Journal articles on the topic 'Spectra'
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Ibrahim, Amr, Adriana Predoi-Cross, and Chad Povey. "Handling techniques for channel spectra in synchrotron-based Fourier transform spectra." Canadian Journal of Physics 91, no. 11 (November 2013): 910–23. http://dx.doi.org/10.1139/cjp-2013-0050.
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Recently, the high radiance of synchrotron sources has been used to enhance FTIR spectrometer performance. However, excessive channel spectra when synchrotron sources are used degrade the quality of retrieved spectral parameters. We have investigated seven different techniques for handling channel spectra. These techniques were used to reduce channel spectra for a test group of seven samples of CO2 mixed with air recorded using the synchrotron source at the Canadian Light Source. The increases in signal to noise ratio (SNR) of spectra handled with each technique were calculated. SNR results showed that transmission spectra, produced using synthetic background spectra with simulated channel spectra, achieved the highest SNR improvement. However, when the spectra groups were fitted using a nonlinear least square fit algorithm, the technique using channel spectra fitting produced the smallest fitting residual. Moreover, the retrieved intensities and air broadening coefficients of 21 spectral lines showed that the spectral fitting technique produced the most accurate values as compared to the HITRAN 2008 database (Rothman et al. J. Quant. Spectrosc. Radiat. Transfer, 110, 533 (2009)). Although the spectral fitting technique was accurate in retrieving spectral line parameters, applying the technique at wider spectral ranges reduced this accuracy.
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Chauhan, H., and B. Krishna Mohan. "Effectiveness of Spectral Similarity Measures to Develop Precise Crop Spectra for Hyperspectral Data Analysis." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-8 (November 27, 2014): 83–90. http://dx.doi.org/10.5194/isprsannals-ii-8-83-2014.
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The present study was undertaken with the objective to check effectiveness of spectral similarity measures to develop precise crop spectra from the collected hyperspectral field spectra. In Multispectral and Hyperspectral remote sensing, classification of pixels is obtained by statistical comparison (by means of spectral similarity) of known field or library spectra to unknown image spectra. Though these algorithms are readily used, little emphasis has been placed on use of various spectral similarity measures to select precise crop spectra from the set of field spectra. Conventionally crop spectra are developed after rejecting outliers based only on broad-spectrum analysis. Here a successful attempt has been made to develop precise crop spectra based on spectral similarity. As unevaluated data usage leads to uncertainty in the image classification, it is very crucial to evaluate the data. Hence, notwithstanding the conventional method, the data precision has been performed effectively to serve the purpose of the present research work. The effectiveness of developed precise field spectra was evaluated by spectral discrimination measures and found higher discrimination values compared to spectra developed conventionally. Overall classification accuracy for the image classified by field spectra selected conventionally is 51.89% and 75.47% for the image classified by field spectra selected precisely based on spectral similarity. KHAT values are 0.37, 0.62 and Z values are 2.77, 9.59 for image classified using conventional and precise field spectra respectively. Reasonable higher classification accuracy, KHAT and Z values shows the possibility of a new approach for field spectra selection based on spectral similarity measure.
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Ivanov, Valentin D., Lodovico Coccato, Mark J. Neeser, Fernando Selman, Alessandro Pizzella, Elena Dalla Bontà, Enrico M. Corsini, and Lorenzo Morelli. "MUSE library of stellar spectra." Astronomy & Astrophysics 629 (September 2019): A100. http://dx.doi.org/10.1051/0004-6361/201936178.
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Context. Empirical stellar spectral libraries have applications in both extragalactic and stellar studies, and they confer an advantage over theoretical libraries because they naturally include all relevant chemical species and physical processes. In recent years we have seen a stream of new sets of high-quality spectra, but increasing the spectral resolution and widening the wavelength coverage means resorting to multi-order echelle spectrographs. Assembling the spectra from many pieces results in lower fidelity of their shapes. Aims. We aim to offer the community a library of high-signal-to-noise spectra with reliable continuum shapes. Furthermore, the use of an integral field unit (IFU) alleviates the issue of slit losses. Methods. Our library was built with the MUSE (Multi-Unit Spectroscopic Explorer) IFU instrument. We obtained spectra over nearly the entire visual band (λ ∼ 4800–9300 Å). Results. We assembled a library of 35 high-quality MUSE spectra for a subset of the stars from the X-shooter Spectral Library. We verified the continuum shape of these spectra with synthetic broadband colors derived from the spectra. We also report some spectral indices from the Lick system, derived from the new observations. Conclusions. We offer a high-fidelity set of stellar spectra covering the Hertzsprung-Russell diagram. These can be used for both extragalactic and stellar studies and demonstrate that the IFUs are excellent tools for building reliable spectral libraries.
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Zhou, Qian, Zhiyong Zou, and Lin Han. "Deep Learning-Based Spectrum Reconstruction Method for Raman Spectroscopy." Coatings 12, no. 8 (August 22, 2022): 1229. http://dx.doi.org/10.3390/coatings12081229.
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Raman spectroscopy, measured by a Raman spectrometer, is usually disturbed by the instrument response function and noise, which leads to certain measurement error and further affects the accuracy of substance identification. In this paper, we propose a spectral reconstruction method which combines the existing maximum a posteriori (MAP) method and deep learning (DL) to recover the degraded Raman spectrum. The proposed method first employs the MAP method to reconstruct the measured Raman spectra, so as to obtain preliminary estimated Raman spectra. Then, a convolutional neural network (CNN) is trained by using the preliminary estimated Raman spectra and the real Raman spectra to learn the mapping from the preliminary estimated Raman spectra to the real Raman spectra, so as to achieve a better spectral reconstruction effect than merely using the MAP method or a CNN. To prove the effectiveness of the proposed spectral reconstruction method, we employed the proposed method and some traditional spectral reconstruction methods to reconstruct the simulated and measured Raman spectra, respectively. The experimental results show that compared with traditional methods, the estimated Raman spectra reconstructed by the proposed method are closer to the real Raman spectra.
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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 (May 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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Zhang, Xiaodian, Kun Gao, Junwei Wang, Pengyu Wang, Zibo Hu, Zhijia Yang, Xiaobin Zhao, and Wei Li. "Target Detection Adapting to Spectral Variability in Multi-Temporal Hyperspectral Images Using Implicit Contrastive Learning." Remote Sensing 16, no. 4 (February 18, 2024): 718. http://dx.doi.org/10.3390/rs16040718.
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Hyperspectral target detection (HTD) is a crucial aspect of remote sensing applications, aiming to identify targets in hyperspectral images (HSIs) based on their known prior spectral signatures. However, the spectral variability resulting from various imaging conditions in multi-temporal hyperspectral images poses a challenge to both classical and deep learning (DL) methods. To overcome the limitations imposed by spectral variability, an implicit contrastive learning-based target detector (ICLTD) is proposed to exploit in-scene spectra in an unsupervised way. First, only prior spectra are utilized for explicit supervision, while an implicit contrastive learning module (ICLM) is designed to normalize the feature distributions of prior and in-scene spectra. This paper theoretically demonstrates that the ICLM can transfer the gradients from prior spectral features to those of in-scene spectra based on their feature similarities and differences. Because of transferred gradient signals, the ICLTD is regularized to extract similar representations for the prior and in-scene target spectra, while augmenting feature differences between the target and background spectra. Additionally, a local spectral similarity constraint (LSSC) is proposed to enhance the capability of scene adaptation by leveraging the spectral similarities among in-scene targets. To validate the performance of the ICLTD under spectral variability, multi-temporal HSIs captured under various imaging conditions are collected to generate prior spectra and in-scene spectra. Comparative evaluations against several DL detectors and classical methods reveal the superior performance of the ICLTD in achieving a balance between target detectability and background suppressibility under spectral variability.
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Feng, Wei Bin, Bin Yang, Hai Jing Cao, and Xing Ye Ni. "Study on Wave Spectra in South Coastal Waters of Jiangsu." Applied Mechanics and Materials 212-213 (October 2012): 193–200. http://dx.doi.org/10.4028/www.scientific.net/amm.212-213.193.
