Quantum Fisher information is used to witness the quantum phase transition in a non-Hermitian trapped ion system with balanced gain and loss,from the viewpoint of quantum parameter estimation.We formulate a general no...Quantum Fisher information is used to witness the quantum phase transition in a non-Hermitian trapped ion system with balanced gain and loss,from the viewpoint of quantum parameter estimation.We formulate a general non-unitary dynamic of any two-level non-Hermitian system in the form of state vector.The sudden change in the dynamics of quantum Fisher information occurs at an exceptional point characterizing quantum criticality.The dynamical behaviors of quantum Fisher information are classified into two different ways which depends on whether the system is located in symmetry unbroken or broken phase regimes.In the phase regime where parity and time reversal symmetry are unbroken,the oscillatory evolution of quantum Fisher information is presented,achieving better quantum measurement precision.In the broken phase regime,quantum Fisher information undergoes the monotonically decreasing behavior.The maximum value of quantum estimation precision is obtained at the exceptional point.It is found that the two distinct kinds of behaviors can be verified by quantum entropy and coherence.Utilizing quantum Fisher information to witness phase transition in the non-Hermitian system is emphasized.The results may have potential applications to non-Hermitian quantum information technology.展开更多
High-precision polar motion prediction is of great significance for deep space exploration and satellite navigation.Polar motion is affected by a variety of excitation factors,and nonlinear prediction methods are more...High-precision polar motion prediction is of great significance for deep space exploration and satellite navigation.Polar motion is affected by a variety of excitation factors,and nonlinear prediction methods are more suitable for polar motion prediction.In order to explore the effect of deep learning in polar motion prediction.This paper proposes a combined model based on empirical wavelet transform(EWT),Convolutional Neural Networks(CNN)and Long Short Term Memory(LSTM).By training and forecasting EOP 20C04 data,the effectiveness of the algorithm is verified,and the performance of two forecasting strategies in deep learning for polar motion prediction is explored.The results indicate that recursive multi-step prediction performs better than direct multi-step prediction for short-term forecasts within 15 days,while direct multi-step prediction is more suitable for medium and long-term forecasts.In the 365 days forecast,the mean absolute error of EWT-CNN-LSTM in the X direction and Y direction is 18.25 mas and 15.78 mas,respectively,which is 23.5% and 16.2% higher than the accuracy of Bulletin A.The results show that the algorithm has a good effect in medium and long term polar motion prediction.展开更多
Based on the monitoring data of ambient air quality and meteorological observation data,the characteristics and meteorological influencing factors of air pollution in Luojiang District of Deyang City from 2018 to 2022...Based on the monitoring data of ambient air quality and meteorological observation data,the characteristics and meteorological influencing factors of air pollution in Luojiang District of Deyang City from 2018 to 2022 were analyzed.The results show that from 2018 to 2022,the main air pollutants affecting the air quality of Luojiang District of Deyang City were PM_(2.5) and PM_(10),and the primary pollutant on heavy pollution days was basically PM_(2.5).PM_(2.5) and PM_(10) pollution showed obvious seasonal differences,and PM_(2.5) concentration exceeded the limit mainly in spring and winter,among which it was the most serious in early spring,especially in January and February,followed by December.PM_(10) exceeding the standard had a high seasonal correlation with PM_(2.5) exceeding the standard,mainly in spring and winter,among which it was the most serious in winter,especially in December,followed by January.PM_(2.5) and PM_(10) pollution showed an overall weakening trend.PM_(2.5) and PM_(10) concentration were closely related to meteorological factors such as temperature,relative humidity,wind speed,precipitation and air pressure,and were mainly affected by rainfall.展开更多
A perimeter security system based on ultra-weak fiber Bragg grating high-speed wavelength demodulation was proposed. The demodulation system for signal acquisition and high-speed wavelength calculation was designed ba...A perimeter security system based on ultra-weak fiber Bragg grating high-speed wavelength demodulation was proposed. The demodulation system for signal acquisition and high-speed wavelength calculation was designed based on field programmable gate array (FPGA) platform. The principle of ultra-weak fiber Bragg grating high-speed demodulation and signal recognition method were analyzed theoretically, and the Support Vector Machine model was introduced to optimize the event recognition accuracy of the system. A perimeter security experimental system containing 1000 ultra-weak fiber Bragg gratings, ultra-weak fiber Bragg grating sense optical cables with a diameter of 2.0 mm and a reflectivity of 0.01%, steel space frames and demodulation equipments was built to recognize four typical events such as knocking, shaking, wind blowing and rainfall. The experimental resulted show that the system has a spatial resolution of 1m and an acquisition frequency of 200 Hz. The joint time-frequency domain detection method is used to achieve 99.2% alarm accuracy, and 98% recognition accuracy of two intrusion events, which has good anti-interference performance.展开更多
