cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7831763
title: ERGA Post Assembly training dataset

description: This Zenodo repository includes the required datasets for following the ERGA post-assembly quality control training. Protein accession file. Hi-C fastq file parts for erythrolamprus reginae. assembly fasta erythrolamprus reginae
DOI: 10.6084/m9.figshare.22640140
title: Row data for the article: "Share of and absolute costs of informal care in five subpopulations of outpatients with dementia in Croatia: A latent profile analysis" submited to the Journal of Alzheimer's Disease on February 14, 2023.

description: Data for the article: <strong>Share of and absolute costs of informal care in five subpopulations of outpatients with dementia in Croatia: A latent profile analysis, </strong>submited to the Journal of Alzheimer's Disease on Feburary 14, 2023. <br> Authors: Jelena <strong>Sušaca</strong>, Jakša <strong>Vukojević</strong>a, Siniša <strong>Debogović</strong>a, Žarko <strong>Bajić</strong>b, Aleksandar <strong>Savić</strong>a,c, Nataša <strong>Đuran</strong>a, Miroslav <strong>Hanževački</strong>d*, Dinko <strong>Vitezić</strong>e,f, Ninoslav <strong>Mimica</strong>a,c a University Psychiatric Hospital Vrapče, 10000 Zagreb, Croatia2 b Psychiatric Clinic Sveti Ivan, Zagreb, Croatia c School of Medicine, University of Zagreb, Zagreb, Croatia d General and Family Medicine Clinic, Health Center Zagreb-Zapad, Zagreb, Croatia e School of Medicine, University of Rijeka, Rijeka, Croatia f University Hospital Centre Rijeka, Rijeka, Croatia <br> Stata do file with labels and recodes are posted on this repository and are available from Žarko Bajić (zarko@biometrika.hr).
DOI: 10.6084/m9.figshare.22640140.v1
title: Row data for the article: "Share of and absolute costs of informal care in five subpopulations of outpatients with dementia in Croatia: A latent profile analysis" submited to the Journal of Alzheimer's Disease on February 14, 2023.

description: Data for the article: <strong>Share of and absolute costs of informal care in five subpopulations of outpatients with dementia in Croatia: A latent profile analysis, </strong>submited to the Journal of Alzheimer's Disease on Feburary 14, 2023. <br> Authors: Jelena <strong>Sušaca</strong>, Jakša <strong>Vukojević</strong>a, Siniša <strong>Debogović</strong>a, Žarko <strong>Bajić</strong>b, Aleksandar <strong>Savić</strong>a,c, Nataša <strong>Đuran</strong>a, Miroslav <strong>Hanževački</strong>d*, Dinko <strong>Vitezić</strong>e,f, Ninoslav <strong>Mimica</strong>a,c a University Psychiatric Hospital Vrapče, 10000 Zagreb, Croatia2 b Psychiatric Clinic Sveti Ivan, Zagreb, Croatia c School of Medicine, University of Zagreb, Zagreb, Croatia d General and Family Medicine Clinic, Health Center Zagreb-Zapad, Zagreb, Croatia e School of Medicine, University of Rijeka, Rijeka, Croatia f University Hospital Centre Rijeka, Rijeka, Croatia <br> Stata do file with labels and recodes are posted on this repository and are available from Žarko Bajić (zarko@biometrika.hr).
DOI: 10.6084/m9.figshare.22640191
title: Experimental data for "The sorption behaviors of barium"

description: Experimental data for "The sorption behaviors of barium"
DOI: 10.6084/m9.figshare.22640191.v1
title: Experimental data for "The sorption behaviors of barium"

description: Experimental data for "The sorption behaviors of barium"
DOI: 10.5281/zenodo.7833742
title: desmognathus_carolinensis_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.7833741
title: desmognathus_carolinensis_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.6084/m9.figshare.22640197
title: Experimental data.xlsx

description: Data set for the manuscript of The sorption behaviors of barium during reinjection of gas field produced water into sandstone reservoir: An experimental water-rock interaction study
DOI: 10.6084/m9.figshare.20666115
title: Table S1 - TSE_BiomassFilterWeights

description: Fungi for this experiment were cultured in liquid media (with or without Se(IV)) for a certain time frame (up to 32 days) and harvested using a pre-weighed 0.2 µm mixed cellulose ester filter. Fungal biomass and any associated Se solids were dried overnight at room temperature and weighed again the next day. Biomass weight reported here is that of the all dried components minus the original filter weight.
DOI: 10.6084/m9.figshare.20666115.v1
title: Table S1 - TSE_BiomassFilterWeights

