Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI present...Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.展开更多
In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above ...In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.展开更多
Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in...Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.展开更多
Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).C...Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.展开更多
Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter i...Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter identification model that is independent of position error by combining the dq-axis voltage equations. Then, a novel dual signal alternate injection method is proposed to address the rank-deficiency issue, i.e., during one injection period, a zero, positive, and negative d-axis current injection together with a rotor position offset injection, to simultaneously identify the multi-parameters, including stator resistance, dq-axis inductances, and PM flux linkage. The proposed method is verified by experiments at different dq-axis current conditions.展开更多
This study aims to investigate the responses of a perovskite-based direct-conversion dual-layer flat-panel detector(DL-FPD)numerically.To this end,the X-ray sensitivity,spatial resolution quantified by the modulation ...This study aims to investigate the responses of a perovskite-based direct-conversion dual-layer flat-panel detector(DL-FPD)numerically.To this end,the X-ray sensitivity,spatial resolution quantified by the modulation transfer function(MTF),and detective quantum efficiency(DQE)of the DL-FPD are evaluated numerically using a linear cascade model.In addition,both the single-crystal(SC)and polycrystalline(PC)structures of MAPbI_(3)are investigated,along with various other key parameters such as the material thickness,electric field strength,X-ray beam spectrum,and electronic readout noise.The results demonstrate that SC perovskite consistently exhibits better performance than PC perovskite owing to fewer material defects.Increasing the layer thickness may decrease the MTF,but can also enhance the sensitivity and DQE.Moreover,appropriately increasing the external electric field within the material can improve the sensitivity,MTF,and DQE.Finally,reducing the electronic readout noise can significantly enhance the DQE for low-dose imaging.This study demonstrates the potential of high-quality dual-energy X-ray imaging using direct-conversion perovskite DL-FPDs.展开更多
Traditional digitizers for signal readout of PET detectors are based on commercial analog-to-digital converters(ADC).However,the cost and power consumption of an entire electronic readout system based on digitizers fo...Traditional digitizers for signal readout of PET detectors are based on commercial analog-to-digital converters(ADC).However,the cost and power consumption of an entire electronic readout system based on digitizers for a PET scanner are high.To address this problem,a soft-core ADC based on a field-programmable gate array(FPGA)was proposed.An FPGA-based ADC(FPGA-ADC)combines low loss and high performance.To achieve good performance,the FPGA-ADC requires three calibrations:time-to-digital converter(TDC)length calibration,TDC alignment calibration,and TDC-to-ADC calibration.A prototype front-end electronics based on FPGA-ADC was built to evaluate the performance of time-of-flight positron emission tomography(TOF PET)detectors.Each PET detector consists of a LYSO crystal single-ended coupled to a silicon photomultiplier(SiPM).The experimental results show that the full-width at half-maximum(FWHM)energy resolution for 511 keV gamma photons after saturation correction of the SiPM was 12.3%.The FWHM coincidence timing resolution(CTR)of the TOF PET detector with the readout of the front-end electronic prototype is 385.2 ps.FPGA-ADCbased front-end electronics are very promising for multichannel,low-cost,highly integrated,and power-efficient readout electronic systems for radiation detector applications.展开更多
Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effect...Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effects and flexible extensibility for visualization in HEP experiments.In this study,we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory(JUNO)experiment.This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces.The VR methodology facilitates an immersive exploration of the virtual environment in JUNO,enabling users to investigate the detector geometry,visualize event data,and tune the detector simulation and event reconstruction algorithms.Additionally,this approach supports applications in data monitoring,physics data analysis,and public outreach initiatives.展开更多
