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6,335 results for “direct”
FIGURE 7 in A new species of direct-developing frog of the genus Pristimantis (Anura: Terrarana: Craugastoridae) from Cordillera del Cóndor, Ecuador, with comments on threats to the anuran fauna of the region
FIGURE 7. Distribution of Pristimantis yantzaza sp. nov. (triangles) in eastern Ecuador. The blue pentagon indicates the type locality.
Operational sex ratio predicts the opportunity and direction of sexual selection across animals
<p>The operational sex ratio (OSR) has long been assumed to be a key ecological factor determining the opportunity and direction of sexual selection. However, recent theoretical work has challenged this view, arguing that a biased OSR does not necessarily result in greater monopolisation of mates and therefore stronger sexual selection in the mate-limited sex. Hence, the role of the OSR for shaping animal mating systems remains a conundrum in sexual selection research. Here we took a meta-analytic approach to test whether OSR explains interspecific variation in sexual selec- tion metrics across a broad range of animal taxa. Our results demonstrate that the OSR predicts the opportunity for sexual selection in males and the direction of sexual selection in terms of sex differences in both the opportunity for sexual selection and the Bateman gradient (i.e. the selection differential of mating success), as predicted by classic theory.</p>
Data for "RegulaTome: a corpus of typed, directed, and signed relations between biomedical entities in the scientific literature"
<div> <p><strong>RegulaTome corpus</strong>: this <a href="../api/records/10808330/files/RegulaTome-corpus.tar.gz/content" target="_blank" rel="noopener">file</a> contains the RegulaTome corpus in <a href="https://brat.nlplab.org/">BRAT</a> format. The directory <strong>"splits" </strong>has the corpus split based on the train/dev/test used for the training of the relation extraction system</p> <p><strong>RegulaTome annodoc</strong>: The annotation guidelines along with the annotation configuration files for BRAT are provided in <a href="../api/records/10808330/files/annodoc+config.tar.gz/content" target="_blank" rel="noopener">annodoc+config.tar.gz</a>. The online version of the annotation documentation can be found here: <a href="https://katnastou.github.io/s1000-corpus-annotation-guidelines/">https://katnastou.github.io/regulatome-annodoc/ </a></p> <p>The tagger software can be found here: <a href="https://github.com/larsjuhljensen/tagger">https://github.com/larsjuhljensen/tagger</a>. The command used to run tagger before large-scale execution of the RE system is:</p> <p><code>gzip -cd `ls -1 pmc/*.en.merged.filtered.tsv.gz` `ls -1r pubmed/*.tsv.gz` | cat dictionary/excluded_documents.txt - | tagger/tagcorpus --threads=16 --autodetect --types=dictionary/curated_types.tsv --entities=dictionary/all_entities.tsv --names=dictionary/all_names_textmining.tsv --groups=dictionary/all_groups.tsv --stopwords=dictionary/all_global.tsv --local-stopwords=dictionary/all_local.tsv --type-pairs=dictionary/all_type_pairs.tsv --out-matches=all_matches.tsv</code></p> <p><strong>Input documents </strong>for large-scale execution, which is done on entire <a href="https://a3s.fi/March-2024-PubMed/PubMed_20230314.tar.gz" target="_blank" rel="noopener">PubMed</a> (as of March 2024) and <a href="https://a3s.fi/Jan-2024-documents/PMC_Nov_23.tar.gz" target="_blank" rel="noopener">PMC Open Access</a> (as of November 2023) articles in BioC format. The files are converted to a <a href="https://a3s.fi/March-2024-PubMed/all_documents.tsv" target="_blank" rel="noopener">tab-delimited format </a>to be compatible with the RE system input (see below).