Not so fast: swimming behavior of sailfish during predator-prey interactions using high-speed video and accelerometry

Billfishes are considered among the fastest swimmers in the oceans. Despite early estimates of extremely high speeds, more recent work showed that these predators (e.g., blue marlin) spend most of their time swimming slowly, rarely exceeding 2 m s(-1). Predator-prey interactions provide a context within which one may expect maximal speeds both by predators and prey. Beyond speed, however, an important component determining the outcome of predator-prey encounters is unsteady swimming (i.e., turning and accelerating). Although large predators are faster than their small prey, the latter show higher performance in unsteady swimming. To contrast the evading behaviors of their highly maneuverable prey, sailfish and other large aquatic predators possess morphological adaptations, such as elongated bills, which can be moved more rapidly than the whole body itself, facilitating capture of the prey. Therefore, it is an open question whether such supposedly very fast swimmers do use high-speed bursts when feeding on evasive prey, in addition to using their bill for slashing prey. Here, we measured the swimming behavior of sailfish by using high-frequency accelerometry and high-speed video observations during predator-prey interactions. These measurements allowed analyses of tail beat frequencies to estimate swimming speeds. Our results suggest that sailfish burst at speeds of about 7 m s(-1) and do not exceed swimming speeds of 10 m s(-1) during predator-prey interactions. These speeds are much lower than previous estimates. In addition, the oscillations of the bill during swimming with, and without, extension of the dorsal fin (i.e., the sail) were measured. We suggest that extension of the dorsal fin may allow sailfish to improve the control of the bill and minimize its yaw, hence preventing disturbance of the prey. Therefore, sailfish, like other large predators, may rely mainly on accuracy of movement and the use of the extensions of their bodies, rather than resorting to top speeds when hunting evasive prey.

High-speed pollen release in the white mulberry tree, Morus alba L

Anemophilous plants described as catapulting pollen explosively into the air have rarely attracted detailed examination. We investigated floral anthesis in a male mulberry tree with high-speed video and a force probe. The stamen was inflexed within the floral bud. Exposure to dry air initially resulted in a gradual movement of the stamen. This caused fine threads to tear at the stomium, ensuring dehiscence of the anther, and subsequently enabled the anther to slip off a restraining pistillode. The sudden release of stored elastic energy in the spring-like filament drove the stamen to straighten in less than 25 μs, and reflex the petals to velocities in excess of half the speed of sound. This is the fastest motion yet observed in biology, and approaches the theoretical physical limits for movements in plants.

Intelligent DDoS packet filtering in high-speed networks

Currently high-speed networks have been attacked by successive waves of Distributed Denial of Service (DDoS) attacks. There are two major challenges on DDoS defense in the high-speed networks. One is to sensitively and accurately detect attack traffic, and the other is to filter out the attack traffic quickly, which mainly depends on high-speed packet classification. Unfortunately most current defense approaches can not efficiently detect and quickly filter out attack traffic. Our approach is to find the network anomalies by using neural network, deploy the system at distributed routers, identify the attack packets, and then filter them quickly by a Bloom filter-based classifier. The evaluation results show that this approach can be used to defend against both intensive and subtle DDoS attacks, and can catch DDoS attacks’ characteristic of starting from multiple sources to a single victim. The simple complexity, high classification speed and low storage requirements make it especially suitable for DDoS defense in high-speed networks.

Classifying DDoS packets in high-speed networks

Recently high-speed networks have been utilized by attackers as Distributed Denial of Service (DDoS) attack infrastructure. Services on high-speed networks also have been attacked by successive waves of the DDoS attacks. How to sensitively and accurately detect the attack traffic, and quickly filter out the attack packets are still the major challenges in DDoS defense. Unfortunately most current defense approaches can not efficiently fulfill these tasks. Our approach is to find the network anomalies by using neural network and classify DDoS packets by a Bloom filter-based classifier (BFC). BFC is a set of spaceefficient data structures and algorithms for packet classification. The evaluation results show that the simple complexity, high classification speed and accuracy and low storage requirements of this classifier make it not only suitable for DDoS filtering in high-speed networks, but also suitable for other applications such as string matching for intrusion detection systems and IP lookup for programmable routers.

High-precision five-axis machine for high-speed material processing using linear motors and parallel-serial kinematics

The paper describes some details of the mechanical and kinematics design of a five-axis mechanism. The design has been utilized to physically realize an industrial-scale five-axis milling machine that can carry a three KW spindle. However, the mechanism could be utilized in other material processing and factory automation applications. The mechanism has five rectilinear joints/axes. Two of these axes are arranged traditionally, i.e. in series, and the other three axes utilize the concept of parallel kinematics. This combination results in a design that allows three translational and two rotational two-mode degrees of freedom (DOFs). The design provides speed, accuracy and cost advantages over traditional five-axis machines. All axes are actuated using linear motors.

