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Related Concept Videos

Hierarchy of Motor Control01:18

Hierarchy of Motor Control

The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Circuit Terminology01:14

Circuit Terminology

An electrical network is a system composed of interconnected elements, such as resistors, capacitors, inductors, and voltage or current sources. Unlike a circuit, an electrical network does not necessarily form a closed path. In other words, while all circuits can be considered networks due to their interconnected nature, not every network qualifies as a circuit.
A circuit, on the other hand, is also an interconnected system of electrical elements but must contain one or more closed paths.
Protein Networks02:26

Protein Networks

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Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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Directing Effect of Substituents: meta-Directing Groups01:09

Directing Effect of Substituents: meta-Directing Groups

Substituents on the benzene ring that direct an incoming electrophile to undergo substitution at the meta position are called meta directors. All meta directors either have a positive charge on the atom directly bonded to the ring or a partial positive charge. These groups function by withdrawing electrons from the ring through inductive and resonance effects. Consider the carbocation intermediates formed upon the addition of an electrophile on nitrobenzene at the ortho, meta, and para...

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Related Experiment Video

Updated: May 13, 2026

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

Hierarchy in directed random networks.

Enys Mones1

  • 1Department of Biological Physics, Eötvös Loránd University, Pázmány Péter Sétány 1/A, H-1117 Budapest, Hungary. enys@hal.elte.hu

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|March 19, 2013
PubMed
Summary
This summary is machine-generated.

Complex network hierarchy is influenced by correlations. Optimal hierarchy levels exist, differing between networks with and without giant components, and are affected by one-point correlations.

Related Experiment Videos

Last Updated: May 13, 2026

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

Area of Science:

  • Complex systems science
  • Network theory
  • Statistical physics

Background:

  • Real-world systems (social, biological) exhibit complex interaction structures.
  • Network analysis is crucial for understanding system properties.
  • Hierarchy is a key characteristic of complex networks.

Purpose of the Study:

  • To analyze hierarchical properties of random network models.
  • To investigate the impact of correlations on network hierarchy.
  • To determine how different correlation types affect hierarchical structure.

Main Methods:

  • Qualitative analytical results for random networks with zero correlations.
  • Numerical investigations of network models with varying correlations.
  • Analysis of network hierarchy in the presence and absence of giant components.

Main Results:

  • Network hierarchy differs significantly with and without giant components.
  • One-point correlations drastically alter hierarchical structure.
  • Hierarchy does not monotonically change with correlations; an optimum exists.

Conclusions:

  • Correlations play a critical role in shaping network hierarchy.
  • The presence of correlations, especially one-point correlations, can fundamentally change network structure.
  • An optimal level of correlation exists for maximizing network hierarchy.