cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23805525.v1
title: DirittiInternet_FINALE.sav

description: The demoscopic survey, carried out by the University of Udine and the Ixè Institute of Trieste, involved a sample of 600 respondents, representative of the Italian population aged over 18 (50,243,518 as of 1/1/2019). The sampling followed a proportional design, with a priori definition of sample quotas, aligned with the most recent ISTAT data, with respect to the following parameters: gender, age class, geographical area, and size class of the municipality of residence. Considering the correlation with the phenomena investigated, based on official data, an a posteriori weighting was also carried out to guarantee correct distribution with respect to school level and voting behaviour at the last political elections. The sample size used ensured a fair degree of precision of the estimates, with a maximum margin of error of +/-4.01%. The interviews were carried out based on a structured questionnaire. Prior to the administration of the interviews to the sample, a pre-test was carried out between 01/10/2020 and 02/10/2020, by means of around 20 pilot interviews, which allowed for the validation of the questionnaire design and the wording of the various questions. Between 6/10/2020 and 10/10/2020, a total of 600 complete interviews were carried out, distributed as follows according to the survey technique: 100 telephone interviews (CATI system - Computer Assisted Telephone Interviewing) and 500 online interviews (CAWI system - Computer Assisted Web Interviewing). This distribution of interview techniques made it possible to over-sample the segment of Internet users during the survey phase, consistent with the topics addressed. The a posteriori weighting procedure in any case ensured sampling representativeness with respect to the overall distribution of the Italian adult population. Concerning the telephone interviews, public telephone directories and a panel of mobile phone numbers, provided with prior consent, in the availability of a partner of the Ixè Institute, were used. For the telephone interviews, a strategy based on a maximum of 6 contacts was followed, obtaining, after the survey, a response rate of 2.67%, in conformity with Response Rate 2, as defined by the American Association for Public Opinion Research. Regarding the online interviews, a panel of e-mails, provided with prior consent, was drawn from a partner of the Ixè Institute. A total of 1,447 invitations were sent out, obtaining 500 complete compilations from the target subjects according to the sample stratification established a priori, with a response rate of 34.55%.<br>
DOI: 10.5281/zenodo.8194083
title: Organic carbon dynamics in clay soils: impact of management practices on microorganism structure and abundance under semi-arid conditions

description: Proper management of soil organic matter in arid and semi-arid regions improves organic carbon storage in the soil, helps in compact soil degradation, mitigates climate change impacts, and preserves ecosystem functionality and sustainability food security. This study aims to provide a better insight into the biogeochemical processes that drive the organic carbon dynamics of saline clay soil in a semi-arid area. The study is not intended to be exhaustive but contributes to analyzing the relationship between bacterial microflora, physicochemical properties, and organic carbon dynamics as a function of different soil management modes. The monitoring was carried out on three different plots located at the National Institute of Agronomic Research of Algeria. A physicochemical characterization of the soils was performed. A metagenomic study was also conducted to identify bacterial biodiversity using PCR-amplified DNA sequencing. The study results show that the control plot has the highest average organic carbon stock value at 47 Mg ha-1. This was followed by the amended plot and the conventional plot, respectively, with 43 Mg ha-1 and 38 Mg ha-1. In the context of this study, organic carbon dynamics would appear to depend on the interaction of several biotic and abiotic factors. Soil management methods would impact the density and diversity of bacterial microflora. This, in turn, affects the soil's physicochemical properties and, more specifically, organic carbon dynamics and storage.
DOI: 10.5281/zenodo.8194082
title: Organic carbon dynamics in clay soils: impact of management practices on microorganism structure and abundance under semi-arid conditions

description: Proper management of soil organic matter in arid and semi-arid regions improves organic carbon storage in the soil, helps in compact soil degradation, mitigates climate change impacts, and preserves ecosystem functionality and sustainability food security. This study aims to provide a better insight into the biogeochemical processes that drive the organic carbon dynamics of saline clay soil in a semi-arid area. The study is not intended to be exhaustive but contributes to analyzing the relationship between bacterial microflora, physicochemical properties, and organic carbon dynamics as a function of different soil management modes. The monitoring was carried out on three different plots located at the National Institute of Agronomic Research of Algeria. A physicochemical characterization of the soils was performed. A metagenomic study was also conducted to identify bacterial biodiversity using PCR-amplified DNA sequencing. The study results show that the control plot has the highest average organic carbon stock value at 47 Mg ha-1. This was followed by the amended plot and the conventional plot, respectively, with 43 Mg ha-1 and 38 Mg ha-1. In the context of this study, organic carbon dynamics would appear to depend on the interaction of several biotic and abiotic factors. Soil management methods would impact the density and diversity of bacterial microflora. This, in turn, affects the soil's physicochemical properties and, more specifically, organic carbon dynamics and storage.
DOI: 10.6084/m9.figshare.21669917.v2
title: Duke William’s 1066 Campaign, the Historical Climatology

