cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23631492.v1
title: Bothrops_alternatus_BUSCO_tetrapoda_odb10

description: BUSCO output using the trapoda_odb10 dataset to analyze the genome assembly of the urutu lancehead (Bothrops alternatus). <br> This data is linked to the BioSample SAMN16930333 in NCBI. <br> <br>
DOI: 10.6084/m9.figshare.22227583.v1
title: Bothrops_alternatus_toxin_annotation

description: Toxin annotation of Bothrops alternatus genome using ToxCodAn-Genome. This data is linked to the BioSample SAMN16930333 in NCBI.
DOI: 10.6084/m9.figshare.22227583.v2
title: Bothrops_alternatus_toxin_annotation

description: Toxin annotation of Bothrops alternatus genome using ToxCodAn-Genome. This data is linked to the BioSample SAMN16930333 in NCBI.
DOI: 10.6084/m9.figshare.22227580.v2
title: Bothrops_alternatus_genome_annotation

description: Genome annotation of Bothrops alternatus using funannotate. This data is linked to the BioSample SAMN16930333 in NCBI.
DOI: 10.6084/m9.figshare.22227580.v1
title: Bothrops_alternatus_genome_annotation

description: Genome annotation of Bothrops alternatus using funannotate. This data is linked to the BioSample SAMN16930333 in NCBI.
DOI: 10.6084/m9.figshare.22227565.v1
title: Bothrops_alternatus_genome_assembly

description: Genome assembly of Bothrops alternatus using PacBio HiFi data. This data is linked to the BioSample SAMN16930333 in NCBI.
DOI: 10.18462/iir.icr.2023.0174
title: Method for evaluating the energy efficiency of free cooling and refrigerating systems in hydraulically linked circuits.
DOI: 10.18462/iir.icr.2023.0172
title: Caloric cooling modelling with a novel tool for simulating thermal control circuits.
DOI: 10.5281/zenodo.10117299
title: Datasets, scripts and log files to PHIRST respiratory syncytial virus analysis (South Africa, 2017-2018)

description: No description provided.
DOI: 10.5281/zenodo.10117300
title: Datasets, scripts and log files to PHIRST respiratory syncytial virus analysis (South Africa, 2017-2018)

description: No description provided.
DOI: 10.5281/zenodo.8132045
title: ΔvapHm-RDKit: Standard Vaporization Enthalpy Database

description: We present a database to Predict Standard Vaporization Enthalpies through Intelligible Features.
This database presents a variety of molecules of diverse chemical families with known experimental Standard Vaporization Enthalpy (ΔvapHm°) values. Entries were collected from the NIST WebBook Library through a web scraping routine, considering only ΔvapHm° experimental values, ranging from 15 kJ mol-1 to 400 kJ mol-1. Experimental value scrapping was automatically made, without duplicates, by selecting the first listed value (either a from single or average of values as determined by NIST). The database includes each value's original literature, along with experimental uncertainties (when available). 
Each compound is represented by its molecular family, SMILES string and respective InChlKey & InChl identifiers. The curated database consists of 1781 molecules over 15 different chemical families. The chemical descriptors used to feed our model were generated using RDKit version 2022.09.4, running on top of Python 3.9. Descriptors were calculated from the "MolFromSmiles" function in "RDKIT.Chem" as descriptors with non-numerical values were removed. The descriptors encode significant chemical information and are used to present physicochemical characteristics of compounds, building a relationship between structure and ΔvapHm° determinations.
Through Machine Learning regression algorithms, we have developed models that were able to make accurate ΔvapHm° predictions, based on the information encoded in each chemical feature. Our models can be accessed through GitHub.
DOI: 10.5281/zenodo.8132046
title: ΔvapHm-RDKit: Standard Vaporization Enthalpy Database