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The paper examined the spectral characteristics of shallow water waves, which was based on the wave data collected along the south coast of Jiangsu. It proposes a tentative spectra model which can work better than Joint North Sea Wave Project (JONSWAP)spectra. Both of the value of tentative spectral parameters (α and γ) increase with significant wave height and spectral peak frequency. According to a regression analysis, empirical equations are achieved, which is related to the parameters with significant wave height and spectral peak frequency. The study shows that the measured wave spectra can be represented by tentative spectra, and the fitting results in high-frequency tail of tentative spectra are better than that of JONSWAP spectrum with modified parameters.
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Sun, Yan, Wensheng Cai, and Xueguang Shao. "Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy." Molecules 27, no. 2 (January 11, 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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Dotsenko, M. A. "ABSORPTION AND LUMINESCENCE PROPERTIES OF ACID AND SALT FORMS OF MONONUCLEOTIDES, THEIR COMPONENTS AND COMPLEXES WITH D-MANNITOL AT ROOM TEMPERATURE." Biotechnologia Acta 17, no. 2 (April 30, 2024): 36–37. http://dx.doi.org/10.15407/biotech17.02.036.
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Aim. The aim of this work was to analyze and compare spectral properties of aqueous nucleotide solutions in conditions close to biological systems. We studied the absorption and luminescence (Ex and Em fluorescence and Em phosphorescence) of monoribonucleotides, their disodium salts, bases and nucleosides, and mixes with D-mannitol dissolved in water at room temperature. Methods. There were measured absorbance spectra using a Specord 210plus instrument and fluorescence excitation and emission and phosphorescence spectra using Horiba Fluoro Max 4+ instruments. Results. There were obtained the absorption, excitation, and luminescence spectra of aqueous solutions 1 mg/ml of nucleotides, their components, and mixtures with mannitol (in ratio 1:4). We observed a change in the ratio between the peaks of the spectra of acidic and salt forms of nucleotides. Conclusions. The observations confirmed that nucleotides, nucleosides, and nucleic acid bases exhibit luminescence at room temperature, which might be useful information for further research in this area. In addition, a comparative analysis of the spectra showed possible interactions between nucleotide molecules and mannitol.
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Hofstraat, J. W., and M. J. Latuhihin. "Correction of Fluorescence Spectra." Applied Spectroscopy 48, no. 4 (April 1994): 436–47. http://dx.doi.org/10.1366/000370294775269027.
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Several methods that can be applied to remove wavelength-dependent instrumental effects from fluorescence emission and excitation spectra have been investigated. Removal of such artifacts is necessary for the comparison of spectra that have been obtained on different instruments. Without correction, spectral line positions and relative intensities will be instrument-determined to a great extent. Furthermore, the application of adequate correction procedures provides excitation spectra which can be directly compared to absorption spectra; comparison of corrected excitation spectra and absorption spectra can be used to interpret the efficiency and pathways of radiative processes. Finally, corrected reflection spectra can be obtained, which can be directly transformed into absorption spectra and are useful for remote sensing applications. The methods that have been studied for the correction of emission spectra are the application of a standard lamp with calibrated spectral output and the use of fluorescence standards. The standards are a series of luminescent phosphors in polymer films and a solution of quinine sulfate dihydrate in perchloric acid, all provided with certified spectral emission values. For correction of excitation spectra, a quantum counter was applied. Several quantum counters were investigated. The best results were obtained for application of a mixture of the dyes basic blue and HITC, which provided good correction for the wavelength range 250 to 820 nm. No good quantum counters have been reported thus far for this (large) wavelength range. Correction for wavelength dependence of the excitation optics was realized by measurement of the excitation light intensity at the sample position and at the reference position with a Si photodiode. Correction factors for the excitation spectra were checked with a number of reference materials. Attention has also been paid to polarization-dependent effects that may occur in fluorescence spectra. The application of correction procedures was demonstrated for phytoplankton fluorescence spectra.
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Zhang, Shao Dong, Chun Ming Huang, Kai Ming Huang, Ye Hui Zhang, Yun Gong, and Quan Gan. "Vertical wavenumber spectra of three-dimensional winds revealed by radiosonde observations at midlatitude." Annales Geophysicae 35, no. 1 (January 13, 2017): 107–16. http://dx.doi.org/10.5194/angeo-35-107-2017.
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Abstract. By applying 12-year (1998–2009) radiosonde data over a midlatitude station, we studied the vertical wavenumber spectra of three-dimensional wind fluctuations. The horizontal wind spectra in the lower stratosphere coincide well with the well-known universal spectra, with mean spectral slopes of −2.91 ± 0.09 and −2.99 ± 0.09 for the zonal and meridional wind spectra, respectively, while the mean slopes in the troposphere are −2.64 ± 0.07 and −2.70 ± 0.06, respectively, which are systematically less negative than the canonical slope of −3. In both the troposphere and lower stratosphere, the spectral amplitudes (slopes) of the horizontal wind spectra are larger (less negative) in winter, and they are larger (less negative) in the troposphere than in the lower stratosphere. Moreover, we present the first statistical results of vertical wind fluctuation spectra, which revealed a very shallow spectral structure, with mean slopes of −0.58 ± 0.06 and −0.23 ± 0.05 in the troposphere and lower stratosphere, respectively. Such a shallow vertical wind fluctuation spectrum is considerably robust. Different from the horizontal wind spectrum, the slopes of the vertical wind spectra in both the troposphere and lower stratosphere are less negative in summer. The height variation of vertical wind spectrum amplitude is also different from that of the horizontal wind spectrum, with a larger amplitude in the lower stratosphere. These evident differences between the horizontal and vertical wind spectra strongly suggest they should obey different spectral laws. Quantitative comparisons with various theoretical models show that no existing spectral theories can comprehensively explain the observed three-dimensional wind spectra, indicating that the spectral features of atmospheric fluctuations are far from fully understood.
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Ferus, M., P. Kubelík, L. Petera, L. Lenža, J. Koukal, A. Křivková, V. Laitl, et al. "Main spectral features of meteors studied using a terawatt-class high-power laser." Astronomy & Astrophysics 630 (October 2019): A127. http://dx.doi.org/10.1051/0004-6361/201935816.
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Context. Meteor spectra are commonly interpreted using data from databases and tables. Several studies have demonstrated very sophisticated calculations of elemental compositions of meteoroid bodies based on the computation of synthetic meteor spectra or on the spectral analysis of airglow plasma containing evaporated, atomized, and ionized meteoroid matter. However, considering accuracy, reliability of computations, lack of laboratory experimental data in this field, as well as the complicated physical structure of meteor plasma, such qualitative assignment or quantitative calculations are still extensively discussed in the scientific community. Even on the laboratory level, many studies have shown the high complexity of the acquisition and interpretation of the data that are recorded with techniques of emission spectroscopy that are in fashion and philosophy similar to the spectral analysis of meteor plasma, that is, detection and quantification of the elements that are ablated from complicated multicomponent matrices. Aims. The current study is focused on the application of terawatt-class laser-induced breakdown spectroscopy (TC-LIBS) of real samples of chondritic meteorites. We recorded emission spectra with high resolution and high precision that contain spectral lines that are typical for real meteoric spectra. Experimental data were compiled in a form that is convenient for the meteoric spectra interpretation and calibration. Methods. TC-LIBS was carried out by a high-power terawatt-class laser facility, the Prague Asterix Laser System (PALS). The spectra were simultaneously recorded by an echelle high-resolution spectrograph in the UV/VIS spectral ranges and by a low-resolution spectrograph that was used for real observation of meteor spectra. We also present calculated synthetic spectra based on data from the NIST atomic spectra database. Results. We assembled etalon qualitative tables of major meteoric spectral features that can be used both for the spectral wavelength calibration of low-resolution observational instruments and for the exact interpretation of meteor spectra. The data are compared with real meteor spectra.
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Huang, Yuping, Yutu Yang, Ye Sun, Haiyan Zhou, and Kunjie Chen. "Identification of Apple Varieties Using a Multichannel Hyperspectral Imaging System." Sensors 20, no. 18 (September 8, 2020): 5120. http://dx.doi.org/10.3390/s20185120.
