We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training ph...We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training phase, the connection weights of the unified NN are updated again in verification phase according to error between the predicted and target gains to eliminate the inherent error of the NNs. The simulation results show that the mean of root mean square error(RMSE) and maximum error of gains are 0.131 d B and 0.281 d B, respectively. It shows that the method can realize adaptive adjustment function of FRA gain with high accuracy.展开更多
This study aimed to explore the application of surface-enhanced Raman scattering(SERS)in the rapid diagnosis of gastric cancer.The SERS spectra of 68 serum samples from gastric cancer patients and healthy volunteers w...This study aimed to explore the application of surface-enhanced Raman scattering(SERS)in the rapid diagnosis of gastric cancer.The SERS spectra of 68 serum samples from gastric cancer patients and healthy volunteers were acquired.The characteristic ratio method(CRM)and principal component analysis(PCA)were used to differentiate gastric cancer serum from normal serum.Compared with healthy volunteers,the serum SERS intensity of gastric cancer patients was relatively high at 722 cm^(-1),while it was relatively low at 588,644,861,1008,1235,1397,1445 and 1586 cm^(-1).These results indicated that the relative content of nucleic acids in the serum of gastric cancer patients rises while the relative content of amino acids and carbohydrates decreases.In PCA,the sensitivity and specificity of discriminating gastric cancer were 94.1%and 94.1%,respectively,with the accuracy of 94.1%.Based on the intensity ratios of four characteristic peaks at 722,861,1008 and 1397 cm^(-1),CRM presented the diagnostic sensitivity and specificity of 100%and 97.4%,respectively,and the accuracy of 98.5%.Therefore,the three peak intensity ratios of I_(722)/I_(861),I_(722)/I_(1008)and I_(722)/I_(1397)can be considered as biologicalfingerprint information for gastric cancer diagnosis and can rapidly and directly reflect the physiological and pathological changes associated with gastric cancer development.This study provides an important basis and standards for the early diagnosis of gastric cancer.展开更多
As an effective and universal acaricide, amitraz is widely used on beehives against varroasis caused by the mite Varroa jacobsoni. Its residues in honey pose a great danger to human health. In this study, a sensitive,...As an effective and universal acaricide, amitraz is widely used on beehives against varroasis caused by the mite Varroa jacobsoni. Its residues in honey pose a great danger to human health. In this study, a sensitive, rapid, and environmentally friendly surface-enhanced Raman spectroscopy method (SERS) was developed for the determination of trace amount of amitraz in honey with the use of silver nanorod (AgNR) array substrate. The AgNR array substrate fabricated by an oblique angle deposition technique exhibited an excellent SERS activity with an enhancement factor of -10^7. Density function theory was employed to assign the characteristic peak of amitraz. The detection of amitraz was further explored and amitraz in honey at concentrations as low as 0.08 mg/kg can be identified. Specifically, partial least square regression analysis was employed to correlate the SERS spectra in full-wavelength with Camitraz to afford a multiple-quantitative amitraz predicting model. Preliminary results show that the predicted concentrations of amitraz in honey samples are in good agreement with their real concentrations. Compared with the conventional univariate quantitative model based on single peak’s intensity, the proposed multiple-quantitative predicting model integrates all the characteristic peaks of amitraz, thus offering an improved detecting accuracy and anti-interference ability.展开更多
Human serum albumin(HSA)injectable product is a severely afflicted area on drug safety due to its high price and restricted supply.Raman spectroscopy performances high specificity on HSA detection and it is even possi...Human serum albumin(HSA)injectable product is a severely afflicted area on drug safety due to its high price and restricted supply.Raman spectroscopy performances high specificity on HSA detection and it is even possible to determine HSA injectable products noninvasively.In this study,we developed a noninvasive rapid screening method for of HSA injectable products by using portable Raman spectrometer.Qualitative models were established by using principal component analysis combined with classical least squares(PCA-CLS)algorithm,while quanti-tative model was established by using partial least squares(PLS)algorithm.Model transfer in different instruments of both the same and different apparatus modules was further discussed in this paper.A total of 34 HSA injectable samples collected from markets were used for verification.The identification results showed 100%accuracy and the predicted concentrations of those identified as true HSA were consistent with their labeled concentrations.The quantitative results also indicated that model transfer was excellent in the same apparatus modules of Raman spectrometer at all concentration levels,and still good enough in the different apparatus modules although the relative standard deviation(RSD)value showed a little increasing trend at low HSA concentration level.In conclusion,the method was proved to be feasible and efficient for screening HSA injections,especially on its screening speed and the consideration of glass containers.Moreover,with inspiring results on the model transfer,the method could be used as a universal screening mean to different Raman instruments.展开更多
Silver nano-particles with average diameter of about 60 nm were compacted in a high-strength mold under different pressures at 523 K to produce nano-structured Ag solid materials. The structure and characteristic of t...Silver nano-particles with average diameter of about 60 nm were compacted in a high-strength mold under different pressures at 523 K to produce nano-structured Ag solid materials. The structure and characteristic of the nano-structured Ag solid materials (NSS-Ag) were studied using X-ray diffraction (XRD), scanning electron microscope (SEM) and Raman spectrometer. The NSS-Ag could be used as highly efficient surface-enhanced Raman scattering (SERS) active substrates. The common probe molecules Rhodamine 6G (R6G, 1×10-10 mol/L) were used to test the SERS activity on these substrates at very low concentrations. It is found that the SERS enhancement ability is dependent on the density of NSS-Ag. When the relative density of NSS-Ag is 83.87%, the materials reveal great SERS signal.展开更多
基金supported by the Natural Science Research Project of Colleges and Universities in Anhui Province (No.KJ2021A0479)the Science Research Program of Anhui University of Finance and Economics (No.ACKYC22082)。
文摘We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training phase, the connection weights of the unified NN are updated again in verification phase according to error between the predicted and target gains to eliminate the inherent error of the NNs. The simulation results show that the mean of root mean square error(RMSE) and maximum error of gains are 0.131 d B and 0.281 d B, respectively. It shows that the method can realize adaptive adjustment function of FRA gain with high accuracy.
