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

Modeling with Differential Equations01:25

Modeling with Differential Equations

21
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
21
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

6.5K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
6.5K
Modeling and Similitude01:12

Modeling and Similitude

620
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
620
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

705
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
705
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

5.3K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
5.3K
Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

20.2K
Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
20.2K

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

Lenacapavir-induced lattice hyperstabilization is central to HIV-1 capsid failure at the nuclear pore complex and in the cytoplasm.

eLife·2026
Same author

Systematic bottom-up coarse-graining of hydrated excess proton transport across scales.

Nature computational science·2026
Same author

Thermally activated snap-through transitions controlled by tunable free energy landscape.

The Journal of chemical physics·2026
Same author

Mechanism of HIV-1 Capsid Rupture and Uncoating by Reverse Transcription.

bioRxiv : the preprint server for biology·2026
Same author

Physical Confinement Modulates the Rate-Limiting Transition in the Release of Phosphate from Actin Filaments.

bioRxiv : the preprint server for biology·2026
Same author

Hydration-Controlled Proton Transport in Respiratory Complex I.

Journal of the American Chemical Society·2026

相关实验视频

Updated: Jan 18, 2026

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
09:32

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

10.2K

针对粗粒度模型中的动态匹配的对抗性训练.

Yihang Wang1, Gregory A Voth1

  • 1Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, 5735 S. Ellis Ave., SCL 123, Chicago, Illinois 60637, USA.

The Journal of chemical physics
|September 8, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了对抗性训练,以改进粗粒度 (CG) 模拟. 新的框架确保了分子模型的动态一致性,提高了复杂系统模拟的可靠性.

更多相关视频

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.7K
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

1.2K

相关实验视频

Last Updated: Jan 18, 2026

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
09:32

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

10.2K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.7K
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

1.2K

科学领域:

  • 计算化学是一种计算化学.
  • 分子动力学模拟的模拟.
  • 生物物理学的生物物理.

背景情况:

  • 分子动力学 (MD) 模拟对于理解分子系统至关重要,但在计算上昂贵.
  • 粗粒度 (CG) 模型简化系统以降低计算成本,但往往缺乏动态一致性,限制了它们在动力学研究中的使用.
  • 现有的CG方法难以准确地复制复杂分子系统的动态.

研究的目的:

  • 开发一种新的对抗性训练框架,用于自下而上的粗粒度建模.
  • 通过与全原子 (AA) 参考动力学对齐,确保粗粒度模拟中的热力学和动力学真实性.
  • 为维护复杂分子系统的动态一致性提供系统和原则性的方法.

主要方法:

  • 开发了一个对抗式学习框架,结合了基于物理的生成器和神经网络歧视器.
  • 该框架训练CG模型以生成与AA参考轨迹无法区分的轨迹.
  • CG参数被逆向优化,消除了对预定义的动力特征的需求.

主要成果:

  • 该方法成功地重现了液态水的关键性质,包括辐射和角分布功能.
  • 实现了动态平均平方位移的准确预测.
  • 该框架展示了从短期培训轨迹中推断出长时间范围的动态的能力.

结论:

  • 拟议的对抗性培训框架为开发准确的粗粒度模型提供了一个强大的方法.
  • 这种方法提高了CG模拟对动力学驱动过程的可靠性.
  • 它代表了自下而上的CG建模的重大进步,确保了动态的一致性.