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FIGURE 6. The handle form 1. A in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 6. The handle form 1. A, production process. The component numbers correspond to those in Figure 2; B, the handle in right lateral view; C, the handle in top view; D, the handle with the socket head screw (M4) in bottom view; E, the handle in left lateral view.
FIGURE 5. The Wada air scribe. A in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 5. The Wada air scribe. A, the structure of the Wada air scribe. The component numbers correspond to those in the Figure 2; B, diagram of the Wada air scribe in lateral view; C, cross section of the Wada air scribe in lateral view.
FIGURE 3 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 3. The junction (A-E), cylinder (F-J), and bushing (K-O) in right lateral (A, B, C, F, G, H, K, L, and M), back (D), and front (I and N) views. The component numbers correspond to those of Figure 2. A, one-fifth from the screw head of a fully threaded hex screw; B, the junction; C, diagram of the junction; D, the junction; E, cross section of the junction; F, a coupling nut; G, the cylinder; H, diagram of the cylinder; I, the cylinder; J, cross section of the cylinder; K, middle part of a partially threaded socket head screw; L, the bushing; M, diagram of the bushing highlighting the stem and an exhaust hole; N, the bushing; O, cross section of the bushing.
FIGURE 7. The handle form 2. A in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 7. The handle form 2. A, production process of the support rod; B, production process of the body holder; C, the support rod in right lateral view; D, the support rod in top view; E. the support rod in bottom view; F, the support rod in front view; G, the body holder in right lateral view; H, the body holder in front view. The component numbers correspond to those in Figure 2.
FIGURE 2 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 2. List of the components for one Wada air scribe and two forms of the handle. The "M" designation for metric screws indicates the outer diameter of the screw thread in mm.
FIGURE 1 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 1. Usage example of a conventional pen-shaped pneumatic air scribe. A. Fossil preparation inside of the deep cavity. Note that preparators are required to hold the air scribe at an awkward angle when they try to prepare a hard-to-reach area. B. Micropreparation using the pen-shaped air scribe. The handle of the air scribe could be caught on the rim of the objective lens.
FIGURE S3. The production flow for a in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE S3. The production flow for a cylinder. Schematic diagrams in lateral (upper row) and front (lower row) views are shown.
FIGURE S2. The production flow for a in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE S2. The production flow for a junction. Schematic diagrams in lateral view (upper row) and crosssections (lower row) are shown.
FIGURE 10. Comparison between the commercially available air scribe and the Wada air scribes. A, a in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 10. Comparison between the commercially available air scribe and the Wada air scribes. A, a penshaped air scribe (Micro Jack 2 from PaleoTools®); B, the Wada air scribe.
FIGURE 4 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 4. The assembly drawing of the stylus, spring, and bushing. Note that the distance between the bushing and the base of the stylus must be more than 1 mm.
FIGURE 9. The Wada air scribe with handle forms 1 in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE 9. The Wada air scribe with handle forms 1 (A-C) and 2 (D-F) at a straight angle (0 degrees) (A and D) and a right angle (90 degrees) (B and D), respectively. Using a closed-cell polyurethane foam sleeve cover to encase the handles can effectively reduce the impact on the hand (C and F).
Fig. 2 in Chromosome evolution in fishes: a new challenging proposal from Neotropical species
Fig. 2. Scatter-plot of (a, c) diploid number (2n), and (b, d) pg of DNA per haploid nucleus (C-Value), against the phylogenetic position of Actinopterygii families presented by Nelson (2006). Data include all available species (a, b) or exclude possible polyploidy species (c, d). Ellipses with 95% confidence are used as a correlation indicator.
Fig. 1 in Chromosome evolution in fishes: a new challenging proposal from Neotropical species
Fig. 1. Scatter-plot of (a) diploid number (2n) and (b) fundamental number (FN), against the phylogenetic position of Actinopterygii families presented by Nelson (2006) for 103 fish species. Ellipses with 95% confidence are used as a correlation indicator.
FIGURE 4 in Seeking for gaps in taxonomic descriptions of endemic fishes: a pathway to challenge the Linnean shortfall in a Neotropical basin
FIGURE 4 | Histograms of the year of endemic fish species descriptions according to the fluvial hierarchy of watercourses. Higher negative skewness (-3,18) in low order streams (first to third order, left histogram), and lower negative skewness (-2,57) in high order streams (seventh to ninth order, right histogram).
FIGURE 1 in Seeking for gaps in taxonomic descriptions of endemic fishes: a pathway to challenge the Linnean shortfall in a Neotropical basin
FIGURE 1 | Spatial distribution of localities where the holotype of endemic fish species was found in the Tocantins-Araguaia River basin (grey circles). The red circles delimit the transition zone between upper, middle, and lower sections of the basin.
