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The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
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相关实验视频

Updated: Feb 28, 2026

Flow Virometry to Analyze Antigenic Spectra of Virions and Extracellular Vesicles
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VFMol:一个离散的流量匹配变化自编码器用于分子图形生成.

Yanglan Gan1, Jieli Su1, Kaili Wang1

  • 1School of Computer Science and Technology, Donghua University, Shanghai 201620, China.

Journal of chemical information and modeling
|February 26, 2026
PubMed
概括

通过结合变量自编码器和离散流匹配,VFMol增强了用于药物发现的分子图形生成. 这种新的框架改善了复合质量和财产控制,克服了现有方法的局限性.

科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 机器学习是机器学习.

背景情况:

  • 分子图生成对于识别新药候选药物至关重要.
  • 使用变化自编码器 (VAE) 和离散流匹配 (DFM),但有局限性.
  • 现有的方法与换不变性,生成瓶和可适应的先前初始化作斗争.

研究的目的:

  • 引入VFMol,这是一个整合VAE和DFM的新型框架,用于改进分子生成.
  • 在初始化之前解决VAE解码器和DFM的局限性.
  • 为了实现高效,可控制和高质量的分子图形生成.

主要方法:

  • VFMol在协同作用下将个性化的VAE潜伏空间建模与DFM的逐步采样相结合.
  • 编码器学习了每个输入图的定制后部分布.
  • 使用KAN和无分类器指导的属性导向框架可以实现条件生成.

主要成果:

  • 在分子生成任务上,VFMol实现了最先进的性能.
  • 显示出优越的分子结构质量和属性可控性.
  • 在数据集中验证框架的通用性和有效性.

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结论:

  • 在药物发现的分子图表生成方面,VFMol提供了显著的进步.
  • 综合方法克服了先前方法的主要局限性.
  • VFMol提供了一个强大的工具,用于设计具有所需性质的新型化合物.