To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a de...To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a deep unfolded amplitude-phase error self-calibration network.Firstly,a sparse-based DOA model with an array convex error restriction is established,which gets resolved via an alternating iterative minimization(AIM)algo-rithm.The algorithm is then unrolled to a deep network known as AE-AIM Network(AE-AIM-Net),where all parameters are opti-mized through multi-task learning using the constructed com-plete dataset.The results of the simulation and theoretical analy-sis suggest that the proposed unfolded network achieves lower computational costs compared to typical sparse recovery meth-ods.Furthermore,it maintains excellent estimation performance even in the presence of array magnitude-phase errors.展开更多
Microstructured roll workpieces have been widely used as functional components in the precision industries. Current researches on quality control have focused on surface profile measurement of microstructured roll wor...Microstructured roll workpieces have been widely used as functional components in the precision industries. Current researches on quality control have focused on surface profile measurement of microstructured roll workpieces, and types of measurement systems and measurement methods have been developed. However, low measurement efficiency and low measurement accuracy caused by setting errors are the common disadvantages for surface profile measurement of microstructured roll workpieces. In order to shorten the measurement time and enhance the measurement accuracy, a method for self-calibration and compensation of setting errors is proposed for surface profile measurement of microstructured roll workpieces. A measurement system is constructed for the measurement, in which a precision spindle is employed to rotate the roll workpiece and an air-bearing displacement sensor with a micro-stylus probe is employed to scan the microstructured surface of the roll workpiece. The resolution of the displacement sensor is 0.14 nm and that of the rotary encoder of the spindle was 0.15r~. Geometrical and mathematical models are established for analyzing the influences of the setting errors of the roll workpiece and the displacement sensor with respect to the axis of the spindle, including the eccentric error of the roll workpiece, the offset error of the sensor axis and the zero point error of the sensor output. Measurement experiments are carded out on a roll workpiece on which periodic microstructures are a period of 133 i^m along the circumferential direction. Experimental results demonstrate the feasibility of the self-compensation method. The proposed method can be used to detect and compensate the setting errors without using any additional accurate artifact.展开更多
Laser tracking system （LTS） is an advanced device for large size 3D coordinates measuring with the advantages of broad range, high speed and high accuracy. However, its measuring accuracy is highly dominated by the ...Laser tracking system （LTS） is an advanced device for large size 3D coordinates measuring with the advantages of broad range, high speed and high accuracy. However, its measuring accuracy is highly dominated by the geometric errors of the tracking mirror mechanism. Proper calibration of LTS is essential prior to the use of it for metrology. A kinematics model that describes not only the motion but also the geometric variations of LTS is developed. Through error analysis of the proposed model, it is claimed that gimbals axis misalignments and tracking mirror center off-set are the key contributors to measuring errors of LTS. A self-calibration method is presented of calibrating LTS with planar constraints. Various calibration strategies utilizing single-plane and multiple-plane constraints are proposed for different situations. For each calibration strategy, issues about the error parameter estimation of LTS are exploded to find out in which conditions these parameters can be uniquely estimated. Moreover, these conditions reveal the applicability of the planar constraints to LTS self-calibration. Intensive studies have been made to check validity of the theoretical results. The results show that the measuring accuracy of LTS has increased by 5 times since this technique for calibration is used.展开更多
Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibratio...Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibration ratiometric fluorescent sensing platform has been designed for sensitive visual detection of levofloxacin(LEV)based on fluorescent europium metal-organic framework(Eu-MOF)probe.Specifically,the Eu-MOF was facilely synthesized via directly mixing Eu^(3+)with 1,10-phenanthroline-2,9-dicarboxylic acid(PDA)ligand at room temperature,which exhibited well-stable red fluorescence at 612 nm.Upon the addition of target LEV,the significant fluorescence quenching from Eu^(3+)was observed owing to the inner filter effect between the Eu-MOF and LEV.While the intrinsic fluorescence for LEV at 462nm was gradually enhanced,thereby realizing the self-calibration ratiometric fluorescence responses to LEV.Through this strategy,LEV can be detected down to 27 nmol/L.Furthermore,a test paper-based Eu-MOF integrated with the smartphone assisted RGB color analysis was exploited for the quantitative monitoring of LEV through the multi-color changes from red to blue,thus achieved portable,convenient and visual detection of LEV in honey and milk samples.Therefore,the developed strategy could provide a useful tool for supporting the practical on-site test in food samples.展开更多
