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978 results for “Instability”
Instability caused swimming of ferromagnetic filaments in pulsed field
<p>This repository contains experimental data and numerical results related to the publication: Zaben, A., Kitenbergs, G. & Cēbers, A. Instability caused swimming of ferromagnetic filaments in pulsed field. <em>Sci Rep</em> 11, 23399 (2021). https://doi.org/10.1038/s41598-021-02541-3. </p> <p>'Experimental.rar' file contains experimental images: the files are named by the filament length 'L = ....' followed by the value of field frequency 'x_Hz'. </p> <p>'Numerica.rar' file contains (x,y) filament coordinates obtained by numerical simulation over the dimensionless time t : the files are named as the absolute value of <span class="math-tex">\(\lambda\)</span> followed by Cm number. Matlab data files are named as the values of (Cm...._<span class="math-tex">\(T/\tau\)</span> ......_abs(<span class="math-tex">\(\lambda\)</span>)...) defined in the simulations. </p> <p>'Fig_2.rar' : contains numerical results of figure 2 presented in the paper : files are named with the figure subtitle (b) and (c). Matlab data files are named with the values of Cm and <span class="math-tex">\(T/\tau\)</span> defined in the simulations. </p> <p>'Fig_1.rar': data of figure 1 presented in the paper, field readings ( M_F_R.xlsx) with the corresponding experimental images (highlighted as the image number) and numerical simulation (index of the dimensional time t) in Cm51_tau9.21E-03.mat file. </p> <p>'Fig_3.xlsx': contains data points presented in figure 3. </p> <p>'Fig_5.xlsx': contains data for experimental results presented in figure 5. </p>
Data and output files for the paper, "Dynamical systems inference at scale reveals intrinsic instability in the dysbiotic microbiome"
<p>The above files contain the output of the model, which we call MDSINE2, developed in the paper titled, "<em>Dynamical systems inference at scale reveals intrinsic instability in the dysbiotic microbiome</em>" (See https://github.com/gerberlab/MDSINE2_Paper for implementation details). More specifically, forward_sims.tgz contains the output of forward simulations in .npy format; mixed_prior_fixed.tgz contains the pickle files corresponding to the output of the MCMC simulations for fixed topology; mixed_prior_unfixed.tgz contains the pickle files corresponding to the output of the MCMC simulations for unfixed topology; other_files contains information on eigenvalues and cycles, results for Phylogenetic Neighborhood Analysis, Keystoneness Analysis and the output in .npy format for comparator methods; ASV_OTU_aggregate_and_plylogeneteic trees contains the plots of trajectories (relative abundance) of OTUS and their constituent ASVs, and of phylogenetic trees. </p>
In situ monitoring reveals cellular environmental instabilities in human pluripotent stem cell culture
<p>Mammalian cell cultures are a keystone resource in biomedical research, but the results of published experiments often suffer from reproducibility challenges. This has led to a focus on the influence of cell culture conditions on cellular responses and reproducibility of experimental findings. Here, we perform frequent in situ monitoring of dissolved O<sub>2</sub> and CO<sub>2</sub> with optical sensor spots and contemporaneous evaluation of cell proliferation and medium pH in standard batch cultures of three widely used human somatic and pluripotent stem cell lines. We collate data from the literature to demonstrate that standard cell cultures consistently exhibit environmental instability, indicating that this may be a pervasive issue affecting experimental findings. Our results show that <i>in vitro</i> cell cultures consistently undergo large departures of environmental parameters during standard batch culture. These findings should catalyze further efforts to increase the relevance of experimental results to the in vivo physiology and enhance reproducibility.</p>
Increasing Instability of a Rocky Intertidal Meta-Ecosystem
<p>Climate change threatens to destabilize ecological communities, potentially moving them from persistently-occupied "basins of attraction" to different states. Increasing variation in key ecological processes can signal impending state shifts in ecosystems. In a rocky intertidal meta-ecosystem consisting of three distinct regions spread across 260 km of the Oregon coast, we show that annually cleared sites are characterized by communities that exhibit signs of increasing destabilization (loss of resilience) over the past decade despite persistent community states. In all cases, recovery rates slowed and became more variable over time. The conditions underlying these shifts appear to be external to the system, with thermal disruptions (e.g., marine heat waves, El Niño-Southern Oscillation) and shifts in ocean currents (e.g., upwelling) being the likely proximate drivers. Although this iconic ecosystem has long-appeared resistant to stress, the evidence suggests that subtle destabilization has occurred over at least the last decade.</p>
