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10,735 results for “dependability”
Projection matrices for numerical examples of "An adaptive model order reduction technique for parameter-dependent modular structures"
<p>This data set contains supplementary data for the paper:<br> 'An adaptive model order reduction technique for parameter-dependent modular structures'</p> <p>The Authors are:<br> Stephan Ritzert (a), Domen Macek (a), Jaan-Willen Simon (b), Stefanie Reese (a)</p> <p>Affiliations:<br> (a) Institute of Applied Mechanics, RWTH Aachen University, Mies-van-der-Rohe-Str. 1, 52074 Aachen, Germany<br> (b) Civil Engineering Mechanics, University of Wuppertal, Pauluskirchstr. 7, 42285 Wuppertal, Germany</p> <p>Contact: stephan.ritzert@ifam.rwth-aachen.de</p> <p>### The Dataset ###</p> <p>The dataset contains all mesh files and all projection matrices used for the numerical examples 2,3, and 4.</p> <p>Example 2: Naming of projections matrices<br> -Square: The projection matrices depend on the parameter alpha: {0,5,10,...,90}<br> The name of the projection matrix is 'PsiTransIso' + alpha + '.txt'</p> <p> -Rectangle: The projection matrices depend on the parameter alpha: {0,5,10,...,180}, and the length lx: {600,700,800,900,1000,1100,1200}<br> The name of the projection matrix is 'PsiTransIso' + alpha + '-' + lx + '.txt'</p> <p>Example 3: Naming of projections matrices<br> -Square: The projection matrices depend on the parameter alpha: {0,5,10,...,90}<br> The name of the projection matrix is 'PsiTransIso' + alpha + '.txt'</p> <p> -Rectangle: The projection matrices depend on the parameter alpha: {0,5,10,...,180}, and the length lx: {600,700,800,900,1000,1100,1200}<br> The name of the projection matrix is 'PsiTransIso' + alpha + '-' + lx + '.txt'</p> <p><br> Example 4: Naming of projections matrices<br> -curved: The projection matrices depend on the parameter phi: {20,30,...,90}<br> The name of the projection matrix is 'PsiIso' + phi + '.txt'</p> <p> -rectangle: The projection matrices depend on the parameter lx: {600,800,1000,1200}<br> The name of the projection matrix is 'PsiIso' + lx + '.txt'</p> <p> </p> <p> </p>
Domain-dependent strain and stacking in two-dimensional van der Waals ferroelectrics
<p>The sample is PVD growth 2D vdW ferroelectric SnSe (Chiu, M. <i>et al.</i> <i>Adv. Electron. Mater.</i> <strong>9</strong>, (2023)). The datasets were collected by electron microscope pixel array detector (EMPAD) under the condition described in this paper (Shi, C. <i>et al.</i> <i>Nat. Commun.</i> <strong>14</strong>, 7168 (2023)). The data analysis code is available in https://github.com/Chuqiao2333/2D_ferroelectric_SnSe </p>
Data of "An enhanced lattice beam element model for the numerical simulation of rate-dependent self-healing in cementitious materials"
Open the record for dataset details and reuse information.
Effects of mitochondrial stress on intestinal tumor development depends on Apc status
<p>Mitochondrial stress triggers both metabolic and transcriptomic reprogramming but its effects on tumor development remains unclear. It is also unknown whether the genetic status has any influence on the capacity of mitochondrial stress to control tumor development. To explore these issues, we generated a mouse model lacking the lipid transfer protein Stard7 in intestinal epithelial cells (IECs) and assessed tumor development in both Wnt-dependent tumor initiation and in inflammation-driven tumor development. The loss of Stard7 in both models of intestinal tumors impaired mitochondrial Complex I activity, led to a severe metabolic and lipidomic reprogramming and potentiated mTORC1 activation. As a result, levels of enzymes involved in serine biosynthesis were enhanced in Stard7-deficient IECs showing or not constitutive Wnt signaling. Strikingly, despite similar molecular signatures upon Stard7 deficiency in intestinal crypts showing or not constitutive Wnt signaling, Stard7 contributed to tumor development in AOM/DSS-treated mice but inhibits Wnt-driven cancer initiation in the intestine. Apc+/Min mice lacking Stard7 in IECs developed more tumors in the distal colon. Collectively, our results suggest that the Apc genetic status critically controls the effects of mitochondrial stress on intestinal tumor development.</p>
Pulsed 193 nm Excimer laser processing of 4H-SiC(0001) wafers with radiant exposure dependent "in situ" reflectivity studies for process optimization.
