cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20338182
title: wanessa GOES - Table_S3.xlsx

description: Using normalized read depth analysis to assess gene copy number variation in the PH8 strain, we identified 205 genes presenting a somy greater than 1.8. Among these genes that were considered supernumerary or expanded, 104 encode hypothetical proteins, with unknown function. Multigene families encoding amino acid transporters, serine threonine phosphatase, ferredoxins, kinases, calpains, and GP63 metalloproteases are among the supernumerary genes with known function, several of them, being characterized as virulence factors and are discussed in the next section. Gene ontology analysis on the expanded genes showed that this group is enriched for genes involved in biological process related to transmembrane transport (8 genes) and lipid metabolism (13 genes), representing 447 haploid copies in PH8 genome.
DOI: 10.6084/m9.figshare.20338182.v1
title: wanessa GOES - Table_S3.xlsx

description: Using normalized read depth analysis to assess gene copy number variation in the PH8 strain, we identified 205 genes presenting a somy greater than 1.8. Among these genes that were considered supernumerary or expanded, 104 encode hypothetical proteins, with unknown function. Multigene families encoding amino acid transporters, serine threonine phosphatase, ferredoxins, kinases, calpains, and GP63 metalloproteases are among the supernumerary genes with known function, several of them, being characterized as virulence factors and are discussed in the next section. Gene ontology analysis on the expanded genes showed that this group is enriched for genes involved in biological process related to transmembrane transport (8 genes) and lipid metabolism (13 genes), representing 447 haploid copies in PH8 genome.
DOI: 10.5281/zenodo.6913130
title: Mormyrops boulengeri decontaminated gx

description: .
DOI: 10.5281/zenodo.6913129
title: Mormyrops boulengeri decontaminated gx

description: .
DOI: 10.26050/wdcc/modataintotr21stclandfl
title: Tracking 21st century anthropogenic and natural carbon fluxes through model-data integration

description: Project: Model-data integration to assess land carbon fluxes - This project is embedded in the project 'High-resolution monitoring of avoided carbon emissions and carbon restoration potentials from land use change', funded by German Stifterverband für die Deutsche Wissenschaft e.V. in collaboration with Volkswagen AG for the period 2020-2021. The project aims at providing updated and more reliable estimates of terrestrial land use and natural carbon fluxes by integrating observation-based datasets into global carbon cycle models. Summary: A time series of 21st century observation-based woody vegetation carbon stocks (Xu et al.,2021; https://www.science.org/doi/10.1126/sciadv.abe9829) was assimilated into the bookkeeping model BLUE ('bookkeeping of land use emissions') (Hansis et al.,2015; https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2014GB004997). Two data-integration experiments were performed to isolate anthropogenic and natural carbon fluxes. The 'transient' experiment relies on assimilating the time series of observation-based vegetation carbon stocks at each (annual) time step in BLUE. In the 'transient' experiment, changes in woody vegetation carbon between two time steps are due to the combination of environmental and anthropogenic processes. In the 'fixed' experiment, the time series of observation-based woody vegetation carbon is only assimilated in BLUE at the first time step and changes in woody vegetation carbon between two time steps are only due to anthropogenic processes. The environmental carbon fluxes were subsequently derived by taking the difference in vegetation carbon stocks between the transient and fixed experiments. All spatially explicit variables are on a geographical latitude-longitude grid with a resolution of 0.25°.
DOI: 10.26165/juelich-data/iho9np
title: Archive of 0D simulations of the CO2 vibrational kinetics

description: Archive of the results of 0D simulations of the CO2 vibrational kinetics for conditions which mimic those behind shock fronts and in gas discharges. Only CO2 molecules, two-modes approximation [V Kotov, Plasma Sources Sci. Technol, vol. 30 (2021) 055003]
DOI: 10.6084/m9.figshare.20367496
title: master_SIN_lab infection prevalence.xlsx from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367499
title: Figure 2 code.R from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367502
title: master_SIN_microscopic evaluations.xlsx from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367505
title: Figure 4 code.R from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367508
title: master_SIN_lab spore counts.xlsx from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367505.v1
title: Figure 4 code.R from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367508.v1
title: master_SIN_lab spore counts.xlsx from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367511
title: Figure 3 code.R from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367511.v1
title: Figure 3 code.R from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367514
title: master_SIN_field density and prevalence.xlsx from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.6084/m9.figshare.20367514.v1
title: master_SIN_field density and prevalence.xlsx from Timescale reverses the relationship between host density and infection risk

description: Host density shapes infection risk through two opposing phenomena. First, when infective stages are subdivided among multiple hosts, greater host densities decrease infection risk through ‘safety in numbers’. Hosts, however, represent resources for parasites, and greater host availability also fuels parasite reproduction. Hence, host density increases infection risk through ‘density-dependent transmission’. Theory proposes that these phenomena are not disparate outcomes but occur over different timescales. That is, higher host densities may reduce short-term infection risk, but because they support parasite reproduction, may increase long-term risk. We tested this theory in a zooplankton-disease system with laboratory experiments and field observations. Supporting theory, we found that negative density–risk relationships (safety in numbers) sometimes emerged over short timescales, but these relationships reversed to ‘density-dependent transmission’ within two generations. By allowing parasite numerical responses to play out, time can shift the consequences of host density, from reduced immediate risk to amplified future risk.
DOI: 10.5281/zenodo.6913071
title: Estimates of soil nutrient limitation on the CO2 fertilization effect for tropical vegetation

