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18,621 results for “development;”
Development of an imaging toolbox to assess the therapeutic potential and biodistribution of macrophages in a mouse model of multiple organ dysfunction
<p>Data set to accompany manuscript entitled "Development of an imaging toolbox to assess the therapeutic potential and biodistribution of regenerative therapies in a mouse model of multiple organ dysfunction " which can be found on BioRxiv.</p>
ToyLabs - A new toy development methodology
<p>Enabling an Open Innovation Model for EU Toy Industry SMEs through Co-Creation with FabLabs, Safety Experts and Customer Communities</p> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732559.</p> <p>The scope of ToyLabs is to introduce a new innovation model realised via an open ICT platform supporting the creativity processes and production cycles of the Toy Industry SMEs, putting into the picture Fabrication Laboratories (FabLabs), Toy Safety Experts and End Customers in terms of co-creation, co-design and decentralised product prototyping. ToyLabs will act as a collaboration bus interconnecting the aforementioned stakeholder types, towards the direction of changing the market positioning and the prospects of SMEs in the Toy Industry, overcoming obstacles like geographical barriers and fragmented markets.</p> <p><br> </p>
Characteristics of wound dressing developed within the MEDILIGHT project
<p>The data set contains details on characteristics of wound dressing developed by URGO within the H2020 funded project MEDILIGHT.</p>
Development of Radix balthica embryos under contrasting temperatures for the duration of their development
<p>Sample datasets, HR modelling data and video acquired using the EmbryoPhenomics platform. Experiment assessing influence of three (20, 25 and 30C) contrasting temperatures on the development of the aquatic gastropod <em>Radix balthica</em>. Imaging was performed from first cell division to hatching and the EmbryoCV package was used to produce phenome-level data. Datasets and associated video for an individual embryo from each temperature are provided.</p> <p>EmbryoPhenomics datasets can be accessed using the XArray library in Python (or if EmbryoCV is installed see www.embryocv.org for instructions on loading data):</p> <ul> <li>results = xr.open_mfdataset(path_to_file). This will reveal the various data arrays.</li> </ul> <p>EmbryoPhenomics HR data can be loaded using the Numpy library in Python:</p> <ul> <li>hr = np.load(path_to_file)[()]<br> filt = hr[embryoLabel i.e. B3, C5 or D6]<br> </li> </ul>
Physiological parameters for four fish species (rainbow trout, zebra fish, fathead minnow and three-spined stickleback) as the basis for the development of generic physiologically-based kinetic models
<p>This excel file (DOI: 10.5281/zenodo.1414332) provides physiological parameters and their inter-individual variability (mean, coefficient of variation, sample size) for four fish species: rainbow trout (<em>Onchorhynchus mykiss</em>), zebrafish (<em>Danio rerio</em>), fathead minnow (<em>Pimephales promelas</em>), and three-spined stickleback (<em>Gasterosteus aculeatus</em>). These physiological parameters were estimated based on the results of extensive literature searches and specific experimental data described in Grech et al., (2018). </p> <p>This file is associated with R codes (DOI: 10.5281/zenodo.1414332) for generic PB-K models, partition coefficient Quantitative Structure Activity Relationship (QSAR) models for each fish species and parameterisation of model for males and females of each species separately.</p> <p>The full data collection and implementation of the models using case studies are described in Grech et al., 2018 (<a href="https://doi.org/10.1016/j.scitotenv.2018.09.163">https://doi.org/10.1016/j.scitotenv.2018.09.163</a>)</p>
Developing a Tryptophan Fluorescence Assay for Screening Ligands against USP5 Zf-UBD
<p>Development of a fluorescence based assay by measuring changes in UV tryptophan fluorescence of USP5 zinc finger ubiquitin binding domain (Zf-UBD) with addition of ligands</p>
Data and Source Codes used in "Development of a Global Quasi-3-D Multiscale Modeling Framework: I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"
<p>Data and Source Codes used in the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework: I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"</p> <p>Advection Test (ADV): East-West A_TST (100km, Cube), C_TST (25km, Cube), E_TST (5km, Cube),</p> <p> North-South K_TST (100km, Cube), M_TST (25km, Cube), O_TST (5km, Cube) </p> <p>Barotropic Test (BAR): A_TST5 (100km, Cube), Y_TST4 (100km, RLL), C_TST3 (5km, Cube), C_TST1 (5km, RLL)</p> <p>Baroclinic Test (BCL): J_TST30 (100km, Cube), J_TST20 (100km, RLL)</p>
Tomographic data for testing, demonstrating, and developing methods of removing ring artifacts
