Spectroscopy Quantitative(光谱定量)研究综述
Spectroscopy Quantitative 光谱定量 - Background Magnetic resonance spectroscopy quantitatively monitors biomarkers of neuron-myelin coupling (N-acetylaspartate (NAA)), and inflammation (total creatine (tCr), total choline (tCho), myo-inositol (mI)) in the brain. [1] Based on the artificially configured DBP samples, this study used a near-infrared spectroscopy quantitative analysis model to predict the DBP content in liquor. [2] A NIR spectroscopy quantitative model was developed with partial least square (PLS) regression. [3] In order to further improve the performance of the near-infrared (NIR) spectroscopy quantitative model for detecting cyclic adenosine monophosphate (cAMP) content in red jujube, in this paper, support vector regression (SVR) is used for spectral analysis and compared with partial least squares (PLS) model results. [4] By using molecular dynamics simulations with an efficient enhanced sampling technique and in combination with nuclear magnetic resonance (NMR) spectroscopy quantitative structural information on α-2,8-linked sialic acids is presented. [5] RESULTS The thermogravimetric analysis and energy dispersive spectroscopy quantitative results suggested that the nanoparticles are biphasic in nature (bio-molecule + Ag0) and layered in structure, suggesting the formation of nanoparticles through a different mechanism than what was described in the literature. [6]背景 磁共振波谱定量监测大脑中神经元-髓磷脂偶联（N-乙酰天冬氨酸（NAA））和炎症（总肌酸（tCr）、总胆碱（tCho）、肌醇（mI））的生物标志物。 [1] 本研究基于人工配置的 DBP 样品，采用近红外光谱定量分析模型预测白酒中 DBP 的含量。 [2] 使用偏最小二乘 (PLS) 回归开发了 NIR 光谱定量模型。 [3] 为了进一步提高近红外（NIR）光谱定量模型检测红枣环磷酸腺苷（cAMP）含量的性能，本文采用支持向量回归（SVR）进行光谱分析，并与部分模型进行比较。最小二乘 (PLS) 模型结果。 [4] 通过使用具有高效增强采样技术的分子动力学模拟，并结合核磁共振 (NMR) 光谱，提供了关于 α-2,8 连接的唾液酸的定量结构信息。 [5] 结果 热重分析和能量色散光谱定量结果表明，纳米粒子本质上是双相的（生物分子 + Ag0）并且在结构上是分层的，这表明纳米粒子的形成机制与文献中描述的机制不同。 [6]
spectroscopy quantitative model 光谱定量模型
A NIR spectroscopy quantitative model was developed with partial least square (PLS) regression. [1] In order to further improve the performance of the near-infrared (NIR) spectroscopy quantitative model for detecting cyclic adenosine monophosphate (cAMP) content in red jujube, in this paper, support vector regression (SVR) is used for spectral analysis and compared with partial least squares (PLS) model results. [2]使用偏最小二乘 (PLS) 回归开发了 NIR 光谱定量模型。 [1] 为了进一步提高近红外（NIR）光谱定量模型检测红枣环磷酸腺苷（cAMP）含量的性能，本文采用支持向量回归（SVR）进行光谱分析，并与部分模型进行比较。最小二乘 (PLS) 模型结果。 [2]