Compressed hyperspectral imaging is a powerful technique for satellite-borne and airborne sensors that can effectively shift the complex computational burden from the resource-constrained encoding side to a presumably more capable base-station decoder. Reconstruction algorithms play a pivotal role in compressive imaging systems. Traditional model-based reconstruction approaches are computationally burdensome and achieve limited success. Deep learning-based approaches, while improving in reconstruction accuracy and speed, depend heavily on data, which is a major challenge for satellite-borne hyperspectral compressed imaging. In this article, we combine the respective advantages of model-based and learning-based approaches in a distributed compressed hyperspectral sensing framework, employing linear mixed model assumptions and spectral library learning to simultaneously improve the reconstruction speed and accuracy without using a large amount of additional hyperspectral data. First, the relationship between the CS band and the key band is learned from the spectral library to ensure that the key band endmembers can be accurately predicted. Then, the joint horizontal and vertical difference operators are proposed to enhance the estimation of the initial values of abundance. Finally, the CS band endmembers and residuals are updated in the reconstruction module to deal with the endmember and abundance mismatch. Extensive experimental results on five real hyperspectral datasets demonstrate that the proposed spectral library learning, abundance initialization, and reconstruction strategy can effectively improve the compressed sensing reconstruction accuracy, outperforming the existing state-of-the-art methods.
{"title":"Distributed Compressed Hyperspectral Sensing Imaging Incorporated Spectral Unmixing and Learning","authors":"Hua Xiao, Zhongliang Wang, Xueying Cui, Liping Wang, Hongsheng Yang, Yingbiao Jia","doi":"10.1155/2022/7788657","DOIUrl":"https://doi.org/10.1155/2022/7788657","url":null,"abstract":"Compressed hyperspectral imaging is a powerful technique for satellite-borne and airborne sensors that can effectively shift the complex computational burden from the resource-constrained encoding side to a presumably more capable base-station decoder. Reconstruction algorithms play a pivotal role in compressive imaging systems. Traditional model-based reconstruction approaches are computationally burdensome and achieve limited success. Deep learning-based approaches, while improving in reconstruction accuracy and speed, depend heavily on data, which is a major challenge for satellite-borne hyperspectral compressed imaging. In this article, we combine the respective advantages of model-based and learning-based approaches in a distributed compressed hyperspectral sensing framework, employing linear mixed model assumptions and spectral library learning to simultaneously improve the reconstruction speed and accuracy without using a large amount of additional hyperspectral data. First, the relationship between the CS band and the key band is learned from the spectral library to ensure that the key band endmembers can be accurately predicted. Then, the joint horizontal and vertical difference operators are proposed to enhance the estimation of the initial values of abundance. Finally, the CS band endmembers and residuals are updated in the reconstruction module to deal with the endmember and abundance mismatch. Extensive experimental results on five real hyperspectral datasets demonstrate that the proposed spectral library learning, abundance initialization, and reconstruction strategy can effectively improve the compressed sensing reconstruction accuracy, outperforming the existing state-of-the-art methods.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"107 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74878455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laser-induced fluorescence (LIF) of certain edible oils (olive, mustard, sunflower, corn, sesame, peanut, rice bran, and flaxseed) and one unique aromatic oil (frankincense oil) have been studied using compact blue and violet lasers operating at 447 nm and 405 nm, respectively. LIF studies excited at these wavelengths have not been performed before, to our knowledge. The various features of the obtained spectra and their possible molecular origins have been discussed. The presence of vitamin E has been confirmed in corn, rice bran, peanut, sunflower, and frankincense oils, and the possible origin of the double peaks in the red region for olive oil has been explained.
