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関連する概念動画

Spontaneity02:21

Spontaneity

A spontaneous process is one that occurs naturally under certain conditions. A nonspontaneous process, on the other hand, will not take place unless it is “driven” by the continual input of energy from an external source. Processes have a natural tendency to occur in one direction under a given set of conditions. Water will naturally flow downhill (spontaneous process), but uphill flow (nonspontaneous process) requires outside intervention such as the use of a pump. Iron exposed to the earth’s...
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
Random Variables01:09

Random Variables

A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Poisson Probability Distribution01:09

Poisson Probability Distribution

A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
Entropy02:39

Entropy

Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...

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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

ランダムなネットワークで爆発物が漏れ落ちる.

Dimitris Achlioptas1, Raissa M D'Souza, Joel Spencer

  • 1Department of Computer Science, University of California at Santa Cruz, Santa Cruz, CA 95064, USA.

Science (New York, N.Y.)
|March 17, 2009
PubMed
まとめ
この要約は機械生成です。

ランダムなネットワーク形成に選択を導入すると,不連続の浸透移行が起こり,ネットワーク科学にとって新しい発見となる. これは,ネットワークが臨界点の近くでどのように結びついているかについての以前の仮定に異議を唱えます.

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Fast Imaging Technique to Study Drop Impact Dynamics of Non-Newtonian Fluids
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Fast Imaging Technique to Study Drop Impact Dynamics of Non-Newtonian Fluids

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Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model
09:47

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model

Published on: October 18, 2015

関連する実験動画

Last Updated: Jun 24, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

Fast Imaging Technique to Study Drop Impact Dynamics of Non-Newtonian Fluids
10:09

Fast Imaging Technique to Study Drop Impact Dynamics of Non-Newtonian Fluids

Published on: March 5, 2014

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model
09:47

Interfacing 3D Engineered Neuronal Cultures to Micro-Electrode Arrays: An Innovative In Vitro Experimental Model

Published on: October 18, 2015

科学分野:

  • ネットワーク科学 ネットワーク科学
  • 統計物理学 統計物理
  • 複雑なシステム 複雑なシステム

背景:

  • ランダムなネットワーク形成モデルは,エルドース-レニイモデルのように,通常,連続的な浸透移行を示します.
  • 浸透移行は,臨界点の周辺のネットワーク接続の突然の増加を伴う.
  • ランダムなネットワークにおける不連続の浸透移行の可能性は,まだ開かれた理論上の問題でした.

研究 の 目的:

  • ランダムなネットワークにおけるパルコレーショントランジションが不連続であるかどうかを調査する.
  • ネットワーク形成モデルに限られた選択肢を導入することの影響を調査する.
  • ランダムグラフでの浸透現象の確立された理解に異議を唱える.

主な方法:

  • クラシックなエルドース-レニーのネットワーク形成モデルの修正.
  • 限られた選択メカニズムを接続形成プロセスに組み込む.
  • 結果のネットワーク構造と浸透行動の分析.

主要な成果:

  • 制限された選択を導入すると,不連続の浸透の移行につながるという実証.
  • 移行点より上のネットワークコンポーネントの突然の大規模なリンクの観測.
  • これは,純粋にランダムなモデルで観察される典型的に連続した移行と対照的です.

結論:

  • ランダムなネットワークにおける浸透移行は,特定の条件下で不連続である可能性があります.
  • ネットワーク形成における選択肢の制限は,この不連続性を引き起こす重要な要因である.
  • 発見は,複雑なシステムの行動とネットワークの強度に関する新しい洞察を提供します.