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

Null and Alternative Hypotheses01:16

Null and Alternative Hypotheses

8.3K
The actual hypothesis testing begins by considering two hypotheses. They are termed  the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As  a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
8.3K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

57
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
57
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

79
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
79
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

733
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
733
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

71
Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's...
71
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

151
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
151

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

A generalized simplicial model and its application.

Chaos (Woodbury, N.Y.)·2024
Same author

Higher-order link prediction via local information.

Chaos (Woodbury, N.Y.)·2023
Same author

Non-structural carbohydrates in maize with different nitrogen tolerance are affected by nitrogen addition.

PloS one·2019
Same author

Knockdown of long noncoding RNA XIST mitigates the apoptosis and inflammatory injury of microglia cells after spinal cord injury through miR-27a/Smurf1 axis.

Neuroscience letters·2019
Same author

One-Step Hydrothermal Synthesis of P25 @ Few Layered MoS<sub>2</sub> Nanosheets toward Enhanced Bi-catalytic Activities: Photocatalysis and Electrocatalysis.

Nanomaterials (Basel, Switzerland)·2019
Same author

Electrospun thymosin Beta-4 loaded PLGA/PLA nanofiber/ microfiber hybrid yarns for tendon tissue engineering application.

Materials science & engineering. C, Materials for biological applications·2019

相关实验视频

Updated: Jul 12, 2025

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

599

超零模型及其应用.

Yujie Zeng1,2, Bo Liu1,2, Fang Zhou1,2

  • 1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China.

Entropy (Basel, Switzerland)
|October 28, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的超边缘交换方法,用于创建超图的零模型. 这些超零模型有助于分析网络结构和动态,在各种科学场景中具有广泛的适用性.

关键词:
超图是指一个超图.网络动态 网络动态无效模型 无效模型 无效模型随机性 随机性 随机性

更多相关视频

In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

20.7K
Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models
10:49

Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models

Published on: June 16, 2022

2.6K

相关实验视频

Last Updated: Jul 12, 2025

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

599
In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

20.7K
Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models
10:49

Hydrogel Arrays Enable Increased Throughput for Screening Effects of Matrix Components and Therapeutics in 3D Tumor Models

Published on: June 16, 2022

2.6K

科学领域:

  • 网络科学 网络科学
  • 图形理论 图形理论
  • 复杂的系统复杂的系统.

背景情况:

  • 零模型对于理解网络拓学至关重要.
  • 对高阶网络 (超图) 的零模型的研究是有限的.

研究的目的:

  • 开发一种创新的方法,用于构建超图的零模型.
  • 分析这些超零模型的属性和相互关系.
  • 评估超图的随机性对网络动态的影响.

主要方法:

  • 引入了一种基于超边缘交换的方法来生成超零模型.
  • 保留特定的网络属性,同时改变其他网络属性.
  • 利用高图来评估零模型的随机性.
  • 分析统计属性和网络动态 (拆解,流行病传染).

主要成果:

  • 产生了六个不同的超零模型,不同的顺序.
  • 在四个数据集中使用超图验证了超零模型的随机性.
  • 在零模型和原始网络之间观察到统计属性的差异.
  • 证明了超图的随机性对网络动态的影响.

结论:

  • 提出的超零模型是有效的,适用于各种场景.
  • 这项工作为超图零模型的生成和分析提供了一个全面的框架.
  • 为更高层次的网络结构及其影响开辟了新的研究途径.