description: Fungi for this experiment were cultured in liquid media (with or without Se(IV)) for a certain time frame (up to 32 days) and harvested using a pre-weighed 0.2 µm mixed cellulose ester filter. Fungal biomass and any associated Se solids were dried overnight at room temperature and weighed again the next day. Biomass weight reported here is that of the all dried components minus the original filter weight.
DOI: 10.6084/m9.figshare.20666166
title: Table S2 - TSE_AqueousPhaseSe

description: Data listed are aqueous Se(IV) concentrations in fungal culture experiments after exposure to an initial amount of aqueous Se(IV). Aqueous phase Se(IV) was determined via ion chromatography.
DOI: 10.6084/m9.figshare.20666166.v1
title: Table S2 - TSE_AqueousPhaseSe

description: Data listed are aqueous Se(IV) concentrations in fungal culture experiments after exposure to an initial amount of aqueous Se(IV). Aqueous phase Se(IV) was determined via ion chromatography.
DOI: 10.6084/m9.figshare.20666223
title: Table S3 - TSE_MassBalance

description: Data listed are mass balance calculations used to determine the amount of Se that was volatilized (missing) from fungal cultures exposed to Se(IV). Mass balance was calculated by subtracting the amount of Se(IV) originally added to each fungal culture or control from the amount quantified in the aqueous and solid phases for each respective experiment. Aqueous phase Se(IV) was determined via ion chromatography and solid phase Se was determined via inductively coupled plasma - optical emission spectrometry.
DOI: 10.6084/m9.figshare.20666223.v1
title: Table S3 - TSE_MassBalance

description: Data listed are mass balance calculations used to determine the amount of Se that was volatilized (missing) from fungal cultures exposed to Se(IV). Mass balance was calculated by subtracting the amount of Se(IV) originally added to each fungal culture or control from the amount quantified in the aqueous and solid phases for each respective experiment. Aqueous phase Se(IV) was determined via ion chromatography and solid phase Se was determined via inductively coupled plasma - optical emission spectrometry.
DOI: 10.6084/m9.figshare.20666313
title: Table S4 - TSE_SolidAssociatedSe

description: Data listed are solid-associated Se concentrations in fungal culture experiments exposed to an initial amount of aqueous Se(IV). Solid phase Se was determined by a preliminary chemical digestion of all dry biomass in hydrogen peroxide and trace metal grade nitric acid, which was then run on an inductively coupled plasma - optical emission spectrometer.
DOI: 10.6084/m9.figshare.20666313.v1
title: Table S4 - TSE_SolidAssociatedSe

description: Data listed are solid-associated Se concentrations in fungal culture experiments exposed to an initial amount of aqueous Se(IV). Solid phase Se was determined by a preliminary chemical digestion of all dry biomass in hydrogen peroxide and trace metal grade nitric acid, which was then run on an inductively coupled plasma - optical emission spectrometer.
DOI: 10.6084/m9.figshare.20666262
title: Table S5 - TSE_XAS_LCF_results_all_preliminary

description: Data listed are X-ray Absorption Spectroscopy / Extended X-ray Absorption Fine Structure (EXAFS) measurements taken at the Advanced Photon Source at Argonne National Laboratory. Samples are liquid fungal cultures exposed to Se(IV) and sampled at 5 points between day 0 and 32.
DOI: 10.6084/m9.figshare.20666262.v1
title: Table S5 - TSE_XAS_LCF_results_all_preliminary

description: Data listed are X-ray Absorption Spectroscopy / Extended X-ray Absorption Fine Structure (EXAFS) measurements taken at the Advanced Photon Source at Argonne National Laboratory. Samples are liquid fungal cultures exposed to Se(IV) and sampled at 5 points between day 0 and 32.
DOI: 10.17909/jgah-0b96
title: Beta UMa IUE Spectrophotometry SWP and LWR
DOI: 10.6084/m9.figshare.22640203
title: Expert's analysis dataset.xlsx

description: This data is a collection of experts' opinions on the effectiveness of the key COVID-19 policies implemented in Ghana in 2020/2021 to address the COVID-19 pandemic. The experts here include thirty-four academics from diverse health and economics disciplines in Ghana. The evaluated policies include the partial lockdown, public awareness campaigns, bans on social gatherings and incentives for healthcare workers. The dataset includes both quantitative and qualitative data.
DOI: 10.6084/m9.figshare.22640203.v1
title: Expert's analysis dataset.xlsx