description: We present a database to Predict Standard Vaporization Enthalpies through Intelligible Features.
This database presents a variety of molecules of diverse chemical families with known experimental Standard Vaporization Enthalpy (ΔvapHm°) values. Entries were collected from the NIST WebBook Library through a web scraping routine, considering only ΔvapHm° experimental values, ranging from 15 kJ mol-1 to 400 kJ mol-1. Experimental value scrapping was automatically made, without duplicates, by selecting the first listed value (either a from single or average of values as determined by NIST). The database includes each value's original literature, along with experimental uncertainties (when available). 
Each compound is represented by its molecular family, SMILES string and respective InChlKey & InChl identifiers. The curated database consists of 1781 molecules over 15 different chemical families. The chemical descriptors used to feed our model were generated using RDKit version 2022.09.4, running on top of Python 3.9. Descriptors were calculated from the "MolFromSmiles" function in "RDKIT.Chem" as descriptors with non-numerical values were removed. The descriptors encode significant chemical information and are used to present physicochemical characteristics of compounds, building a relationship between structure and ΔvapHm° determinations.
Through Machine Learning regression algorithms, we have developed models that were able to make accurate ΔvapHm° predictions, based on the information encoded in each chemical feature. Our models can be accessed through GitHub.
DOI: 10.18462/iir.icr.2023.0151
title: Projecting the carbon emissions from refrigeration used in the UK food industry to 2050.
DOI: 10.18462/iir.icr.2023.0150
title: Vapour compression and caloric refrigeration in combination for a new hybrid refrigeration system.
DOI: 10.18462/iir.icr.2023.0145
title: How to optimize the floating high pressure
DOI: 10.18462/iir.icr.2023.0221
title: Experimental study on a multi-mode hybrid adsorption refrigeration and dehumidification system for low grade heat utilization.
DOI: 10.7298/01da-ka24
title: Dataset: Ocean-bottom P and S arrival waveform dataset from the Alaska Amphibious Community Seismic Experiment, 2018
DOI: 10.18462/iir.icr.2023.0084
title: Evaluation of global optimization algorithms for capillary tube suction line heat exchanger sizing.
DOI: 10.18462/iir.icr.2023.0065
title: Dynamic model of mixing and separation of refrigerant with lubricant in compressor oil sumps.
DOI: 10.18462/iir.icr.2023.0297
title: Numerical study on three CO2 transcritical two-stage refrigeration systems used in cold storage.
DOI: 10.18462/iir.icr.2023.0877
title: Molecular simulation for property prediction of low GWP refrigerant mixtures.
DOI: 10.4121/4a9dac6d-dd4e-4dc2-a5ba-72e35d86ac93
title: Data underlying the publication: Sizing batteries for power flow management in distribution grids

description: Includes the following datasets:The IEEE Test Grid Excel file which is read into the Python model to generate the test grid (.xlsx file).Load Patterns used for consumer connections in the Python model, with variable simultaneity (simultaneity % is indicated after the '_' in the file name) (.csv files).A generation pattern file used in the Python model. The file is currently filled with 0's, but can be adapted to test decentral generation effects (.csv file).The final results and data analysis (.xlsm file).<br>Also included is the .py file with the code used to simulate power flows in the grid.<br>This work is supported by Hanze University of Applied Sciences.
DOI: 10.4121/4a9dac6d-dd4e-4dc2-a5ba-72e35d86ac93.v2
title: Data underlying the publication: Sizing batteries for power flow management in distribution grids

description: Includes the following datasets:The IEEE Test Grid Excel file which is read into the Python model to generate the test grid (.xlsx file).Load Patterns used for consumer connections in the Python model, with variable simultaneity (simultaneity % is indicated after the '_' in the file name) (.csv files).A generation pattern file used in the Python model. The file is currently filled with 0's, but can be adapted to test decentral generation effects (.csv file).The final results and data analysis (.xlsm file).<br>Also included is the .py file with the code used to simulate power flows in the grid.<br>This work is supported by Hanze University of Applied Sciences.
DOI: 10.18462/iir.icr.2023.0873
title: Condensation heat transfer of refrigerant mixtures of R1234yf and R32 in multiport minichannels.
DOI: 10.18462/iir.icr.2023.0862
title: Development of an electrochemical membrane dehumidifier.
DOI: 10.18462/iir.icr.2023.0855
title: Solid-liquid equilibrium property measurements for R23 alternative candidates.
DOI: 10.18462/iir.icr.2023.0851
title: Measurements of isobaric heat capacity of R1336mzz(Z).
DOI: 10.5281/zenodo.10171557
title: Fig 6b - FWHM vs distance - broken membrane

