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相关概念视频

Diffusion01:12

Diffusion

215.7K
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...
215.7K
Diffusion01:21

Diffusion

6.1K
Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
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Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

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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...
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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

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Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
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Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

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

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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...
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相关实验视频

Updated: Jan 10, 2026

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
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ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

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DDGC:用于动态图集群的基于扩散的方法.

Shengtao Shen1, Xulun Ye1, Jieyu Zhao1

  • 1Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China.

Neural networks : the official journal of the International Neural Network Society
|November 26, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了动态图集群的新扩散模型,有效地处理不断变化的图结构和未知的类. 该方法提高了识别新类的准确性,并适应不断变化的数据,优于现有的方法.

关键词:
扩散模型是一个扩散模型.动态图表学习,动态图表学习,动态图表学习图形集群是指图形的集群.

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
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科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 图形理论 图形理论

背景情况:

  • 静态图集群方法与不断变化的网络结构和动态节点类别作斗争.
  • 现有的动态图集群方法往往无法同时解决少数类和新兴未知的类.

研究的目的:

  • 提出一种基于扩散模型的新型动态图集群方法,用于具有未知类的演变图.
  • 在动态图集群场景中增强新和少数类别的识别.

主要方法:

  • 图形卷积网络 (GCN) 与扩散模型的集成.
  • 在嵌入空间中利用内核密度估计和Tweedie密度调整公式.
  • 使用数据密度波动进行无监督的伪标签分配.

主要成果:

  • 拟议的方法在动态图表集群任务上表现优于最先进的基线.
  • 在出现未知类和少数样本的场景中表现出卓越的表现.
  • 在静态和演化的图形环境中实现了自适应类发现和样本增强.

结论:

  • 新的扩散模型有效地解决了动态图集群现有方法的局限性.
  • 该框架为在线图表理解和现实世界的动态应用提供了强大的解决方案.
  • 这项工作弥合了静态和动态图表集群研究之间的差距.