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4,010 results for “Stabilization”
Phase I trial of CX-5461, a first-in-class G-quadruplex stabilizer in patients with advanced solid tumors enriched for DNA-repair deficiencies (CCTG IND.231) - Variant Calls
<p>Variant Calls from Phase I trial of CX-5461, a first-in-class G-quadruplex stabilizer in patients with advanced solid tumors enriched for DNA-repair deficiencies (CCTG IND.231)</p> <p>See publication for methodology.</p>
Numerical data for "Black Hole Metamorphosis and Stabilization by Memory Burden [arXiv:2006.00011]"
<p>This is the numerical data that belongs to the paper</p> <p>G. Dvali, L. Eisemann, M. Michel, S. Zell, <em>Black Hole Metamorphosis and Stabilization by Memory Burden</em>, <a href="https://doi.org/10.1103/PhysRevD.102.103523">Phys. Rev. D <strong>102</strong> (2020) 103523</a>, <a href="https://arxiv.org/abs/2006.00011">arXiv:2006.00011</a>.</p> <p>The numerical data is generated using the computer program <em>TimeEvolver</em>, which was presented in</p> <p>M. Michel, S. Zell, <em>TimeEvolver: A Program for Time Evolution With Improved Error Bound, </em><a href="https://doi.org/10.1016/j.cpc.2022.108374">Comput. Phys. Commun. <strong>277</strong> (2022) 108374</a>, <a href="https://arxiv.org/abs/2205.15346">arXiv:2205.15346</a>.</p> <p>In the following, equation numbers refer to the latest arXiv-version of <a href="https://arxiv.org/abs/2006.00011">arXiv:2006.00011</a>, where also all relevant definitions can be found. In this paper, the procedure for generating the data, which we summarize in the following, is also described in more detail.</p> <p>First, among the five parameters N<sub>c</sub>; <sup><span class="math-tex">\(\epsilon\)</span></sup><sub>m</sub>; C<sub>0</sub>; ∆N<sub>c</sub>; K all but one are fixed (according to eq. (36)). Then for different values of the remaining unfixed parameter - subsequently called X - the following 2-step process is performed.</p> <ol> <li>Time evolution is computed (with the initial state shown in eq. (35)) for many different values of the parameter C<sub>m</sub> in the interval [0;1] (sampling step 10<sup>-3</sup>). The results for X are stored in five folders called "X", the subfolders of which contain data for different values of X. For example, the subfolder "01" of the folder "C0" consists of data for C<sub>0</sub>=0.01. Please note that the folders "Cgap", "N0" and "Q" correspond to X=<span class="math-tex">\(\epsilon\)</span><sub>m</sub>, X=N<sub>c</sub> and X=K, respectively. Subsequently, "rewriting values" of C<sub>m</sub> are selected as those for which the amplitude of n<sub>0</sub> is sufficiently large (1.2 times than in the case C<sub>m</sub>=0). This is done in Mathematica-notebooks "_New.nb". Finally, rewriting values for different values of X are collected using Mathematica-notebooks with names that start on "_Meta". These notebooks generate the 5 plots shown in figures 4(a), 5(a), 6(a), 7(a) and 8(a).</li> <li>Next finer scans are performed around some of the rewriting values determined in step 1 (new sampling step 5 10<sup>-5</sup>). The results are stored in five folders called "XRates", where again subfolders correspond to different values of X. For example, the subfolder "01" of the folder "C0Rates" consists of finer scans in C<sub>m</sub> around rewriting value of C<sub>m</sub> for C<sub>0</sub>=0.01. Next, Mathematica-notebooks with the names "_New.nb" or "_NewRates.nb" are used to select around each rewriting value the C<sub>m</sub> that leads to the largest rate (see definition in <a href="https://arxiv.org/abs/2006.00011">arXiv:2006.00011</a>). Finally, these maximal rates for different values of X are collected using Mathematica-notebooks with names that start on "_Meta" and end on "Rates.nb". These notebooks generate the 5 plots shown in figures 4(b), 5(b), 6(b), 7(b) and 8(b).</li> </ol>
Stability characterization of microfluidic lipid-stabilized double emulsions under physiologically-relevant conditions
<p>Double emulsions (DEs) are water-in-oil-in-water (or oil-in-water-in-oil) droplets with the potential to deliver combinatory therapies due to their ability to co-localize hydrophilic and hydrophobic molecules in the same carrier. However, DEs are thermodynamically unstable and only kinetically trapped. Extending this transitory state, rendering DEs more stable, would widen the possibilities of real-world applications, yet characterization of their stability in physiologically-relevant conditions is lacking. In this work, we used microfluidics to produce lipid-stabilized DEs with reproducible monodispersity and high encapsulation efficiency. We investigated DE stability under a range of physico-chemical parameters such as temperature, pH and mechanical