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FIGURE 8 in Evaluating the ecology of Spinosaurus: Shoreline generalist or aquatic pursuit specialist?

FIGURE 8. Depth of water required for Spinosaurus to avoid the considerable effects of wave drag. Even with the hind limbs lifted up, the animal is nearly 3 m in dorsoventral height so to avoid wave drag (fully submerged by over 3.5 m) the water would need to be close to 6 m in depth for Spinosaurus to swim efficiently. This is a minimum and the real value is likely to be higher (see text for details). Outline modified from Ibrahim et al. (2020a) and scale bar equals 1 m.

FIGURE 4 in Evaluating the ecology of Spinosaurus: Shoreline generalist or aquatic pursuit specialist?

FIGURE 4. Graph of theropod ungual curvature vs ungual length. The inset shows how the curvature of the unguals was measured. In lateral view a line AB is drawn between the ungual tip and the base. This is bisected by a perpendicular line until it contacts the ungual at point C. Lines are drawn from A to C and A to B and the internal angle measured. Unguals of Spinosaurus are in red, a further specimen attributed to a spinosaur is in yellow, and individual specimens are abbreviated as follows: Ab, abelisaurid; Ac, Acrocanthosaurus; Ai, Alioramus; Al, Allosaurus; Ca, Caudipteryx; Ce, ceratosaur; Co, Compsognathus; Di, Dilophosaurus; Ga, Gaulicho; Gg, Gigantoraptor; Gl, Gallimimus; Gu, Guanlong; Ha, Halszkaraptor; Ju, Juravenator; Ki, Kileskus; Li, Limusaurus; Mj, Majungasaurus; Sc, Spectrovenator; Sd, spinosaurid; Sn, Sinraptor; Sp, Spinosaurus; SB, Spinosaurus B; Tt, Tyrannotitan; Ty, Tyrannosaurus.

FIGURE 3 in Evaluating the ecology of Spinosaurus: Shoreline generalist or aquatic pursuit specialist?

FIGURE 3. Graphs of various skull measurements to show the relationship between skull shape for different ecotypes. The red point is Spinosaurus, yellow are other spinosaurids, green are terrestrial taxa, pale blue are semi-aquatic and dark blue, fully aquatic animals. Least squares regressions are given for the terrestrial, semi-aquatic and aquatic datasets (the various spinosaurids were not included in these calculations), and the R2 values for these regressions are given.

FIGURE 2 in Evaluating the ecology of Spinosaurus: Shoreline generalist or aquatic pursuit specialist?

FIGURE 2. Principal Components Analysis of various measurements of the skull rescaled to skull length. Principal Component 1 (83.5% of variance) plotted against Principal Component 2 (13.7% of variance), plotted using eigenvalue scale. The red point is Spinosaurus, yellow are other spinosaurids, green are terrestrial taxa, pale blue are semi-aquatic, and dark blue, fully aquatic animals. Silhouettes are from PhyloPic.org and color-coordinated with the lines of the convex hulls for the groups of taxa they represent: the red Suchomimus (representing Spinosauridae; red Xs), the light green Allosaurus (representing non-spinosaurid Theropoda; open light green circles), and the orange Paleorhinus (representing phytosaurs: light brown pluses) are by Scott Hartman; blue Peloneustes (representing Plesiosauria: solid dark blue circles) by Nobu Tamura; dark green Varanus (representing terrestrial lepidosaurs: green asterisks) and dark brown Crocodylus (representing Crocodyliformes: dark brown pluses) by Steven Traver. Additional taxa plot include thallatosuchians (solid light blue circles), the mosasauroid Plotosaurus (blue asterisk), the nothosauroid Lariosaurus (solid aqua circle), and freshwater semi-aquatic lepidosaurs (open orange squares). The inset shows a reptile skull and how measurements were taken for the data used here and in Figure 3.

FIGURE 1 in Evaluating the ecology of Spinosaurus: Shoreline generalist or aquatic pursuit specialist?

FIGURE 1. Skeleton in a standing posture as if dip fishing in water following the wading model, and in a swimming posture (based on Ibrahim et al., 2020a) following the pursuit predator model. A non-exhaustive set of lines of evidence as described in the text are indicated by arrows that either directly support either model (white arrow), are ambiguous or do not contradict the model (grey arrow), or actively contradict the model (black arrow). Key traits are as follows: A) laterally compressed skull, B) nares position, C) mechanical jaw performance, D) orbit position, E) neck stiffness and posture, F) non-hydrodynamic shape, G) instability in water, H) sub-anguilliform locomotion, I) thin caudal neural spines, J) tail propulsion, K) distal tail flexibility, L) low swimming efficiency, M) somewhat reduced hind limbs, N) enlarged 1st toe, O) pachyostosis, P) pneumatic elements, Q) forelimbs not reduced, R) neck ventriflexion, S) quadrate shape, T) head posture (as determined for Irritator), U) isotopic data from teeth, V) tooth enamel ridges, W) rostral sensory system. Skeleton modified from the original by Genya Masukawa (used with permission) and scaled to the size of the neotype. Scale bar is 1 m.

