cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8198946
title: Annex F – Exposure Mineral Oil Saturated Hydrocarbons (MOSH)

description: The annex contains the chronic dietary exposure estimations for MOSH.
description: EU; en ; xlsx; feedco@efsa.europa.eu
DOI: 10.5281/zenodo.8198947
title: Annex F – Exposure Mineral Oil Saturated Hydrocarbons (MOSH)

description: The annex contains the chronic dietary exposure estimations for MOSH.
description: EU; en ; xlsx; feedco@efsa.europa.eu
DOI: 10.5281/zenodo.8198926
title: Annex D – Dietary surveys for chronic exposure assessment

description: The Annex contains the information on the food consumption data used for the exposure assessment of MOH in food.
description: EU; en ; xls; feedco@efsa.europa.eu
DOI: 10.5281/zenodo.8198927
title: Annex D – Dietary surveys for chronic exposure assessment

description: The Annex contains the information on the food consumption data used for the exposure assessment of MOH in food.
description: EU; en ; xls; feedco@efsa.europa.eu
DOI: 10.5281/zenodo.8198938
title: Annex E – Raw occurrence dataset

description: The Annex contains the raw occurrence dataset for MOH in food
description: EU; en ; csv; feedco@efsa.europa.eu
DOI: 10.5281/zenodo.8198939
title: Annex E – Raw occurrence dataset

description: The Annex contains the raw occurrence dataset for MOH in food
description: EU; en ; csv; feedco@efsa.europa.eu
DOI: 10.4121/7349e277-d28c-48e6-953b-93e61654ef00
title: Software firms dataset about diversification and interdependence

description: We start by identifying U.S.-based software organizations in the computer programming and data processing industry (SIC 737), as a knowledge-intensive high-growth setting. We integrate two main data sources. First, to collect the knowledge-based measures, we use publicly available data provided by the U.S. Patent and Trademark Office (USPTO). Using the General Architecture for Text Engineering (GATE) software, we design queries that retrieve the complete class and subclass information for each patent, as well as citations, inventors, and total patents granted between 1998 and 2011 inclusive. We aggregate the data by organization-year observation at the class and subclass levels and use these aggregated measures to compute the knowledge-based predictors and covariates. To compute moving averages for some variables, we collect five years of additional USPTO data which makes our knowledge dataset span between 1993 and 2011. Second, we use Compustat to collect organization-level control variables such as assets, number of employees, market valuation, R&D expenditures, intangibles, solvency, and slack. The integration of the two datasets yields a final sample panel of 100 organizations with 3.2 years of observations on average per organization from 1998 to 2011.
DOI: 10.4121/7349e277-d28c-48e6-953b-93e61654ef00.v1
title: Software firms dataset about diversification and interdependence

description: We start by identifying U.S.-based software organizations in the computer programming and data processing industry (SIC 737), as a knowledge-intensive high-growth setting. We integrate two main data sources. First, to collect the knowledge-based measures, we use publicly available data provided by the U.S. Patent and Trademark Office (USPTO). Using the General Architecture for Text Engineering (GATE) software, we design queries that retrieve the complete class and subclass information for each patent, as well as citations, inventors, and total patents granted between 1998 and 2011 inclusive. We aggregate the data by organization-year observation at the class and subclass levels and use these aggregated measures to compute the knowledge-based predictors and covariates. To compute moving averages for some variables, we collect five years of additional USPTO data which makes our knowledge dataset span between 1993 and 2011. Second, we use Compustat to collect organization-level control variables such as assets, number of employees, market valuation, R&D expenditures, intangibles, solvency, and slack. The integration of the two datasets yields a final sample panel of 100 organizations with 3.2 years of observations on average per organization from 1998 to 2011.
DOI: 10.5281/zenodo.8339867
title: Las Neus Drone 09.09.2023

description: Las Neus Drone 09.09.2023
DOI: 10.5281/zenodo.8339866
title: Las Neus Drone 09.09.2023

description: Las Neus Drone 09.09.2023
DOI: 10.57841/casdc.0002184
title: 球形摩擦纳米波浪能发电机的多物理场耦合建模方法研究
DOI: 10.6084/m9.figshare.22672546
title: Original data of the ES in the Three River basin, China

description: The folder includes the original Excel data and GIS files for all the tables and figures of the paper.
DOI: 10.6084/m9.figshare.22672546.v1
title: Original data of the paper entitled-Scaling effect of aquatic biodiversity for quantifying the ecological impact of hydropower development