description: This data is a collection of experts' opinions on the effectiveness of the key COVID-19 policies implemented in Ghana in 2020/2021 to address the COVID-19 pandemic. The experts here include thirty-four academics from diverse health and economics disciplines in Ghana. The evaluated policies include the partial lockdown, public awareness campaigns, bans on social gatherings and incentives for healthcare workers. The dataset includes both quantitative and qualitative data.
DOI: 10.6084/m9.figshare.22640221.v1
title: IdaTweets.csv

description: The dataset under consideration comprises a collection of tweets that pertain to the hurricane Ida disaster and have been generated using the Twitter API in conjunction with meshwords. The dataset is time-stamped and includes tweets spanning the period leading up to, during, and following the hurricane. The tweets contain a wide range of information, including eyewitness accounts, official alerts, news updates, and personal reflections on the disaster. In addition to the textual content of the tweets, the dataset also includes other important metadata such as the Twitter handle of the user who posted the tweet, the date and time of posting, the number of likes and retweets, and the geographic location (if available) of the user who posted the tweet. This metadata provides important context for understanding the tweets and the broader social media conversation surrounding the hurricane Ida disaster.
DOI: 10.6084/m9.figshare.22640221
title: IdaTweets.csv

description: The dataset under consideration comprises a collection of tweets that pertain to the hurricane Ida disaster and have been generated using the Twitter API in conjunction with meshwords. The dataset is time-stamped and includes tweets spanning the period leading up to, during, and following the hurricane. The tweets contain a wide range of information, including eyewitness accounts, official alerts, news updates, and personal reflections on the disaster. In addition to the textual content of the tweets, the dataset also includes other important metadata such as the Twitter handle of the user who posted the tweet, the date and time of posting, the number of likes and retweets, and the geographic location (if available) of the user who posted the tweet. This metadata provides important context for understanding the tweets and the broader social media conversation surrounding the hurricane Ida disaster.
DOI: 10.6084/m9.figshare.22640224
title: Partner preferences on matrimonial sites

description: Data set on partner preferences on matrimonail sites.
DOI: 10.34740/kaggle/dsv/5424976
title: Mahanagar Yatayat Dataset
DOI: 10.34740/kaggle/dsv/5424944
title: Transport for London (TfL) Entry & Exit Dataset
DOI: 10.34740/kaggle/dsv/5425177
title: Nigerian Presidential Election 2023 Tweets
DOI: 10.6084/m9.figshare.22640041
title: snp44k.11047.csv

description: The SNP marker data of 44k rice analyzed in this study.
DOI: 10.6084/m9.figshare.22640044
title: snp_soybean.txt

description: The SNP marker data of the soybean dataset analyzed in this study.
DOI: 10.6084/m9.figshare.22640044.v1
title: snp_soybean.txt

description: The SNP marker data of the soybean dataset analyzed in this study.
DOI: 10.6084/m9.figshare.22640020
title: snp_tropical.txt

description: The SNP marker dataset for the tropical rice analyzed in this study.
DOI: 10.6084/m9.figshare.22640020.v1
title: snp_tropical.txt

description: The SNP marker dataset for the tropical rice analyzed in this study.
DOI: 10.6084/m9.figshare.22640047
title: phenotype_soybean.csv

description: The phenotype dataset for soybean analyzed in this study.
DOI: 10.5281/zenodo.7833833
title: desmognathus_imitator_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7833832
title: desmognathus_imitator_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7833853
title: desmognathus_conanti_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7833852
title: desmognathus_conanti_decontaminated_gx.fasta.gz

description: .
DOI: 10.6084/m9.figshare.22640038
title: phenotype_44k_FT.csv

description: The phenotype dataset for 44K rice which was analyzed in the study -- Training set optimization for identifying the best genotypes from a candidate population in genomic selection. <br>
DOI: 10.6084/m9.figshare.22640038.v1
title: phenotype_44k_FT.csv

description: The phenotype dataset for 44K rice which was analyzed in the study -- Training set optimization for identifying the best genotypes from a candidate population in genomic selection. <br>
DOI: 10.6084/m9.figshare.22640032
title: SNP_wheat_winter.txt