description: To estimate the weather in 1066, a multiple regression was conducted in R where September and October total precipitation and average air pressure were modelled against the precipitation reconstructions, NAO and temperature. The models were evaluated with a selection of running means to determine the optimal model. The 1066 values were then averaged for the optimal running mean range for each independent variable. The optimal models were used to estimate the 1066 values for September – October precipitation and air pressure. Lastly, the modeled values for 1066 were visualized in comparison to the modern values.
DOI: 10.5281/zenodo.8197583
title: Datensatz gesammelt in der Benutzerstudie im Feb. 2021

description: Der Prototype der EVIDENCE-App wurde von 6 Studenten getestet und für 10 Lemmata die Satzbelege aus dem DWDS Fashion & Mode Webkorpus via Best-Worst-Scaling gerankt. Aus den extrahierten Paarvergleichen können die Trainingscores für ein Supervised Learning Modell ermittelt werden.
DOI: 10.5281/zenodo.8197582
title: Datensatz gesammelt in der Benutzerstudie im Feb. 2021

description: Der Prototype der EVIDENCE-App wurde von 6 Studenten getestet und für 10 Lemmata die Satzbelege aus dem DWDS Fashion & Mode Webkorpus via Best-Worst-Scaling gerankt. Aus den extrahierten Paarvergleichen können die Trainingscores für ein Supervised Learning Modell ermittelt werden.
DOI: 10.6084/m9.figshare.23805576
title: Data from Fourqurean et al 2023

description: Dataset from Fourqurean et al 2023. Data from 13 distinct sites across the Western Atlantic. Seagrass meadow characteristics (biomass, shoot density, canopy height), seagrass elemental content (%CNP), seagrass soil characteristics (% organic carbon, % inorganic carbon, %CNP).
DOI: 10.6084/m9.figshare.23805579
title: Total data of SIB,MCMC,CORONA LAB.xlsx

description: This dataset contains the general data of the sources used in the study
DOI: 10.6084/m9.figshare.23805579.v1
title: Total data of SIB,MCMC,CORONA LAB.xlsx

description: This dataset contains the general data of the sources used in the study
DOI: 10.3886/e183966v1
title: Technological change, completeness of financing microstructures, and impact on well-being and income inequality

description: Financing microstructures are increasingly seen as a means of financial inclusion and improving overall well-being in developing countries. In practice, digital transformation in finance can accelerate the optimal functioning of financing microstructures, such as access by households to microfinance and microinsurance. Large households' access to finance can lead to a reduction in income inequality and an overall improvement in well-being. This paper explores the impact of access to digital finance and financing microstructures on household well-being and the reduction of income inequality. To this end, we use the propensity score matching, the double difference, and the smooth instrumental quantile regression as estimation methods with two periods of survey data. The paper uses the FinScope consumer data (2016) and the Harmonized Living Standards Measurement Study (2018) from Togo (West Africa) in a comparative perspective. The results indicate that access to digital finance, as a cultural game changer, and to financing microstructures improves overall household well-being and contributes significantly to reducing income inequality.
DOI: 10.34740/kaggle/dsv/6221480
title: Balochi Language to English Translation Dataset
DOI: 10.34740/kaggle/dsv/6221470
title: socialmedia
DOI: 10.5281/zenodo.7512773
title: CCG Starter Data Kit: Angola

description: A starter data kit for Angola
DOI: 10.5281/zenodo.7512774
title: CCG Starter Data Kit: Angola

description: A starter data kit for Angola
DOI: 10.6084/m9.figshare.24130158.v1
title: Additional file 14 of Specific pathway abundances in the neonatal calf faecal microbiome are associated with susceptibility to Cryptosporidium parvum infection: a metagenomic analysis

description: Additional file 14. Stratified Pathway Abundance Species Assignment Table.
DOI: 10.6084/m9.figshare.24130152
title: Additional file 12 of Specific pathway abundances in the neonatal calf faecal microbiome are associated with susceptibility to Cryptosporidium parvum infection: a metagenomic analysis

