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FIGURE 2 in Correspondence of larval and postlarval instars in two species of the subgenus Zaracarus (Acari: Erythraeidae: Erythraeus) established with laboratory rearing
FIGURE 2. Erythraeus (Zaracarus) budapestensis Fain and Ripka, 1998, female: a—leg setae, deutonymph: b—palp, medial aspect, c—crista metopica, d—genital opening, e—anal opening.
FIGURE 1 in Correspondence of larval and postlarval instars in two species of the subgenus Zaracarus (Acari: Erythraeidae: Erythraeus) established with laboratory rearing
FIGURE 1. Erythraeus (Zaracarus) budapestensis Fain and Ripka, 1998, female: a—palp, medial aspect, b—non-sensillary seta (AM = AL), c—crista metopica, d—dorsal opisthosomal setae, e—ventral seta, f—genital opening, g—anal opening.
FIGURE 4 in Correspondence of larval and postlarval instars in two species of the subgenus Zaracarus (Acari: Erythraeidae: Erythraeus) established with laboratory rearing
FIGURE 4. Erythraeus (Zaracarus) budapestensis Fain and Ripka, 1998, larva: a—gnathosoma, ventral view, b—idiosoma, dorsal view, c—idiosoma, ventral view. Abbreviations: as—adoral seta, bs—hypostomal seta, cs—oral spine like seta, elcp—supracoxala, elcI—supracoxal seta on coxae I, ω—solenidion, ζ—eupathidium.
FIGURE 7 in Correspondence of larval and postlarval instars in two species of the subgenus Zaracarus (Acari: Erythraeidae: Erythraeus) established with laboratory rearing
FIGURE 7. Attachment sites of larval Erythraeus (Zaracarus) budapestensis Fain and Ripka, 1998, at Uroleucon spp. a—attached to the head and thorax, b—attached to the abdomen, c—attached to the antenna, d—attached to the leg. Not to scale.
FIGURE 12 in Correspondence of larval and postlarval instars in two species of the subgenus Zaracarus (Acari: Erythraeidae: Erythraeus) established with laboratory rearing
FIGURE 12. Erythraeus (Zaracarus) rupestris (Linnaeus, 1758), larva: a—dorsal view of idiosoma with details of posterior dorsal seta and anterior sensillum, b—ventral view of idiosoma with detail of seta ps.
LiDAR and thermal data for camera pose estimation using the depth-map correspondence algorithm
<p>Folder and file structure:</p> <ul> <li>lidar_roi.ply : ~360 MB mesh file which is a sub-part of the whole Orlova Chuka scan collected in [1]</li> <li>yyyy-mm-dd total of ~17 GB. All video data including raw data, exported video, digitised xy points and calibration results <ul> <li>2018-08-19</li> <li>2018-08-17</li> <li>2018-08-14</li> <li>2018-07-28</li> <li>2018-07-25</li> <li>2018-07-21</li> </ul> </li> </ul> <p><em>Thermal camera YYYY-MM-DD folder substructure</em>: Each of the yyyy-mm-dd dates is one recording session. Each session folder has the following structure:</p> <ul> <li>avi_files (present on some nights)</li> <li>cave_photos: (present on some nights)</li> <li>mic_and_wall_points</li> <li>tmc_files: (present on some nights) The TMC files is a proprietary format to store thermal camera video data (TeAx GmbH, Germany). on 2018-08-17, only P0000000 is provided as it doesnt' have humans blocking the scene. Each frame can be exported to csv using the ThermoViewer tool, downloadable at: https://thermalcapture.com/thermoviewer-download/</li> <li>video_calibration: results and associated data to get DLT coefficients estimated using the easyWand [2] workflow. <ul> <li>image : csv file with pixel values of the images used for annotations</li> <li>mics : 2D point locations of mics placed on the cave walls</li> <li>other_cave_surface : other points on the cave surface that were pointed at <ul> <li>calibration_output: results from easyWand runs. Choose the highest round number <ul> <li>yyyy-mm-dd_roundX_<wandscore>_cam1Tforms.mat (undistortion files)</li> <li>yyyy-mm-dd_roundX_<wandscore>_cam2Tforms.mat</li> <li>yyyy-mm-dd_roundX_<wandscore>_cam3Tforms.mat</li> <li>yyyy-mm-dd_roundX_<wandscore>_dltCoefs.csv (each column is one camera's DLT coefficients)</li> <li>yyyy-mm-dd_roundX_<wandscore>_easyWandData.mat (easyWand session file)</li> </ul> </li> <li>gravity: (mostly there) video and xy points for a falling object to align the calbiration to gravity. Output from DLTdv7 clicking session.