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3,696 results for “reference”
AllScale: Reference data of a flow over a plane. DPW-4 performed with Fine/Open
<p>The present computation has been performed on a 66 millions cells mesh. The turbulence model used is the Spalart Allmaras using CPU-Booster.</p> <p> </p> <p>Flow configuration : </p> <ul> <li>M = 0.85</li> <li>Re = 5 000 000</li> <li>AoA = 0.040472087 radians</li> </ul> <p>Integral results: </p> <ul> <li>CL = 0.49328</li> <li>CD = 2.701862e-2</li> <li>CM = -4.89841e-2</li> </ul> <p>Geometry and refernce data can be found on the DPW-4 website : https://aiaa-dpw.larc.nasa.gov/Workshop4/DPW4-geom.html</p> <p>The data set provide one cgns file of the 3D mesh with the primitives variables in order to compare the reference application and the AllScale prototype. </p>
Dataset records and references extracted from GBIF used for wild boar distribution modelling
<p>These are the datasets containing wild boar records downloaded from Global Biodiversity Information Facility (GBIF) used to fit presence-only and presence-background models. It indicates the data key, publishing organization key, licenses and references.</p>
3D cranial landmark coordinates from the Athens Collection. A modern Greek population reference dataset for testing 3D-ID software
<p>The present dataset comprises the landmark coordinates of 158 intact crania (80 males and 78 females) of adult individuals from the Athens Collection. The 3D coordinates of up to 34 landmarks have been extracted from high quality textured 3D models produced with photogrammetry. The dataset aims to evaluate the correct classification performance of 3D-ID software. Hence, the dataset contains the landmark 3D coordinates both in Meshlab's PickedPoints files (.pp) but also in 3D-ID's input text format (.3did). The dataset is accompanied by certain GNU Octave scripts and functions used for data conversion and integrity check. For more details see the Dataset Description pdf.</p>
The reference index files used for RNA-seq workflow benchmark in CWL-metrics manuscript
<p>The reference files used in the RNA-Seq workflow benchmark in the manuscript "Accumulating computational resource usage of genomic data analysis workflow to optimize cloud computing instance selection" (https://doi.org/10.1101/456756).</p>
CID2013: A Database for Evaluating No-Reference Image Quality Assessment Algorithms
<p>The CID2013 Camera Image Database consists of real images taken by consumer cameras and mobile phones. It is developed to provide useful tool to allow researchers target more commercially relevant distortions when developing processes of objective image quality assessment algorithms.</p> <p>The CID2013 database consists of 480 evaluated images captured by 79 imaging devices (mobile phones, DSC, DSLR) in six Image Sets. Note that the actual number of images in the database is 474. In Image Set II, Device 6 is evaluated twice as we wanted to test inter-observer reliablity. The scores are later combined into a single MOS value as the two evaluations correlated strongly.</p> <p>If you use this database in your research, we kindly ask that you follow the copyright notice bellow and cite the following paper:</p> <p>Virtanen, T., Nuutinen, M., Vaahteranoksa, M., Oittinen, P. and Häkkinen, J. “CID2013: a database for evaluating no-reference image quality assessment algorithms”, IEEE Transactions on Image Processing, vol. 24, no. 1, pp. 390-402, Jan. 2015. <a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6975172">[pdf]</a></p> <p><strong>Method</strong></p> <p>The images are evaluated by 188 observers using Dynamic Reference (DR-ACR) method (explained below). A separate scale realignment ACR data consisting evaluations from 34 observers is also included that allows to combine the data from the six image sets</p> <p>In other respects the DR-ACR method resembles very much a basic Absolute Category Rating (ACR) method (ITU-R 500-11), except the observers saw a slideshow of all the other images in the test depicting the same scene before every evaluation (See DR_demo.mp4). By seeing the other images in the test setup as reference the observers were more aware of the total variation of quality represented within a single image set. This improved their evaluation as they didn’t need to save the far ends of the scale in case there would be even more better or worse image later on the experiment. The DR-ACR method is explained in detail in:</p> <p>Mikko Nuutinen, Toni Virtanen, Tuomas Leisti, Terhi Mustonen, Jenni Radun, Jukka Häkkinen (2014) A new method for evaluating the subjective image quality of photographs : dynamic reference Multimedia Tools and Applications 75: 4. 2367-2391 Dec.</p> <p>Database contains consumer camera images and their subjective evaluations in mean opinion score (MOS), sharpness, graininess, lightness and color saturation scales. It includes the complete raw data and background information from the naïve observers used to evaluate the images. Subjects’ vision was controlled for the near visual acuity, near contrast vision (near F.A.C.T.) and color vision (Farnsworth D15) before the participation. They received movie tickets as a reward. Outlier removal is made for mean opinion score (MOS) evaluations using ITU-R 500-11 recommendations to ease out the implementation of the database.