cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15151/esrf-es-1214162243
title: Post-mortem and operando Bragg coherent diffraction imaging of degradation in high-voltage LiMn1.5Ni0.5O4 cathode materials

description: High voltage spinel cathode materials such as LiMn1.5Ni0.5O4 are considered to be the next step in the evolution of lithium-ion battery technology due to their high energy density, fast charging capabilities, low material costs and the absence of Co. However, this material widespread use is hindered by its significant degradation problem in particular capacity fade due to Mn dissolution from the surface of the particle. Both operando and post mortem BCDI studies are very well suited to study this phenomenon since they will allow to gather structural information on the strain gradients inside the particles. We expect BCDI to give us insight into the interfacial reactions between Jahn-Teller distorted surface lattices and the electrolyte that is responsible for the capacity fade in LMNO. Moreover, the operando BCDI data on strain transformation inside a single particle would give us valuable information about the change of lithium ionic order and phase evolution at the nanoscale.
DOI: 10.5519/qd.9y6kbjsh
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (2 records)
DOI: 10.5281/zenodo.8118389
title: Unveiling the Life Cycle of User Feedback: Best Practices from Software Practitioners

description: This data represents four artifacts from our research in studying how software organizations manage user feedback, particularly social media feedback, to help improve existing products. It includes our interview questions, information about the study participants, the codebook with example quotes, and table with the code to concept generation. This page includes supplementary materials associated with our paper entitled "Unveiling the Life Cycle of User Feedback: Best Practices from Software Practitioners".
DOI: 10.5281/zenodo.7783838
title: Unveiling the Life Cycle of User Feedback: Best Practices from Software Practitioners

description: This data represents four artifacts from our research in studying how software organizations manage user feedback, particularly social media feedback, to help improve existing products. It includes our interview questions, information about the study participants, the codebook with example quotes, and table with the code to concept generation. This page includes supplementary materials associated with our paper entitled "Unveiling the Life Cycle of User Feedback: Best Practices from Software Practitioners".
DOI: 10.5281/zenodo.8123040
title: Codon similarity data in ATTED-II ver 8.0 (Ath, Gma, Osa, Sly, Vvi)

description: Codon similarity data in ATTED-II ver 8.0 The gene-to-gene codon similarity data is organized in the form of tables, each named according to the Entrez Gene ID of a particular query gene. Each table encompasses three columns, specifying: the Entrez Gene ID of a corresponding gene, an MR (Mutual Rank) value (where a smaller number signifies a stronger relationship), and a Pearson correlation coefficient (where a larger number suggests a stronger association). Protein-coding sequences utilized in this study were retrieved from NCBI's RefSeq database. For each gene, a 61-dimensional vector was derived from the count of codons in the protein-coding sequence. In instances where multiple RefSeq sequences were associated with a single gene, the longest sequence was selected for the codon usage calculation. Pearson correlation coefficients (PCCs) were determined between the vectors of any two given genes. These PCCs were subsequently converted into MRs, employed as an index to evaluate the similarity in codon usage between the genes.
description: {"references": ["Aoki Y, Okamura Y, Tadaka S, Kinoshita K, Obayashi T. (2016) ATTED-II in 2016: a plant coexpression database towards lineage-specific coexpression. Plant Cell Physiology, 57, e5."]}
DOI: 10.5281/zenodo.8055517
title: Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China

description: Ambient volatile organic compounds (VOCs) are crucial precursors for the formation of secondary organic aerosol (SOA) and ozone (O<sub>3</sub>). We have conducted in-situ observations and compiled a comprehensive dataset of ambient volatile organic compound (VOC) compositions and concentrations in Beijing, China, spanning the period from 2016 to 2020. The dataset covers a wide range of VOC species including 29 alkanes, 11 alkenes, 1 alkyne, 16 aromatics, 28 halohydrocarbons, 13 oxygenated VOCs (OVOCs), and 1 nitrogenous VOC (acetonitrile). The presentation and analysis of this dataset is available in a paper submitted to Earth System Science Data (Simon et al, in prep). The findings and analysis of this dataset have been documented in a paper that has been submitted to Earth System Science Data (Liu et al., in prep). If you use the dataset for related scientific research, please cite the corresponding reference: Liu et al (in prep); Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China; Earth System Science Data.
DOI: 10.5281/zenodo.8055518
title: Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China

