Journal of Applied Spectroscopy最新文献

The development of an operational noninvasive technique for assessing the state of the microcirculatory blood vessels in the cardiovascular system is a promising direction for the creation of equipment for the differential diagnosis of the causes of vascular dystonia and arterial hypertension. The feasibility of using diffuse reflection spectroscopy to determine the major parameters of the microvasculature is analyzed. A computational model for the formation of the spectral-temporal profile of local light diffuse reflection by pulsating blood-filled tissue is proposed based on the diffusion approximation of radiation transfer in scattering media and simplified analytical expressions describing the relationship between the shape of the photoplethysmogram and blood pressure. The structural features of the microcirculatory bed and the relationship of the parameters of the arterial vessels of the pulsating section of this bed to the systolic and diastolic blood pressure have been analyzed. It has been shown that taking account of the relative resistance to blood flow of different sections of the bloodstream and using a normalized photoplethysmogram to calculate intraluminal blood pressure in arterioles allow us to obtain an expression for the annular distensibility of arteriole walls. A technique for recording spectral-temporal diffuse reflection profiles and their modeling as well as forming the corresponding residual function and searching for its minimum are considered. The results obtained using a model for determining the parameters of the microvasculature taking into account equipment noise are presented. These results confirm the feasibility of creating a complex unit based on a miniature spectrophotometer, pulse oximeter, and pulse wave velocity sensors designed for the rapid noninvasive assessment of both the stiffness of the major arterial vessels and small arterial vessels of the microvasculature.

The primary, bioactive component of Cordyceps militaris, known as cordycepin (3'-deoxyadenosine), has been utilized extensively as a traditional medicinal ingredient and a nutritious diet in Asian nations. To determine the amount of cordycepin in the C. militaris, high-performance liquid chromatography (HPLC) is shown to be an effective, sensitive, and straightforward analytical technique. Other methods for estimating cordycepin include near infrared spectroscopy and capillary electrophoresis–mass spectrometry. The UV-Vis spectroscopy approach was used to quantify cordycepin, and the results were statistically confirmed and compared with an HPLC method. For linearity, repeatability, precision, reproducibility, limit of detection and limit of quantification, the method was verified. The established approach can be utilized for routine, quality control analysis of cordycepin, as it is easy to use, sensitive, accurate, precise, repeatable, and most importantly, cost-effective.

The extended cavity diode lasers were stabilized using the first and third derivatives obtained by the frequency modulation method from the hyperfine resonances of the ⁸⁷Rb D₂ transition line. The frequency stability values were measured as 3.1 × 10^-12, 5.6 × 10^-13, and 1.9 × 10^-12 for integration times of 1, 10², and 10⁴ s, respectively, using the first derivatives of F=1 → F′=1 and F=1 → F′=2 resonances. By use of the third derivatives of F=2 → F′=1,3 and F=2 → F′=2,3 cross-over resonances, 4.0 × 10^-12 − 1 s, 5.7 × 10^-13 − 10² s, 9.3 × 10^-13 − 10⁴ s frequency stability values were obtained. These values compared with the results of the previous study obtained by the Zeeman modulation method.

The quality of pork is largely influenced by moisture, fat, and protein. In the meat industry, the establishment of a fast and accurate prediction system is always welcomed. Near infrared spectroscopy (NIRS) can satisfy the requirements of the evaluation. An automatic routine based on support vector regression (SVR), a backpropagation neural network (BPNN), and principal component analysis–backpropagation neural network (PCA–BPNN) was developed to predict three components of pork using 16 combinations of pretreatment (convolution function-based moving average, detrending based on the standard normal variate, and multiplicative scatter correction). Model comparisons were implemented to evaluate the influence of pretreatment and calibration models on the prediction ability of models. The correction method and smoothing methods can significantly reduce the model prediction error. Most of the SVR models have high prediction accuracy and are suitable for predicting moisture and protein. The BPNN and PCA–BPNN are more suitable for dealing with nonlinearity between fat and NIR observations.

The effect of plasmonic nanoparticles (NPs) on the fluorescence and phosphorescence intensity of organic dye molecules was studied theoretically and experimentally. A theoretical model that takes into account nonradiative transfer of excitation energy from a molecule to an NP and the changes in the rates of spontaneous emission and light absorption by a molecule near an NP was proposed to calculate the luminescence intensity of a molecule in the presence of a plasmonic NP. Numerical estimates for an erythrosine molecule and a silver NP showed that the greatest increase in luminescence was observed at distances of 4–8 nm between the molecule and the NP surface. Experimentally observed changes in luminescence spectra and shortening of the erythrosine triplet state lifetime in poly(vinyl alcohol) films doped with silver NPs were explained using the proposed model.