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3,206 results for “property (T)”
Datasets for understanding the importance of conformation in property prediction models
<p>Descriptor and conformer data sets for molecular property and reaction selectivity prediction tasks. The PQC data set was created based on a part of the PubChemQC PM6 dataset (J. Chem. Inf. Model. 2020, 60, 12, 5891–5899), which contains two- and three-dimensional descriptors and conformers. The APTC data sets are based on the data sets for asymmetric phase transfer catalysts with enantio-selectivity (<a href="https://github.com/Laboratoire-de-Chemoinformatique/3D-MIL-QSSR/tree/main/datasets" target="_blank" rel="noopener">https://github.com/Laboratoire-de-Chemoinformatique/3D-MIL-QSSR/tree/main/datasets</a>). The melting point data set was created from the Jean-Claude Bradley Double Plus Good (Highly Curated and Validated) Melting Points Dataset (<a href="https://doi.org/10.6084/m9.figshare.1031638.v1">https://doi.org/10.6084/m9.figshare.1031638.v1</a>).</p> <p>They contained descriptors and conformers to train and validate machine learning models.</p> <p>Detailed explanations on how to use these datasets are found in the Github repository: <a href="https://github.com/YuHamakawa/Conformation-Importance-ML-Models">https://github.com/YuHamakawa/Conformation-Importance-ML-Models</a>. </p> <p> </p> <p> </p>
Morphological profiling data resource enables prediction of chemical compound properties
<p><span><span>Morphological profiling with the Cell Painting assay has </span><span>emerged</span><span> as a promising method in drug discovery research. The assay captures morphological changes across various cellular compartments enabling the rapid prediction of compound </span></span><span><span><span>bioactivity</span></span></span><span><span>. We present a comprehensive morphological profiling resource using the carefully curated and well-annotated EU-OPENSCREEN Bioactive Compounds. </span><span>The data was generated across four imaging sites with high-throughput confocal microscopes using the </span><span>Hep</span><span> G2 as well as the U2 OS cell line.</span><span> We employed an extensive assay optimization process to achieve high data quality across the different sites. An analysis of the extracted profiles </span><span>validates</span><span> the robustness of the generated data. <span>We used this resource to compare the morphological features of the different cell lines. By correlating the profiles with overall activity, cellular toxicity, several specific mechanisms of action (MOAs), and protein targets, we </span><span>demonstrate</span><span> the dataset's potential for </span><span>facilitating</span><span> more extensive exploration of mechanisms of action.</span> </span></span></p>
Red rice bran polyphenols suppress invasive properties of HepG2 cells, possibly through Wnt/β-catenin-mediated EMT reversal.
<p>Data collection in its raw form is performed in a specific sequence dictated by the manuscript.</p>
Dataset and statistical analysis related to "Amphibian studies to investigate the endocrine disrupting properties of chemicals through the Thyroid modality: a comparison of their statistical power"
Open the record for dataset details and reuse information.
Geometry and segmentation of Cerberus Fossae, Mars: implications for marsquake properties.
<p>The dataset is made of three different files:</p> <p>- <a href="https://zenodo.org/api/files/3cf0564e-08ba-4561-b383-7db9438f6296/Perrin-et-al-Calculated-DEMs.zip">Perrin-et-al-Calculated-DEMs.zip </a>: we use HiRISE stereo pair images (https://www.uahirise.org/) to compute high-resolution DEMs along the Cerberus Fossae system using the SOCET SET mapping software (©BAE Systems). The stereo images are selected at different locations on the fossae in order to get an overall view of the lateral variation of the morphology along the Cerberus Fossae system. Stereo pairs were identified through ISIS image processing software package (USGS). They are calibrated based on the HiRISE camera specifications, corrected from jitter effects by the USGS ISIS software and then implemented into SOCET SET. Bundle adjustment is made in an absolute reference frame defined by MOLA. The coarser first iteration of DEM calculation is seeded on the gridded MOLA elevations at a resolution of 2 m/pixel. It is then followed by a refined DEM computation at higher resolution (up to 1 m/pixel). Post-processing DEM corrections are performed on outlying points to discard aberrant calculations.</p> <p>- <a href="https://zenodo.org/api/files/3cf0564e-08ba-4561-b383-7db9438f6296/Perrin-et-al-SegmentationFig4.xlsx">Perrin-et-al-SegmentationFig4.xlsx</a>: list of the segment names and lengths that have been identified along Cerberus Fossae, Mars.</p> <p>- <a href="https://zenodo.org/api/files/3cf0564e-08ba-4561-b383-7db9438f6296/Perrin-et-al-Width-Throw-Fig9.xlsx">Perrin-et-al-Width-Throw-Fig9.xlsx</a>: measurements of widths and throws performed along Cerberus Fossae (Graben 1). Throw measurements are from Vetterlein and Roberts 2010 (MOLA data). Width measurements have been done using CTX images. Wa, Wt and Wb are respectively apparent widths, and widths measured at the top and the bottom of inferred fault scarps (i.e., steepest slopes).</p> <p>See Perrin et al., submitted to JGR Planets 2021 for details.</p>
