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1,271 results for “Data Flow”
tobac-flow Validation data
<p>Validation results for the detection of cores and anvils using the tobac-flow method</p> <p>Validation was performed over 297 days in 2018. Other days were excluded due to missing ABI or GLM data. Validation was performed over a subset of the GOES-16 CONUS scan region.</p>
Data from: Restriction site-associated DNA sequencing reveals local adaptation despite high levels of gene flow in Sardinella lemuru (Bleeker, 1853) along the northern coast of Mindanao, Philippines
<p>Stock identification and delineation are important in the management and conservation of marine resources. These were highlighted as priority research areas for Bali sardinella (<em>Sardinella lemuru</em>) which is among the most commercially important fishery resources in the Philippines. Previous studies have already assessed the stocks of <em>S. lemuru</em> between Northern Mindanao Region (NMR) and Northern Zamboanga Peninsula (NZP), yielding conflicting results. Phenotypic variation suggests distinct stocks between the two regions, while mitochondrial DNA did not detect evidence of genetic differentiation for this high gene flow species. This paper tested the hypothesis of regional structuring using genome-wide single nucleotide polymorphisms (SNPs) acquired through restriction-site associated DNA sequencing (RADseq). We examined patterns of population genomic structure using a full panel of 3,573 loci, which was then partitioned into a neutral panel of 3,348 loci and an outlier panel of 31 loci. Similar inferences were obtained from the full and neutral panels, which were contrary to the inferences from the outlier panel. While the full and neutral panels suggested a panmictic population (global F<sub>ST</sub> ~ 0, p > 0.05), the outlier panel revealed genetic differentiation between the two regions (global F<sub>ST</sub> = 0.161, p = 0.001; F<sub>CT</sub> = 0.263, p < 0.05). This indicated that while gene flow is apparent, selective forces due to environmental heterogeneity between the two regions play a role in maintaining adaptive variation. Annotation of the outlier loci returned five genes that were mostly involved in organismal development. Meanwhile, three unannotated loci had allele frequencies that correlated with sea surface temperature. Overall, our results provided support for local adaptation despite high levels of gene flow in <em>S. lemuru</em>. Management therefore should not only focus on demographic parameters (e.g., stock size, catch volume), but also consider the preservation of adaptive variation.</p>
Experimental data on the effects of an azimuthal mean flow on the (thermo)acoustic modes in the annular electroacoustic feedback setup at TU Berlin
<p>Experimental data obtained in the presence of an azimuthal mean flow on the acoustic/thermoacoustic response in the annular electroacoustic feedback setup at TU Berlin. This dataset was used for the published article<br> S. C. Humbert, J. P. Moeck, A. Orchini, C. O. Paschereit, "Effect of an Azimuthal Mean Flow on the Structure and Stability of Thermoacoustic Modes in an Annular Combustor Model With Electroacoustic Feedback", J. Eng. Gas Turbines Power. June 2021, 143(6): 061026. Experimental data as well as Matlab scripts to use them are provided. Useful information is contained in "readme" files.</p>
Thermal demagnetization data of Risica et al. (Deposit-derived block-and-ash flows: the hazard posed by perched temporary tephra accumulations on volcanoes; 2018 Fuego disaster, Guatemala)
<p>Thermal demagnetization data (repository data) of Risica et al. "Deposit-derived block-and-ash flows: the hazard posed by perched temporary tephra accumulations on volcanoes; 2018 Fuego disaster, Guatemala".</p>
Scale dependent spatial structuring of mountain river large bed elements maximizes flow resistance - Data Revision
<p>Datasets and R code related to manuscript entitled, "Scale dependent spatial structuring of mountain river large bed elements maximizes flow resistance". See '0_READ_ME.rtf' file for additional description of available files.</p>
Data from: Inversion Invasions: when the genetic basis of local adaptation is concentrated within inversions in the face of gene flow
