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首页> 外文期刊>Journal of the Royal Society Interface >Built for rowing: frog muscle is tuned to limb morphology to power swimming
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Built for rowing: frog muscle is tuned to limb morphology to power swimming

机译:专为划船而设计:将青蛙肌肉调整为肢体形态,以助游泳

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摘要

Rowing is demanding, in part, because drag on the oars increases as the square of their speed. Hence, as muscles shorten faster, their force capacity falls, whereas drag rises. How do frogs resolve this dilemma to swim rapidly? We predicted that shortening velocity cannot exceed a terminal velocity where muscle and fluid torques balance. This terminal velocity, which is below V_(max), depends on gear ratio (GR = outlever/inlever) and webbed foot area. Perhaps such properties of swimmers are 'tuned', enabling shortening speeds of approximately 0.3V_(max) for maximal power. Predictions were tested using a 'musculo-robotic' Xenopus laevis foot driven either by a living in vitro or computational in silico plantaris longus muscle. Experiments verified predictions. Our principle finding is that GR ranges from 11.5 to 20 near the predicted optimum for rowing (GR ≈ 11). However, gearing influences muscle power more strongly than foot area. No single morphology is optimal for producing muscle power. Rather, the 'optimal' GR decreases with foot size, implying that rowing ability need not compromise jumping (and vice versa). Thus, despite our neglect of additional forces (e.g. added mass), our model predicts pairings of physiological and morphological properties to confer effective rowing. Beyond frogs, the model may apply across a range of size and complexity from aquatic insects to human-powered rowing.
机译:划船的要求很高,部分原因是桨的阻力随着速度的平方增加而增加。因此,随着肌肉更快地缩短,它们的力量下降,而阻力上升。青蛙如何解决这个快速游泳的难题?我们预测缩短速度不能超过肌肉和流体扭矩平衡的最终速度。低于V_(max)的最终速度取决于齿轮比(GR =伸出/伸出)和蹼足面积。也许游泳者的这些特性被“调整”了,从而使最大功率的缩短速度降低了约0.3V_(max)。使用“肌肉机器人”非洲爪蟾脚来测试预测,该脚由活体外或计算机计算的足底长肌驱动。实验验证了预测。我们的主要发现是,GR的范围从11.5到20,接近划船的预测最佳值(GR≈11)。但是,齿轮比脚部区域对肌肉力量的影响更大。没有任何一种形态是产生肌肉力量的最佳选择。而是,“最佳” GR随脚的大小而减小,这意味着划船能力不必影响跳跃(反之亦然)。因此,尽管我们忽略了附加力(例如增加的质量),但我们的模型仍预测了生理和形态特性的配对以赋予有效的划船力。除了青蛙之外,该模型还可以应用于从水生昆虫到人力划船的各种大小和复杂性。

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