description: The SNP marker data for wheat which was analyzed in the study -- Training set optimization for identifying the best genotypes from a candidate population in genomic selection.
DOI: 10.6084/m9.figshare.22640032.v1
title: SNP_wheat_winter.txt

description: The SNP marker data for wheat which was analyzed in the study -- Training set optimization for identifying the best genotypes from a candidate population in genomic selection.
DOI: 10.6084/m9.figshare.22640029
title: phenotype_wheat.csv

description: The phenotype dataset for wheat which was analyzed in the study -- Training set optimization for identifying the best genotypes from a candidate population in genomic selection.
DOI: 10.6084/m9.figshare.22640023
title: phenotype_tropical.csv

description: The phenotype dataset for tropical rice which was analyzed in the study -- Training set optimization for identifying the best genotypes from a candidate population in genomic selection.
DOI: 10.6084/m9.figshare.22640023.v1
title: phenotype_tropical.csv

description: The phenotype dataset for tropical rice which was analyzed in the study -- Training set optimization for identifying the best genotypes from a candidate population in genomic selection.
DOI: 10.5281/zenodo.7725147
title: Roy et al. 2023 Supplemental Information for "Sediment-encased pressure–temperature maturation experiments elucidate the impact of diagenesis on melanin-based fossil color and its paleobiological implications."

description: <em>Supplemental Information for</em> Sediment-encased pressure–temperature maturation experiments elucidate the impact of diagenesis on melanin-based fossil color and its paleobiological implications. Arindam Roy<em><sup>*</sup></em> (https://orcid.org/0000-0002-4890-6851) Michael Pittman<em><sup>*</sup></em> (https://orcid.org/0000-0002-6149-3078) Thomas G. Kaye (https://orcid.org/0000-0001-7996-618X) Evan T. Saitta (https://orcid.org/0000-0002-9306-9060) *Corresponding author(s) <strong>Email: </strong>ar15313@bristol.ac.uk ; mpittman@cuhk.edu.hk The Dataset contains two files, (1) Supporting Information and (2) Supporting Data PCA worksheet. The first contains Supplementary tables and figures (.docx file) while the structural organisation of the second (.xlsx file) is provided below: Sheets: |----- PCA whole : contains Sample ID, treatment categories, mass by charge (m/Z) ratios of peaks, peak identity and raw intensity counts. |-----PCA Norm : same data as PCA whole but peak raw intensity counts normalised. |-----PCA Mean Centered: same data as PCA Norm but with peak raw intensity counts normalised. |-----PCA All Loading Matrix: Loading matrix for PCA using all peaks. |-----PCA without Lipids RAW: same data as PCA whole but without peaks suspected to arise from lipids (e.g., CxH- ) |-----PCA without Lipids Norm: same data as PCA without Lipids RAW but with peak raw intensity counts normalised. |-----PCA without Lipids MeanCentred: same data as PCA without Lipids Norm but with peak raw intensity counts normalised. |-----PCAwithoutLipidsLoading Matrix: Loading matrix for PCA using peaks excluding peaks of lipid origin (CxH-). The dataset can be created in Microsoft Office 365 (Excel: .xlsx file). The file can also be also be opened and edited using the following softwares. Google Sheets Apache Open Office Libre Office PAST 4 (free software for scientific data analysis, with functions for data manipulation, plotting, univariate and multivariate statistics, ecological analysis, time series and spatial analysis, morphometrics and stratigraphy).
DOI: 10.5281/zenodo.3419929
title: Data and code for figures in "Two-tone optomechanical instability and its fundamental implications for backaction-evading measurements"