</p> <p><strong>Input dictionary files</strong>: all the files necessary to execute the command above are available in <a href="../api/records/10808330/files/tagger_dictionary_files.tar.gz/content" target="_blank" rel="noopener">tagger_dictionary_files.tar.gz </a></p> <p><strong>Tagger output</strong>: we filter the results of the tagger run down to gene/protein hits, and documents with more than 1 hit (since we are doing relation extraction) before feeding it to our RE system. The filtered output is available in <a href="../api/records/10808330/files/tagger_matches_ggp_only_gt_1_hit.tsv.gz/content" target="_blank" rel="noopener">tagger_matches_ggp_only_gt_1_hit.tsv.gz</a></p> <p><strong>Relation extraction system input</strong>: <a href="../api/records/10808330/files/combined_input_for_re.tar.gz/content" target="_blank" rel="noopener">combined_input_for_re.tar.gz</a>: these are the directories with all the .ann and .txt files used as input for the large-scale execution of the relation extraction pipeline. The files are generated from the tagger tsv output (see above, <a href="../api/records/10808330/files/tagger_matches_ggp_only_gt_1_hit.tsv.gz/content" target="_blank" rel="noopener">tagger_matches_ggp_only_gt_1_hit.tsv.gz</a>) using the <a href="https://github.com/spyysalo/string-db-tools/blob/main/tagger2standoff.py">tagger2standoff.py</a> script from the <a href="https://github.com/spyysalo/string-db-tools/">string-db-tools</a> repository.</p> <p><strong>Relation extraction models</strong>. The Transformer-based model used for large-scale relation extraction and prediction on the test set is at <a href="../api/records/10808330/files/relation_extraction_multi-label-best_model.tar.gz/content" target="_blank" rel="noopener">relation_extraction_multi-label-best_model.tar.gz</a></p> <p>The pre-trained RoBERTa model on PubMed and PMC and MIMIC-III with a BPE Vocab learned from PubMed (RoBERTa-large-PM-M3-Voc), which is used by our system is available <a href="https://github.com/facebookresearch/bio-lm/blob/main/README.md">here</a>.</p> <p><strong>Relation extraction system output</strong>: the tab-delimited outputs of the relation extraction system are found at <a href="https://a3s.fi/regulatome-ls/large_scale_relation_extraction_results.tar.gz" target="_blank" rel="noopener">large_scale_relation_extraction_results.tar.gz </a><strong>!!!ATTENTION this file is approximately 1TB in size, so make sure you have enough space to download it on your machine!!!</strong></p> <p>The relation extraction system output files have 86 columns: PMID, Entity BRAT ID1, Entity BRAT ID2, and scores per class produced by the relation extraction model. Each file has a header to denote which score is in which column.</p> </div>
Data from: Direct and indirect effects of cougar predation on bighorn sheep fitness
<div> <p>We sought to evaluate the direct and indirect fitness effects of intense cougar (<em>Puma concolor</em>) predation using 48 years of data on marked bighorn sheep (<em>Ovis canadensis</em>) in Ram Mountain, Alberta, Canada. We compared years of intense cougar predation with years with no or occasional cougar predation. We first quantified the effects of predation on neonatal, weaning, and overwinter lamb survival, three metrics potentially affected by direct and indirect effects. We then investigated the possible indirect effects of intense cougar predation on lamb production, female summer mass gain, and lamb mass at weaning. Indirect effects included a 14.2% decline in lamb production. Female summer mass gain decreased by 15.6 % and lamb mass at weaning declined by 8.0% in years of intense cougar predation. Here are the six datasets, joined with a README.md file for the data description, in addition to the six corresponding R scripts for replicating the results.</p> </div>
Demo data and model weights for "Direct Observation of Atmospheric Turbulence with a Video-rate Wide-field Wavefront Sensor"
<p>Demo data and model weights for "Direct Observation of Atmospheric Turbulence with a Video-rate Wide-field Wavefront Sensor". For usage, please refer to https://github.com/freemercury/Widefield_wavefront_sensor.</p>
A Novel Equivalent Transmission-Line Model for Efficient Analysis of Huygens Source Antennas Embedded inside Low-Loss Multilayer EBG Superstrates for Directivity Enhancement
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A translation-independent directed evolution strategy to engineer aminoacyl-tRNA synthetases_NGS data analysis
<p>These data files are associated with the NGS analysis done in the publication :"A translation-independent directed evolution strategy to engineer aminoacyl-tRNA synthetases". This compressed file contains the raw file as well as the processed files to arrive at the conclusions published. The python scripts used for processing the data are available on github (link provided in the manuscript).</p>
Distance Tuneable Integral Membrane Protein Containing Floating Bilayers via In Situ Directed Self-Assembly : Data and Analysis Scripts
