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6,782 results for “project”
SEM Figures related to CIGNUS project
<p>SEM images collected during the CIGNUS project from 2019 to 2021. Contact the author for details and information.</p>
Prehistoric Mining sites in the Lower Inn Valley - Federal Monuments Office documentation of the project Austrian Science Fund project "Prehistoric copper production in the eastern and central Alps" (I 1670)
<p>The dataset contains all tables and RDF-triples created based on the following Federal Monuments Office Documentations</p> <ul> <li>87002.15.01_Verhuettungsplatz_suedlich_Ruine_Rottenburg: <a href="https://zenodo.org/record/5243460"> https://zenodo.org/record/5243460</a></li> <li>87002.16.01_Verhuettungsplatz_suedlich_Ruine_Rottenburg: <a href="https://zenodo.org/record/5244755"> https://zenodo.org/record/5244755</a></li> <li>87002.17.01_Verhuettungsplatz_suedlich_Ruine_Rottenburg: <a href="https://zenodo.org/record/5244794"> https://zenodo.org/record/5244794</a></li> <li>87007.15.01_Bergbaurevier_Schwaz_Brixlegg: <a href="https://zenodo.org/record/5236664"> https://zenodo.org/record/5236664</a></li> <li>87007.16.01_Bergbaurevier_Schwaz_Brixlegg: <a href="https://zenodo.org/record/5243123"> https://zenodo.org/record/5243123</a></li> <li>87009.16.01_Erzaufbereitungsplatz_Schrofen: <a href="https://zenodo.org/record/5243416"> https://zenodo.org/record/5243416</a></li> </ul>
data set regarding to project Optimal assessment of nutritional status in older subjects with the chronic obstructive pulmonary disease
<p>data set regarding to project Optimal assessment of nutritional status in older subjects with the chronic obstructive pulmonary disease</p>
Projection of high-dimensional genome-wide expression on SOM transcriptome landscapes: supplementary datasets
<p>This is a supplementary dataset with raw data, scripts, and complete analysis results for the paper "Supervised projection of high-dimensional genome-wide expression on SOM transcriptome landscapes". </p> <p>The archive contains three folders:</p> <p>1. "Simdata" folder contains data, scripts, and results of performance evaluation of extension SOM and supervised SOM with simulated data. </p> <p>2. "IBD" - folder contains data, scripts, and results of analysis of Inflammatory bowel disease datasets.</p> <p>3. "BC" - folder contains data, scripts, and results of analysis of breast cancer datasets.</p>
Jemma Metadata Projects
<p>Jemma Metadata Projects</p> <p>> file: Jemma_Metadata_Projects.csv<br> > size: 4.7 MB<br> > num_rows: 50,000<br> > columns: project_id, project_path, project_name</p>
Raw Data for the "Reading Kultura from a Distance" project.
<p>These are the datasets extracted from the Polish journal <em>Kultura</em> (1946-1989) which was collected and curated in 2010-2014, for the project <em>Reading Kultura from a Distance</em>, developed by Jessie Labov at the Ohio State University with the help of Ewa Zegler-Poleska and Adam Pruss. There are four distinct datasets, which correspond to the authors, letter writers, funders, and rejected authors of <em>Kultura</em>. Much research was carried out to determine the location of the authors, while the other categories self-identified in the journal itself. These points were also georeferenced and plotted, the results of which can be seen here: https://eurasia.omeka.fas.harvard.edu/exhibits/show/distant-kultura and also in the book by project leader Jessie Labov, <em>Transatlantic Central Europe: Contesting Geography and Redefining Culture Beyond the Nation</em> (CEU Press, 2019).</p>
ALIMENTOPIA Project - CETAPS The Portuguese Vegetarian Database
<pre>One of the main goals of the ALIMENTOPIA/Utopian Foodways Project (2016-2020) was to rescue from the collective amnesia an unprecedented phenomenon in Portugal in the early 20th century: the Portuguese Vegetarian Society. As a priceless cultural artifact, <em>O Vegetariano: Mensário Naturista Ilustrado</em>, published uninterruptedly between 1909 and 1935, was more than just the official organ of the Vegetarian Society of Portugal (SVP), founded in 1911. It was indeed an aggregating platform for a community that reached, at its peak, more than 3,500 subscribers. All the entries of all the publications are indexed in this searchable database, making it a useful tool for any researcher working on Food, Utopian movements, vegetarianism, naturism and Portuguese History.</pre>
Projection of hourly extreme precipitation over Eastern China
<p>Data used in the manuscript "<strong>Projection of hourly extreme precipitation over Eastern China</strong>" which will be submitted to Journal of Geophysical Research: Atmospheres.</p>
data set regarding to project Optimal assessment of nutritional status in older subjects with the chronic obstructive pulmonary disease – a comparison of three screening tools used in the GLIM diagnostic algorithm
<p>data set regarding to project Optimal assessment of nutritional status in older subjects with the chronic obstructive pulmonary disease – a comparison of three screening tools used in the GLIM diagnostic algorithm </p>
Is it best to add native shrubs to a coastal sage scrub restoration project as seeds or as seedlings?
