Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
677
datasets available to search
ShareScore release 0.9.0
Dataset results
677 results for “Inversion”
Datasets related to paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion"
<p>The files include Satellite gravity data, topography and earthquake data used in the paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion" by Chamoli A., Rana S., Dwivedi D., Pandey A.K.. This has been submitted to Journal of Geophysical Research: Solid Earth. Restrictions applied to the availability of the land gravity data set.</p>
Data for: Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction (Part 2/2)
<p>Magnetic Resonance Imaging measurement data used in our paper about "Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction". The data is provided in a file format used by the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>)</p>
Drosophila melanogaster recombination experiments with inversion heterozygotes
<p>Recombination suppression in chromosomal inversion heterozygotes is a well-known but poorly understood phenomenon. Surprisingly, recombination suppression extends far outside of inverted regions where there are no intrinsic barriers to normal chromosome pairing, synapsis, double-strand break formation, or recovery of crossover products. The interference hypothesis of recombination suppression proposes heterozygous inversion breakpoints possess chiasma-like properties such that recombination suppression extends from these breakpoints in a process analogous to crossover interference. This hypothesis is qualitatively consistent with chromosome-wide patterns of recombination suppression extending to both inverted and uninverted regions of the chromosome. The present study generated quantitative predictions for this hypothesis using a probabilistic model of crossover interference with gamma-distributed inter-event distances. These predictions were then tested with experimental genetic data (>40,000 meioses) on crossing-over in intervals that are external and adjacent to four common inversions of <em>Drosophila melanogaster</em>. The crossover interference model accurately predicted the partially suppressed recombination rates in euchromatic intervals outside inverted regions. Furthermore, assuming interference does not extend across centromeres dramatically improved model fit and partially accounted for excess recombination observed in pericentromeric intervals. Finally, inversions with breakpoints closest to the centromere had the greatest excess of recombination in pericentromeric intervals, an observation that is consistent with negative crossover interference previously documented near <em>Drosophila</em> <em>melanogaster</em> centromeres. In conclusion, the experimental data support the interference hypothesis of recombination suppression, validate a mathematical framework for integrating distance-dependent effects of structural heterozygosity on crossover distribution, and highlight the need for improved modeling of crossover interference in pericentromeric regions.</p>
Error curves of finite completely monotonic functions associated with inverse power functions by exponential sum approximations
<p>Each figure of page <span class="math-tex">\(M=1,\ldots,17\)</span> in each PDF file represents the error curve of a finite completely monotonic function <span class="math-tex">\(f(x) = \int_a^b \mathrm{e}^{-xt} \frac{t^{\eta - 1}}{\Gamma(\eta)} \mathrm{d}t\)</span> by an <span class="math-tex">\(M\)</span>-term exponential sum approximation. Each PDF file corresponds to the following parameters:</p> <p>inverse_power0.5_a0.5_b1_EMx.pdf for <span class="math-tex">\(\eta = 0.5, a = 2^{-1}, b = 1\)</span><br> inverse_power0.5_a0.0009765625_b1_EMx.pdf for <span class="math-tex">\(\eta = 0.5, a = 2^{-10}, b = 1\)</span><br> inverse_power1_a0.5_b1_EMx.pdf for <span class="math-tex">\(\eta = 1, a = 2^{-1}, b = 1\)</span><br> inverse_power1_a0.0009765625_b1_EMx.pdf for <span class="math-tex">\(\eta = 1, a = 2^{-10}, b = 1\)</span><br> inverse_power2_a0.5_b1_EMx.pdf for <span class="math-tex">\(\eta = 2, a = 2^{-1}, b = 1\)</span><br> inverse_power2_a0.0009765625_b1_EMx.pdf for <span class="math-tex">\(\eta = 2, a = 2^{-10}, b = 1\)</span></p> <p> </p> <p>Each page includes 6 row figures:<br> Row=1 Best exponential sum approximation<br> Row=2 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\Phi_{a/b}(u)\)</span><br> Row=3 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\exp, a/b}(u)\)</span><br> Row=4 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\mathcal{P}_2, a/b}(u)\)</span><br> Row=5 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\mathcal{P}_1, a/b}(u)\)</span><br> Row=6 Approximation by the Gaussian quadrature with the variable transformation <span class="math-tex">\(\varphi_{\mathcal{R}_{0, 1}, a/b}(u)\)</span></p> <p> </p> <p>The figures were generated by</p> <p>https://github.com/ymkoyama/fcmf, commit 17342bf3974eee9b4d6b3d21b06f13b87929a85b on January 21, 2023.</p>
Grond reports for the seismic moment tensor inversions done for "The January 2022 Hunga Volcano explosive eruption from the multi-technological perspective of CTBT monitoring"