We present the preparation and measurement of the radioactive isotope^(37)Ar,which was produced using thermal neutrons from a reactor,as a calibration source for liquid xenon time projection chambers.^(37)Ar is a low-...We present the preparation and measurement of the radioactive isotope^(37)Ar,which was produced using thermal neutrons from a reactor,as a calibration source for liquid xenon time projection chambers.^(37)Ar is a low-energy calibration source with a half-life of 35.01 days,making it suitable for calibration in the low-energy region of liquid xenon dark-matter experiments.Radioactive isotope^(37)Ar was produced by irradiating ^(36)Ar with thermal neutrons.It was subsequently measured in a gaseous xenon time projection chamber(GXe TPC)to validate its radioactivity.Our results demonstrate that^(37)Ar is an effective and viable calibration source that offers precise calibration capabilities in the low-energy domain of xenon-based detectors.展开更多
We here report a high system detection efficiency(SDE)superconducting single-photon detector(SSPD)at 2μm wavelength.The device integrates a SiO_(2)/Ta_(2)O_(5)distributed Bragg reflector(DBR)and a sandwich-structured...We here report a high system detection efficiency(SDE)superconducting single-photon detector(SSPD)at 2μm wavelength.The device integrates a SiO_(2)/Ta_(2)O_(5)distributed Bragg reflector(DBR)and a sandwich-structured double-layer NbN nanowire to enhance the optical absorption efficiency.A cold development technique is implemented to optimize the superconducting nanowires with sub-40-nm linewidths,thus enhancing the intrinsic detection efficiency(IDE).The fabricated SSPD shows an SDE exceeding 90% at 2μm wavelength.Moreover,the detector allows an operational working temperature of 2.2 K provided by a compact GM cryo-cooler.This detector delivers excellent performance at the 2μm wavelength,and its optimized structural design implies promising potential for extending detection toward longer infrared bands.It thus holds value for advancing high-sensitivity quantum technologies,mid-infrared optical communications,and dark matter detection research.展开更多
The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such...The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.展开更多
Formamidinium lead iodide(FAPbI_(3))perovskite exhibits an impressive X-ray absorption coefficient and a large carrier mobility-lifetime product(μτ),making it as a highly promising candidate for X-ray detection appl...Formamidinium lead iodide(FAPbI_(3))perovskite exhibits an impressive X-ray absorption coefficient and a large carrier mobility-lifetime product(μτ),making it as a highly promising candidate for X-ray detection application.However,the presence of larger FA^(+)cation induces to an expansion of the Pb-I octahedral framework,which unfortunately affects both the stability and charge carrier mobility of the corresponding devices.To address this challenge,we develop a novel low-dimensional(HtrzT)PbI_(3) perovskite featuring a conjugated organic cation(1H-1,2,4-Triazole-3-thiol,HtrzT^(+))which matches well with theα-FAPbI_(3) lattices in two-dimensional plane.Benefiting from the matched lattice between(HtrzT)PbI_(3) andα-FAPbI_(3),the anchored lattice enhances the Pb-I bond strength and effectively mitigates the inherent tensile strain of theα-FAPbI_(3) crystal lattice.The X-ray detector based on(HtrzT)PbI_(3)(1.0)/FAPbI_(3) device achieves a remarkable sensitivity up to 1.83×10^(5)μC Gy_(air)^(−1) cm^(−2),along with a low detection limit of 27.6 nGy_(air) s^(−1),attributed to the release of residual stress,and the enhancement in carrier mobility-lifetime product.Furthermore,the detector exhibits outstanding stability under X-ray irradiation with tolerating doses equivalent to nearly 1.17×10^(6) chest imaging doses.展开更多
Soft X-ray detectors play a vital role in materials science,high-energy physics and medical imaging.Cs_(2)AgBiBr_(6),a lead-free double perovskite,has gained attention for its excellent optoelectronic properties,stabi...Soft X-ray detectors play a vital role in materials science,high-energy physics and medical imaging.Cs_(2)AgBiBr_(6),a lead-free double perovskite,has gained attention for its excellent optoelectronic properties,stability,and nontoxicity.However,its fast crystallization and requirement for high-temperature annealing(>250℃)often lead to inferior film quality,limiting its application in flexible devices.This study introduces an alloying strategy that significantly improves the quality of Cs_(2)AgBiBr_(6)thin films annealed at a reduced temperature of 150℃.Devices based on the alloyed thin films exhibit an ultra-low dark current of 0.32 nA·cm^(-2)and a quantum efficiency of 725%.Furthermore,the first successful integration of Cs_(2)AgBiBr_(6)with a thinfilm transistor backplane demonstrates its superior imaging performance,indicating that Cs_(2)AgBiBr_(6)is a promising material for next-generation soft X-ray sensors.展开更多
Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings ...Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings to remain competitive.Instructors cannot effectively monitor every individual in a virtual environment,which raises significant concerns about participant fatigue.Our proposed system monitors fatigue,identifying attentive and drowsy individuals throughout the online session.We leverage Dlib’s pre-trained facial landmark detector and focus on the eye landmarks only,offering a more detailed analysis for predicting eye opening and closing of the eyes,rather than focusing on the entire face.We introduce an Eye Polygon Area(EPA)formula,which computes eye activity from Dlib eye landmarks by measuring the polygonal area of the eye opening.Unlike the Eye Aspect Ratio(EAR),which relies on a single distance ratio,EPA adapts to different eye shapes(round,narrow,or wide),providing a more reliable measure for fatigue detection.The VMFD system issues a warning if a participant remains in a fatigued condition for 36 consecutive frames.The proposed technology is tested under multiple scenarios,including low-to high-lighting conditions(50-1400 lux)and both with and without glasses.This study builds an OpenCV application in Python,evaluated using the iBUG 300-W dataset,achieving 97.5%accuracy in detecting active participants.We compare VMFD with conventional methods relying on the EAR and show that the EPA technique performs significantly better.展开更多
Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powe...Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.展开更多
Electric vehicle power battery consistency is the key factor affecting the performance of power batteries. it is not scientific to evaluate the consistency of the battery depending on voltage or capacity. In this pape...Electric vehicle power battery consistency is the key factor affecting the performance of power batteries. it is not scientific to evaluate the consistency of the battery depending on voltage or capacity. In this paper, multi- parameter evaluation method for battery consistency based on principal component analysis is proposed. Firstly, the characteristic parameters of battery consistency are analyzed, the principal component score can be used as the basis for evaluating the consistency of the battery. Then, the function that multi-parameter evaluation of battery consistency is established. Finally, battery balancing strategy based on fuzzy control is developed. The basic principle of fuzzy control is to fuzzy the input quantity based on expert knowledge, and the fuzzy control auantitv is obtained bv fuzzy control rule_ Th~ re.~nlt.~ ~ro v^rlfiocl hv t,~t展开更多
AIM In our previous study, we have built a nine-gene(GPC3, HGF, ANXA1, FOS, SPAG9, HSPA1 B, CXCR4, PFN1, and CALR) expression detection system based on the Ge XP system. Based on peripheral blood and Ge XP, we aimed t...AIM In our previous study, we have built a nine-gene(GPC3, HGF, ANXA1, FOS, SPAG9, HSPA1 B, CXCR4, PFN1, and CALR) expression detection system based on the Ge XP system. Based on peripheral blood and Ge XP, we aimed to analyze the results of genes expression by different multi-parameter analysis methods and build a diagnostic model to classify hepatocellular carcinoma(HCC) patients and healthy people.METHODS Logistic regression analysis, discriminant analysis, classification tree analysis, and artificial neural network were used for the multi-parameter gene expression analysis method. One hundred and three patients with early HCC and 54 age-matched healthy normal controls were used to build a diagnostic model. Fiftytwo patients with early HCC and 34 healthy people were used for validation. The area under the curve, sensitivity, and specificity were used as diagnostic indicators.RESULTS Artificial neural network of the total nine genes had the best diagnostic value, and the AUC, sensitivity, and specificity were 0.943, 98%, and 85%, respectively. At last, 52 HCC patients and 34 healthy normal controls were used for validation. The sensitivity and specificity were 96% and 86%, respectively.CONCLUSION Multi-parameter analysis methods may increase the diagnostic value compared to single factor analysis and they may be a trend of the clinical diagnosis in the future.展开更多
An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Sin...An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.展开更多
Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods r...Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.展开更多
The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary r...The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary relationship and the design of highspeed pantographs.Good pantograph-catenary coupling quality is the essential condition to ensure safe and efficient operation of high-speed train,stable and reliable current collection,and reduction in the wear of contact wires and pantograph contact strips.Among them,the dynamic parameters of high-speed pantographs are crucial to pantograph-catenary coupling quality.With the reduction of the standard deviation of the pantograph-catenary contact force as the optimization goal,multi-parameter joint optimization designs for the high-speed pantograph with two contact strips at multiple running speeds are proposed.Moreover,combining the sensitivity analysis at the optimal solutions,with the parameters and characteristics of in-service DSA380 highspeed pantograph,the optimization proposal of DSA380 was given.展开更多
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(Grant No.2021QNLM020001)the National Key R&D Program of China(Grant No.2019YFC0605503C)+2 种基金the Major Scientific and Technological Projects of China National Petroleum Corporation(CNPC)(Grant No.ZD2019-183-003)the National Outstanding Youth Science Foundation(Grant No.41922028)the National Innovation Group Project(Grant No.41821002).
文摘Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.
基金Supported by The National Undergraduate Innovation Training Program(Grant No.202310290069Z).
