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1,572 results for “Sedimentation”
Tectonic and magmatic evolution of NE Cathaysia Block controls sediment geochemical heterogeneity of rivers in SE China
<p>The supplementary data of the manuscript: <strong>Tectonic and magmatic evolution of NE Cathaysia Block controls sediment geochemical heterogeneity of rivers in SE China</strong></p>
Raw data on water, submerged plants, benthic cyanobacteria, and sediments in ecological experiments
<p>This study aimed to determine the effects of nitrogen (N) and phosphorus (P) on the growth of submerged macrophytes (<em>Vallisneria natans</em>) and benthic cyanobacteria (<em>Leptolyngbya</em> sp.), and analyze the redistribution of N and P in the water and sediments under nutrient loading. We detected a total of nine experimental gradients (two replicates), totaling 18 treatment groups at 0, 5, 10, 15, 20, 30, 40, and 50 d. The final resulting raw data include the concentrations of physicochemical factors (the pH, dissolved oxygen (DO), redox potential (Eh), electrical conductivity (EC), total phosphorus (TP), and total nitrogen (TN)) in the water, chlorophyll a (Chl-a) in the water, <em>V. natans</em>, and Leptolyngbya sp. biofilms. The dry weight (DW), plant height and ramet numbers of <em>V. natans</em>, and the TP amount in <em>V. natans</em> and sediments were also measured.</p>
Woerthersee sediment core data for the publication "Validation of seismic hazard curves using a calibrated 14 ka lacustrine record in the Eastern Alps, Austria"
<p>This dataset comprises sediment core data of Wörthersee, a lake in the Eastern European Alps, Austria. Together with a dataset comprising the seismic data (10.5281/zenodo.6479186), this is the basis for the publication Daxer et al. "Validation of seismic hazard curves using a calibrated 14 ka lacustrine record in the Eastern Alps, Austria".</p> <p>The files contain the following data:</p> <ul> <li>Core images Long Cores.zip: Core images of the Wörthersee Kullenberg-type long cores acquired with an ITRAX core scanner</li> <li>Core images Short Cores.zip: Core images of the Wörthersee gravity short cores (hammer-coring or trigger cores of the Kullenberg system) acquired with an ITRAX core scanner; provided as .tif files</li> <li>CT data WOER18-L5-X-Dicom.zip: X-ray computed tomography data acquired with a Siemens SOMATOM Definition AS (voxel size 0.2 x 0.2 x 0.3 mm); provided in DICOM format</li> <li>MSCL data.zip: Data acquired with a Geotek Multi-sensor core logger (e.g. magnetic susceptibility and gamma density); provided as Excel spreadsheets</li> <li>XRF data.zip: X-ray fluorescence data acquired with a ITRAX core scanner; provided in .csv format</li> </ul>
Doodleverse/Segmentation Zoo Res-UNet models for 4-class (water, whitewater, sediment and other) segmentation of Sentinel-2 and Landsat-7/8 7-band (RGB+NIR+SWIR+NDWI+MNDWI) images of coasts.
<p>Doodleverse/Segmentation Zoo Res-UNet models for 4-class (water, whitewater, sediment and other) segmentation of Sentinel-2 and Landsat-7/8 7-band (RGB+NIR+SWIR+NDWI+MNDWI) images of coasts.</p> <p>Models have been created using Segmentation Gym* using the following dataset**: https://doi.org/10.5281/zenodo.7344571</p> <p>Classes: {0=water, 1=whitewater, 2=sediment, 3=other}</p> <p>File descriptions</p> <p>For each model, there are 5 files with the same root name:</p> <p>1. '.json' config file: this is the file that was used by Segmentation Gym* to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse.</p> <p>2. '.h5' weights file: this is the file that was created by the Segmentation Gym* function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym* function `seg_images_in_folder.py`. Models may be ensembled.</p> <p>3. '_modelcard.json' model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model</p> <p>4. '_model_history.npz' model training history file: this numpy archive file contains numpy arrays describing the training and validation losses and metrics. It is created by the Segmentation Gym function `train_model.py`</p> <p>5. '.png' model training loss and mean IoU plot: this png file contains plots of training and validation losses and mean IoU scores during model training. A subset of data inside the .npz file. It is created by the Segmentation Gym function `train_model.py`</p> <p>Additionally, BEST_MODEL.txt contains the name of the model with the best validation loss and mean IoU</p> <p><br> References</p> <p>*Segmentation Gym: Buscombe, D., & Goldstein, E. B. (2022). A reproducible and reusable pipeline for segmentation of geoscientific imagery. Earth and Space Science, 9, e2022EA002332. https://doi.org/10.1029/2022EA002332 See: https://github.com/Doodleverse/segmentation_gym</p> <p>** Buscombe, Daniel. (2022). Images and 4-class labels for semantic segmentation of Sentinel-2 and Landsat RGB, NIR, and SWIR satellite images of coasts (water, whitewater, sediment, other) (v1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7344571</p> <p> </p>
