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1,399 results for “manual”
Fig. 24. Right manual digit II in The Osteology Of Balaur Bondoc, An Island-Dwelling Dromaeosaurid (Dinosauria: Theropoda) From The Late Cretaceous Of Romania
Fig. 24. Right manual digit II of Balaur bondoc (EME PV.313). Right phalanx II-1 (A–F), right phalanx II-2 (G–L), and right phalanx II-3 (M–N) in extensor (A, G), flexor (B, H), lateral (C, I, N), medial (D, J, M), proximal (E, K), and distal (F, L) views. Scale bar equals 1 cm.
Scalasca analysis report of the ASCI Sweep3D benchmark on 294,912 processes in virtual-node mode on IBM Blue Gene/P with manually annotated iterations
<p>A Cube3 performance analysis report written by the Scalasca parallel analyzer of a measurement of the ASCI benchmark Sweep3D, executed in virtual-node mode on 294,912 processes of the IBM Blue Gene/P system JUQUEEN, operated by Forschungszentrum Jülich GmbH. The measurement includes system topology information and manual annotations of the twelve iterations.</p>
Figure 7 in Basic laboratory and field manual for conducting research with the entomopathogenic nematodes, Steinernema and Heterorhabditis, and their bacterial symbionts
Figure 7. Scanning electron microscopy images of Steinernema beitlechemi infective juvenile and female. A–D: Infective juvenile. A: Head region with four papillae, amphid openings (a) and excretory pore (ep); B: Lateral field in mid-body (ridges numbered 1–6); C: Lateral field in tail region with anus and phasmid opening (arrow); D: Tail region with anus and phasmid openings (arrows), ventral view. E, F: First generation female. E: Vulva; F: Tail with mucron (m), ventro-lateral.
Figure 6 in Basic laboratory and field manual for conducting research with the entomopathogenic nematodes, Steinernema and Heterorhabditis, and their bacterial symbionts
Figure 6. Storage of entomopathogenic nematodes in clear tissue culture flasks on the left and Tetrapak containers on the right.
Figure 3 in Basic laboratory and field manual for conducting research with the entomopathogenic nematodes, Steinernema and Heterorhabditis, and their bacterial symbionts
Figure 3. White trap system with entomopathogenic nematode-infected Galleria mellonella and Tenebrio molitor cadavers. Color change of infected cadavers is observed a few days after death. Heterorhabdid- infected cadaver generally turns red (A and C); steinernematids- infected are brown, tan or even black (C and D).
Fig. 3. Global temperature trends 1880–2017 in Book Review The Wildlife Techniques Manual, Eighth Edition
Fig. 3. Global temperature trends 1880–2017. Global mean estimates based on land and ocean data. https://data.giss.nasa.gov/ gistemp/graphs/. Graphic in the Public Domain.
Fig. 2 in Book Review The Wildlife Techniques Manual, Eighth Edition
Fig. 2. The Wildlife Techniques Manual (8th edition, 2 volumes) compared to the slender 1st edition published 60 years earlier (Mosby 1960), which has 17 chapters. Photo by Howard Clark.
Fig. 1. The Wildlife Techniques Manual, 2 in Book Review The Wildlife Techniques Manual, Eighth Edition
Fig. 1. The Wildlife Techniques Manual, 2 Volumes. Editor, Silvy NJ. The Johns Hopkins University Press, Baltimore, Maryland, USA. 8th Edition, published 28 July 2020.
Recordings of zebra finch group behaviors with manually annotated vocal segments
<div> <div>This dataset contains recording files and manually annotated vocal segments of freely behaving zebra finches in the BirdPark. The files contain animal-borne accelerometer, microphone and video channels. Birds are housed in groups of different sizes (2, 4, or 8 birds, (one 7-mins file per group). The dataset contains 112 mins of recordings from 4 different experiments.</div> </div> <p>The dataset is published as an appendix of the following paper:</p> <p><a href="https://doi.org/10.1101/2022.09.23.509166">Rüttimann, L., Wang, Y., Rychen, J., Tomka, T., Hörster, H., Rocha, M. D., & Hahnloser, R. H. (2024). Multimodal system for recording individual-level behaviors in songbird groups. bioRxiv.</a></p> <p>See the README.pdf file for a detailed description.</p>
FIGURE 16. Right manual ungual phm I-2 in Articulated bone sets of manus and pedes of Camarasaurus (Sauropoda, Dinosauria)
FIGURE 16. Right manual ungual phm I-2 of the Camarasaurus SMA 0002 in medial (left), dorsal, lateral, and palmar (right, top to bottom) views. Schematic drawing indicates location of the claw. The metal bar overlain with semi-transparent white in the photo of the lateral view functions as support for the mount. Abbreviation: mg, medial groove. Scale bar equals 5 cm.