{"title":"Laser-Induced Fluorescence Studies on Some Edible Oils and Aromatic Frankincense Oil Excited by Blue and Violet Diode Lasers at 447 nm and 405 nm","authors":"K. M. Abedin","doi":"10.1155/2022/2417545","DOIUrl":"https://doi.org/10.1155/2022/2417545","url":null,"abstract":"Laser-induced fluorescence (LIF) of certain edible oils (olive, mustard, sunflower, corn, sesame, peanut, rice bran, and flaxseed) and one unique aromatic oil (frankincense oil) have been studied using compact blue and violet lasers operating at 447 nm and 405 nm, respectively. LIF studies excited at these wavelengths have not been performed before, to our knowledge. The various features of the obtained spectra and their possible molecular origins have been discussed. The presence of vitamin E has been confirmed in corn, rice bran, peanut, sunflower, and frankincense oils, and the possible origin of the double peaks in the red region for olive oil has been explained.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"108 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80818685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaogang Jiang, Mingwang Zhu, Jinliang Yao, Yuxiang Zhang, Yande Liu
Soluble solids content (SSC) is a vital evaluation index for the internal quality of apples, and NIR spectroscopy is the preferred technique for predicting the SSC of apples. Due to the differences in fruits’ sizes, their SSC prediction models have poor robustness and low prediction accuracy, so it is important to eliminate the effects brought by the differences in fruit sizes to improve the accuracy of fruit sorting models. The NIR spectra of apples with different fruit sizes were collected by applying NIR spectroscopy online detection device, and after various preprocessing of the spectra, the partial least squares (PLS) models of apple SSC were established, respectively, and then the modeling set in the apple fruit size group of 75 mm–85 mm was used to predict the prediction set samples in the apple fruit size group of 65 mm–75 mm and 85 mm–95 mm, respectively. To better address the effects of apple size differences, data fusion techniques were used to perform an intermediate fusion of apple fruit diameter and spectra, firstly, the competitive adaptive reweighting algorithm (CARS) and the continuous projection algorithm (SPA) were used to select spectral variables and build their prediction models for apple SSC, respectively, and the results showed that the models built with 61 spectral variables selected by CARS had better performance, greatly reduced the amount of data involved in modeling, effectively simplified the model, and improved the stability of the model. The apple size variables were added to the wavelength variables selected by CARS, and the data were normalized to establish a PLS model of apple SSC with the normalized spectral and apple fruit diameter data, and the results showed that the size compensation model based on intermediate fusion had the best prediction performance, with the prediction set Rp of 0.886 for fruit diameter of 65 mm–75 mm, RMSEP of 0.536%, and its prediction set Rp was 0.913 and RMSEP was 0.497% for the fruit diameter of 85 mm–95 mm. Therefore, adding the fruit diameter variable to establish the size-compensated model of apple SSC can improve the prediction performance of the model.
可溶性固形物含量(SSC)是苹果内部品质的重要评价指标，近红外光谱是预测苹果可溶性固形物含量的首选技术。由于果实大小的差异，其SSC预测模型鲁棒性较差，预测精度较低，因此消除果实大小差异带来的影响对于提高果实分选模型的准确性非常重要。利用近红外光谱在线检测装置采集不同果粒大小苹果的近红外光谱，对光谱进行各种预处理后，分别建立苹果SSC的偏最小二乘(PLS)模型，然后利用75 mm - 85 mm苹果果粒大小组的建模集分别预测65 mm - 75 mm和85 mm - 95 mm苹果果粒大小组的预测集样本。为了更好地解决苹果大小差异的影响，采用数据融合技术对苹果果实直径和光谱进行中间融合，首先采用竞争自适应重加权算法(CARS)和连续投影算法(SPA)分别选择光谱变量并建立苹果SSC预测模型，结果表明，CARS选择的61个光谱变量所建立的模型具有较好的预测效果;大大减少了建模所涉及的数据量，有效地简化了模型，提高了模型的稳定性。将苹果大小变量加入CARS选择的波长变量中，对数据进行归一化处理，利用归一化光谱和苹果果径数据建立了苹果SSC的PLS模型，结果表明，基于中间融合的尺寸补偿模型预测效果最好，对果径65 mm ~ 75 mm的预测集Rp为0.886,RMSEP为0.536%;果实直径为85 mm ~ 95 mm的预测集Rp为0.913,RMSEP为0.497%。因此，加入果径变量建立苹果SSC的尺寸补偿模型可以提高模型的预测性能。