stimulus. Stability through time was inversely proportional to temperature. DEs were significantly stable up to 8 days at 4 oC, 5 days at RT and 2 days at 37 oC. When encapsulating a cargo, DE stability decreased significantly. When exposed to a pH change, unloaded DEs were only significantly unstable at the extremes (pH 1 and 13), largely outside physiological ranges. When exposed to flow, unloaded DEs behaved similarly regardless of the mechanical stimulus applied, with approximately 70% remaining after 100 flow cycles of 10s. These results indicate that lipid-stabilized DEs produced via microfluidics could be tailored to endure physiologically-relevant conditions and act as carriers for drug delivery. Special attention should be given to the composition of the solutions, e.g. osmolarity ratio between inner and outer solutions, and the interaction of the molecules, e.g. carrier and cargo, involved in the final formulation.</p>
First-principles investigation of phase stability in substoichiometric zirconium carbide under high pressure
<p>This is a data set that supports a first-principles investigation into the phase stability of zirconium carbide under high pressure. High throughput density function theory data is used to train a cluster expansion. The trained model is used to sample the phase space of the substoichiometric ZrC system into high pressures. This sampling sheds insight on how pressure affects the stability and partial vacancy ordering in the ZrC system.</p>
Data: Stability and biological response of PEGylated gold nanoparticles
<p><span>This dataset is focused on thermal stability of PEGylated Au NPs at 4 and 37 °C and after sterilization in autoclave.</span></p>
Data for Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents
<div> <p>Full set of data related to the publication "Stabilization of non-native folds and programmable protein gelation in compositionally designed deep eutectic solvents", published in ACS Nano with DOI:<a title="https://doi.org/10.1021/acsnano.4c01950" href="https://doi.org/10.1021/acsnano.4c01950">10.1021/acsnano.4c01950</a></p> <p> Full details on data treatment and logging are included in the file "DataLogging.pdf". All data use ASCII encoding in delimited .txt files.</p> <p> </p> </div>
Supplementary Data: Impact of vacuum stability, perturbativity and XENON1T on global fits of Z2 and Z3 scalar singlet dark matter (arXiv:1806.11281)
<p> </p> <p><strong>Supplementary Data</strong></p> <p> </p> <p><em>Impact of vacuum stability, perturbativity and XENON1T on global fits of Z<sub>2</sub> and Z<sub>3</sub> scalar singlet dark matter</em> <a href="https://arxiv.org/abs/1806.xxxxx"><em>arXiv:</em></a><em><a href="https://arxiv.org/abs/1806.11281">1806.11281</a></em></p> <p>The files in this record contain data for the scalar singlet dark matter models considered in the <a href="http://gambit.hepforge.org">GAMBIT</a> "Scalar singlet Mark II" paper.</p> <p>The files consist of</p> <ul> <li>30 regular YAML files</li> <li><code>StandardModel_SLHA2_scan.yaml</code>, a universal YAML fragment included from the other YAML files</li> <li>14 hdf5 files. 8 of these correspond to the complete set of combined samples for each fit. These 8 fits are generated from all binary permutations of three run properties: Z2 or Z3 model, with or without absolute vacuum stability demanded, and with constraints from the 2017 or 2018 XENON1T data. These 8 hdf5 files are used to generate the profile likelihood plots in the paper. The other 6 hdf5 files are the results of T-Walk runs, and are used to generate the posterior pdfs in the paper.</li> <li>Some example pip files for producing plots from the hdf5 files using <a href="github.com/patscott/pippi">pippi</a></li> <li>A tarball <code>best_fits_yaml.tar.gz</code> containing YAML files of the best-fit point in each of the 8 fits.</li> </ul> <p>The files follow the naming scheme <code>SingletDM_[model]_[slice]_[vacuum]_[xenon]_[prior]_[scanner].yaml</code>.</p> <ul> <li>model: <code>Z2</code> or <code>Z3</code></li> <li>slice: <code>full</code>, <code>lowmass</code>, <code>neck</code> or absent (for hdf5 files)</li> <li>vacuum: <code>ms</code> (metastable) or <code>vs</code> (absolute vacuum stability)</li> <li>prior: <code>logmu3</code>, <code>flatmu3</code> or absent (for Z<sub>2</sub> scans)</li> <li>scanner: <code>TWalk</code> or absent (implies Diver scans in the case of YAML files, and indicates merged samples potentially from both Diver and T-Walk in the case of hdf5 files)</li> </ul> <p>A few caveats to keep in mind:</p> <ol> <li> <p>The YAML files are designed to work with GAMBIT 1.2.0, commit e4d3f739, and the pip files are tested with pippi 2.1, commit c094b8c8. They may or may not work with later versions of either software (but you can of course always obtain the version that they do work with via the git history).</p> </li> <li> <p>The pip files are examples only. Users wishing to reproduce the more advanced plots in any of the GAMBIT papers should contact us for tips or scripts, or experiment for themselves. Many of these scripts are in multiple parts and require undocumented manual interventions and steps in order to implement various plot-specific customisations, so please don't expect the same level of polish as for files provided here or in the GAMBIT repo. </p> </li> </ol> <p> </p>
