts of their coded dataset with us. Details related to the analysis procedure are provided in a paper which is currently under review (on the date of submission of this deliverable - November 2022), no link to a repository is available. Contact the main authors if you have interest to receive further information). References: Phillips, T., Porticella, N., Constas, M., & Bonney, R. (2018). A framework for articulating and measuring individual learning outcomes from participation in citizen science. Citizen Science: Theory and Practice, 3(2). More information on this research can be found in D2.2 section 5.1. <strong>Content and grouping: </strong> coding rubric used (Main category, Subcategory, Definition (Draft) and Inclusion/exclusion criteria) columns) complete coding (i.e. including CS Track projects title) calculation of rate of agreement between coders list of keywords extracted list of projects titles and the website URL from where we extracted the information
description: Other related information about CS project descriptions and data source websites can be found in the following: https://doi.org/10.5281/zenodo.7310096 and https://doi.org/10.5281/zenodo.7310295 .
DOI: 10.5281/zenodo.7310401
title: Analysis Intended Educational Outcome in citizen science - Dataset

description: This dataset contains the analysis of intended educational outcomes in a selected list of citizen science projects.
description: Other related information about CS project descriptions and data source websites can be found in the following: https://doi.org/10.5281/zenodo.7310096 and https://doi.org/10.5281/zenodo.7310295 .
DOI: 10.5281/zenodo.7346804
title: Identifying learning dimensions in CS project descriptions

description: For this study, we conducted a qualitative content analysis of a random sample of 94 English-language project descriptions stored in the CS Track database with the goal of determining which dimensions of learning are reflected most prominently in these texts. Using a slightly modified version of the model of individual learning outcomes developed by Phillips et al. in 2018 as a coding rubric, two members of the research team independently coded all project descriptions by manually assigning phrases, sentences and short paragraphs to eight main categories and 21 subcategories. From these text snippets, distinctive and frequently occurring keywords were extracted, which have since been used in follow-up studies. Our analysis revealed that some learning dimensions (such as data collection or using technology) are very prominently discussed in the project descriptions we studied, while others (e.g. experimenting, study design, community action) are clearly underrepresented. In other words, the project descriptions analysed only partially reflect the educational potential of participation in CS. Based on these findings, we suggested possible explanations and ways in which the issue could be addressed on the level of both project design and project communication. This study profited immensely from the kind support of Tina Phillips and her colleagues, who agreed to share parts of their coded dataset with us. Details related to the analysis procedure are provided in a paper which is currently under review (on the date of submission of this deliverable - November 2022), no link to a repository is available. Contact the main authors if you have interest to receive further information). References: Phillips, T., Porticella, N., Constas, M., & Bonney, R. (2018). A framework for articulating and measuring individual learning outcomes from participation in citizen science. Citizen Science: Theory and Practice, 3(2). More information on this research can be found in D2.2 section 5.1. <strong>Content and grouping: </strong> coding rubric used (Main category, Subcategory, Definition (Draft) and Inclusion/exclusion criteria) columns) complete coding (i.e. including CS Track projects title) calculation of rate of agreement between coders list of keywords extracted list of projects titles and the website URL from where we extracted the information
description: Other related information about CS project descriptions and data source websites can be found in the following: https://doi.org/10.5281/zenodo.7310096 and https://doi.org/10.5281/zenodo.7310295 .
DOI: 10.5281/zenodo.7374000
title: Identifying learning dimensions in CS project descriptions

description: For this study, we conducted a qualitative content analysis of a random sample of 94 English-language project descriptions stored in the CS Track database with the goal of determining which dimensions of learning are reflected most prominently in these texts. Using a slightly modified version of the model of individual learning outcomes developed by Phillips et al. in 2018 as a coding rubric, two members of the research team independently coded all project descriptions by manually assigning phrases, sentences and short paragraphs to eight main categories and 21 subcategories. From these text snippets, distinctive and frequently occurring keywords were extracted, which have since been used in follow-up studies. Our analysis revealed that some learning dimensions (such as data collection or using technology) are very prominently discussed in the project descriptions we studied, while others (e.g. experimenting, study design, community action) are clearly underrepresented. In other words, the project descriptions analysed only partially reflect the educational potential of participation in CS. Based on these findings, we suggested possible explanations and ways in which the issue could be addressed on the level of both project design and project communication. This study profited immensely from the kind support of Tina Phillips and her colleagues, who agreed to share parts of their coded dataset with us. Details related to the analysis procedure are provided in a paper which is currently under review (on the date of submission of this deliverable - November 2022), no link to a repository is available. Contact the main authors if you have interest to receive further information). References: Phillips, T., Porticella, N., Constas, M., & Bonney, R. (2018). A framework for articulating and measuring individual learning outcomes from participation in citizen science. Citizen Science: Theory and Practice, 3(2). More information on this research can be found in D2.2 section 5.1. <strong>Content and grouping: </strong> coding rubric used (Main category, Subcategory, Definition (Draft) and Inclusion/exclusion criteria) columns) complete coding (i.e. including CS Track projects title) calculation of rate of agreement between coders list of keywords extracted list of projects titles and the website URL from where we extracted the information
description: Other related information about CS project descriptions and data source websites can be found in the following: https://doi.org/10.5281/zenodo.7310096 and https://doi.org/10.5281/zenodo.7310295 .
DOI: 10.5281/zenodo.7371834
title: Downscaling climatic data 2021-2100 in North Korea

description: Please refer to the 'Readme' file.
DOI: 10.5281/zenodo.7371833
title: Downscaling climatic data 2021-2100 in North Korea

