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Journal articles on the topic 'Overlapping spectra'

Author: Grafiati

Published: 2 June 2025

Last updated: 19 July 2025

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1

Rex, A. F., M. A. Olson, and N. J. Silva. "The Improvement of Mossbauer Spectra by FIRO Deconvolution." Applied Spectroscopy 42, no. 5 (1988): 775–82. http://dx.doi.org/10.1366/0003702884428996.

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A deconvolution method similar to that used by Shimokoshi, Kanzaki, and Jones [Applied Spectroscopy 39, 1014 (1985)] has been used to study 57Fe Mossbauer spectra containing various mixtures of iron compounds. In all cases the spectra studied contained one or more sets of overlapping spectral lines. The resolution of these overlapping lines can often be improved by deconvolution to the point at which the integrated intensities of the deconvoluted peaks provide reliable information about sample concentrations. A comparison of the results which can be obtained for different deconvolution parameters and different degrees of overlapping is presented.

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2

Koryukina, E. V., and G. Revalde. "Separation of the overlapping spectral lines using derivative spectra." Russian Physics Journal 49, no. 4 (2006): 435–41. http://dx.doi.org/10.1007/s11182-006-0122-9.

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3

Preda, Dana-Maria, Mircea-Alexandru Comănescu, Victor Voicu, Nelu Grinberg, and Andrei-Valentin Medvedovici. "Peak Spectral Homogeneity in LC/DAD: Exploring Alternatives in Peak Purity Evaluations." Processes 12, no. 12 (2024): 2887. https://doi.org/10.3390/pr12122887.

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Spectral peak purity evaluations are often used to control inadequate selectivity issues appearing in liquid chromatography separations coupled with UV-Vis photodiode detection, despite known limitations related to (a) the lack of characteristic absorption bands in UV-Vis for target analytes and overlapping related impurities; (b) increased similarity between the spectral characteristics of co-eluting compounds; (c) large concentration differences between overlapping compounds; (d) perfect co-elution cases. We propose an alternative protocol to evaluate differences between spectra collected over a peak’s elution interval. After normalizing the acquired spectra, linear regression was applied between each pair of spectra, resulting in slope, intercepts, and correlation coefficient sets, from each comparison. The means and standard deviations of each variable are thus computed. An ellipsoid in the 3D Cartesian space illustrates these computations, having the mean coordinates as center and 2 × standard deviations of the variables as the axes. The volume of the ellipsoid should be related to the similarity between the compared spectra; a smaller volume indicates a higher spectral similarity. This approach was evaluated with respect to the (a) concentration of the analytes; (b) spectral acquisition parameters (spectral resolution, spectral frequency acquisition); (c) spectral similarity between overlapping peaks; (d) perfect co-elution situation; (e) influence of spectral processing (derivation, wavelength rationing), using test solutions of carbamazepine (a,b), acetyl cysteine and enalapril maleate (c), or nitrazepam and diazepam (d,e).

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4

Huang, J. B., and M. W. Urban. "Effect of Overlapping Bands on Intensities in ATR FT-IR Spectra." Applied Spectroscopy 46, no. 6 (1992): 1014–19. http://dx.doi.org/10.1366/0003702924124466.

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In this study, several spectra were simulated, and the effect of spectral resolution and intensity is compared for ATR and transmission measurements. The analysis of ATR spectra shows that the intensity differences become more pronounced with the increasing band intensities and decreasing separation of the bands. The intensity ratio differences in ATR spectra are due to the superposition of the asymmetric dispersion bands of the refractive index spectrum. The difference between the spectral features in an overlapping region in ATR and transmission measurements is illustrated, and it is shown that the optical dispersion effect can be effectively eliminated by converting an ATR spectrum into its absorbance counterpart with the use of the Kramers-Kronig transform.

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5

Schulze, H. Georg, Shreyas Rangan, Martha Z. Vardaki, Michael W. Blades, Robin F. B. Turner, and James M. Piret. "Critical Evaluation of Spectral Resolution Enhancement Methods for Raman Hyperspectra." Applied Spectroscopy 76, no. 1 (2021): 61–80. http://dx.doi.org/10.1177/00037028211061174.

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Overlapping peaks in Raman spectra complicate the presentation, interpretation, and analyses of complex samples. This is particularly problematic for methods dependent on sparsity such as multivariate curve resolution and other spectral demixing as well as for two-dimensional correlation spectroscopy (2D-COS), multisource correlation analysis, and principal component analysis. Though software-based resolution enhancement methods can be used to counter such problems, their performances often differ, thereby rendering some more suitable than others for specific tasks. Furthermore, there is a need for automated methods to apply to large numbers of varied hyperspectral data sets containing multiple overlapping peaks, and thus methods ideally suitable for diverse tasks. To investigate these issues, we implemented three novel resolution enhancement methods based on pseudospectra, over-deconvolution, and peak fitting to evaluate them along with three extant methods: node narrowing, blind deconvolution, and the general-purpose peak fitting program Fityk. We first applied the methods to varied synthetic spectra, each consisting of nine overlapping Voigt profile peaks. Improved spectral resolution was evaluated based on several criteria including the separation of overlapping peaks and the preservation of true peak intensities in resolution-enhanced spectra. We then investigated the efficacy of these methods to improve the resolution of measured Raman spectra. High resolution spectra of glucose acquired with a narrow spectrometer slit were compared to ones using a wide slit that degraded the spectral resolution. We also determined the effects of the different resolution enhancement methods on 2D-COS and on chemical contrast image generation from mammalian cell spectra. We conclude with a discussion of the particular benefits, drawbacks, and potential of these methods. Our efforts provided insight into the need for effective resolution enhancement approaches, the feasibility of these methods for automation, the nature of the problems currently limiting their use, and in particular those aspects that need improvement.