description: Additional file 12. Destratified Pathway Abundance Table.
DOI: 10.6084/m9.figshare.24130167.v1
title: Additional file 17 of Specific pathway abundances in the neonatal calf faecal microbiome are associated with susceptibility to Cryptosporidium parvum infection: a metagenomic analysis

description: Additional file 17. Molecular Functions MaAsLin2 Results Table.
DOI: 10.6084/m9.figshare.24130164.v1
title: Additional file 16 of Specific pathway abundances in the neonatal calf faecal microbiome are associated with susceptibility to Cryptosporidium parvum infection: a metagenomic analysis

description: Additional file 16. Cellular Components MaAsLin2 Results Table.
DOI: 10.6084/m9.figshare.24143785.v1
title: Additional file 1 of Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

description: Additional file 1: Table S1: Proportion of variation in AGE explained by SNPs for each purebred subset using five replications of randomly simulated genotype data.
DOI: 10.6084/m9.figshare.24143788
title: Additional file 2 of Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

description: Additional file 2: Table S2: Number of SNPs significantly associated with AGE for each subset using five replicates of randomly simulated genotype data.
DOI: 10.6084/m9.figshare.24143791.v1
title: Additional file 3 of Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

description: Additional file 3: Table S3: Population, chromosome, SNP effect, Q-value, gene identifier, associated human traits, and associated pig traits for SNPs associated with AGE from GPSM analyses.
DOI: 10.6084/m9.figshare.24143791
title: Additional file 3 of Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

description: Additional file 3: Table S3: Population, chromosome, SNP effect, Q-value, gene identifier, associated human traits, and associated pig traits for SNPs associated with AGE from GPSM analyses.
DOI: 10.6084/m9.figshare.24143785
title: Additional file 1 of Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

description: Additional file 1: Table S1: Proportion of variation in AGE explained by SNPs for each purebred subset using five replications of randomly simulated genotype data.
DOI: 10.6084/m9.figshare.24143788.v1
title: Additional file 2 of Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

description: Additional file 2: Table S2: Number of SNPs significantly associated with AGE for each subset using five replicates of randomly simulated genotype data.
DOI: 10.6084/m9.figshare.24587628
title: Additional file 1 of Bioinformatic and literature assessment of toxicity and allergenicity of a CRISPR-Cas9 engineered gene drive to control Anopheles gambiae the mosquito vector of human malaria

description: Additional file 1. Searches for homologues of F. necrophorum VapC in other species.
DOI: 10.6084/m9.figshare.24587628.v1
title: Additional file 1 of Bioinformatic and literature assessment of toxicity and allergenicity of a CRISPR-Cas9 engineered gene drive to control Anopheles gambiae the mosquito vector of human malaria

description: Additional file 1. Searches for homologues of F. necrophorum VapC in other species.
DOI: 10.6084/m9.figshare.24587689
title: Additional file 2 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 2: Table S1. Metadata donors.
DOI: 10.6084/m9.figshare.24587689.v1
title: Additional file 2 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 2: Table S1. Metadata donors.
DOI: 10.6084/m9.figshare.24587692
title: Additional file 3 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 3: Table S2. Marker genes.
DOI: 10.6084/m9.figshare.24587692.v1
title: Additional file 3 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 3: Table S2. Marker genes.
DOI: 10.6084/m9.figshare.24587695
title: Additional file 4 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 4: Table S3. ChEA3 results per subgroup.
DOI: 10.6084/m9.figshare.24587695.v1
title: Additional file 4 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 4: Table S3. ChEA3 results per subgroup.
DOI: 10.6084/m9.figshare.24587698
title: Additional file 5 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 5: Table S4. Unique DEGs per subgroup upon Cocktail.
DOI: 10.6084/m9.figshare.24587698.v1
title: Additional file 5 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 5: Table S4. Unique DEGs per subgroup upon Cocktail.
DOI: 10.6084/m9.figshare.24587701
title: Additional file 6 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 6: Table S5. Differential expression Cocktail vs. DMSO.
DOI: 10.6084/m9.figshare.24587701.v1
title: Additional file 6 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 6: Table S5. Differential expression Cocktail vs. DMSO.
DOI: 10.6084/m9.figshare.24587704
title: Additional file 7 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 7: Table S6. Significance levels coefficient of variation
DOI: 10.6084/m9.figshare.24587704.v1
title: Additional file 7 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 7: Table S6. Significance levels coefficient of variation
DOI: 10.6084/m9.figshare.24587707
title: Additional file 8 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 8: Table S7. Differential expression FFA vs. DMSO.
DOI: 10.6084/m9.figshare.24587707.v1
title: Additional file 8 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 8: Table S7. Differential expression FFA vs. DMSO.
DOI: 10.6084/m9.figshare.24587710
title: Additional file 9 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 9: Table S8. Differential expression FFA+Cocktail vs. DMSO.
DOI: 10.6084/m9.figshare.24587710.v1
title: Additional file 9 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 9: Table S8. Differential expression FFA+Cocktail vs. DMSO.
DOI: 10.6084/m9.figshare.24587713
title: Additional file 10 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 10: Table S9. Genes up-regulated upon Cocktail with and without FFA.
DOI: 10.6084/m9.figshare.24587713.v1
title: Additional file 10 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 10: Table S9. Genes up-regulated upon Cocktail with and without FFA.
DOI: 10.6084/m9.figshare.24587716
title: Additional file 11 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 11: Table S10. Drug Cocktail preparation
DOI: 10.6084/m9.figshare.24587716.v1
title: Additional file 11 of Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