description: The temperature profile on a broken patterned silicon membrane. (b) The line width versus the relative distance between the moving heating laser and the DBT-Ac nanocrystal. The error bars correspond to repeated laser scans, as explained in Sec. III A from the related publication. (c) The temperature profile as a function of the relative distance between the moving heating laser and the DBT-Ac nanocrystal. The red circles denote temperatures estimated from experimental measurements in (b) considering a calibration curve as described in Sec. III A. The solid lines represent simulated temperature profiles assuming different power laws of dependence of the thermal conductivity on the temperature, as well as the presence or lack thereof of the tear, as described in the text.
DOI: 10.5281/zenodo.10171558
title: Fig 6b - FWHM vs distance - broken membrane

description: The temperature profile on a broken patterned silicon membrane. (b) The line width versus the relative distance between the moving heating laser and the DBT-Ac nanocrystal. The error bars correspond to repeated laser scans, as explained in Sec. III A from the related publication. (c) The temperature profile as a function of the relative distance between the moving heating laser and the DBT-Ac nanocrystal. The red circles denote temperatures estimated from experimental measurements in (b) considering a calibration curve as described in Sec. III A. The solid lines represent simulated temperature profiles assuming different power laws of dependence of the thermal conductivity on the temperature, as well as the presence or lack thereof of the tear, as described in the text.
DOI: 10.60520/ieda/113065
title: Chemical and stable isotope analyses of kersantite xenoliths from the Quimsachata volcano in Southern Peru

description: This dataset includes chemical analyses preformed on a suite of xenoliths collected from the Quimsachata volcano near the towns of San Pedro and Raqchi in Southern Peru. Analyses covered in this dataset include: 1) major and trace element analyses of seven kersantite xenoliths and one wehrlite xenolith, 2) hydrogen isotope ratios and chemical compositions of phlogopite separates from these xenoliths, and 3) major and trace element compositions of four lava flows from southern Peru belonging to the Quaternary Rumicolca formation, including the Quimsachata flow. This data was collected to interrogate the history of mantle metasomatism below the northern Altiplano Plateau and to constrain the petrogenesis of Quaternary backarc volcanism in this region. For a detailed discussion of the research motivation, geologic background, analytical techniques, and interpretations, please refer to the associated publication submitted to Geochemistry, Geophysics, and Geosystems.
description: Hiett, C.D., Newell, D.L., Shervais, J.W., "Shallow subduction-derived metasomatism at the root of alkaline backarc magmatism in the northern Altiplano." Submitted to Geochemistry, Geophysics, and Geosystems.
DOI: 10.5281/zenodo.10171573
title: Spatial Informatics Group (SIG)_asdf

description: asdf
DOI: 10.5281/zenodo.10171574
title: Spatial Informatics Group (SIG)_asdf

description: asdf
DOI: 10.5281/zenodo.10171311
title: Risk of drought damage in Swedish forests