Supplementary Materials for Evaluation role of ferroptosis long non-coding RNAs for immune microenvironment and microsatellite instability in colon cancer
<p>Supplementary Materials for "Evaluation role of ferroptosis long non-coding RNAs for immune microenvironment and microsatellite instability in colon cancer"</p>
Axion Instability Supernovae
<p>Reproduction package for the paper "Axion Instability Supernovae".</p> <p> </p> <p>The package contains inlists and run_star_extras.f files that can be used in MESA to simulate the evolution of massive stars when a new scalar particle of mass 511keV is included in the equation of state. Also included is a Mathematica script to generate inlists for bosons of user-supplied masses and spins.</p>
Translin facilitates RNA polymerase II dissociation and suppresses genome instability during RNase H2- and Dicer-deficiency (data files)
<p>The conserved nucleic acid binding protein Translin contributes to numerous facets of mammalian biology and genetic diseases. It was first identified as a binder of cancer-associated chromosomal translocation breakpoint junctions leading to the suggestion that it was involved in genetic recombination. With a paralogous partner protein, Trax, Translin has subsequently been found to form a hetero-octomeric RNase complex that drives some of its functions, including passenger strand removal in RNA interference (RNAi). The Translin-Trax complex also degrades the precursors to tumour suppressing microRNAs in cancers deficient for the RNase III Dicer. This oncogenic activity has resulted in the Translin-Trax complex being explored as a therapeutic target. Additionally, Translin and Trax have been implicated a wider range of biological function ranging from sleep regulation to telomere transcript control. Here we reveal a Trax- and RNAi-independent function for Translin in dissociating RNA polymerase II from its genomic template, with loss of Translin function resulting in increased transcription-associated recombination and elevated genome instability. This provides genetic insight into the longstanding question of how Translin might influence chromosomal rearrangements in human genetic diseases and provides important functional understanding of an oncological therapeutic target.</p>
Figures data for "Investigation of Kinetic Ballooning Instability in 2D Harris Sheet Equilibrium with Finite Normal $B_z$ Field"
<p>To make it simpler for readers to understand and reproduce the work, the data for all the figures in the article titled "Investigation of Kinetic Ballooning Instability in 2D Harris Sheet Equilibrium with Finite Normal $B z$ Field" are being uploaded.</p>
Genome-wide survey of D/E repeats in human proteins uncovers their instability and aids in identification of their role in the chromatin regulator ATAD2
<p>Raw digital images of Western blots that comprise Figure 8E of the manuscript</p>
Dataset of PNAS article "Morphological instability and roughening of growing 3D bacterial colonies"
<p>Dataset of the PNAS article "Morphological instability and roughening of growing 3D bacterial colonies", including numerical simulations and raw images of all Main Text and SI figures.</p>
Fig. 3 in Deep Instability in the Phylogenetic Backbone of Heteroptera is Only Partly Overcome by Transcriptome-Based Phylogenomics
Fig. 3. Metrics resulting from quartet sampling of the amino acid alignment over the phylogeny resulting from maximum likelihood analyses of amino acids. Clade support is depicted as: QC/QD/QI.
Fig. 1 in Deep Instability in the Phylogenetic Backbone of Heteroptera is Only Partly Overcome by Transcriptome-Based Phylogenomics
Fig. 1. Phylogeny of Heteroptera resulting from partitioned analysis of concatenated nucleotides. Clade support is based on bootstrap replicates and the scale bar is average substitutions per site.
Fig. 2 in Deep Instability in the Phylogenetic Backbone of Heteroptera is Only Partly Overcome by Transcriptome-Based Phylogenomics
Fig. 2. Metrics resulting from quartet sampling of the nucleotide alignment over the phylogeny resulting from maximum likelihood analyses of concatenated nucleotides. Clade support is depicted as: QC/QD/QI.
Fig. 4 in Deep Instability in the Phylogenetic Backbone of Heteroptera is Only Partly Overcome by Transcriptome-Based Phylogenomics
Fig. 4. Subtree of Pentatomomorpha based on the ML analysis of concatenated nucleotides and subsequent quartet sampling. Clade support is depicted as: QC/QD/QI.