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6

Dinç, Erdal, Zehra Ceren Ertekin, and Asiye Üçer. "Simultanuous Quantitation of Amlodipine and Rosuvastatin by Artificial Neural Network." Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi 20, no. 1 (2025): 1–9. https://doi.org/10.29233/sdufeffd.1516938.

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Artificial neural network (ANN) is a useful tool in chemometrics to model the complex relationship in spectral data resulting in overlapping spectra, spectral interferences, non-linearity, and deviations from Lambert-Beer law. In this work, a new application of ANN was proposed for the simultaneous spectrophotometric quantification of amlodipine (AML) and rosuvastatin (ROS) in tablets despite their overlapping spectra. The relationship between the actual concentrations and absorption data of binary calibration samples was modeled by ANN. The validity of the method was proved by analyzing AML and ROS in their laboratory-made mixtures, intra and, inter-day samples, as well as standard addition samples. The developed method was then applied to the simultaneous quantitation of AML and ROS in commercial tablets and a good agreement was reported between label claim assay results.

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7

Chen, Li, Wee Chew, and Marc Garland. "Spectral Pattern Recognition of in Situ FT-IR Spectroscopic Reaction Data Using Minimization of Entropy and Spectral Similarity (MESS): Application to the Homogeneous Rhodium Catalyzed Hydroformylation of Isoprene." Applied Spectroscopy 57, no. 5 (2003): 491–98. http://dx.doi.org/10.1366/000370203321666489.

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An improved algorithm using minimization of entropy and spectral similarity (MESS) was tested to recover pure component spectra from in situ experimental Fourier transform infrared (FT-IR) reaction spectral data, which were collected from a homogeneous rhodium catalyzed hydroformylation of isoprene. The experimental spectra are complicated and highly overlapping because of the presence of multiple intermediate products in this reaction system. The traditional entropy minimization method fails to resolve real reaction mixture spectra, but MESS can successfully reconstruct pure component spectra of unknown intermediate products for real reaction systems by the addition of minimization of spectral similarity. The quantitative measure of spectral similarity between two spectra was given by their inner products. The results indicate that MESS is a stable and useful algorithm for spectral pattern recognition of highly overlapped experimental reaction spectra. Comparison is also made between MESS, entropy minimization, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA), interactive principle component analysis (IPCA), and orthogonal projection approach–alternating least squares (OPA-ALS).

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8

Egorova, Iryna, Johanna Michor, and Gerald Teschl. "Long-Time Asymptotics for the Toda Shock Problem: Non-Overlapping Spectra." Zurnal matematiceskoj fiziki, analiza, geometrii 14, no. 4 (2018): 406–51. http://dx.doi.org/10.15407/mag14.04.406.

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9

Sun, Yan, Wensheng Cai, and Xueguang Shao. "Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy." Molecules 27, no. 2 (2022): 452. http://dx.doi.org/10.3390/molecules27020452.

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Temperature-dependent near-infrared (NIR) spectroscopy has been developed and taken as a powerful technique for analyzing the structure of water and the interactions in aqueous systems. Due to the overlapping of the peaks in NIR spectra, it is difficult to obtain the spectral features showing the structures and interactions. Chemometrics, therefore, is adopted to improve the spectral resolution and extract spectral information from the temperature-dependent NIR spectra for structural and quantitative analysis. In this review, works on chemometric studies for analyzing temperature-dependent NIR spectra were summarized. The temperature-induced spectral features of water structures can be extracted from the spectra with the help of chemometrics. Using the spectral variation of water with the temperature, the structural changes of small molecules, proteins, thermo-responsive polymers, and their interactions with water in aqueous solutions can be demonstrated. Furthermore, quantitative models between the spectra and the temperature or concentration can be established using the spectral variations of water and applied to determine the compositions in aqueous mixtures.

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10

KAFKA, WOLF A. "Peripheral Coding by Graded Overlapping Reaction Spectra?." Annals of the New York Academy of Sciences 510, no. 1 Olfaction and (1987): 391–95. http://dx.doi.org/10.1111/j.1749-6632.1987.tb43567.x.