description: The folder includes the original Excel data and GIS files for all the tables and figures of the paper entitled “Scaling effect of aquatic biodiversity for quantifying the ecological impact of hydropower development”
DOI: 10.4121/b503546d-87a3-4d44-b14c-0d510bbdf4c8
title: Data underlying the research for manuscript "The Role of CEO Biases and Heuristics for Large Firms’ Innovation"

description: While for a long time “out of the spotlight,” large firms’ innovation is unique in that it is more common and not such a high-risk strategy. This brings into the light overlooked antecedents such as the biases imposed by CEOs’ personality (narcissism and self-monitoring) and the heuristics driven by CEOs’ motivations (promotion and prevention foci) for certain courses of action. Do different CEO biases affect large firms’ innovation differently and to what extent are these effects bounded by CEOs’ heuristics? We find that narcissistic CEOs differ from self-monitoring CEOs when it comes to innovation. Further, these effects are conditioned by CEOs’ regulatory focus in that the interplay of personality and motivation matters for self-monitors, but it does not matter for narcissistic CEOs. We identify large science and engineering firms in pharmaceutical (SIC 283), communications (SIC 481) and software (SIC 737) industries. We use a number of sources to retrieve data: SEC (annual reports), Execucomp (compensation), LexisNexis (press releases), USPTO (patents and citations), Compustat (financials). Our final dataset is a panel of large firms analyzed between 2006 and 2012 inclusive.
DOI: 10.4121/b503546d-87a3-4d44-b14c-0d510bbdf4c8.v1
title: Data underlying the research for manuscript "The Role of CEO Biases and Heuristics for Large Firms’ Innovation"

description: While for a long time “out of the spotlight,” large firms’ innovation is unique in that it is more common and not such a high-risk strategy. This brings into the light overlooked antecedents such as the biases imposed by CEOs’ personality (narcissism and self-monitoring) and the heuristics driven by CEOs’ motivations (promotion and prevention foci) for certain courses of action. Do different CEO biases affect large firms’ innovation differently and to what extent are these effects bounded by CEOs’ heuristics? We find that narcissistic CEOs differ from self-monitoring CEOs when it comes to innovation. Further, these effects are conditioned by CEOs’ regulatory focus in that the interplay of personality and motivation matters for self-monitors, but it does not matter for narcissistic CEOs. We identify large science and engineering firms in pharmaceutical (SIC 283), communications (SIC 481) and software (SIC 737) industries. We use a number of sources to retrieve data: SEC (annual reports), Execucomp (compensation), LexisNexis (press releases), USPTO (patents and citations), Compustat (financials). Our final dataset is a panel of large firms analyzed between 2006 and 2012 inclusive.
DOI: 10.25345/c58g8ft7c
title: MassIVE MSV000092845 - Oncogenic KEAP1 mutations activate TRAF2-NFkB signaling to prevent apoptosis in lung cancer cells
title: Affinity purification and mass spectrometry (AP-MS) study of wild type (wt) KEAP1 and mutants was used to investigate differences in the protein interactome.
DOI: 10.6084/m9.figshare.24118626.v2
title: SDWSNIDS_Dataset.zip

description: The dataset is copyrighted by the University of Johannesburg.
DOI: 10.4121/8d6ee0b0-8ed5-43f3-b1c9-7665cc163e87.v1
title: A Comparative Conflict Resolution Dataset Derived from Argoverse-2: Scenarios with vs. without Autonomous Vehicles

description: As the deployment of autonomous vehicles (AVs) becomes increasingly prevalent, ensuring safe and smooth interactions between AVs and other human agents is of critical importance. In the urban environment, how vehicles resolve conflicts has significant impacts on both driving safety and traffic efficiency. To expedite the studies on evaluating conflict resolution in AV-involved and AV-free scenarios at unsignalized intersections, this paper presents a high-quality dataset derived from the open Argoverse-2 motion forecasting data. First, scenarios of interest are selected by applying a set of heuristic rules regarding post-encroachment time (PET), minimum distance, trajectory crossing, and speed variation. Next, the quality of the raw data is carefully examined. We found that position and speed data are not consistent in Argoverse-2 data and its improper processing induced unnecessary errors. To address these specific problems, we propose and apply a data processing pipeline to correct and enhance the raw data. As a result, 5k+ AV-involved scenarios and 16k+ AV-free scenarios with smooth and consistent position, speed, acceleration, and heading direction data are obtained. Further assessments show that this dataset comprises diverse and balanced conflict resolution regimes. This informative dataset provides a valuable resource for researchers and practitioners in the field of autonomous vehicle assessment and regulation.
DOI: 10.34740/kaggle/dsv/6462724
title: Contrastive Language Image Pretraining by openai
DOI: 10.6084/m9.figshare.21648767
title: Raw sequencing reads for "Gut microbiota parallelism and divergence associated with colonisation of novel habitats"