Model output for: Rate of mass loss across the instability threshold for Thwaites Glacier determines rate of mass loss for entire basin
<p><strong>Results from “Rate of mass loss across the instability threshold for Thwaites Glacier determines rate of mass loss for entire basin.”</strong></p> <p>The tar files herein contain multi-resolution grounding line position data and 4 km resolution output of modeled fields for all model runs. The region of interest represented is the Thwaites catchment in West Antarctica. The files for modeled fields have been coarsened or “flattened” to 4 km from their original adaptive mesh refinement (AMR) structure.</p> <p>Metadata contents</p> <p><em>1. Grounding line position data – text files</em></p> <p><em>2. Modeled Fields – HDF5 files</em></p> <p><em>3. BISICLES grid and coordinate system</em></p> <p> </p> <p><em>1. Grounding line position data</em></p> <p>Tar Files with "GLposition" in the title contain the annual grounding line positions, at cell faces, over the discretized Thwaites catchment for the specified model run. Each tar file contains a series of text files for a particular model run that used a specific background melt rate. The background marine melt rate is specified in the third field of the tar file name as delimited by the underscore character (“_”). Additionally, the last year of anomalous forcing before it was turned off leaving only the background marine melting is listed in the third field.</p> <p>nonuniformMM indicates the non-uniform background marine melting.</p> <p>uniformMM indicates the uniform background marine melting.</p> <p>260 and 270 are the last model years where anomalous marine melting were applied.</p> <p>After untarring a file, the naming convention for the individual text files is seen to be similar to the name of the respective tar file. The first field as delimeted by the underscore character contains either “glnonMM” or “gluniMM” followed by the last year of anomalous forcing used; e.g “gluniMM260”. The second field indicates the model year. Note that the last year forced is included for all runs.</p> <p>The text files contain three columns of data: an indicator of model resolution followed by <em>x- </em>and<em> y-</em>coordinates, respectively. Location coordinate units are meters and are BISICLES physical coordinates (see 3. BISICLES grid and coordinate system).</p> <p>For the first column:</p> <p>1 is 2 km resolution</p> <p>2 is 1 km resolution</p> <p>3 is 500 m resolution</p> <p>4 is 250 m resolution</p> <p>Zero (0) would be the base resolution of 4 km, however, all grounded ice was tagged to refine to level 1 so it does not appear in these files. Additionally, if a region was refined at a high resolution, then the grounding line positions for this region are not reported at any lower resolutions below this.</p> <p> </p> <p><em>2. Modeled fields</em></p> <p>Modeled fields are 4 km resolution in Chombo HDF5 file format. Each tar file contains the annual data as individual HDF5 files for the specified model run. The second field of the tar file as delimited by the underscore character specifies the background melt rate used and the last year of anomalous marine forcing (ramp).</p> <p>NonUniformMM260 indicates the non-uniform background marine melt rate with ramp shutoff after year 260.</p> <p>NonUniformMM270 same as above but ramp shutoff at year 270</p> <p>UniformMM260 indicates the spatially uniform background marine melt rate with ramp shutoff after year 270</p> <p>UniformMM270 same as above but ramp shutoff at year 270</p> <p>HDF5 files: The third field as delimited by the period (“.”) character shows the background melt rate used in individual HDF5 files and the fifth field indicates the model year.</p> <p>Contents of HDF5 files (field name: variable)</p> <p>xVel: velocity in the direction of the x-axis (m/a)</p> <p>yVel: velocity in the direction of the y-axis (m/a)</p> <p>Z_surface: upper ice surface elevation (masl)</p> <p>Z_bottom: underside surface ice elevation (masl)</p> <p>Z_base: bed elevation (masl)</p> <p>basal_friction: Basal friction coefficients</p> <p>div_uh: mass divergence</p> <p>mask: differentiates physical setting of cells (Note that coarsening introduces averages of numbers below at interfaces)</p> <p> grounded ice = 1</p> <p> floating ice = 2</p> <p> ocean = 4</p> <p> rock = 8</p> <p>basalThicknessSource: melt rate (m/a)</p> <p>surfaceThicknessSource: accumulation rate (m/a)</p> <p>surfaceThicknessBalance: sum of melt rate and accumulation rate (m/a)</p> <p> </p> <p><em>3. BISICLES grid and coordinate system</em></p> <p>The BISICLES model uses cell-centered grids with each cell represented by (i, j) pairs that begin numbering at (0,0) typically in the lower left hand corner of a domain. This project maintained the number ordering for the continental dataset such that (i = 366, j = 561) is the lower left cell for the included 4 km resolution HDF5 files and (i = 504, j=732) is the upper right cell. As the resolution is 4 km, this is noted as dx = 4000 in the HDF5 files.</p> <p>Since the data is located at cell centers, the physical coordinates relative to the BISICLES grid for a variable at (i, j) in meters is:</p> <p>(dx*(i + 0.5), dx*(j + 0.5)) = (BISICLES_X, BISICLES_Y)</p> <p>where dx is the cell resolution</p> <p>The translation from BISICLES physical coordinates (m) to polar stereographic projection in meters (standard parallel at -71 degrees) is as follows:</p> <p>(BISICLES_X – 3071500, BISICLES_Y – 3072500)</p> <p><br> </p> <p><br> </p> <p><br> </p> <p><br> </p> <p> </p>
