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38 results for “morphodynamics”
Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures
<p>To whom concerned,</p> <p>This dataset is the supplementary dataset for the publication in <em>Environmental Research Letters</em> entitled '<a href="https://dx.doi.org/10.1088/1748-9326/abc122"><em>Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures</em></a>' authored by Danghan Xie, et al. in 2020. The publication can be freely downloaded here: <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abc122">https://iopscience.iop.org/article/10.1088/1748-9326/abc122</a>. The dataset consists of both model results and corresponding codes that one can easily reproduce figures either in the manuscript or the supplementary document. </p> <p>To use the code, one needs to pre-install the Matlab (R2017a) and changes the pre-set route (in the code) to the directory where the dataset is stored. The figure shapes may vary with the size of the user's monitor so output figures may be either squeezed or extended in unpredictable ways, but the window size of the figure can be adjusted to match the shape and the results will not be affected.</p> <p>The author is appreciated that any potential concerns or questions regarding our research from any party or person, so please contact me through the email: <a href="mailto:d.xie@uu.nl">d.xie@uu.nl</a> or <a href="mailto:xiedanghan@gmail.com">xiedanghan@gmail.com</a>. To know more about my research, you can also follow the <a href="https://www.researchgate.net/profile/Danghan_Xie">ResearchGate</a>.</p> <p>With Kind Regards,</p> <p>Danghan</p> <p>11th of November, 2020</p>
Accompanying dataset for: "Flow and detailed 3D morphodynamic data from laboratory experiments of fluvial dike breaching"
<p>This dataset accompanies the manuscrpit "Flow and detailed 3D morphodynamic data from laboratory experiments of fluvial dike breaching" submitted to Scientific Data.</p>
Shape, membrane morphology, and morphodynamic response of metabolically active human mitochondria revealed by scanning ion conductance microscopy
<p>This contains the hole data set as well as all analysed data for the paper published in Beilstein Journal of Nanotechnology "Shape, membrane morphology and morphodynamic response of metabolically active human mitochondria revealed by Scanning Ion Conductance Microscopy".</p> <p>Most of the images were taken with the SICM. These uncompressed tiff files can be read and processed with the Gwyddion software or other scanning probe image processing software.</p>
Morphodynamic stability of river and tidal bifurcations around bars tested in the Fast Flow Facility
<p>Multithread rivers such as the Jamuna and Mekong have networks of channels and bars that change with every flood. Tidal systems such as the Scheldt, Humber and Columbia estuaries and short tidal basins in the Wadden Sea and in Florida, have perpetually changing and interacting channels and shoals formed by ebb and flood currents. Current models fail to forecast these natural dynamics, yet main channels are economically important shipping fairways, whilst shoal areas that emerge and submerge daily are ecologically valuable habitats. Human interference, changing river discharge and sealevel rise threaten all functions. Furthermore, there are strong indications that fairway deepening leads to reduced urban safety due to enhanced flow resistance by groynes in rivers and enhanced tidal range in estuaries (e.g. Bolla Pittaluga et al. 2015 in AWR, Seminara et al., in EH 2011). This enhances dike failure risk during low water level and flooding during high water level. We urgently need dynamic forecasting models to optimise management strategies for these multiple functions (Wang et al. 2012 in Ocean Coastal Manage., Coco et al. 2013 in Mar. Geol.).</p> <p>Here we target firstly river bifurcations and secondly the mutually evasive ebb- or flood-dominated channels that form around bars and are found in all sandy tidal systems in the world (van Veen 1950/2002 in J. R. Dutch Geograph. Soc.). The cause for the mutual evasion is still incompletely understood despite the fact that they also appear in our numerical model results and experiments (Canestrelli et al., in JGR 2010; Kleinhans et al. 2015 in JGR). The nodes where ebb and flood channels connect can be seen as asymmetric bifurcations where one channel is preferred during ebb and the other during flood. Such bifurcations are critical elements that partition flow and sediment through the channel network, govern bar merging and splitting and are locations where bed steps form in shipping lanes, as in river bifurcations. Stability and equilibrium configurations are mostly unknown for tidal bifurcations except for one recent theory (Wang et al in prep.). In particular, we have a fair understanding of the tidal dynamics, but this is incomplete for the morphodynamics, especially related to understanding the sediment division at the bifurcation.