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

Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

61
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
61
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

540
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
540
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.1K
Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
16.1K
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

4.3K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
4.3K
Design Example: Measuring Distance Between Two Points with Obstructions01:10

Design Example: Measuring Distance Between Two Points with Obstructions

44
When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
44
Outliers and Influential Points01:08

Outliers and Influential Points

4.1K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
4.1K

You might also read

Related Articles

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

Sort by
Same author

State-of-the-Art Biosensors in China.

Biosensors·2026
Same author

Spatial distribution of the proteome in the human body and in cancers.

Nature·2026
Same author

Intelligent label-free droplet microfluidic sorting system for single-cell encapsulation and morphology-guided screening.

Microsystems & nanoengineering·2026
Same author

Flexible Wearable Closed-Loop Diagnostic and Therapeutic System: A New Paradigm for Skin Health Management.

ACS sensors·2026
Same author

Decoding coral resistance to eutrophication through the association of hyper‑efficient denitrifiers as key microbial allies.

Nature communications·2026
Same author

Changes in vitamin C, vitamin E, and carotenoid metabolism during early kernel development in maize.

Journal of the science of food and agriculture·2026

Related Experiment Video

Updated: Jul 14, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.1K

Estimation and update of betweenness centrality with progressive algorithm and shortest paths approximation.

Nan Xiang1,2,3, Qilin Wang4, Mingwei You4

  • 1Liangjiang International College, Chongqing University of Technology, Chongqing, 401135, China. xiangnan@cqut.edu.cn.

Scientific Reports
|October 10, 2023
PubMed
Summary

Calculating node importance in large networks is hard. Our Centroids based Betweenness Centrality Approximation (CBCA) algorithm offers an efficient solution for approximating betweenness centrality in complex networks.

More Related Videos

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

590
Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
08:43

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Published on: August 7, 2017

7.9K

Related Experiment Videos

Last Updated: Jul 14, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.1K
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

590
Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment
08:43

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Published on: August 7, 2017

7.9K

Area of Science:

  • Network Science
  • Graph Theory
  • Computational Complexity

Background:

  • Betweenness centrality is crucial for identifying important nodes in networks.
  • Exact calculation of betweenness centrality is computationally infeasible for large-scale networks.

Purpose of the Study:

  • To develop an efficient algorithm for approximating betweenness centrality in large networks.
  • To address the computational intractability of exact betweenness centrality calculations.

Main Methods:

  • Developed the Centroids based Betweenness Centrality Approximation (CBCA) algorithm.
  • Employed progressive sampling and shortest path approximation using network centroids.
  • Utilized Monte Carlo Empirical Rademacher averages for error estimation and sample size determination.
  • Introduced a novel centroid updating strategy considering network density and clustering coefficient for dynamic networks.

Main Results:

  • The CBCA algorithm efficiently provides high-quality approximations of betweenness centrality.
  • Demonstrated effectiveness in large-scale complex networks.
  • Successfully balanced accuracy and computational efficiency.

Conclusions:

  • The CBCA algorithm is an effective and efficient method for approximating betweenness centrality in large networks.
  • The proposed techniques improve scalability and handle dynamic network changes.