Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

139
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
139
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

4.1K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.1K
Decision Making01:20

Decision Making

179
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
179
Decision Making: P-value Method01:09

Decision Making: P-value Method

5.6K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.6K
Structural Classification of Joints01:20

Structural Classification of Joints

3.8K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
3.8K
Functional Classification of Joints01:09

Functional Classification of Joints

4.4K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
4.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Unifying network connectivity from geodesics to random walks via the random cluster model.

Nature communications·2026
Same author

Colonoscope-derived mucus as a novel high-fidelity reservoir for KRAS-mutated precancerous colorectal neoplasia detection.

Translational oncology·2026
Same author

Switching exploration modes in human mobility.

Journal of the Royal Society, Interface·2026
Same author

Persistent collaboration as a structural signature of scientific resilience.

PNAS nexus·2026
Same author

A scalable and generic framework for city-wide traffic prediction with large language model.

Nature communications·2026
Same author

Malignancy risk and management outcomes in adult intussusception: a single-institution retrospective study.

European journal of trauma and emergency surgery : official publication of the European Trauma Society·2026
Same journal

Correction: A method for supervoxel-wise association studies of age and other non-imaging variables from coronary computed tomography angiograms.

Scientific reports·2026
Same journal

Poly(bromophenol blue)/CoSn(OH)<sub>6</sub> cubic particles modified pencil graphite electrode for electrochemical determination of diphenhydramine.

Scientific reports·2026
Same journal

Dietary Chlorella, Spirulina, and acidifier modulate jejunal cytokine-related gene expression in broiler chickens.

Scientific reports·2026
Same journal

Perceived physical activity barriers in university students: associations with fatigue and eating behaviours.

Scientific reports·2026
Same journal

Refuge limitation structures habitat use in agricultural landscapes: evidence from Sunda pangolins.

Scientific reports·2026
Same journal

Lightweight stateless transaction verification with outsourced witness updates for UTXO blockchains.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Aug 22, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.4K

An influential node identification method considering multi-attribute decision fusion and dependency.

Chao-Yang Chen1,2, Dingrong Tan3, Xiangyi Meng4

  • 1School of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan, 411201, People's Republic of China. ouzk@163.com.

Scientific Reports
|November 14, 2022
PubMed
Summary
This summary is machine-generated.

We developed a new method to measure node influence in interdependent networks, improving the understanding of cascading failures and system reliability. This approach enhances the robustness of critical infrastructure systems.

More Related Videos

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
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

11.9K

Related Experiment Videos

Last Updated: Aug 22, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.4K
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
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
14:38

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

11.9K

Area of Science:

  • Network Science
  • Complex Systems
  • Systems Engineering

Background:

  • Interdependent networks are crucial for modern systems.
  • Understanding network robustness is key to reliability.
  • Cascading failures pose significant risks to these systems.

Purpose of the Study:

  • To investigate the robustness and centrality of interdependent networks.
  • To model cascading failures using a nonlinear load-capacity model.
  • To develop a more realistic load distribution based on node influence.

Main Methods:

  • Utilized an automated entropy-weighted multi-attribute algorithm to measure node influence.
  • Considered node centrality and interdependencies for influence calculation.
  • Analyzed nearest and next-nearest neighbors' influence.
  • Investigated network resilience under varying parameters and coupling strengths.

Main Results:

  • Node influence is determined by a comprehensive algorithm, not random distribution.
  • Network resilience is significantly affected by node influence and coupling.
  • The study provides a more accurate assessment of interdependent system reliability.

Conclusions:

  • The proposed model offers a more practical and accurate approach to studying interdependent networks.
  • Findings aid in better monitoring and managing complex interdependent systems.
  • This research contributes to building more robust and reliable networked systems.