</li> <li>wand: video and xy points of the 'wand' calibration object. Output from DLTdv7 clicking session.</li> <li>camera_intrinsic.txt or thermalcam_camprofiles_profile.txt : the camera instrinsics</li> </ul> </li> </ul> </li> </ul> <ul> <li>alignment_results: ~887 MB zipped folder. <ul> <li>dmcp_experiments: the results of DMCP alignment <ul> <li>round_01 : <em>ignore this folder</em></li> <li>round_03 : <em>ignore this folder</em></li> <li>round_05: here yyyy-mm-dd is short for all other nights. Each yyyy-mm-dd folder has multiple csv files. The 'transform.csv' is the most relevant file, as it holds the transformation matrix to move 3D points from camera triangulations into the LiDAR coordinate system. <ul> <li>2018-07-21--cam0</li> <li>2018-07-21--cam1</li> <li>2018-07-21--cam2</li> <li>yyyy-mm-dd--cam0</li> <li>yyyy-mm-dd--cam1</li> <li>yyyy-mm-dd--cam2</li> <li>...</li> <li>...</li> <li>...</li> <li>2018-08-19--cam0</li> <li>2018-08-19--cam1</li> <li>2018-08-19--cam2</li> </ul> </li> </ul> </li> </ul> </li> </ul> <p> </p> <p>CITATION: If you use this dataset for your research please cite this Zenodo dataset and the accompanying paper.</p> <p>This uploaded dataset is part of the <em>Ushichka</em> dataset [3]. The audio-video system was designed by Holger R. Goerlitz. The LiDAR data was collected by Asparuh Kamburov. Video data collected by Thejasvi Beleyur.</p> <p>References</p> <p>[1] : Kamburov, A., Goerlitz, H. R., Beleyur, T 2018, Geospatial modelling inside the "Orlova Chuka" cave in Bulgaria, <em>non-peer reviewed conference contribution</em>, XXVIII International Symposium on Modern Technologies and Professional Practise in Geodesy and related fields</p> <p>[2]: Theriault, D. H., Fuller, N. W., Jackson, B. E., Bluhm, E., Evangelista, D., Wu, Z., M., Betke & Hedrick, T. L. (2014). A protocol and calibration method for accurate multi-camera field videography. <em>Journal of Experimental Biology</em>, <em>217</em>(11), 1843-1848.</p> <p>[3]: Beleyur Thejasvi, 2021. Theoretical and empirical investigations of echolocation in bat groups, PhD dissertation, University of Konstanz (<a href="http://nbn-resolving.de/urn:nbn:de:bsz:352-2-q41u3qlu1em03">http://nbn-resolving.de/urn:nbn:de:bsz:352-2-q41u3qlu1em03</a>)</p>
Software artifacts corresponding to the paper "Pragmatic Random Sampling of the Linux Kernel: Enhancing the Randomness and Correctness of the conf Tool"
<div><strong>Software artifacts corresponding to the paper "Pragmatic Random Sampling of the Linux Kernel: Enhancing the Randomness and Correctness of the conf Tool"</strong></div> <div> </div> <div> <div> <div>This repository is organized in two main folders:</div> <br> <div>1. <strong>randconfig+</strong> includes the source code of our tool randconfig+, which improves the randomness and correctness of the conf tool (a built-in Linux kernel tool for generating random samples of kernel configurations). It has two subfolders:</div> - <strong>source</strong>: includes the source code of randconfig+. <div> - <strong>bin</strong>: includes the compiled version of randconfig+.</div> <br> <div>2. <strong>experimental_validation</strong> includes the experimental validation of randconfig+ reported in the paper.