Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Diversity of Protists IV

Diversity of Protists IV

Amoebozoa represent a diverse group of terrestrial and aquatic protists that utilize lobe-shaped pseudopodia for locomotion and feeding. This characteristic differentiates them from the Rhizaria, which possess threadlike pseudopodia. The primary classifications within Amoebozoa include gymnamoebas, entamoebas, and the plasmodial and cellular slime molds. Phylogenetic evidence indicates that Amoebozoa diverged from a lineage that ultimately gave rise to fungi and animals.Gymnamoebas and...

You might also read

Related Articles

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

Sort by

Same author

Na<b><sup>+</sup></b> Solvation and Association in Na(SO<sub>3</sub>CF<sub>3</sub>)-Dimethoxyethane Electrolytes by Large-Angle X-Ray Scattering and DFT Calculations.

The journal of physical chemistry. B·2026

Same author

Observation of the Structure and Dynamics of Water in Aqueous Alkaline Chloride Solutions under Gigapascal Pressure by Neutron Scattering.

The journal of physical chemistry letters·2026

Same author

Large language model assisted hyper-heuristic evolutionary algorithm for groundwater level prediction.

Scientific reports·2026

Same author

Mechanism of Mg<sup>2+</sup>-induced and ultrasound-assisted rapid synthesis of macallisterite: Raman, DFT, and morphology control.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2026

Same author

Cross-modal fusion of chemical language and physicochemical features enables accurate and interpretable multi-label odor prediction.

Journal of hazardous materials·2026

Same author

Structure and Crystallization Behavior of Aqueous K<sub>2</sub>SO<sub>4</sub>-MgSO<sub>4</sub> Solutions.

The journal of physical chemistry. B·2026

Search research articles

Related Experiment Video

Updated: Oct 1, 2025

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

Published on: December 5, 2016

DTSMA: Dominant Swarm with Adaptive T-distribution Mutation-based Slime Mould Algorithm.

Shihong Yin^1,2,3, Qifang Luo^1,2,3, Yanlian Du^4,5

¹College of Artificial Intelligence, Guangxi University for Nationalities, Nanning 530006, China.

Mathematical Biosciences and Engineering : MBE

|March 4, 2022

Summary

This summary is machine-generated.

This study introduces a novel slime mould algorithm (SMA) enhancement, the dominant swarm with adaptive t-distribution mutation (DTSMA), improving convergence and balancing exploration for better optimization results.

Keywords:

Slime mould algorithm engineering problems functions optimization metaheuristic optimization t-distribution mutation

More Related Videos

Evaluation of Motor Impairment in C. elegans Models of Amyotrophic Lateral Sclerosis

Evaluation of Motor Impairment in C. elegans Models of Amyotrophic Lateral Sclerosis

Published on: September 2, 2021

Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays

Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays

Published on: April 7, 2015

Related Experiment Videos

Last Updated: Oct 1, 2025

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

Published on: December 5, 2016

Evaluation of Motor Impairment in C. elegans Models of Amyotrophic Lateral Sclerosis

Evaluation of Motor Impairment in C. elegans Models of Amyotrophic Lateral Sclerosis

Published on: September 2, 2021

Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays

Preparation, Imaging, and Quantification of Bacterial Surface Motility Assays

Published on: April 7, 2015

Area of Science:

Computational Intelligence
Metaheuristic Optimization
Swarm Intelligence

Background:

The slime mould algorithm (SMA) is a recent metaheuristic inspired by slime mould behavior.
Existing SMA suffers from imbalanced exploration-exploitation and a tendency towards local optima.

Purpose of the Study:

To propose an improved slime mould algorithm (SMA) named DTSMA.
To enhance convergence speed, exploration-exploitation balance, and population diversity.

Main Methods:

Introduced dominant swarm for improved convergence speed.
Implemented adaptive t-distribution mutation for enhanced exploration-exploitation.
Integrated a new exploitation mechanism to increase population diversity.

Main Results:

DTSMA demonstrated superior performance on CEC2019 benchmark functions.
DTSMA achieved better results than SMA and other algorithms on engineering design problems.
DTSMA effectively solved the inverse kinematics problem for a 7-DOF robot manipulator.

Conclusions:

DTSMA shows significant improvements over the standard SMA.
The proposed DTSMA is a promising metaheuristic for global optimization challenges.
DTSMA offers enhanced optimization capabilities for complex problems.