</p> <p>We take advantage of the better but yet incomplete understanding of river bifurcations. The stability of river bifurcations has been studied for two decades in fieldwork, experimentation, linear stability theory and numerical modelling (e.g. Wang et al. 1995, JHR, see review in Kleinhans et al. 2013, ESPL) and our recent theory (Bolla Pittaluga et al. 2015 in GRL) synthesises many of the earlier results as follows: In bedload-dominated rivers, symmetrical bifurcations are unstable and develop towards a highly asymmetrical division of discharge and sediment. The same is the case for suspended sediment-dominated rivers, but the theory predicts stable bifurcations for intermediate sediment mobility. However, there is very little data for conditions intermediate between low and high mobility rivers. Moreover, we have no idea whether bifurcations in reversing tidal flow are unstable for similar configurations and conditions as in rivers. Here we mean configurations that are entirely free of topographic forcings on the flow: straight channels split into two channels over some length and depth.</p> <p>Our objective was therefore to experimentally investigate bifurcation stability in a range of sediment mobilities in unidirectional flow and reversing tidal flow ceteris paribus.</p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 4 relative to Figure 7 – ArhGEF11 CRISPR interference
<p><span>Raw image files (TIFF format), corresponding 2D-cartographies (_2Dmap.tiff files) and metadata files for 2D-cartographies (.xml files, readable with the opensource software Icy), relative to <strong>Figure 7B </strong>and<strong> Figure 7 - Figure Supplement 6</strong> (see <strong>Materials and Methods — Morphological and morphometric analysis of aortic and hemogenic cells</strong>).</span></p> <p><span>The source data comprises for each 48 - 55 hpf <em>Tg(kdrl:eGFP-JAM3b; kdrl:nls-mKate2)</em> zebrafish embryo 3 z-stack and 2D cartographies (segments 1 to 3) encompassing the whole length of the aorta, for control condition (n = 2 individuals) and morpholino splicing interference condition (n = 2 individuals). For z-stacks of both control and morphant conditions, two fluorescence channels were acquired, corresponding to the nuclear mKate2 expressed in endothelial cells and the eGFP-JAMs signal localized at the intercellular junctions of endothelial cells. Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.3 µm. 2D-cartographies were obtained using the Icy plugin “TubeSkinner”, and the semi-manual segmentation of all aortic cells can be uploaded from the corresponding metadata file on the 2D-cartographies using the load ROI function of Icy.</span></p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 3 relative to Figure 7 – ArhGEF11 morpholino splicing interference
<p><span>Raw image files (TIFF format), corresponding 2D-cartographies (_2Dmap.tiff files) and metadata files for 2D-cartographies (.xml files, readable with the opensource software Icy), relative to <strong>Figure 7A </strong>and<strong> Figure 7 - Figure Supplement 5</strong> (see <strong>Materials and Methods — Morphological and morphometric analysis of aortic and hemogenic cells</strong>).</span></p> <p><span>The source data comprises for each 48 - 55 hpf <em>Tg(kdrl:eGFP-JAM2a; kdrl:nls-mKate2)</em> zebrafish embryo 3 z-stack and 2D cartographies (segments 1 to 3) encompassing the whole length of the aorta, for control condition (n = 2 individuals) and morpholino splicing interference condition (n = 3 individuals). For z-stacks of both control and morphant conditions, two fluorescence channels were acquired, corresponding to the nuclear mKate2 expressed in endothelial cells and the eGFP-JAMs signal localized at the intercellular junctions of endothelial cells. Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.3 µm. 2D-cartographies were obtained using the Icy plugin “TubeSkinner”, and the semi-manual segmentation of all aortic cells can be uploaded from the corresponding metadata file on the 2D-cartographies using the load ROI function of Icy.</span></p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 1 relative to Figure 3
<p><span>Raw image files (TIFF format) relative <strong>to Figure 3</strong> (see <strong>Materials and Methods — Dt-runx1 phenotype analysis – cell count</strong>).</span></p> <p><span>The source data comprises for each 52 - 55 hpf zebrafish embryo 3 z-stack (segments 1 to 3) encompassing the whole length of the aorta, for control condition (<em>Tg(Kdrl:Gal4;UAS:RFP), </em>n = 3 individuals) and mutant condition (<em>Tg(kdrl:Gal4;UAS:RFP;4xNR:dt-runx1-eGFP), </em>n = 7 individuals). For control condition, one fluorescence channel was acquired, corresponding to the cytoplasmic RFP expressed in endothelial cells. For mutant condition, two fluorescence channels were acquired, corresponding first to the cytoplasmic RFP expressed in endothelial cells using the same reporter as for the control condition, and second the cleaved cytoplasmic GFP reporting the expression of our dt-runx1 mutant construct in endothelial cells. Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.3 µm.</span></p>
Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 2 relative to Figure 4
<p><span>Raw image files (TIFF format) and segmented 3D images (.ims, Imaris proprietary files) relative to <strong>Figure 4</strong> and <strong>Figure 4 Figure Supplement 3</strong> (see <strong>Materials and Methods — RNAscope image analysis – Pard3</strong>).</span></p> <p><span>The source data comprises for each 52 - 55 hpf zebrafish embryos 2 z-stack (segments 1 to 2) encompassing the whole length of the aorta, for control condition (<em>Tg(Kdrl:eGFP), </em>n = 7 individuals) and mutant condition (<em>Tg(kdrl:Gal4; 4xNR:dt-runx1-eGFP), </em>n = 12 individuals). For both control and mutant conditions, two fluorescence channels are displayed, corresponding to the cytoplasmic GFP expressed in endothelial cells (in green) and the RNAscope signal (OPAL-570, in magenta). Z-stack were acquired using a confocal spinning disk microscope. Voxel size: x: 0.1635, y: 0.1635, z:0.4 µm. The .ims files contain the 3D rendering of the z-stacks as well as the segmentations of Pard3ba mRNA RNAscope spots (in magenta), in the aorta (Spots 1 Selection) or outside (Spots 1), as well as the segmentation of endothelial cells (green) (Cells 1) and hemogenic endothelial cells (Cells 1 Cell export).</span></p>
Fig. 3 in Fish assemblages along a morphodynamic continuum on three tropical beaches
Fig. 3. Variation in the mean number of individuals (CPUE average ±SE), biomass (±SE) and number of species (±SE) at Mamanguape River estuary in Brazil.
Fig. 1 in Fish assemblages along a morphodynamic continuum on three tropical beaches
Fig. 1. Map of Mamanguape River estuary with locations of the sampling sites: CPO, Curva do Pontal Beach; PON, Pontal Beach; and CAM, Campina Beach.
Coupled High Frequency Measurements of Swash Sediment Transport and Morphodynamic data set produced at the CIEM flume, Hydralab IV
<p>The data set here presented aims to increase the understanding of the nearshore sediment dynamics. The experiments aimed at obtaining high quality data of hydrodynamics, sediment concentration and beach-face evolution with an intra-wave time scale. The specific objectives of CoSSedM access project were i) to obtain information of the effect of the wave group periods on the beach morphological evolution; ii) To obtain detailed sediment transport information at the inner surf and swash zones with different bi-chromatic wave conditions and iii) To obtain intra-wave measurements of beach-face evolution.</p> <p>The present work was developed in the framework of the HYDRALAB IV Transnational Access projects. The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona. This is a wave flume 100 m long, 3 m wide, and 4.5 m deep. The working water depth was at around 2.5 m over the horizontal flume section and was varied slightly depending on the wave test. A beach was installed made of commercial well-sorted sand (d50 = 0.25 mm) with an overall mean beach gradient of approximately 1:15.</p> <p>Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.</p> <p>More information can be found on the published papers:</p> <p>Alsina, J.M., Padilla, E.M. and Cáceres, I., 2016. Sediment transport and beach profile evolution induced by bi-chromatic wave groups with different group periods. Coastal Engineering, Vol. 114, 325-340.</p> <p>Van der Zanden, J.; Alsina, J.; Caceres, I.; Buijsrogge, R. H.; Ribberink, J. , 2015. Bed level motions and sheet flow processes in the swash zone : observations with a new conductivity-based concentration measuring technique (CCM+) . Coastal Engineering, Vol. 105, 47-65.</p>
In-stream tidal energy resources in macrotidal non-cohesive sediment environments: effect of morphodynamic changes at two bays in the upper Gulf of California
<p>Project_info: This dataset was obtained during the project CeMIE-Oceano (2017-2021), and was party financed by SENER-CONACyT (contract no. 249795).<br> License: The authors appreciate that users of these data: 1) Contact Vanesa Magar (vmagar@cicese.edu.mx) to follow the uses of the data, and 2) Include the requested acknowledgment (cite using the DOI of this dataset) in any presentations or publications.</p> <p>This dataset includes data used for producing Figures 4,5 and Tables 1,2 of paper "IN-STREAM TIDAL ENERGY RESOURCES IN MACROTIDAL NON-COHESIVE SEDIMENT ENVIRONMENTS: EFFECT OF MORPHODYNAMIC CHANGES AT TWO BAYS IN THE UPPER GULF OF CALIFORNIA" published in<br> Journal of Marine Science and Engineering.</p> <p>Bermúdez-Romero, Anahí; Vanesa Magar; Markus S. Gross; Victor M. Godínez; Manuel López-Mariscal; Julio Candela. In-Stream tidal energy resources in macrotidal non-cohesive sediment environment: Effect ofmorphodynamic changes at two bays in the upper Gulf of California. Journal of Marine Science and Enginnering, 9:411. https://doi.org/10.3390/jmse9040411</p>
Morphodynamic atlas for Drosophila development
Open the record for dataset details and reuse information.