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This paper reports the nondestructive detection of apple varieties using a multichannel hyperspectral imaging system consisting of an illumination fiber and 30 detection fibers arranged at source–detector distances of 1.5–36 mm over the spectral range of 550–1650 nm. Spatially resolved (SR) spectra were obtained for 1500 apples, 500 each of three varieties from the same orchard to avoid environmental and geographical influences. Partial least squares discriminant analysis (PLSDA) models were developed for single SR spectra and spectral combinations to compare their performance of variety detection. To evaluate the effect of spectral range on variety detection, three types of spectra (i.e., visible region: 550–780 nm, near-infrared region: 780–1650 nm, full region: 550–1650 nm) were analyzed and compared. The results showed that the single SR spectra presented a different accuracy for apple variety classification, and the optimal SR spectra varied with spectral types. Spectral combinations had better accuracies for variety detection with best overall classifications of 99.4% for both spectral ranges in the NIR and full regions; however, the spectral combination could not improve the results over the optimal single SR spectra in the visible region. Moreover, the recognition of golden delicious (GD) was better than those of the other two varieties, with the best classification accuracy of 100% for three types of spectra. Overall, the multichannel hyperspectral imaging system provides more spatial-spectral information for the apples, and the results demonstrate that the technique gave excellent classifications, which suggests that the multichannel hyperspectral imaging system has potential for apple variety detection.
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Qi, Yingyong, and Bernd Weinberg. "Spectral Slope of Vowels Produced by Tracheoesophageal Speakers." Journal of Speech, Language, and Hearing Research 34, no. 2 (April 1991): 243–47. http://dx.doi.org/10.1044/jshr.3402.243.
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Spectra of vowels were analyzed to determine whether differences exist between the spectral slope of vowels produced by tracheoesophageal (TE) speakers and normal speakers and, if so, to quantify such differences. The linear predictive autocorrelation method was used to calculate smoothed spectra and the spectra were normalized with respect to a low frequency component. Comparisons between normalized spectral energy within a selected high frequency range revealed that energy within this frequency range for vowels produced by TE speakers was significantly higher than that produced by normal speakers. A least-square distance matching procedure was used to quantify speaker group differences in the spectral slope of vowels. Average spectra of vowels produced by the normal speakers could be matched to average spectra of vowels produced by the TE speakers by decreasing the spectral slope of their vowels by 2–3 dB/octave.
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Malofeev, Valerij M. "Pulsar Radio Spectra." International Astronomical Union Colloquium 160 (1996): 271–77. http://dx.doi.org/10.1017/s0252921100041695.
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AbstractA review of simultaneous and compiled spectra is presented, and a catalog of radio spectra for 340 pulsars reported. Pulsars with flux density measurements at three and more frequencies are included. Statistics of spectral indices and frequencies of the energy maximum and the break are presented, as well as the correlations with other pulsar parameters. The classification of 127 rich pulsar spectra has been made. Three main types of spectra are identified.
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Zhang, Yuling, and Yadong Wu. "Decomposition and Classification of Carbon Star Spectra." Academic Journal of Science and Technology 4, no. 3 (February 8, 2023): 116–19. http://dx.doi.org/10.54097/ajst.v4i3.4909.
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Automatic classification of stellar spectra is an important research component of astronomical data processing and is the basis for studying stellar evolution and parameter measurements. As a rare kind of stellar spectra, carbon star spectra put forward more efficient and accurate requirements for classification methods. The traditional manual classification methods have the disadvantages of slow speed and low accuracy, which can no longer meet the practical needs of automatic classification of massive stellar spectra, especially low signal-to-noise ratio stellar spectra, and machine learning algorithms have been widely applied to stellar spectral classification. A distinctive feature of stellar spectra is high data dimensionality, and dimensionality reduction can not only realize feature extraction, but also reduce the computational effort, which is the first task of spectral classification. Traditional linear dimensionality reduction methods such as principal component analysis reduce the spectra only based on the variance, and different types of spectra will appear crossover after projection into the low-dimensional feature space, while streamwise learning can produce excellent classification boundaries, which will avoid overlap and facilitate subsequent classification. In view of the high dimensionality of spectral data, we investigate the distribution of spectral data in high-dimensional space and the principle of dimensionality reduction of high-dimensional linear data by stream shape learning, compare the effect of two-dimensionality reduction methods, t - SNE and principal component analysis, on spectral data, and finally analyze the experimental results and compare and validate them using various machine learning classifiers. The algorithm is implemented using Python language and Scikit - learn third-party library to perform experiments on 1000 low signal-to-noise carbon star spectra from LAMOST, and finally achieve high accuracy automatic processing and classification of the spectral data. The experimental results show that for the dimensionality reduction processing of spectral data, the t - SNE method based on stream shape learning can recover the low-dimensional stream shape structure in the high-dimensional spectral data, and after feature extraction, satisfactory classification accuracy can be achieved on the test dataset using a machine learning classifier.
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Duignan, J. P., I. D. H. Oswald, I. C. Sage, L. M. Sweeting, K. Tanaka, T. Ishihara, K. Hirao, and G. Bourhill. "Do triboluminescence spectra really show a spectral shift relative to photoluminescence spectra?" Journal of Luminescence 97, no. 2 (May 2002): 115–26. http://dx.doi.org/10.1016/s0022-2313(01)00412-4.
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Kwaśniewicz, Michał, and Mirosław A. Czarnecki. "The Effect of Chain Length on Mid-Infrared and Near-Infrared Spectra of Aliphatic 1-Alcohols." Applied Spectroscopy 72, no. 2 (November 14, 2017): 288–96. http://dx.doi.org/10.1177/0003702817732253.
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Effect of the chain length on mid-infrared (MIR) and near-infrared (NIR) spectra of aliphatic 1-alcohols from methanol to 1-decanol was examined in detail. Of particular interest were the spectra-structure correlations in the NIR region and the correlation between MIR and NIR spectra of 1-alcohols. An application of two-dimensional correlation analysis (2D-COS) and chemometric methods provided comprehensive information on spectral changes in the data set. Principal component analysis (PCA) and cluster analysis evidenced that the spectra of methanol, ethanol, and 1-propanol are noticeably different from the spectra of higher 1-alcohols. The similarity between the spectra increases with an increase in the chain length. Hence, the most similar are the spectra of 1-nonanol and 1-decanol. Two-dimensional hetero-correlation analysis is very helpful for identification of the origin of bands and may guide selection of the best spectral ranges for the chemometric analysis. As shown, normalization of the spectra pronounces the intensity changes in various spectral regions and provides information not accessible from the raw data. The spectra of alcohols cannot be represented as a sum of the CH3, CH2, and OH group spectra since the OH group is involved in the hydrogen bonding. As a result, the spectral changes of this group are nonlinear and its spectral profile cannot be properly resolved. Finally, this work provides a lot of evidence that the degree of self-association of 1-alcohols decreases with the increase in chain length because of the growing meaning of the hydrophobic interactions. For butyl alcohol and higher 1-alcohols the hydrophobic interactions are more important than the OH OH interactions. Therefore, methanol, ethanol, and 1-propanol have unlimited miscibility with water, whereas 1-butanol and higher 1-alcohols have limited miscibility with water.
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Siebert, M. R., R. J. Foley, D. O. Jones, R. Angulo, K. Davis, A. Duarte, E. Strasburger, et al. "Investigating the diversity of Type Ia supernova spectra with the open-source relational data base kaepora." Monthly Notices of the Royal Astronomical Society 486, no. 4 (May 2, 2019): 5785–808. http://dx.doi.org/10.1093/mnras/stz1209.
