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3,696 results for “Reference”
Network of reference tree-ring chronologies for forensic botanical (dendrochronological) examinations and dating of architectural structures in the Tyva Republic.
<p>The database consists of tables. First sheet - general description of tree-ring chronologies (general information: name of chronology, authors, data type, tree-ring parameter, notes, key words; description of sample collection site: site name, location, region, latitude, longitude, height; description of sample collection: collection code designation, number of series, year of first ring, year of last ring, maximum length of sample, average width of year ring; species affiliation - species; support - grant number). Second sheet, first column - years, second column - standardized growth value. The third sheet is a PDF document containing the results of independent testing in the program COFECA (the file is opened by the command: right-click/Acrobat Document object/open). The database is implemented in the OpenOffice.org Calc spreadsheet processor. The table file format is an internal OpenOffice.org Calc format, with the extension .ods. The data is accessed and structured using the standard tools "Sort", "Autofilter", etc. In the database, the integrity restriction control is not implemented, the user is invited to monitor the integrity of the database himself. Computer type: IBM PC. PC; OS: Windows 10.</p> <p>Type and version of the database management system: OpenOffice.org Calc.</p> <p>Database size: 5.6 MB</p>
CheckM v1 reference data
<p><strong>Precalculated data files for CheckM v1.<br> <br> Manuscript:</strong><br> CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes.<br> https://genome.cshlp.org/content/early/2015/05/14/gr.186072.114</p> <p><strong>Installation instructions:</strong><br> https://github.com/Ecogenomics/CheckM/wiki/Installation#how-to-install-checkm.</p>
AntiRef: reference clusters of human antibody sequences
<p><strong>Motivation:</strong> Biases in the human antibody repertoire result in publicly available antibody sequence datasets containing many duplicate or highly similar sequences. These redundant sequences are a barrier to rapid similarity searches and reduce the efficiency with which these datasets can be used to train statistical or machine learning models of human antibodies. Identity-based clustering provides a solution, however, the extremely large size of available antibody repertoire datasets make such clustering operations computationally intensive and potentially out of reach for many scientists and researchers who would benefit from such data.</p> <p><strong>Results:</strong> AntiRef (Antibody Reference Clusters), which is modeled after UniRef, provides clustered datasets of filtered human antibody sequences. Starting from a dataset of ~335M unique, full-length, productive human antibody sequences from the Observed Antibody Space repository, several AntiRef cluster sets were generated. Due to the modular nature of recombined antibody genes, the clustering thresholds used by UniRef (100, 90 and 50 percent identity) to cluster general protein sequences are suboptimal for antibody clustering. AntiRef provides reference antibody sequence datasets clustered at a range of relevant identity thresholds: 100, 99, 98, 96, 94, 92 and 90 percent. AntiRef90, which uses the lowest clustering threshold of any AntiRef dataset, is roughly one-third the size of the filtered input dataset and less than half the size of the non-redundant AntiRef100.</p> <p><strong>Datasets:</strong> AntiRef comprises a series of datasets, each representing one of several clustering thresholds. AntiRef datasets were generated by a nested clustering procedure similar to UniRef which, proceeding in order of decreasing stringency, clusters the representative sequences from the preceding round of clustering. AntiRef datasets can be found at the following links:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.7474657">AntiRef100</a>: representative sequences resulting from clustering all filtered AntiRef input sequences at 100% identity.</li> <li><a href="https://doi.org/10.5281/zenodo.7475961">AntiRef99</a>: representative sequences resulting from clustering AntiRef100 at 99% identity.</li> <li><a href="https://doi.org/10.5281/zenodo.7476040">AntiRef98</a>: representative sequences resulting from clustering AntiRef99 at 98% identity.</li> <li><a href="https://doi.org/10.5281/zenodo.7487182">AntiRef96</a>: representative sequences resulting from clustering AntiRef98 at 96% identity.</li> <li><a href="https://doi.org/10.5281/zenodo.7487199">AntiRef94</a>: representative sequences resulting from clustering AntiRef96 at 94% identity.</li> <li><a href="https://doi.org/10.5281/zenodo.7487264">AntiRef92</a>: representative sequences resulting from clustering AntiRef94 at 92% identity.</li> <li><a href="https://doi.org/10.5281/zenodo.7487298">AntiRef90</a>: representative sequences resulting from clustering AntiRef92 at 90% identity.</li> </ul> <p><strong>Files:</strong> The following files are included in the primary AntiRef data repository:</p> <ul> <li><em>antiref_cluster-manifest.csv.gz:</em> A compressed CSV file containing the cluster assignments for every sequence in the AntiRef input dataset. For each AntiRef round, cluster names correspond to the sequence ID of the representative sequence (as determined by MMSeqs2). The nested clustering process conserves cluster names between iterations, meaning the clustering lineage of any sequence can easily be traced across all AntiRef datasets.</li> <li><em>download_heavy.txt</em>: A plain text file (generated by the <a href="http://opig.stats.ox.ac.uk/webapps/oas/">Observed Antibody Space</a>) containing the commands necessary to download all antibody heavy chain sequences used to create AntiRef.</li> <li><em>download_light.txt:</em> A plain text file (generated by the <a href="http://opig.stats.ox.ac.uk/webapps/oas/">Observed Antibody Space</a>) containing the commands necessary to download all antibody light chain sequences used to create AntiRef.</li> </ul> <p><strong>Code:</strong> All code used to generate AntiRef (data download, filtering, and clustering) is available under the MIT license on <a href="http://www.github.com/briney/antiref">GitHub</a>.</p>