<p>This are the Grond reports of the seismic moment tensor inversion done for the manuscript submitted to GJI titled:</p> <p>"The January 2022 Hunga Volcano explosive eruption from the multi-technological perspective of CTBT monitoring"</p> <p>You can view the summary figures of the inversions in the subfolders for each event manually if you wish.</p> <p>However to view the reports interactively you need to have the pyrocko and grond softwares installed. See here for installation instruction for pyrocko: https://pyrocko.org/ and here for grond https://pyrocko.org/grond/docs/current/</p> <p>After correct installation you can view the reports in any browser by executing the command "grond report --so" in the folder which contains the unpacked "report" folder.</p>
Inversion polymorphism in a complete human genome assembly
<p>Supplementary data including code for an journal article titled 'Inversion polymorphism in a complete human genome assembly'.</p>
Multi-scale full waveform inversion based on a convolutional neural network
<p>The research data from this paper are uploaded here and are available for download.</p>
IMAU-ICE v2.0 version used for Berends et al. 2023 basal inversion experiments
<p>The exact IMAU-ICE v2.0 version that was used to peform the basal inversion experiments presented in Berends et al., 2023: "Compensating errors in inversions for subglacial bed roughness: same steady state, different dynamic response". Includes config files and input files.</p>
Inverse design of multishape metamaterials
<p>This dataset contains all data as used for the paper 'Inverse design of multishape metamaterials'.</p> <p> </p> <p><strong>Abstract:</strong></p> <p>Multishape metamaterials exhibit more than one target shape change, e.g. the same metamaterial can have either a positive or negative Poisson’s ratio. So far, multishape metamaterials have mostly been obtained by trial-and-error. The inverse design of multiple target deformations in such multishape metamaterials remains a largely open problem. Here, we demonstrate that it is possible to design metamaterials with multiple deformations of arbitrary complexity. To this end, we introduce a novel sequential nonlinear method to design multiple target modes. We start by iteratively adding local constraints that match a first specific target mode; we then continue from the obtained geometry by iteratively adding local constraints that match a second target mode; and so on. We apply this sequential method to design up to 3 modes with complex shapes and we show that this method yields at least an 85% success rate. Yet we find that these metamaterials invariably host additional spurious modes, whose number grows with the number of target modes and their complexity, as well as the system size. Our results highlight an inherent trade-off between design freedom and design constraints and pave the way towards multi-functional materials and devices.</p>
A numerical exploration of hyporheic zone solute transport behavior estimated from electrical resistivity inversions
<p>1). We run the Comsol model (ER3D_cs300ws6ds20_Zxl1.m) with an electrical push-pull loop, and then the voltage at every electrode of each time is printed to model_name.out and resistivity to model_name.ro. </p> <p>2). superposition.m is used to create final voltage results for later use in R2 inversions.</p> <p>3). postproc_c_dual.m is used to create the pixel breakthrough curves of the simulated results.</p> <p>4). plot_c_comsol.m read the resistivity result from step (1), convert the resistivity to bulk EC, and plot the bulk EC contour map. </p> <p>5). protocal_pc.m is used to take the voltages, add some random noise, and make the input files and batch scripts for R2.</p> <p>6). runr2.bat and runr2_TL.bat are used to generate inverted bulk EC.</p> <p>7). plot_C_r2_dual.m is used to plot the inversed bulk EC.</p>
Bleaching and Gaussian fitting (Inverse Photobleach Flow)
<p>Bleaching and Gaussian fitting (Inverse Photobleach Flow)</p>
Inverse observation operator parameters/models for master's dissertation: Updating a conceptual rainfall-runoff model based on radar observation and machine learning
<p>Both saved models and results of hyperparameter tuning are given. </p> <p>Code related to this dataset can be found <a href="http://github.com/olivierbonte/master_thesis">here</a></p> <p> </p>
Joint Inversion of Receiver Functions and Apparent Shear Wave Velocity for Martian Crustal Model
<p>Data and Codes of the joint inversion of receiver functions and apparent shear wave velocity for martian crustal model.</p>
Carbon export estimated from an inverse biogeochemical model (Wang et al.,)
<p>Carbon export estimated from an inverse biogeochemical model (Wang et al.,)</p> <p>The four files are from two NPP configurations: CbPM and CAFE and two time scales for labile DOC remineralization e-folding time (12 hours and 24 hours), which are self-explained in the file name.</p> <p>Once the data has been loaded to Matlab, you'll see a structure EXP that contains a total of 9 fields: POCexp: </p> <p>POCexp, lDOCexp, sDOCexp are POC, labile DOC, semi-labile DOC flux at the base of model euphotic zone (~73 m).</p> <p>POC100, lDOC100, sDOC100 are POC, labile DOC, semi-labile DOC flux at 100 m.</p> <p>TOCmld is total carbon export at the base of maximum mixed layer depth.</p> <p>TOC110 and POC1000 are total carbon export at 110 and POC flux at 1000 m, respectively. </p> <p>The units for the export fluxes are in mmol m-2 year-1, and not in mg C m-2 day-1 as used in the paper. For conversion, you need to divide the value by 365.25 and multiply 12.</p>
