cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8197844
title: Deep and fast label-free Dynamic Organellar Mapping - Imaging data

description: Imaging data from the article "Deep and fast label-free Dynamic Organellar Mapping", published in Nature Communications by Schessner et al., from Fig. 6, 7 and Supp. Fig. 6c. Widefield images were captured on a Leica DMi8 inverted microscope equipped with an iTK LMT200 motorised stage, a 63x/1.47 oil objective (HC PL APO 63x/1.47 OIL) and a Leica DFC9000 GTC Camera, and controlled with LAS X (Leica Application Software X). Fig6_GLG1_TGOLN2_GALNT2_SuppFig6c_LC3B: Widefield imaging of wild-type HeLa cells cultured for 1h in either: 1) full growth medium (Control); 2) EBSS to starve the cells (Starve); 3) full growth medium plus 100 nM BafA (Control + BafA); or 4) EBSS plus 100 nM BafA (Starve + BafA). Cells were labelled with anti-GALNT2 (Alexa Fluor 488), in combination with either anti-GLG1 (Alexa Fluor 568) or anti-TGOLN2 (Alexa Fluor 680), as shown in Fig. 6, or were labelled with anti-LC3B (Alexa Fluor 488), as shown in Supp. Fig. 6c. In all images, cells were stained with DAPI to label nuclei. Fig7_GALNT2_GLG1_TM9SF2_TGOLN2_GOLIM4_SDF4: Widefield imaging of HeLa cells left untreated in full growth medium (0h) or cultured in the presence of 100 nM BafA for 0.5, 1, 2, 4, 6 or 8 hours, before fixation. Cells were labelled with anti-GALNT2 (Alexa Fluor 647) in combination with either anti-GLG1, anti-TM9SF2, anti-TGOLN2, anti-GOLIM4 or anti-SDF4 (Alexa Fluor 555). In all images, cells were stained with DAPI and phalloidin-488 to label nuclei and cytoplasm, respectively.
description: This study was supported by The Max-Planck Society for Advancement of Science. AD received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 896725 and a Humboldt Research Fellowship from the Alexander von Humboldt Foundation.
DOI: 10.48510/fk2/j9yfac/aqakip
title: questionnaire_OHS_survey_2005_2007_lv.pdf

description: :unav
DOI: 10.48510/fk2/j9yfac/mvwonb
title: Methodology_OHS_survey_2005_2007_lv.pdf

description: :unav
DOI: 10.48510/fk2/j9yfac/dg0vpv
title: Data_OHS_survey_2005_2007_lv.csv

description: :unav
DOI: 10.48510/fk2/j9yfac
title: Working Conditions and Risks in Latvia 2005 - 2007: Survey of Occupational Health Specialists

description: The Work conditions and risks in Latvia national surveys were conducted in Latvia in 2006, 2010, 2013, 2018 and 2022. The aim of these surveys is to gather evidence on situations related to occupational risk factors, occupational health, safety and to analyze the dynamics of the data obtained and identify the causes of the existing problems. This data serves as a basis to develop proposals for improving the practical implementation of the legal framework and foundation for effective decision making. A more detailed description of the methods is available in the methodology file.
DOI: 10.48510/fk2/iqfjfk/izrric
title: questionnaire_PwROD_survey_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/iqfjfk/p6kjdh
title: Data_PwROD_survey_2019_2021_lv.tab

description: Data for use in SPSS
DOI: 10.48510/fk2/iqfjfk/opui72
title: Data_PwROD_survey_2019_2021_lv.csv

description: Data accessible with different kinds of software
DOI: 10.48510/fk2/iqfjfk/h3csve
title: Methodology_PwROD_survey_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/7tsmvu
title: FGD_OHS_external_experts_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/otikwk
title: FGD_employers_and_represetatives_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/vyvxhl
title: FGD_methodology_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/zcy0b2
title: FGD_medium_big_employers_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/bquhxb
title: FGD_small_employers_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/gnlntq
title: FGD_microenterprise_employers_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/myoiqk
title: FGD_OHS_internal_experts_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx/hrgqha
title: FGD_OHS_guidelines_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/3nmmqx
title: Working Conditions and Risks in Latvia 2019 - 2021: Focus group discussions

