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6,467 results for “process”
Data files for 'Tan et al., (2023). Structural heterogeneity-controlled rupture process of the 2021 Mw 7.1 Fukushima, Japan earthquake revealed by joint inversion of seismic and geodetic data'
<p>slip model.dat: rupture model of the 2021 Mw 7.1 Fukushima earthquake</p> <p>In 'slip model.dat', each row contains the moment rate function of each sub-fault. The numbers of the sub-faults are given in the first two columns.</p>
Performance and process-based evaluation of BARPA-R
<p>Supporting data for figures in GMD draft paper: Performance and process-based evaluation of BARPA-R</p>
Data to Deliverable 3.4 - Co-creation process for innovative planning and governance able to facilitate the transition to a water circular economy
<p>Transcription of co-creation workshops; Worksheets filled by groups of the co-creation workshops; and final worksheets filled of the co-creation workshops.<br> </p>
Data from: Remotely sensed environmental measurements detect decoupled processes driving population dynamics at contrasting scales
<p class="MsoNormal">The increasing availability of satellite imagery has supported a rapid expansion in forward-looking studies seeking to track and predict how climate change will influence wild population dynamics. However, these data can also be used in retrospect to provide additional context for historical data in the absence of contemporaneous environmental measurements. We used 167 Landsat-5 Thematic Mapper (TM) images spanning 13 years to identify environmental drivers of fitness and population size in a well-characterized population of banner-tailed kangaroo rats (<em>Dipodomys spectabilis</em>) in the southwestern United States. We found evidence of two decoupled processes that may be driving population dynamics in opposing directions over distinct time frames. Specifically, increasing mean surface temperature corresponded to increased individual fitness, where fitness is defined as the number of offspring produced by a single individual. This result contrasts with our findings for population size, where increasing surface temperature led to decreased numbers of active mounds. These relationships between surface temperature and (i) individual fitness and (ii) population size would not have been identified in the absence of remotely sensed data, indicating that such information can be used to test existing hypotheses and generate new ecological predictions regarding fitness at multiple spatial scales and degrees of sampling effort. To our knowledge, this study is the first to directly link remotely sensed environmental data to individual fitness in a nearly exhaustively sampled population, opening a new avenue for incorporating remote sensing data into eco-evolutionary studies.</p>
Fig. 3 in Characteristics of thermal processes in ant nests built under stones (Hymenoptera: Formicidae)
Fig. 3 – Temperature distribution for stone No. 2 on 06/19/2021.
A multi-model ensemble of baseline and process-based models improves the predictive skill of near-term lake forecasts: data, forecasts, and scores
<p>This data publication contains zipped parquet from the Falling Creek Reservoir multi-model ensemble (MME) forecasting work using the FLARE (Forecasting Lake And Reservoir Ecosystems) system and baseline models: drivers.zip contains NOAA driver forecast files, targets.zip contains in-situ water temperature observations, forecasts.zip contains forecast parquet files generated from the MME workflow (FLARE & baseline models), and scores.zip contains forecast skill metrics required for analysis.</p>
Dataset - Removal of diclofenac by adsorption process studied in free-base porphyrins Zr-metal organic frameworks (Zr-MOFs)
<p>Dataset for the paper entitled "Removal of diclofenac by adsorption process studied in free-base porphyrins Zr-metal organic frameworks (Zr-MOFs) "</p>
Hyperspectral Placenta Dataset: Hyperspectral Image Acquisition, Annotations, and Processing of Biological Tissues in Microsurgical Training
<p>The dataset consists of 101 hyperspectral images of four fresh human placentas and six hyperspectral images of contrast dyes (i.e., indocyanine green and red and blue food colorant) that were captured in the range 515-900 nm, step = 5 nm. The hyperspectral images were manually annotated, delineating the key anatomical structures: arteries, veins, stroma, and the umbilical cord. Standard reference materials were used for flat-field correction. The dataset can be used to develop machine learning algorithms for the automated classification of biological structures, particularly the classification of superficial and deep vessels and transparent tissue layers.</p>
Dataset associated with paper "On the contribution of transient diabatic processes to ocean heat transport and temperature variability"