Tapioca starch gelatinization properties monitored by TD-NMR and complementary techniques
<p>Tapioca starch gelatinization properties monitored by TD-NMR and complementary techniques</p>
Single-scattering properties of ice particles in the microwave regime: Temperature effect on the ice refractive index with implications in remote sensing
<p>This database is from the paper: Ding, J., L. Bi, P. Yang, G. W. Kattawar, F. Weng, Q. Liu, and T. Greenwald, 2017: Single-scattering properties of ice particles in the microwave regime: temperature effect on the ice refractive index with implications in remote sensing, Journal of Quantitative Spectroscopy & Radiative Transfer, 190, 26-37. DOI: 10.1016/j.jqsrt.2016.11.026.</p>
Dataset for "Diurnal variations of cloud optical properties during day-time over China based on Himawari-8 satellite retrievals"
<p>Dataset for "Diurnal variations of cloud optical properties during day-time over China based on Himawari-8 satellite retrievals".</p>
Spatial autocorrelation shapes liana distribution better than topography and host tree properties in a subtropical evergreen broadleaved forest in SW China
<p>Lianas are an important component of subtropical forests, but the mechanisms underlying their spatial distribution patterns have received relatively little attention. Here, we selected 12 most abundant liana species, constituting up to 96.9% of the total liana stems, in a 20-ha plot in a subtropical evergreen broadleaved forest at 2,472 – 2,628 m elevation in SW China. Combining data on topography (convexity, slope, aspect, and elevation) and host trees (density and size) of the plot, we addressed how liana distribution is shaped by host tree properties, topography and spatial autocorrelation by using principal coordinates of neighbor matrices (PCNM) analysis. We found that lianas had an aggregated distribution based on the Ripley's <i>K</i> function. At the community level, PCNM analysis showed that spatial autocorrelation explained 43% variance in liana spatial distribution. Host trees and topography explained 4% and 18% of the variance, but less than 1% variance after taking spatial autocorrelation into consideration. A similar trend was found at the species level. These results indicate that spatial autocorrelation might be the most important factor shaping liana spatial distribution in subtropical forest at high elevation.</p>
Model output for "Groundwater affects the geomorphic and hydrologic properties of coevolved landscapes"
<p>Model output supporting "Groundwater affects the geomorphic and hydrologic properties of coevolved landscapes" in JGR Earth Surface, DOI:10.1029/2021JF006239. The Python package DupuitLEM v1.0-beta (DOI:10.5281/zenodo.5522828) contains the models and scripts used to generate and post-process output.</p>
Dataset for Co-substituted BiFeO3: thermodynamic, electronic and ferroelectric properties from first principles
<p>Data files related to the publication<em><strong> Co-substituted BiFeO<sub>3</sub>: thermodynamic, electronic and ferroelectric properties from first principles</strong></em>. The paper is yet to be submitted. The dataset includes, (i) VASP input/output files for electronic structure and polarization calculations and (ii) GULP files for the thermodynamic study. </p>
Vertical profiles of 3D cluster properties
<p>The two zip files contain the properties of the 3D clusters used in the submission version of the Paper "Size-dependence of surface-rooted three-dimensional convective objects in continental shallow cumulus simulations". The paper was submitted to JAMES in May 2021.</p> <p>When unzipped, the data is stored in python panda dataframes in pkl files. Warning! Unzipping the files increases the data size by a factor of 20.</p> <p>The two python scripts contain the functions used to segment the 3D snapshots into individual objects. The most interesting things are in proc_watershed, cusize_functions is just a collection of mostly abandoned functions. The functions in proc_watershed are reasonably well commented.</p>
Analytical prediction of scattering properties of spheroidal dust particles with machine learning
<p>This respository includes the data used in the paper "Analytical prediction of scattering properties of spheroidal dust particles with machine learning".</p> <ol> <li>"alldata.zip" represents the extinction and absorption coefficients, and phase matrix elements of spheroids dust particles for both training and test data. These data comes from the Oleg Dubovik's group: <a href="https://www.grasp-open.com/products/spheroid-package-release">https://www.grasp-open.com/products/spheroid-package-release</a>/.</li> <li>"<a href="/api/files/7c2cdcdd-dc47-4a19-adc8-59c944e76e54/tmat_Jacall_norm_intg.pickle?versionId=59294030-26a8-4683-9b26-8e8584c2b44b">tmat_Jacall_norm_intg.pickle</a>" contains the Jacobians simulated from linearized T-matrix model used for training in the paper and "<a href="/api/files/7c2cdcdd-dc47-4a19-adc8-59c944e76e54/tmat_fine_n_intg.pickle?versionId=3d20954d-4318-40bb-a900-a93627915c2e">tmat_fine_n_intg.pickle</a>" involves Jacobians used for testing.</li> </ol>
Nanoprobes for Biomedical Imaging with Tunable Near-Infrared Optical Properties Obtained via Green Synthesis
<p>Dataset of: 10.1002/adpr.202100260</p>
Table with mechanical properties of TPS/PCL blends.