description: The dataset compiled here was used in a study whose objective was to estimate the drought vulnerability for the dominant boreal tree species (Norway spruce, Scots pine, and birch) using the extensive tree-ring network and tree, stand, and site information from the Swedish National Forest Inventory (NFI). The observed climate data used in the modeling process were obtained from the Swedish Meteorological and Hydrological Institute (SMHI). We used tree-ring data from Swedish NFI temporary plots, with cores that were taken between 2010 and 2018, for further analysis. The risk of drought damage was calculated based on the number of years with exceptionally low tree growth because of drought during 1960–2010. We found the most important predictors of forest drought vulnerability and how the risk of drought damage will evolve in space and time due to climate change for the studied species. For more detailed information, please see the reference: Aldea, J. et al., 2023. Current and future drought vulnerability for three dominant boreal tree species. Global Change Biology.
DATA & FILE OVERVIEW
'DB_model': stand, tree and site information collected by temporal inventories from the Swedish NFI, used for modelling approach.
'DB_sampled': stand, tree and site information collected by temporal inventories from the Swedish NFI, used for computing spatial predictions.
'TRW': Tree ring width data from the Swedish NFI temporary plots.
'climate': Gridded Precipitation and Temperature Data from SMHI 
 Future climate projections according to different gas-emission scenarios from SMHI
'Aldea_R_script': Main R-scripts used in the modelling process
DOI: 10.18712/nsd-nsd2904-v6
title: Norwegian Citizen Panel Round 18, 2020

description: The Norwegian Citizen Panel is a platform for internet surveys of public opinion in important areas of society and politics in Norway. Participants are randomly recruited from the Norwegian population register, and they are encouraged to participate over time. The panel was fielded for the first time the fall of 2013 and as of 2017 the survey is carried out three times a year. The data set for The Norwegian Citizen Panel Wave 18, 2020 also contains variables from previous waves, the wave number is indicated by the number after "r" in the variable name. The University of Bergen owns and is responsible for the Citizen panel. The company Ideas 2 Evidence recruits respondents, produces the survey, and provides documentation of the data. Data is stored and shared by Sikt - Norwegian Agency for Shared Services in Education and Research. The different datasets of the Norwegian Citizen Panel have different ID numbers to prevent the identification of individual participants across rounds. If access to data that follows participants over time (time-series/panel data) is desired, then it must be applied for by contacting DIGSSCORE (uib.no/digsscore / digsscore@uib.no). The same applies to text data and other data that is withheld in these datasets for privacy reasons. The Norwegian Citizen Panel welcomes research proposals for survey content. More information about calls and other updates is available at www.uib.no/en/citizen

The full text for the answer options can be found in the codebook, which is located further down the page.
DOI: 10.18712/nsd-nsd2940-v5
title: Norwegian Citizen Panel Round 19, 2020

description: The Norwegian Citizen Panel is a platform for internet surveys of public opinion in important areas of society and politics in Norway. Participants are randomly recruited from the Norwegian population register, and they are encouraged to participate over time. The panel was fielded for the first time the fall of 2013 and as of 2017 the survey is carried out three times a year. The data set for The Norwegian Citizen Panel Wave 19, 2020 also contains variables from previous waves, the wave number is indicated by the number after "r" in the variable name. The University of Bergen owns and is responsible for the Citizen panel. The company Ideas2Evidence recruits respondents, produces the survey, and provides documentation of the data. Data is stored and shared by Sikt - Norwegian Agency for Shared Services in Education and Research. The different datasets of the Norwegian Citizen Panel have different ID numbers to prevent the identification of individual participants across rounds. If access to data that follows participants over time (time-series/panel data) is desired, then it must be applied for by contacting DIGSSCORE (uib.no/digsscore / digsscore@uib.no). The same applies to text data and other data that is withheld in these datasets for privacy reasons. The Norwegian Citizen Panel welcomes research proposals for survey content. More information about calls and other updates is available at www.uib.no/en/citizen

The full text for the answer options can be found in the codebook, which is located further down the page.
DOI: 10.3217/a7fp1-t6k70
title: MD simulation of SlOPR3 with NADH at 298K and 310K

description: The uploaded files include the trajectory files and starting structures (GROMACS files) for the molecular dynamics (MD) simulation of the flavoenzyme 12-oxophytodienoate reductase 3 from tomato (SlOPR3) with NADH at 298K (traj_noHOH_298K.xtc and noHOH_298K.gro) and 310K (traj_00_noHOH_310K.xtc and noHOH_310K.gro). The MD simulations were performed with the MD software GROMACS.
DOI: 10.5517/ccdc.csd.cc2f3w2j
title: CCDC 2238047: Experimental Crystal Structure Determination