<p>Conference paper</p>
Data for manuscript: Temperature dependence of the magnon-phonon interaction in high overtone bulk acoustic resonator-ferromagnetic thin film hybrids
<p>Data of the figures for the manuscript:</p> <p>"Temperature dependence of the magnon-phonon interaction in high overtone bulk acoustic resonator-ferromagnetic thin film hybrids"</p> <p>Identifier: https://doi.org/10.1103/PhysRevApplied.21.034032</p>
Dexamethasone induces sleep disturbance in a dose-dependent manner in mice
<p>This is the data set indicated in <i>Kato et al, 2023, PLOS ONE</i> (DOI: <a href="10.1371/journal.pone.0296028">10.1371/journal.pone.0296028</a>).</p>
Immunophenotypic Alterations in Adult Patients with Steroid-Dependent and Frequently Relapsing Nephrotic Syndrome
<p>Percentages of circulating B and T cell subsets in patient groups and in healthy volunteers</p>
Figure 7 from: Tanaka S (2024) Temperature-dependent phototaxis in overwintering adults of the grasshopper Patanga japonica (Orthoptera, Acrididae). Journal of Orthoptera Research 33(1): 71-86. https://doi.org/10.3897/jor.33.102749
Figure 7 Outdoor enclosure (48 × 80 × 30 cm) for observation of behavior of P. japonica adults.
Figure 1 from: Tanaka S (2024) Temperature-dependent phototaxis in overwintering adults of the grasshopper Patanga japonica (Orthoptera, Acrididae). Journal of Orthoptera Research 33(1): 71-86. https://doi.org/10.3897/jor.33.102749
Figure 1 Tube used to observe daily behavior of P. japonica adults.
The Grouping-Induced Numerosity Illusion Is Attention-Dependent
<p>Data set for generating the figures</p>
Pupillometry correlates of visual priming, and their dependency on autistic traits
<p>Data set for generating the figures with a file pf explanation accompanying </p>
The height-dependent delayed ionospheric response to solar EUV - data comparison - secondary files 123 - 128
<p><strong>Secondary files for doy 123 - 128</strong></p> <p>For comparison with the observational results a TIE-GCM v2.0 model run in the 2.5 × 2.5 configuration is calculated. In order to converge to stable initial condition the model runs for 30 days prior to the final simulation starting at 28 March 2019. This initial run is configured with default parameters. The final run from 27 April 2019 to 24 May 2019 uses the default configuration of TIE-GCM with the Heelis Electric Convection Field Model (Heelis et al., 1982) as the high-latitude potential model. The input forcing is used from the NASA/GSFC’s OMNI data set</p>
Experimental tests of pollinator dependence in Avicennia germinans, the black mangrove
<p><em>Avicennia germinans </em>(L.) L. (Black Mangrove) is a common, sometimes dominant member of intertidal vegetation in tropical and subtropical regions of the Americas and West Africa. Its flowers are known to be attractive to animals – there are records of a variety of floral visitors – and it is widely believed to be zoophilous, but the degree to which it relies on pollinators for full fruit set is not entirely clear. Molecular methods have revealed that <em>A. germinans</em> is self-compatible; however, it has not been definitively shown whether this self-pollination occurs via spontaneous autogamy, via pollinator-mediated fertilization of flowers with either their own pollen or pollen from neighboring flowers on the same plant (geitonogamy), or via both mechanisms. This study's objective was to assess the ability of <em>A. germinans</em> to spontaneously self-pollinate, and to determine if <em>A. germinans </em>is capable of setting fruit in the absence of pollinators.</p>
Figure 3 from: Shoman ME, Abd El-Hafeez AA, Khobrani M, Assiri AA, Al Thagfan SS, Othman EM, Ibrahim ARN (2022) Molecular docking and dynamic simulations study for repurposing of multitarget coumarins against SARS-CoV-2 main protease, papain-like protease and RNA-dependent RNA polymerase. Pharmacia 69(1): 211-226. https://doi.org/10.3897/pharmacia.69.e77021
Figure 3 Structure of naturally occurring coumarins 13–37 reported possessing antiviral activity.
Figure 2 from: Shoman ME, Abd El-Hafeez AA, Khobrani M, Assiri AA, Al Thagfan SS, Othman EM, Ibrahim ARN (2022) Molecular docking and dynamic simulations study for repurposing of multitarget coumarins against SARS-CoV-2 main protease, papain-like protease and RNA-dependent RNA polymerase. Pharmacia 69(1): 211-226. https://doi.org/10.3897/pharmacia.69.e77021
Figure 2 Structure of some coumarin drugs 4–13.
Figure 1 from: Shoman ME, Abd El-Hafeez AA, Khobrani M, Assiri AA, Al Thagfan SS, Othman EM, Ibrahim ARN (2022) Molecular docking and dynamic simulations study for repurposing of multitarget coumarins against SARS-CoV-2 main protease, papain-like protease and RNA-dependent RNA polymerase. Pharmacia 69(1): 211-226. https://doi.org/10.3897/pharmacia.69.e77021
Figure 1 Structure of Aminocoumarin antibiotics Novobiocin, Clorobiocin, and Coumermycin.
