Find research datasets worth reusing

opencc-by-4.0Jul 2020View details →

Fig. 2 in Evaluation of seedling tray drench of insecticides for cabbage maggot (Diptera: Anthomyiidae) management in broccoli and cauliflower

Fig. 2. Least squares means (± SE) of severity of Delia radicum feeding injury to 5 insecticides and an untreated control in (A) broccoli and (B) cauliflower in the greenhouse. Means with different letters are significantly different between treatments for each commodity according to Tukey's HSD test at P <0.05.

opencc-by-4.0Jul 2020View details →

Fig. 4 in Evaluation of seedling tray drench of insecticides for cabbage maggot (Diptera: Anthomyiidae) management in broccoli and cauliflower

Fig. 4. Mean (± SE) of (A) Delia radicum larvae and (B) severity of Delia radicum feeding injury of 20 cauliflower plants in the field trial 4 conducted in 2016. Means with different letters are significantly different between treatments for each parameter according to Tukey's HSD test at P <0.05. Where no differences were observed, no letters are given.

opencc-by-4.0Dec 2017View details →

Figure 1 in An Outcomes Evaluation of the NDC fruit processors factory in Tzaneen (NDC) 2016: Suppliers

Figure 1. – Images of specimens of Pomacanthus showing main identification features; images are purposely drawn to the same scale. A: P. maculosus, based on photograph of specimen from Bahrain by J.E. Randall, available on Fish- Base; B: P. asfur, based on photograph of specimen from Sudan by J.E. Randall, available on Fishbase; C: P. maculosus, based on photograph of specimen from Malta by S. Farrugia (see Evans et al., 2016); D: Specimen from Malta identified as P. asfur by Deidun and Bonnici (2016), based on photograph by C. Bonnici. The characteristics of the two specimens from Malta, including the body colour, presence of markings on the nape and forehead, and the position and extent of the yellow bar, match those of P. maculosus. Scale bars: 50 mm. For specimen (D), no indication of size was provided by Deidun and Bonnici (2016).

opencc-by-4.0Aug 2024View details →

Evaluation of Selected Artificial Aging Protocols for Dental Composites Including Fatigue and Fracture Tests

This research was funded by the National Science Centre, Poland [grant number: UMO-2020/37/N/ST5/00191, 2021]. Datasets was basis for publication entitled:  Evaluation of Selected Artificial Aging Protocols for Dental Composites Including Fatigue and Fracture Tests, published at Applied  Sciences in 2024.  The publication is a summary of the second step of the project, that aims standardizing an artificial aging protocol for dental composites. Until now, there has been no effort to create a standard protocol for evaluating the clinical performance of dental composites in a practical and efficient manner. Dental materials are not required to undergo studies that verify their durability over their expected lifespan before they are released to the market. Implementing a standardized aging process is essential to enhance the dental resin composite's ability to withstand oral conditions. Research in this area has been supported by the Preludium grant from the National Science Center in Poland. Three materials were tested to compare the degradation of resin from that of the filler and resin–filler interface. The first material (Resin F) was unfilled resin. The second and third materials were composites based on a similar resin matrix to Resin F but with differentiated fillers content. On the basis of the obtained data (https://zenodo.org/records/6583563), three protocols were selected for the second part of the project (standardization of artificial aging protocol for dental composites). The influence of three selected aging protocol on the material properties of the samples was determined based on flexural strength (FS), diametral tensile strength (DTS), Vickers hardness (HV) and microstructure evaluation. Additionally, fracture toughness (FT) and flexural fatigue limit (FFL) were determined. The proposed complex aging protocols should simulate prolonged, possibly several to even a dozen or more years of material usage in the oral cavity, thereby furnishing valuable insights into its prospective clinical performance in vitro.  Authors hope to determine an artificial aging method for evaluating the clinical performance of dental composites. Our publication is first attempt to determine standard aging protocol for dental composites.

opencc-by-4.0Dec 2021View details →

Fig. 2 in Toxoplasma gondii contamination at an animal agriculture facility: Environmental, agricultural animal, and wildlife contamination indicator evaluation

