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3,505 results for “completive”
Completing gene trees without species trees in sub-quadratic time
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Submitted Completed pointings to the Gravitational Wave Treasure Map for event S191205ah
<p>Attached in a .json file is the completed pointing information for 12 observation(s) for the EM counterpart search associated with the gravitational wave event S191205ah.</p>
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S191216ap
Attached in a .json file is the completed pointing information for 30 observation(s) for the EM counterpart search associated with the gravitational wave event S191216ap. These observations were taken on the Sinistro, and Spectral instruments.
Raw Nanopore data for "Nanopore Long-Read Guided Complete Genome Assembly of Hydrogenophaga intermedia, and Genomic Insights into 4-Aminobenzenesulfonate, p-Aminobenzoic Acid and Hydrogen Metabolism in the Genus Hydrogenophaga"
<p>This is the raw Nanopore dataset (fast5) for Hydrogenophaga intermedia PBC. The gDNA was prepared using the now obsolete SQK-NSK007 kit and sequenced on a MINION R9 Flowcell. </p>
Appendix II in The Earwig Collection (Dermaptera) of the Manchester Museum, UK, with a complete type catalogue
Appendix II, continued
Appendix II in The Earwig Collection (Dermaptera) of the Manchester Museum, UK, with a complete type catalogue
Appendix II: Correspondence in the Brindle Archive relating to Dermaptera, the Manchester Museum
Fig. 2. A in The Earwig Collection (Dermaptera) of the Manchester Museum, UK, with a complete type catalogue
Fig. 2. A graph showing % of World Dermaptera represented at the Manchester Museum, by family.
Appendix I in The Earwig Collection (Dermaptera) of the Manchester Museum, UK, with a complete type catalogue
Appendix I, continued
Fig. 3. A in The Earwig Collection (Dermaptera) of the Manchester Museum, UK, with a complete type catalogue
Fig. 3. A drawer of the British Dermaptera collection, the Manchester Museum.
Appendix I in The Earwig Collection (Dermaptera) of the Manchester Museum, UK, with a complete type catalogue
Appendix I: Correspondence in the Hincks Archive relating to Dermaptera, the Manchester Museum
Submitted Completed pointings to the Gravitational Wave Treasure Map for event TEST_EVENT
Attached in a .json file is the completed pointing information for 2 observation(s) for the EM counterpart search associated with the gravitational wave event TEST_EVENT. These observations were taken on the DLT40 instrument.
Submitted Completed pointings to the Gravitational Wave Treasure Map for event TEST_EVENT
Attached in a .json file is the completed pointing information for 2 observation(s) for the EM counterpart search associated with the gravitational wave event TEST_EVENT. These observations were taken on the DECam instrument.
Submitted Completed pointings to the Gravitational Wave Treasure Map for event S190814bv
Attached in a .json file is the completed pointing information for 2293 observation(s) for the EM counterpart search associated with the gravitational wave event S190814bv. These observations were taken on the DECam instrument.
Dataset for "Learning to Read and Follow Music in Complete Score Sheet Images"
<p>This is the data used in the paper:<br> Florian Henkel , Rainer Kelz, Gerhard Widmer. "Learning to Read and Follow Music in Complete Score Sheet Images". Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020</p> <p>The dataset is based on the <a href="https://zenodo.org/record/2597505#.XxbJtxGxVhE">MSMD - Multimodal Sheet Music Dataset</a> and processed for the purpose of score following in complete score sheet images.</p> <pre>Please find further information and the corresponding code on this Github page: <a href="https://github.com/CPJKU/audio_conditioned_unet">https://github.com/CPJKU/audio_conditioned_unet</a> </pre>
LAR phylogeny for Güngör et al. 2020: The complete analysis and dataset
<p>Fixing this repository as version 1.00.00 while the corresponding revised manuscript was submitted to new phytologist.</p>
YaCoS: a Complete Infrastructure to the Design and Exploration of Code Optimization Sequences
