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

Improving Translational Accuracy02:07

Improving Translational Accuracy

3.5K
3.5K
Improving Translational Accuracy02:07

Improving Translational Accuracy

14.0K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
14.0K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

261
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...
261
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

467
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
467
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

474
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,...
474
Forced Transdifferentiation01:28

Forced Transdifferentiation

2.3K
Transdifferentiation, also known as lineage reprogramming, was first discovered by Selman and Kafatos in 1974 in silkmoths. They observed that the moths’ cuticle-producing cells transformed into salt-producing cells. Many such cases of natural transdifferentiation occur in organisms. In humans, pancreatic alpha cells can become beta cells. In newts, the loss of the eye’s lens causes the pigmented epithelial cells to transdifferentiate into the lens cells.
Artificial...
2.3K

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

Ginsenosides in Liver Fibrosis: Pharmacological Actions and Therapeutic Potential.

The American journal of Chinese medicine·2026
Same author

Potential roles of plant metabolites and Traditional Chinese Medicine formulas in regulating glycolysis-OXPHOS plasticity in gastric precancerous lesions and gastric cancer: a critical appraisal of the evidence.

Frontiers in pharmacology·2026
Same author

Fluid Biomarkers of Cognitive Impairments Following Traumatic Brain Injury: A Systematic Review and Meta Analysis.

International journal of molecular sciences·2026
Same author

Effects of TUS-NMES Combined with Glucocorticoid on Clinical Outcomes and Rehabilitation Efficacy of Neurosyphilis Patients with Cerebral Infarction.

Therapeutics and clinical risk management·2026
Same author

Effects of Mixed Cotton Stalk and Sugar Beet Pulp Microsilage on Growth Performance, Meat Quality, Muscle Metabolism, and Intestinal Microbiota in Suffolk Rams.

Animals : an open access journal from MDPI·2026
Same author

Geometric Optimization of GMR Biosensors with Trapezoidal Magnetic Flux Concentrators for Detecting <i>Bacillus anthracis</i> in Complex Matrices.

Sensors (Basel, Switzerland)·2026
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026
Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026
Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
查看所有相关文章

相关实验视频

Updated: Jan 8, 2026

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

2.2K

超越隐含映射:通过平滑的最佳运输推进生成模型.

Shenghao Li, Lianbao Jin, Zhanpeng Wang

    IEEE transactions on neural networks and learning systems
    |December 11, 2025
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了使用Nesterov的深度生成模型的明确最佳运输 (OT) 映射.

    相关实验视频

    Last Updated: Jan 8, 2026

    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

    2.2K

    科学领域:

    • 深度学习是一种深度学习.
    • 生成型模型是一种生成型模型.
    • 最佳运输理论的最佳运输理论.

    背景情况:

    • 优化运输 (OT) 在深度学习中对于分销转型至关重要.
    • 深度生成模型中的当前OT方法通常使用隐性映射,限制可解释性和条件生成.
    • 现有的模型面临着诸如训练不稳定,消失梯度和模式崩等挑战.

    研究的目的:

    • 开发一个先进的生成模型,具有明确的最佳运输映射.
    • 提高模型的可解释性,并使有效的条件样本生成成为可能.
    • 在深度学习模型中提高样本生成效率.

    主要方法:

    • 将内斯特罗夫的平滑技术应用于布雷尼尔潜力.
    • 从平滑的潜能中推导出一个明确的最佳运输映射.
    • 在这个显式映射的基础上构建了一个新的深度生成模型.

    主要成果:

    • 拟议的模型明确地捕捉了源到目标域映射,提高了可解释性.
    • 通过平滑的OT映射近似实现了条件样本生成.
    • 与传统方法相比,在无条件和条件生成任务中实现了更高的性能.

    结论:

    • 这种新的方法提供了一个可解释和高效的生成模型.
    • 通过平滑获得的明确OT映射为生成建模提供了一个新的方向.
    • 该方法成功地解决了深度学习中隐性OT映射的局限性.