</div> - <strong>systems</strong>: includes the 10 Linux Kernel versions analyzed in the paper. <div> - <strong>scripts_for_sample_generation</strong>: Bash shell scripts to generate the data.</div> <div> - <strong>data</strong>: includes the following data generated by the experimental validation:</div> <div> + Generated samples (subfolder configuration_samples). The samples are available in two formats: CSV and <a href="https://r4ds.hadley.nz/arrow">Apache Arrow</a>.</div> <div> + Entropies and number of distinct values per configuration option.</div> <div> + Data regarding the correctness of the samples and the time spent to generate them (subfolder correctness_and_runtime).</div> <div> - <strong>statistical_analysis</strong>: R scripts to perform the statistical analysis of the data (subfolder statistical_analysis).</div> <div> - <strong>plots</strong>: graphs produced from the data statistical analysis.</div> </div> </div>
Raman data and corresponding radiosonde from Beijing Institute of Technology
<p>Uploaded data includes: </p> <p>1. data of pure rotational Raman lidar system arranged in Beijing Institute of Technology from the day of Feb. 27 to Mar. 2, 2017,</p> <p>2. radiosonde data for the above dates,</p> <p>3. README files.</p> <p> </p>
Database of conference proceedings references corresponding to Eimeria species that infect ruminants
<p>Database of conference proceedings references corresponding to Eimeria species that infect ruminants</p>
Instances and corresponding solutions for the U-shaped storage layout planning problem (USLPP)
<p>The set of instances and corresponding solutions, which were used in the computational study of the paper “Ergonomic and economic optimization of layout and item assignment of a U-shaped order picking zone”.</p>
ਤ 3.ɹM831 ḺḢŪƤǝğĻȎாΓNjňɹḕḻẳɹKȋ෦]ƟǍō(DZŹՊŸതńffiॴଂ). Fig. 3.ɹDescription of the specimen in the catalog corresponding to M831. This catalogue is owned by NSMT. in DZŹՊŸതńffiॴଂνγd7ണṶğĻṒ =‡żϯϯḩì Canis lupus hodophilax Ḟȑ Is a Skin Specimen of bYamainu`in the Collection of the National Museum of Nature and Science, Tokyo, a Japanese wolf Canis lupus hodophilax?
ਤ 3.ɹM831 ḺḢŪƤǝğĻȎாΓNjňɹḕḻẳɹKȋ෦]ƟǍō(DZŹՊŸതńffiॴଂ). Fig. 3.ɹDescription of the specimen in the catalog corresponding to M831. This catalogue is owned by NSMT.
(1) Correspondence-Henry Heuland-Natural History Museum London- DF1/7 Mineralogy correspondence
<p>Source: Correspondence- Henry Heuland- Charles Konig- NHM-<span>DF1/7 Mineralogy correspondence</span></p>
Correspondence_exchanges_transactions_Forster_Heuland_Humphrey
<p>Database: correspondence of J. Forster, G. Humphrey, H. and C. Heuland (exchanges of natural specimens, commercial transactions, commercial networks).</p>
Correspondence-Transcription-Rashleigh-Forster-Heuland (Cornwall Archives)
<p>Source: Transcription of the letters exchanged between H. Heuland, E. Forster and P. Rashleigh (Cornwall Archives).</p>
Datasets used for chemical space visualization and the corresponding results.
<p>The datasets (.h5 format) used for dimensionality reduction (ChEMBL_datasets) and optimization results (DR_results) in the <a href="https://chemrxiv.org/engage/chemrxiv/article-details/66bb4da5f3f4b05290bccb6e">publication</a>.</p>
Data corresponding to paper: Improving 3D deep learning segmentation with biophysically motivated cell synthesis
<div> <h1>Improving 3D deep learning segmentation with biophysically motivated cell synthesis</h1> <a href="https://github.com/bruchr/cell_synthesis#improving-3d-deep-learning-segmentation-with-biophysically-motivated-cell-synthesis"></a></div> <h3><strong>Roman Bruch, Mario Vitacolonna, Elina Nürnberg, Simeon Sauer, Rüdiger Rudolf and Markus Reischl</strong></h3>
