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Diffusion01:12

Diffusion

227.7K
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...
227.7K
Diffusion01:21

Diffusion

7.1K
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...
7.1K
Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

2.0K
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...
2.0K
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

6.1K
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...
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Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

1.6K
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...
1.6K
Carrier Transport01:21

Carrier Transport

1.1K
The generation of electrical current in semiconductors is fundamentally driven by two mechanisms: drift and diffusion. These processes are essential for the functionality and performance of semiconductor-based devices.
Drift Current:
The drift of charge carriers is started by an external electric field (E). Charged particles, such as electrons and holes, experience an acceleration between collisions with lattice atoms. For electrons, this results in a drift velocity (vd) given by:
1.1K

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Related Experiment Video

Updated: Mar 13, 2026

Spot Variation Fluorescence Correlation Spectroscopy for Analysis of Molecular Diffusion at the Plasma Membrane of Living Cells
05:56

Spot Variation Fluorescence Correlation Spectroscopy for Analysis of Molecular Diffusion at the Plasma Membrane of Living Cells

Published on: November 12, 2020

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The Diffusion Duality.

Subham Sekhar Sahoo1, Justin Deschenaux2, Aaron Gokaslan1

  • 1Computer and Information Science, Cornell Tech, NYC, USA.

Proceedings of Machine Learning Research
|March 12, 2026
PubMed
Summary
This summary is machine-generated.

Duo, a new method for discrete diffusion models, doubles training speed and enables few-step text generation. It bridges the performance gap with autoregressive models by adapting Gaussian diffusion techniques.

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Related Experiment Videos

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Area of Science:

  • Artificial Intelligence
  • Natural Language Processing
  • Machine Learning

Background:

  • Uniform-state discrete diffusion models offer fast text generation but are often outperformed by autoregressive and masked diffusion models.
  • Existing discrete diffusion models face challenges in matching the performance of continuous Gaussian diffusion models.

Purpose of the Study:

  • To narrow the performance gap between uniform-state discrete diffusion models and autoregressive models.
  • To enhance both the training and sampling efficiency of discrete diffusion models.

Main Methods:

  • Leveraging the insight that uniform-state diffusion processes emerge from underlying Gaussian diffusion.
  • Introducing a curriculum learning strategy guided by Gaussian processes to reduce variance and accelerate training.
  • Adapting consistency distillation from continuous to discrete settings via Discrete Consistency Distillation for accelerated sampling.

Main Results:

  • Curriculum learning doubled training speed and improved zero-shot perplexity, surpassing autoregressive models on 3 of 7 benchmarks.
  • Discrete Consistency Distillation enabled few-step generation in diffusion language models, accelerating sampling by two orders of magnitude.
  • The Duo method effectively transfers techniques from Gaussian diffusion to discrete settings, enhancing model performance.

Conclusions:

  • The Duo method significantly improves uniform-state discrete diffusion models, making them competitive with autoregressive models.
  • Efficient training and accelerated few-step sampling are key advancements for diffusion language models.
  • The proposed techniques offer a promising direction for developing faster and more effective text generation models.