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286 results for “data mobilization.”
SMART Radar and WSR-88D Data Associated with "Mobile Radar Observations of Hurricanes at Landfall. Part II: Convectively Coupled Vortex Rossby Waves"
<p>The data contained in this archive are associated with "Mobile Radar Observations of Hurricanes at Landfall. Part II: Convectively Coupled Vortex Rossby Waves" in review in the <em>Journal of the Atmospheric Sciences</em>. Two sets of data associated with Hurricanes Isabel (2003) and Matthew (2016) are contained. Each subset of data contains the raw radar files that contribute to the manuscript in cfradial netCDF format.</p> <p>A readme file in included that describes the variables and format of the radar volume files. Questions about the dataset may be directed to addisonalford@ou.edu, drdoppler@ou.edu, or gordon.carrie-1@ou.edu.</p>
A 24-hour dynamic population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland
<p><strong>Related article:</strong> Bergroth, C., Järv, O., Tenkanen, H., Manninen, M., Toivonen, T., 2022. A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland. <a href="https://www.nature.com/articles/s41597-021-01113-4"><em>Scientific Data</em> 9, 39</a>.<br> </p> <p><strong>In this dataset:</strong></p> <p>We present temporally dynamic population distribution data from the Helsinki Metropolitan Area, Finland, at the level of 250 m by 250 m statistical grid cells. Three hourly population distribution datasets are provided for regular workdays (Mon – Thu), Saturdays and Sundays. The data are based on aggregated mobile phone data collected by the biggest mobile network operator in Finland. Mobile phone data are assigned to statistical grid cells using an advanced dasymetric interpolation method based on ancillary data about land cover, buildings and a time use survey. The data were validated by comparing population register data from Statistics Finland for night-time hours and a daytime workplace registry. The resulting 24-hour population data can be used to reveal the temporal dynamics of the city and examine population variations relevant to for instance spatial accessibility analyses, crisis management and planning. </p> <p><strong>Please cite this dataset as:</strong><br> <br> Bergroth, C., Järv, O., Tenkanen, H., Manninen, M., Toivonen, T., 2022. A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland. Scientific Data 9, 39. https://doi.org/10.1038/s41597-021-01113-4<br> </p> <p><strong>Organization of data</strong></p> <p>The dataset is packaged into a single Zipfile <em>Helsinki_dynpop_matrix.zip</em> which contains following files:</p> <ol> <li> <em>HMA_Dynamic_population_24H_workdays.csv</em> represents the dynamic population for average workday in the study area.</li> <li> <em>HMA_Dynamic_population_24H_sat.csv</em> represents the dynamic population for average saturday in the study area.</li> <li> <em>HMA_Dynamic_population_24H_sun.csv</em> represents the dynamic population for average sunday in the study area.</li> <li><em>target_zones_grid250m_EPSG3067.geojson</em> represents the statistical grid in ETRS89/ETRS-TM35FIN projection that can be used to visualize the data on a map using e.g. QGIS.</li> </ol> <p><strong>Column names</strong></p> <ol> <li><em>YKR_ID </em>: a unique identifier for each statistical grid cell (n=13,231). The identifier is compatible with the statistical YKR grid cell data by Statistics Finland and Finnish Environment Institute.</li> <li><em>H0, H1 ... H23 </em>: Each field represents the proportional distribution of the total population in the study area between grid cells during a one-hour period. In total, 24 fields are formatted as “Hx”, where x stands for the hour of the day (values ranging from 0-23). For example, H0 stands for the first hour of the day: 00:00 - 00:59. <br> The sum of all cell values for each field equals to 100 (i.e. 100% of total population for each one-hour period)</li> </ol> <p>In order to visualize the data on a map, the result tables can be joined with the <em>target_zones_grid250m_EPSG3067.geojson</em> data. The data can be joined by using the field <em>YKR_ID</em> as a common key between the datasets.</p> <p><strong>License</strong><br> Creative Commons Attribution 4.0 International.</p> <p><strong>Related datasets</strong></p> <ul> <li>Järv, Olle; Tenkanen, Henrikki & Toivonen, Tuuli. (2017). Multi-temporal function-based dasymetric interpolation tool for mobile phone data. Zenodo. https://doi.org/10.5281/zenodo.252612</li> <li>Tenkanen, Henrikki, & Toivonen, Tuuli. (2019). Helsinki Region Travel Time Matrix [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3247564</li> </ul> <p><br> </p>
Raw Sensor Data for STRIDE Project J "Improving Work Zone Mobility through Planning, Design and Operations"
<p>This dataset contains the raw traffic data from 9 sensors located on I-59 southbound near Tuscaloosa, Alabama, from October 3 to October 16, 2016. These data were used in the research for STRIDE Project J "Improving Work Zone Mobility through Planning, Design and Operations" and described in the STRIDE Final Project for this project.</p>
Mobility data on county level
<p>This dataset is the supplementary material for </p> <ul> <li>Paltra, S., Bostanci, I., Nagel, K. The effect of mobility reductions on infection growth is quadratic in many cases. DepositOnce (Preprint, Feb 2024) <a href="https://doi.org/10.14279/depositonce-17965">https://doi.org/10.14279/depositonce-17965</a></li> </ul> <p>Tha dataset is also used in the <strong>Math+ project EF4-13 "Modeling Infection Spreading and Counter-Measures in a Pandemic Situation Using Coupled Models"</strong> to perform the epidemic simulation studies. </p> <p>The CSV file contains for each week the average no. of daily hours people spend outside of home on county level.</p> <p>For the terms of use, please see the associated LICENSE file.</p> <p>More information can be found on our website: <a href="https://covid-sim.info/">https://covid-sim.info/</a>. If you have questions, please contact <a href="mailto:covid19@vsp.tu-berlin.de">covid19@vsp.tu-berlin.de</a> .</p>