Table ¹: Previous and new records of G. venusta. The number (Nº) of the localities corresponds to those in Figure 2. in New and unusual records of Glironia venusta (Didelphimorphia, Didelphidae) in Brazil
<p><b>Table ¹:</b> Previous and new records of <i>G</i>. <i>venusta</i><i>.</i> The number (Nº) of the localities corresponds to those in Figure 2.</p><table><thead><tr><th colspan="2">Coordinates</th><th>No. Locality, country</th><th>Reference</th><th>Sex</th><th><b>Type of record</b></th></tr></thead><tbody><tr><th>05.5561</th><td>−53.9374</td><td>1 Saint Laurent du Maroni, French Guiana</td><td>Alexandre and Thoisy (2023)</td><td>U</td><td>Visual</td></tr><tr><th>3.0333</th><td>−53.1000</td><td>2 Monte Itoupé, French Guiana</td><td>Sant and Catzeflis (2018)</td><td>U</td><td>Visual</td></tr><tr><th>−0.0167</th><td>−75.5167</td><td>3 Quebrada El Hacha, Putumayo, Colombia</td><td>Rodríguez-Mahecha et al. (1995)</td><td>U</td><td>Visual</td></tr><tr><th>−0.6500</th><td>−75.2667</td><td>4 Boca de Lagarto Cocha, Ecuador</td><td>Anthony (1926)</td><td>º</td><td>Animal-trade</td></tr><tr><th>−2.0833</th><td>−77.4500</td><td>5 Cantón Pastaza, provincia de Pastaza, Ecuador</td><td>Arguero et al. (2017)</td><td>º</td><td>Animal-trade</td></tr><tr><th>−2.5667</th><td>−76.8000</td><td>6 Río Pastaza, Ecuador</td><td>Arguero et al. (2017)</td><td>º</td><td>Animal-trade</td></tr><tr><th>−2.0667</th><td>−76.9667</td><td>7 Rio Bobonazo, Montalvo, Ecuador</td><td>Marshall (1978)</td><td>º</td><td>Animal-trade</td></tr><tr><th>−3.7833</th><td>−78.4833</td><td>8 Cordillera del Cóndor Las Peñas de la Concesión, Ecuador</td><td>Arguero et al. (2017)</td><td>U</td><td>Visual</td></tr><tr><th>−3.8333</th><td>−78.5167</td><td>9 Cordillera del Cóndor Los Encuentros, Ecuador</td><td>Arguero et al. (2017)</td><td>º</td><td>Pitfall</td></tr><tr><th>−2.3667</th><td>−74.0833</td><td>10 Junction of Rio Curaray with Rio Napo, Loreto, Peru</td><td>Anthony (1926)</td><td>º</td><td>Animal-trade</td></tr><tr><th>−3.5000</th><td>−73.2333</td><td>11 Puerta Almendra, Loreto, Peru</td><td>Díaz and Willig (2004)</td><td>º</td><td>Tomahawk</td></tr><tr><th>−3.5833</th><td>−72.7500</td><td>12 Rio Amazonas and Rio Napo, Loreto, Peru</td><td>Barkley (2008)</td><td>º</td><td>Mistnet</td></tr><tr><th>−10.0667</th><td>−75.5333</td><td>13 Pozuzo, Pasco, Peru</td><td>Thomas (1912a)</td><td>³</td><td>Animal-trade</td></tr><tr><th>−11.8500</th><td>−71.3167</td><td>14 Cocha Cachu, Madre de Dios, Peru</td><td>Pacheco et al. (1993)</td><td>U</td><td>No information</td></tr><tr><th>−12.0695</th><td>−69.4937</td><td>15 Las Piedras Amazon Center, Peru</td><td>Rushford and Glynn (2023)</td><td>U</td><td>Visual</td></tr><tr><th>−14.6000</th><td>−68.5833</td><td>16 Rio Machariapo, La Paz, Bolivia</td><td>Emmons (1991)</td><td>U</td><td>Visual</td></tr><tr><th>−16.1667</th><td>−67.5000</td><td>17 Yungas, La Paz, Bolivia</td><td>Thomas (1912b)</td><td>³</td><td>Animal-trade</td></tr><tr><th>−16.4500</th><td>−62.6500</td><td>18 San Janvier, Santa Cruz, Bolivia</td><td>Anderson (1993)</td><td>U</td><td></td></tr><tr><th>−14.2500</th><td>−61.0167</td><td>19 Parque Nacional Noel Kempff Mercado, Santa Cruz, Bolivia</td><td>Emmons (1998)</td><td>U</td><td>Visual</td></tr><tr><th>−14.4167</th><td>−60.8333</td><td>20 Meseta de Huanchaca, Santa Cruz, Bolivia</td><td>Tarifa and Anderson (1997)</td><td>U</td><td>Visual</td></tr><tr><th>−7.9500</th><td>−72.0667</td><td>21 Reserva Extrativista Riozinho da Liberdade, Acre, Brazil</td><td>Bernarde and Machado (2008)</td><td>U</td><td>Visual</td></tr><tr><th>−7.43694</th><td>−73.6594</td><td>22 Parque Nacional da Serra do Divisor, Acre, Brazil</td><td>Almeida et al. (2022)</td><td>U</td><td>Visual</td></tr><tr><th>−4.8833</th><td>−65.2667</td><td>23 Alto Rio Urucu, Amazonas, Brazil</td><td>Nogueira