<p><span></span></p> <p>Across many species where inversions have been implicated in local adaptation, genomes often evolve to contain multiple, large inversions that arise early in divergence. Why this occurs has yet to be resolved. To address this gap, we built forward-time simulations in which inversions have flexible characteristics and can invade a metapopulation undergoing spatially divergent selection for a highly polygenic trait. In our simulations, inversions typically arose early in divergence, captured standing genetic variation upon mutation, and then accumulated many small-effect loci over time. Under special conditions, inversions could also arise late in adaptation and capture locally adapted alleles. Polygenic inversions behaved similarly to a single supergene of large effect and were detectable by genome scans. Our results show that characteristics of adaptive inversions found in empirical studies (e.g., multiple large, old inversions that are FST outliers, sometimes overlapping with other inversions) are consistent with a highly polygenic architecture, and inversions do not need to contain any large-effect genes to play an important role in local adaptation. By combining a population and quantitative genetic framework, our results give a deeper understanding of the specific conditions needed for inversions to be involved in adaptation when the genetic architecture is polygenic.</p>
Source data belonged to "Geometric flow control in lateral flow assays: Macroscopic single-phase modeling"
<p>This record contains all the necessary data to obtain the results of the study "Geometric flow control in lateral flow assays: Macroscopic single-phase modeling" (<a href="https://doi.org/10.1063/5.0093316">https://doi.org/10.1063/5.0093316</a>).</p>
Data collection for article "Quantifying Local Ecosystem Service Outcomes by Modelling Their Supply, Demand and Flow in Myanmar's Forest Frontier Landscape"
<p>This dataset contains the nine ecosystem service models (in .neta format) underlying the publication "Quantifying Local Ecosystem Service Outcomes by Modelling Their Supply, Demand and Flow in Myanmar’s Forest Frontier Landscape". The ecosystem models were implemented using the commercial software Netica (version 6.05) for constructing and analysing Bayesian Networks.</p>
Intermediate data files from the compilation of Economy-wide Material Flow Accounts for the Domestic Extraction of abiotic materials
<p>These files represent a selection of intermediary files from the compilation of material flow accounts on Domestic Extraction (DE) of abiotic materials. The main output of this compilation has been integrated in the UNEP IRP Global Material Flow Database (GMFD).</p> <p>These files include input files (e.g. IDs for data harmonization, or factors for data conversion), as well as output files (e.g. supplementary information, or detailed data accounts before aggregation and integration into the GMFD).</p> <p>Please note: These files are published exclusively for the purpose of making this information available to interested parties in a transparent and orderly fashion, in particular to other research projects who may have use for it. Therefore, these files are not associated with any publication and have not been adjusted or formatted with regard to any publications standards, i.e. they are uploaded exactly as they have been processed in the respective R Github repository of the underlying data compilation.</p> <p>The following description attempts to give a short overview of the respective types of files and their contents. For more detailed information on the data compilation, please refer to chapters 6, 8, and 10 in the <a href="https://resourcepanel.org/sites/default/files/irp_technical_annex_global_material_flows_database.pdf">technical report</a> of the GMFD.</p> <p> </p> <p><strong>Main data output (i.e. detailed material flow accounts)</strong></p> <p><em>DE_met_min_fos_CCC_2021-11-04.csv</em>: Data aggregated to the official categories (CCC/TCCC) used for integration into the GMFD. With IDs, without names (e.g. for materials and countries).</p> <p><em>DE_met_min_fos_CCC_with_names_2021-11-04.csv</em>: Same as above, but with names.</p> <p><em>DE_met_min_fos_Detailed_2021-11-04.csv</em>: Detailed accounts, as compiled, before final aggregation. With IDs, without names.</p> <p><em>DE_met_min_fos_Detailed_with_names_2021-11-04.csv</em>: Same as above, but with names.</p> <p> </p> <p><em>DE_met_min_fos_Detailed_2022-05-24.csv: </em>Slightly revised version from May 2022. But not included in current GMFD version.</p> <p> </p> <p><strong>ID and concordance tables</strong></p> <p><em>ccc_vs_mat_ids.csv:</em> Concordance table for allocation of detailed material accounts to aggregated CCC accounts.