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1,254 results for “PANs”
PAN Plagiarism Corpus 2011 (PAN-PC-11)
<p>The PAN plagiarism corpus 2011 (PAN-PC-11) is a corpus for the evaluation of automatic plagiarism detection algorithms. For research purposes the corpus can be used free of charge.</p> <p>The PAN-PC-11 contains documents in which plagiarism has been inserted automatically as well as documents in which plagiarism has been inserted manually. The former have been constructed using a so-called random plagiarist, a computer program which constructs plagiarism according to a number of parameters, while the latter have been obtained with crowdsourcing via Amazon's Mechanical Turk.</p>
PAN Wikipedia Quality Flaw Corpus 2012 (PAN-WQF-12)
<p>The PAN Wikipedia Quality Flaw Corpus 2012, PAN-WQF-12, provides human-labeled English Wikipedia articles that contain specific quality flaws.</p> <p>The corpus comprises 1,592,226 articles extracted from the English Wikipedia snapshot from January 4th, 2012. A subset of 208,228 articles is labled with ten specific quality flaws, which are listed in the following table. The labeling is based on human-defined cleanup tags. In addition, the corpus comprises 1,383,998 articles that have not been tagged with any cleanup tag.</p>
PAN Wikipedia Vandalism Corpus 2010 (PAN-WVC-10)
<p>The PAN Wikipedia Vvandalism Ccorpus 2010 (PAN-WVC-10) is a corpus for the evaluation of automatic vandalism detectors for Wikipedia. For research purposes the corpus can be used free of charge.</p> <p>This corpus is supplemented by the <a href="https://doi.org/10.5281/zenodo.3342157">PAN-WVC-11</a>, which features additional edits in English, Spanish and German. Both corpora should be used to get more representative results.</p> <p>As part of our research on automatic vandalism detection we have compiled a corpus of vandalism cases found in Wikipedia. The corpus compiles 32452 edits on 28468 Wikipedia articles, among which 2391 vandalism edits have been identified. To annotate the corpus we have used Amazon's Mechanical Turk; 753 workers have been recruited who cast more than 150000 votes on the edits, so that each edit was reviewed by at least 3 annotators. The achieved level of agreement was analyzed in order to label an edit as "regular" or "vandalism."</p>
PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11)
<p>The PAN Wikipedia Vandalism Corpus 2011 (PAN-WVC-11) is a corpus for the evaluation of automatic vandalism detectors for Wikipedia. For research purposes the corpus can be used free of charge.</p> <p>This corpus supplements the <a href="https://doi.org/10.5281/zenodo.3341488">PAN-WVC-10</a>, which features only English edits. Both corpora should be used to get more representative results.</p> <p>The corpus compiles 29949 edits on 24351 Wikipedia articles, among which 2813 vandalism edits have been identified. The corpus features 9985 English edits, 9990 German edits, and 9974 Spanish edits. To annotate the corpus we have used Amazon's Mechanical Turk; each edit was presented to a number of annotators who were asked to decide whether it is vandalism or regular, and the agreement of the annotators was analyzed in order to label an edit.</p>
SELIS platform for pan-European logistics applications datasets
<p>This publication comes as a result of the SELIS H2020 project (<a href="http://www.selisproject.eu">http://www.selisproject.eu</a>). The provided datasets are anonymized samples of the real data which describe some of the use cases we have encountered.</p> <p>In the interest of the Open Research Data Pilot, this publication (<a href="https://github.com/selisproject/selis-node-connectors">https://github.com/selisproject/selis-node-connectors</a>) provides a basic implementation of connectors used in real world applications for supply chain participants to connect and funnel their data to the SELIS Community Node (SCN). The prototype of the SELIS big data analytics and machine learning infrastructure is also openly available (<a href="https://github.com/selisproject/bda">https://github.com/selisproject/bda</a>).</p> <p>Along with the connectors, obfuscated/test data is also provided for each solution. The connectors all follow the same approach, which is parsing the data provided, transforming them into a SCN-compatible data exchange model and publishing them to the SCN under a specific configuration. The samples provided cover two use cases:</p> <p><strong>Adria Kombi Data set: </strong>This anonymized data set which includes 24 csv files describes a use case developed for the SELIS project. It involves the (as accurate as possible) estimation of time of arrival (ETA) for individual freight trains using historical data and live feeds.</p> <p><strong>SONAE Data set: </strong>This anonymized data set which includes 2 csv files describes a different use case developed for the same project. This specific use case involves the automatic generation of suggested order forecasts for a retailer (SONAE) given stock level data from different warehouses and information such as lead time (minimum time required from order till delivery) per product and supplier, delivery days etc.</p> <p> </p> <p><em>For a more detailed description of the data please refer to the README.md files included in the downloadable zipped directories.</em></p> <p> </p> <p> </p>
Figure. Location of the study area in the Czech Republic near Nové Losiny village (marked by star), delimitation of the studied meadows and placement of pan-traps transects within them. in Comparison of two methods for sampling orthopterans in grassland: differences in species representation and sex ratios
Figure. Location of the study area in the Czech Republic near Nové Losiny village (marked by star), delimitation of the studied meadows and placement of pan-traps transects within them.