Data-driven quasiconformal morphodynamic flows
Open the record for dataset details and reuse information.
Dataset to "Fine-sediment erosion and ridge morphodynamics in coarse-grained immobile beds"
<p>The dataset is connected to the paper "Fine-sediment erosion and ridge morphodynamics in coarse-grained immobile beds".</p> <p>The dataset is subdivided in "topographic" and "PIV" data. Each dataset refers to an experiment presented in the paper.</p> <p>The filenames of the topographic data specify the location where the data were collected ("upstream" or "downstream"). The topographic data contain the bed elevations measured around each sphere over a measurement area as wide as the channel and covering nine patterns of spheres (see paper for a definition of the pattern of spheres). Each topographic dataset contains four structures:</p> <p>- A time vector "T" identifying the sampling times at which the bed topography was measured (unit: h)</p> <p>- A space vector "x" identifying the streamwise position of the spheres with the origin of the coordinate system positioned at the beginning of the measurement areas (upstream or downstream) - unit cm</p> <p>- A space vector "y" identifying the transverse position of the spheres with the coordinate system centred in the middle of the channel and positively oriented towards the left side of the flume looking in streamwise direction - unit cm</p> <p>- A matrix "Z" identifying the protrusion levels of the spheres (as defined in the paper) as a function of space and time (x times y times T) - unit cm</p> <p> </p> <p>The PIV data were acquired during experiments 1b and 5b at the upstream location. The data are a collection of the velocity fields measured above the top of the spheres and over two pattern of spheres in the middle "m" and in the quarter plane "q" of the channel for three different time instants (t1, t2, t3) during the experiments. Each dataset contains 6 variables:</p> <p>- the "sampling time" of the bursts - unit s</p> <p>- the "acquisition time" of the PIV run during the experiments - unit h</p> <p>- a vector "x" identifying the streamwise position of the velocity vectors for a coordinae system centred in the centre of the sphere and pointing in the longitudinal direction.</p> <p>- a vector "z" identifying the vertical direction of the coordinate system with the origin at the top of the sphere and pointing upwards - unit cm</p> <p>- a matrix "vx" containing 1000 fields of the streamwise velocity component - unit cm/s</p> <p>- a matrix "vz" containing 1000 fields of the vertical velocity component - unit cm/s</p>
Temporal morphodynamic evolution of the Glacier d'Otemma proglacial forefield for melt seasons 2020 and 2021: data collection and post-processing
<p><span>The data included in this dataset concern the continuous geomorphic (orthomosaics, DEMs, inundation maps) and sedimentological (grain-size maps) evolution of the Glacier d’Otemma proglacial margin (Southern-Western Swiss Alps) located at an altitude of ca. 2450 m a.s.l. during summer 2020 and 2021. </span></p> <p><span>Data details and formats are available in the pdf document. Further information on data aquisition and post-processing techniques are available in Mancini et al. (2024).</span></p>
April 7, 2024 (v1) Image Open Tuning apicobasal polarity and junctional recycling in the hemogenic endothelium orchestrates the morphodynamic complexity of emerging pre-hematopoietic stem cells —Source data 5 relative to Figure 7 - Figure Supplement 4
<p>Source data file relative to <strong><span>Figure 7 – figure supplement 4 Panel A</span></strong></p> <p><span>Raw image of agarose gel showing the 2 alternative mRNAs encoding for ArhGEF11 in control animals (left track, control) and after injection of the MO at the one cell stage (right track, +MO at 2 and 5ng). The source data includes the raw files (native format .scn and open source format .tiff) as well as a pdf file showing both the full scale image and the cropped image selected for the figure.<br></span></p>
The influence of waves on morphodynamic impacts of energy extraction at a tidal stream turbine site in the Pentland Firth: MIKE3 HD result files
<p>This dataset consists of the MIKE3 HD result files from simulations conducted for the paper 'The influence of waves on morphodynamic impacts of energy extraction at a tidal stream turbine site in the Pentland Firth' ( <a href="https://doi.org/10.1016/j.renene.2018.02.035">https://doi.org/10.1016/j.renene.2018.02.035</a> )</p> <p>Sets of 2D area result files are provided for sediment transport results (ST in file name), hydrodynamic results (HD in file name) and spectral wave results (SW in file name) in different datasets. This dataset contains HD files.</p> <p>Each file name provides details of the resuls contained: time of simulation (Jan or Jun); presence (Turb) or abscence (NoTurb) of tidal stream turbines in the simulations; and inclusion of waves in the simulations (tideAndWave or tide_only).</p> <p>Details of the methodology are given in the above paper. Please reference the paper in any use of these results.</p>