文摘In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.
基金supported by the National Natural Science Foundation of China(Grant No.12075323)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300702).
文摘Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.
基金the financial supports of the National Natural Science Foundation of China(No.52372200)a project supported by the State Key Laboratory of Mechanics and Control for Aerospace Structures(No.MCAS-S-0324G01)。
文摘Battery safety has emerged as a critical challenge for achieving carbon neutrality,driven by the increasing frequency of thermal runaway incidents in electric vehicles(EVs)and stationary energy storage systems(ESSs).Conventional battery monitoring technologies struggle to track multiple physicochemical parameters in real time,hindering early hazard detection.Embedded optical fiber sensors have gained prominence as a transformative solution for next-generation smart battery sensing,owing to their micrometer size,multiplexing capability,and electromagnetic immunity.However,comprehensive reviews focusing on their advancements in operando multi-parameter monitoring remain scarce,despite their critical importance for ensuring battery safety.To address this gap,this review first introduces a classification and the fundamental principles of advanced battery-oriented optical fiber sensors.Subsequently,it summarizes recent developments in single-parameter battery monitoring using optical fiber sensors.Building on this foundation,this review presents the first comprehensive analysis of multifunctional optical fiber sensing platforms capable of simultaneously tracking temperature,strain,pressure,refractive index,and monitoring battery aging.Targeted strategies are proposed to facilitate the practical development of this technology,including optimization of sensor integration techniques,minimizing sensor invasiveness,resolving the cross-sensitivity of fiber Bragg grating(FBG)through structural innovation,enhancing techno-economics,and combining with artificial intelligence(AI).By aligning academic research with industry requirements,this review provides a methodological roadmap for developing robust optical sensing systems to ensure battery safety in decarbonization-driven applications.
文摘Under sensorless control, the position estimation error in interior permanent magnet(PM) synchronous machines will lead to parameter identification errors and a rank-deficiency issue. This paper proposes a parameter identification model that is independent of position error by combining the dq-axis voltage equations. Then, a novel dual signal alternate injection method is proposed to address the rank-deficiency issue, i.e., during one injection period, a zero, positive, and negative d-axis current injection together with a rotor position offset injection, to simultaneously identify the multi-parameters, including stator resistance, dq-axis inductances, and PM flux linkage. The proposed method is verified by experiments at different dq-axis current conditions.
基金supported in part by the National Natural Science Foundation of China(Nos.12305349,12235006,12027812)Shenzhen Science and Technology Program(No.JSGGKQTD20210831174329010)Guangdong Basic and Applied Basic Research Foundation(No.2021TQ06Y108).
文摘This study aims to investigate the responses of a perovskite-based direct-conversion dual-layer flat-panel detector(DL-FPD)numerically.To this end,the X-ray sensitivity,spatial resolution quantified by the modulation transfer function(MTF),and detective quantum efficiency(DQE)of the DL-FPD are evaluated numerically using a linear cascade model.In addition,both the single-crystal(SC)and polycrystalline(PC)structures of MAPbI_(3)are investigated,along with various other key parameters such as the material thickness,electric field strength,X-ray beam spectrum,and electronic readout noise.The results demonstrate that SC perovskite consistently exhibits better performance than PC perovskite owing to fewer material defects.Increasing the layer thickness may decrease the MTF,but can also enhance the sensitivity and DQE.Moreover,appropriately increasing the external electric field within the material can improve the sensitivity,MTF,and DQE.Finally,reducing the electronic readout noise can significantly enhance the DQE for low-dose imaging.This study demonstrates the potential of high-quality dual-energy X-ray imaging using direct-conversion perovskite DL-FPDs.
基金supported by the Key R&D Program of Shandong Province(No.2023SFGC0101)Shandong Excellent Young Scientists Fund Program(Overseas)(No.2023HWYQ-047)+1 种基金the Natural Science Foundation of Shandong Province(No.ZR2022QA039)the National Natural Science Foundation of China(NSFC)(No.U2106202).