REFERENCES DATASET: A SYSTEMATIC REVIEW OF THE EDUCATIONAL USE OF MOBILE PHONES IN TIMES OF COVID-19
<p>The article "A systematic review of the educational use of mobile phones in times of COVID-19" aims to review what research has delved into the educational use of mobile phones during the COVID-19 pandemic. To do this, 38 papers indexed in the Journal Citation Reports database between 2020 and 2021 were analyzed. These works were categorized into the following categories: the mobile phone as part of educational innovation, improvement of results and academic performance, positive attitude towards mobile phone use in education, and risks and/or barriers to mobile phone use. The conclusions show that most teaching innovation experiences focus more on the device than on the student. Beyond its innovative nature, the mobile phone became a tool to allow access and continuity of training during the pandemic, especially in post-compulsory and higher education.</p> <p>This data set is composed of the table with the references used for the review.</p> <p> </p>
WorldCereal open global harmonized reference data repository (CC-BY-SA licensed data sets)
<p>Within the<strong> ESA funded</strong> WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets.</p> <p>This publication includes those harmonized data sets of which the original data set was published under the CC-BY-SA license or a license similar to CC-BY-SA. See document "_In-situ-data-World-Cereal - license - CC-BY-SA.pdf" for an overview of the original data sets.</p>
WorldCereal open global harmonized reference data repository (CC-BY licensed data sets)
<p>Within the <strong>ESA funded </strong>WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets.</p> <p>This publication includes those harmonized data sets of which the original data set was published under the CC-BY license or a license similar to CC-BY. See document "_In-situ-data-World-Cereal - license - CC-BY.pdf" for an overview of the original data sets. </p>
GNSS velocity fields in China and its vicinity under the Eurasian reference
<p>The dataset illustrates the GNSS velocities in China and its vicinity under the Eurasian reference used for calculating the strain rate field.</p>
NanoXSpot project : NxS Tool reference images
<p>The files within this dataset contain digital X-ray images that can be used to evaluate the spot size and shape parameters of simulated or physical X-ray tubes. The images were generated within the scope of NanoXSpot project by means of simulation tools or through experimental acquisitions.</p> <p>The images are organised in folders, depending on the patterns and gauge type, which are specified in the folder name. The images were acquired or generated for different CT systems. The important parameters for evaluation are provided in the file “Systems_parameters.txt”. Each folder contains a .csv file with the output of the NxS Tool. A file containing this description is also included at the root of each main folder, named “_readme.pdf”.</p> <p>The datasets serve as references for the NxS Tool developed by CEA List and freely available for public use, that can be downloaded from the following webpage: <a href="https://nanoxspot-project.cea.fr/NxS%20Tool%20Description/NxS%20Tool%20Releases">NanoXSpot Project - NxS Tool Public Releases (cea.fr)</a></p> <p>The files were intentionally anonymised after the explicit consent from each organization that they can be used in the reference datasets.</p> <p><strong>Image evaluation</strong></p> <p>The image evaluation was carried out using <a href="https://nanoxspot-project.cea.fr/Lists/StaticFiles/v2022.09/NxS_Tool_setup_v2022.09.exe.7z">NxS Tool v2022.09</a>. The user manual is provided on the following web page: <a href="https://nanoxspot-project.cea.fr/NxS%20Tool%20Description/NxS_Tool_User_Manual">NanoXSpot Project - NxS Tool User Manual (cea.fr)</a>.</p> <p><strong>Acknowledgements</strong></p> <p>The NanoXSpot project has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme (EURAMET – EMPIR programme, project id 18NRM07).</p> <p> </p> <p><strong>Terms of use</strong></p> <p>THESE DATASETS ARE PROVIDED BY THE NANOXSPOT CONSORTIUM EACH ONE AS IS AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL ANY OF NANOXSPOT CONSORTIUM PARNERS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</p>
Fig. 1 in A review of the fossil record of spiders (Araneae) with special reference to Africa, and description of a new specimen from the Triassic Molteno Formation of South Africa
Fig. 1. Summary phylogenetic tree of Araneae, produced by combining the fossil record with the cladograms of Coddington and Levi (1991), Griswold (1993), Scharff and Coddington (1997), Griswold et al. (1998, 1999), and Ramírez (2000).
