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相关概念视频

Diffusion01:12

Diffusion

194.1K
Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
194.1K
Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

561
Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting...
561
Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

1.0K
Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
1.0K
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

4.4K
Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
4.4K
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

95
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
95
Porosity and Absorption of Aggregate01:20

Porosity and Absorption of Aggregate

332
Aggregates contain pores of varying sizes; while some are completely enclosed within the particles, others open onto the surface, allowing water to penetrate. The porosity of aggregates is a major factor contributing to the overall porosity of concrete, given that aggregates constitute about three-quarters of concrete's volume.
When all pores in an aggregate are filled with water, the aggregate is considered saturated and surface-dry. If left in dry air, water will evaporate until the...
332

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相关实验视频

Updated: Jul 26, 2025

The Diffusion of Passive Tracers in Laminar Shear Flow
08:01

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

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深度学习用于在多孔介质中传播.

Krzysztof M Graczyk1, Dawid Strzelczyk2, Maciej Matyka2

  • 1Faculty of Physics and Astronomy, Institute of Theoretical Physics, University of Wrocław, pl. M. Borna 9, 50-204, Wrocław, Poland. krzysztof.graczyk@uwr.edu.pl.

Scientific reports
|June 16, 2023
PubMed
概括
此摘要是机器生成的。

卷积神经网络 (CNN) 可以预测多孔介质的特性. 虽然几何分析CNN显示出有限的可转移性,但U-Net架构有效地重建了各种媒体类型的度图,包括沙子和生物组织.

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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

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A Microfluidic Platform to Study Bioclogging in Porous Media
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A Microfluidic Platform to Study Bioclogging in Porous Media

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相关实验视频

Last Updated: Jul 26, 2025

The Diffusion of Passive Tracers in Laminar Shear Flow
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The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates
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A Method for Determination and Simulation of Permeability and Diffusion in a 3D Tissue Model in a Membrane Insert System for Multi-well Plates

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A Microfluidic Platform to Study Bioclogging in Porous Media
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A Microfluidic Platform to Study Bioclogging in Porous Media

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科学领域:

  • 计算物理学的计算物理.
  • 材料科学是一种材料科学.
  • 生物物理学的生物物理.

背景情况:

  • 孔状介质的特征化对于地质学,化学工程和生物医学领域的应用至关重要.
  • 预测诸如多孔性和扩散等有效性质对于理解流体流动和运输现象至关重要.
  • 卷积神经网络 (CNN) 为分析复杂的微观结构和预测材料特性提供了一个有前途的方法.

研究的目的:

  • 研究CNN用于预测多孔介质的基本性质的应用.
  • 为了比较不同的CNN架构 (C-Net,U-Net) 在预测孔隙性和有效扩散系数方面的性能.
  • 评估经过训练的模型在不同多孔介质类型,特别是沙包装和生物组织中的可转移性.

主要方法:

  • 利用格子博尔茨曼方法生成标记数据用于监督学习.
  • 开发和修改了CNN模型,包括具有自我规范化模块的C-Net和U-Net架构.
  • 在两个不同的多孔介质数据集上训练和测试模型:沙包装和生物组织模拟系统.
  • 应用阿奇定律来确定从孔隙度和有效扩散数据中扭曲度.

主要成果:

  • 经过几何分析训练的CNN可以达到合理的准确性,但在沙子和生物介质之间缺乏可转移性.
  • 在重建度场时,U-Net架构表现出高精度.
  • 在一种多孔介质 (如沙子) 上训练的模型有效地对另一种 (如生物组织) 进行了概括,用于度图的重建.
  • 使用阿奇定律成功推导出曲率,将有效的扩散与毛孔性联系起来.

结论:

  • CNNs可以有效地预测多孔介质属性,U-Net显示出优越的性能和可转移性,用于度场重建.
  • 选择CNN架构显著影响不同多孔媒体类型的模型通用性.
  • 该研究强调了深度学习在各种科学领域对复杂的多孔材料进行表征的潜力.