Fig. 2. Post mortem examination. Post mortem examination for typical calves showing signs associated with Theileria infection. A in Exposure of vaccinated and naive cattle to natural challenge from buffalo-derived Theileria parva
Fig. 2. Post mortem examination. Post mortem examination for typical calves showing signs associated with Theileria infection. A: Copious frothy exudate from nasal cavities of BJ031 and BJ037. B: Pleural exudate in thoracic cavities of BJ033 and BJ041. C: Frothing in trachea of BJ026 and BJ033.
Fig. 1 in Exposure of vaccinated and naive cattle to natural challenge from buffalo-derived Theileria parva
Fig. 1. Kaplan–Meier survival analysis. Kaplan–Meier survival analysis of vaccinated (dashed line) and control (solid line) calves following field exposure. The black circle and red cross at day 30 represent the animals remaining alive at the end of the experiment (censored). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 1 in Sea otter health: Challenging a pet hypothesis
Fig. 1. Parasites that spillover from wildlife to sea otters. Top cycle: cats (like this bobcat) are the final host for the protozoan Toxoplasma gondii, for which sea otters are normally a dead-end host. Opossums drive a similar cycle for Sarcosystis neurona. Although pet cats were once blamed as the primary source of toxoplasmosis in sea otters, new evidence shows stronger associations with locations where wild cats are common (Burgess et al., 2013). Bottom cycle: diving ducks (like this surf scoter) and shorebirds are the final hosts for acanthocephalans that use sand crabs as intermediate hosts. Otters become accidental hosts if they eat sand crabs. Although many papers and the popular press purport that human actions put sea otter health at risk, these parasites are a natural, long-standing problem for sea otters.
Trackerless 3D Freehand Ultrasound Reconstruction Challenge 2024 - Validation Dataset
<blockquote> <p><strong>This Challenge will be an open-ended challenge, and we welcome your submission. Please register your team via this <a title="https://forms.office.com/e/dPg47ktV7M" href="https://forms.office.com/e/dPg47ktV7M" target="_blank" rel="noopener">form</a>. You can submit the algorithm via this <a title="https://forms.office.com/e/QChhNkLYiu" href="https://forms.office.com/e/QChhNkLYiu" target="_blank" rel="noopener noreferrer">form</a> for TUS-REC2024 Challenge, and we will test your submitted docker on the test set.</strong></p> <p><strong>We are organising TUS-REC2025 at MICCAI2025. More information is available on the <a href="https://github-pages.ucl.ac.uk/tus-rec-challenge/" target="_blank" rel="noopener">TUS-REC2025 challenge website</a> and <a href="https://github.com/QiLi111/TUS-REC2025-Challenge_baseline" target="_blank" rel="noopener">Baseline code repo</a>.</strong></p> </blockquote> <p><strong>This is the validation dataset. The training dataset is available at <a href="../doi/10.5281/zenodo.11178508" target="_blank" rel="noopener">Part1</a>, <a href="../doi/10.5281/zenodo.11180795" target="_blank" rel="noopener">Part2</a>, and <a href="../doi/10.5281/zenodo.11355499" target="_blank" rel="noopener">Part3</a>.</strong></p> <p>Acquisition devices and config: The 2D US images were acquired using an Ultrasonix machine (BK, Europe) with a curvilinear probe (4DC7-3/40). The associated position information of each frame was recorded by an optical tracker (NDI Polaris Vicra, Northern Digital Inc., Canada). The acquired US frames were recorded at 20 fps, with an image size of 480×640, without speckle reduction. The frequency was set at 6MHz with a dynamic range of 83 dB, an overall gain of 48% and a depth of 9 cm. </p> <div> <p>Scanning protocol: Both left and right forearms of volunteers were scanned. For each forearm, the US probe moves in three different trajectories (straight line shape, "C" shape, and "S" shape), in a distal-to-proximal direction followed by a proximal-to-distal direction, with the US plane perpendicular of and parallel to the scanning direction. The validation dataset contains 72 scans in total, 24 scans associated with each subject.</p> <p>For detailed information please refer to the <a href="https://github-pages.ucl.ac.uk/tus-rec-challenge/TUS-REC2024/" target="_blank" rel="noopener">Challenge website</a>. Baseline code is also provided, which can be found at this <a href="https://github.com/QiLi111/tus-rec-challenge_baseline" target="_blank" rel="noopener">repo</a>.</p> <p>Dataset structure: </p> <ul> <li>Folder <code>frames</code>: contains three folders (one subject per folder), each with 24 scans. Each .h5 file corresponds to one scan, storing image of each frame within this scan. Key-value pair and name of each .h5 file are explained below. <ul> <li>“frames” - All frames in the scan; with a shape of [N,H,W], where N refers to the number of frames in the scan, H and W denote the height and width of a frame. </li> <li>Notations in the name of each .h5 file: “RH”: right arm; “LH”: left arm; “Per”: perpendicular; “Par”: parallel; “L”: straight line shape; “C”: C shape; “S”: S shape; “DtP”: distal-to-proximal direction; “PtD”: proximal-to-distal direction; For example, “RH_Per_L_DtP.h5” denotes a scan on the right forearm, with ultrasound probe perpendicular of the forearm sweeping along straight line, in distal-to-proximal direction.