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Spectroscopy|385 Article(s)
Identification of Shoe-Sole Materials Based on Two-Dimensional Correlation Infrared Spectroscopy
Jingshun Zhang, Lü Xiaobao, Nengbin Cai, and Kuidong Yu
Shoe soles leave trace evidence that can easily be extracted at crime scenes. The Fourier transform infrared spectroscopy, combined with statistical analysis, is highly significant for testing and identifying physical evidence from the sole. In this study, five sole samples that are primarily made of cis-butadiene rubber are selected for identification. The original spectra of the soles that the main materials are the same are identical and difficult to effectively distinguish; therefore, the fingerprint region spectra in the approximate range of 1800?650 cm-1 are selected for the second-derivative analysis and two-dimensional correlation spectral analysis. The results show that the differences in the spectra of the second derivatives are not significant between samples, whereas the number, position, and response order of the cross peaks in the two-dimensional correlation spectra differ; this can be used to distinguish different sole samples. Therefore, using two-dimensional correlation infrared spectroscopy, shoe soles are useful for identifying physical evidence. Thus, two-dimensional correlation spectroscopy has great potential for application in the field of forensic science. Shoe soles leave trace evidence that can easily be extracted at crime scenes. The Fourier transform infrared spectroscopy, combined with statistical analysis, is highly significant for testing and identifying physical evidence from the sole. In this study, five sole samples that are primarily made of cis-butadiene rubber are selected for identification. The original spectra of the soles that the main materials are the same are identical and difficult to effectively distinguish; therefore, the fingerprint region spectra in the approximate range of 1800?650 cm-1 are selected for the second-derivative analysis and two-dimensional correlation spectral analysis. The results show that the differences in the spectra of the second derivatives are not significant between samples, whereas the number, position, and response order of the cross peaks in the two-dimensional correlation spectra differ; this can be used to distinguish different sole samples. Therefore, using two-dimensional correlation infrared spectroscopy, shoe soles are useful for identifying physical evidence. Thus, two-dimensional correlation spectroscopy has great potential for application in the field of forensic science.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2024
- Vol. 61, Issue 9, 0930007 (2024)
Classification of Rosaceae Plants by Infrared Spectroscopy
Junwen Zheng, Xiaoxue Song, Yujia Gan, Zhongyu Wu, Zhongyu Yang, Quanhong Ou, Youming Shi, and Gang Liu
For the development and utilization of Rosaceae plant resources, it is of great significance to collect information on different Rosaceae plant species and clarify their family and generic relationships. In this study, leaves, petals, and stamens of different Rosaceae plant species are analyzed through Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis (PCA), hierarchical cluster analysis (HCA), and soft independent modelling of class analogy (SIMCA). The results revealed that the leaves, petals, and stamens of Rosaceae contained polysaccharides, proteins, lipids, calcium oxalate, lignin, and other components, while the petals and stamens contained phenols in addition. The FTIR spectra of different types of leaves are found to be similar, but the absorption peak intensities in the range of 1660?1000 cm-1 differed significantly. Upon using this range for PCA, the first two principal components could achieve more than 97% of the cumulative variance contribution rate. Using HCA, 11 species of the plant could be correctly classified at the subfamily level. Combined with the SIMCA discriminant model, in the classification of Rosaceae plants with different leaves, petals, and stamens, the correct classification rate reaches 96.08% with the full spectral data in the range of 4000?400 cm-1, and 100% accuracy can be achieved with the data in the range of 1800?800 cm-1. The results reveal that FTIR spectroscopy combined with statistical analysis and discriminant modeling is a suitable method for accurately classifying different species of Rosaceae plants at subfamily and genus levels. For the development and utilization of Rosaceae plant resources, it is of great significance to collect information on different Rosaceae plant species and clarify their family and generic relationships. In this study, leaves, petals, and stamens of different Rosaceae plant species are analyzed through Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis (PCA), hierarchical cluster analysis (HCA), and soft independent modelling of class analogy (SIMCA). The results revealed that the leaves, petals, and stamens of Rosaceae contained polysaccharides, proteins, lipids, calcium oxalate, lignin, and other components, while the