description: Please refer to the 'Readme' file.
DOI: 10.6084/m9.figshare.21636710.v1
title: Deciphering the causal relationship between blood pressure and regional white matter integrity: a two-sample Mendelian randomization study

description: A list of 39 regional white matter (WM) integrity measured by fractional antitropy (FA).
DOI: 10.6084/m9.figshare.21636710.v2
title: Deciphering the causal relationship between blood pressure and regional white matter integrity: a two-sample Mendelian randomization study

description: Table S1. A list of 39 regional white matter (WM) integrity measured by fractional antitropy (FA). Table S2. Self-report neurological characteristics of UK Biobank's participants from two independent association sample sets for the two-sample Mendelian randomization (MR) analysis. Table S3. Numbers of candidate instrumental variables (IVs) determined at each step of our statistical method by separately using UK Biobank (UKB) GWAS and existing meta-analyzed GWAS. Table S4. Gene annotations for determined valid instrumental variables (IVs) carried into the two-sample Mendelian Randomization (MR) analysis by separately using UK Biobank (UKB) GWAS and existing meta-analyzed GWAS. Table S5. Results of association analysis and Mendelian Randomization analysis (implemented with generalized version of inverse-variance weighted (gen-IVW) approach) in the study samples. Table S6. Results of alternative Mendelian randomization (MR) approach and sensitivity analyses by using data from UK Biobank (UKB) cohort. Table S7. Results of adaptively weighted (AW) Fisher's method and mendelian randomization analysis implemented with a generalized version of inverse-variance weights method (gen-IVW) Table S8. Results and numbers of candidate instrumental variables (IVs) in each step of our two reverse two-sample Mendelian Randomization (MR) analyses using UK Biobank (UKB) cohort.
DOI: 10.6084/m9.figshare.21636710.v3
title: Deciphering the causal relationship between blood pressure and regional white matter integrity: a two-sample Mendelian randomization study

description: Table S1. A list of 39 regional white matter (WM) integrity measured by fractional antitropy (FA). Table S2. Self-report neurological characteristics of UK Biobank's participants from two independent association sample sets for the two-sample Mendelian randomization (MR) analysis. Table S3. Numbers of candidate instrumental variables (IVs) determined at each step of our statistical method by separately using UK Biobank (UKB) GWAS and existing meta-analyzed GWAS. Table S4. Gene annotations for determined valid instrumental variables (IVs) carried into the two-sample Mendelian Randomization (MR) analysis by separately using UK Biobank (UKB) GWAS and existing meta-analyzed GWAS. Table S5. Results of association analysis and Mendelian Randomization analysis (implemented with generalized version of inverse-variance weighted (gen-IVW) approach) in the study samples. Table S6. Results of alternative Mendelian randomization (MR) approach and sensitivity analyses by using data from UK Biobank (UKB) cohort. Table S7. Results of adaptively weighted (AW) Fisher's method and mendelian randomization analysis implemented with a generalized version of inverse-variance weights method (gen-IVW) Table S8. Results and numbers of candidate instrumental variables (IVs) in each step of our two reverse two-sample Mendelian Randomization (MR) analyses using UK Biobank (UKB) cohort. Supplmentary File. Results of leave-one-out analyses
DOI: 10.5517/ccdc.csd.cc2bnd8p
title: CCDC 2164552: Experimental Crystal Structure Determination

description: Related Article: Xianqiang Huang, Sen Liu, Gang Liu, Yiwei Tao, Chenran Wang, Yalin Zhang, Zhen Li, Huaiwei Wang, Zhen Zhou, Guodong Shen, Zechun Xue, Di Sun|2023|Applied Catalysis B: Environmental|323|122134|doi:10.1016/j.apcatb.2022.122134
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.cc2bskh6
title: CCDC 2168558: Experimental Crystal Structure Determination

description: Related Article: Noureddine Mhadhbi, Souad Dgachi, Soufienne Belgacem, Ali Ben Ahmed, Natacha Henry, Thierry Loiseau, Samia Nasr, Riadh Badraoui, Houcine Naïli|2023|J.Mol.Struct.|1274|134439|doi:10.1016/j.molstruc.2022.134439
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.cc2bx3ky
title: CCDC 2171970: Experimental Crystal Structure Determination

description: Related Article: Bingyi Zhou, Xinxin Yuan, Liangxin Fan, Zhenliang Pan, Xiaodan Chang, Shengfei Jiang, Lulu Wu, Caixia Wang, Guoyu Yang, Xiaoming Ji, Lijun Shi, Cuilian Xu|2022|J.Saudi Chem.Soc.|26|101572|doi:10.1016/j.jscs.2022.101572
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.cc2bx7vc
title: CCDC 2172103: Experimental Crystal Structure Determination

description: Related Article: Dhouha Abid, Haitham Abid, Wassim Maalej, Elkebir Hlil, Philippe Guionneau, Stanislav Pechev, Nathalie Daro, Zakaria Elaoud|2022|J.Lumin.|252|119251|doi:10.1016/j.jlumin.2022.119251
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.cc2c2xzc
title: CCDC 2177563: Experimental Crystal Structure Determination

description: Related Article: Valentina Ferraro, Jesús Castro, Lodovico Agostinis, Marco Bortoluzzi|2023|Inorg.Chim.Acta|545|121285|doi:10.1016/j.ica.2022.121285
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.cc2c3p28
title: CCDC 2178279: Experimental Crystal Structure Determination

description: Related Article: E.I. Davydova, G. Balázs, M. Bodensteiner, M. Scheer, A.Y. Timoshkin|2023|J.Organomet.Chem.|983|122551|doi:10.1016/j.jorganchem.2022.122551
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.