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

Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

2.6K
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.
2.6K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

58.5K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
58.5K
Speciation Rates01:07

Speciation Rates

21.2K
Overview
21.2K
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

421
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
421
Stability of Equilibrium Configuration01:23

Stability of Equilibrium Configuration

470
Understanding the stability of equilibrium configurations is a fundamental part of mechanical engineering. In any system, there are three distinct types of equilibrium: stable, neutral, and unstable.
A stable equilibrium occurs when a system tends to return to its original position when given a small displacement, and the potential energy is at its minimum. An example of a stable equilibrium is when a cantilever beam is fixed at one end and a weight is attached to the other end. If the weight...
470
Stability of Equilibrium Configuration: Problem Solving01:13

Stability of Equilibrium Configuration: Problem Solving

623
The stability of equilibrium configurations is an important concept in physics, engineering, and other related fields. In simple terms, it refers to the tendency of an object or system to return to its equilibrium position after being disturbed. The stability of an equilibrium configuration can be analyzed by considering the potential energy function of the system and examining its behavior near the equilibrium point.
Problem-solving in the context of the stability of equilibrium configuration...
623

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

Using covariance of node states to design early warning signals for network dynamics.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same author

Temporality modulates the effect of network heterogeneity on cooperation fixation.

Nature communications·2026
Same author

Detecting and forecasting tipping points from sample variance alone.

PNAS nexus·2026
Same author

Non-dilemmatic social dynamics promote cooperation in multilayer networks.

ArXiv·2026
Same author

Genomes from 117 vertebrate species reveal rapidly evolving segmental duplication landscapes.

bioRxiv : the preprint server for biology·2025
Same author

Observing network dynamics through sentinel nodes.

Nature communications·2025

相关实验视频

Updated: Jul 15, 2025

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

14.4K

在转换时间网络上的进化动态中的固定概率.

Jnanajyoti Bhaumik1, Naoki Masuda2,3,4

  • 1Department of Mathematics, State University of New York at Buffalo, Buffalo, NY, 14260-2900, USA.

Journal of mathematical biology
|September 28, 2023
PubMed
概括
此摘要是机器生成的。

时间网络可以抑制选择,与静态网络不同. 大多数小型交换网络都起到抑制作用,为进化动态和人口结构提供了新的见解.

关键词:
莫兰工艺 莫兰工艺时间网络是时间网络.出生至死亡的过程.进化的动态 进化的动态进化图形理论的演化图形理论.

更多相关视频

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

998

相关实验视频

Last Updated: Jul 15, 2025

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
16:23

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Published on: February 26, 2014

14.4K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

998

科学领域:

  • 进化的动力学.
  • 网络理论 网络理论
  • 数学生物学的数学生物学

背景情况:

  • 人口结构显著影响进化轨迹.
  • 选择放大剂促进更适合的突变,而抑制剂则抑制它们.
  • 在标准进化条件下,静态网络主要是放大器.

研究的目的:

  • 研究时间 (时间变化) 网络在进化动态中的作用.
  • 将选择放大器和抑制器的理解扩展到动态网络结构.
  • 分析在出生-死亡过程中切换时间网络的行为.

主要方法:

  • 利用出生死亡过程扩展到切换时间网络.
  • 分析那些在两个静态结构之间决定性或随机交替的网络.
  • 专注于小型网络 (六个节点或更少) 进行详细分析.

主要成果:

  • 切换时间网络的放大效果通常不如它们所组成的静态网络.
  • 大多数小型交换网络都表现出抑制特性,与静态网络形成鲜明对比.
  • 这一发现挑战了标准进化网络模型中扩大器的广泛假设.

结论:

  • 切换时间网络可以作为选择的抑制剂,特别是在较小的系统中.
  • 时间网络的动态引入了在静态网络中没有观察到的新型进化行为.
  • 对时间网络结构的进一步研究对于全面了解进化至关重要.