petals and stamens contained phenols in addition. The FTIR spectra of different types of leaves are found to be similar, but the absorption peak intensities in the range of 1660?1000 cm-1 differed significantly. Upon using this range for PCA, the first two principal components could achieve more than 97% of the cumulative variance contribution rate. Using HCA, 11 species of the plant could be correctly classified at the subfamily level. Combined with the SIMCA discriminant model, in the classification of Rosaceae plants with different leaves, petals, and stamens, the correct classification rate reaches 96.08% with the full spectral data in the range of 4000?400 cm-1, and 100% accuracy can be achieved with the data in the range of 1800?800 cm-1. The results reveal that FTIR spectroscopy combined with statistical analysis and discriminant modeling is a suitable method for accurately classifying different species of Rosaceae plants at subfamily and genus levels.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2024
- Vol. 61, Issue 9, 0930006 (2024)
H2S Volume Fraction Monitoring Based on Characteristic Wavelength-Integrated Absorption Spectroscopy
Shengyu Hu, Fei Wang, and Haibin Cui
At present, producing clean gas through anaerobic digestion is one of the main means to treat food waste. As food waste contains sulfur, H2S gas will inevitably be generated during anaerobic digestion. H2S gas is inevitably generated during anaerobic digestion due to the presence of sulfur in food wastes. The produced H2S can lead to corrosion in pipelines and environmental pollution. Thus, it is essential to measure its volume fraction online. Traditional H2S volume fraction measurement methods, such as methylene blue spectrophotometry, iodometry, and electrochemical methods, involve complex operation, slow measurement speed, and can easily be affected by other gases. In addition, these methods cannot be used to guide the timely adjustment of the working conditions of the desulfurization system. Therefore, we develope an approach combined the ultraviolet absorption spectroscopy and continuous wavelength integration method for the online measurement of H2S volume fraction. The linear relationship between the characteristic value of the absorption spectrum integration and H2S volume fraction is obtained by selecting a 210?230 nm band as the characteristic band, with a fitting degree >0.999. To measure the volume fraction of H2S, we prepare 200×10-6?1200×10-6 of H2S standard gas in a laboratory, and the maximum error of the measured value is 3.1%. Finally, the measurement device is applied to the anaerobic digestion of kitchen wastes, and the field test is conducted. The results demonstrate that the instrument can accurately monitor the change in H2S volume fraction of biogas during the anaerobic digestion process. At present, producing clean gas through anaerobic digestion is one of the main means to treat food waste. As food waste contains sulfur, H2S gas will inevitably be generated during anaerobic digestion. H2S gas is inevitably generated during anaerobic digestion due to the presence of sulfur in food wastes. The produced H2S can lead to corrosion in pipelines and environmental pollution. Thus, it is essential to measure its volume fraction online. Traditional H2S volume fraction measurement methods, such as methylene blue spectrophotometry, iodometry, and electrochemical methods, involve complex operation, slow measurement speed, and can easily be affected by other gases. In addition, these methods cannot be used to guide the timely adjustment of the working conditions of the desulfurization system. Therefore, we develope an approach combined the ultraviolet absorption spectroscopy and continuous wavelength integration method for the online measurement of H2S volume fraction. The linear relationship between the characteristic value of the absorption spectrum integration and H2S volume fraction is obtained by selecting a 210?230 nm band as the characteristic band, with a fitting degree >0.999. To measure the volume fraction of H2S, we prepare 200×10-6?1200×10-6 of H2S standard gas in a laboratory, and the maximum error of the measured value is 3.1%. Finally, the measurement device is applied to the anaerobic digestion of kitchen wastes, and the field test is conducted. The results demonstrate that the instrument can accurately monitor the change in H2S volume fraction of biogas during the anaerobic digestion process.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2024
- Vol. 61, Issue 9, 0930005 (2024)
Using Laser Induced Breakdown Spectroscopy and Machine Learning to Identify Jiangxi Spring Tea Harvesting Periods
Lei Tao, Guangyuan Cai, Zhandong Cheng, Lin Huang, Xiuwen He, Jiang Xu, and Mingyin Yao
