cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19698970.v2
title: Dataset_persistence-related traits_edaphic island plants

description: Dataset for Ottaviani et al. (2022) Sticking around: plant persistence strategies on edaphic islands. Diversity and Distribution. <br> Persistence-related trait data for 13 plant species (5 clonal, 8 non-clonal) specialists of granite outcrop edaphic islands in the Czech Republic. Traits are: lateral spread, plant height, belowground organ dry matter content [BDMC], age, radial growth, storage tissue, vessel size. <br> Biogeographic and environmental predictors measured at each of the 20 studied edaphic islands: target effect [TE], soil fertility [PC1_soil_nut], soil sandiness [Soil_arid], soil depth mean [SD_mean], soil depth CV [SD_cv], PC1_clim, PC2_clim.
DOI: 10.5517/ccdc.csd.cc247zzc
title: CCDC 1973893: Experimental Crystal Structure Determination

description: Related Article: Chanyoung Maeng, Gi Hoon Ko, Heejin Yang, Sang Hoon Han, Gi Uk Han, Hee Chan Noh, Kyungsup Lee, Dongwook Kim, Phil Ho Lee|2022|Org.Lett.|24|3526|doi:10.1021/acs.orglett.2c01232
DOI: 10.5517/ccdc.csd.cc24800g
title: CCDC 1973894: Experimental Crystal Structure Determination

description: Related Article: Chanyoung Maeng, Gi Hoon Ko, Heejin Yang, Sang Hoon Han, Gi Uk Han, Hee Chan Noh, Kyungsup Lee, Dongwook Kim, Phil Ho Lee|2022|Org.Lett.|24|3526|doi:10.1021/acs.orglett.2c01232
DOI: 10.5517/ccdc.csd.cc25r0b9
title: CCDC 2018110: Experimental Crystal Structure Determination

description: Related Article: Chanyoung Maeng, Gi Hoon Ko, Heejin Yang, Sang Hoon Han, Gi Uk Han, Hee Chan Noh, Kyungsup Lee, Dongwook Kim, Phil Ho Lee|2022|Org.Lett.|24|3526|doi:10.1021/acs.orglett.2c01232
DOI: 10.5517/ccdc.csd.cc25r0cb
title: CCDC 2018111: Experimental Crystal Structure Determination

description: Related Article: Chanyoung Maeng, Gi Hoon Ko, Heejin Yang, Sang Hoon Han, Gi Uk Han, Hee Chan Noh, Kyungsup Lee, Dongwook Kim, Phil Ho Lee|2022|Org.Lett.|24|3526|doi:10.1021/acs.orglett.2c01232
DOI: 10.5517/ccdc.csd.cc28grh0
title: CCDC 2099552: Experimental Crystal Structure Determination

description: Related Article: Shengjie Jiang, Yanping Cai, Ambre Carpentier, Iker del Rosal, Laurent Maron, Xin Xu|2022|Inorg.Chem.|61|8083|doi:10.1021/acs.inorgchem.2c00956
DOI: 10.5517/ccdc.csd.cc28grj1
title: CCDC 2099553: Experimental Crystal Structure Determination

description: Related Article: Shengjie Jiang, Yanping Cai, Ambre Carpentier, Iker del Rosal, Laurent Maron, Xin Xu|2022|Inorg.Chem.|61|8083|doi:10.1021/acs.inorgchem.2c00956
DOI: 10.5517/ccdc.csd.cc28grk2
title: CCDC 2099554: Experimental Crystal Structure Determination

description: Related Article: Shengjie Jiang, Yanping Cai, Ambre Carpentier, Iker del Rosal, Laurent Maron, Xin Xu|2022|Inorg.Chem.|61|8083|doi:10.1021/acs.inorgchem.2c00956
DOI: 10.5517/ccdc.csd.cc28grl3
title: CCDC 2099555: Experimental Crystal Structure Determination