<p><strong>Data repository for Yung & Holmes (2023) </strong><i><strong>On the contribution of transient diabatic processes to ocean heat transport and temperature variability</strong></i><strong>, submitted to Journal of Physical Oceanography</strong></p><p>This repository contains:</p><p>- processed global ocean model data (including all data required to reproduce figures)</p><p>- analysis scripts to create figures (extra analysis and computation scripts are available at https://github.com/claireyung/Eddy_Diathermal_Code)</p><p>- 1D mixing model code (also available at https://github.com/claireyung/Diff1D/tree/Claire_2022)</p><p>Files: </p><p>- Diff1D.zip contains matlab code, figure code and output data</p><p>- DHT-MHT-Paper_Plots.ipynb contains figure code for most paper figures</p><p>- Seasonal_range_SST_SHF_MLD.ipynb contains figure code for Fig. 6</p><p>- 10Year-025-Monthly_decomp.ipynb, 1Year-025-Daily_decomp.ipynb demonstrate analysis binning process to go from model data to processed data</p><p>Processed data:</p><p>- ocean_grid.nc, output000fwmass_m_copy.nc have grid information</p><p>- ocean_heat_mean.nc, ocean_month_mean.nc, ocean_wmass_mean.nc contain 10 year means of model diagnostics</p><p>- seasonal_climatology_monthly_temp_SF_MX_mld_compress.nc contains monthly climatology used for Fig. 6</p><p>- min_SST_10yr_daily_data.nc and max_SST_10yr_daily_data.nc have the maximum and minimum daily average SST</p><p>- 10day_mean_10year_means.nc, 2mo_mean_10year_means.nc, sc_2mo_mean_10year_means.nc, 1day_mean_10year_means.nc, Mean_10year_means.nc, True_10year_means.nc are processed and binned data at the various timescales for plotting.</p><p>The model used is the 0.25 degree RYF version of ACCESS-OM2 (Kiss et al. 2020, GMD). The configuration used to run the model can be found here: https://github.com/claireyung/025deg_jra55_ryf/tree/norediGM_run_diaT_exdiags_mixingterms_smallterms . The zenodo repository https://zenodo.org/records/10052149 contains the files needed to run the model.</p><p>Contact: claire.yung@anu.edu.au</p>
Supplemental Material to Article "Quantification of process-induced effects on fatigue life of short-glass-fiber-filled adhesive used in wind turbine rotor blades"
<p>This set supplements the figure data to the article "Quantification of process-induced effects on fatigue life of short-glass-fiber-filled adhesive used in wind turbine rotor blades", DOI: xxx</p>
MITgcm West Antarctic Slope Undercurrent process-oriented model (MITgcm_UC)
<p><strong>MITgcm_UC.zip</strong>: The Matlab scripts used to generate, run and analyze the MITgcm simulations.</p> <ul> <li>MITgcm_UC/newexp_uc: The Matlab scripts used to generate and run the MITgcm simulations.</li> <li>MITgcm_UC/analysis_uc: The Matlab scripts used to calculate products and make figures.</li> </ul> <p><strong>products.zip</strong>: The products calculated from MITgcm_UC model diagnostics and the data used to make figures for the manuscript.</p> <p><strong>All the raw data of the model output are available at: <a href="https://doi.org/10.15144/S4QP4N">https://doi.org/10.15144/S4QP4N</a>.</strong></p> <p>Matlab scripts for vorticity budget analysis in MITgcm_UC/analysis_uc:</p> <ul> <li>calc_all_vorticity.m: A convenient script to load experiments and calculate the vorticity budget</li> <li>functions/calc_BCvorticity_cdw_sw.m: Calculate the vorticity budget for the CDW layer and the surface layer, respectively, after interpolating the momentum budget terms onto a much finer vertical grid (3400 layers in the vertical direction).</li> <li>calc_IceShelfPressureTorque.m: Calculate the pressure torque exerted from the ice shelf to the CDW layer or the surface layer.</li> <li>functions/calc_BCvorticity_ISPT.m: Calculate the decomposition of the pressure torque in the vorticity budget, including the ice-shelf pressure torque, bottom pressure torque, and interfacial pressure torque.</li> <li>functions/calc_BCvorticity_PVint.m: Calculate the potential vorticity of the CDW layer, select PV contours, and then cumulatively integrate the vorticity budget terms for the selected area. </li> <li>plots/fig4_new.m: Plot the vorticity budget (Extended Data Figs. 3 and 6 in the manuscript)</li> <li>plots/fig5_addCDWflux.m: Plot the area-integrated vorticity budget (Fig. 2 of the manuscript)</li> <li>plots/plot_stretch_new.m: Estimated pressure torques of the CDW layer using bottom vertical velocity, the vertical velocity across the upper bound of the CDW layer and the diapycnal velocity. (Extended Data Fig. 4 of the manuscript)</li> </ul> <p><br>Feel free to contact Yidongfang Si via y_si@mit.edu if you have any questions.</p>
Global Datasets of Hourly Carbon and Water Fluxes Simulated Using a Satellite-based Process Model with Dynamic Parameterizations
<p>This new global hourly dataset serves as a 'handshake' among process-based models, remote sensing, and the eddy covariance flux network, providing a reliable long-term estimate of global gross primary productivity (GPP) and evapotranspiration (ET) with diurnal patterns and facilitating studies related to ecosystem functional properties, global carbon, and water cycles.</p> <p>The dataset include the GPP and ET of sunlit and shaded leaf components at an hourly timescale and a spatial resolution of 0.25-degree from 2001 to 2020.</p>
Processed INSDC dataset for MOV analysis
<p>A processed version of a mutation-annotated tree from open SARS-CoV-2 genomic data, originally compiled by UCSC researchers at https://hgwdev.gi.ucsc.edu/~angie/UShER_SARS-CoV-2/. This is used as input to an open-data version of the analysis in <em>A molnupiravir-associated mutational signature in global SARS-CoV-2 genomes</em>.</p>
Excel template process mapping and FMEA
<p>A FMEA analysis tool with prebuild radiation oncology process steps and sub steps that can be modified based on clinical workflow. Also contains an instruction for use and a sample completed document.</p>