description: Raw Illumina sequencing reads (MiSeq 600) of the V4 region of the 16S rRNA gene (515Fx806R). This data was used for analyzing bacterial community composition of cloacal swab samples from three lizard species (<i>Aspidoscleis inornata</i>, <i>Holbrookia maculata</i>, and <i>Sceloporus cowlesi</i>) from the White Sands, the Carrizozo lava flow, and the surrounding Chihuahuan desert in Southern New Mexico. The files are supporting information for our manuscript titled: "Gut microbiota parallelism and divergence associated with colonisation of novel habitats".
DOI: 10.6084/m9.figshare.21648638
title: Supporting information for "Gut microbiota parallelism and divergence associated with colonisation of novel habitats"

description: R scripts and data files used for analyzing bacterial community composition of cloacal swab samples from three lizard species (<i>Aspidoscleis inornata</i>, <i>Holbrookia maculata</i>, and <i>Sceloporus cowlesi</i>) from the White Sands, the Carrizozo lava flow, and the surrounding Chihuahuan desert in Southern New Mexico. The files are supporting information for our manuscript titled: "Gut microbiota parallelism and divergence associated with colonisation of novel habitats".
DOI: 10.6084/m9.figshare.21648638.v1
title: Supporting information for "Gut microbiota parallelism and divergence associated with colonisation of novel habitats"

description: R scripts and data files used for analyzing bacterial community composition of cloacal swab samples from three lizard species (<i>Aspidoscleis inornata</i>, <i>Holbrookia maculata</i>, and <i>Sceloporus cowlesi</i>) from the White Sands, the Carrizozo lava flow, and the surrounding Chihuahuan desert in Southern New Mexico. The files are supporting information for our manuscript titled: "Gut microbiota parallelism and divergence associated with colonisation of novel habitats".
DOI: 10.5281/zenodo.7371277
title: Dataset for "Classification of Stream, Hyperconcentrated, and Debris Flow Using Dimensional Analysis and Machine Learning"

description: Du J. et al., (2022). Dataset for "Classification of Stream, Hyperconcentrated, and Debris Flow Using Dimensional Analysis and Machine Learning", Water Resources Research Table S1: Hydrologic Paramteres and Dimensionless Numbers of Debris Flows Table S2: Hydrologic Paramteres and Dimensionless Numbers of Hyperconcentrated Flows Table S3: Hydrologic Paramteres and Dimensionless Numbers of Stream Flows Table S4: Hydrologic Paramteres and Dimensionless Numbers of Lahars
DOI: 10.5281/zenodo.7371276
title: Dataset for "Classification of Stream, Hyperconcentrated, and Debris Flow Using Dimensional Analysis and Machine Learning"

description: Du J. et al., (2022). Dataset for "Classification of Stream, Hyperconcentrated, and Debris Flow Using Dimensional Analysis and Machine Learning", Water Resources Research Table S1: Hydrologic Paramteres and Dimensionless Numbers of Debris Flows Table S2: Hydrologic Paramteres and Dimensionless Numbers of Hyperconcentrated Flows Table S3: Hydrologic Paramteres and Dimensionless Numbers of Stream Flows Table S4: Hydrologic Paramteres and Dimensionless Numbers of Lahars
DOI: 10.6084/m9.figshare.16802479
title: Wildfire_Carcass_Data_Feng

description: This dataset includes the abundance data of beetles collected in the Lieberoser Heide study.
DOI: 10.6084/m9.figshare.16802479.v1
title: Wildfire_Carcass_Data_Feng

description: This dataset includes the abundance data of beetles collected in the Lieberoser Heide study.
DOI: 10.5281/zenodo.7739880
title: Data for the manuscript "Microscopic Description of Basal Stress Generated by Granular Free-surface Flows"

