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

Complex Power01:14

Complex Power

933
Power engineers have introduced the concept of complex power to determine the cumulative effect of parallel loads. This idea plays a crucial role in power analysis because it encompasses all the details related to the power consumed by a specific load.
Complex power is defined as the multiplication of the voltage and the complex conjugate of the current. The magnitude of this power, known as apparent power, is measured in volt-amperes (VA). Notably, the angle of the complex power equates to the...
933
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Power01:08

Power

13.1K
The concept of work involves force and displacement; meanwhile, the work-energy theorem relates the net work done on a body to the difference in its kinetic energy, calculated between two points on its trajectory. While none of these quantities or relations involves time explicitly, we know that the time available to accomplish work is often just as important as the amount of work itself. For example, sprinters in a race may have achieved the same velocity at the finish, therefore,...
13.1K
Network Covalent Solids02:18

Network Covalent Solids

16.2K
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
16.2K
Sums of Power01:22

Sums of Power

80
In definite integration, Riemann sums approximate the area under a curve by dividing it into subintervals and summing the areas of rectangles. When these approximations follow predictable numerical patterns, such as arithmetic or polynomial sequences, sum formulas offer a more efficient and accurate way to compute the result. In particular, the sum of consecutive integers, squares, and cubes plays an essential role in simplifying these calculations, especially when dealing with uniform...
80
Instantaneous Power01:22

Instantaneous Power

938
Instantaneous power is important in electrical circuits, mainly when dealing with sinusoidal input. Instantaneous power, denoted as p(t), results from the multiplication of the instantaneous voltage (v(t)) across an element and the instantaneous current (i(t)) flowing through it. This relationship adheres to the passive sign convention and represents a fundamental principle in electrical engineering.
938

You might also read

Related Articles

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

Sort by
Same author

A complex network-based approach to detect and investigate connectome motifs in the larval Drosophila.

Computers in biology and medicine·2025
Same author

Investigating the COVID-19 vaccine discussions on Twitter through a multilayer network-based approach.

Information processing & management·2022
Same author

A machine learning based sentient multimedia framework to increase safety at work.

Multimedia tools and applications·2021
Same author

Integrative bioinformatics and omics data source interoperability in the next-generation sequencing era-Editorial.

Briefings in bioinformatics·2021
Same author

Prediction of Multiple Sclerosis Patient Disability from Structural Connectivity using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2020
Same author

Leveraging network analysis to support experts in their analyses of subjects with MCI and AD.

Medical & biological engineering & computing·2019
Same journal

Metabolically Faithful 3D PET Restoration via Volumetric Swin Transformers.

Neuroinformatics·2026
Same journal

CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training.

Neuroinformatics·2026
Same journal

Increasing the Reliability of Functional Connectivity by Predicting Long-Scan Functional Connectivity based on Short-Scan Functional Connectivity: Model Exploration, Explanation, Validation, and Application.

Neuroinformatics·2026
Same journal

HESREN: A Derivative-Informed Reservoir Framework for Detecting Transient Neural Events and Windowless Estimation of Dynamic Functional Connectivity.

Neuroinformatics·2026
Same journal

Computational Morphometry of Peripheral Nerves: A Pipeline Perspective on Reproducibility and Generalization.

Neuroinformatics·2026
Same journal

Multimodal Branched Transport Infers Anatomically Aligned Brain Reaction Maps.

Neuroinformatics·2026
See all related articles

Related Experiment Video

Updated: Feb 14, 2026

Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila
07:13

Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila

Published on: January 7, 2019

14.7K

A Complex Network-Based Approach for Detecting and Characterizing Power Neurons in Drosophila

Enrico Corradini1, Federica Parlapiano1, Giorgio Terracina2

  • 1DII, Polytechnic University of Marche, Ancona, Italy.

Neuroinformatics
|February 13, 2026
PubMed
Summary

No abstract available in PubMed .

Keywords:
Complex network analysisConnectomeConnectome motifsDrosophila melanogasterNeuron backbonePower neurons

More Related Videos

An in vivo Crosslinking Approach to Isolate Protein Complexes From Drosophila Embryos
08:51

An in vivo Crosslinking Approach to Isolate Protein Complexes From Drosophila Embryos

Published on: April 23, 2014

17.6K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.1K

Related Experiment Videos

Last Updated: Feb 14, 2026

Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila
07:13

Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila

Published on: January 7, 2019

14.7K
An in vivo Crosslinking Approach to Isolate Protein Complexes From Drosophila Embryos
08:51

An in vivo Crosslinking Approach to Isolate Protein Complexes From Drosophila Embryos

Published on: April 23, 2014

17.6K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.1K