description: Related Article: Shengjie Jiang, Yanping Cai, Ambre Carpentier, Iker del Rosal, Laurent Maron, Xin Xu|2022|Inorg.Chem.|61|8083|doi:10.1021/acs.inorgchem.2c00956
DOI: 10.6084/m9.figshare.19698970
title: Dataset_persistence-related traits_edaphic island plants

description: Dataset for Ottaviani et al. (2022) Sticking around: plant persistence strategies on edaphic islands. Diversity and Distribution. <br> Persistence-related trait data for 13 plant species (5 clonal, 8 non-clonal) specialists of granite outcrop edaphic islands in the Czech Republic. Traits are: lateral spread, plant height, belowground organ dry matter content [BDMC], age, radial growth, storage tissue, vessel size. <br> Biogeographic and environmental predictors measured at each of the 20 studied edaphic islands: target effect [TE], soil fertility [PC1_soil_nut], soil sandiness [Soil_arid], soil depth mean [SD_mean], soil depth CV [SD_cv], PC1_clim, PC2_clim.
DOI: 10.6084/m9.figshare.19698970.v3
title: Dataset_persistence-related traits_edaphic island plants

description: Dataset for Ottaviani et al. (2022) Sticking around: plant persistence strategies on edaphic islands. Diversity and Distribution. <br> Persistence-related trait data for 13 plant species (5 clonal, 8 non-clonal) specialists of granite outcrop edaphic islands in the Czech Republic. Traits are: lateral spread, plant height, belowground organ dry matter content [BDMC], age, radial growth, storage tissue, vessel size. <br> Biogeographic and environmental predictors measured at each of the 20 studied edaphic islands: target effect [TE], soil fertility [PC1_soil_nut], soil sandiness [Soil_arid], soil depth mean [SD_mean], soil depth CV [SD_cv], PC1_clim, PC2_clim.
DOI: 10.5517/ccdc.csd.cc29gf5d
title: CCDC 2129023: Experimental Crystal Structure Determination

description: Related Article: Hai-Lun Xia, Kang Zhou, Liang Yu, Hao Wang, Xiao-Yuan Liu, Davide M. Proserpio, Jing Li|2022|Inorg.Chem.|61|7980|doi:10.1021/acs.inorgchem.2c00660
DOI: 10.5517/ccdc.csd.cc29y33h
title: CCDC 2143126: Experimental Crystal Structure Determination

description: Related Article: Chanyoung Maeng, Gi Hoon Ko, Heejin Yang, Sang Hoon Han, Gi Uk Han, Hee Chan Noh, Kyungsup Lee, Dongwook Kim, Phil Ho Lee|2022|Org.Lett.|24|3526|doi:10.1021/acs.orglett.2c01232
DOI: 10.5517/ccdc.csd.cc2bbjw3
title: CCDC 2155085: Experimental Crystal Structure Determination

description: Related Article: Chanyoung Maeng, Gi Hoon Ko, Heejin Yang, Sang Hoon Han, Gi Uk Han, Hee Chan Noh, Kyungsup Lee, Dongwook Kim, Phil Ho Lee|2022|Org.Lett.|24|3526|doi:10.1021/acs.orglett.2c01232
DOI: 10.5517/ccdc.csd.cc2bjfgs
title: CCDC 2160745: Experimental Crystal Structure Determination

description: Related Article: Shengjie Jiang, Yanping Cai, Ambre Carpentier, Iker del Rosal, Laurent Maron, Xin Xu|2022|Inorg.Chem.|61|8083|doi:10.1021/acs.inorgchem.2c00956
DOI: 10.5517/ccdc.csd.cc2bjfht
title: CCDC 2160746: Experimental Crystal Structure Determination

description: Related Article: Shengjie Jiang, Yanping Cai, Ambre Carpentier, Iker del Rosal, Laurent Maron, Xin Xu|2022|Inorg.Chem.|61|8083|doi:10.1021/acs.inorgchem.2c00956
DOI: 10.5281/zenodo.6339897
title: MD simulation of POPC bilayer with CHARMM36 force field, 500 mM CaCl2