This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administratio...This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administration.The analysis reveals systematic improvements in both track and intensity forecasts over the decade,with distinct error characteristics observed across various forecast parameters.Track forecast errors have steadily decreased,particularly for longer lead times,while error magnitudes have increased with longer forecast lead times.Intensity forecasts show similar progressive enhancements,with maximum sustained wind speed errors decreasing by 0.26 m/s per year for 120 h forecasts.The study also identifies several key patterns in forecast performance:typhoon-grade or stronger TCs exhibit smaller track errors than week or weaker systems;intensity forecasts systematically overestimate weaker TCs while underestimating stronger systems;and spatial error distributions show greater track inaccuracies near landmasses and regional intensity biases.These findings highlight both the significant advances in TC forecasting capability achieved through improved modeling and observational systems,and the remaining challenges in predicting TC changes and landfall behavior,providing valuable benchmarks for future forecast system development.展开更多
AIM:To evaluate the efficacy of the total computer vision syndrome questionnaire(CVS-Q)score as a predictive tool for identifying individuals with symptomatic binocular vision anomalies and refractive errors.METHODS:A...AIM:To evaluate the efficacy of the total computer vision syndrome questionnaire(CVS-Q)score as a predictive tool for identifying individuals with symptomatic binocular vision anomalies and refractive errors.METHODS:A total of 141 healthy computer users underwent comprehensive clinical visual function assessments,including evaluations of refractive errors,accommodation(amplitude of accommodation,positive relative accommodation,negative relative accommodation,accommodative accuracy,and accommodative facility),and vergence(phoria,positive and negative fusional vergence,near point of convergence,and vergence facility).Total CVS-Q scores were recorded to explore potential associations between symptom scores and the aforementioned clinical visual function parameters.RESULTS:The cohort included 54 males(38.3%)with a mean age of 23.9±0.58y and 87 age-matched females(61.7%)with a mean age of 23.9±0.53y.The multiple regression model was statistically significant[R²=0.60,F=13.28,degrees of freedom(DF=17122,P<0.001].This indicates that 60%of the variance in total CVS-Q scores(reflecting reported symptoms)could be explained by four clinical measurements:amplitude of accommodation,positive relative accommodation,exophoria at distance and near,and positive fusional vergence at near.CONCLUSION:The total CVS-Q score is a valid and reliable tool for predicting the presence of various nonstrabismic binocular vision anomalies and refractive errors in symptomatic computer users.展开更多
Conventional error cancellation approaches separate molecules into smaller fragments and sum the errors of all fragments to counteract the overall computational error of the parent molecules.However,these approaches m...Conventional error cancellation approaches separate molecules into smaller fragments and sum the errors of all fragments to counteract the overall computational error of the parent molecules.However,these approaches may be ineffective for systems with strong localized chemical effects,as fragmenting specific substructures into simpler chemical bonds can introduce additional errors instead of mitigating them.To address this issue,we propose the Substructure-Preserved Connection-Based Hierarchy(SCBH),a method that automatically identifies and freezes substructures with significant local chemical effects prior to molecular fragmentation.The SCBH is validated by the gas-phase enthalpy of formation calculation of CHNO molecules.Therein,based on the atomization scheme,the reference and test values are derived at the levels of Gaussian-4(G4)and M062X/6-31+G(2df,p),respectively.Compared to commonly used approaches,SCBH reduces the average computational error by half and requires only15%of the computational cost of G4 to achieve comparable accuracy.Since different types of local effect structures have differentiated influences on gas-phase enthalpy of formation,substituents with strong electronic effects should be retained preferentially.SCBH can be readily extended to diverse classes of organic compounds.Its workflow and source code allow flexible customization of molecular moieties,including azide,carboxyl,trinitromethyl,phenyl,and others.This strategy facilitates accurate,rapid,and automated computations and corrections,making it well-suited for high-throughput molecular screening and dataset construction for gas-phase enthalpy of formation.展开更多