Major and trace element composition of IODP Site U1429 and Yellow River sediments and simulated rainfall changes in East-Southeast Asia during past 300 ka
<p>This dataset includes major and trace element composition of IODP Site U1429 and Yellow River surface sediments. They are all analyzed based on the clay-sized fractions. It also includes the data of simulated rainfall changes in the northern and southern China, as well as in Southeast Asia during past 300 ka.</p>
Sr-Nd isotopic fingerprints of Red River sediments and its implication for provenance discrimination in the South China Sea
<p>Supplementary Data of the Manuscript titled 'Revisit Sr-Nd isotopic fingerprints of Red River sediments and its implication for provenance discrimination in the South China Sea'</p> <p>Table A1. elemental compositions of Red River estuarine sediment samples</p> <p>Table A2. Literature data on sediment Sr-Nd isotopic ratios, Rb/Sr and K<sub>2</sub>O/(Na<sub>2</sub>O+CaO) in the Red River catchment</p> <p>Table A3. Compiled data on Sr-Nd isotopic compositions of rocks in the Thao River, Song Da and Song Lo basin</p> <p>Table A4. Compiled data of sediment Sr-Nd isotopic composition in the Pearl River, Red River and Mekong River</p>
Biogeochemical data of sinking particulate matter collected by sediment traps at E2M3A mooring (2013-2020) in the Southern Adriatic Sea
<p>The dataset presented (NetCDF format), includes sediment trap derived fluxes (total mass, POC, CaCO<sub>3</sub>, bSiO<sub>2</sub>) at ~1200 m depth from the E2M3A deep-sea mooring in the center of the Southern Adriatic Sea in the period from December 2013 to September 2020. The E2M3A observatory is positioned in the centre of the cyclonic gyre where deep convection process takes place, involving both the atmosphere and the ocean dynamics and forming new dense and oxygenated waters, thus triggering the biological pump. The E2M3A mooring is included in the southern Adriatic regional facilities of EMSO-ERIC consortium managed from OGS Trieste and CNR-ISP. Sediment traps, positioned at two levels (below the photic layer at -120m and near the bottom at -1050m), allow the understanding of the processes responsible for the high-frequency and interannual variability of new production and of phytoplankton biomass. Total mass fluxes (TMF) measured at the shallower trap were generally lower that those measured at the bottom trap, ranging from 16 to 706 mg m<sup>-2</sup> d<sup>-1</sup>, with a time-weighted average of 133 mg m<sup>-2</sup> d<sup>-1</sup>, whereas at the bottom trap TMF varied from 33 to 885 mg m<sup>-2</sup> d<sup>-1</sup>, with a time-weighted average of 190 mg m<sup>-2</sup> d<sup>-1</sup>. The organic carbon flux, followed the same seasonal trend, with higher values below the photic zone, varying from 1.7 to 31.9 mg m<sup>-2</sup> d<sup>-1</sup>, with a mean of 5.8 mg m<sup>-2</sup> d<sup>-1</sup> at the shallow trap.</p>
Pathways of methane removal in the sediment and water column of a seasonally anoxic eutrophic marine basin - dataset
<p>Dataset used in the article: "Pathways of methane removal in the sediment and water column of a seasonally anoxic eutrophic marine basin", Zygadlowska et al., 2023.</p>
Supplementary Dataset of Marine Metagenomes from Surface Sediments along the coastline of Kuwait
<p>This dataset was obtained through shot gun metagenomic sequencing conducted on surface sediments in close vicinity of emergency outfalls discharged through the storm outlets. It provides information on the diverse microbial communities and dominant metabolic functions occuring at these sites under a selective force of various contaminants brought in through the effluent discharges.</p>
Dataset for 'Effects of bubble plumes on lake dynamics, near-bottom turbulence, and transfer of dissolved oxygen at the sediment-water interface'
<p>The dataset associated with the article "Effects of bubble plumes on lake dynamics, near-bottom turbulence, and transfer of dissolved oxygen at the sediment-water interface". </p>
Planktonic foraminifera count, shell weight and size data from sediment traps in the Fram Strait, HAUSGARTEN observatory (TDLT 2014), 2014 - 2015
