We delve into the phenomenon of high-order harmonic generation within a helium atom under the influence of a plasmon-assisted shaping pulse.Our findings reveal an intriguing manipulation of the frequency peak position...We delve into the phenomenon of high-order harmonic generation within a helium atom under the influence of a plasmon-assisted shaping pulse.Our findings reveal an intriguing manipulation of the frequency peak position in the harmonic emission by adjusting the absolute phase parameter within the frequency domain of the shaping pulse.This phenomenon holds potential significance for experimental setups necessitating precisely tuned single harmonics.Notably,we observe a modulated shift in the created harmonic photon energy,spanning an impressive range of 1.2 eV.This frequency peak shift is rooted in the asymmetry exhibited by the rising and falling edges of the laser pulse,directly influencing the position of the peak frequency emission.Our study quantifies the dependence of this tuning range and the asymmetry of the laser pulse,offering valuable insights into the underlying mechanisms driving this phenomenon.Furthermore,our investigation uncovers the emergence of semi-integer order harmonics as the phase parameter is altered.We attribute this discovery to the intricate interference between harmonics generated by the primary and secondary return cores.This observation introduces an innovative approach for generating semi-integer order harmonics,thus expanding our understanding of high-order harmonic generation.Ultimately,our work contributes to the broader comprehension of complex phenomena in laser-matter interactions and provides a foundation for harnessing these effects in various applications,particularly those involving precise spectral control and the generation of unique harmonic patterns.展开更多
Background Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment.Meanwhile,the increasing demand for dairy products will result in more ...Background Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment.Meanwhile,the increasing demand for dairy products will result in more pollution if N losses are not controlled.Therefore,a more efficient,and environmentally friendly production system is needed,in which nitrogen use efficiency(NUE)of dairy cows plays a key role.To genetically improve NUE,extensively recorded and cost-effective proxies are essential,which can be obtained by including mid-infrared(MIR)spectra of milk in prediction models for NUE.This study aimed to develop and validate the best prediction model of NUE,nitrogen loss(NL)and dry matter intake(DMI)for individual dairy cows in China.Results A total of 86 lactating Chinese Holstein cows were used in this study.After data editing,704 records were obtained for calibration and validation.Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait.Results showed that the coefficient of determination(R2)of the best model in within-herd validation was 0.66 for NUE,0.58 for NL and 0.63 for DMI.For external validation,reasonable prediction results were only observed for NUE,with R2 ranging from 0.58 to 0.63,while the R2 of the other two traits was below 0.50.The infrared waves from 973.54 to 988.46 cm−1 and daily milk yield were the most important variables for prediction.Conclusion The results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations.The model of NUE could be used for the datasets that are similar to the calibration dataset.The prediction models for NL and 3-day moving average of DMI(DMI_a)generated lower accuracies in within-herd validation.Results also indicated that information of MIR spectra variables increased the predictive ability of models.Additionally,pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation.These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected.展开更多
We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is in...We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is investigated. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model for the second triplet state of the system. The investigations show that the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.展开更多
A study of a nanosecond laser irradiation on the titanium-layer-buried gold planar target is presented. The timeresolved x-ray emission spectra of titanium tracer are measured by a streaked crystal spectrometer. By co...A study of a nanosecond laser irradiation on the titanium-layer-buried gold planar target is presented. The timeresolved x-ray emission spectra of titanium tracer are measured by a streaked crystal spectrometer. By comparing the simulated spectra obtained by using the FLYCHK code with the measured titanium spectra, the temporal plasma states, i.e.,the electron temperatures and densities, are deduced. To evaluate the feasibility of using the method for the characterization of Au plasma states, the deduced plasma states from the measured titanium spectra are compared with the Multi-1D hydrodynamic simulations of laser-produced Au plasmas. By comparing the measured and simulated results, an overall agreement for the electron temperatures is found, whereas there are deviations in the electron densities. The experiment–theory discrepancy may suggest that the plasma state could not be well reproduced by the Multi-1D hydrodynamic simulation, in which the radial gradient is not taken into account. Further investigations on the spectral characterization and hydrodynamic simulations of the plasma states are needed. All the measured and FLYCHK simulated spectra are given in this paper as datasets. The datasets are openly available at http://www.doi.org/10.57760/sciencedb.j00113.00032.展开更多
