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306 results for “data archive”
Data archive for the peer-reviewed journal article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements"
<p>This data archive accompanying the article "Major source categories of PM2.5 oxidative potential in wintertime Beijing and surroundings based on online dithiothreitol-based field measurements", which was accepted in April 2024 in the peer-reviewed journal <strong><em>Science of the Total Environment</em></strong>. This data archive contains the processed OPvDTT measurements, chemical speciation of PM2.5, and source contribution used in the manuscript.</p>
Iron cuticulosome data archive
<p>The repository contains the raw data from Quantum magnetic imaging of iron organelles within the pigeon cochlea published in PNAS 2021</p>
Predictive utility of task-related functional connectivity vs. voxel activation - Data and code archive
<p>Functional connectivity, both in resting state and task performance, has steadily increased its share of neuroimaging research effort in the last 1.5 decades. In the current study, we investigated the predictive utility regarding behavioral performance and task information for 240 participants, aged 20-77, for both voxel activation and functional connectivity in 12 cognitive tasks, belonging to 4 cognitive reference domains (Episodic Memory, Fluid Reasoning, Perceptual Speed, and Vocabulary). We also added a model only comprising brain-structure information not specifically acquired during performance of a cognitive task. We used a simple brain-behavioral prediction technique based on Principal Component Analysis (PCA) and regression and studied the utility of both modalities in quasi out-of-sample predictions, using split-sample simulations (=5-fold Monte Carlo cross validation) with 1,000 iterations for which a regression model predicting a cognitive outcome was estimated in a training sample, with a subsequent assessment of prediction success in a non-overlapping test sample. The sample assignments were identical for functional connectivity, voxel activation, and brain structure, enabling apples-to-apples comparisons of predictive utility. All 3 models that were investigated included the demographic covariates age, gender, and years of education. A minimal reference model using simple linear regression with just these 3 covariates was included for comparison as well and was evaluated with the same resampling scheme as described above. Results of the comparison between voxel activation and functional connectivity were mixed and showed some dependency on cognitive outcome; however, mean differences in predictive utility between voxel activation and functional connectivity were rather small in terms of within-modality variability or predictive success. More notably, only in the case of Fluid Reasoning did concurrent functional neuroimaging provided compelling about cognitive performance beyond structural brain imaging or the minimal reference model.</p>
Data archive for paper "Machine Learning Emulation of 3D Cloud Radiative Effects"
<p><strong>Overview</strong></p> <p>This archive contains models, data, and the Singularity image to optionally rerun experiments described in "<a href="https://doi.org/10.1029/2021MS002550">Machine Learning Emulation of 3D Cloud Radiative Effects</a>".</p> <p>For the Python tool to generate synthetic data, please refer to the <a href="https://github.com/dmey/synthia">Synthia repository</a>.</p> <p><strong>Prerequisites</strong></p> <ul> <li>Linux or macOS with Bash shell.</li> <li><a href="https://sylabs.io/singularity/">Singularity</a> (tested with version 3.6.3-1.el8)*.</li> <li><a href="https://en.wikipedia.org/wiki/Portable_Batch_System">Portable Batch System</a> (PBS) job scheduler**.</li> </ul> <p>*Please note that all steps require <a href="https://sylabs.io/">Singularity</a> to be installed on your system. If you are looking for information on how to install or use Singularity, please refer to the <a href="https://sylabs.io/docs">Singularity documentation</a>.