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Abstract We present a public, open-source relational data base (we name kaepora) containing a sample of 4975 spectra of 777 Type Ia supernovae (SNe Ia). Since we draw from many sources, we significantly improve the spectra by inspecting these data for quality, removing galactic emission lines and cosmic rays, generating variance spectra, and correcting for the reddening caused by both MW and host-galaxy dust. With our data base, we organize this homogenized data set by 56 unique categories of SN-specific and spectrum-specific metadata. With kaepora, we produce composite spectra of subpopulations of SNe Ia and examine how spectral features correlate with various SN properties. These composite spectra reproduce known correlations with phase, light-curve shape, and host-galaxy morphology. With our large data set, we are also able to generate fine-grained composite spectra simultaneously over both phase and light-curve shape. The colour evolution of our composite spectra is consistent with other SN Ia template spectra, and the spectral properties of our composite spectra are in rough agreement with these template spectra with some subtle differences. We investigate the spectral differences of SNe Ia that occur in galaxies with varying morphologies. Controlling for light-curve shape, which is highly correlated with host-galaxy morphology, we find that SNe Ia residing in late-type and early-type galaxies have similar spectral properties at multiple epochs. However for SNe Ia in these different environments, their spectra appear to have Ca ii near-infrared triplet features that have slightly different strengths. Although this is apparent in the composite spectra and there is some difference in the populations as seen by individual spectra, this difference is not large enough to indicate differences in the underlying populations. All individual spectra and metadata are available in our open-source data base kaepora along with the tools developed for this investigation to facilitate future investigations of SN Ia properties.
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Mikołajewski, M., and J. Mikołajewska. "The Early Outburst Spectra of Nova V1500 Cygni." International Astronomical Union Colloquium 122 (1990): 161–62. http://dx.doi.org/10.1017/s0252921100068512.
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Nova Cygni 1975 (V1500 Cyg) was outstanding in several respects. It was the most luminous galactic nova ever observed, had the largest outburst amplitude, and had the fastest evolution with time.The spectra, with dispersion 28 A/mm and in spectral range λλ3560-5055 A, were obtained with the CCS spectrograph on 90 cm reflector at Toruń Observatory by the research group supervised by prof. A. WoszczyK. The CCS spectrograph was equipped with the 3.5 arcsec aperture Richardson’s image slicer and stars with known spectral energy distributions were observed on each night, so we were able to derive absolute energy distributions for the V1500 Cyg spectra. The calibration of the energy scale was performed by comparing synthetic B magnitudes calculated from our spectra with numerous published B photometry of the nova. The first spectra were obtained about 3h later than spectra reported by Boyarchuk (1977) and about 6h earlier than spectra discussed by Duerbeck and Wolf (1977); thus they are among the earliest spectra of the nova available. Simultaneously, the spectra correspond to the earliest state of spectral evolution of a nova ouburst yet observed. The pre-maximum spectral evolution of Nova V1500 Cyg is extremely fast. The spectra (Figures 1 and 2) secured on JD 2442654 are characterized by a very strong continuum and broad blueshifted absorption lines of OII, NII and CII of unusual strengths, as well as the Balmer series and Hel.
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Belabbaci, C. "Spectral radius of S-essential spectra." Matematychni Studii 54, no. 1 (October 6, 2020): 91–97. http://dx.doi.org/10.30970/ms.54.1.91-97.
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In this paper, we study the spectral radius of some S-essential spectra of a bounded linear operator defined on a Banach space. More precisely, via the concept of measure of noncompactness,we show that for any two bounded linear operators $T$ and $S$ with $S$ non zero and non compact operator the spectral radius of the S-Gustafson, S-Weidmann, S-Kato and S-Wolf essential spectra are given by the following inequalities\begin{equation}\dfrac{\beta(T)}{\alpha(S)}\leq r_{e, S}(T)\leq \dfrac{\alpha(T)}{\beta(S)},\end{equation}where $\alpha(.)$ stands for the Kuratowski measure of noncompactness and $\beta(.)$ is defined in [11].In the particular case when the index of the operator $S$ is equal to zero, we prove the last inequalities for the spectral radius of the S-Schechter essential spectrum. Also, we prove that the spectral radius of the S-Jeribi essential spectrum satisfies inequalities 2) when the Banach space $X$ has no reflexive infinite dimensional subspace and the index of the operator $S$ is equal to zero (the S-Jeribi essential spectrum, introduced in [7]as a generalisation of the Jeribi essential spectrum).
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Brown, B. M., M. S. P. Eastham, and D. K. R. McCormack. "Spectral concentration and perturbed discrete spectra." Journal of Computational and Applied Mathematics 86, no. 2 (December 1997): 415–25. http://dx.doi.org/10.1016/s0377-0427(97)00173-8.
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Kostrykin, Vadim, K. A. Makarov, and A. K. Motovilov. "Perturbation of spectra and spectral subspaces." Transactions of the American Mathematical Society 359, no. 1 (July 20, 2006): 77–89. http://dx.doi.org/10.1090/s0002-9947-06-03930-4.
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Laursen, K. B. "Essential spectra through local spectral theory." Proceedings of the American Mathematical Society 125, no. 5 (1997): 1425–34. http://dx.doi.org/10.1090/s0002-9939-97-03852-5.
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Myers, Daryl R., Keith Emery, and C. Gueymard. "Revising and Validating Spectral Irradiance Reference Standards for Photovoltaic Performance Evaluation." Journal of Solar Energy Engineering 126, no. 1 (February 1, 2004): 567–74. http://dx.doi.org/10.1115/1.1638784.
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In 1982, the American Society for Testing and Materials (ASTM) adopted consensus standards for direct-normal and hemispherical (“global”) tilted solar terrestrial spectra (ASTM E891/E892/G159). These standard spectra were intended to evaluate photovoltaic (PV) device performance and other solar-related applications. The International Standards Organization (ISO) and International Electrotechnical Commission (IEC) adopted these spectra as spectral standards ISO 9845-1 and IEC 60904-3. Additional information and more accurately representative spectra are needed by today’s PV community. Modern terrestrial spectral radiation models, knowledge of atmospheric physics, and measured radiometric quantities are applied to develop new reference spectra under consideration by ASTM.
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Sucuoğlu, Haluk, Murat Diclelil, and Alphan Nurtuğ. "An analytical assessment of elastic and inelastic response spectra." Canadian Journal of Civil Engineering 21, no. 3 (June 1, 1994): 386–95. http://dx.doi.org/10.1139/l94-042.
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A unified assessment of elastic and inelastic response spectra is presented. The effects of various system and excitation parameters on spectral response are investigated. Different spectral forms such as strength spectra, ductility reduction spectra, and damping reduction spectra are employed as graphical tools in the analytical evaluation. The applicability of the expressions for elastic and inelastic response spectra that are employed in seismic design codes is tested by using an ensemble of 21 earthquake accelerograms, all recorded on firm ground along the west coast of North America. New expressions are derived in order to evaluate the coupled effects of damping and ductility ratios on inelastic response spectra. Key words: elastic and inelastic response spectra, damping reduction factor, ductility reduction factor, seismic energy dissipation, strength ratio, mean plus one standard deviation.
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Rehman, Hafeez Ur, Valeria Tafintseva, Boris Zimmermann, Johanne Heitmann Solheim, Vesa Virtanen, Rubina Shaikh, Ervin Nippolainen, et al. "Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach." Molecules 27, no. 7 (April 1, 2022): 2298. http://dx.doi.org/10.3390/molecules27072298.
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Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures. Hence, a preclassification approach to separate infrared spectra for sparse data is needed. In this study, we propose a preclassification approach based on Multiplicative Signal Correction (MSC). The MSC approach was applied on human and the bovine knee cartilage broadband Fourier Transform Infrared (FTIR) spectra and on a sparse data subset comprising of only seven wavelengths. The goal of the preclassification was to separate spectra with analyte-rich signals (i.e., cartilage) from spectra with analyte-poor (and high-matrix) signals (i.e., water). The human datasets 1 and 2 contained 814 and 815 spectra, while the bovine dataset contained 396 spectra. A pure water spectrum was used as a reference spectrum in the MSC approach. A threshold for the root mean square error (RMSE) was used to separate cartilage from water spectra for broadband and the sparse spectral data. Additionally, standard noise-to-ratio and principle component analysis were applied on broadband spectra. The fully automated MSC preclassification approach, using water as reference spectrum, performed as well as the manual visual inspection. Moreover, it enabled not only separation of cartilage from water spectra in broadband spectral datasets, but also in sparse datasets where manual visual inspection cannot be applied.
