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

Real-World Application of Classical Conditioning01:15

Real-World Application of Classical Conditioning

627
Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
627
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

383
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
383
Prediction Intervals01:03

Prediction Intervals

2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.3K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

3.1K
3.1K
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

8.5K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.5K
Local Attraction01:22

Local Attraction

89
Local attraction refers to disturbances in compass readings caused by magnetic influences from nearby objects such as metal fences, buried pipes, vehicles, buildings, power lines, or natural iron ore deposits. Small items like wristwatches, steel tools, or belt buckles can also interfere with the compass by creating local magnetic fields that distort the Earth's natural magnetic field. These distortions lead to inaccurate readings, posing navigation and land surveying challenges.Local...
89

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

AGCLD: an adaptive graph contrastive learning method with denoising for spatial domain identification.

Briefings in bioinformatics·2026
Same author

A Multi-Branch Training Strategy for Enhancing Neighborhood Signals in GNNs for Community Detection.

Entropy (Basel, Switzerland)·2026
Same author

Rumor source localization in social networks based on the propagation direction of observers.

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

The Synergistic Effects of Structural Evolution and Attack Strategies on Network Matching Robustness.

Entropy (Basel, Switzerland)·2025
Same author

A generalized simplicial model and its application.

Chaos (Woodbury, N.Y.)·2024
Same author

Network Higher-Order Structure Dismantling.

Entropy (Basel, Switzerland)·2024

相关实验视频

Updated: Jul 20, 2025

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K

通过本地信息进行更高阶链接预测.

Bo Liu1,2, Rongmei Yang1, Linyuan Lü1,2,3

  • 1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, People's Republic of China.

Chaos (Woodbury, N.Y.)
|August 3, 2023
PubMed
概括

本研究引入了两种新方法,即简化分解权重和封闭比重,用于预测复杂网络中未来的高阶相互作用. 这些基于局部特征的方法在高阶链接预测方面优于现有的基准标准.

更多相关视频

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.7K

相关实验视频

Last Updated: Jul 20, 2025

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K
A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

68.7K

科学领域:

  • 网络科学 网络科学
  • 复杂系统分析 复杂系统分析
  • 数据挖掘 数据挖掘

背景情况:

  • 高级链接预测对于准确建模复杂系统至关重要.
  • 传统的对联网络缺乏高级网络的细节.
  • 由于网络的复杂性,预测更高层次的链接具有挑战性.

研究的目的:

  • 利用本地特征开发高效简洁的高阶链接预测算法.
  • 引入新的相似度指标,用于预测未来的高阶相互作用 (simples) 在simplicial网络.

主要方法:

  • 提出了两个相似度指标:简单分解重量和闭合比重量.
  • 这些指标通过简单分解和集群状态捕获本地更高阶信息.
  • 评估了八个实证简化网络的性能.

主要成果:

  • 拟议的指标在预测第三级和第四级相互作用方面优于现有基准.
  • 这些算法在各种训练集大小中展示了强大的性能.
  • 当地特征对于更高层次的链接预测是有利的.

结论:

  • 新的指标为更高阶链接预测提供了一种有效的方法.
  • 这些发现凸显了局部特征在复杂网络分析中的重要性.
  • 拟议的算法为未来网络科学研究提供了一个有希望的方向.