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Related Concept Videos

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.
Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
Anchoring Junctions01:03

Anchoring Junctions

Anchoring junctions are multiprotein complexes that help cells connect to other cells and the extracellular matrix. Anchoring junctions are present on the lateral and basal surfaces of cells, providing strong and flexible connections. Focal adhesions are often formed due to cell interactions with the ECM substrata, which initiate signal transduction via kinase cascades and other mechanisms. Together, they provide stability and tissue integrity. There are three types of anchoring junctions:...
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.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Mesh Analysis01:20

Mesh Analysis

Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...
Network Covalent Solids02:18

Network Covalent Solids

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...

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Related Experiment Video

Updated: May 30, 2026

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling
06:55

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling

Published on: August 5, 2016

Characterization of spatial networklike patterns from junction geometry.

Andrea Perna1, Pascale Kuntz, Stéphane Douady

  • 1Institut des Systèmes Complexes Paris Île-de France, 57-59 rue Lhomond, F-75005 Paris, France.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|July 30, 2011
PubMed
Summary
This summary is machine-generated.

We developed a new method to analyze spatial networks like leaf veins and street patterns. It uses junction angles to distinguish between globally organized hierarchical networks and locally organized homogeneous networks.

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Modeling the Functional Network for Spatial Navigation in the Human Brain
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Modeling the Functional Network for Spatial Navigation in the Human Brain

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Last Updated: May 30, 2026

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling
06:55

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling

Published on: August 5, 2016

Modeling the Functional Network for Spatial Navigation in the Human Brain
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Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Area of Science:

  • Network science
  • Pattern recognition
  • Geomorphology

Background:

  • Topological estimators alone are insufficient for characterizing complex spatial networks.
  • Similar topologies can arise from different morphogenetic processes, obscuring true structural differences.
  • Existing methods struggle to quantify large-scale spatial coherence in networklike patterns.

Purpose of the Study:

  • To propose a novel quantitative method for characterizing spatial networklike patterns with loops.
  • To incorporate local geometric cues (junction angles) to complement topological information.
  • To differentiate between hierarchical and homogeneous spatial networks based on growth processes and organization.

Main Methods:

  • Developed a quantitative method using local geometric cues (angles at junctions).
  • Applied the method to diverse networklike patterns, including fracture patterns, leaf veins, and urban streets.
  • Utilized the method to rank pattern segments, approximating their order of appearance for time-evolving patterns.

Main Results:

  • Identified a continuous but sharp dichotomy between hierarchical and homogeneous spatial networks.
  • Hierarchical networks exhibit large-scale organization resulting from sequential growth.
  • Homogeneous networks display local organization without global coherence.

Conclusions:

  • The proposed method effectively quantifies spatial coherence in networklike patterns.
  • The distinction between hierarchical and homogeneous networks provides insights into their underlying formation processes.
  • This approach offers a powerful tool for analyzing diverse natural and artificial spatial networks.