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Qajar, Ch O., S. B. Kazymova, M. R. Menzeleyev, and A. S. Gasanova. "Low Resolution Rotational Spectra of Phenol." Applied Physics Research 10, no. 6 (November 30, 2018): 77. http://dx.doi.org/10.5539/apr.v10n6p77.
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The modeling of low-resolution (LR) microwave spectra of phenol C6H5OH molecule has been provided in the frequency regions of 0-700 GHz basing on high-resolution (HR) microwave spectral data. The frequency ranges of most intensive absorption level of low-resolution microwave spectra determined. The most intensive spectral lines forming spectra extremums are developed. The recommendations related to perspectives of practical use of achieved results are given.
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Diaz, Daniel, Alejandro Molina, and David W. Hahn. "Laser-Induced Breakdown Spectroscopy and Principal Component Analysis for the Classification of Spectra from Gold-Bearing Ores." Applied Spectroscopy 74, no. 1 (November 7, 2019): 42–54. http://dx.doi.org/10.1177/0003702819881444.
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Laser-induced breakdown spectroscopy (LIBS) and principal component analysis (PCA) were applied to the classification of LIBS spectra from gold ores prepared as pressed pellets from pulverized bulk samples. For each sample, 5000 single-shot LIBS spectra were obtained. Although the gold concentrations in the samples were as high as 7.7 µg/g, Au emission lines were not observed in most single-shot LIBS spectra, rendering the application of the usual ensemble-averaging approach for spectral processing to be infeasible. Instead, a PCA approach was utilized to analyze the collection of single-shot LIBS spectra. Two spectral ranges of 21 nm and 0.15 nm wide were considered, and LIBS variables (i.e., wavelengths) reduced to no more than three principal components. Single-shot spectra containing Au emission lines (positive spectra) were discriminated by PCA from those without the spectral feature (negative spectra) in a spectral range of less than 1 nm wide around the Au(I) 267.59 nm emission line. Assuming a discrete gold distribution at very low concentration, LIBS sampling of gold particles seemed unlikely; therefore, positive spectra were considered as data outliers. Detection of data outliers was possible using two PCA statistical parameters, i.e., sample residual and Mahalanobis distance. Results from such a classification were compared with a standard database created with positive spectra identified with a filtering algorithm that rejected spectra with an Au intensity below the smallest detectable analytical LIBS signal (i.e., below the LIBS limit of detection). The PCA approach successfully identified 100% of the data outliers when compared with the standard database. False identifications in the multivariate approach were attributed to variations in shot-to-shot intensity and the presence of interfering emission lines.
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Yuan, Hailong, Yanxia Zhang, Yue Wu, Yajuan Lei, Yiqiao Dong, Zongrui Bai, Guangwei Li, Haotong Zhang, and Yongheng Zhao. "A team spectral inspection platform based on ASERA." Proceedings of the International Astronomical Union 12, S325 (October 2016): 320–23. http://dx.doi.org/10.1017/s174392131601262x.
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AbstractCurrently large sky area spectral surveys like SDSS, 2dF, and LAMOST, using the new generation of telescopes and observatories, have provided massive spectral data sets for astronomical research. Most of the data can be automatically handled with pipelines, but visually inspection by human eyes is still necessary in several situations, like low SNR spectra, QSO recognition and peculiar spectra mining. Using ASERA, A Spectrum Eye Recognition Assistant, we can set up a team spectral inspection platform. On a preselected spectral data set, members of a team can individually view spectra one by one, find the best match template and estimate the redshift. Results from different members will be gathered and merged to raise the team work efficiency. ASERA mainly targets the spectra of SDSS and LAMOST fits data formats. Other formats can be supported with some conversion. Spectral templates from SDSS and LAMOST pipelines are embedded and users can easily add their own templates. Convenient cross identification interfaces with SDSS, SIMBAD, VIZIER, NED and DSS are also provided. An application example targeting finding strong emission line spectra from LAMOST DR2 is presented.
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Collins, Clarence O., C. Linwood Vincent, and Hans C. Graber. "A Statistical Method for Correlating Paired Wave Spectra." Journal of Atmospheric and Oceanic Technology 32, no. 11 (November 2015): 2130–46. http://dx.doi.org/10.1175/jtech-d-15-0040.1.
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AbstractOcean wave spectra are complex. Because of this complexity, no widely accepted method has been developed for the comparison between two sets of paired wave spectra. A method for intercomparing wave spectra is developed based on an example paradigm of the comparison of model spectra to observed spectra. Canonical correlation analysis (CCA) is used to investigate the correlation structure of the matrix of spectral correlations. The set of N ranked canonical correlations developed through CCA (here termed the r-sequence) is shown to be an effective method for understanding the degree of correlation between sets of paired spectral observation. A standard method for intercomparing sets of wave spectra based on CCA is then described. The method is elucidated through analyses of synthetic and real spectra that span a range of correlation from random to almost equal.
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Devaux, M. F., D. Bertrand, P. Robert, and M. Qannari. "Application of Principal Component Analysis on NIR Spectral Collection after Elimination of Interference by a Least-Squares Procedure." Applied Spectroscopy 42, no. 6 (August 1988): 1020–23. http://dx.doi.org/10.1366/0003702884430443.
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In NIR spectroscopy, multidimensional analyses such as Principal Component Analysis (PCA) may be applied to examine the similarity between spectra of natural products. However, such an approach is often limited by the effect of spectral interference due to water or particle size distribution of the samples. In the present work, the advantage of the elimination of such spectral interference before performing PCA was investigated. Unwanted component spectra were eliminated by a least-squares procedure. They were first orthogonalized and normalized by the Gram-Schmidt orthogonalization method. The subtraction coefficients were then assessed, similarly to principal component (PC) scores, by projection of the NIR spectra on the orthogonalized component spectra, and PCA was performed on the corrected spectra. This method was applied on an illustrative collection of wheat semolina conditioned in three levels of water content. Water was the component to be eliminated and had been previously modeled by two spectral patterns. These spectral patterns were used as the unwanted component spectra. PCA was applied independently before and after spectral correction of the collection of spectra and graphs obtained by the two procedures were compared. The squared correlation coefficient of the 3 first PC scores with water content was 0.979 before correction, with the 3 groups of water content appearing clearly on PCA graphs. After correction, the corresponding squared correlation coefficient for the 7 first PC scores was 0.016. PCA graphs obtained with corrected spectra also showed that the water effect was completely eliminated. At this moment, samples were separated according to their technological nature. The procedure developed may be useful in pattern recognition study and for automatic clustering of NIR spectra. It may also be applied in fields other than NIR spectroscopy.
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Igbinosun, Osazonamen J., Adam P. Bruckner, and Stephen E. Wood. "In Situ Measurements of Water Content for Sub-Surface Planetary Applications Using Near-Infrared Internal Reflection Spectroscopy (IRS) with a Multimode Optical Fiber." Applied Spectroscopy 74, no. 2 (August 23, 2018): 160–67. http://dx.doi.org/10.1177/0003702818781868.
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Results and analysis of internal reflection spectral absorbance experiments are reported for near-infrared (NIR) spectra obtained using an optical fiber sensor system. We present a preliminary study to diagnose the efficacy of our fiber optic system to observe and distinguish various phases of water, i.e., ice, liquid, and adsorbed. This study was motivated by the need for a technique capable of obtaining soil water content measurements in real time and in situ, at low humidity conditions for simulation studies of planetary bodies such as Mars. Spectral signatures were observed for the solid, liquid, and adsorbed phases of water. For all phases, peak absorbance at λ ≈1.45 and 1.94 μm was observed despite slight peak shifting due to dispersion effects. Dispersion effects commonly obscure spectra obtained with internal reflection spectroscopy for particular spectral regions. Here we report a spectral region with minimal distortions. Internal reflection spectra were compared directly to transmission spectra with only slight variations. Spectral matching was performed to determine sample penetration depths for unknown incidence angles. In general, relative absorbance and spectral shifting can distinguish spectra of the various phases of water.