{"title":"Study on the Effect of Apple Size Difference on Soluble Solids Content Model Based on Near-Infrared (NIR) Spectroscopy","authors":"Xiaogang Jiang, Mingwang Zhu, Jinliang Yao, Yuxiang Zhang, Yande Liu","doi":"10.1155/2022/3740527","DOIUrl":"https://doi.org/10.1155/2022/3740527","url":null,"abstract":"Soluble solids content (SSC) is a vital evaluation index for the internal quality of apples, and NIR spectroscopy is the preferred technique for predicting the SSC of apples. Due to the differences in fruits’ sizes, their SSC prediction models have poor robustness and low prediction accuracy, so it is important to eliminate the effects brought by the differences in fruit sizes to improve the accuracy of fruit sorting models. The NIR spectra of apples with different fruit sizes were collected by applying NIR spectroscopy online detection device, and after various preprocessing of the spectra, the partial least squares (PLS) models of apple SSC were established, respectively, and then the modeling set in the apple fruit size group of 75 mm–85 mm was used to predict the prediction set samples in the apple fruit size group of 65 mm–75 mm and 85 mm–95 mm, respectively. To better address the effects of apple size differences, data fusion techniques were used to perform an intermediate fusion of apple fruit diameter and spectra, firstly, the competitive adaptive reweighting algorithm (CARS) and the continuous projection algorithm (SPA) were used to select spectral variables and build their prediction models for apple SSC, respectively, and the results showed that the models built with 61 spectral variables selected by CARS had better performance, greatly reduced the amount of data involved in modeling, effectively simplified the model, and improved the stability of the model. The apple size variables were added to the wavelength variables selected by CARS, and the data were normalized to establish a PLS model of apple SSC with the normalized spectral and apple fruit diameter data, and the results showed that the size compensation model based on intermediate fusion had the best prediction performance, with the prediction set Rp of 0.886 for fruit diameter of 65 mm–75 mm, RMSEP of 0.536%, and its prediction set Rp was 0.913 and RMSEP was 0.497% for the fruit diameter of 85 mm–95 mm. Therefore, adding the fruit diameter variable to establish the size-compensated model of apple SSC can improve the prediction performance of the model.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"10 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86649343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, Cu20-polyoxotungstate [Cu20Cl(OH)24(H2O)12(P8W48O184)]25− supported on a magnetic substrate was used as a high-performance green method for the reduction of nitrophenol compounds such as 4-nitrophenol (4-NP) and 2,4,6-trinitrophenol (2,4,6-TNP). [Fe3O4@SiO2-NH2-Cu20P8W48] as heterogeneous magnetic nanocatalyst was synthesized and characterized by FT-IR, SEM, TEM, VSM, and TGA. This nanocatalyst has an excellent efficiency in the reduction of nitrophenol compounds to aminophenol compounds. The UV-Vis absorption spectrum is used at different times to evaluate the progress of the reaction. Under optimal conditions, 100% conversion and selectivity in reduction of 4-NP and 2,4,6-TNP to 4-AP and 2,4,6-TAP were obtained, respectively. In addition, after the reaction, the [Fe3O4@SiO2-NH2-Cu20P8W48] was recovered using an external magnetic field and used for the next cycle. The results showed that the nanocatalyst can perform eight consecutive cycles without any significant decrease in efficiency. In the end, according to the results, the proposed mechanism for this reaction was reported.