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11

Hu, Yaogai, Jinyang Liu, and Wei Li. "Resolution of overlapping spectra by curve-fitting." Analytica Chimica Acta 538, no. 1-2 (2005): 383–89. http://dx.doi.org/10.1016/j.aca.2005.02.024.

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12

Zhang, Xiu, Jian Zheng, Hong Gao, and Yun Zeng. "Nested genetic algorithm for resolving overlapping spectra." Fresenius' Journal of Analytical Chemistry 371, no. 3 (2001): 317–22. http://dx.doi.org/10.1007/s002160100943.

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13

Ma, Xin-Pei, G. R. Palmer, and J. D. MacArthur. "Element concentrations from overlapping X-ray spectra." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 22, no. 1-3 (1987): 49–54. http://dx.doi.org/10.1016/0168-583x(87)90292-8.

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14

S. Suprapto, Y. L. Ni’mah, A. S. Putri, V. Baroroh, and T. E. Purbaningtias. "BAYESIAN REGRESSION OF OVERLAPPING IBUPROFENPARACETAMOL UV SPECTRA." RASAYAN Journal of Chemistry 15, no. 04 (2022): 2938–45. http://dx.doi.org/10.31788/rjc.2022.1546961.

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Bayesian regression has been successfully applied to predict a full spectrum of ibuprofen and paracetamol binary mixture. The Bayesian regression models were constructed using 25 ibuprofen and paracetamol mixture with concentration combinations of 6, 8, 10, 12, and 14 ppm for each ibuprofen and paracetamol. The models were validated using synthetic test solutions to acquire the model’s accuracy and precision. The intercept, slopes, and model mean squared error indicated that paracetamol prediction on the test and sample solution was more reliable than ibuprofen. The recovery ranges and mean squared error for both the test solution and pain relief tablet confirm that the models have good accuracy in predicting ibuprofen and paracetamol binary mixture in the pharmaceutical drug. The measurement was carried out at wavelengths ranging from 220 to 270 nm.

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15

Pomerleau-Dalcourt, Natalie, Robert Weersink, and Lothar Lilge. "Partial Least Squares Based Decomposition of Five Spectrally Overlapping Factors." Applied Spectroscopy 59, no. 11 (2005): 1406–14. http://dx.doi.org/10.1366/000370205774783124.

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The development of a multi-sensory fiber-optic based fluence rate probe (MSP) for light monitoring and dosimetry during photodynamic therapy (PDT) created the need for a robust multivariate signal analysis algorithm capable of quantifying the intensity of five component spectra, representing the sensors, which display a large degree of spectral overlap. Partial least squares (PLS) analysis, as an option for such an analysis algorithm, was evaluated through simulations in the presence of three types of noise, which experimentally may limit the accuracy of PLS quantification of component spectra contributions. Random, or white noise, background was varied over a range of 0–15% relative intensity. A non-random (Gaussian) background vector was simulated, as an experimentally relevant spectral interferent, over a range of 0–7% relative intensity. Spectral variation was modeled by a spectral shift of ±1–5 nm. Procedures for selecting preferred combinations of fluorophores, with minimum possible spectral overlap, were developed. To illustrate the importance of this selection process, PLS performance results were compared for two possible combinations of five fluorophores, as well as for the combination of three fluorophores currently in experimental use with MSPs. Experimentally anticipated worst-case quantifications were identified for all three types of simulated noise (5% random background, 0.5% Gaussian background, and ±2 nm spectral shift). The effects of single and combined types of noise were evaluated by independently varying each type of simulated noise over the experimentally relevant range. The mean percentage error in determining the fluorophore contributions and hence quantification of the fluence rate were compared with the required performance standard of better than 10% error for optical power meters in medical use. The PLS algorithm provided an accuracy of 7 ± 2% for five fluorophores and 3.3 ± 0.8% for three fluorophores, indicating that PLS is an appropriate choice for this application.

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16

Cao, Jianfei, Wei Liu, Yongyu Feng, Jianhua Liu, and Yuanlong Ni. "Predicting nickel concentration in soil using fractional-order derivative and visible-near-infrared spectroscopy indices." PLOS ONE 19, no. 8 (2024): e0302420. http://dx.doi.org/10.1371/journal.pone.0302420.

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Accurate monitoring and estimation of heavy metal concentrations is an important process in the prevention and treatment of soil pollution. However, the weak correlation between spectra and heavy metals in soil makes it difficult to use spectroscopy in predicting areas with a risk of heavy metal pollution. In this paper, a method for detection of Ni in soil in eastern China using the fractional-order derivative (FOD) and spectral indices was proposed. The visible-near-infrared (Vis-NIR) spectra were preprocessed using the FOD (range: 0 to 2, interval: 0.1) to solve the problems of baseline drift and overlapping peaks in the original spectra. The product index (PI), ratio index (RI), sum index (SI), difference index (DI), normalized difference index (NDI), and brightness index (BI) were applied and compared. The results showed that the spectral detail increased as the FOD increased, and the interference of the baseline drift and overlapping peaks was eliminated as the spectral reflectance decreased. Furthermore, the FOD extracted the spectral sensitivity information more effectively and improved the correlation between the Vis-NIR spectra and the Ni concentration, and the NDI had a maximum correlation coefficient (r) of 0.803 for order 1.9. The estimation model based on the NDI dataset constructed after FOD processing had the best performance, with a validation accuracy RP2 of 0.735, RMSE of 3.848, and RPD of 2.423. In addition, this method is easy to carry out and suitable for estimating other heavy metal elements in soil.

