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関連する概念動画

Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
State Space Representation01:27

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Multimachine Stability01:25

Multimachine Stability

Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
Cooperative Allosteric Transitions01:58

Cooperative Allosteric Transitions

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...
Stability of structures01:14

Stability of structures

In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
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...

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関連する実験動画

Updated: Jun 13, 2026

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
10:45

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

コミュニティの構造は,時間依存,マルチスケール,マルチプレックスネットワークで構成されています.

Peter J Mucha1, Thomas Richardson, Kevin Macon

  • 1Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, NC 27599, USA. mucha@unc.edu

Science (New York, N.Y.)
|May 15, 2010
PubMed
まとめ
この要約は機械生成です。

複雑なネットワークにおけるコミュニティの構造を分析するための一般的な枠組みを提示します. それは,時間とともに進化するネットワークや,複数のリンクタイプを持つネットワークを含みます. このアプローチは,任意のマルチスライスネットワークで緊密に接続されたノードグループの検出を強化します.

さらに関連する動画

Recording and Analyzing Multimodal Large-Scale Neuronal Ensemble Dynamics on CMOS-Integrated High-Density Microelectrode Array
09:44

Recording and Analyzing Multimodal Large-Scale Neuronal Ensemble Dynamics on CMOS-Integrated High-Density Microelectrode Array

Published on: March 8, 2024

Two-Photon Polymerization 3D-Printing of Micro-scale Neuronal Cell Culture Devices
07:38

Two-Photon Polymerization 3D-Printing of Micro-scale Neuronal Cell Culture Devices

Published on: June 7, 2024

関連する実験動画

Last Updated: Jun 13, 2026

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
10:45

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

Recording and Analyzing Multimodal Large-Scale Neuronal Ensemble Dynamics on CMOS-Integrated High-Density Microelectrode Array
09:44

Recording and Analyzing Multimodal Large-Scale Neuronal Ensemble Dynamics on CMOS-Integrated High-Density Microelectrode Array

Published on: March 8, 2024

Two-Photon Polymerization 3D-Printing of Micro-scale Neuronal Cell Culture Devices
07:38

Two-Photon Polymerization 3D-Printing of Micro-scale Neuronal Cell Culture Devices

Published on: June 7, 2024

科学分野:

  • ネットワーク科学 ネットワーク科学
  • 複雑なシステムの分析分析
  • データサイエンス データサイエンス

背景:

  • コミュニティ検出は,ネットワーク科学の重要な問題です.
  • 既存の方法は,マルチスライスネットワークのような複雑なネットワーク構造としばしば闘う.
  • ネットワークコミュニティを理解することは,多様なシステムを分析する上で極めて重要です.

研究 の 目的:

  • ネットワークの品質機能の汎用的な枠組みを開発する.
  • 任意のマルチスライスネットワークにおけるコミュニティ構造の研究を可能にする.
  • タイム,マルチプレックス,マルチスケールの特性を有するネットワークを分析するための統一されたアプローチを提供する.

主な方法:

  • ネットワーク品質機能の汎用的な枠組みを開発した.
  • このフレームワークを,結合されたネットワークスライスを組み合わせたマルチスライスネットワークに適用しました.
  • このフレームワークは,多重性と複数のスケールで,時間とともに進化するネットワークに対応します.

主要な成果:

  • このフレームワークは,コミュニティ構造の検出を成功裏に一般化しています.
  • 複雑なネットワークトポロジーの分析を可能にします.
  • 様々な種類のネットワークに適用可能なことが実証されています.

結論:

  • 一般化されたフレームワークは,ネットワークコミュニティの検出のための強力なツールを提供します.
  • それは,多様なネットワークの特徴を統一することによって,複雑なシステムの研究を進めます.
  • 相互接続されたシステムの構造と動態に関するより深い洞察を容易にする.