Inborn errors of metabolism(IEM)are rare disorders,most are liver-based with liver transplantation(LT)emerging as an effective cure in the pediatric population.LT has been shown to offer a cure or deter disease progre...Inborn errors of metabolism(IEM)are rare disorders,most are liver-based with liver transplantation(LT)emerging as an effective cure in the pediatric population.LT has been shown to offer a cure or deter disease progression and provide symptomatic improvement in patients with IEM.Each metabolic disorder is unique,with the missing enzyme or transporter protein causing substrate deficiency or toxic byproduct production.Knowledge about the distribution of deficient enzymes,the percentage of enzymes replaced by LT,and the extent of extrahepatic involvement helps anticipate and manage complications in the perioperative period.Most patients have multisystem involvement and can be on complex dietary regimens.Metabolic decompensation can be triggered due to the stress response to surgery,fasting and other unanticipated complications perioperatively.Thus,a multidisciplinary team’s input including those from metabolic specialists is essential to develop disease and patient-specific strategies for the perioperative management of these patients during LT.In this review,we outline the classification of IEM,indications for LT along with potential benefits,basic metabolic defects and their implications,details of extrahepatic involvement and perioperative management strategies for LT in children with some of the commonly presenting IEM,to assist anesthesiologists handling this cohort of patients.展开更多
A digital phase-locked loop （DPLL） based on a new digital phase-frequency detector is presented. The self-calibration technique is employed to acquire wide lock range,low jitter, and fast acquisition. The DPLL works...A digital phase-locked loop （DPLL） based on a new digital phase-frequency detector is presented. The self-calibration technique is employed to acquire wide lock range,low jitter, and fast acquisition. The DPLL works from 60 to 600MHz at a supply voltage of 1.8V. It also features a fraetional-N synthesizer with digital 2nd-order sigma-delta noise shaping, which can achieve a short lock time,a high frequency resolution,and an improved phase-noise spectrum. The DPLL has been implemented in SMIC 0. 18μm 1.8V 1P6M CMOS technology. The peak-to-peak jitter is less than 0. 8% of the output clock period and the lock time is less than 150 times of the reference clock period after the pre-divider.展开更多
A capacitor self-calibration circuit used in a successive approximation analog-to-digital converter （SA-ADC） is presented. This capacitor self-calibration circuit can calibrate erroneous data and work with the ADC b...A capacitor self-calibration circuit used in a successive approximation analog-to-digital converter （SA-ADC） is presented. This capacitor self-calibration circuit can calibrate erroneous data and work with the ADC by adding an additional clock period. This circuit is used in a 10 bit 32 Msample/s time-interleaved SA- ADC. The chip is implemented with Chart 0. 25 μm 2. 5 V process and totally occupies an area of 1.4 mm× 1.3 mm. After calibration, the simulated signal-to-noise ratio （SNR） is 59. 586 1 dB and the spurious-free dynamic range （SFDR） is 70. 246 dB at 32 MHz. The measured signal-to-noise and distortion ratio （SINAD） is 44. 82 dB and the SFDR is 63. 760 4 dB when the ADC samples a 5.8 MHz sinusoid wave.展开更多
On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the m...On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the methods are not suited to directly integrate dynamic production data, such as, hydraulic head and solute concentration, into the study of conductivity distribution. These data, which record the flow and transport processes in the medium, are closely related to the spatial distribution of hydraulic conductivity. In this study, a three-dimensional gradient-based inverse method--the sequential self-calibration （SSC） method--is developed to calibrate a hydraulic conductivity field, initially generated by a geostatistical simulation method, conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one, measured by its mean square error （MSE）, is reduced through the SSC conditional study. In comparison with the unconditional results, the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve, and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further, the reduction of uncertainty is spatially dependent, which indicates that good locations, geological structure, and boundary conditions will affect the efficiency of the SSC study results.展开更多