description: Ambient volatile organic compounds (VOCs) are crucial precursors for the formation of secondary organic aerosol (SOA) and ozone (O<sub>3</sub>). We have conducted in-situ observations and compiled a comprehensive dataset of ambient volatile organic compound (VOC) compositions and concentrations in Beijing, China, spanning the period from 2016 to 2020. The dataset covers a wide range of VOC species including 29 alkanes, 11 alkenes, 1 alkyne, 16 aromatics, 28 halohydrocarbons, 13 oxygenated VOCs (OVOCs), and 1 nitrogenous VOC (acetonitrile). The presentation and analysis of this dataset is available in a paper submitted to Earth System Science Data (Simon et al, in prep). The findings and analysis of this dataset have been documented in a paper that has been submitted to Earth System Science Data (Liu et al., in prep). If you use the dataset for related scientific research, please cite the corresponding reference: Liu et al (in prep); Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China; Earth System Science Data.
DOI: 10.5281/zenodo.8123039
title: Codon similarity data in ATTED-II ver 8.0 (Ath, Gma, Osa, Sly, Vvi)

description: Codon similarity data in ATTED-II ver 8.0 The gene-to-gene codon similarity data is organized in the form of tables, each named according to the Entrez Gene ID of a particular query gene. Each table encompasses three columns, specifying: the Entrez Gene ID of a corresponding gene, an MR (Mutual Rank) value (where a smaller number signifies a stronger relationship), and a Pearson correlation coefficient (where a larger number suggests a stronger association). Protein-coding sequences utilized in this study were retrieved from NCBI's RefSeq database. For each gene, a 61-dimensional vector was derived from the count of codons in the protein-coding sequence. In instances where multiple RefSeq sequences were associated with a single gene, the longest sequence was selected for the codon usage calculation. Pearson correlation coefficients (PCCs) were determined between the vectors of any two given genes. These PCCs were subsequently converted into MRs, employed as an index to evaluate the similarity in codon usage between the genes.
description: {"references": ["Aoki Y, Okamura Y, Tadaka S, Kinoshita K, Obayashi T. (2016) ATTED-II in 2016: a plant coexpression database towards lineage-specific coexpression. Plant Cell Physiology, 57, e5."]}
DOI: 10.5281/zenodo.8127442
title: Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China

description: Ambient volatile organic compounds (VOCs) are crucial precursors for the formation of secondary organic aerosol (SOA) and ozone (O<sub>3</sub>). We have conducted in-situ observations and compiled a comprehensive dataset of ambient volatile organic compound (VOC) compositions and concentrations in Beijing, China, spanning the period from 2016 to 2020. The dataset covers a wide range of VOC species including 29 alkanes, 11 alkenes, 1 alkyne, 16 aromatics, 28 halohydrocarbons, 13 oxygenated VOCs (OVOCs), and 1 nitrogenous VOC (acetonitrile). The presentation and analysis of this dataset is available in a paper submitted to Earth System Science Data (Simon et al, in prep). The findings and analysis of this dataset have been documented in a paper that has been submitted to Earth System Science Data (Liu et al., in prep). If you use the dataset for related scientific research, please cite the corresponding reference: Liu et al (in prep); Long-term variations of ambient volatile organic compounds (VOCs) from 2016 to 2020 in Beijing, China; Earth System Science Data.
DOI: 10.6084/m9.figshare.23650350
title: 这个地方写你上传数据的表的名字或图的名字 Figure or datasheet

description: 把表或图的名字复制上
DOI: 10.6084/m9.figshare.23650350.v1
title: 这个地方写你上传数据的表的名字或图的名字 Figure or datasheet

description: 把表或图的名字复制上
DOI: 10.34740/kaggle/dsv/6103085
title: FoliageDB: A novel database
DOI: 10.6084/m9.figshare.22769732.v1
title: Safety and immunogenicity of a tetravalent and bivalent SARS-CoV-2 protein booster vaccine in men

description: Source Data Listing of Vaccine Related Adverse Events
DOI: 10.6084/m9.figshare.22769732
title: Safety and immunogenicity of a tetravalent and bivalent SARS-CoV-2 protein booster vaccine in men

description: Source Data Listing of Vaccine Related Adverse Events
DOI: 10.6084/m9.figshare.23650413
title: Table 4. List of significantly different metabolites