Fig. 2. Soil sampling and animal trapping locations at Little River Animal and Environmental Unit in Walland, Tennessee, United States.

opencc-by-4.0Dec 2021View details →

Fig. 1 in Toxoplasma gondii contamination at an animal agriculture facility: Environmental, agricultural animal, and wildlife contamination indicator evaluation

Fig. 1. The geographic location of the study site, Little River Animal and Environmental Unit in Walland, Tennessee, United States.

opencc-by-4.0Aug 2021View details →

Fig. 1 in Evaluation of haemoparasite and Sarcocystis infections in Australian wild deer

Fig. 1. Location of eight deer sampling sites in eastern Australia. Queensland: north-east Queensland (1). New South Wales: Liverpool Plains (2), Wollongong (3), and Kiah (4). Victoria: Alpine National Park (5), Upper Yarra Flats and Yellingbo (6). ACT: Canberra (7).

opencc-by-4.0Aug 2021View details →

Fig. 2 in Evaluation of haemoparasite and Sarcocystis infections in Australian wild deer

Fig. 2. Total number of deer samples collected in eastern Australia between March 2018 and November 2019.

Fig. 3 in Evaluation of the stomach contents of Eriphia gonagra from a rocky shore in the southeastern Brazilian coast

Fig. 3. Percentage of itens found in the stomachs of Eriphia gonagra (Fabricius, 1781) captured in the rocky shores (RO) and sand reefs (SR) of Praia Grande, Ubatuba (São Paulo, Brazil). Other animals on RO (0.3%) and SR (0.2%), as well as the presence of nylon threads (RO = 0.05%; SR = 0.06%) are not visible in the figure.

Fig. 6 in Evaluation of the stomach contents of Eriphia gonagra from a rocky shore in the southeastern Brazilian coast

Fig. 6. Frequency of the composition of the main items of the Eriphia gonagra (Fabricius, 1781) diet, according to size classes.

Fig. 2 in Evaluation of the stomach contents of Eriphia gonagra from a rocky shore in the southeastern Brazilian coast

Fig. 2. Percentage of the main food items found in the stomachs of males, females and total population of Eriphia gonagra (Fabricius, 1781) captured on the rocky shore of Praia Grande beach, Ubatuba, São Paulo, Brazil.

Fig. 5 in Evaluation of the stomach contents of Eriphia gonagra from a rocky shore in the southeastern Brazilian coast

Fig. 5. Correspondence Analysis (CA) of frequency of the most relevant food item in the stomachs of males and females of Eriphia gonagra (Fabricius, 1781) at different sampling points of Praia Grande beach, Ubatuba, São Paulo, Brazil.

Fig. 1 in Evaluation of the stomach contents of Eriphia gonagra from a rocky shore in the southeastern Brazilian coast

Fig. 1. Map of Ubatuba Bay with the sampling area between Praia Grande and TenÓrio beaches, state of São Paulo, Brazil.

Fig. 4 in Evaluation of the stomach contents of Eriphia gonagra from a rocky shore in the southeastern Brazilian coast

Fig. 4. Percentage of itens found in the stomachs of Eriphia gonagra (Fabricius, 1781) captured over the seasons in the rocky shores (RO) and sand reefs (SR) of Praia Grande, Ubatuba (São Paulo, Brazil).

opencc-by-4.0Aug 2024View details →

Synthetic Lunar Terrain: A Multimodal Open Dataset for Training and Evaluating Neuromorphic Vision Algorithms