Baroclinic instability induced mesoscale and submesoscale processes in the river plumes: A laboratory investigation on a rotating tank
<p>This dataset studied the baroclinic instability (BI) induced mesoscale and submesoscale processes by conducting laboratory rotating flume experiments. We acquired the high-resolution velocity data by Parrticle Image Velocity (PIV). The mesoscale and submesoscale vortices were identified and tracked, and the variations of the instabilities and kinetic energy of the plume system under different inflow conditions and slopes were summarized. Number '1' to '33' mean cases number; 'gs', 'ss', and 'ns' stand for 'gentle slope', 'steep slope', and 'no slope'; 'T20' to 'T60' correspond to the rotation period from 20 to 60 s; 'g4' to 'g10' correspond to the reduced gravity between the buoyant plume and environmental fluid from 4 to 10 cm/s^2. 'vor_char' means the vortices characteristics including the time series of the vortex center and vortex contour.</p>
Effect of plasma initialization on 3D PIC simulation of Hall 1 thruster azimuthal instability
<p>This dataset only includes the plotting scripts for the research, because the data is too big. More may be uploaded in a later time.</p>
STREAMICE code and inputs for "The West Antarctic Ice Sheet may not be vulnerable to Marine Ice Cliff Instability during the 21st Century"
<p>This repository contains all inputs and code to carry out the STREAMICE calving experiments run for the manuscript "The West Antarctic Ice Sheet may not be vulnerable to Marine Ice Cliff Instability during the 21st Century" using the modelling framework MITgcm.</p> <p>MITgcm-front_retreat/ contains a branch of the MITgcm code that enables calving front advance and retreat in the STREAMICE model, and is a branch of checkpoint 68d. Please see https://github.com/MITgcm/MITgcm/blob/master/LICENSE.txt for the MITgcm open source license detail.</p> <p>code/ contains experiment-specific code for the runs detailed in the manuscript</p> <p>input_fwd/ contains all binary and parameter input files for the runs detailed in the manuscript</p> <p>archer_scripts/ contains shell scripts written for the ARCHER2 UK supercomputer to demonstrate how the model is compiled</p> <p> </p> <p> </p>
New Expression of the Field-line Integrated Rayleigh-Taylor Instability Growth Rate
<p>The data provided in correlation with the journal article bearing the same title.</p>
Supplementary material for "Hybrid-Vlasov modelling of ion velocity distribution functions associated with the Kelvin-Helmholtz instability with a density and temperature asymmetry"
<p>Supplementary material for the article:</p> <p>"Hybrid-Vlasov modelling of ion velocity distribution functions associated with a density and temperature asymmetry" by</p> <p><strong>V. Tarvus</strong>, L. Turc, H. Zhou, T. Nakamura, A. Settino, K.Blasl, G. Cozzani, U. Ganse, Y. Pfau-Kempf, M. Alho, M. Battarbee, M. Bussov, M. Dubart, E. Gordeev, F. Tesema Kebede, K. Papadakis, J. Suni, I. Zaitsev and M. Palmroth</p> <p> </p> <p><strong>Supplementary video A</strong>:</p> <p>The development of the Kelvin-Helmholtz instability (KHI) in a purely transverse geometry (velocity shear perpendicular to the magnetic field), simulated using the hybrid-Vlasov model Vlasiator. The parameters shown are: Proton temperature (panel a), the non-Maxwellianity of the proton velocity distribution function (panel b), proton heat flux (panel c) and vorticity (panel d). A black contour in each panel shows the region where the magnitude of the proton temperature gradient is larger than the maximum gradient at the beginning of the simulation. Arrows in panel d) show the velocity field. The evolution of KHI proceeds from the formation of linear surface waves (t<50 Ω<sub>c,p</sub><sup>-1</sup>, with proton gyroperiod Ω<sub>c,p</sub><sup>-1</sup>) to the waves rolling up into vortices (t>50 Ω<sub>c,p</sub><sup>-1</sup>). Due to the steepening of the velocity shear layer, whose thickness tends towards the thermal proton Larmor radius, finite Larmor radius effects become active at the vortex edges, manifesting as enhanced non-Maxwellianity (panel b) and a heat flux (panel c), which originates from the temperature gradient according to the mechanism described by Braginskii (1965). At the end of the simulation (t=90-100 Ω<sub>c,p</sub><sup>-1</sup>), non-Maxwellianity increases also in the vortex interior, as protons from the two initial regions are mixed together.</p> <p> </p> <p><strong>Supplementary video B</strong>:</p> <p>The same as Supplementary video A, but with an added in-plane magnetic field of the form (<em>B</em><sub>0,z</sub>/5) tanh(x/a) <strong>y</strong>,<strong> </strong>where <em>B</em><sub>0,z</sub> is the magnitude of the background magnetic field perpendicular to the velocity shear. Analogous behavior is found compared to the simulation without an in-plane magnetic field (Supplementary video A), with the exception of the suppression of secondary instabilities by the added magnetic tension. This leads to less irregularities in the vortex structure during the non-linear stage (t>~50 Ω<sub>p</sub><sup>-1</sup>).</p>
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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.