Dynamic simulation of collisions of heavy high-speed trucks with concrete barriers

Real vehicle collision experiments on full-scale road safety barriers are important to determine the outcome of a vehicle versus barrier impact accident. However, such experiments require large investment of time and money. Numerical simulation has therefore been imperative as an alternative method for testing concrete barriers. In this research, spring subgrade models were first developed to simulate the ground boundary of concrete barriers. Both heavy trucks and concrete barriers were modeled using finite element methods (FEM) to simulate dynamic collision performances. Comparison of the results generated from computer simulations and on-site full-scale experiments demonstrated that the developed models could be applied to simulate the collision of heavy trucks with concrete barriers to provide the data to design new road safety barriers and analyze existing ones.

Modelling factors of square tubes in high speed bending situations

Accurate finite element crash simulations of side impact depend upon a thorough understanding of dynamic tube bending. There is a need to understand the dynamic bending mode of square sections (equivalent of automotive structural parts) to obtain a greater confidence in CAE. This work varied strain rate and material definitions, such as Cowper-Symonds vs Zerilli-Armstrong, as well as initial velocity and yield strength. The results show that most of the plastic work is done between strains rates of 30 ¿ 300/s and strains up to 0.3. Peak strain rates were marginally above 1000/s with maximum strain greater than 1. When the strain rate definition and material model were modified, it was shown that a higher yield stress produced a higher reaction force. These results would suggest that the strain rate sensitivity needs to be carefully identified for accurate crash simulations.

Energy efficient, fully-connected mesh networks for high speed applications

Fully-connected mesh networks that can potentially be employed in a range of applications, are inherently associated with major deficiencies in interference management and network capacity improvement. The tree-connected (routing based) mesh networks used in today’s applications have major deficiencies in routing delays and reconfiguration delays in the implementation stage. This paper introduces a CDMA based fully-connected mesh network, which controls the transmission powers of the nodes in order to ensure that the communication channels remain interference-free and minimizes the energy consumption. Moreover, the bounds for the number of nodes and the spatial configuration are provided to ensures that the communication link satisfies the QoS (Quality of Service) requirements at all times.

Information-based regulation of high-velocity foot-targeting tasks

Judging time-to-contact with a target is an important criterion for avoiding harm in everyday walking and running tasks, and maximizing performance in high-velocity sporting tasks. The information-based regulation of step length and duration during target-directed locomotion was examined in relation to gait mode, approach velocity, target task, expertise, and sporting performance during a series of four experiments. The first three experiments examined novice performers (Each n=12, 6 males, 6 females), whilst the last experiment examined expert gymnasts (n=5). Two reference strips with alternating 50cm black and white intervals were placed on either side of the approach strip for all of the experiments. One 50Hz-panning video camera filmed the approach from an elevated position. In Experiment 4, two stationary 250Hz cameras filmed the post-flight performance of the gymnastic vaults and, in addition, two qualified judges provided a performance score for each vaulting trial. The panning video footage in each experiment was digitized to deduce the gait characteristics. In Experiment 4, the high-speed video footage was analyzed three-dimensionally to obtain the performance measures such as post-flight height. The utilization of visual stimulus in target-directed locomotion is affected by the observer's state of motion as characterized by the mode of locomotion and also often the speed of locomotion. In addition, experience plays an important role in the capacity of the observer to utilize visual stimulus to control the muscular action of locomotion when either maintaining or adjusting the step mechanics. The characteristics of the terrain and the target also affect the observer's movement. Visual regulation of step length decreases at higher approach speeds in novice performers, where as expert performers are capable of increasing visual regulation at higher approach speeds. Conservatism in final foot placement by female participants accounts for the observed increase in distance from the critical boundary of the obstacle relative to toe placement. Behavioural effects of gender thus affect the control of final foot placement in obstacle-directed locomotion. The visual control of braking in target-directed locomotion is described by a tau-dot of-0.54. When tau-dot is below -0.54 a hard collision with the obstacle will occur, however, when tau-dot is above -0.54, a soft collision with the target will occur. It is suggested that the tau-dot margin defining the control of braking reveals the braking capacity of the system. In the target-directed locomotion examined a tau-dot greater than -0.70 would possibly exceed the braking capacity of the system, thus, leading to injury if performed. The approach towards the take-off board and vaulting horse in gymnastics is an example of target-directed locomotion in sport. Increased visual regulation of the timing and length of each step is a requirement for a fast running approach, a fundamental building block for the execution of complex vaults in gymnastics. The successful performance of complex vaults in gymnastics leads towards a higher judge's score. Future research suggestions include an investigation of visual regulation of step length in curved target-directed locomotion.

Na+-doped zinc oxide nanofiber membrane for high speed humidity sensor

A novel sensitive humidity nanosensor based on Na1-doped ZnO nanofiber membrane has been prepared via electrospinning and calcination. The product was characterized by scanning electron microscopy and X-ray diffraction. During the whole relative humidity (11%–95%) measurement, the response and recovery time is about 3 and 6 s, respectively, with good linearity, and reproducibility. These remarkable and sensitive sensing performances make our product a good candidate in fabricating humidity sensors.