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4,694 results for “data analysis”
Original data for "Unsupervised Analysis of Optical Imaging Data for the Discovery of Reactivity Patterns in Metal Alloy" article
<p>This upload includes both original and supplementary data for the publication "Unsupervised Analysis of Optical Imaging Data for the Discovery of Reactivity Patterns in Metal Alloy" by R. Li, A. Makogon, T. Galochkina, J-F. Lemineur, F. Kanoufi, and V. Shkirskiy, published in the Small Methods journal. The preprint version of the paper is available on ChemRxiv (<a href="https://doi.org/10.26434/chemrxiv-2023-sgvt0">https://doi.org/10.26434/chemrxiv-2023-sgvt0</a>).</p> <p>The file "Data_processing.zip" contains the original optical image of the interface, maps of film evolution rates in acidic and salt environments, COMSOL data output in acidic and salt environments, as well as a Jupyter Lab file that demonstrates how to process this data.</p> <p>The file "Comparison_of_SEM_images.zip" includes the original SEM images used in the current study and in our previous work (<a href="https://doi.org/10.26434/chemrxiv-2022-rn77b-v3">https://doi.org/10.26434/chemrxiv-2022-rn77b-v3</a>), along with a Jupyter Lab file that illustrates the data processing procedure.</p> <p>The file "Original_data_in_npy_format.zip" contains all original data from SEM/EDX and RM experiments.</p> <p>We recommend opening the Jupyter Lab files in a Python 3 environment. PDF files in the root directory provide outputs of all uploaded Jupyter Lab files.</p>
Data from: Optimisation design and analysis of mobile pump truck frame using response surface methodology
<p><span>In order to realize the lightweight design of mobile pump truck, this paper takes the frame of a certain type of mobile pump truck as the research object. The response surface method is used to carry out lightweight design of the longitudinal beam structure of the frame, and the finite element method is used to establish the finite element model to analyze and compare the frame before and after optimization.The results show that the height, width and thickness of the optimized longitudinal beam section are reduced by 10 mm, 11 mm, and 0.8 mm respectively, and the weight of the whole frame is reduced by 35.8 kg.</span> <span>Before and after optimization, the displacement and stress changes of the frame are small in four motion situations, which meet the lightweight requirements of optimization design.</span></p>
Data and analysis code of "Forestation at the right time with the right species can generate persistent carbon benefits in China"
<p>This collection contains the datasets used in our study ‘<strong><em>Forestation at the right time with the right species can generate persistent carbon benefits in China</em></strong>’.</p> <p> </p> <p><strong><em>Part A: Data</em></strong></p> <p>Most of the data presented here are after pre-processing, such as transforming the projection, extracting variables, clipping to the study region (70<sup>o</sup>E-140<sup>o</sup>E,15<sup>o</sup>N-55<sup>o</sup>N), and resampling to 1-km.</p> <p>The original source of these data sets (usually global, at different resolutions) is given in 'data_original.txt' as well as in the 'Data availability' of the main text.</p> <p>1. Climate_china_1km.7z: This compressed file contains the annual precipitation and temperature from Peng et al. 2019 at 1km.</p> <p>2. Soil_china_1km.7z: This compressed file contains the soil properties derived from Soilgrid250m for China at 1-km resolution.</p> <p>3. Topography_china_1km.7z: This compressed file contains the topographic properties derived from Global Multi-resolution Terrain Elevation Data 2010 for China at 1-km resolution.</p> <p>4. MaxEnt_process.7z: This compressed file contains all the input data and model results of the MaxEnt model: 1) environment layers in ’.asc’, 2) rarefied occurrence points for the 15 forest types, 3) MaxEnt results in ’.tif’ (average of the 10-folds results)</p> <p>5. Potential_china_forest_1km.7z: contains the potential forest distributions for China at 1-km resolution from multiple source (Random Forest, WRI and ORCHIDEE). Note: the forest distribution is in the form of logical variables in the .mat file, where a value of 1 or true means that the grid point is potentially forestable, and a value of 0 or false means this grid is not suitable for forest.</p> <p>6. Existing_china_forest_1km.7z: contains the existing forest distributions for China at 1-km resolution from multiple source (FI2013-2017, Hansen, MODIS, ESA-CCI, CNLUCC, GLC-FCS30 and GlobeLand30). Note: the existing forest distribution is in the form of logical variables in the .mat file, where a value of 1 or true means there is forest distribution, and a value of 0 or false means there is currently no forest distribution.</p> <p>7. Crop_urban_china_1km.7z: similar to the Existing_china_forest_1km.zip, but stores the distribution of cropland and urban.</p> <p>8. Masks_area_china_1km.7z: area mask and the shp files of the national and provincial boundaries of China.