description: Additional file 11: Table S10. Drug Cocktail preparation
DOI: 10.6084/m9.figshare.24587727
title: Additional file 3 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 3: Table S1. Sanger Sequencing HepG2. Results of genotyping WT HepG2 cells and four MCAD-knockouts.
DOI: 10.6084/m9.figshare.24587727.v1
title: Additional file 3 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 3: Table S1. Sanger Sequencing HepG2. Results of genotyping WT HepG2 cells and four MCAD-knockouts.
DOI: 10.6084/m9.figshare.24587733
title: Additional file 5 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 5: Table S2. Full patient urine acylcarnitine profiles. Historical urine acylcarnitine data from symptomatic and asymptomatic MCADD patients.
DOI: 10.6084/m9.figshare.24587733.v1
title: Additional file 5 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 5: Table S2. Full patient urine acylcarnitine profiles. Historical urine acylcarnitine data from symptomatic and asymptomatic MCADD patients.
DOI: 10.6084/m9.figshare.24587754
title: Additional file 11 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 11: Table S3. Full sensitivity analysis. Flux and CoASH concentration response coefficients for all model parameters at [palmitoyl-CoA] = 10 µM and 150 µM.
DOI: 10.6084/m9.figshare.24587754.v1
title: Additional file 11 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 11: Table S3. Full sensitivity analysis. Flux and CoASH concentration response coefficients for all model parameters at [palmitoyl-CoA] = 10 µM and 150 µM.
DOI: 10.6084/m9.figshare.24587769
title: Additional file 15 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 15: Table S4. Overview of patient characteristics. ID, sex, categorisation, age of onset/diagnosis, and description of MCADD and control individuals from whom fibroblasts were taken.
DOI: 10.6084/m9.figshare.24587769.v1
title: Additional file 15 of Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients

description: Additional file 15: Table S4. Overview of patient characteristics. ID, sex, categorisation, age of onset/diagnosis, and description of MCADD and control individuals from whom fibroblasts were taken.
DOI: 10.6084/m9.figshare.24587802
title: Additional file 2 of Disparities in spatially variable gene calling highlight the need for benchmarking spatial transcriptomics methods

description: Additional file 2: Table S1. Reported statistic and associated p-value from each combination of pairwise comparison of results between SpatialDE, SPARK-X, scGCO and Squidpy when reported p-values were compared using the Wilcoxon signed rank test. Table S2. Sensitivity and specificity of Squidpy, SPARK-X, SpatialDE and scGCO when used to analyse both simulated datasets generated with SRTsim. Sensitivity and specificity are reported over a range of q-value cut-offs, from 0.01-1.0. Table S3. Packages included for identification of SVGs in benchmarking study. The packages are ordered by assumptions made on distribution of gene expression. The rows highlighted in blue indicate grouped packages using graph-based methods. Table S4. Overview of publicly available 10X Visium datasets to be included in benchmarking process. FF indicates tissues that are fresh frozen and FFPE indicates tissues that are formalin-fixed paraffin-embedded. The filtered output files and imaging data from the Space Ranger v1.0.0, v1.2.0 or V1.3.0 pipeline were downloaded for each dataset.