The harvesting period of spring tea significantly affects its economic value and consumer preference. To quickly identify different harvesting periods of spring tea, we employed laser-induced breakdown spectroscopy (LIBS) combined with machine learning algorithms. This approach was used to identify the before-brightness tea and before-rain tea of Mt. Lushan fog tea and Dog bull head tea. One hundred spectra were collected for each type of tea leaves and tea infusion, and the training and test sets were randomly divided in a ratio of 3∶2. The LIBS spectra were pre-processed with baseline correction and then 11 sets of spectral data were preferentially selected, and input into the linear discriminant analysis (LDA), support vector machines (SVM), K-nearest neighbor (KNN) and ensemble machine learning (EML) classification models for analysis, respectively. Findings showed that combining tea leaves and tea infusion data effectively identified the spring tea's harvesting period. This fusion approach exhibited superior stability and robustness. Specifically, the LDA model achieved recognition rates of 98.60% and 99.38% in the test sets for Mt. Lushan fog tea and Dog bull head tea, respectively. Therefore, this study demonstrates the feasibility of integrating LIBS with machine learning algorithms to discern different harvesting periods of spring tea. The harvesting period of spring tea significantly affects its economic value and consumer preference. To quickly identify different harvesting periods of spring tea, we employed laser-induced breakdown spectroscopy (LIBS) combined with machine learning algorithms. This approach was used to identify the before-brightness tea and before-rain tea of Mt. Lushan fog tea and Dog bull head tea. One hundred spectra were collected for each type of tea leaves and tea infusion, and the training and test sets were randomly divided in a ratio of 3∶2. The LIBS spectra were pre-processed with baseline correction and then 11 sets of spectral data were preferentially selected, and input into the linear discriminant analysis (LDA), support vector machines (SVM), K-nearest neighbor (KNN) and ensemble machine learning (EML) classification models for analysis, respectively. Findings showed that combining tea leaves and tea infusion data effectively identified the spring tea's harvesting period. This fusion approach exhibited superior stability and robustness. Specifically, the LDA model achieved recognition rates of 98.60% and 99.38% in the test sets for Mt. Lushan fog tea and Dog bull head tea, respectively. Therefore, this study demonstrates the feasibility of integrating LIBS with machine learning algorithms to discern different harvesting periods of spring tea.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2024
- Vol. 61, Issue 9, 0930004 (2024)
Quantitative Analysis Method of Metal Element in Lubricating Oil Based on Laser-Induced Breakdown Spectroscopy and Characteristic Wavelength Fast Selection
Yaohong Liu, Xiao Fu, Fajie Duan, Jinfan Huang, Yu Yan, and Xin Li
Metal elements in lubricating oil can directly reflect the wear status and position of the mechanical structure, and analyzing them quantitatively is an effective means of realizing fault warning and diagnosis. Based on laser-induced breakdown spectroscopy (LIBS) technology, the correlation coefficient method and threshold setting are used to narrow the range of feature wavelengths rapidly. The feature wavelengths are extracted accurately by the iterative predictive weighted partial least squares (IPW-PLS), uninformative variable elimination (UVE), and competitive adaptive reweighted sampling (CARS) methods. Finally, based on partial least squares (PLS) method, a quantitative analysis model of metal elements in lubricating oil is established to analyze metal elements in lubricating oil quantitatively. The experimental results show that the proposed CCPS method can improve the efficiency of characteristic wavelength selection and reduce the running time by more than 50%. The correlation coefficient RP2 and root-mean-square error prediction (RMSEP) values of CCPS-IPW-PLS are 0.9945 and 25.1678 μg/g, respectively. The RP2 and RMSEP values of CCPS-UVE are 0.9790 and 52.7363 μg/g, respectively, and the RP2 and RMSEP values of CCPS-CARS are 0.9939 and 25.0996 μg/g, respectively. These results prove the accuracy and efficiency of the proposed method. The approach provides a new way to perform the rapid, portable, and accurate detection of lubricating oil. Metal elements in lubricating oil can directly reflect the wear status and position of the mechanical structure, and analyzing them quantitatively is an effective means of realizing fault warning and diagnosis. Based on laser-induced breakdown spectroscopy (LIBS) technology, the correlation coefficient method and threshold setting are used to narrow the range of feature wavelengths rapidly. The feature wavelengths are extracted accurately by the iterative predictive weighted partial least squares (IPW-PLS), uninformative variable elimination (UVE), and competitive adaptive reweighted sampling (CARS) methods. Finally, based on partial least squares (PLS) method, a quantitative analysis model of metal elements in lubricating oil is established to analyze metal elements in lubricating oil quantitatively. The experimental results show that the proposed CCPS method can improve the efficiency of characteristic wavelength selection and reduce the running time by more than 50%. The correlation coefficient RP2 and root-mean-square error prediction (RMSEP) values of CCPS-IPW-PLS are 0.9945 and 25.1678 μg/g, respectively. The RP2 and RMSEP values of CCPS-UVE are 0.9790 and 52.7363 μg/g, respectively, and the RP2 and RMSEP values of CCPS-CARS are 0.9939 and 25.0996 μg/g, respectively. These results prove the accuracy and efficiency of the proposed method. The approach provides a new way to perform the rapid, portable, and accurate detection of lubricating oil.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2024