FIGURE 5 in Evaluating the ecology of Spinosaurus: Shoreline generalist or aquatic pursuit specialist?

FIGURE 5. Comparison of skull shape of Spinosaurus and Baryonyx scaled to the same size. The two are very similar, which although this may be expected from their shared evolutionary history would suggest that they fundamentally forage in similar ways for similar prey, which contradicts the idea that one is an aquatic specialist. Not to scale.

FIGURE 7. A in Evaluating the ecology of Spinosaurus: Shoreline generalist or aquatic pursuit specialist?

FIGURE 7. A) Skull of a stork (Leptoptilos - scale bar is 100 mm) with a posteriorly retracted naris allowing them to forage while keeping the nares free of the water as in B) showing Ephipporhynchus senegalensis feeding. Although proportionally much further back here than in Spinosaurus, the absolute distance of the naris from the anterior tip of the jaw is less in the stork. C) Skull of crocodylian (Crocodylus - scale bar is 100 mm) with dorsally positioned naris allowing them to rest with minimal exposure of the head as in D) Crocodylus niloticus resting at the surface (image courtesy of Jonathan J. Meisenbach).

opencc-by-4.0Nov 2018View details →

Data from Churan et al. 2018 Comparison of the precision of smooth pursuit in humans and head unrestrained monkeys

Experiments were performed in two rhesus monkeys, B and E. Each monkey made a combination of slow and fast eye-movements following a visual target. The target was stationary at first and then either abruptly started moving (at a speed of 10°/s) in a certain direction (Ramp paradigm) or made a Step before starting the motion (Step-Ramp paradigm). By using a specific Step size and Step direction the initial saccade was eliminated in the Step-Ramp paradigm. The direction of the stimulus motion was predominantly horizontal with a smaller vertical component that was systematically varied between 0° and +-20°. We investigated how precisely the monkeys can follow this vertical component of the stimulus motion. The files: There are separate files for each monkey (B and E) and paradigm (Ramp and Step_Ramp). The files are MATLAB data files. Ramp: Each file consists of three variables – ‘alldatx’, ‘alldaty’, and ‘init’. ‘alldatx’ and ‘alldaty’ are cell arrays in which each cell represents one vertical component of the stimulus: 1=20° up, 2=10° up, 3=5° up, 4=2° up, 5=0° , 6=2° down, 7=5° down, 8=10° down, 9=20° down. Each cell contains a matrix of n x 2001 elements. Each row represents the eye velocities during one individual trial between 1000 ms before and 1000 ms after the start of stimulus motion with a sampling rate of 1000 Hz. ‘init’ is a cell array in which each cell represents one vertical component of the stimulus (s. above). Each cell contains a structure array which shows the approximate properties of the initial saccade in each trial: ‘init.t’: Start end end time of the saccade (in ms) after the start of stimulus motion. ‘init.amp’: Amplitude of the initial saccade in deg ‘init.startpos’, ‘init.endpos’: start- and end-position (x, y) of the saccade Step_Ramp: Each file consists of two variables – ‘alldatx’, ‘alldaty’. Description is the same as for Ramp.

opencc-zeroJan 2023View details →

Hoverfly (Eristalis tenax) pursuit of artificial targets

The ability to visualize small moving objects is vital for the survival of many animals, as these could represent predators or prey. For example, predatory insects, including dragonflies, robber flies and killer flies, perform elegant, high-speed pursuits of both biological and artificial targets. Many non-predatory insects, including male hoverflies and blowflies, also pursue targets during territorial or courtship interactions. To date, most hoverfly pursuits were studied outdoors. To investigate naturalistic hoverfly (Eristalis tenax) pursuits under more controlled settings, we constructed an indoor arena that was large enough to encourage naturalistic behavior. We presented artificial beads of different sizes, moving at different speeds, and filmed pursuits with two cameras, allowing subsequent 3D reconstruction of the hoverfly and bead position as a function of time. We show that male E. tenax hoverflies are unlikely to use strict heuristic rules based on angular size or speed to determine when to start pursuit, at least in our indoor setting. We found that hoverflies pursued faster beads when the trajectory involved flying downwards towards the bead. Furthermore, we show that target pursuit behavior can be broken down into two stages. In the first stage the hoverfly attempts to rapidly decreases the distance to the target by intercepting it at high speed. During the second stage the hoverfly's forward speed is correlated with the speed of the bead, so that the hoverfly remains close, but without catching it. This may be similar to dragonfly shadowing behavior, previously coined 'motion camouflage'.

opencc-zeroMay 2023View details →

Data from: Strategic predatory pursuit of the stealthy, highly maneuverable, slow flying bat Corynorhinus townsendii