</p> <p>**Although PBS in not a strict requirement, it is required to run all helper scripts as included in this repository. Please note that depending on your specific system settings and resource availability, you may need to modify PBS parameters at the top of submit scripts stored in the <code>hpc</code> directory (e.g. <code>#PBS -lwalltime=24:00:00</code>).</p> <p><strong>Initialization</strong></p> <p>Deflate the data archive with:</p> <pre><code>./init.sh </code></pre> <p>Compile ecRad with Singularity:</p> <pre><code>./tools/singularity/compile_ecrad.sh </code></pre> <p><strong>Usage</strong></p> <p>To reproduce the results as described in the paper, run the following commands from the <code>hpc</code> folder:</p> <pre><code>qsub -v JOB_NAME=mlp_default ./submit_grid_search_default.sh qsub -v JOB_NAME=mlp_synthia ./submit_grid_search_synthia.sh qsub submit_benchmark.sh </code></pre> <p>then, to plot stats and identify notebooks run:</p> <pre><code>qsub submit_stats.sh </code></pre> <p><strong>License</strong></p> <p>Paper code released under the <a href="./LICENSE.txt">MIT license</a>. Data released under <a href="./data/LICENSE.txt">CC BY 4.0</a>. <a href="https://confluence.ecmwf.int/display/ECRAD">ecRad</a> released under the <a href="./ecrad/LICENSE">Apache 2.0 license</a>.</p>
Proteomic source data archive
<p>Source data from proteomic analysis performed in manuscript "<strong>Mitochondrially targeted tamoxifen alleviates markers of obesity and type 2 diabetes mellitus" </strong>by<strong> </strong>Vacurova et al.</p>
Archive data supporting the results in the paper: Long-term soil warming alters fine root dynamics and morphology, and their ectomycorrhizal fungal community in a temperate forest soil"
<p><span>Climate warming is predicted to affect temperate forests severely, but the response of fine roots, key to plant nutrition, water uptake, soil carbon and nutrient cycling is unclear. Understanding how fine roots will respond to increasing temperature is a prerequisite for predicting the functioning of forests in a warmer climate. We studied the response of fine roots and their ectomycorrhizal (EcM) fungal and root-associated bacterial communities to soil warming by 4 °C in a mixed spruce-beech forest in the Austrian Limestone Alps after 8 and 14 years of soil warming, respectively. Fine root biomass (FRB) and fine root production were 17% and 128% higher in the warmed plots, respectively, after 14 years. The increase in FRB (13%) was not significant after 8 years of treatment, whereas specific root length, specific root area, and root tip density were significantly higher in warmed plots at both sampling occasions. Soil warming did not affect EcM exploration types and diversity, but changed their community composition, with an increase in the relative abundance of <em>Cenoccocum</em> at 0 – 10 cm soil depth, a drought-stress tolerant genus, and an increase in short and long-distance exploration types like <em>Sebacina </em>and <em>Boletus </em>at 10 – 20 cm soil depth. Warming increased the root-associated bacterial diversity but did not affect their community composition. Soil warming did not affect nutrient concentrations of fine roots, though we found indications of limited soil phosphorus (P) and potassium (K) availability. </span><span>Our findings suggest that, in the studied ecosystem, global warming could persistently increase soil carbon inputs due to accelerated fine root growth and turnover, and could simultaneously alter fine root morphology and EcM fungal community composition towards improved nutrient foraging. </span></p>
ROOOH modeling data — archive
<p>This archive contains ECHAM-HAMMOZ model output files used for the paper:</p> <p>Hydrotrioxide (ROOOH) formation in the atmosphere</p> <p>by Berndt et al.</p> <p> </p>
Archive for regression and estimation of the total freeboard of the Arctic using AMSR2 data v2.0
<p>This fileset contains data used for generating Tables and Figures in Kim et al. (2022). All file has csv format separated by a comma. In the first line of the individual file, we provide the variable name and unit of each column.</p> <p> </p> <p>The fileset has 6 sub-directories. The name of each directory indicates the figures corresponding to its contents.</p> <p>• Figure 2,7</p> <p>• Figure 4 (and Table 1-3)</p> <p>• Figure 5</p> <p>• Figure 6,8</p> <p>• Figure 6_ICESat2</p> <p>• Figure A1</p>