</p> <p><strong>Material</strong></p> <p>The images in CID2013 are intended to represent typical photographs that consumers might capture with their cameras. The photographed scenes were based partly on the Photospace approach described by I3A (CPIQ Initiative Phase 1 White Paper: Fundamentals and review of considered test methods, I3A, 2007) The I3A CPIQ project has migrated under IEEE.</p> <p><strong>The test environment</strong></p> <p>The room has been covered with medium gray curtains to diffuse the ambient illumination. Fluorescent lights (5800K) were positioned behind the monitors and reflected from the back wall covered with grey curtain to create dim and uniform ambient illumination in the room. The light hitting the monitors measured below 20 lx. The subject’s viewing distance (approximately 80 cm) was controlled by a line hanging from the ceiling, and they were instructed to keep their forehead steady next to the line. Because of the display size, images were scaled to a size of 1600 x 1200 pixels using the bicubic interpolation method. Eizo ColorEdge CG241W, with 1920x1200 pixel resolution, monitors in was calibrated to sRGB having target values of: 80 cd/m2, 6500K and gamma 2.2 using EyeOne Pro calibrator (X-rite co.).</p> <p> </p> <p>-----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------</p> <p>Copyright (c) 2014 The University of Helsinki<br> All rights reserved.</p> <p>Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this database (the videos, the images, the results and the source files) and its documentation for any purpose, provided that the copyright notice in its entirely appear in all copies of this database, and the original source of this database,Visual Cognition research group (www.helsinki.fi/psychology/groups/visualcognition/index.htm) and the Institute of Behavioral Science (www.helsinki.fi/ibs/index.html) at the University Helsinki (www.helsinki.fi/university/), is acknowledged in any publication that reports research using this database. Individual videos and images may not be used outside the scope of this database (e.g. in marketing purposes) without prior permission.</p> <p>The database and our paper are to be cited in the bibliography as:</p> <p>-----------------------------------------------------------------------------<br> Virtanen, T., Nuutinen, M., Vaahteranoksa, M., Oittinen, P. and Häkkinen, J. “CID2013: a database for evaluating no-reference image quality assessment algorithms”, IEEE Transactions on Image Processing, 2014, In press.<br> -----------------------------------------------------------------------------</p> <p>LIMITATION OF LIABILITY</p> <p>UNIVERSITY OF HELSINKI SHALL IN NO CASE BE LIABLE IN CONTRACT, TORT OR OTHERWISE FOR ANY LOSS OF REVENUE, PROFIT, BUSINESS OR GOODWILL OR ANY DIRECT, INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL OR PUNITIVE COST, DAMAGES OR EXPENSE OF ANY KIND HOWEVER CAUSED OR HOWEVER ARISING UNDER OR IN CONNECTION WITH THE USE OF THIS DATABASE.</p> <p>THE UNIVERSITY OF HELSINKI SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATABASE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF HELSINKI HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.</p> <p>THIS AGREEMENT SHALL BE CONSTRUED AND INTERPRETED IN ACCORDANCE WITH THE LAWS OF FINLAND, EXCLUDING ITS RULES FOR CHOICE OF LAW.</p> <p>-----------COPYRIGHT NOTICE ENDS WITH THIS LINE------------</p> <p> </p>
From fine sand to boulders: examining the relationship between beach-face slope and sediment size. Dataset and references.
<p>A collection of 2144 pairs of beach-face slope and median sediment size measurements gathered from 78 publications that covers the whole range of coastal sediments.<br> </p> <p>Size-Slope-Data-Points.ods :<br> Size/slope values and their references. The 'Type' column separates beaches from boulder ridges.</p> <p>Size-Slope-References.ods :<br> Details of each reference used.</p> <p> </p>
SYNOPSIS OF SPECIES WITH PAGE AND PLATE REFERENCES. in New genera and species from the Belly River Series (mid-Cretaceous)
SYNOPSIS OF SPECIES WITH PAGE AND PLATE REFERENCES.
The miRBase release 22 reference files: stem-loop sequences (hairpins) and mature miRNA sequences
<pre>The miRBase Sequence Database -- Release 22 ------------------------------------------- The miRBase database provides a searchable online repository for published microRNA sequences and associated annotation. miRBase also provides a gene naming and nomenclature function in the miRBase Registry. Release 22 of the database contains 38589 entries representing hairpin precursor miRNAs, expressing 48885 mature miRNA products, in 271 species. The data are freely available to all through the web interface at http://www.mirbase.org/ and in flatfile form from ftp://mirbase.org/pub/mirbase/. </pre>
Comparison of Reference Setups for Calibrating Power Transformer Loss Measurement Systems
<p>Data set belonging to the IEEE Trans. Instr. Meas. paper with DOI: <a href="https://doi.org/10.1109/TIM.2018.2879171">10.1109/TIM.2018.2879171</a></p> <p>G. Rietveld, E. Mohns, E. Houtzager, H. Badura, and D. Hoogenboom,<br> <em>Comparison of Reference Setups for Calibrating Power Transformer Loss Measurement Systems</em></p> <p>This project has received funding from the European Metrology Programme for Innovation and Research co-financed by the Participating States and in part by the European Union’s Horizon 2020 Research and Innovation Programme.</p>
Figure 1 in Waterbirds of Arunachal Pradesh with special reference to high altitude rivers and wetlands
Figure 1. Map of the study Namdapha Tiger Reserve, Arunachal Pradesh.