Stability in water and electrochemical properties of the Na3V2(PO4)2F3 – Na3(VO)2(PO4)2F solid solution
<p>Graphitical Abstract of the publication "Stability in water and electrochemical properties of the Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3</sub> – Na<sub>3</sub>(VO)<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F solid solution" <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/science/journal/24058297/20/supp/C">Energy Storage Materials Volume 20</a>, 2019, p. 324-334 - DOI : <a href="https://doi-org.docelec.u-bordeaux.fr/10.1016/j.ensm.2019.04.010">https://doi.org/10.1016/j.ensm.2019.04.010</a></p> <p>Abstract : Polyanionic materials have been intensively studied as promising active materials for <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/engineering/positive-electrode">positive electrodes</a> in Na-ion batteries thanks to their excellent stability upon cycling and the fast ionic mobility in their structural framework. Among them, Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3</sub> and Na<sub>3</sub>(VO)<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F are two of the most promising ones due to their high voltages for Na<sup>+</sup>-ion extraction and their high energy densities: 500 mWh g<sup>−1</sup> and 495 mWh g<sup>−1</sup>, respectively. Here, we study the formation mechanism as well as the stability of these phases in <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/engineering/aqueous-medium">aqueous media</a> and the possible use of a washing step in water in order to remove undesirable <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/materials-science/impurity">impurities</a> formed during the synthesis. Furthermore, the origin of the extra capacity observed at the high voltage region for Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3</sub> and Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>1.5</sub>O<sub>1.5</sub> was studied by <em>operando</em> <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/materials-science/x-ray-absorption-spectroscopy">X-ray absorption spectroscopy</a>.</p> <p> </p>
Supplemental Data for "Stability of fractional Chern insulators with a non-Landau level continuum limit"
<p>Scripts and data to supplement the paper "Stability of fractional Chern insulators with a non-Landau level continuum limit".</p>
Structural build-up and stability of hybrid monoglyceride-triglyceride oleogels
<p>This dataset was used in the publication <em>"</em><em>Structural build-up and stability of hybrid monoglyceride-triglyceride oleogels</em><em>"</em>. An overview of files is given below:</p>
ZIRFs: zero-inflated random forests for estimating gene regulatory networks from single cell RNA-seq data (assessment of predictive accuracy and VIM stability)
<p>We developed a zero-inflated random forests (ZIRFs) algorithm to produce a metric of connection strength between regulator genes and target genes. This file contains SCENIC results for the aorta and diaphragm tissue data sets from the Tabula Muris Consortium results. SCENIC is a genetic regulatory network analysis published by Aibar et al. (2017). The purpose of the data sets and R source code are described by README files in each directory.</p>
IEEE New England 39-bus test case: Dataset for the Transient Stability Assessment
<p>The <strong>dataset</strong> contains <strong>350</strong> <strong>features</strong> engineered from the phasor measurements (PMU-type) signals from the <strong>IEEE New England 39-bus power system</strong> test case network, which are generated from the 9360 systematic MATLAB®/Simulink electro-mechanical transients simulations. It was prepared to serve as a convenient and open database for experimenting with different types of <strong>machine learning</strong> techniques for <strong>transient stability assessment</strong> (TSA) of electrical power systems.