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相关概念视频

Entropy02:39

Entropy

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Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

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In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
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Third Law of Thermodynamics02:38

Third Law of Thermodynamics

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A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
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The Second Law of Thermodynamics01:14

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In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
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Entropy and the Second Law of Thermodynamics01:20

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The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
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Entropy within the Cell01:22

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A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that...
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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在动态复杂网络中最大的.

Noam Abadi1, Franco Ruzzenenti1

  • 1Integrated Research on Energy, Environment and Society, Faculty of Science and Engineering, <a href="https://ror.org/012p63287">University of Groningen</a>, Groningen, Netherlands.

Physical review. E
|December 18, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的信息理论方法,用于动态复杂网络,超越固定模型. 最大口径方法准确地描述了网络演变,与随机模拟和既定原则保持一致.

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科学领域:

  • 复杂的网络 复杂的网络
  • 网络科学 网络科学
  • 信息理论 信息理论

背景情况:

  • 复杂网络分析交互系统,经常使用随机化来理解属性.
  • 现有的信息理论随机化方法仅限于静止网络描述.
  • 动态网络的随机随机化方法缺乏一般的理论基础.

研究的目的:

  • 扩展用于分析动态复杂网络模型的信息理论方法.
  • 使用最大口径原理构建动态网络集合分布.
  • 为了对这些分布与随机随机化模拟进行验证.

主要方法:

  • 运用信息理论原理的最大口径来构建动态网络集.
  • 在整个网络演变过程中使用了代表已知的统计属性的约束 (例如,平均程度).
  • 将最大口径分布与在相同约束条件下的随机化模拟进行比较.

主要成果:

  • 从模拟中得出的集合分布与使用最大口径原理计算的分布非常相匹配.
  • 收的平衡分布与给定约束的已确定的最大值结果一致.
  • 证明了超越固定模型的最大口径对动态网络分析的有效性.

结论:

  • 最大口径原理为动态复杂网络的信息理论分析提供了坚实的框架.
  • 这种方法弥合了静态信息理论方法和动态随机过程之间的差距.
  • 未来的研究可以探索与最大和其他网络动态方法的进一步联系.