description: Table 4. List of significantly different metabolites
DOI: 10.6084/m9.figshare.23650413.v1
title: Table 4. List of significantly different metabolites

description: Table 4. List of significantly different metabolites
DOI: 10.6084/m9.figshare.23650395
title: code.zip

description: Data sets for IJGIS submission. Include raw data and model codes.
DOI: 10.6084/m9.figshare.23650395.v1
title: code.zip

description: Data sets for IJGIS submission. Include raw data and model codes.
DOI: 10.6084/m9.figshare.23632773
title: <strong> The Causal Relationship between Thyroid Volume and Thyroid Disease: A Mendelian Randomization Study</strong>

description: <strong>supplemental file for peer review</strong> 1.Supplementary Figure 1: Scatter plot for genetically predicted thyroid volume on thyroid diseases. Inverse variance weighted, weighted median, MR-Egger, simple mode and weighted mode slopes represent results from these regression analyses. 2.Supplementary Table 1: Information about the selected databases. 3.Supplementary Table 2: Information on the selected SNPs. 4.Supplementary Table 3: Five MR Methods estimate the causal effect of thyroid volume on thyroid disease and TSH. 5.Supplementary Table 4: Testing for genetic pleiotropy.
DOI: 10.6084/m9.figshare.23632773.v4
title: <strong> The Causal Relationship between Thyroid Volume and Thyroid Disease: A Mendelian Randomization Study</strong>

description: <strong>supplemental file for peer review</strong> 1.Supplementary Figure 1: Scatter plot for genetically predicted thyroid volume on thyroid diseases. Inverse variance weighted, weighted median, MR-Egger, simple mode and weighted mode slopes represent results from these regression analyses. 2.Supplementary Table 1: Information about the selected databases. 3.Supplementary Table 2: Information on the selected SNPs. 4.Supplementary Table 3: Five MR Methods estimate the causal effect of thyroid volume on thyroid disease and TSH. 5.Supplementary Table 4: Testing for genetic pleiotropy.
DOI: 10.6084/m9.figshare.23632773.v3
title: <strong>The Causal Relationship between Thyroid Volume and Thyroid Disease: A Mendelian Randomization Study</strong>

description: 1.Supplementary Figure 1: Scatter plot for genetically predicted thyroid volume on thyroid diseases. Inverse variance weighted, weighted median, MR-Egger, simple mode and weighted mode slopes represent results from these regression analyses. 2.Supplementary Table 1: Information about the selected databases. 3.Supplementary Table 2: Information on the selected SNPs. 4.Supplementary Table 3: Five MR Methods estimate the causal effect of thyroid volume on thyroid disease and TSH. 5.Supplementary Table 4: Testing for genetic pleiotropy.
DOI: 10.6084/m9.figshare.23650434
title: <strong>Tree mycorrhizal type mediates responses of</strong> <strong>foliar stoichiometry to functionally dissimilar neighbours in a subtropical forest experiment</strong>

description: <strong>Tree mycorrhizal type mediates responses of</strong> <strong>foliar stoichiometry to functionally dissimilar neighbours in a subtropical forest experiment</strong>
DOI: 10.6084/m9.figshare.23650434.v1
title: <strong>Tree mycorrhizal type mediates responses of</strong> <strong>foliar stoichiometry to functionally dissimilar neighbours in a subtropical forest experiment</strong>

description: <strong>Tree mycorrhizal type mediates responses of</strong> <strong>foliar stoichiometry to functionally dissimilar neighbours in a subtropical forest experiment</strong>
DOI: 10.5281/zenodo.8127464
title: Source code and data files for the fetal kick simulator developed in the Biomechatronics Lab at Imperial College London, UK

description: This repository holds the code for Fetal Kick Simulator Copyright (c) 2020, Imperial College London All rights reserved. Authors: Abhishek Kumar Ghosh, Ravi Vaidyanathan, Niamh C Nowlan. Imperial College London. This program is a free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. Acknowledgements: If this software is helpful, then Please consider acknowledging or referencing the authors. Publication: Link for the publication related to this repository is https://www.mdpi.com/1424-8220/20/21/6020
DOI: 10.5281/zenodo.8127463
title: Source code and data files for the fetal kick simulator developed in the Biomechatronics Lab at Imperial College London, UK

