Wasted Efforts Impair Random Search Efficiency and Reduce Choosiness in Mate-Pairing Termites.

AbstractRandom search theories predict that animals employ movement patterns that optimize encounter rates with target resources. However, animals are not always able to achieve the best search strategy. Energy depletion, for example, limits searchers' movement activities, forcing them to adjust their behaviors before and after encounters.

Ant foragers might present variation and universal property in their movements.

Investigating the locomotion mechanisms of animals improves our understanding of both their inherent movements and responses to external stimuli. Moreover, identifying the movement patterns of animals reveals their foraging search efficiency. The navigational mechanisms of foraging ants have been well studied; they present typical search strategies for pinpointing their goal.

Deep learning-assisted comparative analysis of animal trajectories with DeepHL.

A comparative analysis of animal behavior (e.g., male vs.

Arousal from Tonic Immobility by Vibration Stimulus.

Tonic immobility (TI) is an effective anti-predator strategy. However, long immobility status on the ground increases the risk of being eaten by predators, and thus insects must rouse themselves when appropriate stimulation is provided. Here, the strength of vibration causing arousal from the state of TI was examined in strains artificially selected for longer duration of TI (L-strains: long sleeper) in a beetle.

Regulatory mechanism predates the evolution of self-organizing capacity in simulated ant-like robots.

The evolution of complexity is one of the prime features of life on Earth. Although well accepted as the product of adaptation, the dynamics underlying the evolutionary build-up of complex adaptive systems remains poorly resolved. Using simulated robot swarms that exhibit ant-like group foraging with trail pheromones, we show that their self-organizing capacity paradoxically involves regulatory behavior that arises in advance.

Anomalous diffusion on the servosphere: A potential tool for detecting inherent organismal movement patterns.

Tracking animal movements such as walking is an essential task for understanding how and why animals move in an environment and respond to external stimuli. Different methods that implemented image analysis and a data logger such as GPS have been used in laboratory experiments and in field studies, respectively. Recently, animal movement patterns without stimuli have attracted an increasing attention in search for common innate characteristics underlying all of their movements.