<p>These tomographic data were used for demonstrating our methods of eliminating ring artifacts published in Optics Express, <em>Nghia T. Vo, Robert C. Atwood, and Michael Drakopoulos, "Superior techniques for eliminating ring artifacts in X-ray micro-tomography," <strong>26</strong>, 28396-28412 (2018)</em><em>. </em>In sinogram, the artifacts appear as straight lines or stripe artifacts. The data have many types of stripe artifacts: full stripes, partial stripes, unresponsive stripes, fluctuating stripes, and blurry stripes. They are very useful for testing and developing methods of removing ring artifacts.</p> <p>Documentation: <a href="https://sarepy.readthedocs.io/">https://sarepy.readthedocs.io/</a></p> <p>Python implementations of these methods:</p> <p><a href="https://github.com/nghia-vo/sarepy">https://github.com/nghia-vo/sarepy</a></p> <p>In Tomopy:</p> <p><a href="https://tomopy.readthedocs.io/en/latest/api/tomopy.prep.stripe.html">https://tomopy.readthedocs.io/en/latest/api/tomopy.prep.stripe.html</a></p> <p>In Savu:</p> <p><a href="http://github.com/DiamondLightSource/Savu/tree/master/savu/plugins/ring_removal">https://github.com/DiamondLightSource/Savu/tree/master/savu/plugins/ring_removal</a></p> <p>In Algotom:</p> <p><a href="https://github.com/algotom/algotom/blob/master/algotom/prep/removal.py">https://github.com/algotom/algotom/blob/master/algotom/prep/removal.py</a> </p>
ANN development + final testing datasets
<p><strong>File name definitions:</strong></p> <p>'...v_50_175_250_300...' - dataset for velocity ranges [50, 175] + [250, 300] m/s</p> <p>'...v_175_250...' - dataset for velocity range [175, 250] m/s</p> <p>'ANNdevelop...' - used to perform 9 parametric sub-analyses where, in each one, many ANNs are developed (trained, validated and tested) and the one yielding the best results is selected</p> <p>'ANNtest...' - used to test the best ANN from each aforementioned parametric sub-analysis, aiming to find the best ANN model; this dataset includes the 'ANNdevelop...' counterpart</p> <p> </p> <p><strong>Where to find the input (independent) and target (dependent) variable values for each dataset/excel ?</strong></p> <p>input values in 'IN' sheet </p> <p>target values in 'TARGET' sheet</p> <p> </p> <p><strong>Where to find the results from the best ANN model (for each target/output variable and each velocity range)?</strong></p> <p>open the corresponding excel file and the expected (target) vs ANN (output) results are written in 'TARGET vs OUTPUT' sheet</p> <p> </p> <p> </p> <p><strong>Check reference below</strong> (to be added when the paper is published)</p> <p><a href="https://www.researchgate.net/publication/328849817_11_Neural_Networks_-_Max_Disp_-_Railway_Beams">https://www.researchgate.net/publication/328849817_11_Neural_Networks_-_Max_Disp_-_Railway_Beams</a></p>
USP5 Expression and Purification & Development of a Mass Spectrometry USP5 Catalytic Activity Assay
<p>Expression and purification of full length USP5<sup>1-835</sup> for optimization of a mass spectrometry (MS) based assay to detect polyubiquitin cleavage</p>
dataset for Biases in the Visual and Haptic Subjective Vertical Reveal the Role of Proprioceptive/Vestibular Priors in Child Development
<p>dataset for "Biases in the Visual and Haptic Subjective Vertical Reveal the Role of Proprioceptive/Vestibular Priors in Child Development" publication. </p>
Replication Package: Developer Reading Behavior while Summarizing Java Methods: Size and Context Matters
<p>A replication package for the study presented in the ICSE 2019 paper titled "Developer Reading Behavior while Summarizing Java Methods: Size and Context Matters" by Abid, Sharif, Dragan, Alrasheed, and Maletic</p>
Timbral Characterisation Tool v0.2 Development Dataset
<p>This dataset contains data generated as part of the AudioCommons project (DS 5.6.2). Data relate to Deliverable D5.6, the second prototype of timbral characterisation tools for semantically annotating non-musical content.</p> <p>Data comprise Max-based listening test interfaces, audio files, test results in the form of csv files, and documentation.</p> <p><strong>References</strong></p> <p>D5.6 (2018): A.Pearce, S.Safavi, T.Brookes, R.Mason, W.Wang, M.Plumbley, "Second prototype of timbral characterisation tool for semantically annotating non-musical content", AudioCommons Deliverable Report<br> - http://www.audiocommons.org/materials/</p>
Timbral Characterisation Tool v0.1 Development Dataset
<p>This dataset contains data generated as part of the AudioCommons project (DS 5.2.1). Data relate to the development of Deliverable D5.2 which was the first prototype of a set of timbral characterisation tools for semantically annotating audio content.</p> <p>Data comprise Max-based listening test interfaces, audio files, test results in the form of csv files, and documentation.</p> <p><strong>References</strong></p> <p>D5.2 (2016): A.Pearce, T.Brookes, R.Mason, "First prototype of timbral characterisation tools for semantically annotating non-musical content", AudioCommons Deliverable Report<br> - http://www.audiocommons.org/materials/</p> <p>Martin (2017): C.Martin, "Timbral Tagging: Towards the Development of a model for Metallic-natured sounds", Undergraduate technical project, Institute of Sound Recording, University of Surrey, Guildford, Surrey, UK.</p>
(06)-He2019A-DS0001 – Tribolium castaneum foxQ2-5' line long-term live imaging dataset of embryonic development acquired with light sheet fluorescence microscopy
<p>(06)-He2019A-DS0001 – <em>Tribolium castaneum</em> foxQ2-5' line long-term live imaging dataset of embryonic development acquired with light sheet fluorescence microscopy</p>
Developing Youth Track and Field Athletes - Diversification Dataset