The dynamics of bi-directional exchange flows: implication for morphodynamic change within estuaries and sea straits
<p>Environmental and geophysical flows, including dense bottom gravity currents in the ocean and buoyancy-driven exchange flows in marginal seas,<br> are strongly controlled by topographic features.<br> These are known to exert significant influence on both internal mixing and secondary circulations generated by these flows.<br> In such cases, uni-directional or bi-directional exchange flows develop when horizontal density differences<br> and/or pressure gradients are present between adjacent water bodies connected by a submerged channel.<br> The flow dynamics of the dense lower layer depend primarily on the volumetric flux and channel cross-sectional shape,<br> while the stratified interfacial flow mixing characteristics, leading to fluid entrainment/detrainment,<br> are also dependent on the buoyancy flux and motion within the upper (lower density) water mass.<br> For submerged channels that are relatively wide compared to the internal Rossby radius of deformation,<br> Earth rotation effects introduce geostrophic adjustment of these internal fluid motions,<br> which can suppress turbulent mixing generated at the interface and result in the development of Ekman layers that induce secondary,<br> cross-channel circulations, even within straight channels.<br> Moreover, recent studies of dense, gravity currents generated in rotating and non-rotating systems,<br> respectively, indicated that the V-shaped channel topography had a strong influence on both flow distribution<br> and associated interfacial mixing characteristics along the channel.<br> However, such topographic controls on the interfacial mixing and secondary circulations generated by bi-directional exchange flows<br> are not yet fully understood and remain to be investigated thoroughly in the laboratory.<br> Also the effect of mobile bed for bi-directional exchange flows generated in deformable channels along with the physical interactions<br> between the lower dense water flow and the erodible bed sediments<br> will have a strong influence in (re-)shaping the overall channel bed topography (i.e. bed morphodynamics).<br> Consequently, the resulting temporal changes in cross-sectional channel bathymetry (i.e. through erosion and deposition processes)<br> would also be expected to have associated feedbacks on transverse asymmetries in the bi-directional exchange flow structure,<br> as well as on the internal flow stability.</p>
Wave-influenced Delta Morphodynamics, Long-term Sediment Bypass and Trapping Controlled by Relative Magnitudes of Riverine and Wave-driven Sediment Transport
<p>This repository contains supporting data for *Wave-influenced Delta Morphodynamics, Long-term Sediment Bypass and Trapping Controlled by Relative Magnitudes of Riverine and Wave-driven Sediment Transport,* submitted to Geophysical Research Letters.</p> <p>Delft3D Config for Q1000Qs100Hs15.docx → contains configuration file info for running the Delft3d simulation Q1000Qs100Hs15.</p> <p>Matlab 2022b was used to load Delft3D output files and process the data.</p> <p>WaveDelta_Depth&DepositThick.mat Contains:</p> <p>Depth → timesteps x 322 x 142. Timesteps are variable for each simulation.</p> <p>MSEDRiverSum → 4 x 322 x 142. Mass of sediments from riverine source at four intermediate timesteps. </p> <p>MSEDWaveSum → 4 x 322 x 142. Mass of sediments from longshore transport (LSTUp) source at four intermediate timesteps.</p> <p>VolRiverSum → 322 x 142. Final Volume of sediments from riverine source.</p> <p>VolWaveSum → 322 x 142. Final Volume of sediments from longshore transport (LSTUp) source.</p> <p>XCOR & YCOR are the X and Y grid coordinate locations for maps (322 x 142).</p> <p>Shift2&4km are used for cases highly skewed downdrift to correct for 0 location at the river mouth.</p> <p>Cerc_formula.mlx Computes CERC longshore transport for the simulation conditions.</p> <p>J.mlx calculates river mouth balance (J) values (Nienhuis et al. (2016)) presented in Figure S4. </p> <p>Additional 114 Figures are provided in Data_Visualization_Figures.rar to show Depth and thickness; subaqueous morphodynamics and depth and sediment transport (quiver).</p>
ScienceDex guides
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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.