Archival bundle of the data used for "Extending OpenStack Monasca for Predictive Elasticity Control"
<p>This archive contains the data used for the paper</p> <p><strong>Extending OpenStack Monasca for Predictive Elasticity Control</strong><br> <a href="mailto:giacomo.lanciano@sns.it">Giacomo Lanciano</a>*, Filippo Galli, Tommaso Cucinotta, Davide Bacciu, Andrea Passarella</p> <p> </p> <p>Follow the instructions provided in the <a href="https://github.com/giacomolanciano/predictive-elasticity-monasca">companion repo</a> to automatically download and decompress the archive. The following files are included:</p> <table> <tbody> <tr> <td><strong>File</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td> <p>amphora-x64-haproxy.qcow2</p> </td> <td> <p>Image used to create Octavia amphorae</p> </td> </tr> <tr> <td> <p>distwalk-{lin,aim,mlp,rnn,stc}-<INCREMENTAL-ID>.csv</p> </td> <td> <p>Run traces</p> </td> </tr> <tr> <td> <p>distwalk-{lin,mlp,rnn,stc}-<INCREMENTAL-ID>.log</p> </td> <td> <p>distwalk run log</p> </td> </tr> <tr> <td> <p>distwalk-{lin,mlp,rnn,stc}-<INCREMENTAL-ID>-pred.json</p> </td> <td> <p>Predictive metric data exported from Monasca DB</p> </td> </tr> <tr> <td> <p>distwalk-{lin,mlp,rnn,stc}-<INCREMENTAL-ID>-real.json</p> </td> <td> <p>Actual metric data exported from Monasca DB</p> </td> </tr> <tr> <td> <p>distwalk-{lin,mlp,rnn,stc}-<INCREMENTAL-ID>-times.csv</p> </td> <td> <p>Client-side response time for each request sent during a run</p> </td> </tr> <tr> <td> <p>model_dumps/*</p> </td> <td> <p>Dumps of the models and data scalers used for the validation</p> </td> </tr> <tr> <td> <p>predictor.log</p> </td> <td> <p>monasca-predictor log</p> </td> </tr> <tr> <td> <p>predictor-times.log</p> </td> <td> <p>monasca-predictor` log (timing info only)</p> </td> </tr> <tr> <td> <p>predictor-times-{lin,mlp,rnn}.{csv,log}</p> </td> <td> <p>monasca-predictor log (timing info only, group by predictor)</p> </td> </tr> <tr> <td> <p>super_steep_behavior.csv</p> </td> <td> <p>Dataset used to train MLP and RNN models</p> </td> </tr> <tr> <td> <p>test_behavior_02_distwalk-6t_last100.dat</p> </td> <td> <p>distwalk load trace</p> </td> </tr> <tr> <td> <p>ubuntu-20.04-min-distwalk.img</p> </td> <td> <p>Image used to create Nova instances for the scaling group</p> </td> </tr> </tbody> </table> <p>This work extends our <a href="https://doi.org/10.1145/3468737.3494104">previous one</a> appeared at the <em>IEEE/ACM 14th International Conference on Utility and Cloud Computing (UCC'21)</em>. </p> <p>* <em>contact author</em></p>
Aesthetic Trends and Semantic Web Adoption of Media Outlets Identified through Automated Archival Data Extraction
<p>This dataset includes a variety of structured data gathered via various Web data extraction techniques which were employed in order to collect current and archival data from almost a thousand news websites that are popular in Greece, for the purpose of monitoring and recording their progress through time. The collected information, that took the form of a website’s source code and an impression of their homepage in different time instances of the last decade, has been used to identify trends concerning Semantic Web integration, DOM structure complexity, number of graphics, color usage and more. In total more than ten thousands impressions (including screenshots and source code) were analyzed which resulted to conclusions regarding the evolution of aesthetics and the adoption of new technologies.</p>
Data Archive of 'Hadley Cell Edge Modulates the Role of Ekman Heat Flux in a Future Climate'
<p>Output data used to create figures in ' Hadley Cell Edge Modulates the Role of Ekman Heat Flux in a Future Climate ' is archived. Original data sources from which the output data are generated are Reanalysis Products (ERA5, JRA55, NCEP/NCAR reanalysis) and 8 CMIP6 model simulations.</p>
Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 12 September 2015
<p>Open Language Archive Community (OLAC) Nightly Data Dump (XML) from 12 September 2015</p>
Figures - Semantic analysis of web archive historical data 1983 "Marche pour l'égalité et contre le racisme"
Open the record for dataset details and reuse information.
