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相关概念视频

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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Downsampling01:20

Downsampling

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When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
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Upsampling01:22

Upsampling

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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

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The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
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Bandpass Sampling01:17

Bandpass Sampling

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In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
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IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
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Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy
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空间压缩的光谱正向直角分解.

Guanzhong Ma1, Shiyan Lin1, Ruiyu Li1

  • 1Northwestern Polytechnical University, Northwestern Polytechnical University, School of Power and Energy, Xi'an 710072, China and The National Key Laboratory of Science and Technology on Advanced Light-Duty Gas-Turbine, Xi'an 710072, China.

Physical review. E
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PubMed
概括

一种新的空间压缩光谱正直角分解 (scSPOD) 方法从稀疏的数据中重建全球流模式. 这种技术显著降低了流体流量分析的计算成本和内存需求.

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科学领域:

  • 流体动力学 流体动力学
  • 计算力学 计算力学 计算力学
  • 数据科学数据科学数据科学

背景情况:

  • 从稀疏的数据中恢复连贯的流体结构是具有挑战性的.
  • 传统的光谱正正直角分解 (SPOD) 方法面临高计算成本和内存限制.
  • 不完整的数据采样阻碍了准确的流量诊断.

研究的目的:

  • 提出一个空间压缩的SPOD (scSPOD) 方法,用于从不统一的数据集中重建全球流模式.
  • 在计算成本和数据要求方面克服传统 SPOD 的局限性.
  • 为了从稀疏或不完整的流域数据中实现准确的流量诊断.

主要方法:

  • 整合光谱转换假设,聚类,压缩传感和优化.
  • 从空间子集中直接恢复SPOD模式,同时保留光谱特征.
  • 使用直接的数值模拟通过一个气的流量和尖端泄漏流量的大模拟的验证.

主要成果:

  • scSPOD准确地识别了整个域内的空间流动模式结构.
  • 对于低级第一阶模式的高定量重建精度.
  • 证明了显著的数据减少 (例如,高精度的数据<10%),具有光谱度度度值 (θ≥0.75).

结论:

  • scSPOD方法是可行且有效的,可以从稀疏的数据中重建流动模式.
  • scSPOD为复杂流体系统的流量诊断提供了低成本,高保真度的解决方案.
  • 该方法对数据采集有限或计算成本昂贵的应用具有重大潜力.