description: MD simulation of POPC bilayer with CHARMM36 force field, 500 mM CaCl<sub>2</sub> Dataset contains simulation files including centered trajectory files. For the ease of the upload, trajectory files (.xtc) are divided to 100ns pieces (Cacl500mM_x-x.xtc) System: POPC bilayer in water Number of lipids: 200 (100/leaflet) Number of waters: 8880 Salt: CaCl<sub>2</sub> Concentration: 500 mM Number of cations: 80 Simulation time: 1000 ns Simulation engine: GROMACS 2019.5 Temperature: 300 K
DOI: 10.6084/m9.figshare.18094172
title: Widespread HGT in insects: a foreign gene enhances male courtship in lepidopterans

description: This repository contains sequences of 1,410 HGT-acquired genes, 1,410 gene trees, the ML phylogeny of 218 insects, and a concatenation data matrix. <br> Each folder corresponds to each topic in our study. <br> Please let me know if you have any questions about them. <br> email: xingxingshen@zju.edu.cn <br>
DOI: 10.5281/zenodo.6579366
title: Probability of wildfire containment

description: Raster layer depicting the probatility of containing a fire according to the landscape configuration: accessibility, aerial means, relief complexity and vegetation density.
description: {"references": ["https://doi.org/10.1111/risa.13524"]}
DOI: 10.5281/zenodo.6579365
title: Probability of wildfire containment

description: Raster layer depicting the probatility of containing a fire according to the landscape configuration: accessibility, aerial means, relief complexity and vegetation density.
description: {"references": ["https://doi.org/10.1111/risa.13524"]}
DOI: 10.5281/zenodo.6337812
title: MD simulation of POPC bilayer with CHARMM36 force field, 200 mM CaCl2

description: MD simulation of POPC bilayer with CHARMM36 force field, 200 mM CaCl<sub>2</sub> Dataset contains simulation files including centered trajectory files. For the ease of the upload, trajectory files (.xtc) are divided to 100ns pieces (Cacl200mM_x-x.xtc) System: POPC bilayer in water Number of lipids: 200 (100/leaflet) Number of waters: 8880 Salt: CaCl<sub>2</sub> Concentration: 200 mM Number of cations: 32 Simulation time: 1000 ns Simulation engine: GROMACS 2019.5 Temperature: 300 K
DOI: 10.5281/zenodo.6579389
title: Test data for jga-analysis per-sample workflow

description: Test data for jga-analysis per-sample workflow. Please see: - https://github.com/biosciencedbc/jga-analysis - https://github.com/biosciencedbc/jga-analysis/blob/main/per-sample/Workflows/per-sample.cwl
DOI: 10.6084/m9.figshare.19705519.v1
title: Supplementary Material for: Novel “T-Dimension” Therapies for Pediatric Optic Pathway Glioma: A Timely, Targeted, and Tailored Treatment Trend

description: INTRODUCTION Novel targeted and tailored therapies can substantially improve the prognosis for optic pathway glioma (OPG), especially when implemented in a timely manner. However, their tremendous potential remains underestimated. Therefore, in this study, we provide an updated overview of the clinical trials, current trends, and future perspectives for OPG’s novel therapeutic strategies. METHODS We completed an extensive literature review using the PubMed, MEDLINE, and ClinicalTrials.gov databases.” We analyzed and reported the data following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS Thioguanine, procarbazine, lomustine, and vincristine/vinblastine, as well as cisplatin−etoposide, provided excellent results in advanced-Phase trials. Selumetinib and trametinib, two oral MEK-inhibitors, have been approved for recurrent or refractory OPGs in association with the angiogenetic inhibitor bevacizumab. Among the mTOR inhibitors, everolimus and sirolimus showed the best results. Stereotactic radiosurgery and proton beam radiation therapy have advantages over conventional radiotherapy regimens. Timely treatment is imperative for acute visual symptoms with evidence of tumor progression. This latest evidence can help define a novel “T-Dimension” for pediatric OPG therapies. CONCLUSION The novel “T-Dimension” for pediatric OPGs is based on recent evidence-based treatments, including combination chemotherapy regimens, molecular targeted therapies, stereotactic radiosurgery, and proton beam radiation therapy. Additional clinical trials are essential for validating each of these new therapies.
DOI: 10.6084/m9.figshare.19705519
title: Supplementary Material for: Novel “T-Dimension” Therapies for Pediatric Optic Pathway Glioma: A Timely, Targeted, and Tailored Treatment Trend