description: Data for CO2 fertilization experiments and CMIP6 model simulations used in publication: "Estimates of soil nutrient limitation on the CO2 fertilization effect for tropical vegetation"
DOI: 10.5281/zenodo.6913070
title: Estimates of soil nutrient limitation on the CO2 fertilization effect for tropical vegetation

description: Data for CO2 fertilization experiments and CMIP6 model simulations used in publication: "Estimates of soil nutrient limitation on the CO2 fertilization effect for tropical vegetation"
DOI: 10.6084/m9.figshare.20325438
title: Dierickxetal-Supplementary-tables.xlsx from Peptide mass fingerprinting of preserved collagen in archaeological fish bones for the identification of flatfish in European waters

description: xlsx file containing 11 tables with additional data: sequences of the 8 peptide biomarkers per species; details of all archaeological samples analysed; comparisons between osteological studies and ZooMS
DOI: 10.6084/m9.figshare.20325438.v2
title: Dierickxetal-Supplementary-tables.xlsx from Peptide mass fingerprinting of preserved collagen in archaeological fish bones for the identification of flatfish in European waters

description: xlsx file containing 11 tables with additional data: sequences of the 8 peptide biomarkers per species; details of all archaeological samples analysed; comparisons between osteological studies and ZooMS
DOI: 10.6084/m9.figshare.20325438.v1
title: Dierickxetal-Supplementary-tables.xlsx from Peptide mass fingerprinting of preserved collagen in archaeological fish bones for the identification of flatfish in European waters

description: xlsx file containing 11 tables with additional data: sequences of the 8 peptide biomarkers per species; details of all archaeological samples analysed; comparisons between osteological studies and ZooMS
DOI: 10.34740/kaggle/dsv/3992330
title: 1234567890
DOI: 10.5281/zenodo.3751335
title: Wireshark captures of a residential WLAN testbed

description: This dataset contains the Wireshark captures obtained from the WLAN testbed used in the magazine paper entitled "Usage of Network Simulators in Machine-Learning-Assisted 5G/6G Networks". More details regarding the experimental setup can be found at https://github.com/fwilhelmi/usage_of_simulators_in_future_networks.
DOI: 10.5281/zenodo.3751334
title: Wireshark captures of a residential WLAN testbed

description: This dataset contains the Wireshark captures obtained from the WLAN testbed used in the magazine paper entitled "Usage of Network Simulators in Machine-Learning-Assisted 5G/6G Networks". More details regarding the experimental setup can be found at https://github.com/fwilhelmi/usage_of_simulators_in_future_networks.
DOI: 10.34740/kaggle/dsv/3992360
title: 1234567890
DOI: 10.26180/20381580
title: Neogi_Singh_2022

description: Data and codes for the paper: <br> Neogi, S. & Singh, M.S. (2022). Understanding changes in the tropical circulation under global warming using a cloud resolving model and a conceptual model. J. Climate, in press, doi:10.1175/JCLI-D-21-0854.1.
DOI: 10.26180/20381580.v2
title: Neogi_Singh_2022

description: Data and codes for the paper: <br> Neogi, S. & Singh, M.S. (2022). Understanding changes in the tropical circulation under global warming using a cloud resolving model and a conceptual model. J. Climate, in press, doi:10.1175/JCLI-D-21-0854.1.
DOI: 10.26180/20381580.v1
title: Neogi_Singh_2022.zip

description: Data and codes for the paper: <br> Neogi, S. & Singh, M.S. (2022). Understanding changes in the tropical circulation under global warming using a cloud resolving model and a conceptual model. J. Climate, in press, doi:10.1175/JCLI-D-21-0854.1.
DOI: 10.3886/e117662v1-124100
title: Data and Code for: Multidimensional Skills, Sorting, and Human Capital Accumulation

description: We construct a structural model of on-the-job search in which workersdiffer in skills along several dimensions and sort themselves intojobs with heterogeneous skill requirements along those same dimensions.Skills are accumulated when used, and depreciate when not used. Weestimate the model combining data from O{*}NET with the NLSY79. Weuse the model to shed light on the origins and costs of mismatch alongheterogeneous skill dimensions. We highlight the deficiencies of relyingon a unidimensional model of skill when decomposing the sources ofvariation in the value of lifetime output between initial conditionsand career shocks.
DOI: 10.5281/zenodo.6827093
title: Surrogate-modelling & machine learning dataset : finite element stress analysis of biaxial specimen with random elastic properties - 1000 samples

description: Dataset finite element stress analysis of biaxial specimen with random elastic properties Unzip and execute dataset.py to visualise data samples. PyVista is needed.
DOI: 10.5281/zenodo.6819575
title: Surrogate-modelling & machine learning dataset : finite element stress analysis of biaxial specimen with random elastic properties - 1000 samples

description: Dataset finite element stress analysis of biaxial specimen with random elastic properties Unzip and execute dataset.py to visualise data samples. PyVista is needed.
DOI: 10.5281/zenodo.6827035
title: Surrogate-modelling & machine learning dataset : finite element stress analysis of biaxial specimen with random elastic properties - 100 samples

description: Dataset finite element stress analysis of biaxial specimen with random elastic properties Unzip and execute dataset.py to visualise data samples. PyVista is needed