{"title":"Nano-Polyoxotungstate [Cu20P8W48] Immobilized on Magnetic Nanoparticles as an Excellent Heterogeneous Catalyst Nanoreactors for Green Reduction of Nitrophenol Compounds","authors":"Reza Haddad, Ali Roostaie","doi":"10.1155/2022/7019037","DOIUrl":"https://doi.org/10.1155/2022/7019037","url":null,"abstract":"In this study, Cu20-polyoxotungstate [Cu20Cl(OH)24(H2O)12(P8W48O184)]25− supported on a magnetic substrate was used as a high-performance green method for the reduction of nitrophenol compounds such as 4-nitrophenol (4-NP) and 2,4,6-trinitrophenol (2,4,6-TNP). [Fe3O4@SiO2-NH2-Cu20P8W48] as heterogeneous magnetic nanocatalyst was synthesized and characterized by FT-IR, SEM, TEM, VSM, and TGA. This nanocatalyst has an excellent efficiency in the reduction of nitrophenol compounds to aminophenol compounds. The UV-Vis absorption spectrum is used at different times to evaluate the progress of the reaction. Under optimal conditions, 100% conversion and selectivity in reduction of 4-NP and 2,4,6-TNP to 4-AP and 2,4,6-TAP were obtained, respectively. In addition, after the reaction, the [Fe3O4@SiO2-NH2-Cu20P8W48] was recovered using an external magnetic field and used for the next cycle. The results showed that the nanocatalyst can perform eight consecutive cycles without any significant decrease in efficiency. In the end, according to the results, the proposed mechanism for this reaction was reported.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"18 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85604603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. A. Mesaik, A. Khalid, Ashraf N. Abdalla, S. Sultana, Abdel-Rahman Youssef, I. E. Ahmed, Y. Mohammed, H. Mirghani, Z. Rehman, H. Alhazmi, M. Al Bratty
Smokeless tobacco (SLT) has been reported to have deleterious effects on the health of its users. This study aims to analyze the constituents of locally collected SLT sample extracts (S1–S11) from Tabuk region of Saudi Arabia using GC-MS and investigate their cytotoxic effect on human gingival fibroblasts (hGFs), normal human fibroblasts (MRC5), and two cancer cell lines (HT29 and HepG2) using MTT assay. GC-MS results showed that pyridine, 3-(1-methyl-1H-pyrrol-2-yl)-, tetracyclo[4.4.1.1(7,10).0(2,5)]dodec-3-en-11-ol, and cotinine were found in S1, while ethyl iso-allocholate was traced in S2. Compounds 9,12-octadecadienoic acid, ethyl ester, 7-methyl-Z-tetradecen-1-ol acetate, cis-10-heptadecenoic acid and octadecanoic acid, ethyl ester, and nicotine traces were found in S4, while compound 3,7,11,15-tetramethyl-2-hexadecen-1-ol, tetradecamethyl-hexasiloxane, and phytol in S5. Additionally, octadecamethyl cyclononasiloxane, oleic acid, and trimethylsilyl ester were found in S6 and S9, respectively. Interestingly, extracts S4, S10, and S6 were the most cytotoxic to the normal fibroblasts (hGF and MRC5, with low selectivity index: <1), compared with doxorubicin and with their effect on the cancerous cells (HT29 and HepG2). Various components detected in SLT samples were carcinogenic, including nicotine and its derivatives, hexadecanoic acid, 1,2-benzenedicarboxylic acid, and octadecanoic acid. The present study showed that the cytotoxic and possibly carcinogenic effects of the SLT samples on gingiva and lung cells are attributed to many compounds and not only nicotine derivatives, all of which could create health threats for SLT users and lead to various types of cancers, including oral, lung, colon, and liver cancers.
据报道，无烟烟草(SLT)对使用者的健康有有害影响。本研究旨在利用气相色谱-质谱法分析沙特阿拉伯Tabuk地区当地采集的SLT样品提取物(S1-S11)的成分，并利用MTT法研究其对人牙龈成纤维细胞(hGFs)、正常人成纤维细胞(MRC5)和两种癌细胞(HT29和HepG2)的细胞毒性作用。GC-MS结果显示，S1中检出吡啶、3-(1-甲基- 1h -吡咯-2-基)-、四环[4.4.1.1(7,10).0(2,5)]、十二-3-烯-11-醇和可替宁，S2中检出异胆酸乙酯。化合物9,12-十八烯二酸、乙酯、7-甲基- z -十四烯-1-乙酸酯、顺-10-十七烯酸、十八烯酸、乙酯和烟碱的痕迹在S4中发现，而化合物3,7,11,15-四甲基-2-十六烯-1-醇、十四烯二甲基-六硅氧烷和叶绿醇在S5中发现。此外，在S6和S9中分别发现十八甲基环壬硅氧烷、油酸和三甲基硅氧烷酯。有趣的是，与阿霉素相比，提取物S4、S10和S6对正常成纤维细胞(hGF和MRC5)的细胞毒性最强，选择性指数较低:<1)，对癌细胞(HT29和HepG2)的作用也较弱。SLT样品中检测到的多种致癌成分包括尼古丁及其衍生物、十六烷酸、1,2-苯二甲酸和十八烷酸。目前的研究表明，SLT样品对牙龈和肺细胞的细胞毒性和可能的致癌作用归因于许多化合物，而不仅仅是尼古丁衍生物，所有这些化合物都可能对SLT使用者造成健康威胁，并导致各种类型的癌症，包括口腔癌、肺癌、结肠癌和肝癌。