</p> <p>Different load and generation levels of the New England 39-bus benchmark power system were systematically covered, as well as all three major types of short-circuit events (three-phase, two-phase and single-phase faults) in all parts of the network. The consumed power of the network was set to 80%, 90%, 100%, 110% and 120% of the basic system load levels. The short-circuits were located on the busbar or on the transmission line (TL). When they were located on a TL, it was assumed that they can occur at 20%, 40%, 60%, and 80% of the line length. Features were obtained directly from the time-domain signals at the pickup time (pre-fault value) and at the trip time (post-fault value) of the associated distance protection relays.</p> <p>This is a <strong>stochastic dataset</strong> of 3120 cases, created from the population of 9360 systematic simulations, which features a statistical distribution of different fault types, as follows: single-phase (70%), double-phase (20%) and three-phase faults (10%). It also features a <strong>class imbalance</strong>, with less than 20% of cases belonging to the unstable class. Dataset is a compressed CSV file.</p> <p><strong>List of feature names in the dataset:</strong></p> <ul> <li><em>WmGx</em> - rotor speed for each generator Gx, from G1 to G10,</li> <li><em>DThetaGx</em> - rotor angle deviation for each generator Gx, from G1 to G10,</li> <li><em>ThetaGx</em> - rotor mechanical angle for each generator Gx, from G1 to G10,</li> <li><em>VtGx</em> - stator voltage for each generator Gx, from G1 to G10,</li> <li><em>IdGx</em> - stator d-component current for each generator Gx, from G1 to G10,</li> <li><em>IqGx</em> - stator q-component current for each generator Gx, from G1 to G10,</li> <li><em>LAfvGx</em> - pre-fault power load angle for each generator Gx, from G1 to G10,</li> <li><em>LAlvGx</em> - post-fault power load angle for each generator Gx, from G1 to G10,</li> <li><em>PfvGx</em> - pre-falut value of the generator active power for each generator Gx, from G1 to G10,</li> <li><em>PlvGx</em> - post-falut value of the generator active power for each generator Gx, from G1 to G10,</li> <li><em>QfvGx</em> - pre-falut value of the generator reactive power for each generator Gx, from G1 to G10,</li> <li><em>QlvGx</em> - post-falut value of the generator reactive power for each generator Gx, from G1 to G10,</li> <li><em>VAfvBx</em> - pre-fault bus voltage magnitude in phase A for each bus Bx, from B1 to B39,</li> <li><em>VBfvBx</em> - pre-fault bus voltage magnitude in phase B for each bus Bx, from B1 to B39,</li> <li><em>VCfvBx</em> - pre-fault bus voltage magnitude in phase C for each bus Bx, from B1 to B39,</li> <li><em>VAlvBx</em> - post-fault bus voltage magnitude in phase A for each bus Bx, from B1 to B39,</li> <li><em>VBlvBx</em> - post-fault bus voltage magnitude in phase B for each bus Bx, from B1 to B39,</li> <li><em>VClvBx</em> - post-fault bus voltage magnitude in phase C for each bus Bx, from B1 to B39,</li> <li><em>Stability</em> - binary indicator (0/1) that determines if the power system was stable or unstable (0 - stable, 1 - unstable); this is the label variable.</li> </ul> <p><strong>License</strong>:<strong> </strong>Creative Commons CC-BY.</p> <p><strong>Disclaimer</strong>: This dataset is provided "as is", without any warranties of any kind.</p>
mofdscribe data - thermal stability
<p>Dataset used by the <a href="https://github.com/kjappelbaum/mofdscribe">mofdscribe software</a>.</p> <p>Contains a subset of the original data, as well as hashes and features.</p> <p><em>Not intended for direct use.</em></p>
Stability of the Modulator in a Plasma-Modulated Plasma Accelerator
<p>Input decks for the particle-in-cell code WarpX used in a new study to simulate the modulator stage of a recently proposed laser-plasma accelerator scheme [Phys. Rev. Lett. <strong>127</strong>, 184801 (2021)], dubbed the Plasma-Modulated Plasma Accelerator (P-MoPA). </p>
Static and Dynamic DFT Data Sets for Polymorphs of l-Cysteine - Stability and Terahertz Spectra
<p>Data sets associated with static and dynamic density functional calculations are reported for the four known polymorphs of l-cysteine and for models associated with the known disorder in Form I.. </p> <p>Static calculations are used to explore the relative free energies (within the harmonic approximation) of the polymorphs as a function of pressure. The energetics for dihedral angle rotation are explored and the barriers for rotation between the hydrogen bonding motifs have been calculated for each polymorph.</p> <p>Molecular dynamics calculations are reported for each polymorph and for models of hydrogen bond disorder which are known to exist at higher temperatures.</p> <p>Finally static and dynamic calculations of the infrared and terahertz spectra are performed.</p>
Data for: "A Route to Stabilize Uranium(II) and Uranium(I) Synthons in Multimetallic Complexes"