description: Data and Code for the manuscript "Microscopic Description of Basal Stress Generated by Granular Free-surface Flows" The following documents are necessary for reproducing the DEM case indicated in the main article. LIGGGHTS download insttuctions and operation manual can be found in this web site https://www.cfdem.com/media/DEM/docu/Manual.html<br>
DOI: 10.5281/zenodo.7129258
title: Data for the manuscript "Microscopic Description of Basal Stress Generated by Granular Free-surface Flows"

description: Data and Code for the manuscript "Microscopic Description of Basal Stress Generated by Granular Free-surface Flows" The following documents are necessary for reproducing the DEM case indicated in the main article. LIGGGHTS download insttuctions and operation manual can be found in this web site https://www.cfdem.com/media/DEM/docu/Manual.html<br>
DOI: 10.5281/zenodo.8338398
title: Cipher Machine Schlüsselgerät SG 41_surface meshes (Inv. 2017-803)

description: Surface Meshes created from reconstructed CT-image stacks.<br> The inital CT dataset is linked as a related identifier.
DOI: 10.5281/zenodo.8223900
title: Cipher Machine Schlüsselgerät SG 41 (Inv. 2017-803)

description: This dataset represents the computed tomography image acquisition of a historical cipher machine from the collection of the Deutsches Museum. It is composed of CT reconstructed image stacks in the DICOM (.dcm) format.<br> It can be imported in any free or propietary CT-Viewer that supports the DICOM standard to generated 2D and 3D imaging.<br> If segmentations/ROIs are availabe, they are uploaded in a seperate image stacks and are a subset of the scanned cipher machine. object details:<br> name: Schlüsselgerät SG 41<br> Inv.-No. of the Deutsches Museum: 2017-803 file object details:<br> file format: image/dcm<br> pixel spacing unit: mm<br> X pixel spacing: 0.181<br> Y pixel spacing: 0.181<br> Z pixel spacing: 0.181<br> grid size x: 1978<br> grid size y: 1554<br> grid size z: 903<br> color depth: 16Bit ownership & image acquisition:<br> project: 3D-Cipher<br> collection: Deutsches Museum<br> IP holder: Deutsches Museum<br> license: Creative Commons BY-SA 4.0<br> scanning facility: Fraunhofer Development Center X-ray Technology EZRT/Fraunhofer IIS<br> scanning device: High Energy CT XXL-CT<br> Funding attribution: German Federal Ministry of Education and Research<br> acknowledgement: CryptoMuseum (as main source for informations about the cipher machines)
description: Funding: German Federal Ministry of Education and Research (BMBF), grant programme: eHeritage.
DOI: 10.5281/zenodo.8223901
title: Cipher Machine Schlüsselgerät SG 41 (Inv. 2017-803)

description: This dataset represents the computed tomography image acquisition of a historical cipher machine from the collection of the Deutsches Museum. It is composed of CT reconstructed image stacks in the DICOM (.dcm) format.<br> It can be imported in any free or propietary CT-Viewer that supports the DICOM standard to generated 2D and 3D imaging.<br> If segmentations/ROIs are availabe, they are uploaded in a seperate image stacks and are a subset of the scanned cipher machine. object details:<br> name: Schlüsselgerät SG 41<br> Inv.-No. of the Deutsches Museum: 2017-803 file object details:<br> file format: image/dcm<br> pixel spacing unit: mm<br> X pixel spacing: 0.181<br> Y pixel spacing: 0.181<br> Z pixel spacing: 0.181<br> grid size x: 1978<br> grid size y: 1554<br> grid size z: 903<br> color depth: 16Bit ownership & image acquisition:<br> project: 3D-Cipher<br> collection: Deutsches Museum<br> IP holder: Deutsches Museum<br> license: Creative Commons BY-SA 4.0<br> scanning facility: Fraunhofer Development Center X-ray Technology EZRT/Fraunhofer IIS<br> scanning device: High Energy CT XXL-CT<br> Funding attribution: German Federal Ministry of Education and Research<br> acknowledgement: CryptoMuseum (as main source for informations about the cipher machines)
description: Funding: German Federal Ministry of Education and Research (BMBF), grant programme: eHeritage.
DOI: 10.5281/zenodo.8338399
title: Cipher Machine Schlüsselgerät SG 41_surface meshes (Inv. 2017-803)

description: Surface Meshes created from reconstructed CT-image stacks.<br> The inital CT dataset is linked as a related identifier.
DOI: 10.5281/zenodo.8338137
title: Replication package for the paper "Family Resources and Children's Skills: Development of a Skills Attainment Model"