- Vol. 61, Issue 9, 0930003 (2024)
Nitrogen Fixation Reaction Path in Gas-Liquid Two-Phase Dielectric Barrier Discharge Using Emission Spectra
Minchen Zhu, Fangquan Wang, and Weidong Xia
To study the nitrogen fixation reaction path in micro-channel gas-liquid two-phase dielectric barrier discharge (DBD), we propose a method to determine DBD characteristics using emission spectra. Based on the experimental results obtained for gas-liquid two-phase DBD nitrogen fixation, the characteristic parameters and active particle composition of DBD plasma are derived using the measured emission spectra, facilitating an in-depth analysis of the DBD nitrogen fixation reaction path. The experimental results indicate that the proposed method can accurately determine the vibration temperature, rotation temperature, and active particle composition of N2 during the DBD nitrogen fixation reaction. This approach circumvents the plausible effects of traditional intrusive measurement methods on the nitrogen fixation reaction of DBD. Therefore, this study offers a novel, reliable, and practical method for investigating the gas-liquid two-phase DBD nitrogen fixation reaction path. To study the nitrogen fixation reaction path in micro-channel gas-liquid two-phase dielectric barrier discharge (DBD), we propose a method to determine DBD characteristics using emission spectra. Based on the experimental results obtained for gas-liquid two-phase DBD nitrogen fixation, the characteristic parameters and active particle composition of DBD plasma are derived using the measured emission spectra, facilitating an in-depth analysis of the DBD nitrogen fixation reaction path. The experimental results indicate that the proposed method can accurately determine the vibration temperature, rotation temperature, and active particle composition of N2 during the DBD nitrogen fixation reaction. This approach circumvents the plausible effects of traditional intrusive measurement methods on the nitrogen fixation reaction of DBD. Therefore, this study offers a novel, reliable, and practical method for investigating the gas-liquid two-phase DBD nitrogen fixation reaction path.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2024
- Vol. 61, Issue 9, 0930002 (2024)
Determination of Solanine and Nutrient Elements in Potatoes by Laser-Induced Breakdown Spectroscopy
Nan Jiang, Jingwen Li, Xiang Han, Yanting Wang, Fujia Yang, and Li Shen
As a common stem vegetable in daily life, potatoes not only contain rich carbohydrates but also contain minerals, lutein and other active substances beneficial to human health. Studies on the nutrients and solanine contained in the skin, flesh and sprout of potatoes are of great significance for food safety and potato quality assessment. First, the spectra of skin, flesh and sprout of potatoes are obtained by laser-induced breakdown spectroscopy (LIBS), and the nutrient elements and solanine in different parts of potatoes are analyzed. Second, the difference in spectral peak intensity between metallic and non-metallic elements in different parts of the potatoes is observed. Finally, the reason for the difference is discussed in terms of the local thermal equilibrium condition and the ratio of ion to atom densities by the calculation of the temperature and electron density of the laser-induced plasma. Results show that LIBS is a reliable and effective in situ and online test methods for the analysis of various elements in different potato parts. As a common stem vegetable in daily life, potatoes not only contain rich carbohydrates but also contain minerals, lutein and other active substances beneficial to human health. Studies on the nutrients and solanine contained in the skin, flesh and sprout of potatoes are of great significance for food safety and potato quality assessment. First, the spectra of skin, flesh and sprout of potatoes are obtained by laser-induced breakdown spectroscopy (LIBS), and the nutrient elements and solanine in different parts of potatoes are analyzed. Second, the difference in spectral peak intensity between metallic and non-metallic elements in different parts of the potatoes is observed. Finally, the reason for the difference is discussed in terms of the local thermal equilibrium condition and the ratio of ion to atom densities by the calculation of the temperature and electron density of the laser-induced plasma. Results show that LIBS is a reliable and effective in situ and online test methods for the analysis of various elements in different potato parts.
