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arXiv 2509.03418cond-mat.softnlin.AOphysics.bio-ph
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跨尺度控制:信号、信息与适应性生物力学功能

Control across scales: signals, information, and adaptive biological mechanical function

James Clarke, Jake McGrath, Colin Johnson, José Alvarado

AI总结:

本研究指出物理定律不足以完全解释生物系统的感知、决策与适应等控制行为,提出控制理论可作为统一框架,用于理解生物系统在多时空尺度下远离平衡时的动力学调节与稳定性维持机制。

摘要:

生物系统执行着种类惊人的动态过程——包括发育与修复、调节、行为与运动控制、感知与信号传导以及适应等。这些行为由储存能量的转导提供动力,使生物系统能够调节功能、实现特定结果,并在远离热力学平衡的状态下维持稳定性。这些行为在长度和时间上跨越多个数量级:从驱动形态发生的纳米级分子马达,到千米级的季节性迁徙;从毫秒级的反射,到数千年的进化适应。虽然物理定律支配着生物系统的动力学,但仅凭物理定律不足以完全解释生命系统如何感知、决策、适应并最终控制自身的动力学。在本文中,我们提出控制理论提供了一个强大的统一框架,可用于理解生物系统如何调节动力学,以在远离平衡的长度和时间尺度上维持稳定性。

英文摘要:

Biological systems perform an astonishing array of dynamical processes -- including development and repair, regulation, behavior and motor control, sensing and signaling, and adaptation, among others. Powered by the transduction of stored energy resources, these behaviors enable biological systems to regulate functions, achieve specific outcomes, and maintain stability far from thermodynamic equilibrium. These behaviors span orders of magnitude in length and time: from nanometer-scale molecular motors driving morphogenesis to kilometer-scale seasonal migrations, and from millisecond reflexes to millennia of evolutionary adaptations. While physical laws govern the dynamics of biological systems, they alone are insufficient to fully explain how living systems sense, decide, adapt, and, ultimately, control their dynamics. In this article, we argue that control theory provides a powerful, unifying framework for understanding how biological systems regulate dynamics to maintain stability across length and time scales far from equilibrium.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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