BACKGROUND:The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis.In this study,we aim to introduce a model to describe and monitor the immune status of sepsis and to ...BACKGROUND:The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis.In this study,we aim to introduce a model to describe and monitor the immune status of sepsis and to explore its prognostic value.METHODS:A prospective observational study was carried out in Zhongshan Hospital,Fudan University,enrolling septic patients admitted between July 2016 and December 2018.Blood samples were collected at days 1 and 3.Serum cytokine levels(e.g.,tumor necrosis factor-α[TNF-α],interleukin-10[IL-10])and CD14+monocyte human leukocyte antigen-D-related(HLA-DR)expression were measured to serve as immune markers.Classifi cation of each immune status,namely systemic inflammatory response syndrome(SIRS),compensatory anti-inflammatory response syndrome(CARS),and mixed antagonistic response syndrome(MARS),was defined based on levels of immune markers.Changes of immune status were classifi ed into four groups which were stabilization(SB),deterioration(DT),remission(RM),and non-remission(NR).RESULTS:A total of 174 septic patients were enrolled including 50 non-survivors.Multivariate analysis discovered that IL-10 and HLA-DR expression levels at day 3 were independent prognostic factors.Patients with MARS had the highest mortality rate.Immune status of 46.1%patients changed from day 1 to day 3.Among four groups of immune status changes,DT had the highest mortality rate,followed by NR,RM,and SB with mortality rates of 64.7%,42.9%,and 11.2%,respectively.CONCLUSIONS:Severe immune disorder defi ned as MARS or deterioration of immune status defi ned as DT lead to the worst outcomes.The preliminary model of the classifi cation and dynamic monitoring of immune status based on immune markers has prognostic values and is worthy of further investigation.展开更多
文摘Quantum Fisher information is used to witness the quantum phase transition in a non-Hermitian trapped ion system with balanced gain and loss,from the viewpoint of quantum parameter estimation.We formulate a general non-unitary dynamic of any two-level non-Hermitian system in the form of state vector.The sudden change in the dynamics of quantum Fisher information occurs at an exceptional point characterizing quantum criticality.The dynamical behaviors of quantum Fisher information are classified into two different ways which depends on whether the system is located in symmetry unbroken or broken phase regimes.In the phase regime where parity and time reversal symmetry are unbroken,the oscillatory evolution of quantum Fisher information is presented,achieving better quantum measurement precision.In the broken phase regime,quantum Fisher information undergoes the monotonically decreasing behavior.The maximum value of quantum estimation precision is obtained at the exceptional point.It is found that the two distinct kinds of behaviors can be verified by quantum entropy and coherence.Utilizing quantum Fisher information to witness phase transition in the non-Hermitian system is emphasized.The results may have potential applications to non-Hermitian quantum information technology.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.42304044the Natural Science Foundation of Henan,China under grant No.222300420385。
文摘High-precision polar motion prediction is of great significance for deep space exploration and satellite navigation.Polar motion is affected by a variety of excitation factors,and nonlinear prediction methods are more suitable for polar motion prediction.In order to explore the effect of deep learning in polar motion prediction.This paper proposes a combined model based on empirical wavelet transform(EWT),Convolutional Neural Networks(CNN)and Long Short Term Memory(LSTM).By training and forecasting EOP 20C04 data,the effectiveness of the algorithm is verified,and the performance of two forecasting strategies in deep learning for polar motion prediction is explored.The results indicate that recursive multi-step prediction performs better than direct multi-step prediction for short-term forecasts within 15 days,while direct multi-step prediction is more suitable for medium and long-term forecasts.In the 365 days forecast,the mean absolute error of EWT-CNN-LSTM in the X direction and Y direction is 18.25 mas and 15.78 mas,respectively,which is 23.5% and 16.2% higher than the accuracy of Bulletin A.The results show that the algorithm has a good effect in medium and long term polar motion prediction.