</li> </ul> </li> </ul> </div> <div> <ul> <li>Folder <code>transfs</code>: contains three folders (one subject per folder), each with 24 scans. Each .h5 file corresponds to one scan, storing transformation of each frame within this scan. Key-value pair and name of each .h5 file are explained below. <ul> <li>“tforms” - All transformations in the scan; with a shape of [N,4,4], where N is the number of frames in the scan, and the transformation matrix denotes the transformation from tracker tool space to camera space. </li> <li>Notations in the name of each .h5 file is the same as in folder <code>frames</code>.</li> </ul> </li> <li>Folder <code>landmark</code>: contains three .h5 files. Each corresponds to one subject, storing coordinates of landmarks for 24 scans of this subject. For each scan, the coordinates are stored in numpy array with a shape of [20,3]. The first column is the index of frame; the second and third columns denote the coordinates of landmarks in the image coordinate system.</li> <li><code>calib_matrix.csv</code>: The calibration matrix was obtained using a pinhead-based method. The "scaling_from_pixel_to_mm" and "spatial_calibration_from_image_coordinate_system_to_tracking_tool_coordinate_system" are provided in the “calib_matrix.csv”.</li> <li><code>dataset_keys.h5</code>: stores the paths to all the scans of the data set. Keys in “dataset_keys.h5” denotes all the available scans in validation set, in a format of “sub%03d__%s” where %03d denotes folder name, and %s denotes the scan name. For example, “sub050__LH_Par_C_DtP” means the scan in folder “050”, with file name of “LH_Par_C_DtP.h5”</li> </ul> <div> <p><strong>Data Usage Policy:</strong></p> <ul> <li>The training and validation data provided may be utilized within the research scope of this challenge and in subsequent research-related publications. However, commercial use of the training and validation data is prohibited. In cases where the intended use is ambiguous, participants accessing the data are requested to abstain from further distribution or use outside the scope of this challenge.</li> <li><span>If you use our dataset in your publication, </span>please cite the challenge paper and some of the following optional articles: <ul> <li>Challenge paper: <ul> <li><strong>Qi Li et al. "TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker." <em>arXiv preprint arXiv:<a title="https://arxiv.org/abs/2506.21765" href="https://doi.org/10.48550/arXiv.2506.21765" target="_blank" rel="noopener">2506.21765</a></em> (2025).</strong></li> </ul> </li> <li>Optional articles:<br> <ul> <li>Qi Li, Ziyi Shen, Qianye Yang, Dean C. Barratt, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Nonrigid Reconstruction of Freehand Ultrasound without a Tracker." In <em>International Conference on Medical Image Computing and Computer-Assisted Intervention</em>, pp. 689-699. Cham: Springer Nature Switzerland, 2024. doi: <a href="https://doi.org/10.1007/978-3-031-72083-3_64" target="_blank" rel="noopener">10.1007/978-3-031-72083-3_64.</a></li> <li>Qi Li, Ziyi Shen, Qian Li, Dean C. Barratt, Thomas Dowrick, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker." IEEE Transactions on Biomedical Engineering, vol. 71, no. 3, pp. 1033-1042, 2024. doi: <a href="https://ieeexplore.ieee.org/abstract/document/10288201" target="_blank" rel="noopener">10.1109/TBME.2023.3325551</a>.</li> <li>Qi Li, Ziyi Shen, Qian Li, Dean C. Barratt, Thomas Dowrick, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future frames." In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), pp. 1-5. IEEE, 2023. doi: <a href="https://doi.org/10.1109/ISBI53787.2023.10230773" target="_blank" rel="noopener">10.1109/ISBI53787.2023.10230773.</a></li> <li>Qi Li, Ziyi Shen, Qian Li, Dean C. Barratt, Thomas Dowrick, Matthew J. Clarkson, Tom Vercauteren, and Yipeng Hu. "Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction." In International Workshop on Advances in Simplifying Medical Ultrasound, pp. 142-151. Cham: Springer Nature Switzerland, 2023. doi: <a href="https://doi.org/10.1007/978-3-031-44521-7_14" target="_blank" rel="noopener">https://doi.org/10.1007/978-3-031-44521-7_14.</a></li> </ul> </li> </ul> </li> </ul> </div> </div>
Fig. 1 in Invasion ecology meets parasitology: Advances and challenges
Fig. 1. Number of articles published per year, between 1980 and 2016, on either biological invasions in general, or more specifically on parasitism in the context of biological invasions, from a search of the Web of Science ® (see text). Note the different scales on the y-axes for the two article counts.
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.