<p><strong>The Prevalence of Within-Sport Specialization in Track and Field Athletics, and its Consequences for Participation and Retention </strong></p> <p><strong>Purpose: </strong>The aim of this study was to provide an in-depth analysis of the prevalence and consequences of within-sport specialization in track and field in the United Kingdom. <strong>Method: </strong>The competition histories of top 100 ranked athletes from four representative events (100m, 800m, long jump and shot put) were recorded from a publically-accessible database. Athletes were drawn from Under 20 (U20), U15 and U13 populations from the 2014/15 season, U15 populations from the 2009/10 season, and U13 populations from the 2007/08 season. Athletes’ specialization status was defined based upon the number of event groups (sprint, endurance, jump, throw) in which they had recorded at least one performance. Chi-squared tests were used to examine the relationship between level of specialization at U13 and U15 and both performance and retention at subsequent age grades. <strong>Results: </strong>Within-sport specialization was rare among U13 and U15 track and field athletes, with approximately 10% of top 100 ranked U13s and 25% of top 100 ranked U15s competing in a single event group only. However, less than 35% of participants competed in sprinting, endurance running, jumping and throwing events. There were no sex differences in the extent of specialization. Top ranked U20 female athletes were more likely to have diversified at U13 than their peers. There was no association between specialization at U13/U15 and subsequent retention. <strong>Conclusion: </strong>Administrators and coach educators should consider promoting a more nuanced message regarding participation in track and field, by incorporating advice on between-sport as well as within-sport specialization.</p>
visualizing the developement of painting production in periods of 50 years from 1300 to 2000 (source: https://kor.uni-frankfurt.de)
<p>Data<br> * entities representing a painting were selected<br> ** since there is no classification of works of art in the database, a set of values describing the technical and material features of the works of art were used to filter works of art being most probably paintings. The filter values can be found in ../../unique_material_values_new.xlsx on tabs "Öl auf Leinwand" and "Tafelmalerei"<br> * the selected entities were classified in periods of 50 years starting in 1300 and ending in 2000. Additionally there were two classes for paintings before 1300 and after 2000, and a class for non dated painting entities<br> * for each of the classes, the proprtion of its cardinal number in respect to the global number of selected entities was calculated<br> * class labels and the calculated proportion were written in data.csv (column 1: class labels, column 2: proprtion)</p> <p>Processing<br> * script that creates a bar chart from data in data.tsv<br> ** the script uses d3.js</p> <p> </p>
Replication Package for "How Developers Engage with Static Analysis Tools in Different Contexts"
<p>This is the replication package for the paper "How Developers Engage with Static Analysis Tools in Different Contexts".</p> <p>We include all the artifacts necessary to replicate the results obtained in our paper. Specifically, we provide (i) the survey questions together with all the valid answers we received including the demographics of our respondents, (ii) the most relevant statements that we extracted from the interviews including the demographics of our interviewees, (iii) the results of the card sorting performed on the development activities where our participants adopt Static Analysis Tools, (iv) all the data related to Krippendorff’s Alpha calculation for the performed card sorting, and (v) mapping of ASATs to the "rules" categories defined by Novak et al. (2010) and script for calculating occurrence, definition, and enforcement of the different ASAT types together with input and output data. Furthermore, we include the list of links to Reddit posts and inspected open-source projects together with their inspection data and the scripts for computing the inter-rater agreement during the inspection. Finally, we provide the Github features computed for each project and script for generating the sets of projects.</p>
Driver in the loop experiments for the development of virtual sensors ESR 13
<p>Driver in the loop experiments for the development of virtual sensors.</p>
Scripts developed to modelling the nocturnal ecological continuum of the State of Geneva, Switzerland, based on high-resolution nighttime imagery.
<p>The zipfile contains the scripts developed in the paper on the modelling of the nocturnal ecological continuum of the State of Geneva, Switzerland, based on high-resolution nighttime imagery, as published in Remote Sensing Applications: Society and Environment journal (RSASE - Elsevier). </p> <ul> <li>Scripts developed for the extraction of light sources from night orthophotography ; [SAFE Software Inc. (2017). FME Desktop Esri Edition.Version 2017.1.]</li> <li>ModelBuilder developed for the visibility modelling of light sources ; [ESRI (2017). ArcGIS Desktop Pro.Version 2.1.]</li> </ul>
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.