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

Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

8.9K
Cooperative allosteric transitions can occur in multimeric proteins, where each subunit of the protein has its own ligand-binding site. When a ligand binds to any of these subunits, it triggers a conformational change that affects the binding sites in the other subunits; this can change the affinity of the other sites for their respective ligands. The ability of the protein to change the shape of its binding site is attributed to the presence of a mix of flexible and stable segments in the...
8.9K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

3.1K
3.1K
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

2.7K
2.7K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

7.4K
Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form...
7.4K
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

2.6K
2.6K
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

250
A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
250

You might also read

Related Articles

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

Sort by
Same author

Structure-function analysis of sodium caseinate-gum arabic-EGCG ternary complexes prepared via ultrasound-assisted glycation.

International journal of biological macromolecules·2026
Same author

Bayesian Networks and Causal Discovery.

Entropy (Basel, Switzerland)·2026
Same author

Quasi-Periodic Porous Structures-Based Temperature and Pressure Dual-Mode Electronic Skin for Material Cognition.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Machine learning-assisted dual-amplified visual platform based on fluorescent metal-organic framework and photonic crystals enables ATP detection for pathogen monitoring.

Biosensors & bioelectronics·2025
Same author

An improved greedy equivalent search method based on relative entropy.

Scientific reports·2025
Same author

Bridging Intuition and Data: A Unified Bayesian Framework for Optimizing Unmanned Aerial Vehicle Swarm Performance.

Entropy (Basel, Switzerland)·2025

Related Experiment Video

Updated: Feb 10, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.5K

A Cooperative Search and Coverage Algorithm with Controllable Revisit and Connectivity Maintenance for Multiple

Zhong Liu1, Xiaoguang Gao2, Xiaowei Fu3

  • 1School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China. 2011100490@mail.nwpu.edu.cn.

Sensors (Basel, Switzerland)
|May 9, 2018
PubMed
Summary
This summary is machine-generated.

This study presents a cooperative search algorithm for unmanned aerial vehicles (UAVs) to efficiently find targets in unknown areas. The algorithm minimizes search time and maximizes target discovery using cognitive maps and a revisit mechanism.

Keywords:
collision avoidanceconnectivity maintenancedigital pheromonedistributed receding horizon optimizingminimum spanning treemulti-UAVspotential fieldsearch and coverage

More Related Videos

Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation
16:23

Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation

Published on: May 23, 2017

11.8K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.5K

Related Experiment Videos

Last Updated: Feb 10, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.5K
Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation
16:23

Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation

Published on: May 23, 2017

11.8K
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.5K

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Environmental Monitoring

Background:

  • Cooperative search and coverage are critical for multi-Uobot systems in unknown environments.
  • Unmanned Aerial Vehicles (UAVs) face challenges with non-ideal sensors and limited communication ranges.
  • Efficiently minimizing search time while maximizing target detection is a key objective.

Purpose of the Study:

  • To develop a novel cooperative search and coverage algorithm for UAVs to minimize search time and maximize target discovery.
  • To introduce a controllable revisit mechanism for efficient exploration of high-probability or uncertain areas.
  • To design a distributed path planning algorithm ensuring collision avoidance and communication connectivity.

Main Methods:

  • Utilized cognitive maps, including target probability map (TPM), uncertain map (UM), and digital pheromone map (DPM), with a distributed update and fusion scheme.
  • Developed a controllable revisit mechanism based on the DPM to focus UAVs on promising sub-areas.
  • Implemented a distributed receding horizon optimizing path planning algorithm with potential fields for collision avoidance and connectivity maintenance.
  • Employed minimum spanning tree (MST) for topology optimization to balance coverage and connectivity.

Main Results:

  • The proposed algorithm demonstrated feasibility through comparative simulations, analyzing the impact of the revisit mechanism and connectivity scheme.
  • Monte Carlo simulations validated the influence of UAV number, sensing radius, detection/false alarm probabilities, and communication range.
  • The cognitive map fusion scheme ensured convergence to a unified environmental representation.

Conclusions:

  • The novel cooperative search and coverage algorithm effectively minimizes search time and enhances target detection for UAVs.
  • The controllable revisit mechanism and MST-based connectivity strategy significantly improve search efficiency and system performance.
  • The algorithm's robustness was confirmed across various parameters, highlighting its practical applicability in real-world scenarios.