description: The Work conditions and risks in Latvia national surveys were conducted in Latvia in 2006, 2010, 2013, 2018 and 2022. The aim of these surveys is to gather evidence on situations related to occupational risk factors, occupational health, safety and to analyze the dynamics of the data obtained and identify the causes of the existing problems. This data serves as a basis to develop proposals for improving the practical implementation of the legal framework and foundation for effective decision making. A more detailed description of the methods is available in the methodology file.
DOI: 10.48510/fk2/3nmmqx/beyxsm
title: FGD_employers_guidelines_2019_2021_lv.pdf

description: :unav
DOI: 10.48510/fk2/js1ats/dpzxvq
title: FGD_group_3_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/js1ats/lrdh3i
title: FGD_group_2_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/js1ats/8joksd
title: FGD_methodology_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/js1ats/xm1kls
title: FGD_group_1_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/js1ats/kb6ruf
title: FGD_guidelines_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/js1ats/lz5dnz
title: FGD_group_4_2012_2013_lv.pdf

description: :unav
DOI: 10.48510/fk2/js1ats
title: Working Conditions and Risks in Latvia 2012 - 2013: Focus group discussions

description: The Work conditions and risks in Latvia national surveys were conducted in Latvia in 2006, 2010, 2013, 2018 and 2022. The aim of these surveys is to gather evidence on situations related to occupational risk factors, occupational health, safety and to analyze the dynamics of the data obtained and identify the causes of the existing problems. This data serves as a basis to develop proposals for improving the practical implementation of the legal framework and foundation for effective decision making. A more detailed description of the methods is available in the methodology file.
DOI: 10.6084/m9.figshare.23812830.v8
title: Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiratio

description: Regridding Global CMIP6 GCMs dataset(0.5 degree)Historical dataset:14 CMIP6 GCMs (1850-2014)Future dataset: 14CMIP6 GCMs and 4 SSP scenarios (2015-2100)Composition of dataset: Average temperature, Maximum temperature, Minimum temperature, Windspeed, Relative humidity, Solar radiationIf you are using our codes and dataset, please use the following references:Song, Y.H., Chung, E.S., Shahid, S., Kim, Y.J., Kim, D.K. 2023. Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration. Scientific Data.<br>
DOI: 10.26050/wdcc/ar6.c6cmcmcch
title: IPCC DDC: CMCC CMCC-CM2-HR4 model output prepared for CMIP6 CMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CMCC.CMCC-CM2-HR4' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-HR4 climate model, released in 2016, includes the following components: aerosol: prescribed MACv2-SP, atmos: CAM4 (1deg; 288 x 192 longitude/latitude; 26 levels; top at ~2 hPa), land: CLM4.5 (SP mode), ocean: NEMO3.6 (ORCA0.25 1/4 deg from the Equator degrading at the poles; 1442 x 1051 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.
DOI: 10.26050/wdcc/ar6.c6cmcmccs
title: IPCC DDC: CMCC CMCC-CM2-SR5 model output prepared for CMIP6 CMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CMCC.CMCC-CM2-SR5' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6cmcmcmc
title: IPCC DDC: CMCC CMCC-ESM2 model output prepared for CMIP6 CMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CMCC.CMCC-ESM2' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-ESM2 climate model, released in 2017, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), ocnBgchem: BFM5.2, seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6spcmccs
title: IPCC DDC: CMCC CMCC-CM2-SR5 model output prepared for CMIP6 ScenarioMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CMCC.CMCC-CM2-SR5' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.
DOI: 10.26050/wdcc/ar6.c6spcmcmc
title: IPCC DDC: CMCC CMCC-ESM2 model output prepared for CMIP6 ScenarioMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.CMCC.CMCC-ESM2' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CMCC-ESM2 climate model, released in 2017, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), ocnBgchem: BFM5.2, seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
DOI: 10.5066/p9b8srmw
title: Acoustic Telemetry Evaluation of Invasive Carp in Kaukauna, Wisconsin (Summer 2019)