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17

Benda, Aleš, Peter Kapusta, Martin Hof, and Katharina Gaus. "Fluorescence spectral correlation spectroscopy (FSCS) for probes with highly overlapping emission spectra." Optics Express 22, no. 3 (2014): 2973. http://dx.doi.org/10.1364/oe.22.002973.

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18

Crawford, Andrew M., Ben Huntsman, Monica Y. Weng, et al. "Abridged spectral matrix inversion: parametric fitting of X-ray fluorescence spectra following integrative data reduction." Journal of Synchrotron Radiation 28, no. 6 (2021): 1881–90. http://dx.doi.org/10.1107/s1600577521008419.

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Recent improvements in both X-ray detectors and readout speeds have led to a substantial increase in the volume of X-ray fluorescence data being produced at synchrotron facilities. This in turn results in increased challenges associated with processing and fitting such data, both temporally and computationally. Herein an abridging approach is described that both reduces and partially integrates X-ray fluorescence (XRF) data sets to obtain a fivefold total improvement in processing time with negligible decrease in quality of fitting. The approach is demonstrated using linear least-squares matrix inversion on XRF data with strongly overlapping fluorescent peaks. This approach is applicable to any type of linear algebra based fitting algorithm to fit spectra containing overlapping signals wherein the spectra also contain unimportant (non-characteristic) regions which add little (or no) weight to fitted values, e.g. energy regions in XRF spectra that contain little or no peak information.

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19

Windholz, Laurentius. "Comparison of Optogalvanic and Laser-Induced Fluorescence Spectroscopy." Photonics 11, no. 3 (2024): 279. http://dx.doi.org/10.3390/photonics11030279.

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When investigating complex atomic spectra, it may happen accidentally that two or even several transitions between different pairs of combining energy levels have nearly the same wavenumber, and the observed spectral lines are overlapping (blend situations). In such cases, investigations of hyperfine structures can be very helpful in the identification of the involved transitions. In this paper, two complicated blend situations within the spectra of lanthanide atoms (Praseodymium and Lanthanum) are discussed as examples. The experimental methods applied are optogalvanic and laser-induced fluorescence spectroscopy, combined with emission spectra gained via Fourier transform spectroscopy. It is shown that, in such cases, a combination of optogalvanic and laser-induced fluorescence detection is necessary to find all transitions contributing to the observed spectral signatures.

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20

Cernescu, Adrian, Thorsten Maly, and Thomas F. Prisner. "2D-REFINE spectroscopy: Separation of overlapping hyperfine spectra." Journal of Magnetic Resonance 192, no. 1 (2008): 78–84. http://dx.doi.org/10.1016/j.jmr.2008.02.018.

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21

GAO, H., T. LI, K. CHEN, W. LI, and X. BI. "Overlapping spectra resolution using non-negative matrix factorization." Talanta 66, no. 1 (2005): 65–73. http://dx.doi.org/10.1016/j.talanta.2004.09.017.

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22

Eakin, R. T. "Interference in transmission spectra of overlapping Lorentzian lines." Journal of Quantitative Spectroscopy and Radiative Transfer 39, no. 3 (1988): 225–36. http://dx.doi.org/10.1016/s0022-4073(88)90074-x.

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23

Charlesworth, J. M. "Deconvolution of overlapping relaxations in dynamic mechanical spectra." Journal of Materials Science 28, no. 2 (1993): 399–404. http://dx.doi.org/10.1007/bf00357816.

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24

Phillips, D. P., and S. E. Hall. "Auditory temporal gap detection for noise markers with partially overlapping and non-overlapping spectra." Hearing Research 174, no. 1-2 (2002): 133–41. http://dx.doi.org/10.1016/s0378-5955(02)00647-0.

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25

Hong, Sungtak, and Jun Shen. "Magnetic Field Dependence of Spectral Correlations between 31P-Containing Metabolites in Brain." Metabolites 13, no. 2 (2023): 211. http://dx.doi.org/10.3390/metabo13020211.

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Spectral correlations between metabolites in 31P magnetic resonance spectroscopy (MRS) spectra of human brain were compared at 3 and 7 Tesla, the two commonly used magnetic field strengths for clinical research. It was found that at both field strengths, there are significant correlations between 31P-containing metabolites arising from spectral overlap, and their downfield correlations are markedly altered by the background spectral baseline. Overall, the spectral correlations between 31P-containing metabolites are markedly reduced at 7 Tesla with the increased chemical shift dispersion and the decreased membrane phospholipid signal. The findings provide the quantitative landscape of pre-existing correlations in 31P MRS spectra due to overlapping signals. Detailed procedures for quantifying the pre-existing correlations between 31P-containing metabolites are presented to facilitate incorporation of spectral correlations into statistical modeling in clinical correlation studies.