Data from: Robust single-image tree diameter estimation with mobile phones
<p>Ground-based forest inventories are a key element of forest carbon monitoring, reporting, and verification schemes and a cornerstone of forest ecology research. Recent work using LiDAR-equipped mobile phones to automate parts of the forest inventory process assumes that tree trunks are well-spaced and visually unoccluded, or else requires manual intervention or offline processing to identify and measure tree trunks.</p> <p>In this paper, we design an algorithm that exploits a low-cost smartphone LiDAR sensor to estimate trunk diameter automatically from a single image in complex and realistic field conditions. We implement our design and build it into an app on a Huawei P30 Pro smartphone, demonstrating that the algorithm has low enough computational cost to run on this commodity platform in near real-time.</p> <p>We evaluate our app in three different forests across three seasons and find that in a corpus of 97 sample tree images, our app estimates trunk diameter with RMSE of 3.7 cm (R<sup>2</sup> = .97; 8.0% mean error) compared to manual DBH measurement. It achieves a 100% tree detection rate while reducing surveyor time by up to a factor of 4.6.</p> <p>Our work contributes to the search for a low-cost, low-expertise alternative to Terrestrial Laser Scanning that is nonetheless robust and efficient enough to compete with manual methods. We highlight the challenges that low-end mobile depth scanners face in occluded conditions and offer a lightweight, fully automatic approach for segmenting depth images and estimating trunk diameter despite these challenges. Our approach lowers the barriers to in situ forest measurement outside of an urban or plantation context, maintaining a tree detection and accuracy rate comparable to previous mobile phone methods even in complex forest conditions.</p>
supplementary data Chemical and Microbial Leaching of Valuable Metals from PCBs and Tantalum Capacitors of Spent Mobile Phones
<p>Table S1: Chemical composition of waste PCBs and tantalum capacitors (VICs)without HF precious metals; Table S2: Leaching with organic acids; Table S3: Leaching with inorganic acids; Table S4: Bacterial leaching of PCBS varying pulp density; Table S5: Bacterial leaching of PCBS varying ferrous iron concentration; Table S6: Bacterial leaching of PCBS and tantalum capacitor scrap varying particle size; Table S7: Fungal leaching of metals by <em>A</em>. <em>niger</em> spores and filtrate.</p>
The workload of manual data entry for integration between mobile health applications and eHealth infrastructure
<div> <p>In this study, we conducted a time-motion study observing healthcare workers (HCWs) completing data management activities including monitoring and evaluation (M&E) and manual data linkage of individual-level app data to electronic medical records (EMRS). This study served as a baseline study for an open-source app to mirror EMRS and reduce HCW workload while improving care in the Nurse-led Community-based Antiretroviral therapy Program (NCAP) in Lilongwe, Malawi.</p> </div>
Data for manuscript "Estimating grain stress and distinguishing between mobility and transportability improves bedload transport estimates in coarse-bedded mountain rivers"
<p>This repository contains data collected that was used in the manuscript:</p> <p><span>Estimating grain stress and distinguishing between mobility and transportability improves bedload transport estimates in coarse-bedded mountain rivers</span></p> <p> </p>
Census-based mobility graph data across 12 U.S. metro regions
<p>This dataset contains mobility information among census tracts for 12 U.S. cities in 2021. Mobility is defined to be the daily commute flow of residents, the data for which is retrieved from the Longitudinal Employer-Household Dynamics (LEHD), a U.S. Census Bureau program. </p> <p>In each of the individual city's directory, the file 'city_network_edges.csv', the 'S000' column the commute flow number between 'origin' and 'destination' census tracts of the city. The geographical boundaries of census tracts are also present in each directory, with 'city_network_nodes' representing shapefiles.</p>
Copy number variation introduced by a massive mobile element facilitates global thermal adaptation in a fungal wheat pathogen - Supplementary Data files
<p>Supplementary Data file 3-4 included in the manuscript Copy number variation introduced by a massive mobile element facilitates global thermal adaptation in a fungal wheat pathogen. </p>
Cryogenic quantum computer control signal generation using high-electron-mobility transistors data
<p>Data generated for the publication "Cryogenic quantum computer control signal generation using high-electron-mobility transistors"</p>
Shapefiles and data associated with the study of "Subsurface Sediment Mobilization in the Southern Chryse Planitia on Mars"
<p>This zip file contains the shapefiles for ArcGIS project with the positions of the five types of edifices within the southern part of the Chryse Planitia on Mars which were subject of the study "Subsurface Sediment Mobilization in the Southern Chryse Planitia on Mars" by Brož et al. (2019, JGR-Planets).</p>