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Czarnecki, Mirosław A. "Two-Dimensional Correlation Spectroscopy: The Power of Power Spectra." Applied Spectroscopy 74, no. 8 (June 8, 2020): 894–99. http://dx.doi.org/10.1177/0003702820931156.
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Power spectra are a powerful tool provided by two-dimensional correlation analysis. However, this tool is seldom used in practice. This work shows selected examples of using of the power spectra for the study of various kinds of samples with the aim to promote more common use of this tool. By examination of the power spectrum of specific sample, one can estimate the sensitivity of different molecular fragments on a given perturbation. Determination of the power spectra for smaller data subsets provides information on the dynamics of perturbation-induced spectral changes. If the experimental spectra of different samples in the same perturbation window are recorded, the comparison of the power spectra yields information on differences in the sensitivity of various samples on common perturbation. This possibility is particularly useful for studies of the spectra-structure correlations, interactions, and molecular dynamics. A comparison of the power spectra obtained by using different reference spectra provides information on the nature of spectral changes at different wavenumbers.
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Balmer, Paul. "Spectra, spectra, spectra – Tensor triangular spectra versus Zariski spectra of endomorphism rings." Algebraic & Geometric Topology 10, no. 3 (July 2, 2010): 1521–63. http://dx.doi.org/10.2140/agt.2010.10.1521.
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Burgess, J. M. "Is spectral width a reliable measure of GRB emission physics?" Astronomy & Astrophysics 629 (September 2019): A69. http://dx.doi.org/10.1051/0004-6361/201935140.
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The spectral width and sharpness of unfolded, observed gamma-ray burst (GRB) spectra have been presented as a new tool to infer physical properties about GRB emission via spectral fitting of empirical models. Following the tradition of the “line-of-death”, the spectral width has been used to rule out synchrotron emission in a majority of GRBs. This claim is investigated via reexamination of previously reported width measures. Then, a sample of peak-flux GRB spectra are fit with an idealized, physical synchrotron model. It is found that many spectra can be adequately fit by this model even when the width measures would reject it. Thus, the results advocate for fitting a physical model to be the sole tool for testing that model. Finally, a smoothly-broken power law is fit to these spectra allowing for the spectral curvature to vary during the fitting process in order to understand why the previous width measures poorly predict the spectra. It is found that the failing of previous width measures is due to a combination of inferring physical parameters from unfolded spectra as well as the presence of multiple widths in the data beyond what the Band function can model.
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Ji, Wei, Chao Liu, Licai Deng, Bo Zhang, Jiadong Li, Hao Tian, and Jiao Li. "All Spectral Type LAMOST Spectra Library (ATLAS)." Astrophysical Journal Supplement Series 265, no. 2 (April 1, 2023): 61. http://dx.doi.org/10.3847/1538-4365/acbf42.
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Abstract We present an empirical stellar spectra library, ATLAS, with resolution R ∼ 1800 and wavelength coverage from 3800–8700 Å. These spectra are homogeneously observed by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope and have been released in its DR5. ATLAS is separated into two groups, ATLAS-A and -T. The former contains 5584 spectra covering spectral types from O- to M-type and some special types such as A supergiant, blue horizontal-branch, and carbon stars. All of the spectra have absolutely calibrated fluxes at certain characteristic wavelengths corresponding to the optical passbands with accuracy better than 2.9% by comparing with PanSTARRS1 g-, r-, and i-band photometry. In addition, greater than 1% systematic uncertainty from the fundamental calibration should be considered separately. ATLAS-A contains 5342 spectra with spectral energy distribution effective temperature, surface gravity, and metallicity and 242 spectra with only the effective temperature and surface gravity. These parameters are consistent with the spectroscopic derived parameters of the same stars. Compared to current empirical libraries, ATLAS-A contains more cool giant stars, which may play a critical role in understanding the evolution of galaxies. ATLAS-T, on the other hand, contains 1118 spectral templates averaging over spectra with similar stellar parameters from ATLAS-A. It smooths out some special features in the individual spectra and can be used as a “standard” atlas of stellar spectra. Containing stellar spectra with almost all normal types, ATLAS may not only be a complete training data set for stellar spectra parameter determination but also an ideal legacy for stellar population synthesis.
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Tsuda, H., and J. Arends. "Raman Spectra of Human Dental Calculus." Journal of Dental Research 72, no. 12 (December 1993): 1609–13. http://dx.doi.org/10.1177/00220345930720121401.
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Raman spectra of human dental calculus have been observed for the first time by use of micro-Raman spectroscopy. The spectral features of calculus were influenced easily by heating caused by laser irradiation. Therefore, the measurements were carried out at relatively low power (5 mW, 1-μm spot size). The spectra could be characterized as phosphate vibrational bands due to the v1, v2, v 3, and v4 modes. The overall spectral features did not resemble those of pure minerals such as brushite, octacalcium phosphate, and hydroxyapatite. There were spectral differences among mixed calculus particles obtained from 18 adults, probably due to variations in local mineral composition and differences among patients. However, the averaged spectral features did not vary significantly with formation period from 1 to 6 months. Freshly removed and stored (5-11 months) calculus also gave comparable Raman spectra. Measurements on a fractured sample indicated that Raman spectra at saliva and dentin interfaces are nearly identical, and major mineral constituents may not vary significantly along the growth axis of calculus.
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Adibekyan, V., S. G. Sousa, N. C. Santos, P. Figueira, C. Allende Prieto, E. Delgado Mena, J. I. González Hernández, et al. "Benchmark stars, benchmark spectrographs." Astronomy & Astrophysics 642 (October 2020): A182. http://dx.doi.org/10.1051/0004-6361/202038793.
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Context. Gaia benchmark stars are selected to be calibration stars for different spectroscopic surveys. Very high-quality and homogeneous spectroscopic data for these stars are therefore required. We collected ultrahigh-resolution ESPRESSO spectra for 30 of the 34 Gaia benchmark stars and made them public. Aims. We quantify the consistency of the results that are obtained with different high- (R ~ 115 000), and ultrahigh- (R ~ 220 000) resolution spectrographs. We also comprehensively studied the effect of using different spectral reduction products of ESPRESSO on the final spectroscopic results. Methods. We used ultrahigh- and high-resolution spectra obtained with the ESPRESSO, PEPSI, and HARPS spectrographs to measure spectral line characteristics (line depth; line width; and equivalent width, EW) and determined stellar parameters and abundances for a subset of 11 Gaia benchmark stars. We used the ARES code for automatic measurements of the spectral line parameters. Results. Our measurements reveal that the same individual spectral lines measured from adjacent 2D (spectrum in the wavelength-order space) echelle orders of ESPRESSO spectra differ slightly in line depth and line width. When a long list of spectral lines is considered, the EW measurements based on the 2D and 1D (the final spectral product) ESPRESSO spectra agree very well. The EW spectral line measurements based on the ESPRESSO, PEPSI, and HARPS spectra also agree to within a few percent. However, we note that the lines appear deeper in the ESPRESSO spectra than in PEPSI and HARPS. The stellar parameters derived from each spectrograph by combining the several available spectra agree well overall. Conclusions. We conclude that the ESPRESSO, PEPSI, and HARPS spectrographs can deliver spectroscopic results that are sufficiently consistent for most of the science cases in stellar spectroscopy. However, we found small but important differences in the performance of the three spectrographs that can be crucial for specific science cases.
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Haaland, David M. "Synthetic Multivariate Models to Accommodate Unmodeled Interfering Spectral Components during Quantitative Spectral Analyses." Applied Spectroscopy 54, no. 2 (February 2000): 246–54. http://dx.doi.org/10.1366/0003702001949177.