{"title":"GC-MS and Cellular Toxicity Studies on Smokeless-Tobacco Show Alerting Cytotoxic effect on Human Gingiva and Lung Fibroblasts","authors":"M. A. Mesaik, A. Khalid, Ashraf N. Abdalla, S. Sultana, Abdel-Rahman Youssef, I. E. Ahmed, Y. Mohammed, H. Mirghani, Z. Rehman, H. Alhazmi, M. Al Bratty","doi":"10.1155/2022/4005935","DOIUrl":"https://doi.org/10.1155/2022/4005935","url":null,"abstract":"Smokeless tobacco (SLT) has been reported to have deleterious effects on the health of its users. This study aims to analyze the constituents of locally collected SLT sample extracts (S1–S11) from Tabuk region of Saudi Arabia using GC-MS and investigate their cytotoxic effect on human gingival fibroblasts (hGFs), normal human fibroblasts (MRC5), and two cancer cell lines (HT29 and HepG2) using MTT assay. GC-MS results showed that pyridine, 3-(1-methyl-1H-pyrrol-2-yl)-, tetracyclo[4.4.1.1(7,10).0(2,5)]dodec-3-en-11-ol, and cotinine were found in S1, while ethyl iso-allocholate was traced in S2. Compounds 9,12-octadecadienoic acid, ethyl ester, 7-methyl-Z-tetradecen-1-ol acetate, cis-10-heptadecenoic acid and octadecanoic acid, ethyl ester, and nicotine traces were found in S4, while compound 3,7,11,15-tetramethyl-2-hexadecen-1-ol, tetradecamethyl-hexasiloxane, and phytol in S5. Additionally, octadecamethyl cyclononasiloxane, oleic acid, and trimethylsilyl ester were found in S6 and S9, respectively. Interestingly, extracts S4, S10, and S6 were the most cytotoxic to the normal fibroblasts (hGF and MRC5, with low selectivity index: <1), compared with doxorubicin and with their effect on the cancerous cells (HT29 and HepG2). Various components detected in SLT samples were carcinogenic, including nicotine and its derivatives, hexadecanoic acid, 1,2-benzenedicarboxylic acid, and octadecanoic acid. The present study showed that the cytotoxic and possibly carcinogenic effects of the SLT samples on gingiva and lung cells are attributed to many compounds and not only nicotine derivatives, all of which could create health threats for SLT users and lead to various types of cancers, including oral, lung, colon, and liver cancers.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"98 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73838362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Long-term industrial activities tend to cause surface subsidence and damage to ground facilities and local ecological environment. Monitoring and analyzing surface subsidence is of great significance to prevent potential disasters. The surface type of the Yellow River Delta in China is complex and there are many industrial activities, so it is necessary to monitor the surface subsidence in this area. Small Baseline Subset InSAR (SBAS-InSAR) can monitor the surface subsidence with millimeter-level accuracy, but it takes a long time to process wide images (Sentinel-1) and is seriously affected by atmospheric errors. To avoid these limitations, we constructed a method combining the CenterNet network and SBAS-InSAR (CNSBAS-InSAR). Firstly, the CenterNet network is used to automatically detect the subsidence areas from the wide differential interferogram formed by two SAR satellite images and determine the location of the subsidence area. Then, the SBAS-InSAR monitoring is performed on the detected multiple subsidence areas. Finally, the small-scale subsidence results are obtained. In this study, based on 24 Sentinel-1A satellite images acquired from 10 January 2018 to 24 December 2018, nine subsidence areas in Yellow River Delta were detected. Three of them had long-term surface subsidence. They were located in Zhanhua District, Xianhe Town, and Hongguang Village, respectively. This paper focuses on analyzing these three areas. The maximum subsidence rate of Zhanhua District, Xianhe Town, and Hongguang Village were −135.21 mm/a, −330.91 mm/a, and −209.68 mm/a, respectively. In addition, the analysis showed that precipitation in the Zhanhua District could effectively slow down the subsidence rate of the area. The subsidence of Xianhe Town threatened the safety of the Shugang Expressway. The subsidence of Hongguang Village caused the safety risks of buildings. The results of this study prove that CNSBAS-InSAR method is reliable for monitoring subsidence areas and it can provide a reference for local construction and protection of Yellow River Delta.