description: Replication package for the paper “Family Resources and Children’s Skills: Development of a Skills Attainment Model”. The package contains the Stata code for the data preparation and the Mplus code for the analyses performed in the paper. The used data set is available in the highly secure environment of Statistics Netherlands. To gain access, a number of steps must be completed, which can be found on the following website: https://www.cbs.nl/en-gb/our-services/customised-services-microdata/microdata-conducting-your-own-research.
description: This work was supported by the Dutch Ministry of Education, Culture and Science and the Netherlands Initiative for Education Research under Grant 405-17-900.
DOI: 10.5281/zenodo.8338136
title: Replication package for the paper "Family Resources and Children's Skills: Development of a Skills Attainment Model"

description: Replication package for the paper “Family Resources and Children’s Skills: Development of a Skills Attainment Model”. The package contains the Stata code for the data preparation and the Mplus code for the analyses performed in the paper. The used data set is available in the highly secure environment of Statistics Netherlands. To gain access, a number of steps must be completed, which can be found on the following website: https://www.cbs.nl/en-gb/our-services/customised-services-microdata/microdata-conducting-your-own-research.
description: This work was supported by the Dutch Ministry of Education, Culture and Science and the Netherlands Initiative for Education Research under Grant 405-17-900.
DOI: 10.6084/m9.figshare.23634468
title: result.xls

description: This data is the collection of measurements of subcortical nuclei of brain in MRI of brains.
DOI: 10.6084/m9.figshare.23634468.v3
title: result.xls

description: This data is the collection of measurements of subcortical nuclei of brain in MRI of brains.
DOI: 10.5281/zenodo.7386308
title: Dataset for 'Made to be a woman'

description: This repository contains the datasets on which the article 'Made to be a woman. A case study on the categorization of gender using an individuation-based approach in the analysis of literary texts' is based on.
DOI: 10.5281/zenodo.7388960
title: Dataset for 'Made to be a woman'

description: This repository contains the datasets on which the article 'Made to be a woman. A case study on the categorization of gender using an individuation-based approach in the analysis of literary texts' is based on.
DOI: 10.5281/zenodo.8339980
title: Dataset for 'Made to be a woman'

description: This repository contains the datasets on which the article 'Made to be a woman. A case study on the categorization of gender using an individuation-based approach in the analysis of literary texts' is based on.
DOI: 10.5281/zenodo.7386307
title: Dataset for 'Made to be a woman'

description: This repository contains the datasets on which the article 'Made to be a woman. A case study on the categorization of gender using an individuation-based approach in the analysis of literary texts' is based on.
DOI: 10.6084/m9.figshare.24125445
title: DATA.xlsx

description: <b>Estimation of changes in </b><b>biomass carbon sequestration and its economic value with varying stand density of subtropical plantations in China</b>
DOI: 10.6084/m9.figshare.24125445.v1
title: DATA.xlsx

description: <b>Estimation of changes in </b><b>biomass carbon sequestration and its economic value with varying stand density of subtropical plantations in China</b>
DOI: 10.5281/zenodo.8338002
title: Observational datasets for validation of Mediterranean Biogeochemical Copernicus Modelling System, period 2018-2020

description: Datasets used for the validation of the biogeochemical component of the Mediterranean Analysis and Forecast center of the EU Copernicus Marine Service for the period 2018-2020. The list of datasets includes: 1) the Delay Mode Satellite chlorophyll from https://data.marine.copernicus.eu/product/OCEANCOLOUR_MED_BGC_L3_NRT_009_141/description after interpolation to the 1/24° horizontal resolution, weekly averages and quality check with internal climatology 2) the BGC-Argo float profiles of nitrate, chlorophyll and oxygen from Coriolis DAC (ftp://ftp.ifremer.fr/ifremer/argo; https://doi.org/10.17882/42182#76230) after an internal quality check procedure which is described in Salon et al., 2019. 3) the climatological profiles for 16 subbasins of nitrate, phosphate, silicate, oxygen, DIC, alkalinity, pCO2 and pH computed from the Emodnet 2018 data collection and additional scientific datasets as described in Salon et al., 2019. Ref.: Salon, S., Cossarini, G., Bolzon, G., Feudale, L., Lazzari, P., Teruzzi, A., Solidoro, C. and Crise, A., 2019. Novel metrics based on Biogeochemical Argo data to improve the model uncertainty evaluation of the CMEMS Mediterranean marine ecosystem forecasts. <em>Ocean Science</em>, <em>15</em>(4), pp.997-1022.