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

Social Exchange Theory02:06

Social Exchange Theory

34.5K
We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
34.5K
Flame Photometry: Overview01:02

Flame Photometry: Overview

612
Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
612
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
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.5K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.5K
Optimal Foraging00:48

Optimal Foraging

12.1K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
12.1K
Determination of Michaelis Constant and Maximum Elimination Rate01:20

Determination of Michaelis Constant and Maximum Elimination Rate

115
The Michaelis constant (KM) and the theoretical maximum process rate (Vmax) are vital parameters in the Michaelis-Menten equation, central to many biochemical reactions. They provide essential insights into enzyme kinetics and drug metabolism.
These parameters can be estimated by analyzing plasma concentration data post-drug administration. A notable example of this application is phenytoin, a drug with capacity-limited kinetics. It's recommended that phenytoin should be administered at two...
115

You might also read

Related Articles

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

Sort by
Same author

Effect of Medicaid coverage of tobacco-dependence treatments on smoking cessation.

International journal of environmental research and public health·2010
Same author

Cytokine and autoantibody patterns in acute liver failure.

Journal of immunotoxicology·2009
Same author

A novel scoring system for prognostic prediction in d-galactosamine/lipopolysaccharide-induced fulminant hepatic failure BALB/c mice.

BMC gastroenterology·2009
Same author

Mammalian target of rapamycin signaling pathway contributes to glioma progression and patients' prognosis.

The Journal of surgical research·2009
Same author

Estrogen receptor neurobiology and its potential for translation into broad spectrum therapeutics for CNS disorders.

Current molecular pharmacology·2009
Same author

Transcriptional and post-translational regulation of adiponectin.

The Biochemical journal·2009
Same journal

Novel Parent Survey Measures Sensory Behaviors Incorporating Sensory Modality and Stimulus Intensity.

Heliyon·2026
Same journal

Expression of concern: "SQSTM1/p62 promotes the progression of gastric cancer through epithelial-mesenchymal transition" [Heliyon 10 (2024) e24409].

Heliyon·2026
Same journal

Expression of concern: "TL1A promotes metastasis and EMT process of colorectal cancer" [Heliyon 10 (2024) e24392].

Heliyon·2026
Same journal

Expression of concern: "Factors affecting timing of surgery following neoadjuvant chemoradiation for esophageal cancer" [Heliyon 9 (2023) e23212].

Heliyon·2026
Same journal

Expression of concern: "On stratified single-valued soft topogenous structures" [Heliyon 10 (2024) e27926].

Heliyon·2026
Same journal

Expression of concern: "Artifact removal and motor imagery classification in EEG using advanced algorithms and modified DNN" [Heliyon 10 (2024) e27198].

Heliyon·2026
See all related articles

Related Experiment Video

Updated: Jul 9, 2025

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations
14:33

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Published on: October 1, 2013

14.4K

A new technique for influence maximization on social networks using a moth-flame optimization algorithm.

Qi Cui1, Feng Liu1

  • 1The College of Economics and Management, Shenyang Agricultural University, Shenyang, 111000, LiaoNing, China.

Heliyon
|December 7, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new Moth-Flame Optimization Algorithm (MFA) to solve the NP-hard influence maximization problem in social networks. The MFA approach efficiently identifies key influencers, improving accuracy and reducing execution time.

Keywords:
GraphMaximum influenceMoth-flame algorithmSocial network

More Related Videos

Flame Experiments at the Advanced Light Source: New Insights into Soot Formation Processes
10:04

Flame Experiments at the Advanced Light Source: New Insights into Soot Formation Processes

Published on: May 26, 2014

12.9K
Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames
10:29

Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames

Published on: June 1, 2016

11.8K

Related Experiment Videos

Last Updated: Jul 9, 2025

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations
14:33

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Published on: October 1, 2013

14.4K
Flame Experiments at the Advanced Light Source: New Insights into Soot Formation Processes
10:04

Flame Experiments at the Advanced Light Source: New Insights into Soot Formation Processes

Published on: May 26, 2014

12.9K
Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames
10:29

Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames

Published on: June 1, 2016

11.8K

Area of Science:

  • Computer Science
  • Network Analysis
  • Artificial Intelligence

Background:

  • Social networks are integral to modern communication and information dissemination across various sectors.
  • Influence maximization is crucial for targeted outreach but is an NP-hard problem.
  • Identifying key influencers is vital for efficient information spread and resource allocation.

Purpose of the Study:

  • To propose a novel method for influence maximization in social networks.
  • To leverage the Moth-Flame Optimization Algorithm (MFA) for enhanced influence maximization.
  • To identify potential influencers within a network graph with improved accuracy and efficiency.

Main Methods:

  • The study employs the Moth-Flame Optimization Algorithm (MFA) to address the influence maximization problem.
  • A new method is presented to find maximum influence by selecting optimal vertices in a social network graph.
  • The MFA approach, termed Maximal First Activation, is utilized to approximate maximum influence.

Main Results:

  • The proposed MFA-based method demonstrates superior performance and scalability for influence maximization.
  • Simulations show the MFA approach significantly reduces execution time for influence approximation.
  • The technique achieved a 3.140% improvement in accuracy and a 12.2% improvement in execution time compared to existing methods.

Conclusions:

  • The Moth-Flame Optimization Algorithm (MFA) offers a highly effective and scalable solution to the influence maximization problem.
  • The MFA approach enhances both the accuracy and efficiency of identifying key influencers in social networks.
  • This research provides a valuable tool for businesses and researchers seeking to optimize information dissemination strategies.