{"title":"Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with CenterNet Network and SBAS-InSAR","authors":"Zhenjin Li, Zhiyong Wang, Wei Liu, Xing Li, Maotong Zhou, Baojing Zhang","doi":"10.1155/2022/2672876","DOIUrl":"https://doi.org/10.1155/2022/2672876","url":null,"abstract":"Long-term industrial activities tend to cause surface subsidence and damage to ground facilities and local ecological environment. Monitoring and analyzing surface subsidence is of great significance to prevent potential disasters. The surface type of the Yellow River Delta in China is complex and there are many industrial activities, so it is necessary to monitor the surface subsidence in this area. Small Baseline Subset InSAR (SBAS-InSAR) can monitor the surface subsidence with millimeter-level accuracy, but it takes a long time to process wide images (Sentinel-1) and is seriously affected by atmospheric errors. To avoid these limitations, we constructed a method combining the CenterNet network and SBAS-InSAR (CNSBAS-InSAR). Firstly, the CenterNet network is used to automatically detect the subsidence areas from the wide differential interferogram formed by two SAR satellite images and determine the location of the subsidence area. Then, the SBAS-InSAR monitoring is performed on the detected multiple subsidence areas. Finally, the small-scale subsidence results are obtained. In this study, based on 24 Sentinel-1A satellite images acquired from 10 January 2018 to 24 December 2018, nine subsidence areas in Yellow River Delta were detected. Three of them had long-term surface subsidence. They were located in Zhanhua District, Xianhe Town, and Hongguang Village, respectively. This paper focuses on analyzing these three areas. The maximum subsidence rate of Zhanhua District, Xianhe Town, and Hongguang Village were −135.21 mm/a, −330.91 mm/a, and −209.68 mm/a, respectively. In addition, the analysis showed that precipitation in the Zhanhua District could effectively slow down the subsidence rate of the area. The subsidence of Xianhe Town threatened the safety of the Shugang Expressway. The subsidence of Hongguang Village caused the safety risks of buildings. The results of this study prove that CNSBAS-InSAR method is reliable for monitoring subsidence areas and it can provide a reference for local construction and protection of Yellow River Delta.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"2 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138528311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. H. Khan, M. Ullah, Bulu Rahman, A. Talukder, M. Wahadoszamen, K. M. Abedin, A. Haider
Laser-induced breakdown spectroscopy (LIBS) has emerged as a promising technique for both quantitative and qualitative analysis of elements in a wide variety of samples. However, conventional LIBS suffers from a high limit of detection (LoD) compared with other analytical techniques. This review briefly discusses several methods that demonstrate the applicability and prospects for trace element detection while lowering the LoD when coupled with LIBS. This review compares the enhancement mechanisms, advantages, and limitations of these techniques. Finally, the recent development and application of LIBS coupled techniques for trace element detection are also discussed for various samples such as metal alloys, biomaterials, rare earth elements, explosives, drinking water, and water bodies.