Time-integrated optical emission analysis of laser-induced plasma on Teflon is presented.Plasma was induced under atmospheric pressure air using transversely excited atmospheric CO_(2) laser pulses.Teflon is a C-based...Time-integrated optical emission analysis of laser-induced plasma on Teflon is presented.Plasma was induced under atmospheric pressure air using transversely excited atmospheric CO_(2) laser pulses.Teflon is a C-based polymer that is,among other things,interesting as a substrate for laser-induced breakdown spectroscopy analysis of liquid samples.This study aimed to determine the optimal experimental conditions for obtaining neutral and ionized C spectral lines and C2 and CN molecular band emission suitable for spectrochemical purposes.Evaluation of plasma parameters was done using several spectroscopic techniques.Stark profiles of appropriate C ionic lines were used to determine electron number density.The ratio of the integral intensity of ionic-to-atomic C spectral lines was used to determine the ionization temperature.A spectral emission of C2 Swan and CN violet bands system was used to determine the temperature of the colder,peripheral parts of plasma.We critically analyzed the use of molecular emission bands as a tool for plasma diagnostics and suggested methods for possible improvements.展开更多
Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS...Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS)rate.This approach even allowed to obtain,by far,the best resolved ^(1)H spectra of molecular solids[1](https://doi.org/10.1002/anie.202216607).Deep learning based artificial intelligence is developing rapidly,and its application is deepening.Currently,there are many applications of deep learning in the field of magnetic resonance,such as the reconstruction of the under-sampled multidimensional spectra[2-4],the deconvolution of two-dimensional NMR spectra[5]and noise suppression and weak peak retrial[6],etc.展开更多
基金This project was supported by the National Key Research and Development Program of China(Grant Nos.2022YFE134200 and 2019YFA0307700)the National Natural Science Foundation of China(Grant Nos.11604119,12104177,11904192,12074145,and 11704147)the Fundamental Research Funds for the Central Universities(Grant Nos.GK202207012 and QCYRCXM-2022-241).
文摘We delve into the phenomenon of high-order harmonic generation within a helium atom under the influence of a plasmon-assisted shaping pulse.Our findings reveal an intriguing manipulation of the frequency peak position in the harmonic emission by adjusting the absolute phase parameter within the frequency domain of the shaping pulse.This phenomenon holds potential significance for experimental setups necessitating precisely tuned single harmonics.Notably,we observe a modulated shift in the created harmonic photon energy,spanning an impressive range of 1.2 eV.This frequency peak shift is rooted in the asymmetry exhibited by the rising and falling edges of the laser pulse,directly influencing the position of the peak frequency emission.Our study quantifies the dependence of this tuning range and the asymmetry of the laser pulse,offering valuable insights into the underlying mechanisms driving this phenomenon.Furthermore,our investigation uncovers the emergence of semi-integer order harmonics as the phase parameter is altered.We attribute this discovery to the intricate interference between harmonics generated by the primary and secondary return cores.This observation introduces an innovative approach for generating semi-integer order harmonics,thus expanding our understanding of high-order harmonic generation.Ultimately,our work contributes to the broader comprehension of complex phenomena in laser-matter interactions and provides a foundation for harnessing these effects in various applications,particularly those involving precise spectral control and the generation of unique harmonic patterns.
基金supported by the earmarked fund for China Agriculture Research System (CARS-36)the Key Research Project of Henan Province (221111111100)+3 种基金the Key Research Project of Ningxia Hui Autonomous Region (2022BBF02017)the Program for Changjiang Scholar and Innovation Research Team in University (IRT_15R62)China Scholarship Council (No.201913043)Hainan University.
