Jove
Visualize
联系我们

相关概念视频

What is Evolutionary History?02:35

What is Evolutionary History?

43.4K
Scientists record evolutionary history by analyzing fossil, morphological, and genetic data. The fossil record documents the history of life on Earth and provides evidence for evolution. However, both fossil and living organisms offer evidence that outlines Earth’s evolutionary history.
43.4K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

8.7K
Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
8.7K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

3.1K
3.1K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

7.4K
Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
7.4K
The Evidence for Evolution02:55

The Evidence for Evolution

48.2K
Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.
48.2K
Convergent Evolution01:54

Convergent Evolution

32.9K
Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
32.9K

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

Public goods games on any population structure.

Science advances·2026
Same author

Punishment in bipartite societies.

Chaos (Woodbury, N.Y.)·2026
Same author

Inter-role reciprocity in evolutionary trust game on square lattices.

Chaos (Woodbury, N.Y.)·2025
Same author

Evolutionary dynamics of any multiplayer game on regular graphs.

Nature communications·2024
Same author

Zealous cooperation does not always promote cooperation in public goods games.

Chaos (Woodbury, N.Y.)·2023
Same author

A simple epidemic model for semi-closed community reveals the hidden outbreak risk in nursing homes, prisons, and residential universities.

International journal of dynamics and control·2022
Same journal

Multiscale dynamics of special memristive ion channels in a neural circuit.

Chaos (Woodbury, N.Y.)·2026
Same journal

Symmetry-protected delay spectroscopy in oscillator networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Mesoscale community organization governs epidemic onset and spread in metapopulations.

Chaos (Woodbury, N.Y.)·2026
Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
查看所有相关文章
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

相关实验视频

Updated: Feb 4, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.6K

灾后资源再分配和合作的演变基于双层网络进化游戏.

Yu Chen1,2, Genjiu Xu1,3, Sinan Feng1,2

  • 1School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China.

Chaos (Woodbury, N.Y.)
|February 2, 2026
PubMed
概括
此摘要是机器生成的。

有效的灾后恢复需要理解庇护所-受害者合作. 这项研究模拟了这种相互作用,寻找适度的激励来促进合作,而有针对性的惩罚和校准的制裁是抵御能力的关键.

更多相关视频

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.4K
Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation
05:52

Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation

Published on: March 8, 2018

19.8K

相关实验视频

Last Updated: Feb 4, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.6K
WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
08:18

WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

Published on: August 15, 2020

5.4K
Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation
05:52

Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation

Published on: March 8, 2018

19.8K

科学领域:

  • 复杂系统科学 复杂系统科学
  • 灾害管理 灾害管理
  • 游戏理论的游戏理论.

背景情况:

  • 灾后恢复面临资源短缺和基础设施故障.
  • 庇护所和受害者之间的有效协调对于社区的性至关重要.
  • 灾难网络中双层行为反的动态尚未得到充分理解.

研究的目的:

  • 开发一个双层网络模型,用于庇护所与受害者的互动.
  • 分析激励和惩罚对合作的影响.
  • 评估加强灾后协调的战略.

主要方法:

  • 开发了一个双层网络模型,将资源再分配 (公共产品游戏) 和受害者互动 (进化游戏) 结合起来.
  • 在无尺度网络上使用蒙特卡洛模拟.
  • 使用来自北京的真实世界避难所数据验证了模型.

主要成果:

  • 适度的激励措施 (公共产品的提升,补贴) 促进合作;过度的激励措施导致自由行.
  • 可信的惩罚有效地减少了叛逃.
  • 对中央庇护所的有针对性的惩罚改善了在资源限制下的合作.

结论:

  • 校准的激励措施和可执行的制裁对于促进灾难恢复合作至关重要.
  • 关键实体的结构性向可以提高网络的弹性.
  • 该模型为改善灾后协调策略提供了实际见解.