{"title":"Laser-Induced Breakdown Spectroscopy (LIBS) for Trace Element Detection: A Review","authors":"Z. H. Khan, M. Ullah, Bulu Rahman, A. Talukder, M. Wahadoszamen, K. M. Abedin, A. Haider","doi":"10.1155/2022/3887038","DOIUrl":"https://doi.org/10.1155/2022/3887038","url":null,"abstract":"Laser-induced breakdown spectroscopy (LIBS) has emerged as a promising technique for both quantitative and qualitative analysis of elements in a wide variety of samples. However, conventional LIBS suffers from a high limit of detection (LoD) compared with other analytical techniques. This review briefly discusses several methods that demonstrate the applicability and prospects for trace element detection while lowering the LoD when coupled with LIBS. This review compares the enhancement mechanisms, advantages, and limitations of these techniques. Finally, the recent development and application of LIBS coupled techniques for trace element detection are also discussed for various samples such as metal alloys, biomaterials, rare earth elements, explosives, drinking water, and water bodies.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"32 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90555486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Attimarad, M. Chohan, Venugopala Katharigatta Narayanaswamy, Anroop B Nair, N. Sreeharsha, S. Shafi, Marysheela David, A. Balgoname, Abdulrahman Ibrahim Altaysan, Efren II Plaza Molina, P. Deb
A simple, eco-friendly four analytical methods were established by improving the selectivity through the application of mathematical processing of UV absorption spectra for concurrent quantification of chlorthalidone (CTL) and azelnidipine (AZE). The UV absorption spectra were recorded using environment-friendly ethanol (10% v/v) and were mathematically processed using simple software provided with a UV spectrophotometer. The analytes’ peak amplitude was determined using zero-crossing point first derivative spectra and ratio first derivative spectra of CTL and AZE, which were measured at 238.5 nm and 239.5 nm for CTL and 272.1 nm and 342.1 nm for AZE, respectively. The peak amplitude difference was determined from the ratio spectra of CTL and AZE by measuring the peak amplitudes at 211.8 and 267.2 nm for CTL and 328.4 and 286.1 nm for AZE. Further, ratio spectra of CTL and AZE were converted into zero-order spectra by subtracting the constant followed by multiplication with divisor spectra, and the peak amplitudes were measured at 226.9 nm and 257.3 nm for CTL and AZE zero-order spectra, respectively. Further, validation results of all the four methods confirmed the accuracy and precision of the methods by displaying good recovery (98.37–100.34%) and percentage relative standard deviation (0.397–1.758%), respectively. Good linearity was observed in the range of 1–15 μg/mL for both analytes with less than a 1 μg/mL limit of quantification. Further, the greenness and whiteness of the methods were evaluated by recently proposed AGREEness, complexGAPI, and white analytical chemistry techniques. The proposed UV spectroscopic methods were environmentally friendly, safe, economic, and effective, hence, could be used for regular quality control study of a formulation containing CTL and AZE.
{"title":"Mathematically Processed UV Spectroscopic Method for Quantification of Chlorthalidone and Azelnidipine in Bulk and Formulation: Evaluation of Greenness and Whiteness","authors":"M. Attimarad, M. Chohan, Venugopala Katharigatta Narayanaswamy, Anroop B Nair, N. Sreeharsha, S. Shafi, Marysheela David, A. Balgoname, Abdulrahman Ibrahim Altaysan, Efren II Plaza Molina, P. Deb","doi":"10.1155/2022/4965138","DOIUrl":"https://doi.org/10.1155/2022/4965138","url":null,"abstract":"A simple, eco-friendly four analytical methods were established by improving the selectivity through the application of mathematical processing of UV absorption spectra for concurrent quantification of chlorthalidone (CTL) and azelnidipine (AZE). The UV absorption spectra were recorded using environment-friendly ethanol (10% v/v) and were mathematically processed using simple software provided with a UV spectrophotometer. The analytes’ peak amplitude was determined using zero-crossing point first derivative spectra and ratio first derivative spectra of CTL and AZE, which were measured at 238.5 nm and 239.5 nm for CTL and 272.1 nm and 342.1 nm for AZE, respectively. The peak amplitude difference was determined from the ratio spectra of CTL and AZE by measuring the peak amplitudes at 211.8 and 267.2 nm for CTL and 328.4 and 286.1 nm for AZE. Further, ratio spectra of CTL and AZE were converted into zero-order spectra by subtracting the constant followed by multiplication with divisor spectra, and the peak amplitudes were measured at 226.9 nm and 257.3 nm for CTL and AZE zero-order spectra, respectively. Further, validation results of all the four methods confirmed the accuracy and precision of the methods by displaying good recovery (98.37–100.34%) and percentage relative standard deviation (0.397–1.758%), respectively. Good linearity was observed in the range of 1–15 μg/mL for both analytes with less than a 1 μg/mL limit of quantification. Further, the greenness and whiteness of the methods were evaluated by recently proposed AGREEness, complexGAPI, and white analytical chemistry techniques. The proposed UV spectroscopic methods were environmentally friendly, safe, economic, and effective, hence, could be used for regular quality control study of a formulation containing CTL and AZE.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"30 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89947141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hongmin Sun, Fanze Kong, Cheng Xiu, Weizheng Shen, Yan Wang
A specific variable selection method was proposed based on a three-step hybrid strategy for near-infrared spectral analysis. By analyzing functions of each step and characteristics of various variable selection methods, synergy interval partial least squares, iterative variable subset optimization, and bootstrapping soft shrinkage were chosen for three steps. To test the effect of the three-step hybrid method, it was applied to corn and soil spectral data and compared to other common methods. Results for oil content in corn data showed that the three-step hybrid variable selection method selected 1% variables of full spectrum, calibration determination coefficient, and prediction determination coefficient reached 0.998 and 0.993 where the explained variance was increased by 27.30%. It could effectively extract variables related to the tested substance and provide a new variable selection method for near-infrared spectral analysis.