description: This repository holds the code for Fetal Kick Simulator Copyright (c) 2020, Imperial College London All rights reserved. Authors: Abhishek Kumar Ghosh, Ravi Vaidyanathan, Niamh C Nowlan. Imperial College London. This program is a free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details. Acknowledgements: If this software is helpful, then Please consider acknowledging or referencing the authors. Publication: Link for the publication related to this repository is https://www.mdpi.com/1424-8220/20/21/6020
DOI: 10.15151/esrf-es-1118655682
title: The Iberian cryoEM community BAG

description: The Iberian cryoEM BAG is a large consortium (&gt; 30 groups) composed of Portuguese and Spanish groups working in biologically relevant problems including disease related metabolic enzymes, antibiotic resistance, DNA replication and DNA maintenance, protein synthesis, virus structure and mechanisms, and macromolecular complexes involved in the control of key cellular processes like protein folding and degradation.
DOI: 10.6084/m9.figshare.23650440
title: Macro and Micro economic factors for market performance collected from public domain and authentic sources for academic pupose.

description: Macro and Micro economic factors for market performance collected from public domain and authentic sources for academic pupose.
DOI: 10.6084/m9.figshare.23650440.v1
title: Macro and Micro economic factors for market performance collected from public domain and authentic sources for academic pupose.

description: Macro and Micro economic factors for market performance collected from public domain and authentic sources for academic pupose.
DOI: 10.34740/kaggle/dsv/6103421
title: AutoXGB
DOI: 10.5281/zenodo.8127419
title: Codon similarity data in ATTED-II ver 8.0 (Ptr, Zma)

description: Codon similarity data in ATTED-II ver 8.0 The gene-to-gene codon similarity data is organized in the form of tables, each named according to the Entrez Gene ID of a particular query gene. Each table encompasses three columns, specifying: the Entrez Gene ID of a corresponding gene, an MR (Mutual Rank) value (where a smaller number signifies a stronger relationship), and a Pearson correlation coefficient (where a larger number suggests a stronger association). Protein-coding sequences utilized in this study were retrieved from NCBI's RefSeq database. For each gene, a 61-dimensional vector was derived from the count of codons in the protein-coding sequence. In instances where multiple RefSeq sequences were associated with a single gene, the longest sequence was selected for the codon usage calculation. Pearson correlation coefficients (PCCs) were determined between the vectors of any two given genes. These PCCs were subsequently converted into MRs, employed as an index to evaluate the similarity in codon usage between the genes.
DOI: 10.5281/zenodo.8127418
title: Codon similarity data in ATTED-II ver 8.0 (Ptr, Zma)

description: Codon similarity data in ATTED-II ver 8.0 The gene-to-gene codon similarity data is organized in the form of tables, each named according to the Entrez Gene ID of a particular query gene. Each table encompasses three columns, specifying: the Entrez Gene ID of a corresponding gene, an MR (Mutual Rank) value (where a smaller number signifies a stronger relationship), and a Pearson correlation coefficient (where a larger number suggests a stronger association). Protein-coding sequences utilized in this study were retrieved from NCBI's RefSeq database. For each gene, a 61-dimensional vector was derived from the count of codons in the protein-coding sequence. In instances where multiple RefSeq sequences were associated with a single gene, the longest sequence was selected for the codon usage calculation. Pearson correlation coefficients (PCCs) were determined between the vectors of any two given genes. These PCCs were subsequently converted into MRs, employed as an index to evaluate the similarity in codon usage between the genes.
DOI: 10.6084/m9.figshare.23650458
title: <strong>A novel collaborative electric vehicle routing problem with multiple prioritized time windows and time-dependent hybrid recharging</strong>

description: This is the experimental data of the manuscript entitled “A novel collaborative electric vehicle routing problem with multiple prioritized time windows and time-dependent hybrid recharging”. In these instances,the number of depots is set to 3, 4, and 5, and the number of customers is set to 50, 75, 100, and 125 respectively. In these instances, the number of recharging stations varies from 2 to 6, and customer demand ranged from 10 to 40. The name of each instance is composed of a combination of {type} {quantity} for customers, depots, and recharging stations. For example, the instance "C50_D3_R2" means that the delivery system includes 50 customers, 3 depots, and 2 recharging stations.
DOI: 10.6084/m9.figshare.23650458.v1
title: <strong>A novel collaborative electric vehicle routing problem with multiple prioritized time windows and time-dependent hybrid recharging</strong>