<p>Neutron Reflectometry data and analysis scripts (for RasCal software) and Quartz Crystal Microbalance data and plotting script for data shown in Figures 1, 3, 4 and 5 of the Article: Distance Tuneable Integral Membrane Protein Containing Floating Bilayers via In Situ Directed Self-Assembly.</p>
A Directed Acyclic Graph of causal relations between diseases mined from the literature
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Replication package for: "The Short- and Long-Run Impacts of Free Education on Schooling: Direct Effects and Intra-household Spillovers"
<p>The replication package contains the following folders: (1) The "do" folder, which contains all ".do" and ".R" files used to reproduce all figures and tables in the paper and the appendix; (2) The "outputs" folder, which stores all figures and tables; and (3) The "add-ons" folder, which includes all necessary Stata or R add-on packages. Additionally, the replication package contains a README PDF file to illustrate the result replication procedure.</p>
Plant measurements and analytical results of direct and indirect iron deficiency of grapevine rootstocks
<p>Iron deficiency causes severe symptoms of leaf chlorosis with many crop species. In many cases the stess situation is induced by high lime stone content in soils. This study analyzed the response of grapevine rootstocks to no iron availability (-Fe) and a reduced iron availability (+Fe+BiC) with the aim to differentiate the response reaction. Plants were grown as woody cutting in pots filled with sand and fertilized with an half-strength Hoagland solution. Mesurements taken and data were obtained from samples collected at the end of the experiment after 4 weeks.</p>
Supplementary data for "Undergraduate Gender Diversity and the Direction of Scientific Research" (PART 1)
<p>All files in this depository contain Microsoft Academic Graph data (April 2018 Extract) used for "Undergraduate Gender Diversity and the Direction of Scientific Research" </p> <p>The attribution license of the Microsoft Academic Graph is <a href="https://opendatacommons.org/licenses/by/1-0/">ODC-BY</a></p> <p>Please cite the following paper in publications and reports using the Microsoft Academic Graph:</p> <p>Arnab Sinha, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, and Kuansan Wang. 2015. An Overview of Microsoft Academic Service (MA) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). ACM, New York, NY, USA, 243-246. DOI=http://dx.doi.org/10.1145/2740908.2742839</p> <p>All files are in the repository are original and are the full extract. However, PaperAbstractInvertedIndex.txt has been split into 9 parts because the original file is 137GB, which exceeds the upload limit of Zenodo. PaperAbstractInvertedIndex_3.txt to PaperAbstractInvertedIndex_9.txt are available in a separate repository (Supplementary data for "Undergraduate Gender Diversity and the Direction of Scientific Research" (PART 2) DOI=10.5281/zenodo.11388912). </p> <p>To replicate the results in "Undergraduate Gender Diversity and the Direction of Scientific Research", please decompress all files (except for the PaperAbstractInvertedIndex files) and place all files in "data/raw/MAG/". The associated code repository can be found AEA Data and Code Repository openicpsr-204361.</p> <p> </p> <ul> <li>Affiliations.txt <ul> <li>Description Type</li> <li>Affiliation ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Paper count</li> <li>Citation count </li> </ul> </li> <li>Authors.txt <ul> <li>Author ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Last known affiliation ID</li> <li>Paper count</li> <li>Citation count</li> </ul> </li> <li>FieldsOfStudy.txt <ul> <li>Field of study ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Level</li> <li>Paper count</li> <li>Citation count</li> </ul> </li> <li>FieldsOfStudyChildren.txt <ul> <li>Field of study ID</li> <li>Child field of study ID </li> </ul> </li> <li>Journals.txt <ul> <li>Journal ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Paper count</li> <li>Citation count </li> </ul> </li> <li>Papers.txt <ul> <li>Paper ID</li> <li>Rank</li> <li>Doi</li> <li>Doc type</li> <li>Paper title</li> <li>Original title</li> <li>Book title</li> <li>Year</li> <li>Date</li> <li>Publisher</li> <li>Journal ID </li> <li>Conference Series ID</li> <li>Conference instance ID</li> <li>Volume</li> <li>Issue</li> <li>First page</li> <li>Last page </li> <li>Reference count</li> <li>Citation count</li> <li>Estimated citation </li> </ul> </li> <li>PaperAbstractInvertedIndex.txt <ul> <li>Paper ID</li> <li>Abstract</li> </ul> </li> <li>PaperAuthorAffiliations.txt <ul> <li>Paper ID</li> <li>Author ID</li> <li>Affiliation ID</li> <li>Author sequence number </li> </ul> </li> <li>PaperFieldsOfStudy.txt <ul> <li>Paper ID</li> <li>Field of study ID</li> <li>Similarity</li> </ul> </li> <li>PaperReferences.txt <ul> <li>Paper ID</li> <li>Paper reference ID <br><br></li> </ul> </li> </ul>