</p> <p>9. CMIP6_outputs.7z: contains historical (1970-2014) and future (2015-2100) climate and CO2 fertilization factor simulated by Earth System Models participating in CMIP6.</p> <p>10. Ori_carbon_all_grid_1km.mat: Living biomass carbon densities in 2010 for China at 1-km (unit: Mg C ha<sup>-1</sup>). Both aboveground and belowground biomass carbon values are included. The original biomass map is from Spawn et al. 2020.</p> <p>11. Forest_inventory_data_5th_9th.xlsx: 1) The forest area reported in 5th to 9th national forest inventory 2) The forest area of different age classes derived from the 9th national forest inventory.</p> <p>12. Forest_age_CN2019.7z: the forest stand age map for China updated to 2019.</p> <p>13. data_original.txt: the original source of these data sets</p> <p><strong>Part B: MATLAB Code</strong></p> <p>This file (Matlab_code.7z) contains the code, functions and parameters for our analysis of the data, mainly MATLAB files (.m or mat)</p> <p><strong>Part C: Demo/Example data and code</strong></p> <p>This file (Demo.7z) contains the demo of our code running, which includes the demo code along with code comments, input data for the demo, and the expected output results.</p> <p><strong>Part D: Docs</strong></p> <p>Reference and guidelines (Docs.7z).</p> <p>If you have any questions or suggestions, please contact xuhaotony@pku.edu.cn</p>
The second data release from the European Pulsar Timing Array I. The dataset and timing analysis
<p>Pulsar timing arrays offer a probe of the low-frequency gravitational wave spectrum (1−100 nanohertz), which is intimately connected to a number of markers that can uniquely trace the formation and evolution of the Universe. We present the dataset and the results of the timing analysis from the second data release of the European Pulsar Timing Array (EPTA). The dataset contains high-precision pulsar timing data from25 millisecond pulsars collected with the five largest radio telescopes in Europe, as well as the Large European Array for Pulsars. The dataset forms the foundation for the search for gravitational waves by the EPTA, presented in associated papers. We describe the dataset and present the results of the frequentist and Bayesian pulsar timing analysis for individual millisecond pulsars that have been observed over the last∼25 years.We discuss the improvements to the individual pulsar parameter estimates, as well as new measurements of the physical properties of these pulsars and their companions. This data release extends the dataset from EPTA Data Release 1 up to the beginning of 2021, with individual pulsar datasets with timespans ranging from 14 to 25 years. These lead to improved constraints on annual parallaxes, secular variation of the orbital period, and Shapiro delay for a number of sources. Based on these results, we derived astrophysical parameters that include distances, transverse velocities,binary pulsar masses, and annual orbital parallaxes.</p>
Data and Code Repository for Expanding non-target analysis methods to characterize the prenatal exposome
<p>Data and Code Repository for the following manuscript: Expanding non-target analysis methods to characterize the prenatal exposome. </p>
Data from: A comparative analysis of stably expressed genes across diverse angiosperms exposes flexibility in underlying promoter architecture
<p><span>Promoters regulate both the amplitude and pattern of gene expression—key factors needed for optimization of many synthetic biology applications. Previous work in <em>Arabidopsis</em> found that promoters that contain a TATA-box element tend to be expressed only under specific conditions or in particular tissues, while promoters which lack any known promoter elements, thus designated as Coreless, tend to be expressed more ubiquitously. To test whether this trend represents a conserved promoter design rule, we identified stably expressed genes across multiple angiosperm species using publicly available RNA-seq data. Comparisons between core promoter architectures and gene expression stability revealed differences in core promoter usage in monocots and eudicots. Furthermore, when tracing the evolution of a given promoter across species, we found that core promoter type was not a strong predictor of expression stability. Our analysis suggests that core promoter types are correlative rather than causative in promoter expression patterns and highlights the challenges in finding or building constitutive promoters that will work across diverse plant species.</span></p>
Complex I simulation data and analysis code
<p>NAMD simulation data and code used for analysis of WT and A52T Complex I:</p> <p>all CoQH2 steered trajectories</p> <p>all CoQ FEP trajectories</p> <p>unconstrained CoQ trajectories used in figure 2b</p> <p>Zipped files were renamed as (enclosing folder)--(name of zipped file). Enclose each set of zipped files in an appropriately name folder before unzipping.</p>
Data-driven transcriptomics analysis identifies PCSK9 as a novel key regulator in liver aging. (Histology Images)
<p>These are the histology images on "Data-driven transcriptomics analysis identifies PCSK9 as a novel key regulator in liver aging."</p>
Analyzing sources of error in TIRM experiments and data analysis.
