中药黄柏主要活性成分的光谱成像检测技术

为了实现中药主要活性成分的在体检测,运用光谱成像技术检测中药活性成分.使用自行开发的液晶光谱成像装置对中药黄柏的主要活性成分盐酸小檗碱进行了在体检测,选取紫外光源波长254 nm,获取了检品480～700 nm之间的连续荧光光谱图像.在分析检品光谱剖面图的基础上,以中国药品生物制品检定所提供的盐酸小檗碱标准品的光谱剖面图为依据,设计了高通滤波器得到了检品的特征光谱数据.对八种不同来源的市售黄柏饮片特征光谱,以及黄柏与其同科植物黄皮特征光谱的比较显示,使用本方法对中药进行定性、定量的检测,样品无需特殊处理,可在原生态的情况下进行;检测过程无损、实时;检测结果指纹特征明显.     

贝塞尔-高斯脉冲光束在色散介质中的时间和光谱特性

 对等衍射长度贝塞尔-高斯脉冲光束在色散介质中的时间和光谱特性作了研究,结果表明,通过选择适当的空间参数,贝塞尔-高斯脉冲光束沿轴上传输时,脉冲宽度不变。传输距离小于无衍射长度时,随衍射角增加,功率谱形状未变,脉冲波形保持不变;传输距离大于无衍射长度时,随衍射角增加,光谱由蓝移变为红移,脉冲展宽。     

8-羟基喹啉铋的合成、表征与光谱研究

8-羟基喹啉及其衍生物是以喹啉环为母体的化合物,具有较大的共轭π键结构,吸光系数高,分子中处于邻位的羟基O和杂环N原子上都含有孤对电子,与金属离子易形成双齿配位具有特殊光学特性的五员环配合物[1-3].金属铋被认为是安全稳定的绿色重金属元素,其化合物除了广泛应用于医学外,其配合物的用途正日益被开发[4-5].本文用元素分析仪、XRD、热重-差热、红外等手段对由8-羟基喹啉形成的铋配合物的组成和结构进行表征.并初步研究了生成物的光致发光性和紫外吸收光谱.     

抛物方程时间周期问题的有限元多格子动力学迭代

本文我们研究线性周期抛物方程的有限元多格子动力学迭代.多格子动力学迭代又称多重网格波形松弛,它是在函数空间中的一种迭代过程.对于由加速技术得到的多格子动力学迭代算子,我们通过计算周期函数的Fourier系数给出了新的谱表达式.从这些有用的表达式出发,我们推导了时间连续和离散格式的迭代收敛条件.数值实验进一步验证了本文的理论结果.     

Spectroscopic and theoretical studies on Cr (III), Mn (II) and Cu (II) complexes of hydrazone derived from picolinic hydrazide and O-vanillin and evaluation of biological potency

Trivalent Cr (III) and divalent of both Mn (II) and Cu (II) complexes containing hydrazone ligands derived from the condensation of picolinohydrazide with O-vanillin were synthesised and characterized by elemental analysis, spectral and magnetic measurements. The suggested octahedral structures were confirmed by applying DFT optimization and conformational studies. The thermal decomposition behaviour of Mn (II) complex is discussed. The evaluation of kinetic parameters (E_a, A, ∆H, ∆S and ∆G) of all thermal degradation stages have been evaluated using Coats-Redfern and Horowitz-Metzger approaches. The band gap results suggested that these complexes are semi-conductors and lie in same range of highly efficient photovoltaic materials. Antibacterial studies showed that higher activity of complexes than of ligands. Assay on the antioxidant activity (DPPH and SOD) of the above complexes revealed the high SOD-activity of Mn (II) complex and high DPPH-activity for ligand.     

A Theoretical Perspective of the Photochemical Potential in the Spectral Performance of Photovoltaic Cells

We present a novel theoretical approach to the problem of light energy conversion in thermostated semiconductor junctions. Using the classical model of a two-level atom, we deduced formulas for the spectral response and the quantum efficiency in terms of the input photons’ non-zero chemical potential. We also calculated the spectral entropy production and the global efficiency parameter in the thermodynamic limit. The heat transferred to the thermostat results in a dissipative loss that appreciably controls the spectral quantities’ behavior and, therefore, the cell’s performance. The application of the obtained formulas to data extracted from photovoltaic cells enabled us to accurately interpolate experimental data for the spectral response and the quantum efficiency of cells based on Si-, GaAs, and CdTe, among others.     

Non‐Hermitian perturbations of Hermitian matrix‐sequences and applications to the spectral analysis of the numerical approximation of partial differential equations

This article concerns the spectral analysis of matrix‐sequences which can be written as a non‐Hermitian perturbation of a given Hermitian matrix‐sequence. The main result reads as follows. Suppose that for every n there is a Hermitian matrix X_n of size n and that {X_n}_n～_λf, that is, the matrix‐sequence {X_n}_n enjoys an asymptotic spectral distribution, in the Weyl sense, described by a Lebesgue measurable function f; if $\Vert Y_n{\Vert }_2=o(\sqrt{n})$ with ‖·‖₂ being the Schatten 2 norm, then {X_n+Y_n}_n～_λf. In a previous article by Leonid Golinskii and the second author, a similar result was proved, but under the technical restrictive assumption that the involved matrix‐sequences {X_n}_n and {Y_n}_n are uniformly bounded in spectral norm. Nevertheless, the result had a remarkable impact in the analysis of both spectral distribution and clustering of matrix‐sequences arising from various applications, including the numerical approximation of partial differential equations (PDEs) and the preconditioning of PDE discretization matrices. The new result considerably extends the spectral analysis tools provided by the former one, and in fact we are now allowed to analyze linear PDEs with (unbounded) variable coefficients, preconditioned matrix‐sequences, and so forth. A few selected applications are considered, extensive numerical experiments are discussed, and a further conjecture is illustrated at the end of the article.