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The analysis accuracy and precision of any multivariate calibration method will be severely degraded if unmodeled sources of spectral variation are present in the unknown sample spectra. A synthetic method for correcting errors generated by the presence of unmodeled components or other sources of unmodeled spectral variation has been developed. If the spectral shape of the unmodeled spectral component can be obtained and mathematically added in variable amounts to the original calibration spectra, then a new synthetic multivariate calibration model can be generated from the augmented data to accommodate the presence of the unmodeled source of spectral variation. The new method is demonstrated for a case where unmodeled temperature variations are present in the unknown sample spectra of dilute aqueous solutions of urea, creatinine, and NaCl. When constant-temperature partial least-squares (PLS) models are applied to spectra of variable-temperature samples, the standard errors of prediction (SEP) are approximately an order of magnitude higher than those of the original cross-validated SEPs of the constant-temperature PLS models. Synthetic models based upon constant-temperature data augmented with a classical least-squares (CLS) estimate of the spectral effect of temperature obtained from variable-temperature aqueous sample spectra are demonstrated to significantly reduce errors when predicting concentrations from spectra of solutions at variable-temperature. We demonstrate that the prediction precisions approach the original calibration precisions when the new synthetic PLS models are applied to variable-temperature solution spectra. Although spectrometer drift added bias errors to the analyte determinations, a method is demonstrated that can minimize the effect of long-term drift on prediction errors through the measurement and use of spectra obtained from a small subset of samples measured during both calibration and prediction. In addition, sample temperature can be predicted with high accuracy (±0.13 °C) with this new synthetic PLS modeling method without the need to recalibrate using actual variable-temperature sample data. Therefore, the synthetic method eliminates the need for expensive generation of new calibration samples and collection of their spectra. The method is quite general and can be applied by using any known source of spectral variation and used with any multivariate calibration method.
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Duan, Yanting, Chaodong Wu, Xiaodong Zheng, Yucheng Huang, and Jian Ma. "Coherence based on spectral variance analysis." GEOPHYSICS 83, no. 3 (May 1, 2018): O55—O66. http://dx.doi.org/10.1190/geo2017-0158.1.
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The eigenstructure-based coherence attribute is a type of efficient and mature tool for mapping geologic edges such as faults and/or channels in the 3D seismic interpretation. However, the eigenstructure-based coherence algorithm is sensitive to low signal-to-noise ratio seismic data, and the coherence results are affected by the dipping structures. Due to the large energy gap between the low- and high-frequency components, the low-frequency components play the principal role in coherence estimation. In contrast, the spectral variance balances the difference between the low- and high-frequency components at a fixed depth. The coherence estimation based on amplitude spectra avoids the effect of the time delays resulting from the dipping structures. Combining the spectral variance with the amplitude spectra avoids the effect of dipping structures and enhances the antinoise performance of the high-frequency components. First, we apply the short-time Fourier transform to obtain the time-frequency spectra of seismic data. Next, we compute the variance values of amplitude spectra. Then, we apply the fast Fourier transform to obtain the amplitude spectra of spectral variance. Finally, we calculate the eigenstructure coherence by using the amplitude spectra of spectral variance as the input. We apply the method to the theoretical models and practical seismic data. In the Marmousi velocity model, the coherence estimation using the amplitude spectra of the spectral variance as input shows more subtle discontinuities, especially in deeper layers. The results from field-data examples demonstrate that the proposed method is helpful for mapping faults and for improving the narrow channel edges’ resolution of interest. Therefore, the coherence algorithm based on the spectral variance analysis may be conducive to the seismic interpretation.
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Wang, Yuhao, Xuehu Liu, Pingping Zhang, Hu Lu, Zhengzheng Tu, and Huchuan Lu. "TOP-ReID: Multi-Spectral Object Re-identification with Token Permutation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 6 (March 24, 2024): 5758–66. http://dx.doi.org/10.1609/aaai.v38i6.28388.
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Multi-spectral object Re-identification (ReID) aims to retrieve specific objects by leveraging complementary information from different image spectra. It delivers great advantages over traditional single-spectral ReID in complex visual environment. However, the significant distribution gap among different image spectra poses great challenges for effective multi-spectral feature representations. In addition, most of current Transformer-based ReID methods only utilize the global feature of class tokens to achieve the holistic retrieval, ignoring the local discriminative ones. To address the above issues, we step further to utilize all the tokens of Transformers and propose a cyclic token permutation framework for multi-spectral object ReID, dubbled TOP-ReID. More specifically, we first deploy a multi-stream deep network based on vision Transformers to preserve distinct information from different image spectra. Then, we propose a Token Permutation Module (TPM) for cyclic multi-spectral feature aggregation. It not only facilitates the spatial feature alignment across different image spectra, but also allows the class token of each spectrum to perceive the local details of other spectra. Meanwhile, we propose a Complementary Reconstruction Module (CRM), which introduces dense token-level reconstruction constraints to reduce the distribution gap across different image spectra. With the above modules, our proposed framework can generate more discriminative multi-spectral features for robust object ReID. Extensive experiments on three ReID benchmarks (i.e., RGBNT201, RGBNT100 and MSVR310) verify the effectiveness of our methods. The code is available at https://github.com/924973292/TOP-ReID.
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Felsen, L. B. "Real spectra, complex spectra, compact spectra." Journal of the Optical Society of America A 3, no. 4 (April 1, 1986): 486. http://dx.doi.org/10.1364/josaa.3.000486.
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Bulajić, Borko Đ., Marijana Hadzima-Nyarko, and Gordana Pavić. "Vertical to Horizontal UHS Ratios for Low to Medium Seismicity Regions with Deep Soil atop Deep Geological Sediments—An Example of the City of Osijek, Croatia." Applied Sciences 11, no. 15 (July 23, 2021): 6782. http://dx.doi.org/10.3390/app11156782.
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The severity of vertical seismic ground motions is often factored into design regulations as a component of their horizontal counterparts. Furthermore, most design codes, including Eurocode 8, ignore the impact of local soil on vertical spectra. This paper investigates vertical pseudo-absolute acceleration spectral estimates, as well as the ratios of spectral estimates for strong motion in vertical and horizontal directions, for low to medium seismicity regions with deep local soil and deep geological sediments beneath the local soil. The case study region encompasses the city of Osijek in Croatia. New regional frequency-dependent empirical scaling equations are derived for the vertical spectra. According to these equations, for a 0.3 s spectral amplitude at deep soils atop deep geological sediments compared to the rock sites, the maximum amplification is 1.48 times. The spectra of vertical components of various real strong motions recorded in the surrounding region are compared to the empirical vertical response spectra. The new empirical equations are used to construct a Uniform Hazard Spectra for Osijek. The ratios of vertical to horizontal Uniform Hazard Spectra are generated, examined, and compared to Eurocode 8 recommendations. All the results show that local soil and deep geology conditions have a significant impact on vertical ground motions. The results also show that for deep soils atop deep geological strata, Eurocode 8 can underestimate the vertical to horizontal spectral ratios by a factor of three for Type 2 spectra while overestimating them by a factor of two for Type 1 spectra.
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Xu, Zhengyuan, Shengbo Chen, Peng Lu, Zibo Wang, Anzhen Li, Qinghong Zeng, and Liwen Chen. "Optimizing a Standard Spectral Measurement Protocol to Enhance the Quality of Soil Spectra: Exploration of Key Variables in Lab-Based VNIR-SWIR Spectral Measurement." Remote Sensing 14, no. 7 (March 23, 2022): 1558. http://dx.doi.org/10.3390/rs14071558.
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The method of proximal VNIR-SWIR (with a spectral region of 400–2500 nm) spectroscopy in a laboratory setting has been widely employed in soil property estimations. Increasing attention has been focused recently on establishing an agreed-upon protocol for soil spectral measurement, fueled by the recognition that studies carried out under different laboratory settings have made future data sharing and model comparisons difficult. This study aimed to explore the key factors in a lab-based spectral measurement procedure to provide recommendations for enhancing the spectra quality and promoting the development of the spectral measurement protocol. To this aim, with the support of the standard spectral laboratory at Jilin University, China, we designed and performed control experiments on four key factors—the light interference in the measurement course, soil temperature, soil moisture, and soil particle size—to quantify the variation in the spectra quality by the subsequent estimation accuracies of different estimation models developed with different spectra obtained from control groups. The results showed that (1) the soil–probe contact measurement derived the optimum spectra quality and estimation accuracy; however, close-non-contact measurement also achieved acceptable results; (2) sieving the soil sample into particle sizes below 1 mm and drying before spectral measurement effectively enhanced spectra quality and estimation accuracy; (3) the variation in soil temperature did not have a distinct influence on spectra quality, and the estimation accuracies of models developed based on soil samples at 20–50 °C were all acceptable. Moreover, a 30-min warm-up of the spectrometer and contact probe was found to be effective. We carried out a complete and detailed control experiment process, the results of which offer a guide for optimizing the process of laboratory-based soil proximal spectral measurement to enhance spectra quality and corresponding estimation accuracy. Furthermore, we present theoretical support for the development of the spectral measurement protocol. We also present optional guidance with relatively lower accuracy but effective results, which are save time and are low cost for future spectral measurement projects.