<p>Counts, shell weight and shell size data of planktonic foraminifera from two depths of the sediment Trap TDLT 2014 in the HAUSGARTEN observatory in the eastern Fram Strait. Comparison of the count data done in the context of this study with count data conducted after the initial retrieval of the trapped material indicate high deviation. It is likely that the samples were affected by dissolution during the storage between retrieval (2015) and analysis (2020/2021), therefore both counts and weight and size data might not be representative.<br> <br> This data is supplement to the dissertation from Tell (2023).</p>
Data for Intra-seasonal variability in sediment provenance and transport processes in the Brahmaputra basin
<p>No description provided.</p>
Data from: A study on the Influence of submergence ratio on the transportation of suspended sediment in a partially vegetated channel flow
<p><span>Riparian or aquatic vegetation thrives with seasons. The understanding of canopies' Submergence-Ratio SR (stems' height to water depth) influence on suspended sediments' transportation is still limited. Thus, Large Eddy Simulations (LES) coupled with the Discrete Phase Method (DPM) are used to investigate the particles' 3-dimensional distribution in a partially vegetated straight channel. The spanwise distribution of particles is quantified by the Probability Density Function (PDF), showing a non-uniformity of particles in time as quantified by the PDF variance. The findings and conclusions: (Ⅰ) With SR rising, the particles' depletion effects exerted by the vegetation-side mixing layer are improved along the interface between vegetated and vegetation-side bare channel region. However, the SR has little effect on the variance of the particles' PDF in the spanwise direction when the mixing layer is fully developed. (Ⅱ) During the developing stage of the over-canopy mixing layer, submerged vegetation with higher SR gain a stronger upwards (vertical) entrainment capability. </span><span>The case (SR=60%) has a higher sediment concentration than other cases in the fully developed vertical mixing layer region above canopy.</span><span> (III) </span><span>The vertical suspension of particles in the vegetation-side bare channel region is analysed. Particles migrating from the vegetated region are entrained into the vegetation-side bare channel region by turbulent structures. Nevertheless, the vertical concentration profile is more uniform in the vegetated region than in the vegetation-side bare channel at the same streamwise location. The cases SR=40% and 60% still have higher sediment concentrations than other cases in the vegetation-side bare channel's upper region.</span></p>
Geochronologic and Paleoenviromental data from pelagic sediments
<p>Geochronologic date including bulk sediments thorium isotopes and authigenic beryllium isotopes data for a pelagic sediment core from northwestern Pacific Ocean are presented in this dataset. Moreover, Nd isotopic compositions of the authigenic Fe–Mn oxyhydroxide fractions extracted from pelagic sediments, together with the redox-sensitive metal proxies (e. g., Mn/Al and Mn/Ti ratios) and grain sizes of bulk sediments fron this sediment core are also included in this dataset.</p>
Baseline concentrations, spatial distribution and origin of trace elements in marine surface sediments of the northern Antarctic Peninsula
<p>Supplementary data to article published in Marine Pollution Bulletin 187 (2023) 114501: https://doi.<br> org/10.1016/j.marpolbul.2022.114501</p>
Moving bedforms control CO2 production and distribution in sandy river sediments
<p>This dataset includes raw and processed data, as well as modeling codes that were used to produce the results presented in Schulz et al. (submitted) "Moving bedforms control CO<sub>2</sub> production and distribution in sandy river sediments" submitted to Journal of Geophysical Research: Biogeosciences.</p> <p> </p> <p>The dataset contains:</p> <p>1) Data for sediment characterization: Grain size distribution, hydraulic conductivity, loss on ignition, and porosity data.</p> <p>2) Data on hydrology and morphodynamics: Bedform celerity, height, and length, Damkoehler number, shear velocities, and Python codes for modeling the hyporheic exchange flux.</p> <p>3) Data compilation: Data of online sensors that continuously measured various parameters of the streamwater, atmospheric pressure, and CO<sub>2 </sub>air concentrations.</p> <p>4) Digital raw images of dye tracer experiments.</p> <p>5-10) Image data: Raw and processed planar optode and IR images, spreadsheets containing data analysis results.</p>
Mg and Fe isotopes and other geochemical data for Gangdese arc mafic plutonic rocks and trench sediments
<p>These files content unpublished Mg and Fe isotopes and other geochemical data for the Gangdese arc mafic plutonic rocks and trench sediments.</p>
