Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

397
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
397
Diffusion01:21

Diffusion

6.9K
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...
6.9K
Diffusion01:12

Diffusion

224.3K
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...
224.3K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

299
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
299
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
Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

876
Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...
876

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

[Full-length transcriptome analysis and identification of the HXK gene family of <i>Lilium tsingtauense</i>].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology·2026
Same author

rSiglec-10(V set) armed oncolytic adenovirus improves the effects of virotherapy through enhancing oncolysis and antitumor immunity.

International immunopharmacology·2026
Same author

A Low-Profile Self-Stealth Programmable Metasurface with In-Band and Out-of-Band RCS Reduction.

Research (Washington, D.C.)·2026
Same author

Wavelet Spectrum in a Multi-Channel Network May Reduce Biopsy Rates on Diagnosis of Breast Tumors with BI-RADS Category 4a or Higher.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine·2026
Same author

CLCNet: a contrastive learning and chromosome-aware network for genomic prediction in plants.

Briefings in bioinformatics·2026
Same author

Self-assembled micelles stabilized by covalent α-lipoic acid-carboxymethyl chitosan conjugates: Enabling stable delivery and glutathione-responsive release of coenzyme Q10.

Food research international (Ottawa, Ont.)·2026
Same journal

Continual Slow-and-Fast Adaptation of Latent Neural Dynamics (CoSFan): Meta-Learning What-How & When to Adapt.

... International Conference on Learning Representations·2026
Same journal

Topology-Aware Segmentation Using Discrete Morse Theory.

... International Conference on Learning Representations·2026
Same journal

TOPODIFFUSIONNET: A TOPOLOGY-AWARE DIFFUSION MODEL.

... International Conference on Learning Representations·2026
Same journal

GEOMETRY OF LONG-TAILED REPRESENTATION LEARNING: REBALANCING FEATURES FOR SKEWED DISTRIBUTIONS.

... International Conference on Learning Representations·2026
Same journal

Probabilistic Geometric Principal Component Analysis with application to neural data.

... International Conference on Learning Representations·2026
Same journal

BRAID: Input-driven nonlinear dynamical modeling of neural-behavioral data.

... International Conference on Learning Representations·2026
查看所有相关文章

相关实验视频

Updated: Feb 28, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.3K

区块扩散:在自逆向和扩散语言模型之间进行互联.

Marianne Arriola1, Aaron Kerem Gokaslan1, Justin T Chiu2

  • 1Cornell Tech, NY, USA.

... International Conference on Learning Representations
|February 27, 2026
PubMed
概括
此摘要是机器生成的。

区块扩散语言模型克服了自回归和扩散模型的局限性,使灵活的长度生成和提高效率成为可能. 这种新方法在语言建模基准中实现了最先进的性能.

更多相关视频

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.7K

相关实验视频

Last Updated: Feb 28, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.3K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.7K

科学领域:

  • 人工智能的人工智能
  • 自然语言处理自然语言处理.
  • 机器学习 机器学习

背景情况:

  • 扩散语言模型提供并行生成和可控制性,但在概率建模和固定长度输出方面存在困难.
  • 自动回归模型的概率很高,但缺乏并行化和灵活性.

研究的目的:

  • 引入区块扩散语言模型,以弥合离散拒绝扩散和自动回归模型之间的差距.
  • 解决现有模型的局限性,使灵活的长度生成和更高的推理效率.

主要方法:

  • 开发了一种新的区块扩散语言模型类型.
  • 提出了一个培训配方,包括高效的算法,梯度方差估计器和数据驱动的噪声时间表.
  • 实现了KV缓存和并行令牌采样,以改善推理.

主要成果:

  • 区块扩散模型在语言建模基准上实现了最先进的性能.
  • 证明了灵活长度生成能力,克服了固定长度限制.
  • 与之前的扩散模型相比,展示了较好的推断效率.

结论:

  • 区块扩散代表了扩散语言模型的重大进步.
  • 提出的方法允许有效的培训和灵活的,高性能语言生成.
  • 代码,模型重量和更多细节可在项目页面上找到.