Laser & Optoelectronics Progress
- Publication Date: May. 10, 2024
- Vol. 61, Issue 9, 0930001 (2024)
Indoor CO2 Online Monitoring Based on Open-Path Tunable Diode Laser Absorption Spectroscopy
Qi Huang, Qing Wang, Kaitao Wang, Congshan Wang, Ruyue Cui, Hongpeng Wu, and Lei Dong
To investigate the variation in indoor carbon dioxide (CO2) volume fractions and their relationship with human activities, this study designs an open-path tunable diode laser absorption spectroscopy (TDLAS) sensing system to monitor indoor CO2 volume fractions. A distributed feedback (DFB) laser with a central wavelength of 2004 nm is employed as the excitation light source to measure the R(16) characteristic absorption line of carbon dioxide. The Levenberg-Marquardt method of nonlinear least squares fitting is employed to fit the measured spectra, allowing for volume fraction measurements without requiring calibration. Comparative measurements with a commercial XENSIVTM PAS CO2 sensor yield a high correlation (R2=0.89). The results indicate that the daily average indoor CO2 volume fraction is 4.63×10-4, slightly surpassing outdoor levels, whereas the fluctuation range of indoor CO2 volume fraction within a day is 3.86×10-4?5.66×10-4. Indoor CO2 volume fraction is volume fractions influenced by ventilation and indoor human activities, and the daily volume fraction trends are highly correlated with working hours. At a personnel density of 0.005 persons/m3, the growth rate of CO2 volume fraction is measured at 2.3×10-5 h-1. Therefore, timely ventilation is recommended for crowded indoor environments to prevent elevated CO2 volume fractions that may cause discomfort. To investigate the variation in indoor carbon dioxide (CO2) volume fractions and their relationship with human activities, this study designs an open-path tunable diode laser absorption spectroscopy (TDLAS) sensing system to monitor indoor CO2 volume fractions. A distributed feedback (DFB) laser with a central wavelength of 2004 nm is employed as the excitation light source to measure the R(16) characteristic absorption line of carbon dioxide. The Levenberg-Marquardt method of nonlinear least squares fitting is employed to fit the measured spectra, allowing for volume fraction measurements without requiring calibration. Comparative measurements with a commercial XENSIVTM PAS CO2 sensor yield a high correlation (R2=0.89). The results indicate that the daily average indoor CO2 volume fraction is 4.63×10-4, slightly surpassing outdoor levels, whereas the fluctuation range of indoor CO2 volume fraction within a day is 3.86×10-4?5.66×10-4. Indoor CO2 volume fraction is volume fractions influenced by ventilation and indoor human activities, and the daily volume fraction trends are highly correlated with working hours. At a personnel density of 0.005 persons/m3, the growth rate of CO2 volume fraction is measured at 2.3×10-5 h-1. Therefore, timely ventilation is recommended for crowded indoor environments to prevent elevated CO2 volume fractions that may cause discomfort.