Figure 6 in Kinorhynchs from sandy coastal habitats in Turkey, with the description of a new pan-Mediterranean species of Echinoderes (Cyclorhagida: Echinoderidae)
Figure 6. Light micrographs showing overviews and details of female Echinoderes riedli, NHMD-872891, from Balıkesir, Ayvalık, Turkey. (A) Ventral overview. (B) Segments 1 to 6, dorsal view. (C) Segments 1 to 6, ventral view. (D) Segments 6 to 9, dorsal view. (E) Segments 5 to 9, ventral view. (F) Segments 10 to 11, focusing on tergal extensions. Abbreviations: ltas, lateral terminal accessory spine; lvs, lateroventral spine; lvt, lateroventral tube; mdgco1, middorsal glandular cell outlet type 1; mds, middorsal spine; pdgco1, paradorsal glandular cell outlet; te, tergal extensions; vlt, ventrolateral tubes.
Figure 7 in Kinorhynchs from sandy coastal habitats in Turkey, with the description of a new pan-Mediterranean species of Echinoderes (Cyclorhagida: Echinoderidae)
Figure 7. Light micrographs showing overviews and details of (A–E, G–I) male Echinoderes sp. from Muğla, NHMD-872893, and (F) male paratype of Echinoderes charlotteae, ZMUC KIN-870, from the Gulf of Mexico. (A) Ventral overview. (B) Segments 1 to 5, dorsal view. (C) Segments 1 to 5, ventral view. (D) Segments 4 to 8, dorsal view. (E–F) Segment 8, ventral view, comparison of tube positions in (E) Echinoderes sp. and (F) E. charlotteae. (G) Segments 8 to 10, dorsal view. (H) Segments 10 to 11, dorsal view. (I) Segments 10 to 11, ventral view. Abbreviations: lat, lateral accessory tube; lts, lateral terminal spine; lvs, lateroventral spine; lvt, lateroventral tube; mdgco1, middorsal glandular cell outlet type 1; mds, middorsal spine; pdgco1, paradorsal glandular cell outlet type 1; pdss, paradorsal sensory spot; pe, penile spine; sdgco2, subdorsal glandular cell outlet type 2; slgco2, sublateral glandular cell outlet type 2; slt, sublateral tube; te, tergal extensions; vlt, ventrolateral tubes.
Figure 3 in Kinorhynchs from sandy coastal habitats in Turkey, with the description of a new pan-Mediterranean species of Echinoderes (Cyclorhagida: Echinoderidae)
Figure 3. Diagram of mouth cone (grey area), introvert and placids in Echinoderes shahmaranae sp. nov., showing distribution of inner oral styles (full circles), outer oral styles (diamonds), primary scalids (triangles), spinoscalids (fat open circles), and trichoscalids (stars), with positions of trichoscalid plates and placids indicated. Table shows the scalid arrangement by sector; single-lined boxes mark quincunxes, double- lined boxes mark "double diamonds".
Figure 4 in Kinorhynchs from sandy coastal habitats in Turkey, with the description of a new pan-Mediterranean species of Echinoderes (Cyclorhagida: Echinoderidae)
Figure 4. Light micrographs showing overviews and details of (A–H) male holotype, NHMD-872854, and (I) female paratype, NHMD- 872856, of Echinoderes shahmaranae sp. nov. from Fethiye, Turkey. (A) Ventral overview. (B) Segments 1 to 3, dorsal view. (C) Segments 1 to 3, ventral view. (D) Segments 4 to 8, dorsal view. (E) Segment 5, ventral view. (F) Segments 6 to 8, ventral view. (G) Segments 8 to 10, dorsal view. (H) Detail of segments 10 to 11, dorsal view, showing male sexual dimorphism. (I) Segments 10 to 11, ventral view, showing female sexual dimorphism. Abbreviations: lat, lateral accessory tube; ldt, laterodorsal tube; ltas, lateral terminal accessory spine; lts, lateral terminal spine; lvs, lateroventral spine; lvt, lateroventral tube; mds, middorsal spine; pdgco1, paradorsal glandular cell outlet type 1; pe, penile spine; pvb, paraventral bristles; sdtu, subdorsal tubes; slgco2, sublateral glandular cell outlet type 2; te, tergal extensions; vlt, ventrolateral tubes.