<p>Ecological restoration frequently involves the addition of native plants, but the effectiveness (in terms of plant growth, plant survival, and cost) of using seeds versus container plants has not been studied in many plant communities. It is also not known if plant success would vary by species or based on functional traits. To answer these questions, we added several shrub species to a coastal sage scrub restoration site as seeds or as seedlings in a randomized block design. We measured percent cover, density, species richness, size, survival, and costs. Over the two years of the study, shrubs added to the site as seeds grew more and continued to have greater density than plants added from containers. Seeded plots also had greater native species richness than planted plots. However, shrubs from containers had higher survival rates, and percent cover was comparable between the planted and seeded treatments. Responses varied by species depending on functional traits, with deep-rooted evergreen species establishing better from container plants. Our cost analysis showed that it is more expensive to use container plants than seed, with most of the costs attributed to labor and supplies needed to grow plants. Our measurements of shrub density, survival, species richness, and growth in two years in our experimental plots lead us to conclude that coastal sage scrub restoration with seeds is optimal for increasing density and species richness with limited funds, yet the addition of some species from container plants may be necessary if key species are desired as part of the project objectives.</p>
Data set of eradication project on Tsuken Island
<p>Host plant survey.csv: Result of host plant surveys</p> <p>SIT.csv: Date and the number of sterile insects released</p> <p>Sweet potato.csv: Result of host plant survey on sweet potato</p> <p>Trap.csv: Result of trap surveys</p>
A collection of X-ray projections of 131 pieces of modeling clay containing stones for machine learning-driven object detection
<p><strong>Summary</strong></p> <p>This submission contains a collection of 235800 X-ray projections of 131 pieces of modeling clay (Play-Doh) with various numbers of stones inserted. The submission is intended as an extensive and easy-to-use training dataset for supervised machine learning driven object detection. The ground truth locations of the stones are included. The data is supplementary material to the paper titled "A tomographic workflow enabling deep learning for X-ray based foreign object detection" [Zeegers 2022].</p> <p> </p> <p><strong>Description</strong></p> <p><em>Sample information</em></p> <p>The samples are modeling clay (Play-Doh, Hasbro, RI, USA) with various numbers of pieces of gravel included. In total 131 samples are prepared, of which 20 samples contain 5-8 inserted stones, 3 samples contain three stones, 35 contain two stones, 62 contain one stone and 11 contain no stones. The stones have an average diameter of ca. 7mm (ranging from 3mm to 11mm). The Play-Doh is remolded for every sample.</p> <p><em>Apparatus</em></p> <p>The dataset is acquired in the FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. The CT scanner consists consists of a cone-beam microfocus polychromatic X-ray point source, and a 1944x1536 pixel, 14-bit, flat detector panel (Dexela1512NDT). Full details can be found in [Coban 2020].</p> <p><em>Scanning setup</em></p> <p>For each sample, 1800 radiographs are collected by rotating the sample over 360 degrees in a circular and continuous motion. A peak voltage of 90kV is used, and the target power is set to 20W. The distance between the source and detector is 69.80 cm and the distance between the source and the object is 44.14 cm. An exposure time of 20 ms is used for each projection.</p> <p><em>Experimental plan</em></p> <p>This data is the result of a demonstration of a workflow to collect annotated data for supervised machine learning for X-ray based object detection. The ground truth locations are retrieved by tomographic reconstruction, segmentation and virtual projections with the same acquisition angles. A detailed description for the workflow to obtain a training dataset is given in [Zeegers 2022].</p> <p><em>Technical details</em></p> <p>All projections have been corrected with flatfield images (averaged over 10 pre and 10 post radiographs) and darkfield images (averaged over 10 pre and 10 post images). Both the X-ray projections and the ground truth images are resized to 128x128 pixels. The raw data is made available in another (larger) submission for complete reproduction (<a href="https://zenodo.org/record/5866228">https://zenodo.org/record/5866228</a>). All images are stored in .tif format. The data for samples with 5-8 stones are put in a separate folder from the data with 0-3 stones. The size of the completely unpacked dataset is 19.6 GB.</p> <p><strong>NOTE</strong>: Because the dataset consists of 471600 files, fully extracting the dataset may take a while. Therefore, an additional and significantly smaller zip-file is included for previewing the data, with one X-ray projection for each sample.