<p>The datasets contain the experimental and simulated intensity traces underlying the figures published in the paper "Analyzing sources of error in TIRM experiments and data analysis." by J. A. Rivera-Moran and P. R. Lang in the MDPI Polymers Special issue "Interaction and Dynamics of Polymers and Colloidal Particles Near Interfaces".</p>
Supplemental data for 'Biophysical analysis reveals autophosphorylation as an important negative regulator of LRRK2 dimerization''
<p><strong>Supplemental mass photomerty raw data used in Figure 3</strong> of 'Guaitoli, G., Zhang, X., Saitta, F., Miglionico, P., Silbermann, L.M., Ho, F.Y., Zweydorf, F.v., Signorelli, M., Tych, K., Fessas, D., Raimondi, F., Kortholt, A., and Gloeckner, C.J. (2023). Biophysical analysis reveals autophosphorylation as an important negative regulator of LRRK2 dimerization. <em>bioRxiv</em>, 2023.2008.2011.549911 doi: 10.1101/2023.08.11.549911'</p> <p><strong>Raw data Figure 3A:</strong> Mass photometry raw data for LRRK2 wild-type in presence of different G-nucleotides at different LRRK2 concentrations. Three biological replicates have been considered for the statistical analysis.</p> <p><strong>Raw data Figure 3B: </strong>Mass photometry raw data for LRRK2 WT (left panel), LRRK2 WT + MLi-2 (middle panel) and kinase-dead LRRK2 (right panel) without and with ATP pre-incubation (-/+ ATP). Two biological and three technical replicates have been considered for the statistical analysis.</p> <p><strong>Raw data Figure 3C</strong><strong>:</strong> Mass photometry raw data for pathogenic LRRK2 variants in presence of different G-nucleotides. Two biological and two technical replicates have been considered for the statistical analysis<strong>.</strong></p> <p> </p>
Data from: Single-cell analysis identifies conserved features of immune dysfunction in simulated microgravity and spaceflight
<p>3-dimensional super-resolution microscopy volumes of human PBMCs recorded on a Zeiss LSM980 Airyscan2 laser scanning confocal microscope.</p> <p>Sample preparation and image capture:</p> <p>Live PBMCs were stained with 60 nM MitoTracker Red-CMX-Ros (ThermoFisher, Waltham, MA) either in 6-well plates or in the microgravity chambers for the last 2 hr of the microgravity simulation. At the end of the microgravity simulation cells were immediately fixed by 1:1 mixing the cell suspensions with 2× concentrated fixative (10% Sucrose (w/v) 120 mM KCl, 1% (w/v) glutaraldehyde, 8% (w/v) PFA pH 7.4) and incubated for 15 minutes at room temperature followed by 15 minutes on ice. Fixed cells were washed and stored in PBS until further staining for up to a week at 4 °C. 1 million fixed cells were resuspended in 1 mL of permeabilization solution (0.1% TritonX-100 in PBS) for 5 minutes. After twice washing in PBS, pellets were resuspended in 0.5 mL 1% BSA PBS containing Phalloidin-iFluor-488 (cat# ab176753, Abcam plc., Cambridge, UK) at the manufacturer’s recommended dilution, and were incubated for 90 minutes with gentle agitation. After washing in PBS, cells were stained with Hoechst 33342 (1 µg/mL in PBS) for 10 minutes. The fixed-stained cells were immobilized at 3 × 10<sup>5</sup> cells per well density in glass-bottom 96-well microplates (Greiner Bio-One, Monroe, NC), which were pre-coated with polyethyleneimine (1:15,000 (w/v)) for 16 hours in a 37 °C incubator, and washed twice with PBS. Microplates with the cell suspensions were centrifuged in a swing plate rotor centrifuge (Eppendorf 5810 R) at 400 × <em>g</em> and for 10 min and then fixed on the surface by adding an equal volume of 8% (w/v) PFA for 5 min. Finally, the fixative was replaced with 100 µL of antifade reagent (Vector Prolong Gold (ThermoFisher)). Samples were imaged immediately after this procedure on a Zeiss LSM980 Airyscan2 laser scanning confocal microscope (Carl Zeiss Microscopy, White Plains, NY). Single PBMCs were manually selected for recording based on low-resolution preview scans showing only nuclei. All singlet cells were selected in a small neighborhood to avoid biases. In each microscopy session, 24-40 cells were selected for recording in one well for each condition. This was performed in an interleaved manner, capturing 6-8 cells at a time, and then moving to the next well and then repeating this multiple times using the Experiment Designer module for automation. Super-resolution volumes of (358 × 358 × 70 pixels, 0.035 × 0.035 × 0.13 µm/voxel resolution) were recorded in the above-determined positions using Definite Focus autofocusing. A Plan-Apochromat 63 × 1.40 Oil lens, Airyscan2 SR (super-resolution) mode with optimal sampling and frame switching between 3 fluorescence channels to minimize spectral cross-bleed were used. MitoTracker Red, iFluor488, and Hoechs33342 were excited with 561, 488, and 405 nm solid-state lasers, respectively, using the optimal emission filter for each channel. 