description: Here we prepare the data and process scripts to reconstruct figure 4 of the paper (Two-tone optomechanical instability and its fundamental implications for backaction-evading measurements). The folder contains several subfolders and files: “Raw data”: In this folder, you can find the raw data recorded by measurement devices during the experiment. It follows the hierarchical structure. We have three pairs of folders corresponding to three cooperativities (3.5, 7, 14). One folder of each pair contains raw data files in text format (.dat) and the other one contains plots and a Numpy dictionary of the extracted parameter for each cooperativity (superdict.npy). If you need to redo the extraction process from the raw data you can simply run “181031_CXX_Final_NOQT_BAE_2D_post_processeing.py” (XX: 3.5 or 7 or 14) python code to rewrite superdict.npy files and replot all plots in the Raw data folder.<br> “NRBcodes”: A side package for the circle fit (Lorentzian fitting) in the complex plane.<br> “Dicts”: A folder containing Numpy dictionaries needed for the final plot. “superdictXX.npy” are copies of Numpy dictionaries in the Raw data folder. “powers_XX.npy” and “Ds_nor_XX.npy” are Numpy dictionaries needed for the theory plots. You can reproduce them by the uncommenting first part of the “Final_plot.py” and correcting the corresponding cooperativity.<br> “getdata.py” and “postprocessing_libs.py”: Side packages help to read the raw data files.<br> <br> All post-processes are done on the raw data and you just need to run the “Final_plot.py” to reproduce the plot. If you want to access the post-processed data you can simply read “superdictXX.npy” in the Dicts folder. <br> Please do not hesitate to contact us in case of any questions. <br> amir.youssefi@epfl.ch
description: Tested with Python 3.6.5, mathplotlib 2.2.2, scipy 1.1.0, uncertainties 3.1.2
DOI: 10.5281/zenodo.3419928
title: Data and code for figures in "Two-tone optomechanical instability and its fundamental implications for backaction-evading measurements"

description: Here we prepare the data and process scripts to reconstruct figure 4 of the paper (Two-tone optomechanical instability and its fundamental implications for backaction-evading measurements). The folder contains several subfolders and files: “Raw data”: In this folder, you can find the raw data recorded by measurement devices during the experiment. It follows the hierarchical structure. We have three pairs of folders corresponding to three cooperativities (3.5, 7, 14). One folder of each pair contains raw data files in text format (.dat) and the other one contains plots and a Numpy dictionary of the extracted parameter for each cooperativity (superdict.npy). If you need to redo the extraction process from the raw data you can simply run “181031_CXX_Final_NOQT_BAE_2D_post_processeing.py” (XX: 3.5 or 7 or 14) python code to rewrite superdict.npy files and replot all plots in the Raw data folder.<br> “NRBcodes”: A side package for the circle fit (Lorentzian fitting) in the complex plane.<br> “Dicts”: A folder containing Numpy dictionaries needed for the final plot. “superdictXX.npy” are copies of Numpy dictionaries in the Raw data folder. “powers_XX.npy” and “Ds_nor_XX.npy” are Numpy dictionaries needed for the theory plots. You can reproduce them by the uncommenting first part of the “Final_plot.py” and correcting the corresponding cooperativity.<br> “getdata.py” and “postprocessing_libs.py”: Side packages help to read the raw data files.<br> <br> All post-processes are done on the raw data and you just need to run the “Final_plot.py” to reproduce the plot. If you want to access the post-processed data you can simply read “superdictXX.npy” in the Dicts folder. <br> Please do not hesitate to contact us in case of any questions. <br> amir.youssefi@epfl.ch
description: Tested with Python 3.6.5, mathplotlib 2.2.2, scipy 1.1.0, uncertainties 3.1.2
DOI: 10.5281/zenodo.7765607
title: The data and code for "Gap-Filling of Turbulent Heat Fluxes over Rice–Wheat-Rotation Croplands Using the Random Forest Model""

description: This file contains the dataset and code for the paper "Gap-Filling of Turbulent Heat Fluxes over Rice–Wheat-Rotation Croplands Using the Random Forest Model".
DOI: 10.5281/zenodo.4289835
title: Database of global glendonite and ikaite records throughout the Phanerozoic

description: Here database of Phanerozoic occurrences and isotopic characteristics of metastable cold-water calcium carbonate hexahydrate (ikaite; CaCO3•6H2O) and its pseudomorphs (glendonites) is represented. The previous version of this database included 690 records ranged from Cambrian to recent, based on 323 references, the authors’ data and additional personal communications from the colleagues [https://doi.org/10.5281/zenodo.3991964]. The updated database includes 53 additional localities based on extra 41 references. Database is provided as Excel2003 (.xls)- file, which consists from 5 sheets. The major sheet ‘Glendonites and latitudes’ includes a list of localities along with latitude / longitude, geologic age (in Ma and substage), palaeolatitude, references, environments and host rock for all records. Three sheets, entitled “Cenozoic glendonite and ikaite”, “Mesozoic glendonite” and “Paleozoic glendonite” includes data concerning carbon and oxygen stable isotope values of, respectively, Cenozoic, Mesozoic and Paleozoic samples. The last sheet “References” contains list of references in APA style, accompanied by DOI numbers and hyperlinks to electronic versions (if available). This database is a part of the MS submitted for publication to ESSD [https://doi.org/10.5194/essd-2020-222]