Code, benchmarks and experiment data for the AAAI 2019 paper "Deep Learning for Cost-Optimal Planning: Task-Dependent Planner Selection"
<p>This bundle contains code, scripts and benchmarks for reproducing all experiments reported in the paper. It also contains the data generated for the paper. Except for the code base, it contains the same files as the Zenodo entry for our IPC 2018 planner Delfi: https://zenodo.org/record/6683892.</p> <p>sievers-et-al-aaai2019-fast-downward.zip contains the implementation based on Fast Downward. It also contains the experiment scripts (hopefully) compatible with Lab 2.1 for reproducing all experiments of the paper, under experiments/ipc2018. While this code base contains a few more scripts used for this AAAI paper compared to the IPC 2018 code, it hasn't been updated to contain, e.g., a requirements.txt file for setting up a Python virtual environment like we did for our IPC 2018 planners. Please see katz-et-al-ipc2018-delfi1.zip and katz-et-al-ipc2018-delfi2.zip in the above mentioned Zenodo entry.</p> <p>sievers-et-al-aaai2019-scripts.zip contain all scripts for the learning pipeline used to train the planner selection models.</p> <p>sievers-et-al-aaai2019-benchmarks.zip contains the benchmarks. It consists of the IPC benchmarks used in all optimal sequential tracks of IPCs up to 2014 (suite optimal from https://github.com/aibasel/downward-benchmarks).</p> <p>sievers-et-al-aaai2019-lab.zip contains a copy of Lab 2.1 (https://github.com/aibasel/lab).</p> <p>sievers-et-al-aaai2019-raw-data.zip and sievers-et-al-aaai2019-parsed-data.zip contain the experimental data. Directories in sievers-et-al-aaai2019-raw-data.zip (without the "-eval" ending) contain raw data, distributed over a subdirectory for each experiment. Each of these contain a subdirectory tree structure "runs-*" where each planner run has its own directory. For each run, there are symbolic links to the input PDDL files domain.pddl and problem.pddl (can be resolved by putting the benchmarks directory to the right place), the run log file "run.log" (stdout), possibly also a run error file "run.err" (stderr), the run script "run" used to start the experiment, and a "properties" file that contains data parsed from the log file(s). Directories in sievers-et-al-aaai2019-parsed-data.zip (with the "-eval" ending) contain a "properties" file, which contains a JSON directory with combined data of all runs of the corresponding experiment. In essence, the properties file is the union over all properties files generated for each individual planner run.</p> <p>The image data set used for training can be found online: https://github.com/IBM/IPC-image-data</p> <p>Note on license: we chose GPL v3.0 or later mainly because we consider our implementation based on Fast Downward the main contribution of this package, and Fast Downward comes with GPL v3.0. We only include a copy of Lab and the benchmarks for convenience.</p>
An updated metal-dependent theoretical scenario for Classical Cepheids (full sample of theoretical light curves converted in Johnsons, Gaia and HST-WFC3 filters))
<p>Converted_light_curves --> Main directory containing 4 subdirectories Z0p004, Z0p008, Z0p02, and Z0p03 for the four different analyzed chemical compositions</p> <p> </p> <p>Z0p004--> directory containing results for a metallicity Z=0.004 and Helium content Y=0.25</p> <p>Z0p008--> directory containing results for a metallicity Z=0.008 and Helium content Y=0.25</p> <p>Z0p02--> directory containing results for a metallicity Z=0.02 and Helium content Y=0.28</p> <p>Z0p03--> directory containing results for a metallicity Z=0.03 and Helium content Y=0.28</p> <p>Inside each of these 4 subdirectories are two subdirectories 'curves_F' and 'curves_FO' for the two analyzed pulsational modes, fundamental (F) and first overtone (FO).</p> <p>Inside 'curves_F' and 'curves_FO' are the files of the bolometric light curves converted into the Gaia EDR3 filters, G, GBP, and GRP, the HST WFC3 filters F110W, F160W, F814W, F125W, F475W, F606W and F555W and the Johnson-Cousins bands U, B, V, R, J, H, K.</p> <p>The file names are tokenized as follows.</p> <p>curves_token1_token2_token3_token4_token5_token6_token7_token8_token9.csv'</p> <p> </p> <p>where</p> <p>token1 is the effective temperature in Kelvin</p> <p>token2 is the logarithmic luminosity in solar units</p> <p>token3 is the stellar mass in solar units</p> <p>token4 is the mixing length value</p> <p>token5 is the ML relation assumption (See text for more details)</p> <p>token6 is the period in days</p> <p>token7 is the chemical composition</p> <p>token8 is the pulsational mode</p> <p>token9 is the photometric passband</p> <p> </p> <p>Inside each curves’ file, the various columns represent the time in seconds, the bolometric magnitude, and the converted magnitudes in the aforementioned bands.</p>
Spectral Emission Dependence of Tin-Vacancy Centers in Diamond from Thermal Processing and Chemical Functionalization
<p>A systematic photoluminescence (PL) investigation of the spectral emission properties of individual optical defects fabricated in diamond upon ion implantation and annealing is reported. Three spectral lines at 620, 631, and 647 nm are identified and attributed to the SnV center due to their occurrence in the PL spectra of the very same single-photon emitting defects. It is shown that the relative occurrence of the three spectral features can be modified by oxidizing the sample surface following thermal annealing. The relevant emission properties of each class of individual emitters, including the excited state emission lifetime and the emission intensity saturation parameters are reported.</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.