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26

Morita, Shin-Ichi, and Yukihiro Ozaki. "Pattern Recognitions of Band Shifting, Overlapping, and Broadening Using Global Phase Description Derived from Generalized Two-Dimensional Correlation Spectroscopy." Applied Spectroscopy 56, no. 4 (2002): 502–8. http://dx.doi.org/10.1366/0003702021954953.

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In this paper we propose a new method for pattern recognitions of band shifting, overlapping, and broadening using a global phase map derived from generalized two-dimensional correlation spectroscopy (global 2D phase map). To obtain the distinct patterns for band shifting, overlapping, and broadening, original spectra are subjected to scaling so that the spectra after the scaling do not cross one another. After such pretreatment the band shifting creates the tilting of a correlation plane, the band overlapping yields four flat terraces, and the band broadening generates an asymmetric curved plane with respect to the diagonal line in the global 2D phase map. An example of the application of this method has been investigated using two bands due to the CH2 symmetric stretching and CN stretching vibrations in temperature-dependent infrared (IR) transmission spectra of an eleven-layer Langmuir–Blodgett (LB) film of 2-dodecyl-7,7,8,8-tetracyanoquinodimethane (dodecyl-TCNQ). The global 2D phase maps develop the clearly distinct patterns due to the shifting, overlapping, and broadening even if the shifting and broadening bands are overlapped with other bands.

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27

Bharucha, Jamshed J., and Keiko Stoeckig. "Priming of chords: Spreading activation or overlapping frequency spectra?" Perception & Psychophysics 41, no. 6 (1987): 519–24. http://dx.doi.org/10.3758/bf03210486.

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28

Dane, C. Brent, Rudolf Brüggemann, Robert F. Curl, Jerome V. V. Kasper, and Frank K. Tittel. "Multiwavenumber linearized diode laser spectra by overlapping frequency scans." Applied Optics 26, no. 1 (1987): 95. http://dx.doi.org/10.1364/ao.26.000095.

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29

Fu, Shouzhong, Zhong Wang, and Guangsheng Wei. "Three spectra inverse Sturm–Liouville problems with overlapping eigenvalues." Electronic Journal of Qualitative Theory of Differential Equations, no. 31 (2017): 1–7. http://dx.doi.org/10.14232/ejqtde.2017.1.31.

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30

Wang, Jian, Thomas Baer, Brian R. Glasberg, Michael A. Stone, Datian Ye, and Brian C. J. Moore. "Pitch perception of concurrent harmonic tones with overlapping spectra." Journal of the Acoustical Society of America 132, no. 1 (2012): 339–56. http://dx.doi.org/10.1121/1.4728165.

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31

Belyaev, O. F., V. V. Kochervinskii, and Yu V. Zelenev. "Separating overlapping bands in the IR spectra of polymers." Journal of Applied Spectroscopy 51, no. 1 (1989): 682–86. http://dx.doi.org/10.1007/bf00664367.

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32

Voráč, Jan, Lukáš Kusýn, and Petr Synek. "Deducing rotational quantum-state distributions from overlapping molecular spectra." Review of Scientific Instruments 90, no. 12 (2019): 123102. http://dx.doi.org/10.1063/1.5128455.

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33

Bowman, Michael K., and Alexei M. Tyryshkin. "Electron Nuclear Quadruple Resonance for Assignment of Overlapping Spectra." Journal of Magnetic Resonance 144, no. 1 (2000): 74–84. http://dx.doi.org/10.1006/jmre.2000.2043.

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34

Thompson, Avery. "Adapting infrared spectroscopy for protein amyloid mixtures." Scilight 2023, no. 12 (2023): 121107. http://dx.doi.org/10.1063/10.0017766.

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35

Şaka, Irfan, and Azmi Gençten. "A Theoretical Investigation of 2D MAXY-JRES NMR Spectroscopy of CDnCDm Groups." Zeitschrift für Naturforschung A 63, no. 5-6 (2008): 339–50. http://dx.doi.org/10.1515/zna-2008-5-614.

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There exists a variety of multiple-pulse NMR experiments for spectral editing of complex molecules in solution. Maximum quantum correlation NMR (MAXY NMR) spectroscopy is one of the techniques for distinguishing CHn groups by editing 1H NMR spectra. Spectral assignments of 2D homonuclear J-resolved NMR spectroscopy become too difficult, due to complex overlapping spectra. In order to overcome this problem a new technique called 2D MAXY-JRES NMR spectroscopy, which is the combination of MAXY NMR and homonuclear J-resolved NMR spectroscopy, is used. In this study, product operator description of 2D MAXY-JRES NMR spectroscopy is performed for ISnI’S’ m (I = I’ = ½ ; S = S’ = 1; n = 1,2, 3; m = 1, 2) multi-spin systems. Experimental suggestions are made and simulated spectra are presented for the 2D MAXY-JRES NMR experiment. Therefore, it is shown that 2D MAXY-JRES NMR spectroscopy can be used to distinguish CD, CD2 and CD3 groups from each other in CDnCDm groups.

