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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
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Linearization and Approximation01:26

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Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...
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A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
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在主节点网络模型中的回火近似值.

M O Hase1, Anderson A Ferreira2, André C R Martins1

  • 1University of São Paulo, School of Arts, Sciences, and Humanities, São Paulo, SP 03828-000, Brazil.

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概括
此摘要是机器生成的。

本研究使用主节点网络模型探讨了意见动态,揭示了不对称的社会影响 (人性) 如何通过阶段过渡推动系统走向共识或两极分化.

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科学领域:

  • 复杂的系统复杂的系统.
  • 统计物理 统计物理
  • 社会动力学 社会动力学

背景情况:

  • 意见动态模型往往简化了社会影响.
  • 了解阶段过渡是集体行为的关键.
  • 奇拉性 (非对称影响) 是形成意见的一个研究不足的因素.

研究的目的:

  • 调查意见动态中的吸收状态阶段过渡.
  • 分析性参数 (R和L) 在网络相互作用中的作用.
  • 开发一个理论框架意见的趋同和分歧.

主要方法:

  • 使用主节点网络模型.
  • 在分析中使用了回火近似方法.
  • 研究了三种基本制度:分歧,共识和混合结果.

主要成果:

  • 确定了无序和有序相之间的连续和不连续相位过渡.
  • 证明了性参数控制相位行为.
  • 在有两个吸收状态的系统中观察到不连续的过渡,取决于初始条件.

结论:

  • 非对称的社会影响 (人性) 是形成意见的关键对称性破坏因素.
  • 该模型解释了网络如何导致两极分化或共识.
  • 在具有多个吸收状态的系统中,初始条件极大地影响最终状态.