Laser & Optoelectronics Progress
- Publication Date: Mar. 10, 2024
- Vol. 61, Issue 5, 0530004 (2024)
Evaluation of T91 Steel Aging Grade Based on Portable Laser-Induced Breakdown Spectroscopy Device
Weiye Lu, Meirong Dong, Kaijie Bai, Zihan Shang, Zhichun Li, Xiaoxuan Chen, Junbin Cai, and Jidong Lu
Microstructure and mechanical properties of heat-resistant steel will deteriorate during the service process. The real-time monitoring of the aging state is of great significance for safe operation and production. In this study, a portable laser-induced breakdown spectroscopy (LIBS) device is used to quickly diagnose the aging grade of T91 steel, while the obtained spectral features are dimensionally reduced and the modeling method is optimized. Principal component analysis (PCA) and linear discriminant analysis (LDA) are used to optimize and simplify the spectral features. Finally, after dimensionality reduction, the data are used to evaluate the aging grade model based on the K-nearest neighbor and the support vector machine (SVM) algorithms. Further, the influence of key parameter selection on the model performance is studied. The results show that the spectral data reduced by LDA can achieve a better clustering distribution and improve the accuracy of the evaluation model. In addition, the LDA-SVM model can achieve 94.58% accuracy, which is the highest among all the mentioned aging grade evaluation models. The result demonstrates that the modeling method can efficiently realize the aging grade evaluation of T91 steel based on portable LIBS. Microstructure and mechanical properties of heat-resistant steel will deteriorate during the service process. The real-time monitoring of the aging state is of great significance for safe operation and production. In this study, a portable laser-induced breakdown spectroscopy (LIBS) device is used to quickly diagnose the aging grade of T91 steel, while the obtained spectral features are dimensionally reduced and the modeling method is optimized. Principal component analysis (PCA) and linear discriminant analysis (LDA) are used to optimize and simplify the spectral features. Finally, after dimensionality reduction, the data are used to evaluate the aging grade model based on the K-nearest neighbor and the support vector machine (SVM) algorithms. Further, the influence of key parameter selection on the model performance is studied. The results show that the spectral data reduced by LDA can achieve a better clustering distribution and improve the accuracy of the evaluation model. In addition, the LDA-SVM model can achieve 94.58% accuracy, which is the highest among all the mentioned aging grade evaluation models. The result demonstrates that the modeling method can efficiently realize the aging grade evaluation of T91 steel based on portable LIBS.
Laser & Optoelectronics Progress
- Publication Date: Mar. 10, 2024
- Vol. 61, Issue 5, 0530003 (2024)
Information Encryption Based on Laser-Induced Breakdown Spectroscopy
Xiang Han, Lixing Yao, xin Zhang, Xiangyang Tian, Xing Su, Jinliang Lou, and Li Shen
In order to satisfy the requirements of information encryption security in the information era, this paper presents a method of information encryption based on laser-induced breakdown spectroscopy (LIBS) technology. The information to be encrypted was written on white paper with an aqueous solution prepared from zinc gluconate tablets and deionized water. By analyzing the LIBS spectra of white paper and of white paper coated with aqueous zinc gluconate solution, the spectral lines of Zn I at 328.23 nm, 472.22 nm, and 481.05 nm were used to decrypt the information. The LIBS spectra of different positions on the white paper containing the encrypted information were obtained by scanning, and the contrast of the spatial distribution of spectral intensity was improved by baseline correction, normalization, and spectral superposition, allowing the encrypted information to be interpreted more clearly and completely. The experimental results show that this method achieves efficient extraction of hidden information with zinc gluconate tablets commonly used in daily life, and has the advantages of high security, low cost, and convenient production. It provides a new idea for LIBS in the field of information encryption, and has value for certain potential applications. In order to satisfy the requirements of information encryption security in the information era, this paper presents a method of information encryption based on laser-induced breakdown spectroscopy (LIBS) technology. The information to be encrypted was written on white paper with an aqueous solution prepared from zinc gluconate tablets and deionized water. By analyzing the LIBS spectra of white paper and of white paper coated with aqueous zinc gluconate solution, the spectral lines of Zn I at 328.23 nm, 472.22 nm, and 481.05 nm were used to decrypt the information. The LIBS spectra of different positions on the white paper containing the encrypted information were obtained by scanning, and the contrast of the spatial distribution of spectral intensity was improved by baseline correction, normalization, and spectral superposition, allowing the encrypted information to be interpreted more clearly and completely. The experimental results show that this method achieves efficient extraction of hidden information with zinc gluconate tablets commonly used in daily life, and has the advantages of high security, low cost, and convenient production. It provides a new idea for LIBS in the field of information encryption, and has value for certain potential applications.
Laser & Optoelectronics Progress
- Publication Date: Mar. 10, 2024
- Vol. 61, Issue 5, 0530002 (2024)
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