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As eusocial creatures, bees display unique macro col- lective behavior and local body dynamics that hold potential ap- plications in various fields, such as computer animation, robotics, and social behavior. Unlike birds and fish, bees fly in a low-aligned zigzag pattern. Additionally, bees rely on visual signals for foraging and predator avoidance, exhibiting distinctive local body oscilla- tions, such as body lifting, thrusting, and swaying. These inherent features pose significant challenges to realistic bee simulations in practical animation applications. In this article, we present a bio-inspired model for bee simulations capable of replicating both macro collective behavior and local body dynamics of bees. Our approach utilizes a visually-driven system to simulate a bee’s local body dynamics, incorporating obstacle perception and body rolling control for effective collision avoidance. Moreover, we develop an oscillation rule that captures the dynamics of the bee’s local bodies, drawing on insights from biological research. Our model extends beyond simulating individual bees’ dynamics; it can also represent bee swarms by integrating a fluid-based field with the bees’ in- nate noise and zigzag motions. To fine-tune our model, we utilize pre-collected honeybee flight data. Through extensive simulations and comparative experiments, we demonstrate that our model can efficiently generate realistic low-aligned and inherently noisy bee swarms. 

As an electron-deficient element, boron possesses fascinating three-dimensional structures and unconventional chemical bonds. Nanoclusters of boron have also been found to exhibit intriguing structural properties, observed to have predominantly planar structures, in stark contrast to bulk boron allotropes, which are composed of the ubiquitous B₁₂icosahedral building blocks. Here, we report observation of the 2D-to-3D transition and bulk-like structural features in the size-selected boron clusters, as revealed by photoelectron spectroscopy, chemisorption experiments, and first-principles calculations. In the small to medium cluster size range, planar boron cluster anions are found to be unreactive and only B₄₆^–and B₅₆^–are observed to chemisorb C₂H₄and CO under ambient conditions, suggesting major structural transitions at these cluster sizes. Notably, B₅₆^–is also found to be able to chemisorb and activate CO₂. The global minimum of B₄₆^–is found to adopt a core-shell structure (B₂@B₄₄^–), consisting of a B₂core within a B₄₄shell, reminiscent of the interstitial B₂dumbbells in the high-pressureγ-B₂₈form of bulk boron. More remarkably, both the global minimum and the second most stable isomer of B₅₆^–exhibit nest-like configurations, featuring the iconic B₁₂icosahedral core surrounded by a B₄₄half-shell (B₁₂@h-B₄₄^–), signifying the onset of bulk-like structural characteristics in boron nanoclusters. 

Realistic simulation of the intricate wing deformations seen in flying insects not only deepens our comprehension of insect fight mechanics but also opens up numerous applications in fields such as computer animation and virtual reality. Despite its importance, this research area has been relatively under-explored due to the complex and diverse wing structures and the intricate patterns of deformation. This paper presents an efficient skeleton-driven model specifically designed to real-time simulate realistic wing deformations across a wide range of flying insects. Our approach begins with the construction of a virtual skeleton that accurately reflects the distinct morphological characteristics of individual insect species. This skeleton serves as the foundation for the simulation of the intricate deformation wave propagation often observed in wing deformations. To faithfully reproduce the bending effect seen in these deformations, we introduce both internal and external forces that act on the wing joints, drawing on periodic wing-beat motion and a simplified aerodynamics model. Additionally, we utilize mass- spring algorithms to simulate the inherent elasticity of the wings, helping to prevent excessive twisting. Through various simulation experiments, comparisons, and user studies, we demonstrate the effectiveness, robustness, and adaptability of our model.