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36

Yang, Jun-Ho, and Jack J. Yoh. "Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches." Applied Spectroscopy 72, no. 7 (2018): 1047–56. http://dx.doi.org/10.1177/0003702818765183.

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A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

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37

Zhao, Hailong, Shu Gan, Xiping Yuan, Lin Hu, Junjie Wang, and Shuai Liu. "Application of a Fractional Order Differential to the Hyperspectral Inversion of Soil Iron Oxide." Agriculture 12, no. 8 (2022): 1163. http://dx.doi.org/10.3390/agriculture12081163.

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Iron oxide is the main form of iron present in soils, and its accumulation and migration activities reflect the leaching process and the degree of weathering development of the soil. Therefore, it is important to have information on the iron oxide content of soils. However, due to the overlapping characteristic spectra of iron oxide and organic matter in the visible-near infrared, appropriate spectral transformation methods are important. In this paper, we first used conventional spectral transformation (continuum removal, CR; standard normal variate, SNV; absorbance, log (1/R)), continuous wavelet transform (CWT), and fractional order differential (FOD) transform to process original spectra (OS). Secondly, competitive adaptive reweighted sampling (CARS) was used to extract characteristic wavelengths. Finally, two regression models (backpropagation neural network, BPNN; support vector regression (SVR) were used to predict the content of iron oxide. The results show that the FOD can significantly improve the correlation with iron oxide compared with the CR, SNV, log (1/R) and CWT; the baseline drift and overlapping peaks decrease with increasing the order of FOD; the CARS algorithm based on 50th averaging can select more stable characteristic wavelengths; the FOD achieves better results regardless of the modelling method, and the model based on 0.5-order differential has the best prediction performance (R2 = 0.851, RMSE = 5.497, RPIQ = 3.686).

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38

Suprapto, Suprapto, Yatim Lailun Ni'mah, and Rifda Alifah Hisana. "Robust Regression Analysis of Full Overlapping Caffeine and Pyridoxine HCl UV-Vis Spectra in Pharmaceutical Tablet." Malaysian Journal of Fundamental and Applied Sciences 19, no. 4 (2023): 539–52. http://dx.doi.org/10.11113/mjfas.v19n4.2918.

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The determination of caffeine and pyridoxine HCl in medicinal tablets has been successfully carried out. The mixture of caffeine and pyridoxine solution produces UV-Vis with full overlapping spectra. The full overlapping spectra can not be analyzed using conventional multicomponent analysis, as they do not have a distinct maximum wavelength. This research proposed a full overlapping spectra analysis using Robust regression. The regression models used in this research were based on Huber, RANSAC, and Theil-Sen Regression. Robust regression is a regression method that was not sensitive to the presence of outliers from the input or output data. Robust Regression models were trained using 25 standard solutions of caffeine and pyridoxine HCl at varied ratios. The models were validated using test solutions with known concentration ratios. The validated models were applied to determine the concentration of medicinal tablets. From this study, the recovery values of medicinal tablets obtained using Huber, RANSAC, and Theil-Sen Regression methods for caffeine were 96.94%, 97.19%, and 96.16% respectively, while the recoveries of pyridoxine HCl were 122.65%, 104.89%, and 107.48%.

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Li, Shizhe, Jan Willem van der Veen, Li An, et al. "Cerebral phosphoester signals measured by 31P magnetic resonance spectroscopy at 3 and 7 Tesla." PLOS ONE 16, no. 3 (2021): e0248632. http://dx.doi.org/10.1371/journal.pone.0248632.

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Abnormal cell membrane metabolism is associated with many neuropsychiatric disorders. Free phosphomonoesters and phosphodiesters, which can be detected by in vivo 31P magnetic resonance spectroscopy (MRS), are important cell membrane building blocks. However, the quantification of phosphoesters has been highly controversial even in healthy individuals due to overlapping signals from macromolecule membrane phospholipids (MP). In this study, high signal-to-noise ratio (SNR) cerebral 31P MRS spectra were acquired from healthy volunteers at both 3 and 7 Tesla. Our results indicated that, with minimal spectral interference from MP, the [phosphocreatine (PCr)]/[phosphocholine (PC) + glycerophosphocholine (GPC)] ratio measured at 7 Tesla agreed with its value expected from biochemical constraints. In contrast, the 3 Tesla [PCr]/[PC+GPC] ratio obtained using standard spectral fitting procedures was markedly smaller than the 7 Tesla ratio and than the expected value. The analysis suggests that the commonly used spectral model for MP may fail to capture its complex spectral features at 3 Tesla, and that additional prior knowledge is necessary to reliably quantify the phosphoester signals at low magnetic field strengths when spectral overlapping is significant.