A predator's capacity to catch prey depends on its ability to navigate its environment in response to prey movements or escape behavior. In predator-prey interactions that involve an active chase, pursuit behavior can be studied as the collection of rules that dictate how a predator should steer to capture prey. It remains unclear how variable this behavior is within and across species since most studies have detailed the pursuit behavior of high-speed, open-area foragers. In this study, we analyze the pursuit behavior in 44 successful captures by Corynorhinus townsendii, Townsend's big-eared bat (n = 4). This species forages close to vegetation using slow and highly maneuverable flight, which contrasts with the locomotor capabilities and feeding ecologies of other taxa studied to date. Our results indicate that this species relies on an initial stealthy approach, which is generally sufficient to capture prey (32 out of 44 trials). In cases where the initial approach is not sufficient to perform a capture attempt (12 out of 44 trials), C. townsendii continues its pursuit by reacting to prey movements in a manner best modeled with a combination of pure pursuit, or following prey directly, and proportional navigation, or moving to an interception point.

opengpl-2.0Aug 2023View details →

Artifact for MobiCom'23: Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility

This dataset contains the anonymized failure data collected from our physical and device farms over a three-month period. The failure data involves 5,918 physical devices as well as 5,918 virtualized devices running on ARM commodity servers. For more details, please visit our website (<a href="https://android-emulation-testing.github.io/">Android-Emulation-Testing.github.io</a>) or read our paper: <ul> <li>[MobiCom'23] Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility</li> </ul> If you use our dataset in your work, please reference it using: <pre><code>@inproceedings {lin2022virtual, author = {Lin, Hao and Qiu, Jiaxing and Wang, Hongyi and Li, Zhenhua and Gong, Liangyi and Gao, Di and Liu, Yunhao and Qian, Feng and Zhang, Zhao and Yang, Ping and Xu, Tianyin}, title = {{Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility}}, booktitle = {The 29th Annual International Conference on Mobile Computing and Networking (ACM MobiCom'23)}, year = {2023}, publisher = {ACM} }</code></pre>

opencc-zeroSep 2023View details →

Hoverfly (Eristalis tenax) descending neurons respond to pursuits of artificial targets

Many animals use motion vision information to control dynamic behaviors. Predatory animals, for example, show an exquisite ability to detect rapidly moving prey followed by pursuit and capture. Such target detection is not only used by predators but can also play an important role in conspecific interactions. Male hoverflies (Eristalis tenax), for example, vigorously defend their territories against conspecific intruders. Visual target detection is believed to be subserved by specialized target-tuned neurons that are found in a range of species, including vertebrates and arthropods. However, how these target-tuned neurons respond to actual pursuit trajectories is currently not well understood. To redress this, we recorded extracellularly from target selective descending neurons (TSDNs) in male Eristalis tenax hoverflies. We show that the neurons have dorso-frontal receptive fields, with a preferred direction up and away from the visual midline, with a clear division into a TSDNLeft and a TSDNRight cluster. We next reconstructed visual flow-fields as experienced during pursuits of artificial targets (black beads). We recorded TSDN responses to six reconstructed pursuits and found that each neuron responded consistently at remarkably specific time points, but that these time points differed between neurons. We found that the observed spike probability was correlated with the spike probability predicted from each neuron's receptive field and size tuning. Interestingly, however, the overall response rate was low, with individual neurons responding to only a small part of each reconstructed pursuit. In contrast, the TSDNLeft and TSDNRight populations responded to substantially larger proportions of the pursuits, but with lower probability. This large variation between neurons could be useful if different neurons control different parts of the behavioral output.

publicMay 2023View details →

Data from: Strategic predatory pursuit of the stealthy, highly maneuverable, slow flying bat Corynorhinus townsendii

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publicJan 2023View details →

Hoverfly (Eristalis tenax) pursuit of artificial targets

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publicMar 2024View details →

Descending neurons of the hoverfly respond to pursuits of artificial targets

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publicSep 2020View details →

Habitat features and performance interact to determine the outcomes of terrestrial predator-prey pursuits

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opencc-zeroMar 2016View details →

LRP predicts smooth pursuit eye movement onset during the ocular tracking of self-generated movements

Dataset relative to the following publication: Chen, J., Valsecchi, M. & Gegenfurtner, K.R. (2016). LRP predicts smooth pursuit eye movement onset during the ocular tracking of self-generated movements. Journal of Neurophysiology, in press Each folder contains the data relative to one experiment and the script that was used to generate them. Please refer to "Description on data format.txt" for the usage of the data. Additional information can be deducted from the experimental scripts.

opencc-by-4.0May 2017View details →

Visual sensitivity for luminance and chromatic stimuli during the execution of smooth pursuit and saccadic eye movements

Dataset relative to the following publication: Braun, D. I., Schütz, A. C., & Gegenfurtner, K. R. (2017). Visual sensitivity for luminance and chromatic stimuli during the execution of smooth pursuit and saccadic eye movements. Vision Research

opencc-by-4.0Jun 2017View details →

Discrimination of curvature from motion during smooth pursuit eye movements and fixation

One folder contains all the data for the main experiment. In the folder you can find a file dataREADME, which explains the format and the content of the individual files. A second folder contains the data files for the additional control experiment with shorter presentation durations. The structure of the data is the same. It includes two folders. One which constains the perceptual data for the shorter presentation durations and one with eye traces of the same participants for the oculometric thresholds. The name of the folder indicates also the length of the presentation duration, either 150 or 300 ms.