description: INTRODUCTION Novel targeted and tailored therapies can substantially improve the prognosis for optic pathway glioma (OPG), especially when implemented in a timely manner. However, their tremendous potential remains underestimated. Therefore, in this study, we provide an updated overview of the clinical trials, current trends, and future perspectives for OPG’s novel therapeutic strategies. METHODS We completed an extensive literature review using the PubMed, MEDLINE, and ClinicalTrials.gov databases.” We analyzed and reported the data following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS Thioguanine, procarbazine, lomustine, and vincristine/vinblastine, as well as cisplatin−etoposide, provided excellent results in advanced-Phase trials. Selumetinib and trametinib, two oral MEK-inhibitors, have been approved for recurrent or refractory OPGs in association with the angiogenetic inhibitor bevacizumab. Among the mTOR inhibitors, everolimus and sirolimus showed the best results. Stereotactic radiosurgery and proton beam radiation therapy have advantages over conventional radiotherapy regimens. Timely treatment is imperative for acute visual symptoms with evidence of tumor progression. This latest evidence can help define a novel “T-Dimension” for pediatric OPG therapies. CONCLUSION The novel “T-Dimension” for pediatric OPGs is based on recent evidence-based treatments, including combination chemotherapy regimens, molecular targeted therapies, stereotactic radiosurgery, and proton beam radiation therapy. Additional clinical trials are essential for validating each of these new therapies.
DOI: 10.5281/zenodo.6579385
title: Data file for: Three-Dimensional Electrical Imaging Across the Cona Woka Rift and Yalaxiangbo Dome in Southern Tibetan Plateau

description: The magnetotellurics data were used to study the lithospheric electrical structure across the Cona Woka rift and Yalaxiangbo dome in the southern Tibetan plateau, conducted by Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences. The data file of CN6.dat was generated by the Matlab code EM3DVP. You are recommended to refer to the Kelbert et al., 2014 paper: https://doi.org/10.1016/j.cageo.2014.01.010 for a brief understanding of the data file formats.
DOI: 10.5281/zenodo.6579278
title: Data file for: Three-Dimensional Electrical Imaging Across the Cona Woka Rift and Yalaxiangbo Dome in Southern Tibetan Plateau

description: The magnetotellurics data were used to study the lithospheric electrical structure across the Cona Woka rift and Yalaxiangbo dome in the southern Tibetan plateau, conducted by Institute of Geophysical and Geochemical Exploration, Chinese Academy of Geological Sciences. The data file of CN6.dat was generated by the Matlab code EM3DVP. You are recommended to refer to the Kelbert et al., 2014 paper: https://doi.org/10.1016/j.cageo.2014.01.010 for a brief understanding of the data file formats.
DOI: 10.34740/kaggle/dsv/3692991
title: AutoXGB
DOI: 10.5281/zenodo.6341419
title: MD simulation of POPC bilayer with CHARMM36 force field, 100 mM CaCl2

description: MD simulation of POPC bilayer with CHARMM36 force field, 100 mM CaCl<sub>2</sub> Dataset contains simulation files including centered trajectory files. For the ease of the upload, trajectory files (.xtc) are divided to 100ns pieces (Cacl100mM_x-x.xtc) System: POPC bilayer in water Number of lipids: 200 (100/leaflet) Number of waters: 8880 Salt: CaCl<sub>2</sub> Concentration: 100 mM Number of cations: 16 Simulation time: 1000 ns Simulation engine: GROMACS 2019.5 Temperature: 300 K
DOI: 10.5281/zenodo.6341898
title: MD simulation of POPC bilayer with CHARMM36 force field, 50 mM CaCl2