Fig. 2 in A review of the fossil record of spiders (Araneae) with special reference to Africa, and description of a new specimen from the Triassic Molteno Formation of South Africa
Fig. 2. Location map of the Telemachus Spruit locality (Eastern Cape, South Africa) in relation to the outcrop of the Late Triassic Molteno Formation (shown in black) (after Anderson et al. 1998).
Figs 4, 5. T. andersonorum specimen PRE-F 17234 Tel 111 in A review of the fossil record of spiders (Araneae) with special reference to Africa, and description of a new specimen from the Triassic Molteno Formation of South Africa
Figs 4, 5. T. andersonorum specimen PRE-F 17234 Tel 111 from Telemachus Spruit: (4) camera lucida illustration, (5) actual fossil dry (A) and under ethanol (B). Abbreviations: fe – femur, mt – metatarsus, pa – patella, ta – tarsus, ti – tibia. Scale bar = 0.5 mm.
Figs 28–31 in A review of the volvatory Polydesmida, with special reference to the patterns of volvation (Diplopoda)
Figs 28–31. Scanning electron micrographs of Amphitomeus attemsi (Schubart, 1934) (Oniscodesmidae), cross-section of a midbody segment and caudal body end, front, lateral, ventral, and dorsal views, respectively. [All after Golovatch et al. (2002) (reprinted courtesy of Arthropoda Selecta).]
Figs 32–36 in A review of the volvatory Polydesmida, with special reference to the patterns of volvation (Diplopoda)
Figs 32–36. Structure of some 'oniscoid' Polydesmida. 32. Amphitomeus attemsi (Schubart, 1934) (Oniscodesmidae), left gonopod, caudal view. 33 & 34. Elassystremma sp. (Ammodesmidae), entire animal and ventral side of male body segment 7, lateral and ventral views respectively. 35 & 36. Hyperothrix orophura Attems, 1900 (?Pyrgodesmidae), anterior body portion and left gonopod, lateral and caudal views, respectively. [32 after Golovatch et al. (2002) (reprinted courtesy of Arthropoda Selecta); 33 & 34 after Van den Spiegel (in prep.) (reprinted courtesy of the Royal Museum for Central Africa, Nadine Van Noppen del.); 35 & 36 after Attems (1900). Scale bar 0.1 mm (32), others reproduced not to scale.]
Figs 45 & 46. Asphalidesmus leae Silvestri, 1910 in A review of the volvatory Polydesmida, with special reference to the patterns of volvation (Diplopoda)
Figs 45 & 46. Asphalidesmus leae Silvestri, 1910 (Dalodesmoidea). 45. Entire male body, lateral view. 46. Anterior male body end, ventral view. [Both after Mesibov (2002) (reprinted courtesy of the Museum of Victoria). Scale bars 1.0 mm and 0.5 mm, respectively.]
Figs 22–27 in A review of the volvatory Polydesmida, with special reference to the patterns of volvation (Diplopoda)
Figs 22–27. Scanning electron micrographs of some 'oniscoid' Polydesmida. 22 & 23. Elassystremma sp. (Ammodesmidae), anterior body portion and ventral side of male body segment 7, lateral and subcaudal views, respectively. 24–27. Amphitomeus attemsi (Schubart, 1934) (Oniscodesmidae), entire animal, paraterga 2–7, and anterior body end, lateral, lateral, subdorsal, and lateral views, respectively. [22 & 23 after Van den Spiegel (in prep.) (reprinted courtesy of the Royal Museum for Central Africa); 24–27 after Golovatch et al. (2002) (reprinted courtesy of Arthropoda Selecta).]
