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相关概念视频

Scanning Electron Microscopy01:07

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A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
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The early pioneers of microscopy opened a window into the invisible world of microorganisms. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes that leveraged nonvisible light, such as fluorescence microscopy that uses an ultraviolet light source and electron microscopy that uses short-wavelength electron beams. These advances significantly improved magnification, image resolution, and contrast. By comparison, the...
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相关实验视频

Updated: Jun 10, 2025

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在显微镜的散射分析中的初始不确定性量化.

Mengyang Gu1, Yue He1, Xubo Liu1

  • 1Department of Statistics and Applied Probability, <a href="https://ror.org/02t274463">University of California, Santa Barbara</a>, Santa Barbara, California 93106, USA.

Physical review. E
|October 19, 2024
PubMed
概括

我们介绍了初始不确定性量化 (AIUQ),这是一个新的参数估计方法,它消除了在基于散射的分析中手动选择波向量的需要. AIUQ提高了准确性,并使各种物理系统的自动化分析成为可能.

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相关实验视频

Last Updated: Jun 10, 2025

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科学领域:

  • 物理 物理学 物理
  • 数据分析 数据分析
  • 材料科学 材料科学 材料科学

背景情况:

  • 物理学中的参数估计通常涉及到在互空间中最小化损失函数,需要手动选择波向量范围.
  • 在微分动态显微镜 (DDM) 中,传统的方法相当于安装时间变异图,将分析限制在所选波向量上.

研究的目的:

  • 引入一个新的范式,即初始不确定性量化 (AIUQ),用于从数据中进行概率参数估计.
  • 证明AIUQ在微分动态显微镜 (DDM) 中的有效性,以提高准确性和自动化分析.

主要方法:

  • 开发了一个AIUQ的概率生成模型,从数据处理中传播不确定性.
  • 导出了一个最大边际概率估计器,该估计器最佳地利用了所有波向量信息.
  • 使用了一般化的舒尔算法来有效计算概率函数.

主要成果:

  • AIUQ消除了手动波向量选择的需要,提高了估计准确度.
  • 显著降低了概率函数计算的计算成本.
  • 通过各种动态系统的模拟和实验研究验证AIUQ.

结论:

  • AIUQ提供了一个强大的和自动化的方法,用于参数估计在基于散射的分析.
  • 在各种系统中展示了AIUQ的实用性,包括牛顿流体,sol-gel过渡和异型合物.
  • 该方法可以在没有人工干预的情况下实现自动化分析和模型选择.