文摘Background Nitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment.Meanwhile,the increasing demand for dairy products will result in more pollution if N losses are not controlled.Therefore,a more efficient,and environmentally friendly production system is needed,in which nitrogen use efficiency(NUE)of dairy cows plays a key role.To genetically improve NUE,extensively recorded and cost-effective proxies are essential,which can be obtained by including mid-infrared(MIR)spectra of milk in prediction models for NUE.This study aimed to develop and validate the best prediction model of NUE,nitrogen loss(NL)and dry matter intake(DMI)for individual dairy cows in China.Results A total of 86 lactating Chinese Holstein cows were used in this study.After data editing,704 records were obtained for calibration and validation.Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait.Results showed that the coefficient of determination(R2)of the best model in within-herd validation was 0.66 for NUE,0.58 for NL and 0.63 for DMI.For external validation,reasonable prediction results were only observed for NUE,with R2 ranging from 0.58 to 0.63,while the R2 of the other two traits was below 0.50.The infrared waves from 973.54 to 988.46 cm−1 and daily milk yield were the most important variables for prediction.Conclusion The results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations.The model of NUE could be used for the datasets that are similar to the calibration dataset.The prediction models for NL and 3-day moving average of DMI(DMI_a)generated lower accuracies in within-herd validation.Results also indicated that information of MIR spectra variables increased the predictive ability of models.Additionally,pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation.These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected.
文摘We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is investigated. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model for the second triplet state of the system. The investigations show that the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.
基金Project supported by the National Key Research and Development Program of China (Grant No.2017YFA0403300)the National Natural Science Foundation of China (Grant Nos.12074352 and 11675158)Fundamental Research Funds for the Central Universities in China (Grant No.YJ202144)。
文摘A study of a nanosecond laser irradiation on the titanium-layer-buried gold planar target is presented. The timeresolved x-ray emission spectra of titanium tracer are measured by a streaked crystal spectrometer. By comparing the simulated spectra obtained by using the FLYCHK code with the measured titanium spectra, the temporal plasma states, i.e.,the electron temperatures and densities, are deduced. To evaluate the feasibility of using the method for the characterization of Au plasma states, the deduced plasma states from the measured titanium spectra are compared with the Multi-1D hydrodynamic simulations of laser-produced Au plasmas. By comparing the measured and simulated results, an overall agreement for the electron temperatures is found, whereas there are deviations in the electron densities. The experiment–theory discrepancy may suggest that the plasma state could not be well reproduced by the Multi-1D hydrodynamic simulation, in which the radial gradient is not taken into account. Further investigations on the spectral characterization and hydrodynamic simulations of the plasma states are needed. All the measured and FLYCHK simulated spectra are given in this paper as datasets. The datasets are openly available at http://www.doi.org/10.57760/sciencedb.j00113.00032.
基金funded by the Ministry of Education,Science and Technological Development of the Republic of Serbia(Nos.451-03-68/2022-14/200017 and 451-03-68/2022-14/200146)the financial support of the State Committee on Science and Technology of the Republic of Belarusthe Belarusian Republican Foundation for Fundamental Research(No.F20SRBG-001)。
文摘Time-integrated optical emission analysis of laser-induced plasma on Teflon is presented.Plasma was induced under atmospheric pressure air using transversely excited atmospheric CO_(2) laser pulses.Teflon is a C-based polymer that is,among other things,interesting as a substrate for laser-induced breakdown spectroscopy analysis of liquid samples.This study aimed to determine the optimal experimental conditions for obtaining neutral and ionized C spectral lines and C2 and CN molecular band emission suitable for spectrochemical purposes.Evaluation of plasma parameters was done using several spectroscopic techniques.Stark profiles of appropriate C ionic lines were used to determine electron number density.The ratio of the integral intensity of ionic-to-atomic C spectral lines was used to determine the ionization temperature.A spectral emission of C2 Swan and CN violet bands system was used to determine the temperature of the colder,peripheral parts of plasma.We critically analyzed the use of molecular emission bands as a tool for plasma diagnostics and suggested methods for possible improvements.
基金This work was partially supported by the National Natural Science Foundation of China(Grants 22174118 and 22374124).
文摘Recently,an article on ^(1)H solid-state NMR spectra was published,in which the authors proposed a deep learning approach to infer the pure isotropic proton NMR spectra obtained at an infinite magic angle spinning(MAS)rate.This approach even allowed to obtain,by far,the best resolved ^(1)H spectra of molecular solids[1](https://doi.org/10.1002/anie.202216607).Deep learning based artificial intelligence is developing rapidly,and its application is deepening.Currently,there are many applications of deep learning in the field of magnetic resonance,such as the reconstruction of the under-sampled multidimensional spectra[2-4],the deconvolution of two-dimensional NMR spectra[5]and noise suppression and weak peak retrial[6],etc.