</p> <p> </p> <p><strong>Additional Links</strong><br> These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI) in Amsterdam, The Netherlands: <a href="https://www.cwi.nl/research/groups/computational-imaging">https://www.cwi.nl/research/groups/computational-imaging</a></p> <p> </p> <p><strong>Contact details</strong><br> zeegers [at] cwi [dot] nl</p> <p> </p> <p><strong>Acknowledgments</strong><br> The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project number 639.073.506. The authors also acknowledge TESCAN-XRE NV for their collaboration and support of the FleX-ray laboratory.</p> <p><br> <strong>References</strong><br> [Zeegers 2022] M. T. Zeegers, T. van Leeuwen, D. M. Pelt, S. B. Coban, R. van Liere, K. J. Batenburg, "A tomographic workflow enabling deep learning for X-ray based foreign object detection", 2022 (in preparation)<br> [Coban 2020] S. B. Coban, F. Lucka, W. J. Palenstijn, D. Van Loo, and K. J. Batenburg, “Explorative imaging and its implementation at the FleX-ray Laboratory,” J. Imaging, vol. 6, no. 18, 2020, doi: 10.3390/jimaging6040018.</p> <p>If you use (parts of) this data in a publication, we would appreciate it if you would refer to the first article.</p>
Wood industry projects dataset
<p>Wood industry projects dataset (Horizon 2020)</p>
Data file for consumer moral identity effects on engagement in sustainable consumption in personal life and workplace environments project
<p>The survey data was collected in year 2018 to identify effects of moral identity on consumer engagement in sustainable consumption. Two environments were considered when collecting data for the project - work and home environments. The data contains survey responses to a number of questions which measure consumer engagement in sustainable consumption at home, consumer engagement in sustainable consumption at work, two dimensions of moral identity and offers demographic data about the respondents. </p>
How are Solidity smart contracts tested in open source projects? An exploratory study
<p>A dataset with 139 Github Solidity projects containing information about testing files, testing tools, and testnets that each project uses.</p>
Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange
<p>Dataset used in the work 'Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange'.</p> <p>Authors not presented due to double blind review.</p>
Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange
<p>Dataset used in the work 'Investigating the Point of View of Project Management Practitioners on Technical Debt - A Preliminary Study on Stack Exchange'.</p>
Future Projection of Solar Energy Over China Based on Multi-Regional Climate Model Simulations
<p>Data for article "Future Projection of Solar Energy Over China Based on Multi-Regional Climate Model Simulations"</p>
Number of participations in projects
<p>Simple dataset of the distribution of project participations per participant (wood industry projects, Horizon 2020)</p>
Infection Delay Project Data
<p>GitHub Repository for the project code can be found here: https://github.com/shivyucel/infection-delay-project</p> <p>The raw data folder contains the census and commuting data, along with their relevant shapefiles and labels. It also contains the shapefiles for the 2599 hexagons used in this analysis.</p> <p>The prelim_data folder contains the h3_IDs table, used to numerically identify hexagons (more info included in info file in folder). It also includes the commuting data, already preprocessed using code in the Effective Distance/SIR Model folder to filter out regions which do not have suitable data. </p> <p>The SIR_model_inputs folder has the mobility matrix based on the commuting data, and the population data (both already filtered to include suitable regions, same as above).</p> <p>The infection_delay_inputs folder contains the baseline and real mobility effective distance matrices. </p> <p>The mobility_data folder contains the raw mobility data from March - September 2020 (raw_mobility_data.csv), the mobility reductions across all hexagons with data around the lockdown (mobility_reduction.csv), and the mobility change (filtered_mobility_reduction.csv) used in the effective_distance_real_changes.py code, filtered for the regions which are suitable for the effective distance/SIR calculations. </p> <p>The result_data folder contains the tables used to generate the results, including the weighted median 10-day infection delay values for every region, the outbreak divided results, merged with income and centrality data. The final data files are 'weighted_hexagon_data.csv' and 'longford_outbreak_split_delays'.</p> <p>NOTE: The infection delay files take up 30+ GB of storage, and are not included here. In both mobility scenario, 2599 tables are generated, each with 2599 columns, representing the time series of every hexagon for every outbreak scenario. These are then duplicated in reorient_infection_delay_tables.py, to make them amenable to analysis.</p> <p>Full commuting and census data, beyond that included in the raw data folder, can be found here (https://www.metro.sp.gov.br/pesquisa-od/) and here (https://censo2010.ibge.gov.br/resultados/resumo.html), respectively.</p> <p> </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.