description: This study deployed acoustic telemetry at the Fox River Navigational System Authority (FRNSA) in lock #2 and the upstream and downstream pools in Kaukauna, WI to document movements and behavior of telemetered fish species in response to injection of carbon dioxide. Telemetry equipment was setup in the test area for approximately 2 months during the summer of 2019. CSV metadata includes telemetry data with position estimates for fish during this time.
DOI: 10.6084/m9.figshare.23816079
title: Evaluation Datasets for GPT-3.5 and GPT-4 in Molecular Generation Tasks

description: This collection includes datasets from ChEBI-20 and ZINC utilized for the performance evaluation of GPT-3.5 and GPT-4 models in three distinct tasks: Molecular Description Generation, Molecular Optimization, and Molecular Generation. The ChEBI-20 dataset was used for the Molecular Description Generation and Molecular Generation tasks, where the LLMs were required to generate accurate descriptions of molecular functional groups and viable molecular structures from scratch, respectively. The ZINC dataset was employed for the Molecular Optimization task, which involves the modification of molecules to optimize a given property, such as the Quantitative Estimate of Drug-likeness (QED). For each task, we selected 10 cases for testing.
DOI: 10.6084/m9.figshare.23816079.v1
title: Evaluation Datasets for GPT-3.5 and GPT-4 in Molecular Generation Tasks

description: This collection includes datasets from ChEBI-20 and ZINC utilized for the performance evaluation of GPT-3.5 and GPT-4 models in three distinct tasks: Molecular Description Generation, Molecular Optimization, and Molecular Generation. The ChEBI-20 dataset was used for the Molecular Description Generation and Molecular Generation tasks, where the LLMs were required to generate accurate descriptions of molecular functional groups and viable molecular structures from scratch, respectively. The ZINC dataset was employed for the Molecular Optimization task, which involves the modification of molecules to optimize a given property, such as the Quantitative Estimate of Drug-likeness (QED). For each task, we selected 10 cases for testing.
DOI: 10.6084/m9.figshare.23812830.v9
title: Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiratio

description: Regridding Global CMIP6 GCMs dataset(0.5 degree)Historical dataset:14 CMIP6 GCMs (1850-2014)Future dataset: 14CMIP6 GCMs and 4 SSP scenarios (2015-2100)Composition of dataset: Average temperature, Maximum temperature, Minimum temperature, Windspeed, Relative humidity, Solar radiationIf you are using our codes and dataset, please use the following references:Song, Y.H., Chung, E.S., Shahid, S., Kim, Y.J., Kim, D.K. 2023. Development of global monthly dataset of CMIP6 climate variables for estimating evapotranspiration. Scientific Data.<br>
DOI: 10.5281/zenodo.8202907
title: Lightme test case IRIS

description: The folder contains Gcode files, photos and Mastercam file.
DOI: 10.5281/zenodo.8202906
title: Lightme test case IRIS

description: The folder contains Gcode files, photos and Mastercam file.
DOI: 10.5281/zenodo.8203034
title: Lightme test case IRIS

description: The folder contains Gcode files, photos and Mastercam file.
DOI: 10.5281/zenodo.8205525
title: Emission-Constrained Optimization of Gas Networks: Input-Convex Neural Network Approach

description: # Emission-Aware Optimization of Gas Networks This repository collects the Belgium gas network dataset, details on the training procedure, and codes to replicate the results reported in the following paper: *Emission-Constrained Optimization of Gas Networks: Input-Convex Neural Network Approach * accepted for presentation at the 62nd IEEE Conference on Decision and Control, Dec. 13-15, 2023, Singapore. Materials are released with the Attribution 4.0 International (CC BY 4.0) license. The repository contains two folders: * ```operation_planning``` folder containing data and codes for neural network training and operation planning optimization * ```long_term_planning``` folder containing data and codes for neural network training and long-term planning optimization The models are implemented in ```Julia-1.6``` Language, using ```JuMP.jl``` using ```Flux.jl``` library for machine learning and JuMP.jl library for mathematical programming. Before running the code, make sure to activate the virtual environment from ```Project.toml``` files stored in each folder, e.g., by running ``` julia&gt; ] (@v1.6) pkg&gt; activate . (operation_planning) pkg&gt; instantiate ``` For experiment settings, refer to ```exp_settings``` dictionary in file ```main.jl```. For network data, refer to ```.../data/case_BE```.