Synthetic Lunar Terrain (SLT) is a dataset based on a reconstruction of a typical cratered lunar surface landscape at the <a href="https://set.adelaide.edu.au/atcsr/space-research/exterres-laboratory" target="_blank" rel="noopener">EXTERRES Laboratory</a> at University of Adelaide, Roseworthy Campus. On a surface area of 3.6m x 4.8m, multiple synthetic craters with different sizes and geometries were sculpted into lunar regolith simulant. A 9kW metal-halide lamp illuminated the scene, providing high contrast drop-shadows from the rims of craters and similar surface features that are characteristic for the Earth's moon. The purpose of this dataset is to provide multimodal recordings of visual information to develop and test algorithms on a hardware analogue of the moon rather than relying on computer simulations. In particular, comparisons between neuromorphic vision sensors like event-based cameras and imaging with conventional monocular cameras are at the core of this work. For this purpose, an event-based camera (Gen4 Prophesee with Prophesee-Sony IMX636 sensor) was mounted downward-pointing next to a optical camera (Basler a2A1920-160ucPRO with Sony IMX392 sensor) on an extendable rod which was moved above the surface in a slow and continuous sweep. In total, SLT consists of camera recordings from 21 different positions/settings, with clockwise and anti-clockwise motions under varying, extreme lighting conditions. The event-stream and grayscale image data can be further referenced via a detailed 3D point cloud obtained by a FARO Focus S70 3D Scanner. This 3D Scan was post-processed, realigned and resampled into a 3D point cloud of ~6.25M points, with a surface density of 1.862 p/mm², providing a ground-truth for the crater geometries. In detail, SLT contains the following: <ul> <li>eventbased.zip: <ul> <li>42 camera orbits in the binary EVT 3.0 format (<a href="https://docs.prophesee.ai/stable/data/encoding_formats/evt3.html" target="_blank" rel="noopener">Prophesee docs</a>) </li> <li>corresponding .mp4 event-frame video rendering for visualization purposes (33.333ms accumulation time at 30FPS)</li> <li>corresponding .bias file containing settings used during recording</li> </ul> </li> <li>code.zip: <ul> <li>Standalone C++ code of the metavision EVT3-to-RAW file decoder, allowing to convert the binary EVT 3.0 format into a plaintext .csv that includes <ul> <li>the coordinates of the event-pixel,</li> <li>the polarity change,</li> <li>and the time-stamp of the event.</li> </ul> </li> <li>This code is an unmodified redistribution from the <a href="https://www.prophesee.ai/metavision-intelligence/" target="_blank" rel="noopener">Metavision SDK</a>, version 4.6.0, released by Prophesee under Apache License 2.0.</li> </ul> </li> <li> optical.zip: <ul> <li>42 image sequences in .tif format (LZW, 1920x1200px, 8bit, grayscale) <ul> <li>Length of image sequences varies between about 300 to 700 images per sequence</li> </ul> </li> </ul> </li> <li>3d_scan.zip: <ul> <li>SLT3d_scan.ply: 3D point cloud of the scene Stanford Polygon File Format</li> <li>SLT3d_scan.xyz: 3D point cloud with plaintext x y z coordinates, white-space separated</li> </ul> </li> <li>cratermap.png: <ul> <li>Annotations of 130 different surface features that have been manually identified as crater-like with approximate x,y-coordinates.</li> </ul> </li> <li>positionmap.png: <ul> <li>Illustration of the different positions from which the rod was moved over the scene (not to scale).</li> </ul> </li> <li>sample.zip: <ul> <li>A sample containing 1 event-camera orbit with the corresponding image sequence (for convenience only, to test the dataset without the need to download it's entirety)</li> </ul> </li> </ul> The global coordinate frame of this dataset puts the origin at the centre of the scene. The shorter side of the terrain is roughly aligned with the x-axis, the longer side with the y-axis. The z-axis represents height/depth (compare with cratermap.png). The different conditions (compare with positionmap.png) from which the data was taken are encoded as follows: <ul> <li>A1, ..., A9 refer to the left side of the scene (negative x)</li> <li>B1, ..., B9 refer to the right side of the scene (positive x)</li> <li>S1, S2, S3 and S4 describe special lighting conditions and/or parameter settings</li> <li>CW refers to a "clockwise" sweeping of the camera-rod, relative to the position</li> <li>ACW refers to an "anti-clockwise" sweeping of the camera-rod, relative to the position</li> </ul> The light from the metal-halide lamp was directed through a small opening, shining along the positive y-axis. In some of the setups, an obstacle was placed between the surface and the opening, blocking out part of the light to create a light-dark separator on the surface, emulating the terminator on the Moon between it's day and night side, resulting in highly contrastive images. We encourage you to consult and cite our related publication, should you find SLT useful. <ul> <li>Märtens, M., Farries, K., Culton, J. and Chin, TJ. "Synthetic Lunar Terrain: A Multimodal Open Dataset for Training and Evaluating Neuromorphic Vision Algorithms", Proceedings of  "International Symposium on Artificial Intelligence, Robotics and Automation in Space (I-SAIRAS), 2024", pp. 609-614</li> </ul>