<p>Table containing micro- and macromechanical properties of TPS/PCL polymer blends.</p> <p>Format: Zipped MS Excel file; description of the data is directly inside the file.</p>
Dataset of "Nonlinear Wave-Particle Interaction is Suppressed by Realistic Properties of Chorus Waves"
<p>Dataset of "Nonlinear Wave-Particle Interaction is Suppressed by Realistic Properties of Chorus Waves", including waveforms of the input PIC-generated chorus wave field (WF_{PIC}) recorded at certain magnetic latitudes, and the evolution of electrons' equatorial pitch angle with magnetic latitude.</p>
Code for GMD publication - Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018
<p>In this repository, we include the source codes for WRF microphysics parameterization used in the GMD publication "Simulated microphysical properties of winter storms from bulk-type microphysics schemes and their evaluation in WRF (v4.1.3) model during ICE-POP 2018."</p> <p>The four 2-moment bulk microphysical parameterization codes, WDM6, WDM7, Thompson, and Morrison, are divided into 3 WDM, Thompson, and Morrison codes, and each code has been modified so that detailed microphysical processes can be checked in wrfout.</p> <p>The WDM6 and WDM7 schemes include numerical errors for ice microphysical parameterization (Kim and lim, 2021) and for cloud evaporation and melting processes (Lei et al., 2020).</p> <p>Namelist files shows the namelist.input for each case.</p> <p> </p> <p> </p>
Data from: Multi-decadal changes in phytoplankton biomass in northern temperate lakes as seen through the prism of landscape properties
<p>Ecologists collectively predict that climate change will enhance phytoplankton biomass in northern lakes. Yet there are unique variations in the structures and regulating functions of lakes to make this prediction challengeable and, perhaps, inaccurate. We used archived Landsat TM/ETM+ satellite products to estimate epilimnetic chlorophyll-<i>a </i>concentration (Chl-<i>a</i>) as a proxy for phytoplankton biomass in 281 northern temperate lakes over 28 years. We explored the influence of climate (air temperature, precipitation) and landscape proxies for nutrient sources (proportion of wetlands in a contributing catchment, size of the littoral zone, potential for wind-driven sediment resuspension as estimated by the dynamic ratio) or nutrient sinks (lake volume) in a random forest model to explain heterogeneity in peak Chl-<i>a</i>. Lakes with higher Chl-<i>a</i> (median Chl-<i>a</i> = 2.4 μg L<sup>-1</sup>, n = 40) had smaller volumes (< 44 × 10<sup>4</sup> m<sup>3</sup>) and were more sensitive to increases in temperature. In contrast, lakes with lower Chl-<i>a</i> (median Chl-<i>a</i> = 0.6 μg L<sup>-1</sup>, n = 241) had larger volumes (≥ 44 × 10<sup>4</sup> m<sup>3</sup>), contributing catchments with smaller proportions of wetlands (< 4.5% of catchment area, n = 70), smaller littoral zones (< 16.4 ha, n = 137), minimal wind-driven sediment resuspension (as defined by the dynamic ratio; < 0.45, n = 232), and were more sensitive to increases in precipitation. Lakes with larger volumes were generally less responsive to climate factors; however, large volume lakes with a significant proportion of wetlands and larger littoral zones behaved similarly to lakes with smaller volumes. Our finding that lakes with different landscape properties respond differently to climate factors may help predict the susceptibility of lakes to eutrophication under changing climate conditions.</p>
Dataset for "Zinc Germanium Nitrides and Oxide Nitrides: The Influence of Oxygen on Electronic and Structural Properties."
<p>Input files for the Quantum Espresso structure optimisations "*-relax.scf.in" and 12 x 12 x 12 MP-grid SCF "*-large-grid.scf.in" as well as lobster input files "*-lobsterin"</p>
Translation, cross-cultural adaptation, and evaluation of psychometric properties of cystic fibrosis stigma scale
<pre>Search database</pre>
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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.