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相关概念视频

Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

4.7K
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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Entropy01:18

Entropy

3.4K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
3.4K
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...
34.7K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.2K
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.
3.2K
The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

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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...
6.6K
Gibbs Free Energy02:39

Gibbs Free Energy

37.8K
One of the challenges of using the second law of thermodynamics to determine if a process is spontaneous is that it requires measurements of the entropy change for the system and the entropy change for the surroundings. An alternative approach involving a new thermodynamic property defined in terms of system properties only was introduced in the late nineteenth century by American mathematician Josiah Willard Gibbs. This new property is called the Gibbs free energy (G) (or simply the free...
37.8K

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相关实验视频

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Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions
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Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions

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对于有限数据的转移.

Alec Kirkley1

  • 1University of Hong Kong, University of Hong Kong, University of Hong Kong, Institute of Data Science, Hong Kong SAR, China; Department of Urban Planning and Design, Hong Kong SAR, China; and Urban Systems Institute, Hong Kong SAR, China.

Physical review. E
|December 23, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了对离散数据的新转移度,克服了小或高卡丁度时间序列分析中的偏差和显著性问题. 它可以在没有模拟的情况下进行可靠的信息流评估.

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Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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相关实验视频

Last Updated: Jan 8, 2026

Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions
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Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions

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Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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科学领域:

  • 复杂系统分析 复杂系统分析
  • 信息理论是信息理论.
  • 时间序列分析时间序列分析.

背景情况:

  • 转移量化了定向的信息流,但面临着连续数据的挑战.
  • 对于离散数据,它遭受了稀疏计数的积极偏差,缺乏统计学意义评估.
  • 现有的方法在有限的数据流中扎,这些数据流的大小小小或核心值很高.

研究的目的:

  • 为有限的离散数据流开发一种新的传输测量方法.
  • 解决现有估计器的局限性,特别是偏差和缺乏意义测试.
  • 为了使非参数统计学显著性评估,而不依赖于模拟.

主要方法:

  • 通过计算有限数据流中的信息内容,推导出一种新的传输度.
  • 避免明确考虑符号作为随机变量.
  • 确保了对标准插件估计器的非对称性.

主要成果:

  • 新的测量方法在异面上相当于标准的插件估计器.
  • 它有效地纠正了与稀疏垃圾箱计数相关的积极偏见问题.
  • 它允许对有限时间序列的统计显著性的完全非参数评估.
  • 该方法适用于小尺寸和/或高枢纽度的时间序列.

结论:

  • 拟议的转移量为分析离散的有限数据中的信息流提供了可靠的解决方案.
  • 它克服了传统方法的关键局限性,提高了可靠性和可解释性.
  • 允许在复杂系统中对指导信息传输进行严格的统计验证.