Data Archival for Economic Cost Modeling of Chinook Habitat Restoration in the Stillaguamish River Basin
<p>We used geospatial data to model economic cost estimates of habitat restoration in the Stillaguamish River Basin in the Puget Sound. We utilized data pertaining to the streams/rivers, floodplain habitat, subbasins, elevation, distance to roads, demographics, and land use within the Stillaguamish River Basin to do so. Analysis included using the different attributes of the Stillaguamish River Basin to create low and high cost estimates for floodplain, engineered log jam, and riparian planting habitat restoration. We specifically looked at the slope and size of streams, area of habitat that needed to be restored, slopes of the riparian area, distance to nearest road, and canopy angles as our model inputs. We followed cost estimate guidance provided by the Puget Sound Shared Strategy to identify our cost ranges and updated them to todays prices using the producer price index. An additional land use analysis was performed to quantify the total area and cost of potential agricultural land in the basin. Lastly, we investigated the demographics of the region to identify areas of POC and low income in relation to proposed restoration actions.</p>
Human Bone Ultrastructure in 3D (nano-CT+qPRS): Data Archive
<p>This is a Data Archive with original data for the manuscript "Human Bone Ultrastructure in 3D: Mltimodal Correlative Study Combining Nanoscale X-Ray Computed Tomography and Quantitative Polarized Raman Spectroscopy".</p> <p>A README file containing all descriptions can be found in the main folder. Data is stuctured into 4 categories: Light Microscopy, nano-CT tilt series, nano-CT reconstruction and Raman (qPRS) Data. Each category is uploaded as a .zip archive and contains files related to respective technique (in their turn groupped into .zip archives by the name of a showcased sample).<br><br></p>
Data Archives - LAFORET et al - Silicate-sulfide interaction within quenched melts of space weathered Ryugu grains
<p>Contains STEM-EDXS raw data used in the paper Laforet et al. submitted in Meteoritics and Planetary Science</p> <p> </p>
Synthetic data RELION project archive for ccpem-pipeliner cryodrgn jobs slow tests
<p>Synthetic data reconstructed via RELION4.0 used for testing CryoDRGN jobs in ccpem-pipeliner (https://gitlab.com/ccpem/ccpem-pipeliner). Micrographs simulated via Roodmus (<span>https://doi.org/10.1101/2024.04.29.590932</span>) using molcular conformations originating from DE Shaw simulation DESRES-ANTON-11021571 (D. E. Shaw Research, "Molecular Dynamics Simulations Related to SARS-CoV-2," D. E. Shaw Research Technical Data, 2020. https://www.deshawresearch.com/downloads/download_trajectory_sarscov2.cgi/)</p>
Raw Data Archive for "A New Cross-Calibration Algorithm for Multi-Mode Secondary Electron Multiplier Detectors"
<p>Raw Thermo Element XR data files for use with the Enhanced Linear Dynamic Range (ELDR) Model. The model inverts raw pulse and analog data from the Element 2/XR inductively coupled plasma mass spectrometer to estimate detector cross-calibration, linear-in-time cross-calibration drift, and detector non-linearity. This data archive contains the raw data comprising 1572 individual laser ablation analyses. Each analysis consists of two files: (1) raw data archive (.dat); and (2) setup information file <em>(</em>.inf). The analytical session is divided into three sequences: SEQ1, SEQ2, SEQ3.</p> <p> </p>
Kclause-Smarch Data Archive
<p>This is data archive for the paper "Uniform Random Sampling of Kconfig System Configurations", submitted to ESEC/FSE 2019</p>
Testing Zenodo Data Archive
<p>Test</p>
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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.