SICS-105: Phase recognition in Manual Small-Incision Cataract Surgery
<p><span>This prospective cross-sectional study introduces the first Manual Small-Incision Cataract Surgery (SICS) video dataset, which is prevalent but understudied in low- and middle-income countries (LMICs), evaluates effectiveness of phase recognition through deep learning (DL) using the MS-TCN++ architecture and compares its results with the well-studied phacoemulsification procedure using the Cataract-101 public dataset. Our novel SICS-105 dataset involved 105 patients recruited at Sankara Eye Hospital in India. Performance is evaluated with frame-wise accuracy, edit distance, F1-score, Precision-Recall AUC, sensitivity, and specificity. The MS-TCN++ architecture performs better on the Cataract-101 dataset across reported metrics, with an accuracy of 89.97% [CI 86.69-93.46%] compared to 84.94% [CI 79.45-92.03%] on the SICS-105 dataset (ROC AUC 99.10% [98.34-99.51%] vs. 98.22% [97.17-99.39%]). Reducing the 20 phases to 13 phase in SICS improved performance without completely bridging the gap. The per-video accuracy distribution and confidence-intervals overlap between the samples. PR-AUC curves for each phase in the SICS dataset range from 46.20 to 94.18%. In conclusion, we replicated phase recognition results from phacoemulsification in a new open-access SICS dataset using DL with slightly lower prediction performance. This research marks a crucial step towards improving postoperative analysis and training for SICS.</span></p>
Linked collectors and determiners for: Manual de las gramíneas de Durango.
Natural history specimen data linked to collectors and determiners held within, "Manual de las gramíneas de Durango". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8031a106-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/8031a106-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8031a106-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/8031a106-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Manual ilustrado de las orquídeas silvestres del estado de Morelos.
Natural history specimen data linked to collectors and determiners held within, "Manual ilustrado de las orquídeas silvestres del estado de Morelos". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/803aa7c4-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/803aa7c4-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/803aa7c4-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/803aa7c4-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
EEG/LFP/EMG data from freely-behaving rats across the sleep/wake cycle (includes manual identification of behavioral state in 4s epochs)
<p>Open-access data set that contains raw EEG/LFP/EMG data recorded from freely-behaving rats. 40 complete 24-hr recordings across 10 male, Sprague Dawley rats are included. Additionally, manual behavioral state classification is provided for all recordings in 4s epochs. These data form the testing and training set for a recently accepted article (Ellen J.G. and Dash, M.B. <em>An automated neural network for automated behavioral state classification rats</em>, peerJ (<em>in press)</em>) which details an open-source artificial neural network for automated classification of behavioral state. R-code for the automated classifier and detailed instructions for its implementation are freely available at: <a href="https://github.com/jellen44/AutomaticSleepScoringTool"><em> https://github.com/jellen44/AutomaticSleepScoringTool</em></a></p> <p>For additional details about the data set, please see the uploaded readme file.</p> <p> </p>
Tracking Data I/II of the publication "A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction"
<p>DATA belonging to the paper<br> "A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction"<br> Katharina Löffler, Tim Scherr, Ralf Mikut<br> doi: https://doi.org/10.1101/2021.03.16.435631</p> <p>-----------------------------</p> <p>To investigate the influence of different segmentation errors on the tracking performance we simulate errorneous segmentation data:<br> - under-segmentation (referred to as "merge" in the folders), over-segmentation("split"), False Negatives ("remove"), combination of the aforementioned errors ("mixed")<br> - percentages: 1,2,5,10,20 of errorneous masks per dataset<br> - runs: 5 randomly initialized runs per combination<br> - datasets: Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ each with two image sequences<br> ---> in total 4 (error types) * 5 (percentage) * 5 (runs) * 2 (data sets) * 2 (image sequences) = 400 datasets</p> <p>The datasets can be recreated by running our code https://git.scc.kit.edu/KIT-Sch-GE/2021-cell-tracking<br> ----------------------------</p> <p>RESULTS<br> We evuated the four tracking algorithms KIT-Sch-GE(1), KTH-SE, MU-Lux-CZ and our proposed algorithm on the aforementioned datasets and compare their performance using the CTC metrics DET, SEG and TRA.