Jove
Visualize
联系我们

相关概念视频

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

23
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
23
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

66
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
66
State Space Representation01:27

State Space Representation

159
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
159
Linear time-invariant Systems01:23

Linear time-invariant Systems

200
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
200
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

93
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
93
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

54
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...
54

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

CAM photosynthesis may have conferred an advantage during the Permian-Triassic mass extinction event.

Nature ecology & evolution·2026
Same author

Can Incorporating Parity Information Improve the Reliability of Completed Cohort Fertility Projections? Insights From a Bayesian Generalized Additive Model Approach.

Demography·2026
Same author

Early evolutionary history of the seed.

Biological reviews of the Cambridge Philosophical Society·2026
Same author

Data navigation on the ENCODE portal.

Nature communications·2025
Same author

Author Correction: Early Triassic super-greenhouse climate driven by vegetation collapse.

Nature communications·2025
Same author

Convergent evolution in the late Permian megaphyllous leaves of the Noeggerathiales progymnosperm Paratingia and the cycad Plagiozamites.

Annals of botany·2025
Same journal

Applying invasion criterion to cultural evolution.

Theoretical population biology·2026
Same journal

The joint spectrum over trees under the Kingman coalescent with varying population.

Theoretical population biology·2026
Same journal

Statistical test to compare the linkage model and the admixture model based on central limit results.

Theoretical population biology·2026
Same journal

Threshold dynamics in age-structured distributions with expanding support: A unified mathematical framework.

Theoretical population biology·2026
Same journal

Mechanistic-statistical model for the expansion of ash dieback.

Theoretical population biology·2026
Same journal

Dynamics of an intraguild predation system with optimal foraging and harvesting.

Theoretical population biology·2026
查看所有相关文章
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

相关实验视频

Updated: May 23, 2025

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.2K

一个数学框架,用于时间变量的多状态亲属关系建模.

Joe W B Butterick1, Peter W F Smith1, Jakub Bijak1

  • 1Department of Social Statistics and Demography, University of Southampton, Southampton SO17 1BJ, United Kingdom.

Theoretical population biology
|March 7, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个新的亲属关系人口统计模型,允许任何个人特征和时间变化的速率. 该模型揭示了空间分布如何影响个体的亲属.

关键词:
年龄×阶段结构的人口.亲属关系的关系马尔科夫过程是一个马尔科夫过程.数学的人口统计学.矩阵投影是指矩阵的投影.

更多相关视频

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K
Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells
10:20

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Published on: March 24, 2023

1.3K

相关实验视频

Last Updated: May 23, 2025

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.2K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.3K
Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells
10:20

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Published on: March 24, 2023

1.3K

科学领域:

  • 人口统计学 人口统计学
  • 数学生物学 数学生物学
  • 社会学 社会学 社会学

背景情况:

  • 人口学中的亲属关系建模已经在多个状态和时间变异的方法中取得了进展.
  • 现有的多国家亲属关系模型在范围和适应性方面存在理论上的限制.
  • 对任意特征和时间依赖过程的亲属关系模型的概括是一个公开的挑战.

研究的目的:

  • 为扩展多国家亲属关系模型提出一个通用的方法.
  • 开发一个灵活的模型,适应任何个别阶段和人口统计率.
  • 为了解决目前人口学中的亲属模型框架的局限性.

主要方法:

  • 开发了一种新的方法来扩展多州亲属关系建模.
  • 利用马尔科夫过程创建一个简洁的数学框架.
  • 将模型应用于英格兰和威尔士的空间人口情景.

主要成果:

  • 拟议的模型理论上适用于时间变量和时间不变设置中的任何阶段.
  • 通过将阶段定义为空间位置 (LAD) 来证明模型的实用性.
  • 阐明了空间分布对亲属网络的影响.

结论:

  • 开发的方法论在人口亲属模型中提供了显著的进步.
  • 该模型为不同的人口结构提供了灵活和理论上强大的方法.
  • 空间分布是影响个人亲属网络的关键人口统计因素.