A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductiv...A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.展开更多
The risk of the illegal addition of anti-inflammatory and analgesic chemical drugs in anti-rheumatic health foods should not be ignored.Market supervision and rapid on-site detection technology need to be strengthened...The risk of the illegal addition of anti-inflammatory and analgesic chemical drugs in anti-rheumatic health foods should not be ignored.Market supervision and rapid on-site detection technology need to be strengthened.Thin-layer chromatography-surface-enhanced Raman spectroscopy(TLC-SERS),which has the advantages of simple operation,fast separation,and qualitative and quantitative detection,was used in this study.And these eleven chemical drugs(acetaminophen,acetylsalicylic acid,aminophenazone,dexamethasone,diclofenac sodium,hydrocortisone,indometacin,naproxen,phenylbutazone,piroxicam,prednisone 21-acetate)that may be added to anti-rheumatic health foods have been simultaneously identified by TLC-SERS combined with chemometrics method.The characteristic signals of the separated drug spots were collected by SERS,which were optimized by the gold colloidal nanoparticles’volume and integration time.Then SERS was subjected to principal component analysis(PCA)to reduce dimensionality and combined with the pattern recognition methods in chemometrics,such as PCA-Linear Discriminant Analysis(LDA),PCA-K Nearest Neighbor and PCA-Support Vector Machine,and eleven drug components were judged and identified.Moreover,the predictive performances of different models were also analyzed and compared.The results showed that the TLC plate and four organic solvents of petroleum ether,chloroform,ethyl acetate and acetic acid were selected as the developing agent.The dropping amount of gold colloidal nanoparticles and the integration time were set and optimized.The limit of detection of the simultaneous detection method of SERS was 10-100 mg/L.Furthermore,SERS was preprocessed by Gap-Segment 2nd Derivative,and then the PCA-LDA model was established,and the model’s prediction accuracy can reach 100%.The method is simple,rapid,sensitive and accurate,and has low experimental instruments and equipment requirements.It is suitable for the on-site simultaneous detection of various anti-inflammatory and analgesic chemical drugs in health foods.It can also provide guarantee and support for the establishment of appropriate rapid detection methods and the development of supervision technology.展开更多
基金supported by the Fundamental Research Funds for the Central Universities (No.3122020072)the Multi-investment Project of Tianjin Applied Basic Research(No.23JCQNJC00250)。
文摘A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.
基金supported by the China Postdoctoral Science Foundation(2020M680064)the Postdoctoral Research Startup Fee of Jiangnan University(1025219032200190)+1 种基金the National Natural Science Foundation of China(32172326)the Open Project of Engineering Research Center of Dairy Quality and Safety Control Technology of Ministry of Education of China(R202101).
文摘The risk of the illegal addition of anti-inflammatory and analgesic chemical drugs in anti-rheumatic health foods should not be ignored.Market supervision and rapid on-site detection technology need to be strengthened.Thin-layer chromatography-surface-enhanced Raman spectroscopy(TLC-SERS),which has the advantages of simple operation,fast separation,and qualitative and quantitative detection,was used in this study.And these eleven chemical drugs(acetaminophen,acetylsalicylic acid,aminophenazone,dexamethasone,diclofenac sodium,hydrocortisone,indometacin,naproxen,phenylbutazone,piroxicam,prednisone 21-acetate)that may be added to anti-rheumatic health foods have been simultaneously identified by TLC-SERS combined with chemometrics method.The characteristic signals of the separated drug spots were collected by SERS,which were optimized by the gold colloidal nanoparticles’volume and integration time.Then SERS was subjected to principal component analysis(PCA)to reduce dimensionality and combined with the pattern recognition methods in chemometrics,such as PCA-Linear Discriminant Analysis(LDA),PCA-K Nearest Neighbor and PCA-Support Vector Machine,and eleven drug components were judged and identified.Moreover,the predictive performances of different models were also analyzed and compared.The results showed that the TLC plate and four organic solvents of petroleum ether,chloroform,ethyl acetate and acetic acid were selected as the developing agent.The dropping amount of gold colloidal nanoparticles and the integration time were set and optimized.The limit of detection of the simultaneous detection method of SERS was 10-100 mg/L.Furthermore,SERS was preprocessed by Gap-Segment 2nd Derivative,and then the PCA-LDA model was established,and the model’s prediction accuracy can reach 100%.The method is simple,rapid,sensitive and accurate,and has low experimental instruments and equipment requirements.It is suitable for the on-site simultaneous detection of various anti-inflammatory and analgesic chemical drugs in health foods.It can also provide guarantee and support for the establishment of appropriate rapid detection methods and the development of supervision technology.