Data from: Detection of vertebrates from natural and artificial inland water bodies in a semi-arid habitat using eDNA from filtered, swept and sediment samples
<p>Climate warming will impact the sustainability of arid and semi-arid zone environments so we need to understand the influence of changes in arid lands on vertebrate populations. However, biomonitoring and biodiversity assessment in arid environments can be prohibitively time-consuming, expensive, and logistically challenging due to their often remote and inhospitable nature. Sampling of environmental DNA (eDNA) coupled with high-throughput sequencing is an emerging biodiversity assessment method. Here we explore the application of eDNA metabarcoding and various sampling approaches to estimate vertebrate richness and assemblage at human-constructed and natural water sources in a semi-arid region of Western Australia. Three sampling methods: sediment samples, filtering through a membrane with a pump, and membrane sweeping in the water body, were compared using two eDNA metabarcoding assays, 12S-V5 and 16smam, for 120 eDNA samples collected from four gnammas (gnamma: Australian Indigenous Noongar language term – granite rock pools) and four cattle troughs in the Great Western Woodlands, Western Australia. We detected higher vertebrate richness in samples from cattle troughs and found differences between assemblages detected in gnammas (more birds and amphibians) and cattle troughs (more mammals, including feral taxa). Total vertebrate richness was not different between swept and filtered samples, but all sampling methods yielded different assemblages. Our findings indicate that eDNA surveys in arid lands will benefit from collecting multiple samples at multiple water sources to avoid underestimating vertebrate richness. The high concentration of eDNA in small, isolated water bodies permits the use of sweep sampling which simplifies sample collection, processing, and storage, particularly when assessing vertebrate biodiversity across large spatial scales.</p>
Rheology of mobile sediment beds in laminar shear flow: effects of creep and polydispersity
<p>Simulation data to accompany the journal article "Rheology of mobile sediment beds in laminar shear flow: effects of creep and polydispersity" by Rettinger et al. (2022) in Journal of Fluid Mechanics.</p> <p>The data set features the four simulation setups with varying degrees of polydispersity, denoted as mono, poly10, poly50, and poly100.</p> <p>Each setup has two subfolders: 'particle' and 'fluid'.</p> <p>The 'particle' folder contains files with particle-related quantities. The name of the file indicates the simulation time step. Each file contains seven columns of data: the x-, y-, and z-coordinate of the particle's center of mass, followed by its radius and the three translational velocity components <strong>u</strong><sub>p</sub> = (u<sub>x</sub>, u<sub>y</sub>, u<sub>z</sub>). Each row thus contains the instantaneous properties of a single particle. Additionally, the row-ordering between time steps remains the same, i.e., the x-th row always denotes the same particle.</p> <p>The 'fluid' folder contains files with fluid-related quantities. Again, the name denotes the simulation time step. Each file contains three columns of data: the three velocity components <strong>u</strong><sub>f</sub> = (u<sub>x</sub>,u<sub>y</sub>,u<sub>z</sub>) of the horizontally averaged flow field. Each row corresponds to a particular vertical (z-) coordinate, denoting the height above the bottom plane. This coordinate is given in the additional file 'height.txt'.</p> <p>All data is given in simulation units where the lattice Boltzmann unit system is used.</p> <p> </p> <p>Updated version 1:</p> <ul> <li>Added a jupyter notebook (in python) that exemplifies how vertical profiles, e.g., of solid volume fraction and fluid velocity, can be extracted from the provided data.</li> <li>Fix in fluid height profiles (height.txt).</li> </ul> <p>Updated version 2:</p> <ul> <li>Added missing last column (z-velocity) to the particle data.</li> <li>Maintained consistent ordering of entries in particle data throughout all time steps.</li> </ul>
Extreme Flood Sediment Production and Export Controlled by Reach-scale Morphology
<p>Output data resulting from the analysis of the morphological impact of the 30<sup>th</sup> July 2019 flood event on the catchments of Slei Gill, Grinton Beck and Barney Beck, located in Upper Swaledale, North Yorkshire, UK. The data comprise processed DEMs of Difference (DoDs) calculated from pre- and post-event topography, simulations of maximum water depth for each catchment derived from modelling within HEC-RAS v2.6.1, and point clouds of the post-event topography.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.