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John, C. M., and N. Kavya. "Integration of multispectral satellite and hyperspectral field data for aquatic macrophyte studies." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 581–88. http://dx.doi.org/10.5194/isprsarchives-xl-8-581-2014.
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Aquatic macrophytes (AM) can serve as useful indicators of water pollution along the littoral zones. The spectral signatures of various AM were investigated to determine whether species could be discriminated by remote sensing. In this study the spectral readings of different AM communities identified were done using the ASD Fieldspec® Hand Held spectro-radiometer in the wavelength range of 325–1075 nm. The collected specific reflectance spectra were applied to space borne multi-spectral remote sensing data from Worldview-2, acquired on 26th March 2011. The dimensionality reduction of the spectro-radiometric data was done using the technique principal components analysis (PCA). Out of the different PCA axes generated, 93.472 % variance of the spectra was explained by the first axis. The spectral derivative analysis was done to identify the wavelength where the greatest difference in reflectance is shown. The identified wavelengths are 510, 690, 720, 756, 806, 885, 907 and 923 nm. The output of PCA and derivative analysis were applied to Worldview-2 satellite data for spectral subsetting. The unsupervised classification was used to effectively classify the AM species using the different spectral subsets. The accuracy assessment of the results of the unsupervised classification and their comparison were done. The overall accuracy of the result of unsupervised classification using the band combinations Red-Edge, Green, Coastal blue & Red-edge, Yellow, Blue is 100%. The band combinations NIR-1, Green, Coastal blue & NIR-1, Yellow, Blue yielded an accuracy of 82.35 %. The existing vegetation indices and new hyper-spectral indices for the different type of AM communities were computed. Overall, results of this study suggest that high spectral and spatial resolution images provide useful information for natural resource managers especially with regard to the location identification and distribution mapping of macrophyte species and their communities.
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Boginskaya, Irina, Robert Safiullin, Victoria Tikhomirova, Olga Kryukova, Natalia Nechaeva, Naida Bulaeva, Elena Golukhova, et al. "Human Angiotensin I-Converting Enzyme Produced by Different Cells: Classification of the SERS Spectra with Linear Discriminant Analysis." Biomedicines 10, no. 6 (June 12, 2022): 1389. http://dx.doi.org/10.3390/biomedicines10061389.
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Angiotensin I-converting enzyme (ACE) is a peptidase widely presented in human tissues and biological fluids. ACE is a glycoprotein containing 17 potential N-glycosylation sites which can be glycosylated in different ways due to post-translational modification of the protein in different cells. For the first time, surface-enhanced Raman scattering (SERS) spectra of human ACE from lungs, mainly produced by endothelial cells, ACE from heart, produced by endothelial heart cells and miofibroblasts, and ACE from seminal fluid, produced by epithelial cells, have been compared with full assignment. The ability to separate ACEs’ SERS spectra was demonstrated using the linear discriminant analysis (LDA) method with high accuracy. The intervals in the spectra with maximum contributions of the spectral features were determined and their contribution to the spectrum of each separate ACE was evaluated. Near 25 spectral features forming three intervals were enough for successful separation of the spectra of different ACEs. However, more spectral information could be obtained from analysis of 50 spectral features. Band assignment showed that several features did not correlate with band assignments to amino acids or peptides, which indicated the carbohydrate contribution to the final spectra. Analysis of SERS spectra could be beneficial for the detection of tissue-specific ACEs.
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Zhang, Jiannan, Xiaoyan Chen, Yue Wu, and Xiangru Li. "An Automated Galaxy Spectra Recognition Method Basing on Spectral Lines Information." Proceedings of the International Astronomical Union 12, S325 (October 2016): 221–24. http://dx.doi.org/10.1017/s1743921316013193.
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AbstractFor the vast amounts of spectra produced by LAMOST, the pipeline basing on PCAZ method is limited by the bad flux calibration and low S/N data. This work focuses on the study of the efficient recognition methods of galaxy spectra of LAMOST basing on spectral lines information. The new method searches spectral lines and extracts the information of spectral lines (position, height, and width et al.) automatically. Using the spectral lines information which are less influenced by the quality of flux calibration and the S/N ratio, galaxy spectra are recognized with the redshift measured through spectral lines matching method. The experiment verified it is feasible for the LAMOST galaxy spectra: the correct recognition rate > 80% for the data with SNR_g > 5, and > 90% for the data with SNR_r > 5. Compared with the redshift of SDSS, the systematic error of our method is 0, and the standard deviation of the error is 0.0002.
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Taylor, Steven R., and Farid U. Dowla. "Spectral yield estimation of NTS explosions." Bulletin of the Seismological Society of America 81, no. 4 (August 1, 1991): 1292–308. http://dx.doi.org/10.1785/bssa0810041292.
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Abstract The yields of 299 NTS explosions have been estimated from Pn, Pg and Lg spectra (between 0.1 and 10 Hz) at four regional seismic stations. A spectral template matching technique is used where the spectra from an explosion of unknown yield are compared with the spectra of explosions of known yield. A matching function is defined that is a scaled inverse of the difference between the spectra from the known and unknown explosions. The yields from the seven closest matching explosions are then averaged to estimate the yield of the unknown event. The spectral matching technique appears to perform as well as standard regression techniques utilizing mb(Pn) and mb(Lg) measurements except that no geologic information (such as gas-filled porosity) is required. However, the spectral matching technique is only applicable to very well-calibrated test sites. The key to spectral matching is that the spectral shape is sensitive to the near-source geology. In addition to affecting the absolute spectral levels (i.e., coupling), the dynamic response of the near source material to the radiated shock wave is a major factor controlling the shape of the radiated spectra. The spectral shape can therefore be used as an indicator for predicting the coupling of an explosion, which can be subsequently used to predict its yield.
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Ridder, T., T. Warneke, and J. Notholt. "Source brightness fluctuation correction of solar absorption Fourier Transform mid infrared spectra." Atmospheric Measurement Techniques Discussions 4, no. 1 (January 20, 2011): 443–59. http://dx.doi.org/10.5194/amtd-4-443-2011.
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Abstract. Solar absorption Fourier Transform infrared spectrometry is considered a precise and accurate method for the observation of trace gases in the atmosphere. The precision and accuracy of such measurements are dependent on the stability of the light source. Fluctuations in the source brightness reduce the precision and accuracy of the trace gas concentrations, but cannot always be avoided. Thus, a strong effort is made within the community to reduce the impact of source brightness fluctuations by applying a correction on the spectra following the measurements. So far, it could be shown that the precision and accuracy of CO2 total column concentrations could be improved by applying a source brightness fluctuation correction to spectra in the near infrared spectral region. The analysis of trace gas concentrations obtained from spectra in the mid infrared spectral region is fundamental. However, spectra below 2000 cm−1 are generally considered uncorrectable, if they are measured with a MCT detector. Such measurements introduce an unknown offset to MCT interferograms, which prevents a source brightness fluctuation correction. Here, we show a method of source brightness fluctuation correction, which can be applied on spectra in the whole infrared spectral region including spectra measured with a MCT detector. We present a solution to remove the unknown offset in MCT interferograms allowing MCT spectra for an application of source brightness fluctuation correction. This gives an improvement in the quality of MCT spectra and we demonstrate an improvement in the retrieval of O3 profiles and total column concentrations. For a comparison with previous studies, we apply our source brightness fluctuation correction method on spectra in the near infrared spectral region and show an improvement in the retrieval of CO2 total column concentrations.