description: This is the experimental data of the manuscript entitled “A novel collaborative electric vehicle routing problem with multiple prioritized time windows and time-dependent hybrid recharging”. In these instances,the number of depots is set to 3, 4, and 5, and the number of customers is set to 50, 75, 100, and 125 respectively. In these instances, the number of recharging stations varies from 2 to 6, and customer demand ranged from 10 to 40. The name of each instance is composed of a combination of {type} {quantity} for customers, depots, and recharging stations. For example, the instance "C50_D3_R2" means that the delivery system includes 50 customers, 3 depots, and 2 recharging stations.
DOI: 10.6084/m9.figshare.23650476
title: Table 4

description: Table 4. List of significantly different metabolites
DOI: 10.6084/m9.figshare.23650476.v1
title: Table 4

description: Table 4. List of significantly different metabolites
DOI: 10.6084/m9.figshare.23650425
title: data

description: data of symbolic aspects in Australia
DOI: 10.6084/m9.figshare.23650425.v1
title: data

description: data of symbolic aspects in Australia
DOI: 10.6084/m9.figshare.23650470
title: <strong>Decadal soil warming decreased vascular plant above- and below-ground production in a subarctic grassland by inducing nitrogen limitation</strong>

description: The database were derived from a field soil warming experiment in a subarctic grassland located in Iceland.
DOI: 10.6084/m9.figshare.23650497
title: SCS2018_OBS3D_rcvr_station.txt

description: industrial and enviromental soundscapes
DOI: 10.6084/m9.figshare.23650497.v1
title: SCS2018_OBS3D_rcvr_station.txt

description: industrial and enviromental soundscapes
DOI: 10.5281/zenodo.8127479
title: Energetic Particle Injection during Short Isolated Bubble as seen in RCM Simulation and Spacecraft Observations in the Flow Braking Region

description: The names of the RCM simulation output files specify the simulation time in a format of "hhmmss". The stored quantities are, "I","J","COLAT","ALOCT","MLT","BNDLOC","XMIN","YMIN","FTV","BMIN","V", "BIRK_fromV(NH)","P(RCM),nPa", "PV_gamma","Vtotx", "Vtoty","Vx_exb","Vy_exb","vel_x","vel_y","Ey","PEDLAM", "PEDPSI", "HALL", "RCM_T_p","RCM_T_e","RCM_N_e","EFLUX","EAVG","f_i_50-75","f_i_75-125","f_i_125-200","f_i_200-300","f_e_50-75","f_e_75-125","f_e_125-200","f_e_200-300","Vm","dbxdz","dbydz","dbrdz","dbzdx","dbzdy".<br> For the first hour of substorm-growth-phase-like quasi-steady convection, we uploaded the RCM simulation output files at 1-minute intervals. Then, the RCM output files were uploaded at 20-second intervals for the next 7 minutes of bubble injection, and at 1-minute intervals for the rest of the simulation.
DOI: 10.5281/zenodo.8127478
title: Energetic Particle Injection during Short Isolated Bubble as seen in RCM Simulation and Spacecraft Observations in the Flow Braking Region

description: The names of the RCM simulation output files specify the simulation time in a format of "hhmmss". The stored quantities are, "I","J","COLAT","ALOCT","MLT","BNDLOC","XMIN","YMIN","FTV","BMIN","V", "BIRK_fromV(NH)","P(RCM),nPa", "PV_gamma","Vtotx", "Vtoty","Vx_exb","Vy_exb","vel_x","vel_y","Ey","PEDLAM", "PEDPSI", "HALL", "RCM_T_p","RCM_T_e","RCM_N_e","EFLUX","EAVG","f_i_50-75","f_i_75-125","f_i_125-200","f_i_200-300","f_e_50-75","f_e_75-125","f_e_125-200","f_e_200-300","Vm","dbxdz","dbydz","dbrdz","dbzdx","dbzdy".<br> For the first hour of substorm-growth-phase-like quasi-steady convection, we uploaded the RCM simulation output files at 1-minute intervals. Then, the RCM output files were uploaded at 20-second intervals for the next 7 minutes of bubble injection, and at 1-minute intervals for the rest of the simulation.