{"title":"A Progressive Combined Variable Selection Method for Near-Infrared Spectral Analysis Based on Three-Step Hybrid Strategy","authors":"Hongmin Sun, Fanze Kong, Cheng Xiu, Weizheng Shen, Yan Wang","doi":"10.1155/2022/2190893","DOIUrl":"https://doi.org/10.1155/2022/2190893","url":null,"abstract":"A specific variable selection method was proposed based on a three-step hybrid strategy for near-infrared spectral analysis. By analyzing functions of each step and characteristics of various variable selection methods, synergy interval partial least squares, iterative variable subset optimization, and bootstrapping soft shrinkage were chosen for three steps. To test the effect of the three-step hybrid method, it was applied to corn and soil spectral data and compared to other common methods. Results for oil content in corn data showed that the three-step hybrid variable selection method selected 1% variables of full spectrum, calibration determination coefficient, and prediction determination coefficient reached 0.998 and 0.993 where the explained variance was increased by 27.30%. It could effectively extract variables related to the tested substance and provide a new variable selection method for near-infrared spectral analysis.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90092690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The calcium silicate hydrate (CSH) concentration in the cement paste mixed with different types of carbon nanotubes (CNTs) and oxide additives is compared by using Raman spectroscopy. The pristine, hydroxyl and carboxyl functionalized CNTs are used in this work. The oxide additives are zinc oxide (ZnO), gadolinium oxide (Gd2O3), and silicon oxide (SiO2). A laser wavelength of 785 nm was used to collect the Raman spectra. It was observed that the concentration of calcium silicate hydrate (CSH) is unaffected in CNTs-OPC matrices regardless of the type and weight percentage of the CNTs. The oxides, as expected, show significant effects on the concentration of the CSH in the matrices. An increase in the CSH concentration is observed in the ZnO and Gd2O3 matrices with cement. For the SiO2 cement paste matrix, however, the CSH concentration appears to be decreased. This study shows CSH concentration can be controlled by using oxide additives whereas CNTs do not react chemically with the cement composites.
{"title":"A Raman Spectroscopic Study of Calcium Silicate Hydrate (CSH) in the Cement Matrix with CNTs and Oxide Additives","authors":"M. Azeem, M. Saleem","doi":"10.1155/2022/2281477","DOIUrl":"https://doi.org/10.1155/2022/2281477","url":null,"abstract":"The calcium silicate hydrate (CSH) concentration in the cement paste mixed with different types of carbon nanotubes (CNTs) and oxide additives is compared by using Raman spectroscopy. The pristine, hydroxyl and carboxyl functionalized CNTs are used in this work. The oxide additives are zinc oxide (ZnO), gadolinium oxide (Gd2O3), and silicon oxide (SiO2). A laser wavelength of 785 nm was used to collect the Raman spectra. It was observed that the concentration of calcium silicate hydrate (CSH) is unaffected in CNTs-OPC matrices regardless of the type and weight percentage of the CNTs. The oxides, as expected, show significant effects on the concentration of the CSH in the matrices. An increase in the CSH concentration is observed in the ZnO and Gd2O3 matrices with cement. For the SiO2 cement paste matrix, however, the CSH concentration appears to be decreased. This study shows CSH concentration can be controlled by using oxide additives whereas CNTs do not react chemically with the cement composites.","PeriodicalId":17079,"journal":{"name":"Journal of Spectroscopy","volume":"1 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79492763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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