Figure 2 in Kinorhynchs from sandy coastal habitats in Turkey, with the description of a new pan-Mediterranean species of Echinoderes (Cyclorhagida: Echinoderidae)
Figure 2. Line art illustrations of Echinoderes shahmaranae sp. nov. (A) Female, dorsal view. (B) Female, ventral view. (C) Segments 10 to 11 in male, dorsal view. (D) Segments 10 to 11 in male, ventral view. Abbreviations: lat, lateral accessory tube; ldt, laterodorsal tube; ltas, lateral terminal accessory spine; lts, lateral terminal spine; lvs, lateroventral spine; lvt, lateroventral tube; mdgco1, middorsal glandular cell outlet type 1; mds, middorsal spine; mlss, midlateral sensory spot; pdgco1, paradorsal glandular cell outlet type 1; pe, penile spines; pvb, paraventral bristles; sdss, subdorsal sensory spot; sdt, subdorsal tube; slgco1/2, sublateral glandular cell outlet type 1/2; slss, sublateral sensory spot; vlss, ventrolateral sensory spot; vlt, ventrolateral tube; vmss, ventromedial sensory spot.
Figure 8 in Kinorhynchs from sandy coastal habitats in Turkey, with the description of a new pan-Mediterranean species of Echinoderes (Cyclorhagida: Echinoderidae)
Figure 8. Scanning electron micrographs showing overviews and details of Cephalorhyncha flosculosa. (A) Lateral overview. (B) Segment 4, subdorsal view. (C) Segments 6 to 7, ventral view. (D) Segments 1 to 3, ventral view. (E) Segments 4 to 6, dorsal view. (F) Segments 10 to 11, dorsal view. Abbreviations: fl, flosculus; mdf, middorsal fissure; mds, middorsal spine; pdss, paradorsal sensory spot; pmf, partial midventral fissure; sdss, subdorsal sensory spot; vlt, ventrolateral tube; vmss, ventromedial sensory spot.
Figure 10 in Kinorhynchs from sandy coastal habitats in Turkey, with the description of a new pan-Mediterranean species of Echinoderes (Cyclorhagida: Echinoderidae)
Figure 10. Comparative light micrographs showing paraventral hair patches in selected echinoderids. Species with paraventral cuticular hairs of same length and thickness as hairs posterior rows on tergal plate (A–C): (A) Echinoderes hispanicus, segments 3 to 6. (B) Echinoderes horni, segments 3 to 6. (C) Echinoderes antalyaensis, segments 3 to 7. Species with conspicuously thicker and longer hairs than other cuticular hairs on segment: (D) Echinoderes bispinosus, segments 4 to 6. Paraventral areas with hairs are indicated with dashed squares.
Figs 2, 3 in Native bee fauna of tomato crops: a comparison of active sampling and pan trapping methods
Figs 2, 3. Richness (Fig. 2) and abundance (Fig. 3) of flower visiting bees sampled bY different pan trap colors in nine tomato crops in GoiÁs state, BraZil. Boxplots represent means while vertical lines represent the 95% confidence interval. Each point represents value for each sampling unit.