To overcome the influence of on-orbit extreme temperature environment on the tool pose(position and orientation) accuracy of a space robot,a new self-calibration method based on a measurement camera(hand-eye vision) a...To overcome the influence of on-orbit extreme temperature environment on the tool pose(position and orientation) accuracy of a space robot,a new self-calibration method based on a measurement camera(hand-eye vision) attached to its end-effector was presented.Using the relative pose errors between the two adjacent calibration positions of the space robot,the cost function of the calibration was built,which was different from the conventional calibration method.The particle swarm optimization algorithm(PSO) was used to optimize the function to realize the geometrical parameter identification of the space robot.The above calibration method was carried out through self-calibration simulation of a six-DOF space robot whose end-effector was equipped with hand-eye vision.The results showed that after calibration there was a significant improvement of tool pose accuracy in a set of independent reference positions,which verified the feasibility of the method.At the same time,because it was unnecessary for this method to know the transformation matrix from the robot base to the calibration plate,it reduced the complexity of calibration model and shortened the error propagation chain,which benefited to improve the calibration accuracy.展开更多
In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innova...In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innovation points are reflected in the following aspects:①The proposed algorithm is not dependent on the Schur complement,and the calculation process is simple and clear;②The complexities of time and space tend to O(n)in the context of world point number is far greater than that of images and cameras,so the calculation magnitude and memory consumption can be reduced significantly;③The proposed algorithm can carry out self-calibration bundle adjustment in single-camera,multi-camera,and variable-camera modes;④Some measures are employed to improve the optimization effects.Experimental tests showed that the proposed algorithm has the ability to achieve state-of-the-art performance in accuracy and robustness,and it has a strong adaptability as well,because the optimized results are accurate and robust even if the initial values have large deviations from the truth.This study could provide theoretical guidance and technical support for the image-based positioning and 3D reconstruction in the fields of photogrammetry,computer vision and robotics.展开更多
A key problem that plagues camera self-calibration, namely that the classical self-calibration algorithms are very sensitive to the initial values of the camera intrinsic parameters, is analyzed and a practical soluti...A key problem that plagues camera self-calibration, namely that the classical self-calibration algorithms are very sensitive to the initial values of the camera intrinsic parameters, is analyzed and a practical solution is provided. The effect of the camera intrinsic parameters, mainly the principal point and the skew factor is first discussed. Then a practical method via a controlled motion of the camera is introduced so as to obtain an accurate estimation of these parameters. Feasibility of this approach is illustrated by carrying out comprehensive experiments using synthetic data as well as real image sequences. Unreasonable initial values can often make self-calibration impossible, yet a precise initialization guarantees a better and successful reconstruction. Trying to obtain a more reasonable initialization is worthwhile the effort in camera self-calibration.展开更多
An improved self-calibrating algorithm for visual servo based on adaptive genetic algorithm is proposed in this paper. Our approach introduces an extension of Mendonca-Cipolla and G. Chesi＇s self-calibration for the ...An improved self-calibrating algorithm for visual servo based on adaptive genetic algorithm is proposed in this paper. Our approach introduces an extension of Mendonca-Cipolla and G. Chesi＇s self-calibration for the positionbased visual servo technique which exploits the singular value property of the essential matrix. Specifically, a suitable dynamic online cost function is generated according to the property of the three singular values. The visual servo process is carried out simultaneous to the dynamic self-calibration, and then the cost function is minimized using the adaptive genetic algorithm instead of the gradient descent method in G. Chesi＇s approach. Moreover, this method overcomes the limitation that the initial parameters must be selected close to the true value, which is not constant in many cases. It is not necessary to know exactly the camera intrinsic parameters when using our approach, instead, coarse coding bounds of the five parameters are enough for the algorithm, which can be done once and for all off-line. Besides, this algorithm does not require knowledge of the 3D model of the object. Simulation experiments are carried out and the results demonstrate that the proposed approach provides a fast convergence speed and robustness against unpredictable perturbations of camera parameters, and it is an effective and efficient visual servo algorithm.展开更多