</p> <p><em>country_ids.csv:</em> General ID table for country IDs and names</p> <p><em>estimated_ids.csv:</em> Material IDs which are assigned during application of ore estimation factors.</p> <p><em>geo_exist.csv:</em> Table for consistent geographic adjustment of data for specific countries which have disintegrated over time (not including regions like Germany, Yemen, Ethiopia, Sudan, which all have been dealt with individually if necessary).</p> <p><em>material_ids.csv:</em> General ID table for material IDs and names.</p> <p><em>source_country_ids.csv:</em> Concordance table for country IDs (i.e. for allocation of harmonized IDs to source namings/IDs)</p> <p><em>source_material_ids.csv:</em> Concordance table for material IDs (i.e. for allocation of harmonized IDs to source namings/IDs)</p> <p><em>source_unit_ids.csv:</em> Concordance table for unit IDs (i.e. for allocation of harmonized IDs to source namings/IDs)</p> <p><em>unit_ids.csv:</em> General ID table for unit IDs and names.</p> <p> </p> <p><strong>Conversion factors</strong></p> <p><em>conversion_elements.csv:</em> Factors applied for conversion from metal compounds to elemental metals.</p> <p><em>conversion_factors_units.csv:</em> Factors applied for unit conversions.</p> <p> </p> <p><strong>Ore estimation factors</strong></p> <ul> <li>These factors represent content-to-ore ratios (i.e. "tonnes of extracted ore/mineral per ton of produced content”).</li> </ul> <p><em>all_integrated_est_fac_2021-11-04.csv:</em> Factors for estimation of metal and mineral ores (all which have been compiled/integrated)</p> <p><em>applied_est_fac_2021-11-04.csv:</em> Factors for estimation of metal and mineral ores (which have actually been applied)</p> <p><em>average_metal_prices_1990-2020.csv:</em> Metal prices applied in the compilation of estimation ratios.</p> <p><em>raw_metal_to_ore_ratios_fineprint.csv:</em> Raw metal-to-ore ratios derived from FINEPRINT mining data.</p> <p><em>raw_metal_to_ore_ratios_snl.csv:</em> Raw metal-to-ore ratios derived from SNL mining data.</p> <p> </p> <p><strong>Intermediate files from data processing</strong></p> <p><em>all_interm_conv_integr_2021-12-13.csv:</em> Harmonized, converted (units & elemental metals), integrated (i.e. without double counting). Before any estimations (ores & construction minerals) and before final cleaning/formatting.</p> <p><em>wmd_bgs_usgs_interm_harmonized_2021-12-13.csv:</em> All harmonized raw data from WMD/BGS/USGS, before any further processing (i.e. with double counting).</p> <p> </p> <p><strong>Comparison data (for mining accounts from FINEPRINT project)</strong></p> <p><em>data_for_comparison_2022-05-24.csv:</em> Data set specifically compiled for comparison with accounts on production of mines from the FINEPRINT project. Has been applied for verification of data published in <em>"Jasansky et al. (2022) An open database on global coal and metal mining"</em>.</p> <ul> <li>Includes all available types of materials which have been reported (e.g. ores and metals and metal compounds) <ul> <li>meaning: also materials which are associated with each other, for example iron ore and iron (and would therefore have been selectively integrated/excluded in the GMFD compilation).</li> </ul> </li> <li>Excludes any double counting for the exact same material from different data sources</li> <li>Harmonized IDs, converted units</li> <li>Includes metal compounds approximated/converted from reported elemental metals (where possible)</li> </ul> <p> </p> <p><strong>materialflows.net</strong></p> <p><em>data_sunburst_material_profiles_20220607.csv:</em> Full detail of data underlying the Sunburst visualization "Global Domestic Extraction in 2019, by material group" in section "Raw Material Profiles" on materialsflow.net. However, for all available years. Includes data on Domestic Extraction of biomass. Includes detail for CCC, MFA13+, MFA4+</p> <p> </p> <p><strong>Outliers</strong></p> <p><em>overview_adjusted_outliers_2021-12-22.csv:</em> Overview of outliers which were adjusted during final formatting.</p> <p> </p> <p><strong>Other</strong></p> <p><em>approximation_tailings_detailed_2021-09-26.csv:</em> Estimation of tailings based on reported amounts of ores/minerals and their respective contents.</p> <p> </p>
Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr
<p>This dataset was used in the CenSierraPywr model created for the project "Optimizing Hydropower Operations While Sustaining Ecosystem Functions in a Changing Climate", for the California Energy Commission. Specifically, this data is to support reproducibility of the article describing the basic methods (Rheinheimer et al., in review). The model was built in Pywr, an open-source, linear programming-based Python package for modeling basin-scale water systems in the Central Sierra Nevada, California. Here, we focus on the Stanislaus and Upper San Joaquin River basins as they have high elevation hydropower typically operated to maximize revenue. CenSierraPywr consists of daily water allocations that include both hydroeconomic drivers for hydropower and more advanced environmental flows. Piecewise linear electricity prices from simulated hourly price data are used to drive discretionary hydropower, while environmental flows include the addition of ramping rates. Hydrological inputs include runoff data at the sub-basin level, based on the historical (1950 to 2011) daily gridded (1/16 degree) runoff data generated by the Variable Infiltration Capacity (VIC) hydrologic model developed by Livneh et al. (2013), forced with observed meteorological data and bias-corrected using local gauge data. All data inputs for reproducibility of CenSierraPywr for the Stanislaus and Upper San Joaquin Rivers are included, including original and preprocessed electricity and hydrological data and management-related data specific to certain hydropower projects or facilities.</p>
The thermal state of Volgo–Uralia from Bayesian inversion of surface heat flow and temperature [data set]
<p>This collection contains the dataset and the code which were used to find the thermal parameters’ lateral variations of the Volgo–Uralian subcraton through the Bayesian Markov Chain Monte Carlo (MCMC) statistical approach. The code originally was given in the analogous study of Antarctica's geothermal structure by Lösing et al. (2020) and it can be found in https://github.com/MareenLoesing/GHF-Antarctica-Bayesian. The main changes to the code of Lösing et al. (2020) are listed in the section 2 of the readme file.</p> <p>For an official use of the Bayesian inversion code please also cite: Lösing, M., Ebbing, J. & Szwillus, W. (2020) Geothermal Heat Flux in Antarctica: Assessing Models and Observations by Bayesian Inversion. Front. Earth Sci., 8, 105. doi:10.3389/feart.2020.00105</p> <p>The lateral variations of the thermal parameters for the single-layer and multi-layer crust are saved in “GHF_Volgo-Uralia_Single-layer.csv” and “GHF_Volgo-Uralia_Multi-layer.csv” respectively.</p>
Data collection for article "Regional scale mapping of ecosystem services supply, demand, flow and mismatches in Southern Myanmar"
<p>This dataset contains supply, demand, and flow maps from nine ecosystem service models (as layer files in .tif format) underlying the publication "Regional scale mapping of ecosystem services supply, demand, flow and mismatches in Southern Myanmar". </p>
Data on elevation of Heixiluo gully after a debris flow event
<p>The data is the elevation of gully after the debris flow in the Heixiluo, which is used in the paper submitted to Geophysical Research Letters (Modeling Progressive Erosion of Consolidated Landslide Dams by Debris Flows, [Paper # 2022GL101764]). </p>
Supplementary data for: Comparison of optical flow derivation techniques for retrieving tropospheric winds from satellite image sequences
<p>This study introduces a validation technique for quantitative comparison of algorithms which retrieve winds from passive detection of cloud- and water vapor-drift motions, also known as Atmospheric Motion Vectors (AMVs). The technique leverages airborne wind-profiling lidar data collected in tandem with 1-min refresh rate geostationary satellite imagery. AMVs derived with different approaches are used with accompanying numerical weather prediction model data to estimate the full profiles of lidar-sampled winds which enables ranking of feature tracking, quality control, and height-assignment accuracy and encourages meso-scale, multi-layer, multi-band wind retrieval solutions. The technique is used to compare the performance of two brightness motion, or "optical flow," retrieval algorithms used within AMVs, 1) Patch Matching (PM; used within operational AMVs) and 2) an advanced Variational Optical Flow (VOF) method enabled for most atmospheric motions by new-generation imagers. The VOF AMVs produce more accurate wind retrievals than the PM method within the benchmark in all imager bands explored. It is further shown that image regions with low texture and multi-layer-cloud scenes in visible and infrared bands are tracked significantly better with the VOF approach, implying VOF produces representative AMVs where PM typically breaks down. It is also demonstrated that VOF AMVs have reduced accuracy where the brightness texture does not advect with the mean wind (e.g. gravity waves), where the image temporal noise exceeds the natural variability, and when the height-assignment is poor. Finally, it is found that VOF AMVs have improved performance when using fine-temporal refresh rate imagery, such as 1-min versus 10-min data.</p>