description: MD simulation of POPC bilayer with CHARMM36 force field, 50 mM CaCl<sub>2</sub> Dataset contains simulation files including centered trajectory files. For the ease of the upload, trajectory files (.xtc) are divided to 100ns pieces (Cacl_x-xns.xtc) System: POPC bilayer in water Number of lipids: 200 (100/leaflet) Number of waters: 8880 Salt: CaCl<sub>2</sub> Concentration: 50 mM Number of cations: 8 Simulation time: 1000 ns Simulation engine: GROMACS 2019.5 Temperature: 300 K
DOI: 10.5258/soton/d2210
title: MATLAB Code for the paper 'Effects of a trailing-edge flap on stall cell characteristics of a NACA0012 wing'

description: Corresponding Flow article DOI: 10.1017/flo.2022.11 published in the Flow journal. This is the dataset corresponding to the case study published in the Flow journal with the same title. The investigation considers experiments on a NACA0012 wing for which the surface flow was visualised with tufts while the lift coefficient was measured. A data driven approach to estimating the angle of attack for the formation of stall cells is presented and evaluated. The Data includes: -readme.txt: the same as the readme.pdf, with the general explanation of the dataset and corresponding paper. - workspace_plot_code.mat: this is a Matlab workspace file containing the data which supports the research from the paper. - plot_code.m: this is a Matlab script with the relevant code to produce the figures in the paper based on the data in the workspace that is included. - AR26_tuft_phase_diagram_flap_0.fig: (similar files for flap_5 and flap_10) these are Matlab figures containing the data points recorded and the corresponding classification based on tuft observations. By opening the files in Matlab all the corresponding data can be read.
DOI: 10.6084/m9.figshare.19864108
title: Dictionary

description: dictionary
DOI: 10.5281/zenodo.6541970
title: AI-TAM: a model to investigate user acceptance and collaborative intention in human-in-the-loop AI applications

description: More and more frequently, digital applications make use of Artificial Intelligence (AI) capabilities<br> to provide advanced features; on the other hand, human-in-the-loop approaches are on the<br> rise to involve people in AI-powered pipelines for data collection, results validation and decision making.<br> Does the introduction of AI features affect user acceptance? Does the AI result quality<br> affect people’s willingness to use such applications? Does the additional user effort required in<br> human-in-the-loop mechanisms change the application adoption and use?<br> This study aims to provide a reference approach to answer those questions. We propose a model<br> that extends the Technology Acceptance Model (TAM) with further constructs explicitly related to<br> AI – user trust in AI and perceived quality of AI output, from explainable AI (XAI) literature – and<br> collaborative intention – willingness to contribute to AI pipelines.<br> We tested the proposed model with an application for car damage claim reporting with AI-powered<br> damage estimation for insurance customers. The results showed that the XAI related factors have<br> a strong and positive effect on behavioral intention, perceived usefulness, and ease of use of the<br> application. Moreover, there is a strong link between behavioral intention and collaborative intention,<br> indicating that indeed human-in-the-loop approaches can be successfully adopted in final user<br> applications. Users were invited to test the interactive prototype of the BumpOut application and to report the given car accident from start to finish. These are the two interactive prototypes experienced by users: FlawlessAI-Group prototype FailingAI-Group prototype This study is shared as a research object adopting the RO-Crate specification.
description: The authors would like to thank all the participants that took part in the crowdsourcing campaign. This research was partially funded by EIT Digital in the AIDE project (Activity Code: 19386).
DOI: 10.5281/zenodo.6541969
title: AI-TAM: a model to investigate user acceptance and collaborative intention in human-in-the-loop AI applications