et al. (1999)</td><td>U</td><td>Firearm</td></tr><tr><th>−2.9167</th><td>−59.9833</td><td>24 Reserva Florestal Adolpho Ducke, Amazonas, Brazil</td><td>Calzada et al. (2008)</td><td>U</td><td>Visual</td></tr><tr><th>−0.9333</th><td>−57.0333</td><td>25 Rio Mapuera, Cachoeira Porteira, Pará, Brazil</td><td>Silva and Langguth (1989)</td><td>³</td><td>Captured</td></tr><tr><th>−5.8000</th><td>−50.5000</td><td>26 Floresta Nacional Tapirapé-Aquiri, Pará, Brazil</td><td>Rossi et al. (2010)</td><td>U</td><td>Visual</td></tr><tr><th>−6.0500</th><td>−50.2500</td><td>27 Floresta Nacional de Carajás, Parauapebas, Pará, Brazil</td><td>Ardente et al. (2013)</td><td>³</td><td>Sherman</td></tr><tr><th>−6.0885</th><td>−49.9729</td><td>28 Floresta Nacional de Carajás,ParauapebaJLs, Pará, Brazil</td><td>Present study</td><td>U, ³</td><td>Roadkill</td></tr><tr><th>−6.3833</th><td>−55.9000</td><td>29 Vila São Chico, Moraes de Almeida, Itaituba, Pará, Brazil</td><td>Mercês et al. (2023)</td><td>º</td><td>Visual</td></tr><tr><th>−6.3000</th><td>−55.7833</td><td>30 Mina do Palito, Jardim do Ouro, taituba, Pará, Brazil</td><td>Mercês et al. (2023)</td><td>º</td><td>Visual</td></tr><tr><th>−9.4667</th><td>−56.7000</td><td>31 Jacareacanga, Rio Teles Pires River, Pará, Brazil</td><td>Silveira et al. (2014)</td><td>º</td><td>Visual</td></tr><tr><th>−9.5603</th><td>−56.7526</td><td>32 Paranaíta, Mato Grosso, Brazil</td><td>Silveira et al. (2014)</td><td>º</td><td>Visual</td></tr><tr><th>−13.1000</th><td>−54.8167</td><td>33 Nova Ubiratã, Mato Grosso, Brazil</td><td>Rossi et al. (2010)</td><td>³</td><td>Suppression-activity (specimen)</td></tr><tr><th>−15.1167</th><td>−58.9500</td><td>34 Usina Hidrelétrica Guaporé, Mato Grosso, Brazil</td><td>Rossi et al. (2010)</td><td>³</td><td>Suppression-activity (specimen)</td></tr><tr><th>−15.5667</th><td>−58.0000</td><td>35 Mirassol d’ Oeste, Mato Grosso, Brazil</td><td>Santos-Filho et al. (2007)</td><td>³</td><td>Tomahawk</td></tr><tr><th>−11.6000</th><td>−60.7167</td><td>36 Fazenda Jaburi, Rondônia, Brazil</td><td>Bernarde and Rocha (2003)</td><td>U</td><td>Pitfall</td></tr><tr><th>−8.8667</th><td>−64.0000</td><td>37 Rio Madeira, Porto Velho, Rondônia, Brazil</td><td>Santos-Filho et al. (2007)</td><td>º</td><td>Tomahawk</td></tr><tr><th>−9.4667</th><td>−64.8167</td><td>38 Caiçara, Porto Velho, Rondônia, Brazil</td><td>Present study</td><td>º</td><td>Mistnet</td></tr></tbody></table><p>U, unknown sex.</p>
intraspecific the to correspond. outgroups bold: grey in in Values; retzii. ) pb Microphis 605 ( : alignment red in; . I nov . subunit sp oxydase arrakisae c Microphis cytochrome: blue the in; on torrentius based) Microphis p-distances: green uncorrected in; (nicoleae matrix distance Microphis : Pairwise yellow In. . 2 divergence TABLE in A new freshwater pipefish species (Syngnathidae: Microphis) from the Sunda shelf islands, Indonesia
intraspecific the to correspond. outgroups bold: grey in in Values; retzii. ) pb Microphis 605 ( : alignment red in; . I nov . subunit sp oxydase arrakisae c Microphis cytochrome: blue the in; on torrentius based) Microphis p-distances: green uncorrected in; (nicoleae matrix distance Microphis : Pairwise yellow In. . 2 divergence TABLE
Figure 7 in Review of specimens corresponding to three species of Thyene (Araneae: Salticidae: Plexippini) in the Peckham Collection
Figure 7. Female Thyene ogdeni from the Peckham Collection showing the darker stripes with paired
Figure 6 in Review of specimens corresponding to three species of Thyene (Araneae: Salticidae: Plexippini) in the Peckham Collection
Figure 6. Second male "Thyene ogdeni" from the Peckham Collection (MCZ:IZ:151907). The
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.