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1,085 results for “Documentation”
Data from: Documenting the progressions of secondary eyewall formations
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Data from: Characterizing population structure and documenting rapid loss of genetic diversity in Chiricahua Leopard Frogs (Lithobates chiricahuensis) with high throughput microsatellite genotyping
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Airborne eDNA documents a diverse and ecologically complex tropical bat and other mammal community
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Data from: Open notes sounds great, but will a provider’s documentation change?
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Santa Barbara Coastal site, station Southern region of kelp harvest as documented by SBC, study of plant biomass in units of gramsPerSquareMeter on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Santa Barbara Coastal (SBC) contains plant biomass measurements in gramsPerSquareMeter units and were aggregated to a yearly timescale.
FIGURE 4. Pegomya disticha Griffiths, adults. A. Male. B. Female. C. Male head, frontal view. D in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 4. Pegomya disticha Griffiths, adults. A. Male. B. Female. C. Male head, frontal view. D. Female head, latero-dorsal view.
FIGURE 3. Pegomya cedrica Huckett. A. Isolated live 3 in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 3. Pegomya cedrica Huckett. A. Isolated live 3rd instar larva with dark gut contents showing through. B. Isolated live puparium. C. Stem with external signs of larval attack. D. Opened stem showing larval tunnel through two successive internodes and larva at base. E. Transect showing larval mine inside the wall. F, G. Basal remains of attacked shoot by early spring exposing a hibernating puparium. Scales in millimetres.
FIGURE 1. Pegomya disticha Griffiths. A in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 1. Pegomya disticha Griffiths. A. Study site with patch of Common scouring-rush, Equisetum hyemale L.. B. Eclosed egg inside nodal sheath. C.1st instar larva at base of internodal chamber. D. 2nd instar larvae at base of two successive internodes. E. 3rd instar larva at base of internode with feeding canal through parenchymal "gall tissue". F. Isolated live 3rd instar larva.
FIGURE 8. Distal ovipositor, flat mounted. A. Pegomya disticha Griffiths. B. P in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 8. Distal ovipositor, flat mounted. A. Pegomya disticha Griffiths. B. P. cedrica Huckett. Abbreviations: Ce = cerci, Hy = hypoproct, Tg = tergite, Stg = sternite. Same scale.
FIGURE 2. Pegomya disticha Griffiths. A in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 2. Pegomya disticha Griffiths. A. Intact stem with escape window (arrow). B. Opened stem showing chamber with puparium at base and larval frass. C. Transects of occupied and healthy internode. D. Two stems with the exit windows sliced open by presumed avian predator. Scale bar in millimetres.
FIGURE 6. Pegomya disticha Griffiths, male terminalia. A. Tergo-sternite VI‒VIII. B. Sternite V. C. Hypopygium, caudal view. D. Same, left lateral view. E in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 6. Pegomya disticha Griffiths, male terminalia. A. Tergo-sternite VI‒VIII. B. Sternite V. C. Hypopygium, caudal view. D. Same, left lateral view. E. Pregonite and postgonite, left lateral view. F. Phallus and ejaculatory pump, left lateral view. Abbreviation: Tg = tergite. Same scale.
FIGURE 9. Cephaloskeleton, 3 in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 9. Cephaloskeleton, 3rd instar larva. A. Pegomya disticha Griffiths, left lateral view. B. Same, dorsal view. C. P. cedrica Huckett, left lateral view. D. Same, dorsal view. Same scale.
FIGURE 10. Spiracles, 3 in Pegomya disticha Griffiths and P. cedrica Huckett (Diptera: Anthomyiidae) - first documented case of insects trespassing the silica barrier of Common scouringrush, Equisetum hyemale L.
FIGURE 10. Spiracles, 3rd instar larva. A. Pegomya disticha Griffiths, anterior spiracle. B. P. cedrica Huckett, anterior spiracle. C. P. disticha Griffiths, posterior spiracles. D. P. cedrica Huckett, posterior spiracles. Same scale.
FIGURE 3 in A protocol for online documentation of spider biodiversity inventories applied to a Mexican tropical wet forest (Araneae, Araneomorphae)
FIGURE 3. Example of a species page documented with standard views Cyrtognatha petila Dimitrov & Hormiga 2009. http:// www.unamfcaracnolab.com/WPGS_TUXV/tuxv.html
FIGURE 4 in A protocol for online documentation of spider biodiversity inventories applied to a Mexican tropical wet forest (Araneae, Araneomorphae)
FIGURE 4. Species richness estimations. Red triangles with values indicated with (*) correspond to the species estimations for those treatments fitted to a lognormal distribution. White and red triangles over the x axis indicate higher overestimations.
FIGURE 5. Species richness estimations slopes. Jack 2s in A protocol for online documentation of spider biodiversity inventories applied to a Mexican tropical wet forest (Araneae, Araneomorphae)
FIGURE 5. Species richness estimations slopes. Jack 2s indicates the slope average for these estimations based on incidence (BAT) and abundance (Bat and Estimates). Same averages were calculated for Jack 1s and Chao 1 and 2 estimation slopes. Column indicated with (*) correspond to the slope value for pitfalls under Chao's estimations.
Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles (Dataset, Models & Code)
<p>Many digital libraries recommend literature to their users considering the similarity between a query document and their repository. However, they often fail to distinguish what is the relationship that makes two documents alike. In this paper, we model the problem of finding the relationship between two documents as a pairwise document classification task. To find the semantic relation between documents, we apply a series of techniques, such as GloVe, Paragraph-Vectors, BERT, and XLNet under different configurations (e.g., sequence length, vector concatenation scheme), including a Siamese architecture for the Transformer-based systems. We perform our experiments on a newly proposed dataset of 32,168 Wikipedia article pairs and Wikidata properties that define the semantic document relations. Our results show vanilla BERT as the best performing system with an F1-score of 0.93,<br> which we manually examine to better understand its applicability to other domains. Our findings suggest that classifying semantic relations between documents is a solvable task and motivates the development of recommender systems based on the evaluated techniques. The discussions in this paper serve as first steps in the exploration of documents through SPARQL-like queries such that one could find documents that are similar in one aspect but dissimilar in another.</p> <p>Additional information can be found on <a href="https://github.com/malteos/semantic-document-relations/">GitHub</a>.</p> <p>The following data is supplemental to the experiments described in our research paper. The data consists of:</p> <ul> <li>Datasets (articles, class labels, cross-validation splits)</li> <li>Pretrained models (Transformers, GloVe, Doc2vec)</li> <li>Model output (prediction) for the best performing models</li> </ul> <p><strong>Dataset</strong></p> <p>The Wikipedia article corpus is available in <code>enwiki-20191101-pages-articles.weighted.10k.jsonl.bz2</code>. The original data have been downloaded as <a href="https://dumps.wikimedia.org/enwiki/">XML dump</a>, and the corresponding articles were extracted as plain-text with <a href="https://radimrehurek.com/gensim/scripts/segment_wiki.html">gensim.scripts.segment_wiki</a>. The archive contains only articles that are available in training or test data.</p> <p>The actual dataset is provided as used in the stratified k-fold with <code>k=4</code> in <code>train_testdata__4folds.tar.gz</code>.</p> <pre><code>├── 1 │ ├── test.csv │ └── train.csv ├── 2 │ ├── test.csv │ └── train.csv ├── 3 │ ├── test.csv │ └── train.csv └── 4 ├── test.csv └── train.csv 4 directories, 8 files </code></pre> <p>Pretrained models</p> <p>PyTorch: vanilla and Siamese BERT + XLNet</p> <p>Pretrained model for each fold is available in the corresponding model archives:</p> <pre><code># Vanilla model_wiki.bert_base__joint__seq512.tar.gz model_wiki.xlnet_base__joint__seq512.tar.gz # Siamese model_wiki.bert_base__siamese__seq512__4d.tar.gz model_wiki.xlnet_base__siamese__seq512__4d.tar.gz </code></pre>
Collection of International Treaties and Legal Documents (CITLD)
<p> </p> <p><strong>Overview</strong></p> <p>The <strong>Collection of International Treaties and Legal Documents (CITLD)</strong> combines around 200 key international treaties and legal documents and is designed to be an accessible set of basic equipment for the well-rounded international lawyer in the digital age. It covers the following subject areas:</p> <ul> <li>Traditional Core of International Law (treaty law, legal personality, diplomacy, peace and security)</li> <li>International Human Rights Law</li> <li>International Humanitarian Law</li> <li>International Criminal Law</li> <li>Disarmament</li> <li>Environmental Law</li> <li>Trade Law</li> <li>Labor Law</li> <li>Culture</li> <li>Law of the Sea</li> <li>Procedural Law</li> </ul> <p>Each legal instrument is contained in a separate PDF file and is richly annotated with filename metadata. This allows users to download the full data set and execute quick local searches for specific documents to assist with their international legal research needs. Every file contains key citation details on its first page. For treaties these generally are date of adoption, date of entry into force and volume/page in the UN Treaty Series (UNTS). PDF files are further organized in folders according to common subject areas.</p> <p> </p> <p><strong>Data Source</strong></p> <p>The source of the documents is the International Law Handbook of the United Nations (vols 1 through 4), which can be downloaded for free here: <a href="https://legal.un.org/avl/handbook.html">https://legal.un.org/avl/handbook.html</a> It is also included in a zip archive below. As per the original dedication of the UN, the data set and the Handbook "<em>may be reproduced for academic purposes to further this goal [the teaching and dissemination of international law] anywhere in the world</em>". I waive any rights arising from the preparation or annotation with metadata under a CC0 Public Domain dedication.</p> <p> </p> <p><strong>Open Access Publications (Fobbe)</strong></p> <p>Website<em> </em>—<em> </em><a href="https://www.seanfobbe.com">www.seanfobbe.com</a></p> <p>Open Data — <a href="https://zenodo.org/communities/sean-fobbe-data/">zenodo.org/communities/sean-fobbe-data/</a></p> <p>Source Code — <a href="https://zenodo.org/communities/sean-fobbe-code/">zenodo.org/communities/sean-fobbe-code/</a></p> <p>Regular Publications — <a href="https://zenodo.org/communities/sean-fobbe-publications/">zenodo.org/communities/sean-fobbe-publications/</a></p> <p> </p>
FIG. 1 in A recent inventory of the bats of Mozambique with documentation of seven new species for the country
FIG. 1. Map of Mozambique showing the sites at which bats were captured during this study (2005–2009). The sampling sites are overlaid on a digital elevation model (altitude in metres). The boundaries of the three biogeographic zones (following Parker, 1999) are represented by the two black lines. The southern line follows the Save River, whereas the northern line follows the Zambezi
FIG. 3 in A recent inventory of the bats of Mozambique with documentation of seven new species for the country
FIG. 3. Ventral (A) and lateral (B) views of the baculum of R. cf. deckenii (DM 8560), from Chinizuia, central Mozambique. One small square on the graph paper represents 1 mm
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.