We study theoretically intense terahertz radiation from multi-color laser pulse with uncommon frequency ratios. Com- paring the two-color laser scheme, of which the uncommon frequency ratio should be set to be a speci...We study theoretically intense terahertz radiation from multi-color laser pulse with uncommon frequency ratios. Com- paring the two-color laser scheme, of which the uncommon frequency ratio should be set to be a specific value, we show that by using multi-color harmonic laser pulses as the first pump component, the lasers as the second pump component can be adjusted in a continuous frequency range. Moreover, these multi-color laser pulses can effectively modulate and enhance the terahertz radiation, and the terahertz yield increases with the increase of the wavelength of the uncommon pump com- ponent and is stable to the laser relative phase. Finally, we utilize the electron densities and velocities of ionization events to illustrate the physical mechanism of the intense terahertz generation.展开更多
Background:Fundus Autofluorescence(FAF)is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium(RPE)associated with various age-related and disease-related changes.The pra...Background:Fundus Autofluorescence(FAF)is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium(RPE)associated with various age-related and disease-related changes.The practical uses of FAF are ever-growing.This study aimed to evaluate the effectiveness of a generative deep learning(DL)model in translating color fundus(CF)images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration(AMD).Methods:A generative adversarial network(GAN)model was trained on pairs of CF and FAF images to generate synthetic FAF images.The quality of synthesized FAF images was assessed objectively by common generation metrics.Additionally,the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve(AUC),using the LabelMe dataset.Results:A total of 8410 FAF images from 2586 patients were analyzed.The synthesized FAF images exhibited an impressive objectively assessed quality,achieving a multi-scale structural similarity index(MS-SSIM)of 0.67.When evaluated on the LabelMe dataset,the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy,with the AUC increasing from 0.931 to 0.968.Conclusions:This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images.The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification.Overall,this study presents a promising approach to enhance largescale AMD screening.展开更多
In this paper, we have investigated theoretically the high harmonic generation form helium atom in long wavelength driving regime at 2000 nm through solving time-dependent Schr6dinger equation. By adding a second harm...In this paper, we have investigated theoretically the high harmonic generation form helium atom in long wavelength driving regime at 2000 nm through solving time-dependent Schr6dinger equation. By adding a second harmonic pulse （1000 nm） and a UV attosecond pulse （200 nm） to the driving field, an efficient method for picking out and enhancing ionization path to generate high-yield supercontinuum harmonics is realized, and then an isolated sub-100 as pulse with a bandwidth of 190 eV is significantly obtained.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.11604205)the Talent Program of Shanghai University of Engineering Science,China
文摘We study theoretically intense terahertz radiation from multi-color laser pulse with uncommon frequency ratios. Com- paring the two-color laser scheme, of which the uncommon frequency ratio should be set to be a specific value, we show that by using multi-color harmonic laser pulses as the first pump component, the lasers as the second pump component can be adjusted in a continuous frequency range. Moreover, these multi-color laser pulses can effectively modulate and enhance the terahertz radiation, and the terahertz yield increases with the increase of the wavelength of the uncommon pump com- ponent and is stable to the laser relative phase. Finally, we utilize the electron densities and velocities of ionization events to illustrate the physical mechanism of the intense terahertz generation.
基金This research received support from the Global STEM Professorship Scheme(P0046113).
文摘Background:Fundus Autofluorescence(FAF)is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium(RPE)associated with various age-related and disease-related changes.The practical uses of FAF are ever-growing.This study aimed to evaluate the effectiveness of a generative deep learning(DL)model in translating color fundus(CF)images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration(AMD).Methods:A generative adversarial network(GAN)model was trained on pairs of CF and FAF images to generate synthetic FAF images.The quality of synthesized FAF images was assessed objectively by common generation metrics.Additionally,the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve(AUC),using the LabelMe dataset.Results:A total of 8410 FAF images from 2586 patients were analyzed.The synthesized FAF images exhibited an impressive objectively assessed quality,achieving a multi-scale structural similarity index(MS-SSIM)of 0.67.When evaluated on the LabelMe dataset,the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy,with the AUC increasing from 0.931 to 0.968.Conclusions:This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images.The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification.Overall,this study presents a promising approach to enhance largescale AMD screening.
基金Supported by the Natural Science Foundation of Hubei Province under Grant No.2008CDB317
文摘In this paper, we have investigated theoretically the high harmonic generation form helium atom in long wavelength driving regime at 2000 nm through solving time-dependent Schr6dinger equation. By adding a second harmonic pulse （1000 nm） and a UV attosecond pulse （200 nm） to the driving field, an efficient method for picking out and enhancing ionization path to generate high-yield supercontinuum harmonics is realized, and then an isolated sub-100 as pulse with a bandwidth of 190 eV is significantly obtained.