3D Airyscan2 processing was performed with standard filtering settings.</p> <p>File naming:</p> <p>Four zip files were deposited named as <Donor#id>.zip, where id goes from 1 to 4.</p> <p>Each zip file contains the following Zeiss Microscopy format image files: <Condition>_<Donor#id>_<Stain#batch>_<Cell>.czi</p> <p><Condition>:</p> <ul> <li>1G – Control culturing in 6-well plates for 25h</li> <li>uG – simulated microgravity culturing for 25h in NASA Rotating Wall Vessels</li> <li>1G+TLR – as above, with TLR 7/8 agonist (1 μM R848)</li> <li>uG+TLR– as above, with TLR 7/8 agonist (1 μM R848)</li> <li>1G+CyD– as above, with cytochalasin D</li> <li>uG+CyD– as above, with cytochalasin D</li> <li>1G+Q – as above, with quercetin 50µM</li> <li>uG+Q – as above, with quercetin 50µM</li> </ul> <p><Donor#id>: 1-4 indicates biological replicates</p> <p><Stain#batch>: 1-2 indicates experimental replicates of phalloidin staining and imaging session</p> <p><Cell>: arbitrary number to distinguish images within the same condition/donor/stain set.</p> <p>See image analysis pipelines used with these data at: https://github.com/gerencserlab/Superresolution-actin-and-mitochondria-analysis</p>
Dataset for "Scanning precession electron diffraction data analysis approaches for phase mapping of precipitates in aluminium alloys"
<p>Data needed to reproduce the results in "Scanning precession electron diffraction data analysis approaches for phase mapping of precipitates in aluminium alloys" published in Ultramicroscopy. The codes and notebooks can be found at 10.5281/zenodo.8321258.</p>
Summary data for "Young mixed planted forests store more carbon than monocultures: a meta-analysis"
<p>This is the dataset used in "Young mixed planted forests store more carbon than monocultures: a meta-analysis" published in Frontiers in Forests & Global Change. </p><p>The dataset contains carbon or biomass data for mixed and monoculture planted forests from 21 sites with a global coverage. We provide summary data necessary to conduct a meta-analysis: mean, standard deviation, and sample size, for each unique mixed and monoculture treatment at each study site. We indicate whether the values provided are aboveground carbon or biomass.</p><p>For each treatment we also provide the species richness, age and species. We provide the longitude, latitude and country for each study site.</p><p>Our study also assessed the effect of study design (experiment vs existing plantation), species origin (native vs non-native/mixed), and presence of nitrogen fixer in the mixture (N fixer present vs absent), we record the value of each of these factors. Finally, we categorised a subset of monocultures as commercial species monocultures based on the species use in that location. </p>
Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems
<p>Data for: Tracking and Analysis of the Movement Behavior of European Seabass (Dicentrarchus labrax) in Aquaculture Systems</p><p>Please read the README.txt file before working with the data.</p>
Supplementary data for "DNATCO v5.0: Integrated Web Platform for 3D Nucleic Acid Structure Analysis"
<p>Supplementary data for "DNATCO: efficient and accurate analysis of nucleic acid structures"</p> <p>The data in "dnatco.datmos.org_1ehz_4qvi_5hix.zip" contains the DNATCO-annotated extended mmCIF files, full validation reports and NtC-specific restraint files for the three example PDB structures (1ehz, 4qvi, and 5hix) is deposited.</p> <p>A snapshot of the core structure processing library source code from the https://github.com/cernylab/libLLKA repository is included in the "libLLKA-main.zip" file.</p> <p>The fully offline multi-platform CLI version of the dnatco.datmos.org using Node.js is provided in the "dnatco.zip" file</p>
Real-world Data Analysis of REN Treatment in Adolescence With Migraine
ClinicalTrials.gov study NCT05443659. IPD Sharing: NO. Countries: 2. Publications: 7.
Treatment Patterns With Targeted Therapies In Mrcc In Sweden - A Retrospective Analysis Of Data From National Registries
ClinicalTrials.gov study NCT04669366. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Resilience of an integrated crop-livestock system to climate change: a simulation analysis of cover crop grazing in southern Brazil
Open the record for dataset details and reuse information.
Data and analysis scripts for: Asymmetrical reproductive barriers in sympatric Jewelflowers: are floral isolation, genetic incompatibilities, and floral trait displacement connected?
Open the record for dataset details and reuse information.
Flow virometry for water-quality assessment: Protocol optimization for a model virus and automation of data analysis
Open the record for dataset details and reuse information.
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.