文摘Traditional digitizers for signal readout of PET detectors are based on commercial analog-to-digital converters(ADC).However,the cost and power consumption of an entire electronic readout system based on digitizers for a PET scanner are high.To address this problem,a soft-core ADC based on a field-programmable gate array(FPGA)was proposed.An FPGA-based ADC(FPGA-ADC)combines low loss and high performance.To achieve good performance,the FPGA-ADC requires three calibrations:time-to-digital converter(TDC)length calibration,TDC alignment calibration,and TDC-to-ADC calibration.A prototype front-end electronics based on FPGA-ADC was built to evaluate the performance of time-of-flight positron emission tomography(TOF PET)detectors.Each PET detector consists of a LYSO crystal single-ended coupled to a silicon photomultiplier(SiPM).The experimental results show that the full-width at half-maximum(FWHM)energy resolution for 511 keV gamma photons after saturation correction of the SiPM was 12.3%.The FWHM coincidence timing resolution(CTR)of the TOF PET detector with the readout of the front-end electronic prototype is 385.2 ps.FPGA-ADCbased front-end electronics are very promising for multichannel,low-cost,highly integrated,and power-efficient readout electronic systems for radiation detector applications.
基金supported by the National Natural Science Foundation of China(Nos.12175321,W2443004,11975021,11675275,U1932101)Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA10010900)+2 种基金National Key Research and Development Program of China(Nos.2023YFA1606000 and 2020YFA0406400)National College Students Science and Technology Innovation ProjectUndergraduate Base Scientific Research Project of Sun Yat-sen University。
文摘Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effects and flexible extensibility for visualization in HEP experiments.In this study,we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory(JUNO)experiment.This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces.The VR methodology facilitates an immersive exploration of the virtual environment in JUNO,enabling users to investigate the detector geometry,visualize event data,and tune the detector simulation and event reconstruction algorithms.Additionally,this approach supports applications in data monitoring,physics data analysis,and public outreach initiatives.
基金supported by National Key R&D grant from the Ministry of Science and Technology of China(Nos.2021YFA1601600,2023YFA1606200)National Science Foundation of China(Nos.12090062,12105008)the Major State Basic Research Development Program of China.
文摘We present the preparation and measurement of the radioactive isotope^(37)Ar,which was produced using thermal neutrons from a reactor,as a calibration source for liquid xenon time projection chambers.^(37)Ar is a low-energy calibration source with a half-life of 35.01 days,making it suitable for calibration in the low-energy region of liquid xenon dark-matter experiments.Radioactive isotope^(37)Ar was produced by irradiating ^(36)Ar with thermal neutrons.It was subsequently measured in a gaseous xenon time projection chamber(GXe TPC)to validate its radioactivity.Our results demonstrate that^(37)Ar is an effective and viable calibration source that offers precise calibration capabilities in the low-energy domain of xenon-based detectors.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDA0520403)Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)+1 种基金Innovation Program for Quantum Science and Technology(Grant No.2023ZD0300100)the National Natural Science Foundation of China(Grant Nos.U24A20320 and 62401554)。
文摘We here report a high system detection efficiency(SDE)superconducting single-photon detector(SSPD)at 2μm wavelength.The device integrates a SiO_(2)/Ta_(2)O_(5)distributed Bragg reflector(DBR)and a sandwich-structured double-layer NbN nanowire to enhance the optical absorption efficiency.A cold development technique is implemented to optimize the superconducting nanowires with sub-40-nm linewidths,thus enhancing the intrinsic detection efficiency(IDE).The fabricated SSPD shows an SDE exceeding 90% at 2μm wavelength.Moreover,the detector allows an operational working temperature of 2.2 K provided by a compact GM cryo-cooler.This detector delivers excellent performance at the 2μm wavelength,and its optimized structural design implies promising potential for extending detection toward longer infrared bands.It thus holds value for advancing high-sensitivity quantum technologies,mid-infrared optical communications,and dark matter detection research.