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Mullins, Oliver C., and Yifu Zhu. "First Observation of the Urbach Tail in a Multicomponent Organic System." Applied Spectroscopy 46, no. 2 (1992): 354–56. http://dx.doi.org/10.1366/0003702924125393.

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The exponential attenuation of electronic absorption in spectral regions removed from the absorption maxima, the “Urbach tail,” has been observed in a variety of materials and has been ascribed to thermal and structural disorder. Here, we report, to our knowledge, the first observation of the Urbach tail in a multicomponent organic system (the asphaltenes) which is due, in part, to the overlapping absorption spectra of the diverse component chromophores within the tail spectral region. The distribution of chromophores produces an unusually large, nonthermal width in the Urbach tail.

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Zhang, Yanjun, Otso Peräkylä, Chao Yan, et al. "A novel approach for simple statistical analysis of high-resolution mass spectra." Atmospheric Measurement Techniques 12, no. 7 (2019): 3761–76. http://dx.doi.org/10.5194/amt-12-3761-2019.

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Abstract. Recent advancements in atmospheric mass spectrometry provide huge amounts of new information but at the same time present considerable challenges for the data analysts. High-resolution (HR) peak identification and separation can be effort- and time-consuming yet still tricky and inaccurate due to the complexity of overlapping peaks, especially at larger mass-to-charge ratios. This study presents a simple and novel method, mass spectral binning combined with positive matrix factorization (binPMF), to address these problems. Different from unit mass resolution (UMR) analysis or HR peak fitting, which represent the routine data analysis approaches for mass spectrometry datasets, binPMF divides the mass spectra into small bins and takes advantage of the positive matrix factorization's (PMF) strength in separating different sources or processes based on different temporal patterns. In this study, we applied the novel approach to both ambient and synthetic datasets to evaluate its performance. It not only succeeded in separating overlapping ions but was found to be sensitive to subtle variations as well. Being fast and reliable, binPMF has no requirement for a priori peak information and can save much time and effort from conventional HR peak fitting, while still utilizing nearly the full potential of HR mass spectra. In addition, we identify several future improvements and applications for binPMF and believe it will become a powerful approach in the data analysis of mass spectra.

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Rossetti, Blair J., Steven A. Wilbert, Jessica L. Mark Welch, Gary G. Borisy, and James G. Nagy. "Semi-blind sparse affine spectral unmixing of autofluorescence-contaminated micrographs." Bioinformatics 36, no. 3 (2019): 910–17. http://dx.doi.org/10.1093/bioinformatics/btz674.

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Abstract Motivation Spectral unmixing methods attempt to determine the concentrations of different fluorophores present at each pixel location in an image by analyzing a set of measured emission spectra. Unmixing algorithms have shown great promise for applications where samples contain many fluorescent labels; however, existing methods perform poorly when confronted with autofluorescence-contaminated images. Results We propose an unmixing algorithm designed to separate fluorophores with overlapping emission spectra from contamination by autofluorescence and background fluorescence. First, we formally define a generalization of the linear mixing model, called the affine mixture model (AMM), that specifically accounts for background fluorescence. Second, we use the AMM to derive an affine nonnegative matrix factorization method for estimating fluorophore endmember spectra from reference images. Lastly, we propose a semi-blind sparse affine spectral unmixing (SSASU) algorithm that uses knowledge of the estimated endmembers to learn the autofluorescence and background fluorescence spectra on a per-image basis. When unmixing real-world spectral images contaminated by autofluorescence, SSASU greatly improved proportion indeterminacy as compared to existing methods for a given relative reconstruction error. Availability and implementation The source code used for this paper was written in Julia and is available with the test data at https://github.com/brossetti/ssasu.

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Sadrian, Mohammad R., Wendy M. Calvin, Andrew E. Perrin, Johann P. Engelbrecht, and Hans Moosmüller. "Variations in Infrared Complex Refractive Index Spectra of Surface Soils from Global Dust Entrainment Regions." Atmosphere 14, no. 4 (2023): 675. http://dx.doi.org/10.3390/atmos14040675.

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We explored spectral diversity in infrared (IR, 4–25 μm) imaginary (k) and real (n) indices of refraction (optical constants) for 26 surface soils that originated from global dust entrainment regions. The k spectra were derived from optical transmission spectra of KBr pellets containing dispersed dust and the n spectra were estimated with the subtractive Kramers–Kronig (SKK) method. We compared k and n obtained by this study with previously published values. Our optical constants from the KBr technique are comparable in magnitude and spectral shape to those from previous studies that used dust aerosols re-suspended in a chamber. This suggests that the SKK method can offer a reliable mechanism for measuring IR spectra of both optical constants for soils. The soils used here exhibit additional spectral variability compared with past studies. We note that the appearance and the shift in positions of the strongest absorption peaks are due to combinations of silicates with overlapping absorption, rather than being related to a single mineral. We note that all dust optical constants have substantially lower magnitudes compared to those of pure minerals. Our results can improve estimates of mineral dust radiative effects and support quantification of surface mineral estimates using satellite and ground-based remote sensing.