文摘Based on the monitoring data of ambient air quality and meteorological observation data,the characteristics and meteorological influencing factors of air pollution in Luojiang District of Deyang City from 2018 to 2022 were analyzed.The results show that from 2018 to 2022,the main air pollutants affecting the air quality of Luojiang District of Deyang City were PM_(2.5) and PM_(10),and the primary pollutant on heavy pollution days was basically PM_(2.5).PM_(2.5) and PM_(10) pollution showed obvious seasonal differences,and PM_(2.5) concentration exceeded the limit mainly in spring and winter,among which it was the most serious in early spring,especially in January and February,followed by December.PM_(10) exceeding the standard had a high seasonal correlation with PM_(2.5) exceeding the standard,mainly in spring and winter,among which it was the most serious in winter,especially in December,followed by January.PM_(2.5) and PM_(10) pollution showed an overall weakening trend.PM_(2.5) and PM_(10) concentration were closely related to meteorological factors such as temperature,relative humidity,wind speed,precipitation and air pressure,and were mainly affected by rainfall.
文摘A perimeter security system based on ultra-weak fiber Bragg grating high-speed wavelength demodulation was proposed. The demodulation system for signal acquisition and high-speed wavelength calculation was designed based on field programmable gate array (FPGA) platform. The principle of ultra-weak fiber Bragg grating high-speed demodulation and signal recognition method were analyzed theoretically, and the Support Vector Machine model was introduced to optimize the event recognition accuracy of the system. A perimeter security experimental system containing 1000 ultra-weak fiber Bragg gratings, ultra-weak fiber Bragg grating sense optical cables with a diameter of 2.0 mm and a reflectivity of 0.01%, steel space frames and demodulation equipments was built to recognize four typical events such as knocking, shaking, wind blowing and rainfall. The experimental resulted show that the system has a spatial resolution of 1m and an acquisition frequency of 200 Hz. The joint time-frequency domain detection method is used to achieve 99.2% alarm accuracy, and 98% recognition accuracy of two intrusion events, which has good anti-interference performance.
基金the National Natural Science Foundation of China(81471840,81171837)the Shanghai Traditional Medicine Development Project(ZY3-CCCX3-3018,ZHYY-ZXYJH-201615)the Key Project of Shanghai Municipal Health Bureau(2016ZB0202).
文摘BACKGROUND:The dynamic monitoring of immune status is crucial to the precise and individualized treatment of sepsis.In this study,we aim to introduce a model to describe and monitor the immune status of sepsis and to explore its prognostic value.METHODS:A prospective observational study was carried out in Zhongshan Hospital,Fudan University,enrolling septic patients admitted between July 2016 and December 2018.Blood samples were collected at days 1 and 3.Serum cytokine levels(e.g.,tumor necrosis factor-α[TNF-α],interleukin-10[IL-10])and CD14+monocyte human leukocyte antigen-D-related(HLA-DR)expression were measured to serve as immune markers.Classifi cation of each immune status,namely systemic inflammatory response syndrome(SIRS),compensatory anti-inflammatory response syndrome(CARS),and mixed antagonistic response syndrome(MARS),was defined based on levels of immune markers.Changes of immune status were classifi ed into four groups which were stabilization(SB),deterioration(DT),remission(RM),and non-remission(NR).RESULTS:A total of 174 septic patients were enrolled including 50 non-survivors.Multivariate analysis discovered that IL-10 and HLA-DR expression levels at day 3 were independent prognostic factors.Patients with MARS had the highest mortality rate.Immune status of 46.1%patients changed from day 1 to day 3.Among four groups of immune status changes,DT had the highest mortality rate,followed by NR,RM,and SB with mortality rates of 64.7%,42.9%,and 11.2%,respectively.CONCLUSIONS:Severe immune disorder defi ned as MARS or deterioration of immune status defi ned as DT lead to the worst outcomes.The preliminary model of the classifi cation and dynamic monitoring of immune status based on immune markers has prognostic values and is worthy of further investigation.