基金Under the auspices of the National Natural Science Foundation of China(No.42271224,41901193)Ministry of Edu cation Humanities and Social Sciences Research Planning Fund Project of China(No.24YJAZH190)+1 种基金Anhui Province Excellent Youth Research Project in Universities(No.2022AH030019)Anhui Social Sciences Innovation Development Research Project(No.2024CXQ503)。
文摘The accessibility of urban public transit directly influences residents’quality of life,travel behavior,and social equity.Its correlation with housing prices has garnered significant attention across disciplines such as geography,economics,and urban planning.Although much existing research focuses on the impact of individual transportation facilities on housing prices,there is a notable gap in comprehensive analyses that assess the influence of overall urban transit accessibility on housing market dynamics.This study selected the main urban area of Hefei,China,as a case to investigate the spatial distribution of housing prices and evaluate public transit accessibility in 2022.Employing techniques such as the optimized parameter geographical detector and local spatial regression models,the study aimed to elucidate the effects and underlying mechanisms of urban transit accessibility on housing prices.The findings revealed that:1)housing prices in Hefei exhibited a clustered spatial pattern,with high prices concentrated in the city center and lower prices in peripheral areas,forming three distinct high-price hotspots with a‘belt-like’distribution;2)public transit accessibility showed a‘coreperiphery’structure,with accessibility declining in a‘circumferential’pattern around the city center.Based on the‘housing price-accessibility’dimension,four categories were identified:high price-high accessibility(37.25%),high price-low accessibility(19.07%),low price-high accessibility(21.95%),and low price-low accessibility(21.73%);3)the impact of transit accessibility on housing prices was spatially heterogeneous,with bus travel showing the strongest explanatory power(0.692),followed by automobile,subway,and bicycle travel.The interaction of these transportation modes generated a synergistic effect on housing price differentiation,with most influencing factors contributing more than 25%.These findings offer valuable insights for optimizing the spatial distribution of public transit infrastructure and improving both urban housing quality and residents’living standards.
基金supports from the National Natural Science Foundation of China(22375220,U2001214,22471302)the Guangdong Basic and Applied Basic Research Foundation(2024B1515020101)Open Project Fund from State Key Laboratory of Optoelectronic Materials and Technologies(OEMT-2024-KF-08).
文摘Formamidinium lead iodide(FAPbI_(3))perovskite exhibits an impressive X-ray absorption coefficient and a large carrier mobility-lifetime product(μτ),making it as a highly promising candidate for X-ray detection application.However,the presence of larger FA^(+)cation induces to an expansion of the Pb-I octahedral framework,which unfortunately affects both the stability and charge carrier mobility of the corresponding devices.To address this challenge,we develop a novel low-dimensional(HtrzT)PbI_(3) perovskite featuring a conjugated organic cation(1H-1,2,4-Triazole-3-thiol,HtrzT^(+))which matches well with theα-FAPbI_(3) lattices in two-dimensional plane.Benefiting from the matched lattice between(HtrzT)PbI_(3) andα-FAPbI_(3),the anchored lattice enhances the Pb-I bond strength and effectively mitigates the inherent tensile strain of theα-FAPbI_(3) crystal lattice.The X-ray detector based on(HtrzT)PbI_(3)(1.0)/FAPbI_(3) device achieves a remarkable sensitivity up to 1.83×10^(5)μC Gy_(air)^(−1) cm^(−2),along with a low detection limit of 27.6 nGy_(air) s^(−1),attributed to the release of residual stress,and the enhancement in carrier mobility-lifetime product.Furthermore,the detector exhibits outstanding stability under X-ray irradiation with tolerating doses equivalent to nearly 1.17×10^(6) chest imaging doses.
基金supported by the NSFC under Grant No.62474169the National Key Research and Development Program of China under Grant No.2024YFB3212200the funding from USTC under Grant Nos.WK2100000025,KY2190000003,and KY2190000006。
文摘Soft X-ray detectors play a vital role in materials science,high-energy physics and medical imaging.Cs_(2)AgBiBr_(6),a lead-free double perovskite,has gained attention for its excellent optoelectronic properties,stability,and nontoxicity.However,its fast crystallization and requirement for high-temperature annealing(>250℃)often lead to inferior film quality,limiting its application in flexible devices.This study introduces an alloying strategy that significantly improves the quality of Cs_(2)AgBiBr_(6)thin films annealed at a reduced temperature of 150℃.Devices based on the alloyed thin films exhibit an ultra-low dark current of 0.32 nA·cm^(-2)and a quantum efficiency of 725%.Furthermore,the first successful integration of Cs_(2)AgBiBr_(6)with a thinfilm transistor backplane demonstrates its superior imaging performance,indicating that Cs_(2)AgBiBr_(6)is a promising material for next-generation soft X-ray sensors.