description: More and more frequently, digital applications make use of Artificial Intelligence (AI) capabilities<br> to provide advanced features; on the other hand, human-in-the-loop approaches are on the<br> rise to involve people in AI-powered pipelines for data collection, results validation and decision making.<br> Does the introduction of AI features affect user acceptance? Does the AI result quality<br> affect people’s willingness to use such applications? Does the additional user effort required in<br> human-in-the-loop mechanisms change the application adoption and use?<br> This study aims to provide a reference approach to answer those questions. We propose a model<br> that extends the Technology Acceptance Model (TAM) with further constructs explicitly related to<br> AI – user trust in AI and perceived quality of AI output, from explainable AI (XAI) literature – and<br> collaborative intention – willingness to contribute to AI pipelines.<br> We tested the proposed model with an application for car damage claim reporting with AI-powered<br> damage estimation for insurance customers. The results showed that the XAI related factors have<br> a strong and positive effect on behavioral intention, perceived usefulness, and ease of use of the<br> application. Moreover, there is a strong link between behavioral intention and collaborative intention,<br> indicating that indeed human-in-the-loop approaches can be successfully adopted in final user<br> applications. Users were invited to test the interactive prototype of the BumpOut application and to report the given car accident from start to finish. These are the two interactive prototypes experienced by users: FlawlessAI-Group prototype FailingAI-Group prototype This study is shared as a research object adopting the RO-Crate specification.
description: The authors would like to thank all the participants that took part in the crowdsourcing campaign. This research was partially funded by EIT Digital in the AIDE project (Activity Code: 19386).
DOI: 10.6084/m9.figshare.19849879.v1
title: TimeseriesData

description: Contains a MATLAB-structure for each participant-roi-model-hemisphere-datatype containing the timeseries in the format of [time,nVoxel], where nVoxel is the same list of voxels as used in each ROI in the response model data structures.
DOI: 10.6084/m9.figshare.19849264.v1
title: ResponseModelDataStructures

description: Contains one structure per participant. Each participant structure contains subdivisions into: ROIs Hemispheres Models Datatype ModelParameters <br> Parameters include: Preferred X values Preferred Y values (where applicable) Sigmas (Tuning width along major axis) SigmaMinor (Where applicable, Tuning width along minor axis) SigmaTheta (Where applicable, Orientation with respect to the x-axis) Ratios (Where applicable, Aspect ratio of response function, computed as sigma minor over sigma major) Compressive exponent Variance Explained Cross-Validated Variance Explained (where applicable) Residual sum of squares Residual sum of squares of original timeSeries data Index for ROI-coordinates
DOI: 10.6084/m9.figshare.19849879
title: TimeseriesData

description: Contains a MATLAB-structure for each participant-roi-model-hemisphere-datatype containing the timeseries in the format of [time,nVoxel], where nVoxel is the same list of voxels as used in each ROI in the response model data structures.
DOI: 10.6084/m9.figshare.19849264
title: ResponseModelDataStructures

description: Contains one structure per participant. Each participant structure contains subdivisions into: ROIs Hemispheres Models Datatype ModelParameters <br> Parameters include: Preferred X values Preferred Y values (where applicable) Sigmas (Tuning width along major axis) SigmaMinor (Where applicable, Tuning width along minor axis) SigmaTheta (Where applicable, Orientation with respect to the x-axis) Ratios (Where applicable, Aspect ratio of response function, computed as sigma minor over sigma major) Compressive exponent Variance Explained Cross-Validated Variance Explained (where applicable) Residual sum of squares Residual sum of squares of original timeSeries data Index for ROI-coordinates
DOI: 10.5281/zenodo.6563860
title: Validation phase on the cell lines using three different commercial NGS panels

description: We performed a validation phase on the selected cell lines using three different commercial NGS panels. Similarly, two independent NGS runs using the OTML, TSO500 and QIAseq Targeted DNA Panel were conducted to ensure consistency of the results.
DOI: 10.5281/zenodo.6563859
title: Validation phase on the cell lines using three different commercial NGS panels

description: We performed a validation phase on the selected cell lines using three different commercial NGS panels. Similarly, two independent NGS runs using the OTML, TSO500 and QIAseq Targeted DNA Panel were conducted to ensure consistency of the results.