Jove
Visualize
联系我们

相关概念视频

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

249
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...
249
Regression Toward the Mean01:52

Regression Toward the Mean

7.1K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.1K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

102.4K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
102.4K
Shrinkage in Concrete01:27

Shrinkage in Concrete

421
Shrinkage in concrete is primarily due to water loss from evaporation, hydration of cement, or carbonation, leading to a reduction in volume. The volumetric contraction results in volumetric strain in concrete. However, in practice, shrinkage is measured as linear strain, which is one-third of the volumetric strain.
When concrete is still in its plastic state, it can undergo a decrease in volume by about 1% of its absolute volume. This decrease is known as plastic shrinkage. It arises either...
421
Drying Shrinkage01:21

Drying Shrinkage

379
When hardened concrete is exposed to air with a relative humidity of less than 100 percent, it begins to lose the free water within its capillaries. As this water evaporates, the water initially adsorbed onto the calcium silicate hydrates migrates towards these now empty spaces and eventually evaporates as well. Over time, as more water leaves, the volume of the concrete decreases, a phenomenon known as drying shrinkage.
A portion of this drying shrinkage can be reversed; if the concrete is...
379
Carbonation Shrinkage01:24

Carbonation Shrinkage

491
Atmospheric CO2 penetrates the concrete's pores and, in the presence of moisture, forms carbonic acid, which then reacts with calcium hydroxide in the hydrated cement, forming calcium carbonate. This process reduces the concrete's volume and is termed carbonation shrinkage.
The concrete's permeability is slightly reduced as calcium carbonate produced during the reaction fills its pores. Furthermore, its strength is slightly enhanced as the water released during the reaction...
491

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 journal

Effects of audio guided loving kindness meditation on psychological well being and laboratory stress responsiveness in healthy university students.

Scientific reports·2026
Same journal

Adaptive cognitive driven cross modal network for few shot fine grained recognition.

Scientific reports·2026
Same journal

Tegoprazan-based dual therapy versus bismuth-containing quadruple therapy for Helicobacter pylori eradication: a prospective, multicenter, open-label, non-inferiority, randomized controlled trial.

Scientific reports·2026
Same journal

Primary tumor resection prior to peptide receptor radionuclide therapy is associated with improved survival in metastatic gastroenteropancreatic neuroendocrine tumors: a systematic review and meta-analysis.

Scientific reports·2026
Same journal

Sleep duration among medical students and its association with bronchial asthma, anxiety, and depression.

Scientific reports·2026
Same journal

MGMT deficiency augments STING-mediated inflammatory responses accompanied by metabolic alterations in macrophages.

Scientific reports·2026
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: Feb 7, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.5K

提高模拟高度多线性数据的准确性,使用回归方法的替代收缩参数.

Nadeem Akhtar1, Muteb Faraj Alharthi2

  • 1Government Degree College Achin Payan Higher Education Department, Peshawar, Khyber Pakhtunkhwa, Pakistan. akhqau@gmail.com.

Scientific reports
|March 29, 2025
PubMed
概括

这项研究引入了三种新的脊回归收缩参数,提高了多对线数据的预测准确性. 提出的CARE估计器,特别是CARE3,在模拟和现实应用中表现优于现有方法.

关键词:
平均平方误差 (MSE) 是指蒙特卡洛模拟的蒙特卡洛模拟.多对线性是多对线性的.回归分析是一种回归分析.收缩山脊估计器 收缩山脊估计器

更多相关视频

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.9K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

11.1K

相关实验视频

Last Updated: Feb 7, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.5K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.9K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

11.1K

科学领域:

  • 统计 统计 统计 统计
  • 机器学习 机器学习

背景情况:

  • 斜坡回归对多线性敏感.
  • 高误差差异可以降低模型的预测准确性.

研究的目的:

  • 介绍了脊回归的新型收缩参数.
  • 开发条件调整估计器 (CAREs) 以提高预测.
  • 应对多对线性和高误差差异的挑战.

主要方法:

  • 开发了三个新的收缩参数.
  • 创建了 CARE1,CARE2 和 CARE3 的估计器.
  • 通过模拟和真实世界数据集使用平均平方误差 (MSE) 评估性能.

主要成果:

  • 拟议的CARE估计器始终优于现有方法.
  • 在各种场景中,CARE3表现出卓越的表现.
  • 在真实世界的数据集分析中验证了有效性.

结论:

  • 新的收缩参数和CARE估计器提高了预测准确度.
  • CARE3是多线数据最有效的估计器.
  • 这些估计器为稳定,准确的预测提供了实际实用性.