Raw data for " Unnatural evolutionary processes of SARS-CoV-2 variants and possibility of deliberate natural selection" DOI 10.5281/zenodo.8248320
<p>Compressed raw data for " Unnatural evolutionary processes of SARS-CoV-2 variants and possibility of deliberate natural selection" </p> <p>DOI 10.5281/zenodo.8248320</p>
Quantitative interpretation of the physical processes associated with the interannual variation of South Asian summer monsoon
<p>This is the CFRAM-A data of "Quantitative interpretation of the physical processes associated with the interannual variation of South Asian summer monsoon". The data includes 10 years: 1997, 1999, 2000, 2001, 2008, 2009, 2013, 2015, 2018, and 2019. Each year includes two "nc" data, one is the partial temperature, the other is the total temperature.</p>
Processed RNA expression count data and metadata from Gupta et al.:Systems genomics of salinity stress response in rice
<p>We assessed gene expression variation in a population of 130 accessions of rice (Oryza sativa) belonging to the major varietal group indica. The field experiment was conducted in the dry season of 2017 at IRRI in Los Banos, Laguna, Philippines. Seeds from each accession were sown on December 16, 2016, and seedlings were then transplanted into the experimental fields at 17 days after sowing (DAS), on January 5, 2017. The field experiments was conducted across two locations close-by: one non-salinized normal field and the other salinized field. Both field environments used a randomized complete block experimental design with each accession planted in three replicates. Each experimental plot included the accessions NSICRC 222 and NSICRC 182 serving as border rows. The application of salt in Block L5 started on January 19, 2017 when the plants were 31 days old. The salinity level was monitored by recording electrical conductivity (EC), using EC meters installed in each of the parcels at a depth of 30 cm. The salinity levels were then maintained at 6 dS/m (considered mild to moderate salinity stress) until maturity. Management and maintenance of the fields included the application of basal fertilizer, spraying of insecticides against thrips and removal of plants potentially infected with the rice tungro virus disease. Tissue collection for transcriptome. Briefly, leaf collection was done at 38 DAS (8 days after the beginning of the salt treatment) in the non-saline and saline field. Transcript levels were measured using a liquid automation-based 3 prime mRNA-seq quantification approach. Samples were multiplexed in batches of 96 per library. Raw sequencing data are available at the SRA in BioProject accession number PRJNA1010833. A key to the raw sequencing data in this BioProject can be found in the metadata of the processed RNA expression count data here</p>
Acc_tcga_2018_processed
<p>This dataset is the final result gotten from preprocessing the Acc_tcga_2018 gotten from the cBio portal and integrating it with the nodes gotten from pathway commons. It contains the edge index, the patients' information and survival time. It is to be used with Pytorch geometric for building GNNs.</p>
Dataset: Evolution Of Computational Ontologies: Assessing Development Processes Using Metrics
<p>Ontologies facilitate meaning between human and computational actors. On the one hand, the underlying technology can be considered mature. It has a standardized language, established tools for editing and sharing, and broad adoption in practice and research. On the other hand, we still know little about how these artifacts evolve over their lifetime, even though knowledge of the development process could influence quality control. It would enable us to give knowledge engineers better modeling or selection guidelines.</p> <p>This paper examines the evolution of computational ontologies using ontology metrics. First, we gathered hypotheses on the ontology development process. We assume that groups of ontologies follow a similar development pattern and that a stereotypical development process exists. Afterward, these hypotheses are tested against historical metric data from 7053 versions from 69 dormant ontologies.</p> <p>We will show that ontology development processes are highly heterogeneous. While the made hypotheses are partly true for a slight majority of ontologies, concluding the bigger picture of ontology development down to the individual ontologies is mostly not possible. Further, the data revealed that most ontologies have disruptive change events for most of the measures attributes. These disruptive events are further examined regarding their occurrences, combinations, and sizes.</p>
Covalent Organic Framework Thin-Film Photodetectors from Solution-Processable Porous Nanospheres
<p>This repository contains the source data for the manuscript <strong>"Covalent Organic Framework Thin-Film Photodetectors from Solution-Processable Porous Nanospheres" </strong></p> <p>The statistical model of 50 layers, 4-6 layers for TpDPP, TpTta, and TpTab.</p> <p>A code for building the statistical structure for layered materials by stacking layers following the Maxwell-Boltzmann energy distribution of their stacking modes. Full Changelog: <a href="https://github.com/Ying-Ying-Zhang/COFpiler/commits/v1.1">https://github.com/Ying-Ying-Zhang/COFpiler/commits/v1.1</a></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.