文摘Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings to remain competitive.Instructors cannot effectively monitor every individual in a virtual environment,which raises significant concerns about participant fatigue.Our proposed system monitors fatigue,identifying attentive and drowsy individuals throughout the online session.We leverage Dlib’s pre-trained facial landmark detector and focus on the eye landmarks only,offering a more detailed analysis for predicting eye opening and closing of the eyes,rather than focusing on the entire face.We introduce an Eye Polygon Area(EPA)formula,which computes eye activity from Dlib eye landmarks by measuring the polygonal area of the eye opening.Unlike the Eye Aspect Ratio(EAR),which relies on a single distance ratio,EPA adapts to different eye shapes(round,narrow,or wide),providing a more reliable measure for fatigue detection.The VMFD system issues a warning if a participant remains in a fatigued condition for 36 consecutive frames.The proposed technology is tested under multiple scenarios,including low-to high-lighting conditions(50-1400 lux)and both with and without glasses.This study builds an OpenCV application in Python,evaluated using the iBUG 300-W dataset,achieving 97.5%accuracy in detecting active participants.We compare VMFD with conventional methods relying on the EAR and show that the EPA technique performs significantly better.
基金provided by the State Key Research Development Program of China (No.2016YFC0801403)Key Research Development Program of Jiangsu Provence (No.BE2015040)+1 种基金National Natural Science Foundation of China (Nos.51674253,51734009 and 51604270)Natural Science Foundation of Jiangsu Province (No.BK20171191)
文摘Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.
基金the Special Research Fund for the National Key Research and Development Program of China(No.2016YFB0100107)the National Natural Science Foundation of China(No.51677183)
文摘Electric vehicle power battery consistency is the key factor affecting the performance of power batteries. it is not scientific to evaluate the consistency of the battery depending on voltage or capacity. In this paper, multi- parameter evaluation method for battery consistency based on principal component analysis is proposed. Firstly, the characteristic parameters of battery consistency are analyzed, the principal component score can be used as the basis for evaluating the consistency of the battery. Then, the function that multi-parameter evaluation of battery consistency is established. Finally, battery balancing strategy based on fuzzy control is developed. The basic principle of fuzzy control is to fuzzy the input quantity based on expert knowledge, and the fuzzy control auantitv is obtained bv fuzzy control rule_ Th~ re.~nlt.~ ~ro v^rlfiocl hv t,~t
基金National Key R&D Program of China,No.2016YFC0106604National Natural Science Foundation of China,No.81471761 and No.81501568
文摘AIM In our previous study, we have built a nine-gene(GPC3, HGF, ANXA1, FOS, SPAG9, HSPA1 B, CXCR4, PFN1, and CALR) expression detection system based on the Ge XP system. Based on peripheral blood and Ge XP, we aimed to analyze the results of genes expression by different multi-parameter analysis methods and build a diagnostic model to classify hepatocellular carcinoma(HCC) patients and healthy people.METHODS Logistic regression analysis, discriminant analysis, classification tree analysis, and artificial neural network were used for the multi-parameter gene expression analysis method. One hundred and three patients with early HCC and 54 age-matched healthy normal controls were used to build a diagnostic model. Fiftytwo patients with early HCC and 34 healthy people were used for validation. The area under the curve, sensitivity, and specificity were used as diagnostic indicators.RESULTS Artificial neural network of the total nine genes had the best diagnostic value, and the AUC, sensitivity, and specificity were 0.943, 98%, and 85%, respectively. At last, 52 HCC patients and 34 healthy normal controls were used for validation. The sensitivity and specificity were 96% and 86%, respectively.CONCLUSION Multi-parameter analysis methods may increase the diagnostic value compared to single factor analysis and they may be a trend of the clinical diagnosis in the future.
基金supported by the National Natural Science Foundation of China(6153102061471383)
文摘An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.
基金co-supported by the National Basic Research Program of China(No.2015CB057304)the National Natural Science Foundation of China(Nos.51535004 and91648111)
文摘Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel.Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.
基金the National Natural Science Foundation of China(Grant No.11672297)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB22020200).
文摘The significant increase in speed of high-speed train will cause the dynamic contact force of the pantograph-catenary system to fluctuate more severely,which poses a challenge to the study of the pantograph-catenary relationship and the design of highspeed pantographs.Good pantograph-catenary coupling quality is the essential condition to ensure safe and efficient operation of high-speed train,stable and reliable current collection,and reduction in the wear of contact wires and pantograph contact strips.Among them,the dynamic parameters of high-speed pantographs are crucial to pantograph-catenary coupling quality.With the reduction of the standard deviation of the pantograph-catenary contact force as the optimization goal,multi-parameter joint optimization designs for the high-speed pantograph with two contact strips at multiple running speeds are proposed.Moreover,combining the sensitivity analysis at the optimal solutions,with the parameters and characteristics of in-service DSA380 highspeed pantograph,the optimization proposal of DSA380 was given.