Figure 1 in Validation of reference genes for quantitative expression analysis by qPCR in various tissues of date mussel (Lithophaga lithophaga)
Figure 1. Distribution of Cq values of candidate reference genes in date mussel (L. lithophaga).
Figure 2 in Validation of reference genes for quantitative expression analysis by qPCR in various tissues of date mussel (Lithophaga lithophaga)
Figure 2. Average expression stability (M-value) of reference genes evaluated by geNorm.
MMSEQS meets AntiRef90: reference clusters of human antibody sequences
<p>This data set contains pre-computed mmseqs databases for the antiref fasta files created by <em>Briney et al.</em> </p> <p>Please cite the original work if you use any of the databases provided here.</p> <p>Sources:</p> <ul> <li><a href="https://github.com/brineylab/antiref">Antiref GitHub</a></li> <li><a href="../records/7474336">Antiref Zenodo</a></li> <li><a href="https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad109/7247530?login=true">Antiref Paper</a></li> </ul> <p> </p> <p>The mmseqs databases were created as follows:</p> <p> </p> <p>```</p> <p>aria2x -x16 -s16 --input-file antiref_links.txt<br>snakemake -s antiref_mmseqs.smk --jobs 1 --cores 1 --local-cores 250</p> <p>```</p> <p> </p> <p>Please check the summary repository for the fasta files and snakemake files. In this sub repo we only store the antiref files matching the title of the repo.</p> <p> </p>
Experimental raw data sets associated with certified reference material BAM-P115 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 140 to 154 m²/g<br>Expected specific surface area for argon (BET): 129 to 135 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Experimental raw data sets associated with certified reference material BAM-P114 (titanium dioxide) for comparison of nitrogen and argon sorption, available in the universal adsorption information format (AIF)
<p>These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.<br>The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.<br>It is recommended to use the following requirements for the molecular cross-sectional area:<br>Nitrogen: 0.1620 nm²<br>Argon: 0.1420 nm²</p> <p>Expected specific surface area for nitrogen (BET): 24 to 25 m²/g<br>Expected specific surface area for argon (BET): 20 m²/g</p> <p>Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.<br>The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.<br>These data are stored in the universal AIF format (adsorption information format), which allows flexible use of the data.</p>
Food Choice Motives of Guardians of Trilok Academy Kathmandu with reference to Gender
Open the record for dataset details and reuse information.
A Novel Integrated Reference-Counter Electrode for Electrochemical Measurements of HOMO and LUMO Levels in Small-Molecule Thin-Film Semiconductors for OLEDs
<p>This dataset <span>includes all raw data, processed data, and analysis scripts necessary to replicate the findings reported in the published paper.</span></p>
Updated annotation for Aedes aegypti reference genome AaegL5 with extended 3' UTRs
<p>Updated annotation file for the AaegL5 genome generated and used in the Adavi et al. 2024 <em>bioRxiv </em>preprint: https://doi.org/10.1101/2024.08.21.608847</p> <p>Key updates (to VectorBase-55_AaegyptiLVP_AGWG.gff) include:</p> <ul> <li>Addition of several chemoreceptors that were annotated in previous work</li> <li>Automated extension of 3' UTRs (by up to 750bp) for all genes where supported by antennal neuron snRNAseq data</li> <li>Further manual extension of 3'UTRs for some chemoreceptors where supported by antennal neuron snRNAseq data</li> </ul> <p>For more information on this annotation and the way it was generated, please see the Methods section of the above preprint.</p>
Reference genome of Digitaria radicosa
<p>The reference genome and annotation data of <em>Digitaria radicosa</em>.</p> <p>Publication: A chromosome-scale genome assembly of Timorese crabgrass (<em>Digitaria radicosa</em>): a useful genomic resource for the Poaceae. doi: https://doi.org/10.1101/2024.05.14.594087</p>
Gold, Lanthanum, Gallium, Cobalt and Tantalum quantification performed with relative standardization-NAA in candidate electronic waste (LED) reference material within the METROCYCLEEU project
<p>Datasets containing uncertainty budgets of measurements performed with Neutron Activation Analysis (NAA) on electronic waste materials (specifically light-emitting diodes, LED).</p> <p>Results reported in the datasets are part of the characterization of CRM candidate material LED.</p> <p>Data are elaborated and resulting dataset files are obtained with INAA-INRIM 3.1 software, pre-release development version.</p>
ScienceDex guides
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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.