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Gamper, B., S. Khan, I. Siddiqui, and L. Windholz. "Modelling of emission spectra of Pr I by summarizing hyperfine patterns of overlapping spectral lines." European Physical Journal Special Topics 222, no. 9 (2013): 2171–78. http://dx.doi.org/10.1140/epjst/e2013-01993-9.

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Arrondo, José Luis R., Ibon Iloro, Julián Aguirre, and Félix M. Goñi. "A two‒dimensional IR spectroscopic (2D‒IR) simulation of protein conformational changes." Spectroscopy 18, no. 1 (2004): 49–58. http://dx.doi.org/10.1155/2004/406126.

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Two‒dimensional IR correlation spectroscopy (2D‒IR) is a novel method that provides the analysis of infrared spectra with the capacity to differentiate overlapping peaks and to distinguish between in‒phase and out‒of‒phase spectral responses. Artificial spectra originated from protein amide I band component parameters have been used to study their variation in the correlation maps. Using spectra composed of one, two or three Gaussian peaks, behaviour patterns of the bands in the synchronous and asynchronous maps have been originated, with changes in intensity, band position and bandwidth. Intensity changes produce high‒intensity spots in the synchronous spectra, whereas only noise is observed in the asynchronous spectra. Band shifting originates more complex patterns. In synchronous spectra, several spots are generated at the beginning and at the end of the shifting band. Also, characteristic asynchronous spectra with butterfly‒like shapes are formed showing the trajectory of the shift. Finally, synchronous maps corresponding to band broadening reveal several spots at peak inflection points, related to the zones with higher intensity variation. The asynchronous spectra are very complex but they follow a characteristic symmetric pattern. Furthermore, examples of maps obtained from polypeptides and proteins using temperature as the perturbing factor are interpreted in terms of the patterns obtained from artificial bands.

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Fernando, Sanduni, Jason Martineau, Erik Jorgensen, and Jordan Gerton. "Optimizing Point Spread Functions to Discern Highly Overlapping Emission Spectra." Microscopy and Microanalysis 27, S1 (2021): 864–67. http://dx.doi.org/10.1017/s1431927621003378.

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Dumitriu, Ioana, and Elliot Paquette. "Spectra of overlapping Wishart matrices and the Gaussian free field." Random Matrices: Theory and Applications 07, no. 02 (2018): 1850003. http://dx.doi.org/10.1142/s201032631850003x.

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Consider a doubly-infinite array of i.i.d. centered variables with moment conditions, from which one can extract a finite number of rectangular, overlapping submatrices, and form the corresponding Wishart matrices. We show that under basic smoothness assumptions, centered linear eigenstatistics of such matrices converge jointly to a Gaussian vector with an interesting covariance structure. This structure, which is similar to those appearing in [A. Borodin, Clt for spectra of submatrices of Wigner random matrices, Mosc. Math. J. 14(1) (2014) 29–38; A. Borodin and V. Gorin, General beta Jacobi corners process and the Gaussian free field, preprint (2013), arXiv:1305.3627; T. Johnson and S. Pal, Cycles and eigenvalues of sequentially growing random regular graphs, Ann. Probab. 42(4) (2014) 1396–1437], can be described in terms of the height function, and leads to a connection with the Gaussian Free Field on the upper half-plane. Finally, we generalize our results from univariate polynomials to a special class of planar functions.

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G. N., Manjunatha Reddy, and Stefano Caldarelli. "Demixing of Severely Overlapping NMR Spectra through Multiple-Quantum NMR." Analytical Chemistry 82, no. 8 (2010): 3266–69. http://dx.doi.org/10.1021/ac100009y.

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Chapados, Camille, Joanna Barwicz, and Ilona Gruda. "Separation of overlapping spectra from evolving systems using factor analysis." Biophysical Chemistry 51, no. 1 (1994): 71–80. http://dx.doi.org/10.1016/0301-4622(94)00030-1.

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Shao, Xueguang, Hua Gu, Jihui Wu, and Yunyu Shi. "Resolution of the NMR Spectrum Using Wavelet Transform." Applied Spectroscopy 54, no. 5 (2000): 731–38. http://dx.doi.org/10.1366/0003702001949997.

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A novel method for resolution of an overlapping nuclear magnetic resonance (NMR) spectrum using the wavelet transform (WT) is proposed. Due to the localization character in terms of both space and scale of the wavelet transform, an NMR spectrum can be decomposed into a series of localized contributions (details and approximations) at different resolution levels, which represent the spectral information of different resolutions. With amplification of the contributions at fine resolution level and then reconstruction (inverse transform), the resolution of the reconstructed NMR spectrum will increase. Therefore, the resolved spectrum can be obtained from a low-resolution spectrum or an overlapping spectrum. Simulated data sets and a spectrum of a biological sample (gramicidin-S) were investigated by this method. It was proven that resolution of NMR spectra can be greatly improved by this approach.

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