Supplementary data: Modelling of future changes in seasonal snowpack and impacts on summer low flows in Alpine catchments
<p>The files in this record represent supplementary data for the article titled “Modelling of future changes in seasonal snowpack and impacts on summer low flows in Alpine catchments” in Water Resources Research. The files contain simulations of the HBV rainfall-runoff model for 14 alpine catchments in Switzerland. The model simulated different water balance components (such as runoff, snow water equivalent and evapotranspiration) for the reference period 1980-2009 and the three scenario periods (2020-2049, 2045-2074 and 2070-2099) using the A1B emission scenario.</p>
Laboratory data - physical modelling of gravel bed rivers under unsteady flow conditions
<p>Sediment transport and topography data from laboratory experiments under unsteady flow conditions.</p> <p>Data supporting the manuscript:<br> Redolfi, M., Bertoldi, W., Tubino, M., & Welber, M. (2018). Bed load variability and morphology of gravel bed rivers<br> subject to unsteady flow: A laboratory investigation. Water Resources Research, 54, 842–862. https://doi.org/<br> 10.1002/2017WR021143<br> Details about the physical model and the experimental procedure can be found in the paper.</p>
Research data supporting "Platinum Nanocatalyst Amplification: Redefining the Gold Standard for Lateral Flow Immunoassays with Ultra-Broad Dynamic Range"
<p>Research data supporting the publication: Loynachan C. N., et al., 2017, ACS Nano, DOI: http://dx.doi.org/10.1021/acsnano.7b06229.</p>
Data for: Quantifying Bankfull Flow Width Using Preserved Bar Clinoforms from Fluvial Strata
<p>Reconstruction of active channel geometry from fluvial strata is critical to constrain the water and sediment fluxes in ancient terrestrial landscapes. Robust methods—grounded in extensive field observations, numerical simulations, and physical experiments—exist for estimating the bankfull flow depth and channel-bed slope from preserved deposits; however, we lack similar tools to quantify bankfull channel widths. We combined high-resolution lidar data from 134 meander bends across 11 rivers that span over two orders of magnitude in size to develop a robust, empirical relation between the bankfull channel width and channel-bar clinoform width (relict stratigraphic surfaces of bank-attached channel bars). We parameterized the bar cross-sectional shape using a two-parameter sigmoid, defining bar width as the cross-stream distance between 95% of the asymptotes of the fit sigmoid. We combined this objective definition of the bar width with Bayesian linear regression analysis to show that the measured bankfull flow width is 2.34 ± 0.13 times the channel-bar width. We validated our model using field measurements of channel-bar and bankfull flow widths of meandering rivers that span all climate zones (R2 = 0.79) and concurrent measurements of channel-bar clinoform width and mud-plug width in fluvial strata (R2 = 0.80). We also show that the transverse bed slopes of bars are inversely correlated with bend curvature, consistent with theory. Results provide a simple, usable metric to derive paleochannel width from preserved bar clinoforms.</p>
Chemical and electromagnetic parameters of NOx-rich gas flow under the influence of multi-frequency electromagnetic field (numerical data)
<p>Metastable and non-stable states lifetime dependence on the exciting electromagnetic field parameters for the quantum series of the main ground state – dissociation consequence.</p> <p>Overtones and main frequencies spectrum and probabilities for NO molecule resonance excitation.</p>
A novel flow chamber for biodegradable alloy assessment in physiologically realistic environments: Supporting Data
<p>Experimental data including Excel analysis and microscopy supporting the publication 'A novel flow chamber for biodegradable alloy assessment in physiologically realistic environments' <a href="https://doi.org/10.1063/1.4821498" target="_blank" rel="noopener">https://doi.org/10.1063/1.4821498</a></p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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