Fig. 9 in A re-evaluation of the enigmatic dinosauriform Caseosaurus crosbyensis from the Late Triassic of Texas, USA and its implications for early dinosaur evolution

Fig. 9. Possible tree topologies recovered within the herrerasaur lineage from the MPTs produced in the analyses that used the dataset of Baron et al. 2017a). A. Tree with Caseosaurus crosbyensis inside Herrerasauria forming the sister taxon to Herrerasauridae. B. Tree with all herrerasaurian taxa included within Herrerasauridae, with Staurikosaurus pricei and Saltopus elginensis forming a clade. C. Tree with all herrerasaurian taxa included within Herrerasauridae, with two distinct clades: 1, Herrerasauria defined as the most inclusive clade that includes Herrerasaurus ischigualastensis but not Liliensternus liliensterni and Plateosaurus engelhardti; 2, the most inclusive clade that includes Staurikosaurus pricei but not Herrerasaurus ischigualastensis; 3, the most inclusive clade that includes Herrerasaurus ischigualastensis but not Staurikosaurus pricei.

Fig. 1 in A re-evaluation of the enigmatic dinosauriform Caseosaurus crosbyensis from the Late Triassic of Texas, USA and its implications for early dinosaur evolution

Fig. 1. The holotype of the herrerasaurian dinosauriform Caseosaurus crosbyensis Hunt, Lucas, Heckert, Sullivan, and Lockley, 1998 (UMMP 8870) from Tecovas Formation, Crosby County, Texas, USA; Carnian, Late Triassic; right ilium in lateral (A) and medial (B) views.

Fig. 4. A. Strict consensus tree produced from 85 in A re-evaluation of the enigmatic dinosauriform Caseosaurus crosbyensis from the Late Triassic of Texas, USA and its implications for early dinosaur evolution

Fig. 4. A. Strict consensus tree produced from 85 MPTs, each of length 1764 steps. B. Reduced strict consensus tree produced from 91 MPTs, each of length 1764, following the removal of the possible chimera Agnosphitys cromhallenesis. For Bremer support values calculated in this analysis for each of the major nodes, see Table 1. Studied specimens in bold.

Fig. 7 in A re-evaluation of the enigmatic dinosauriform Caseosaurus crosbyensis from the Late Triassic of Texas, USA and its implications for early dinosaur evolution

Fig. 7. Comparison of the ilia of Caseosaurus crosbyensis Hunt, Lucas, Heckert, Sullivan, and Lockley, 1998 (A, B) and Silesaurus opolensis Dzik, 2003 (C) showing locations of rugosities and lateral ridge/buttress. A. UMMP 8870, right ilium in lateral view. B. NMMNH P-35995, right ilium in lateral view. C. ZPAL AbIII404/1, left ilium in lateral view (reversed).

Fig. 8 in A re-evaluation of the enigmatic dinosauriform Caseosaurus crosbyensis from the Late Triassic of Texas, USA and its implications for early dinosaur evolution

Fig. 8. Comparison of the ilia of early dinosaurs. A. Buriolestes schultzi. B. Saturnalia tupiniquim. C. Agnosphitys cromhallensis. D. Tawa hallae. E. Coelophysis bauri. F. Lesothosaurus diagnosticus.