An error correction technique to achieve a 14-bit successive approximation register analog-to-digital converter(SAR ADC) is proposed. A tunable split capacitor is designed to eliminate the mismatches caused by parasit...An error correction technique to achieve a 14-bit successive approximation register analog-to-digital converter(SAR ADC) is proposed. A tunable split capacitor is designed to eliminate the mismatches caused by parasitic capacitors. The linearity error of capacitor array caused by process mismatch is calibrated by a novel calibration capacitor array that can improve the sampling rate. The dual-comparator topology ensures both the speed and precision of the ADC. The simulation results show that the SAR ADC after calibration achieves 83.07 dB SNDR and 13.5 bit ENOB at 500 kilosamples/s.展开更多
In the field of converting simulation surveying and traditional close range photogrammetry, it has been developed so far to survey objects by commercial digital camera and this technique is applied widely in every par...In the field of converting simulation surveying and traditional close range photogrammetry, it has been developed so far to survey objects by commercial digital camera and this technique is applied widely in every part of production. In order to get three-dimensional information of objects, commercial digital camera must be examined. For a long time, digital camera has been examined by DLT. Then there must be a high-precision control field. For realizing surveying without control points, a method for self-calibration is proposed.展开更多
Aiming at piezoresistive pressure sensors, this paper studies simulation of standard pressure by using benchmark current source and self-calibration of the sampling data characteristics. A data fusion algorithm for sa...Aiming at piezoresistive pressure sensors, this paper studies simulation of standard pressure by using benchmark current source and self-calibration of the sampling data characteristics. A data fusion algorithm for sample set is presented which transforms a surface problem into a curve fitting and interpolation problem. The simulation result shows that benchmark current source simulating pressure is successful and data fusion algorithm is effective. The maximum measurement error is only 0.098 kPa and maximum relative error is 0.92% at 0-45 kPa and -10-45~C.展开更多
Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimila...Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.展开更多
Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address th...Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.展开更多
基金supported by the National Natural Science Foundation of China(62301598).
文摘To tackle the challenges of intractable parameter tun-ing,significant computational expenditure and imprecise model-driven sparse-based direction of arrival(DOA)estimation with array error(AE),this paper proposes a deep unfolded amplitude-phase error self-calibration network.Firstly,a sparse-based DOA model with an array convex error restriction is established,which gets resolved via an alternating iterative minimization(AIM)algo-rithm.The algorithm is then unrolled to a deep network known as AE-AIM Network(AE-AIM-Net),where all parameters are opti-mized through multi-task learning using the constructed com-plete dataset.The results of the simulation and theoretical analy-sis suggest that the proposed unfolded network achieves lower computational costs compared to typical sparse recovery meth-ods.Furthermore,it maintains excellent estimation performance even in the presence of array magnitude-phase errors.
文摘Microstructured roll workpieces have been widely used as functional components in the precision industries. Current researches on quality control have focused on surface profile measurement of microstructured roll workpieces, and types of measurement systems and measurement methods have been developed. However, low measurement efficiency and low measurement accuracy caused by setting errors are the common disadvantages for surface profile measurement of microstructured roll workpieces. In order to shorten the measurement time and enhance the measurement accuracy, a method for self-calibration and compensation of setting errors is proposed for surface profile measurement of microstructured roll workpieces. A measurement system is constructed for the measurement, in which a precision spindle is employed to rotate the roll workpiece and an air-bearing displacement sensor with a micro-stylus probe is employed to scan the microstructured surface of the roll workpiece. The resolution of the displacement sensor is 0.14 nm and that of the rotary encoder of the spindle was 0.15r~. Geometrical and mathematical models are established for analyzing the influences of the setting errors of the roll workpiece and the displacement sensor with respect to the axis of the spindle, including the eccentric error of the roll workpiece, the offset error of the sensor axis and the zero point error of the sensor output. Measurement experiments are carded out on a roll workpiece on which periodic microstructures are a period of 133 i^m along the circumferential direction. Experimental results demonstrate the feasibility of the self-compensation method. The proposed method can be used to detect and compensate the setting errors without using any additional accurate artifact.