Supplementary data for "Undergraduate Gender Diversity and the Direction of Scientific Research" (PART 2)
<p>All files except for "MTI.zip" in this depository are Microsoft Academic Graph data (April 2018 Extract) used for "Undergraduate Gender Diversity and the Direction of Scientific Research" </p> <p>The attribution license of the Microsoft Academic Graph is <a href="https://opendatacommons.org/licenses/by/1-0/">ODC-BY</a></p> <p>Please cite the following paper in publications and reports using the Microsoft Academic Graph:</p> <p>Arnab Sinha, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June (Paul) Hsu, and Kuansan Wang. 2015. An Overview of Microsoft Academic Service (MA) and Applications. In Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). ACM, New York, NY, USA, 243-246. DOI=http://dx.doi.org/10.1145/2740908.2742839</p> <p>PaperAbstractInvertedIndex.txt has been split into 9 parts because the original file is 137GB, which exceeds the upload limit of Zenodo. PaperAbstractInvertedIndex_3.txt to PaperAbstractInvertedIndex_9.txt are available in this repository. See Supplementary data for "Undergraduate Gender Diversity and the Direction of Scientific Research" (PART 1) DOI=10.5281/zenodo.11388912 for remaining data.</p> <p>MTI.zip contains output from Medical Text Indexer. Specifically, the National Library of Medicine offers an online tool, Medical Text Indexer (MTI) (https://lhncbc.nlm.nih.gov/ii/tools/MTI.html), to provide indexing recommendations based on the Medical Subject Headings (MeSH) vocabulary. Specifically, we uploaded to the first 2500 characters of the title and abstract of all papers in our sample in batch mode (Accessed in October 2021). A copy of the output of the MTI is provided as part of this archive "papers_coed_for_MTI_1_output.txt.zip", "papers_coed_for_MTI_2_output.txt.zip", "papers_coed_for_MTI_3_output.txt.zip"</p> <p>To replicate the results in "Undergraduate Gender Diversity and the Direction of Scientific Research", do <strong>not</strong> decompress the PaperAbstractInvertedIndex files and MTI files. Place the PaperAbstractInvertedIndex files in the "data/raw/MAG" directory and place the MTI files in the "data/raw/MTI" directory. The associated code repository can be found at AEA Data and Code Repository (openicpsr-204361).</p> <p> </p> <ul> <li>Affiliations.txt <ul> <li>Description Type</li> <li>Affiliation ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Paper count</li> <li>Citation count </li> </ul> </li> <li>Authors.txt <ul> <li>Author ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Last known affiliation ID</li> <li>Paper count</li> <li>Citation count</li> </ul> </li> <li>FieldsOfStudy.txt <ul> <li>Field of study ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Level</li> <li>Paper count</li> <li>Citation count</li> </ul> </li> <li>FieldsOfStudyChildren.txt <ul> <li>Field of study ID</li> <li>Child field of study ID </li> </ul> </li> <li>Journals.txt <ul> <li>Journal ID</li> <li>Rank</li> <li>Normalized name</li> <li>Display name</li> <li>Paper count</li> <li>Citation count </li> </ul> </li> <li>Papers.txt <ul> <li>Paper ID</li> <li>Rank</li> <li>Doi</li> <li>Doc type</li> <li>Paper title</li> <li>Original title</li> <li>Book title</li> <li>Year</li> <li>Date</li> <li>Publisher</li> <li>Journal ID </li> <li>Conference Series ID</li> <li>Conference instance ID</li> <li>Volume</li> <li>Issue</li> <li>First page</li> <li>Last page </li> <li>Reference count</li> <li>Citation count</li> <li>Estimated citation </li> </ul> </li> <li>PaperAbstractInvertedIndex.txt <ul> <li>Paper ID</li> <li>Abstract</li> </ul> </li> <li>PaperAuthorAffiliations.txt <ul> <li>Paper ID</li> <li>Author ID</li> <li>Affiliation ID</li> <li>Author sequence number </li> </ul> </li> <li>PaperFieldsOfStudy.txt <ul> <li>Paper ID</li> <li>Field of study ID</li> <li>Similarity</li> </ul> </li> <li>PaperReferences.txt <ul> <li>Paper ID</li> <li>Paper reference ID <br><br></li> </ul> </li> </ul>
