Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Entropy02:39

Entropy

34.9K
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...
34.9K
Entropy01:18

Entropy

3.5K
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...
3.5K
Entropy and Solvation02:05

Entropy and Solvation

8.2K
The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
8.2K
First Law Of Thermodynamics: Problem-Solving01:21

First Law Of Thermodynamics: Problem-Solving

3.8K
The first law of thermodynamics states that the change in internal energy of the system is equal to the net heat transfer into the system minus the net work done by the system. This equation is a generalized form of energy conservation and can be applied to any thermodynamic process.
The following strategies can be used to solve any problem involving the first law of thermodynamics.
3.8K
The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

6.6K
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
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

4.8K
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...
4.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Alternating copolymerization of l-lactide and ε-caprolactone <i>via</i> enantiomorphic site and chain-end synergistic control.

Chemical science·2026
Same author

Inferring cell-specific gene regulatory networks based on causal graph embedding.

Cell reports methods·2026
Same author

Resveratrol synergizes with chloroquine to inhibit the malignant progression of oral squamous cell carcinoma by regulating KIF11.

Naunyn-Schmiedeberg's archives of pharmacology·2026
Same author

Improved YOLOv11n-seg for impurity detection in mechanically harvested sugarcane.

Frontiers in plant science·2026
Same author

Sulfonate-Mediated Cation-Switching in Hydrogel Electrolytes to Unlock Fast Ion Transport for Low-Temperature Zinc Batteries.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Colonization of Mollisia sp. Su100, a novel root endophytic fungus, promoted Catalpa bungei growth under nitrogen deficiency by accumulating melatonin and remodeling fatty acid metabolism.

Tree physiology·2026

相关实验视频

Updated: Jan 17, 2026

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.6K

欧洲议员网络:通过最大的原则,为知识有限的科学问题产生解决方案.

Wuyue Yang1, Liangrong Peng2, Guojie Li3

  • 1Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China.

Chaos (Woodbury, N.Y.)
|September 24, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了MEP-Net,这是一个结合最大值原理 (MEP) 和神经网络的新型神经网络. MEP-Net有效地从时刻约束中生成概率分布,在复杂系统建模中非常有用.

更多相关视频

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

607
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

相关实验视频

Last Updated: Jan 17, 2026

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.6K
Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

607
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

科学领域:

  • 计算生物学 计算生物学
  • 统计物理 统计物理
  • 机器学习 机器学习

背景情况:

  • 最大值原理 (MEP) 是一个强大的工具,可以在不完整的信息下推断概率分布.
  • 神经网络擅长学习复杂的数据分布.
  • 整合这些方法可以增强概率模型.

研究的目的:

  • 提出一种新的神经网络架构,MEP-Net,它将最大值原理 (MEP) 与神经网络集成在一起.
  • 使用这种新架构,从时刻约束生成概率分布.
  • 在非平衡系统中为MEP提供理论基础.

主要方法:

  • 开发MEP-Net架构,将MEP和神经网络结合起来.
  • 使用大偏差原理对非平衡系统的MEP的数学表述和理论理由.
  • 数字实验验证 MEP-Net 的性能.

主要成果:

  • 展示MEP-Net能够从时刻约束中生成概率分布的能力.
  • 在建模生物化学反应网络中概率分布的演变中的成功应用.
  • 从数据中生成复杂分布的有效性.

结论:

  • MEP-Net提供了一种有效而公正的概率推理方法.
  • 该架构显示了计算生物学和复杂数据建模应用的重大前景.
  • 该理论框架支持MEP在非平衡统计物理学中的应用.