Supporting data for "Taking connected mobile-health diagnostics of infectious diseases to the field"
<p>Raw and intermediate data used to create figures 1 and 4 of Wood, C.,<em> et al., "</em>Taking connected mobile-health diagnostics of infectious diseases to the field", <strong>Nature</strong> (2019).</p>
Data for "Boosting propagule transport models with individual-specific data from mobile apps"
<ol> <li>Management of invasive species and pathogens requires information about the traffic of potential vectors. Such information is often taken from vector traffic models fitted to survey data. Here, user-specific data collected via mobile apps offer new opportunities to obtain more accurate estimates and to analyze how vectors' individual preferences affect propagule flows. However, data voluntarily reported via apps may lack some trip records, adding a significant layer of uncertainty. We show how the benefits of app-based data can be exploited despite this drawback.</li> <li>Based on data collected via an angler app, we built a stochastic model for angler traffic in the Canadian province of Alberta. There, anglers facilitate the spread of whirling disease, a parasite-induced fish disease. The model is temporally and spatially explicit and accounts for individual preferences and repeating behaviour of anglers, helping to address the problem of missing trip records.</li> <li>We obtained estimates of angler traffic between all subbasins in Alberta. The model's accuracy exceeds that of direct empirical estimates even when fewer data were used to fit the model. The results indicate that anglers' local preferences and their tendency to revisit previous destinations reduce the number of long inter-waterbody trips potentially dispersing whirling disease. According to our model, anglers revisit their previous destination in 64% of their trips, making these trips irrelevant for the spread of whirling disease. Furthermore, 54% of fishing trips end in individual-specific spatially contained areas with mean radius of 54.7 km. Finally, although the fraction of trips that anglers report was unknown, we were able to estimate the total yearly number of fishing trips in Alberta, matching an independent empirical estimate.</li> <li>We make two major contributions: (1) we provide a model that uses mobile app data to boost the mechanistic accuracy of classic propagule transport models, and (2) we demonstrate the importance of individual-specific behaviour of vectors for propagule transport. Ignoring vectors' local preferences and their tendency to revisit previous destinations can lead to significant overestimates of vector traffic and biased estimates of propagule flows. This has clear implications for the management of invasive species and animal diseases.</li> </ol>
Data for "Dynamic switching of transcriptional regulators between two distinct low-mobility chromatin states"
<p>This deposit contains all the single-molecule trajectories reported in "Dynamic switching of transcriptional regulators between two distinct low-mobility chromatin states", Science Advances, 2023.</p> <p>To access the tracks, open the mat file in MATLAB. This contains a MATLAB table with the following fields:</p> <p><strong>summary_table.cell_protein{i}</strong> identifies the i<sup>th</sup> dataset i.e. cell line + protein + treatment.</p> <p><strong>summary_table.X{i}{j}</strong> is an Nx2 array of x and y coordinates (in microns) for track j in condition i. N is the number of localizations in that track.</p> <p>Time interval between localizations is 200 ms.</p> <p>Details on data acquisition and tracking parameters can be found in the associated manuscript.</p>
Sample data for "Urban Dynamics Through the Lens of Human Mobility"
<p>Sample data in Boston for paper "Urban Dynamics Through the Lens of Human Mobility".</p> <p> </p>
Additional data and code for "You can move, but you can't hide: identification of mobile genetic elements with geNomad"
<ul> <li><strong>benchmark_data:</strong> Data used to train and evaluate the classification models.</li> <li><strong>giant_virus_data:</strong> Sequences and metadata of giant viruses identified in public metagenomes.</li> <li><strong>neural_network_training:</strong> Code used to train geNomad's neural network-based classification model.</li> <li><strong>provirus_data:</strong> Data used to train and evaluate the conditional random field model employed by geNomad to identify provirus regions.</li> <li><strong>reference_sequences:</strong> Sequences of chromosomes, plasmids, and viruses that were used to build geNomad's marker dataset and to generate the training data for the classification models.</li> </ul>
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 from: Climate micro-mobilities as adaptation practice in the Pacific: the case of Samoa
<p>These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4"><strong>10.5061/dryad.bnzs7h4h4</strong></a>. This data set provides the summary of translated interviews with 20 participants from the two research sites in the small Pacific island state of Samoa. The field data was collected between June and August 2021.</p>
Data presented in the "Deconstructing Magnetization Noise: Degeneracies, Phases, and Mobile Fractionalized Excitations in Tetris Artificial Spin Ice" paper
<p>The files contain data presented in the "Deconstructing Magnetization Noise: Degeneracies, Phases, and Mobile Fractionalized Excitations in Tetris Artificial Spin Ice" paper.</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)
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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.