Excessive Firing of Dyskinesia-Associated Striatal Direct Pathway Neurons is Gated By Dopamine and Excitatory Synaptic Input
<p>This folder contains data associated with a submitted manuscript: Ryan, Girasole et al, which was first posted on BioRxiv in 2022. https://www.biorxiv.org/content/10.1101/2022.10.31.514594v1.</p> <p><strong>Files associated with each figure: </strong></p> <p><strong>Figure 1 & Supp Figure 1: </strong></p> <ul> <li>Summary.mat</li> <li>Behavior.mat</li> <li>Data.mat</li> <li>TRAP_InVivo_Analysis.m</li> <li>TRAP_Remove_INs.m</li> </ul> <p><strong>Figure 2 & Supp Figure 2: </strong></p> <ul> <li>See BioStudies for rabies dataset: <a href="https://www.ebi.ac.uk/biostudies/studies/S-BSST1374?key=9a1b2103-25a6-49ed-b257-0269d3ea19a6" target="_blank" rel="noopener">https://www.ebi.ac.uk/biostudies/studies/S-BSST1374?key=9a1b2103-25a6-49ed-b257-0269d3ea19a6</a></li> </ul> <p><strong>Figure 3 & Supp Figure 3 & Supp Figure 4: </strong></p> <ul> <li> <p>Fig3_FigS3_FigS4_Data.xlsx</p> </li> </ul> <p><strong>Figure 4 & Supp Figure 5: </strong></p> <ul> <li>Fig4Data.xlsx</li> <li>RNAscopeAnalysis_D1_D2.m</li> <li>RNAdata.mat</li> <li>RNAscopeAnalysis_D1_pDyn.m</li> <li>RNAScopeAnalysis.m</li> <li>pDynRNAdata.mat</li> <li>pDynSummary.mat</li> </ul> <p><strong>Contributions</strong>: </p> <p>Behavioral data was collected and analyzed by Ally Girasole, Michael Ryan, and Emily Twedell.</p> <p>In vivo electrophysiological data was collected and analyzed by Michael Ryan and Ally Girasole.</p> <p>Ex vivo electrophysiological data was collected and analyzed by Ally Girasole, Michael Ryan, Emily Twedell, and Alexandra Nelson.</p> <p>Anatomical tracing and histology data was collected and analyzed by Ron Paletzki, Chip Gerfen, Michael Ryan, Ally Girasole and Rea Brakaj.</p> <p>RNA Scope data was collected and analyzed by Andrew Flores, Mike Ryan, and Tom Hnasko.</p>
Supplementary file 3; Photographs illustrating different ways in which signs of livestock, humans or wild mammals were detected and recorded as either direct sighting, tracks, spoor or other signs:
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Supplementary File 8; Dot plots summarising the total frequencies of direct observations, tracks, spoor, and other signs of all wild animals detected in radial and transect surveys over the course of the study:
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Szpilko, Budna Sustainable and smart mobility – research directions_UMO-202245BHS401414
<p><span>The data includes a list of publications from the Web of Science and SCOPUS databases considered in the bibliometric analysis. The database contains a total of 8,821 records - bibliographic descriptions of publications. The basic metadata of the publications used in the bibliometric analysis include: the title of the publication, abstract, and keywords</span></p>
Complete dataset for the publication "Phage Paride can kill dormant, antibiotic-tolerant cells of Pseudomonas aeruginosa by direct lytic replication"
<p>This dataset enlists all individual datapoints shown in the publication "Phage Paride can kill dormant, antibiotic-tolerant cells of Pseudomonas aeruginosa by direct lytic replication" (https://doi.org/10.1038/s41467-023-44157-3). For detailed information regarding the individual contributions please check the "Author information" section in the publication. </p>
FIGURE 1 in A new species of direct-developing frog of the genus Eleutherodactylus (Anura: Eleutherodactylidae) from Tamaulipas, Mexico
FIGURE 1. Distribution of some members of the Eleutherodactylus longipes species clade in eastern Mexico. State names are indicated.
FIGURE 4. A in A new species of direct-developing frog of the genus Eleutherodactylus (Anura: Eleutherodactylidae) from Tamaulipas, Mexico
FIGURE 4. A) Photo in life of an individual of Eleutherodactylus coelum sp. nov. from El Cielo Biosphere Reserve, Tamaulipas, Mexico. B) Head in lateral view of the holotype of E. coelum sp. nov. (IBH 36351) in preservative; C) hand in ventral view; D) foot in ventral view. Scale bar is 1 mm. Photos: M. Delia Basanta (4A) and Susana Guzmán Gómez (4B–D).
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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.