High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data
<p>We developed Pan-European maps of timber volume (V), above-ground biomass (AGB), and deciduous-coniferous proportion (DCP) with a pixel size of 10 x 10 m<sup>2</sup> for the reference year 2020 using a combination of a Sentinel 2 mosaic, Copernicus layers, and National Forest Inventory (NFI) data.</p> <p>For mapping, we used the k-Nearest Neighbor (kNN, k=7) approach with a harmonized database of species-specific V and AGB from 14 NFIs across Europe. This database encompasses approximately 151,000 sample plots, which were intersected with the above-mentioned Earth observation data. The maps cover 40<a> European countries, </a>forming a continuous coverage of the western part of the European continent.</p> <p>A sample of 1/3 of NFI plots was left out for validation, whereas 2/3 of the plots were used for mapping. Maps were created independently for 13 multi-country processing areas. Root-mean-squared-errors (RMSEs) for AGB ranged from 53 % in the Nordic processing area to <a>73 % </a>the South-Eastern area.</p> <p>The created maps are the first of their kind as they are utilizing a huge amount of harmonized NFI observations and consistent remote sensing data for high-resolution forest attribute mapping. While the published maps can be useful for visualization and other purposes, they are primarily meant as auxiliary information in model-assisted estimation where model-related biases can be mitigated, and field-based estimates improved. Therefore, additional calibration procedures were not applied, and especially high V and AGB values tend to be underestimated. Summarizing map values (pixel counting) over large regions such as countries or whole Europe will consequently result in biased estimates that need to be interpreted with care.</p> <p>The author list is sorted by last name except for the first and last authors who also serve as corresponding authors.</p> <p>Corresponding authors: <a href="mailto:Jukka.Miettinen@vtt.fi">Jukka.Miettinen@vtt.fi</a>, <a href="mailto:Johannes.Breidenbach@nibio.no">Johannes.Breidenbach@nibio.no</a></p>
Recommendations for reporting equivalent black carbon (eBC) mass concentrations based on long-term pan-European in-situ observations
<p>A reliable determination of equivalent black carbon (eBC) mass concentrations derived from filter absorption photometers (FAPs) measurements depends on the appropriate quantification of the mass absorption cross-section (MAC) for converting the absorption coefficient (babs) to eBC. This study investigates the spatial–temporal variability of the MAC obtained from simultaneous elemental carbon (EC) and babs measurements performed at 22 sites. We compared different methodologies for retrieving eBC integrating different options for calculating MAC including: locally derived, median value calculated from 22 sites, and site-specific rolling MAC. The eBC concentrations that underwent correction using these methods were identified as LeBC (local MAC), MeBC (median MAC), and ReBC (Rolling MAC) respectively. Pronounced differences (up to more than 50 %) were observed between eBC as directly provided by FAPs (NeBC; Nominal instrumental MAC) and ReBC due to the differences observed between the experimental and nominal MAC values. The median MAC was 7.8 ± 3.4 m2 g-1 from 12 aethalometers at 880 nm, and 10.6 ± 4.7 m2 g-1 from 10 MAAPs at 637 nm. The experimental MAC showed significant site and seasonal dependencies, with heterogeneous patterns between summer and winter in different regions. In addition, long-term trend analysis revealed statistically significant (s.s.) decreasing trends in EC. Interestingly, we showed that the corresponding corrected eBC trends are not independent of the way eBC is calculated due to the variability of MAC. NeBC and EC decreasing trends were consistent at sites with no significant trend in experimental MAC. Conversely, where MAC showed s.s. trend, the NeBC and EC trends were not consistent while ReBC concentration followed the same pattern as EC. These results underscore the importance of accounting for MAC variations when deriving eBC measurements from FAPs and emphasize the necessity of incorporating EC observations to constrain the uncertainty associated with eBC.</p>
Supporting data for RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data.
<p>This is the data repository for <em>RCANE: A Deep Learning Algorithm for Whole-genome Pan-Cancer Somatic Copy Number Aberration Prediction using RNA-seq Data</em>. To use this dataset, please refer to <a href="https://github.com/HowardGech/RCANE" target="_blank" rel="noopener">https://github.com/HowardGech/RCANE</a>.</p>
Linked collectors and determiners for: IB PAN Vascular Plant KRAM Herbarium.
Natural history specimen data linked to collectors and determiners held within, "IB PAN Vascular Plant KRAM Herbarium". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/69f4168d-9686-4762-be3e-d4ebc186150e">https://bionomia.net/dataset/69f4168d-9686-4762-be3e-d4ebc186150e</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/69f4168d-9686-4762-be3e-d4ebc186150e">https://gbif.org/dataset/69f4168d-9686-4762-be3e-d4ebc186150e</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Surveys of the bee (Hymenoptera: Apiformes) community in northern hardwood forest and wildlife clearings using pan traps.
Natural history specimen data linked to collectors and determiners held within, "Surveys of the bee (Hymenoptera: Apiformes) community in northern hardwood forest and wildlife clearings using pan traps". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d6a5709f-1de0-4963-b9f9-a882026a968c">https://bionomia.net/dataset/d6a5709f-1de0-4963-b9f9-a882026a968c</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d6a5709f-1de0-4963-b9f9-a882026a968c">https://gbif.org/dataset/d6a5709f-1de0-4963-b9f9-a882026a968c</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Taxonomic revision of Habenaria josephi group (sect. Diphyllae s. l.) in the Pan-Himalaya.
Natural history specimen data linked to collectors and determiners held within, "Taxonomic revision of Habenaria josephi group (sect. Diphyllae s. l.) in the Pan-Himalaya". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/b9ad0c81-e330-4212-835b-8659a2b55aad">https://bionomia.net/dataset/b9ad0c81-e330-4212-835b-8659a2b55aad</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/b9ad0c81-e330-4212-835b-8659a2b55aad">https://gbif.org/dataset/b9ad0c81-e330-4212-835b-8659a2b55aad</a>. Formatted as a Frictionless Data package.
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.