<br> This repository contains all metrics as xls files and all tracking results as image sequences.</p> <p><br> <strong>xls files</strong><br> -----------<br> compare_all_trackers_on_synt_bm.csv<br> Comparing the tracking algorithms MU-Lux-CZ, KTH-SE, KIT-Sch-GE(1) and the proposed tracking algorithm on synthetically degraded segmentation data Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ (Cell Tracking Challenge datasets).<br> Reported scores are DET, SEG and TRA from the Cell Tracking Challenge<br> (Fig8 and Fig9 and Supplementary Figures 3 and 4 are created from this data)</p> <p><br> compare_postprocessing_on_synth_bm.csv<br> Comparing the different post-processing strategies of the proposed tracking algorithm algorithm on synthetically degraded segmentation data Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ (Cell Tracking Challenge datasets).<br> Reported scores are DET, SEG and TRA from the Cell Tracking Challenge<br> (Fig7 and Fig8 and Supplementary Figures 1 and 2 are created from this data)</p> <p><strong>PLEASE NOTE: the folder compare_postprocessing_synth_bm is provided in the repository 10.5281/zenodo.5227610 due to size restrictions.</strong></p> <p><strong>folders </strong>(decompressed approximately 90GB of data!)<br> -----------<br> tracking_data<br> compare_all_synth_bm<br> Contains all tracking results for each tracking algorithm on the synthetically degraded datasets ()</p> <p> compare_all_synth_bm_no_error<br> Contains the tracking results for each tracking algorithm provided with the perfect ground truth segmentation data</p> <p> compare_postprocessing_synth_bm [<strong>will be stored in 10.5281/zenodo.5227610 due to size restrictions</strong>]<br> Contains all tracking resuls for each postprocessing configuration of the proposed cell tracking algorithm<br> the leaf folders are names run_xPOSTPROCESSING where x is the run number and POSTPROCESSING the postprocessing key<br> Postprocessing keys: ("no untangle" or "no masks" is indicated by an overline in the paper)<br> all ("untangle + masks" in the paper)<br> nd ("no untangle + masks")<br> nd_ns-l ("no untangle + no masks")<br> ns-l ("untangle + no masks")</p>
FIGURE 28. Right manual phalanx II-2 in Anatomy of Mahakala omnogovae (Theropoda: Dromaeosauridae), Tögrögiin Shiree, Mongolia
FIGURE 28. Right manual phalanx II-2 of Mahakala omnogovae (IGM 100/1033) in medial (A), dorsal (B), lateral (C), and ventral (D) views.
Figure 11 in On the manual morphology of Compsognathus longipes and its bearing on the diagnosis of Compsognathidae
Figure 11. Right manus, ventral view, with some left elements in the Paris (Canjuers) specimen of Compsognathus longipes NMNH CNJ 79, largely preserved as impressions. Identifiable elements labelled in drawing are as follows: 1, r. mc I; 2, r. mc II; 3, r. mc III; 4, r. ph I-1; 5, r. ph I-2; 6, r. ph II-1; 7, r. ph III-1?; 8, l. mc II; 9, l. mc III; 10, l. ph II-1; 11, l. ph III-1?; 12, r. dc1 +2?; 13, r. radiale; 14, r. radius; 15, r. ulna; 16, l. ulna.
Figure 8 in On the manual morphology of Compsognathus longipes and its bearing on the diagnosis of Compsognathidae
Figure 8. Unguals preserved on Compsognathus slab. A, left digit I ungual, showing robust, deep flexor tubercle. B, right digit I ungual (in articulation) showing deep, robust flexor tubercle as in A. C, left digit II ungual (in articulation) showing more gracile flexor tubercle. D, right digit II ungual medial impression (mirrored for comparison) showing shallow, gracile flexor tubercle as in C.
Figure 12 in On the manual morphology of Compsognathus longipes and its bearing on the diagnosis of Compsognathidae
Figure 12. Comparison of hands of various coelurosaurs. A, Allosaurus fragilis (reconstructed from Madsen, 1976); B, Scipionyx samnictus; C, Nqwebisaurus thwazi (after DeKlerk et al., 2000); D, Huaxiagnathus orientalis (after Hwang et al., 2004); E, Sinosauropteryx sp. NGMC 21124; F, Sinosauropteryx prima (reconstructed from Currie & Chen, 2001); G, Compsognathus longipes.
Figure 7. A, left digit II phalanges 2 and 3 in On the manual morphology of Compsognathus longipes and its bearing on the diagnosis of Compsognathidae
Figure 7. A, left digit II phalanges 2 and 3 (ungual) shown in near articulation. Arrow shows subcircular articular condyles typical of theropod II-2. B, right digit II, phalanx 2 lateral impression.
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.