<p>Low valent uranium can be stabilized via an unprecedented mechanism involving intramolecular ligand migration:the two-and three-electron reduction of the oxo-bridgedU(IV)/U(IV)complex,[{(Ph3SiO)3(DME)U}2(O)], yields formal “U(II)”/U(IV) and “U(I)”/U(IV) complexes,via ligand migration and formation of uranium-arene δ-bond interactions,that can transfer up to threeelectrons tosubstrates by restoring the original ligand arrangement.</p>
Data and scripts to reproduce the results shown in "Stability of attractor local dimension estimates in non-Axiom A dynamical systems"
<p>Here we make available all the codes and datasets to reproduce the results of the paper "Stability of attractor local dimension estimates in non-Axiom A dynamical systems" by Flavio Pons, Gabriele Messori and Davide Faranda.</p> <p>The pre-print of the article is available at https://hal.science/hal-04051659/document.</p> <p>Any question/comment can be sent to flavio.pons@gmail.com.</p> <p>License for the codes and simulation/analysis results (*.Rda files): the code is shared under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license, see https://creativecommons.org/licenses/by-nc-sa/4.0/</p> <p>License and terms of use for the ERA5 data (z500_daily_euro.nc): the ERA5 500 hPa geopotential was downloaded from https://climexp.knmi.nl/start.cgi</p>
Simulation output for Improving the stability of bivariate correlations using informative Bayesian priors: A Monte Carlo simulation study
<p>This repository contains the (compressed) simulation output from <em>Improving the stability of bivariate correlations using informative Bayesian priors: A Monte Carlo simulation study</em>. On a Linux-based system, extract the contents with:</p> <pre><code class="language-bash">tar -xvzf raw_output_compressed.tar.gz </code></pre> <p>Please refer to the published article (https://doi.org/10.3389/fpsyg.2023.1253452) and the associated GitHub (<a href="https://github.com/carldelfin/stability-of-bivariate-correlations">github.com/carldelfin/stability-of-bivariate-correlations</a>) for additional information.</p>
DATASET: Protein Binding Leads to Reduced Stability and Solvated Disorder in the Polystyrene Nanoparticle Corona
<p>This dataset contains the DLS, CD, fluorescence, ITC, TEM, and ANS raw data used for the manuscript.</p>
The effect of normal stress oscillations on fault slip behavior near the stability transition from stable to unstable motion
<p>Tectonic fault zones are subject to normal stress variations with a wide range of spatio-temporal scales. Stress perturbations cover a wide range of frequencies and amplitudes from high frequency seismic waves generated by earthquakes to low frequency transients associated with solid Earth tides. These perturbations can reactivate critically stressed faults and trigger earthquakes. Here, we describe lab experiments to illuminate the physics of such changes in friction and the mechanics of earthquake triggering and fault reactivation. Friction tests were done in a double direct shear configuration for conditions near the stability transition from stable to unstable motion. We studied simulated fault gouge composed of quartz powder and conducted experiments at reference normal stress from 10 to 13.5 MPa. After shearing to steady state sliding, we applied sinusoidal normal stress oscillations of amplitude 0.5 to 2 MPa, and period of 0.5 to 50 s. We performed numerical simulations using measured values of rate/state friction (RSF) parameters to assess our data. Our results show that low frequency stress oscillations cause a Coulomb-like response of shear strength that transitions from stable slip to slow lab earthquakes as frequency increases. At the critical frequency predicted by RSF we observe periodic stick-slip behavior. Perturbations of high amplitude and short period weaken the fault, while lower amplitudes strengthen the fault. We find that a modified RSF formulation is able to accurately match our laboratory data. Our findings highlight the complex effects of stress perturbations for fault strength and the mode of fault slip.</p> <p>The data are uploaded are structured as follow:</p> <p>1) For each experiment a .txt file of the datafile that is recorded from the machine (raw data) and a binary file containing the elaborated data (data_rp). The experiments information are listed in experiment_info.txt</p> <p>2) The folder <a href="https://zenodo.org/api/files/89fe30fb-a2cb-4fcb-b9df-db80583fc652/codes_results.zip">codes_results.zip</a> contain the codes of the data analysis and the related results </p> <p>The data are analyzed using rawPy that can be found at <a href="https://github.com/marcoscuderi/rawPy">https://github.com/marcoscuderi/rawPy</a></p> <p>For any additional information please do not hesitate to contact the corresponding author Federico Pignalberi at federico.pignalberi@uniroma1.it</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.