Revealing Crustal Structure of the Western Philippine Sea Subduction Zone through Seismic, Gravity and Magnetic Joint Inversion Based on Minimum Support Cross-Gradient Coupling
<p>Data contains the synthetic model data and field data.<br> Final model contains the joint and single inverison result. <br> First volum of the data and model represents the location on the profile.</p> <p>Second volum of the model represents the depth of the model, which is all positive.</p> <p>Second volum of the data represent the value of the synthetic data.</p> <p>Rec_obs represents the reflection observed data,fir_tob represents the first arrival travel time observed data, the first and the second volum represents the source number and the receiver number. </p>
Shear wave velocity inversion based on dispersion characteristics of seabed Scholte wave in deep water
<p>Simulated displacement records at the seabed with three different water depths using spectral element method. </p>
Impact of noise on inverse design: The case of NMR spectra matching
<p>Code and data for the corresponding preprint:</p> <p>Impact of noise on inverse design: The case of NMR spectra matching<br> Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld</p> <p>https://doi.org/10.48550/arXiv.2307.03969</p> <p><br> SI_DFT_geo.xyz and SI_DFT_NMR.txt belong to the QM9NMR paper<br> Revving up 13C NMR shielding predictions across chemical space: benchmarks for atoms-in-molecules kernel machine learning with new data for 134 kilo molecules<br> Amit Gupta, Sabyasachi Chakraborty and Raghunathan Ramakrishnan<br> Mach. Learn.: Sci. Technol. 2 (2021) 035010</p> <p>originally hosted here:<br> https://moldis-group.github.io/qm9nmr/<br> https://doi.org/10.17172/NOMAD/2021.10.16-1</p>
Callisto and Synthetic400 inversion data sets
<p>Callisto and Synthetic400 model input files for the Tomofast-x 2.0.</p>
Inverse priority effects: The order and timing of removal of invasive species influence community reassembly
<p>1. An ongoing restoration challenge is to recover native communities after the removal of invasive species. Because priority effects (i.e., the order and timing of species arrival) can strongly determine the trajectory of community assembly, their intentional manipulation is gaining attention to manage invasive plants and achieve restoration goals. Yet, ecologists and conservationists rarely consider how the order and timing of species removal inverse priority effect may impact future plant communities. 2. Here, we evaluated the dependence of community reassembly on inverse priority effects by experimentally removing the target invasives Sweetbriar rose (<em>Rosa rubiginosa</em>) and Scotch broom (<em>Cytisus scoparius</em>) in field and mesocosm communities. We manipulated removal order (rose-before-broom vs. broom-before-rose) and timing (simultaneously early vs. simultaneously late in the season). We performed a Hierarchical Modeling of Species Community to assess differences in community structure in response to order and timing of removal, and to evaluate whether species origin and leaf and seed traits were associated with species responses. 3. We found that the order of removal was as important as timing driving community reassembly. Simultaneous removal favoured nonnatives, more so when performed early. Sequential removals led to contrasting communities. Rose-before-broom removal also favoured nonnative grasses at expense of native species, whereas the inverse order produced small changes in communities. In general, species with high specific leaf area were boosted, regardless of their seed size. 4. Synthesis and applications. Inverse priority effects are neglected mechanisms that can drive variability in the reassembly of plant communities and can potentially upgrade invasive species management. These historical contingencies suggest the existence of an optimal order of removal that facilitates the recovery of the native community. We found that simultaneous removal promoted secondary invasions to a greater extent than sequential removals. Furthermore, removal order affected post-removal community structure. In our system, we suggest removing the rose before the broom to hinder nonnatives and pave the way for restoration of native communities. Our results show that manipulation of the order and timing of removal can help to achieve restoration goals.</p>
Supplementary Materials of "Understanding flow characteristics from tsunami deposits at Odaka, Joban coast, using a DNN inverse model" by Mitra, Naruse and Abe
<p>This is a supplementary figures for the manuscript entitled "Understanding flow characteristics from tsunami deposits at Odaka, Joban coast, using a DNN inverse model" submitted to NHESS.</p>
ScienceDex guides
Understand access before you commit
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.