Figs 12–21 in A review of the volvatory Polydesmida, with special reference to the patterns of volvation (Diplopoda)
Figs 12–21. Structure of some 'oniscoid' Polydesmida. 12–14. Crenatidorsus grandifoliatus Zhang & Wang, 1993 (Doratodesmidae), anterior body portion, left half of body segment 7, and left gonopod, lateral, ventral, and mesal views, respectively. 15 & 16. Ascetophacus macclurei Hoffman, 1977 (Doratodesmidae), anterior body portion and cross-section of a midbody segment, lateral and caudal views, respectively. 17–19. Crypturodesmus sp. (Oniscodesmidae), anterior body portion, right half of body segment 7, and caudal body end, lateral, ventral, and ventral views, respectively. 20 & 21: Cyrtodesmus sp. (Cyrtodesmidae), anterior and posterior body portions, lateral view. [12 & 13, original, male from China, Yunnan, Mengzi County, Cave Chi Be Yi Dong, 07.01.1989, leg. P. Beron (Sofia Museum); 14 after Zhang & Wang (1993); 15 & 16 after Hoffman (1977) (reprinted courtesy of Bishop Museum Press); 17–19, original, male from Brazil, Mato Grosso do Sul, Bonito, Gruto da Carneiro, 6–8.04.1998, leg. R. Pinto-da-Rocha & G. Sessegolo (São Paulo Museum); 20 & 21, original, male from Peru, Prov. Loreto, island at mouth of Yanayacu River, ca 65 km downstream Rio Amazonas from Iquitos, whitewater inundation forest, rotton wood, 22.03.1998, leg. J. Adis, S. Golovatch & A. Mármol (Moscow Museum). Scale bar 1.0 mm (12 & 13) and 2.0 mm (17–21), others reproduced not to scale.]
Figs 1–11 in A review of the volvatory Polydesmida, with special reference to the patterns of volvation (Diplopoda)
Figs 1–11. Structure of some 'oniscoid' Diplopoda. 1: Glomeroides sp. (Glomeridae, Glomerida), lateral view (S = schism, or suture; H = hyposchism, or field below schism; Pg = pygidium). 2 & 3. Sphaeriodesmus sp. (Sphaeriodesmidae, Polydesmida), anterior body portion (III and IV = segment numbers) and cross-section of a midbody segment, lateral and caudal views, respectively. 4–6: Proeilodesmus mecistonyx Hoffman, 1990 (Sphaeriodesmidae, Polydesmida), cross-section of a midbody segment, right half of male body segment 7, and right gonopod, caudal, ventral, and lateral views, respectively. 7. Dorsoporus barroensis Loomis, 1958 (Dorsoporidae, Polydesmida), anterior body portion, lateral view (OZ = ozopore). 8–11. Campodesmus dilobatus (Schiøtz, 1966) (Campodesmidae, Polydesmida), anterior body portion, cross-section of a midbody segment, gonopods in situ, and left gonopod, lateral, front, ventral, and mesal views, respectively. [1 & 2 after Hoffman et al. (2002) (reprinted courtesy of Pensoft Publishers); 3–6 after Hoffman (1990) (reprinted courtesy of the Swiss Zoological Society); 7 after Loomis (1958) (reprinted courtesy of the Journal of the Washington Academy of Sciences); 8–11 after Schiøtz (1966) (reprinted courtesy of the Danish Natural History Society). Scale bars 0.5 mm (10 & 11) and 2.0 mm (8 & 9), others reproduced not to scale.]
Bearings damage dataset for the 5 MW reference drivetrain on spar type floating wind turbine
<p>This dataset contains simulated acceleration measurements for the 5MW reference drivetrain model installed on a spar-type floating wind turbine. Measurements are one-hour simulations with a sample rate of 200 Hz. See Data description file for details.</p> <p>How to cite: Dibaj, Ali, & Nejad, Amir. (2023). Bearings damage dataset for the 5 MW reference drivetrain on spar type floating wind turbine [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7674842</p>
Phylogenetic profile of 100 annotated low complexity proteins against the Uniprot Reference Proteome dataset
<p>Phylogenetic profile of 100 human proteins with characteristic compositional bias, previously recorded by Mier et al (2020) against the Uniprot Reference Proteome, containing a total of 11297 proteomes, excluding viruses. The counts for each protein correspond to homologs found in each proteome. </p> <p>Detailed description of included columns:</p> <p><strong>ref_proteome_identifier</strong>: The<strong> </strong>Uniprot Reference Proteome identifier</p> <p><strong>ncbi_taxid</strong>: The NCBI taxonomy ID</p> <p><strong>species_name</strong>: NCBI common name corresponding to taxonomy ID</p> <p><strong>species_code</strong>: internal species code composed of 9 characters</p> <p><strong>taxonomic domain</strong>: E/B/A for Eukaryota/Bacteria/Archaea classification of proteome</p> <p> </p>
BAM reference data: results of ASTM E139 -11 creep tests on a reference material of Nimonic 75 nickel-base alloy
<p>Results of creep tests on a certified reference material at T = 600°C and a tensile creep load of 160 MPa are provided. The raw data are available in ASCII format (*.lis files). <br> The file "Inhalt_Content_V1.1.pdf" contains further information about the files provided.<br> The evaluated results include the times to reach 2% and 4% creep strain, respectively, and the creep rate after 400 h.</p> <p>The tests were carried out in an accredited test laboratory. The calibrations of all measurands and test and measuring equipment are documented. The calibrations meet the requirements of the test procedure and are metrologically traceable.</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.