基金This work was supported by the Natural Science Foundation of Guangdong Province,China(2018 A0303131000)the project of Academician workstation of Guangdong Province,China(2014B090905001)the Fundamental Research Funds for the Central Universities,China(21617406)and the key project of Scientific and Technological projects of Guang Zhou,China(201604040007,201604020168).
文摘This study aimed to explore the application of surface-enhanced Raman scattering(SERS)in the rapid diagnosis of gastric cancer.The SERS spectra of 68 serum samples from gastric cancer patients and healthy volunteers were acquired.The characteristic ratio method(CRM)and principal component analysis(PCA)were used to differentiate gastric cancer serum from normal serum.Compared with healthy volunteers,the serum SERS intensity of gastric cancer patients was relatively high at 722 cm^(-1),while it was relatively low at 588,644,861,1008,1235,1397,1445 and 1586 cm^(-1).These results indicated that the relative content of nucleic acids in the serum of gastric cancer patients rises while the relative content of amino acids and carbohydrates decreases.In PCA,the sensitivity and specificity of discriminating gastric cancer were 94.1%and 94.1%,respectively,with the accuracy of 94.1%.Based on the intensity ratios of four characteristic peaks at 722,861,1008 and 1397 cm^(-1),CRM presented the diagnostic sensitivity and specificity of 100%and 97.4%,respectively,and the accuracy of 98.5%.Therefore,the three peak intensity ratios of I_(722)/I_(861),I_(722)/I_(1008)and I_(722)/I_(1397)can be considered as biologicalfingerprint information for gastric cancer diagnosis and can rapidly and directly reflect the physiological and pathological changes associated with gastric cancer development.This study provides an important basis and standards for the early diagnosis of gastric cancer.
基金supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (No.16KJB510009 and No.17KJB510017)Jiangsu Province Natural Science Foundation of China (BK20150228)
文摘As an effective and universal acaricide, amitraz is widely used on beehives against varroasis caused by the mite Varroa jacobsoni. Its residues in honey pose a great danger to human health. In this study, a sensitive, rapid, and environmentally friendly surface-enhanced Raman spectroscopy method (SERS) was developed for the determination of trace amount of amitraz in honey with the use of silver nanorod (AgNR) array substrate. The AgNR array substrate fabricated by an oblique angle deposition technique exhibited an excellent SERS activity with an enhancement factor of -10^7. Density function theory was employed to assign the characteristic peak of amitraz. The detection of amitraz was further explored and amitraz in honey at concentrations as low as 0.08 mg/kg can be identified. Specifically, partial least square regression analysis was employed to correlate the SERS spectra in full-wavelength with Camitraz to afford a multiple-quantitative amitraz predicting model. Preliminary results show that the predicted concentrations of amitraz in honey samples are in good agreement with their real concentrations. Compared with the conventional univariate quantitative model based on single peak’s intensity, the proposed multiple-quantitative predicting model integrates all the characteristic peaks of amitraz, thus offering an improved detecting accuracy and anti-interference ability.
基金Youth Develop-ment Research Foundation(No.2015C03)of Na-tional Institutes of Food and Drug Control,P.R.China.
文摘Human serum albumin(HSA)injectable product is a severely afflicted area on drug safety due to its high price and restricted supply.Raman spectroscopy performances high specificity on HSA detection and it is even possible to determine HSA injectable products noninvasively.In this study,we developed a noninvasive rapid screening method for of HSA injectable products by using portable Raman spectrometer.Qualitative models were established by using principal component analysis combined with classical least squares(PCA-CLS)algorithm,while quanti-tative model was established by using partial least squares(PLS)algorithm.Model transfer in different instruments of both the same and different apparatus modules was further discussed in this paper.A total of 34 HSA injectable samples collected from markets were used for verification.The identification results showed 100%accuracy and the predicted concentrations of those identified as true HSA were consistent with their labeled concentrations.The quantitative results also indicated that model transfer was excellent in the same apparatus modules of Raman spectrometer at all concentration levels,and still good enough in the different apparatus modules although the relative standard deviation(RSD)value showed a little increasing trend at low HSA concentration level.In conclusion,the method was proved to be feasible and efficient for screening HSA injections,especially on its screening speed and the consideration of glass containers.Moreover,with inspiring results on the model transfer,the method could be used as a universal screening mean to different Raman instruments.
基金Project(10804101) supported by the National Natural Science Foundation of ChinaProject(2007CB815102) supported by the National Basic Research Program of ChinaProject(2007B08007) supported by the Science and Technology Development Foundation of Chinese Academy of Engineering Physics
文摘Silver nano-particles with average diameter of about 60 nm were compacted in a high-strength mold under different pressures at 523 K to produce nano-structured Ag solid materials. The structure and characteristic of the nano-structured Ag solid materials (NSS-Ag) were studied using X-ray diffraction (XRD), scanning electron microscope (SEM) and Raman spectrometer. The NSS-Ag could be used as highly efficient surface-enhanced Raman scattering (SERS) active substrates. The common probe molecules Rhodamine 6G (R6G, 1×10-10 mol/L) were used to test the SERS activity on these substrates at very low concentrations. It is found that the SERS enhancement ability is dependent on the density of NSS-Ag. When the relative density of NSS-Ag is 83.87%, the materials reveal great SERS signal.