description: Related Article: Ökten Üngör, Stephanie Sanchez, Tyler M. Ozvat, Joseph M. Zadrozny|2023|Inorg.Chem.Front.|10|7064|doi:10.1039/D3QI01641B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.24242887.v1
title: Data & Scripts for Fig. 6A,B and Fig. S6

description: Bacterial growth curves with different aliphatic GLS
DOI: 10.5517/ccdc.csd.cc2fhd9n
title: CCDC 2249121: Experimental Crystal Structure Determination

description: Related Article: Wenxuan Li, Guoying Yao, Yilan Zhang, Lingjiao Zhang, Sujuan Hu, Chuan Liu, Baiquan Liu, Tao Zeng, Zhenyu Yang|2023|Inorg.Chem.Front.|10|6990|doi:10.1039/D3QI01512B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fhdx8
title: CCDC 2249140: Experimental Crystal Structure Determination

description: Related Article: Wenxuan Li, Guoying Yao, Yilan Zhang, Lingjiao Zhang, Sujuan Hu, Chuan Liu, Baiquan Liu, Tao Zeng, Zhenyu Yang|2023|Inorg.Chem.Front.|10|6990|doi:10.1039/D3QI01512B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fhdy9
title: CCDC 2249141: Experimental Crystal Structure Determination

description: Related Article: Wenxuan Li, Guoying Yao, Yilan Zhang, Lingjiao Zhang, Sujuan Hu, Chuan Liu, Baiquan Liu, Tao Zeng, Zhenyu Yang|2023|Inorg.Chem.Front.|10|6990|doi:10.1039/D3QI01512B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fhdzb
title: CCDC 2249142: Experimental Crystal Structure Determination

description: Related Article: Wenxuan Li, Guoying Yao, Yilan Zhang, Lingjiao Zhang, Sujuan Hu, Chuan Liu, Baiquan Liu, Tao Zeng, Zhenyu Yang|2023|Inorg.Chem.Front.|10|6990|doi:10.1039/D3QI01512B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fhf0d
title: CCDC 2249143: Experimental Crystal Structure Determination

description: Related Article: Wenxuan Li, Guoying Yao, Yilan Zhang, Lingjiao Zhang, Sujuan Hu, Chuan Liu, Baiquan Liu, Tao Zeng, Zhenyu Yang|2023|Inorg.Chem.Front.|10|6990|doi:10.1039/D3QI01512B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ft15h
title: CCDC 2258386: Experimental Crystal Structure Determination

description: Related Article: Zhang Weijie|2023|CSD Communication|||
description: Related Article: Wei-Jie Zhang, Wan-Tao Chen, Chen-Hui Li, Wen-Zhu Sun, Jia-Wen Ye, Ling Chen, Hai-Ping Wang, Xiao-Ming Chen|2023|Inorg.Chem.Front.|10|6909|doi:10.1039/D3QI01723K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ft16j
title: CCDC 2258387: Experimental Crystal Structure Determination

description: Related Article: Zhang Weijie|2023|CSD Communication|||
description: Related Article: Wei-Jie Zhang, Wan-Tao Chen, Chen-Hui Li, Wen-Zhu Sun, Jia-Wen Ye, Ling Chen, Hai-Ping Wang, Xiao-Ming Chen|2023|Inorg.Chem.Front.|10|6909|doi:10.1039/D3QI01723K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ft18l
title: CCDC 2258389: Experimental Crystal Structure Determination

description: Related Article: Zhang Weijie|2023|CSD Communication|||
description: Related Article: Wei-Jie Zhang, Wan-Tao Chen, Chen-Hui Li, Wen-Zhu Sun, Jia-Wen Ye, Ling Chen, Hai-Ping Wang, Xiao-Ming Chen|2023|Inorg.Chem.Front.|10|6909|doi:10.1039/D3QI01723K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.