Cancer staging detection is important for clinician to assess the patients' status and make optimal therapy decision. In this study, the machine learning algorithm based on principal component analysis(PCA) and su...Cancer staging detection is important for clinician to assess the patients' status and make optimal therapy decision. In this study, the machine learning algorithm based on principal component analysis(PCA) and support vector machine(SVM) was combined with urine surface-enhanced Raman scattering(SERS) spectroscopy for improving the identification of colorectal cancer(CRC) at early and advanced stages. Two discriminant methods, linear discriminant analysis(LDA) and SVM were compared, and the results indicated that the diagnostic accuracy of SVM(93.65%) was superior to that of LDA(80.95%). This exploratory study demonstrated the great promise of urine SERS spectra along with PCA-SVM for facilitating more accurate detection of CRC at different stages.展开更多
The damage to the rear surface of fused silica under the action of high power laser is more severe than that incurred by the front surface,which hinders the improvement in the energy of the high power laser device.For...The damage to the rear surface of fused silica under the action of high power laser is more severe than that incurred by the front surface,which hinders the improvement in the energy of the high power laser device.For optical components,the ionization breakdown by laser is a main factor causing damage,particularly with laser plasma shock waves,which can cause large-scale fracture damage in fused silica.In this study,the damage morphology is experimentally investigated,and the characteristics of the damage point are obtained.In the theoretical study,the coupling and transmission of the shock wave in glass are investigated based on the finite element method.Thus,both the magnitude and the orientation of stress are obtained.The damage mechanism of the glass can be explained based on the fracture characteristics of glass under different stresses and also on the variation of the damage zone’s Raman spectrum.In addition,the influence of the glass thickness on the damage morphology is investigated.The results obtained in this study can be used as a reference in understanding the characteristics and mechanism of damage characteristics induced by laser plasma shock waves.展开更多
We employed the microscopic reflectance difference spectroscopy （micro-RDS） to determine the layer- number and microscopically image the surface topography of graphene and MoS2 samples. The contrast image shows the ...We employed the microscopic reflectance difference spectroscopy （micro-RDS） to determine the layer- number and microscopically image the surface topography of graphene and MoS2 samples. The contrast image shows the efficiency and reliability of this new clipping technique. As a low-cost, quantifiable, no-contact and non-destructive method, it is not concerned with the characteristic signal of certain materials and can be applied to arbitrary substrates. Therefore it is a perfect candidate for characterizing the thickness of graphene-like two- dimensional materials.展开更多
基金supported by the National Natural Science Foundation of China (No.61975031)the Natural Science Foundation of Fujian Province (No.2020J011121)+3 种基金the Product-University Cooperation Project of Fujian Province (No.2020Y4006)the National Clinical Key Specialty Construction Program (No.2021)the Fujian Provincial Clinical Research Center for Cancer Radiotherapy and Immunotherapy (No.2020Y2012)the Joint Funds for the Innovation of Science and Technology of Fujian Province (No.2021Y9192)。
文摘Cancer staging detection is important for clinician to assess the patients' status and make optimal therapy decision. In this study, the machine learning algorithm based on principal component analysis(PCA) and support vector machine(SVM) was combined with urine surface-enhanced Raman scattering(SERS) spectroscopy for improving the identification of colorectal cancer(CRC) at early and advanced stages. Two discriminant methods, linear discriminant analysis(LDA) and SVM were compared, and the results indicated that the diagnostic accuracy of SVM(93.65%) was superior to that of LDA(80.95%). This exploratory study demonstrated the great promise of urine SERS spectra along with PCA-SVM for facilitating more accurate detection of CRC at different stages.
基金Project supported by the Key Research and Development Projects of Science and Technology Department of Sichuan Province,China(Grant No.2018FZ0032)the National Natural Science Foundation of China(Grant No.U1730141)
文摘The damage to the rear surface of fused silica under the action of high power laser is more severe than that incurred by the front surface,which hinders the improvement in the energy of the high power laser device.For optical components,the ionization breakdown by laser is a main factor causing damage,particularly with laser plasma shock waves,which can cause large-scale fracture damage in fused silica.In this study,the damage morphology is experimentally investigated,and the characteristics of the damage point are obtained.In the theoretical study,the coupling and transmission of the shock wave in glass are investigated based on the finite element method.Thus,both the magnitude and the orientation of stress are obtained.The damage mechanism of the glass can be explained based on the fracture characteristics of glass under different stresses and also on the variation of the damage zone’s Raman spectrum.In addition,the influence of the glass thickness on the damage morphology is investigated.The results obtained in this study can be used as a reference in understanding the characteristics and mechanism of damage characteristics induced by laser plasma shock waves.
基金supported by the State Key Development Program for Basic Research of China(Nos.2012CB921304,2013CB632805,2012CB619306)the National Natural Science Foundation of China(No.61474114)
文摘We employed the microscopic reflectance difference spectroscopy （micro-RDS） to determine the layer- number and microscopically image the surface topography of graphene and MoS2 samples. The contrast image shows the efficiency and reliability of this new clipping technique. As a low-cost, quantifiable, no-contact and non-destructive method, it is not concerned with the characteristic signal of certain materials and can be applied to arbitrary substrates. Therefore it is a perfect candidate for characterizing the thickness of graphene-like two- dimensional materials.