<p>The growing popularity of machine learning frameworks and algorithms has greatly contributed to the design and exploration of good code optimization sequences. Yet, in spite of this progress, mainstream compilers still provide users with only a handful of fixed optimization sequences. Finding optimization sequences that are good in general is challenging because the universe of possible sequences is potentially infinite. This paper describes a infrastructure that provides developers with the means to explore this space. Said infrastructure, henceforth called YaCoS, consists of benchmarks,search algorithms, metrics to estimate the distance between programs, and compilation strategies. YaCoS’s features let users build learning models that predict, for unknown pro-grams, optimization sequences that are likely to yield good results for them. In this paper, as a case study, we have used YaCoS to find good optimization sequences for LLVM, using code size as the objective function. Such study lets us evaluate three feature sets: two variations of the feature vectors proposed by Namolaru at al in 2010, plus the optimization statistics produced by LLVM. Our results show that YaCoSis able to find sequences that improve onto clang -Oz by3.75% on average. Our experiments do not indicate a dominant feature set out of the three approaches that we have investigated—it is possible to find programs in which one of them is strictly better than the others.</p>
Supplementary materials for article focused on traffic information enrichment: Animation and complete overview of all road segments on which basis summary test results were calculated
<p><strong>Supplementary materials </strong>(Appendix A and B) for the article:</p> <p>Traffic Information Enrichment: Creating Long-Term Traffic Speed Prediction Ensemble Model for Better Navigation through Waypoints</p> <p><em>Abstract: </em>Traffic speed prediction for a selected road segment from a short-term and long-term perspective is among the fundamental issues of intelligent transportation systems (ITS). During the course of the past two decades, many artefacts (e.g., models) have been designed dealing with traffic speed prediction. However, no satisfactory solution has been found for the issue of a long-term prediction for days and weeks using the vast spatial and temporal data. This article aims to introduce a long-term traffic speed prediction ensemble model using country-scale historic traffic data from 37,002 km of roads, which constitutes 66% of all roads in the Czech Republic. The designed model comprises three submodels and combines parametric and nonparametric approaches in order to acquire a good-quality prediction that can enrich available real-time traffic information. Furthermore, the model is set into a conceptual design which expects its usage for the improvement of navigation through waypoints (e.g., delivery service, goods distribution, police patrol) and the estimated arrival time. The model validation is carried out using the same network of roads, and the model predicts traffic speed in the period of 1 week. According to the performed validation of average speed prediction at a given hour, it can be stated that the designed model achieves good results, with mean absolute error of 4.67 km/h. The achieved results indicate that the designed solution can effectively predict the long-term speed information using large-scale spatial and temporal data, and that this solution is suitable for use in ITS.</p> <p>Simunek, M., & Smutny, Z. (2021). Traffic Information Enrichment: Creating Long-Term Traffic Speed Prediction Ensemble Model for Better Navigation through Waypoints. <em>Applied Sciences</em>, 11(1), 315. <a href="https://doi.org/10.3390/app11010315">https://doi.org/10.3390/app11010315</a></p> <p> </p> <p><strong>Appendix A</strong><br> Examples of the deviation between the average speed and the FreeFlowSpeed for selected hours.</p> <p> </p> <p><strong>Appendix B</strong><br> The text file provides a complete overview of all road segments on which basis summary test results were calculated in Section 6 of the article.</p>
The complete genome sequence and comparative genomic analyses of four phages (NJ-P3, NB-P21, NC-P34 and NN-P42)
<p>We downloaded and reanalyzed the raw data of four phages genomes (NJ-P3, NB-P21, NC-P34, NN-P42). This is the reassembled whole genomes and comparative genomic analyses of four phages.</p>
The complete mitochondrial genome of dwarf form of Sthenoteuthis oualaniensis (Cephalopoda: Ommastrephidae) from the South China Sea
<p>The purpleback flying squid (<em>Sthenoteuthis oualaniensis</em>) is a pelagic squid with tremendous potential for commercial exploitation. <em>Sthenoteuthis oualaniensis</em> comprises two forms in the South China Sea, dwarf form and medium-sized form. In this study, we described the complete mitochondrial genome of dwarf form of <em>Sthenoteuthis oualaniensis.</em> The genome is 20320 bp in length, encoding the standard set of 13 protein-coding genes, 20 tRNA genes and 2 rRNA genes, with circular organization. The overall base composition of the whole mitochondrial genome was A (37.23%), T (32.78%), G (10.53%) and C (19.46%) with an AT bias of 70.01%. The longest protein-coding genes of these species was <em>ND5</em>, whereas the shortest <em>ATP8</em>.</p>
Multilingual Knowledge Graph Completion With Joint Relation and Entity Alignment
<p>Code and data accompanying AlignKGC.</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.