基金National Natural Science Foundation of China (No. 50475038).
文摘Laser tracking system （LTS） is an advanced device for large size 3D coordinates measuring with the advantages of broad range, high speed and high accuracy. However, its measuring accuracy is highly dominated by the geometric errors of the tracking mirror mechanism. Proper calibration of LTS is essential prior to the use of it for metrology. A kinematics model that describes not only the motion but also the geometric variations of LTS is developed. Through error analysis of the proposed model, it is claimed that gimbals axis misalignments and tracking mirror center off-set are the key contributors to measuring errors of LTS. A self-calibration method is presented of calibrating LTS with planar constraints. Various calibration strategies utilizing single-plane and multiple-plane constraints are proposed for different situations. For each calibration strategy, issues about the error parameter estimation of LTS are exploded to find out in which conditions these parameters can be uniquely estimated. Moreover, these conditions reveal the applicability of the planar constraints to LTS self-calibration. Intensive studies have been made to check validity of the theoretical results. The results show that the measuring accuracy of LTS has increased by 5 times since this technique for calibration is used.
基金supported by the National Natural Science Foundation of China(Nos.32260247 and 22064010)the Natural Science Foundation of Jiangxi Province(Nos.20232BAB215071 and 20224BAB213009).
文摘Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibration ratiometric fluorescent sensing platform has been designed for sensitive visual detection of levofloxacin(LEV)based on fluorescent europium metal-organic framework(Eu-MOF)probe.Specifically,the Eu-MOF was facilely synthesized via directly mixing Eu^(3+)with 1,10-phenanthroline-2,9-dicarboxylic acid(PDA)ligand at room temperature,which exhibited well-stable red fluorescence at 612 nm.Upon the addition of target LEV,the significant fluorescence quenching from Eu^(3+)was observed owing to the inner filter effect between the Eu-MOF and LEV.While the intrinsic fluorescence for LEV at 462nm was gradually enhanced,thereby realizing the self-calibration ratiometric fluorescence responses to LEV.Through this strategy,LEV can be detected down to 27 nmol/L.Furthermore,a test paper-based Eu-MOF integrated with the smartphone assisted RGB color analysis was exploited for the quantitative monitoring of LEV through the multi-color changes from red to blue,thus achieved portable,convenient and visual detection of LEV in honey and milk samples.Therefore,the developed strategy could provide a useful tool for supporting the practical on-site test in food samples.
基金supported by the National Key R&D Program of China [grant number 2023YFC3008004]。
文摘This study presents a comprehensive evaluation of tropical cyclone(TC)forecast performance in the western North Pacific from 2013 to 2022,based on operational forecasts issued by the China Meteorological Administration.The analysis reveals systematic improvements in both track and intensity forecasts over the decade,with distinct error characteristics observed across various forecast parameters.Track forecast errors have steadily decreased,particularly for longer lead times,while error magnitudes have increased with longer forecast lead times.Intensity forecasts show similar progressive enhancements,with maximum sustained wind speed errors decreasing by 0.26 m/s per year for 120 h forecasts.The study also identifies several key patterns in forecast performance:typhoon-grade or stronger TCs exhibit smaller track errors than week or weaker systems;intensity forecasts systematically overestimate weaker TCs while underestimating stronger systems;and spatial error distributions show greater track inaccuracies near landmasses and regional intensity biases.These findings highlight both the significant advances in TC forecasting capability achieved through improved modeling and observational systems,and the remaining challenges in predicting TC changes and landfall behavior,providing valuable benchmarks for future forecast system development.
基金Supported by Ongoing Research Funding Program(ORFFT-2025-054-1),King Saud University,Riyadh,Saudi Arabia.
文摘AIM:To evaluate the efficacy of the total computer vision syndrome questionnaire(CVS-Q)score as a predictive tool for identifying individuals with symptomatic binocular vision anomalies and refractive errors.METHODS:A total of 141 healthy computer users underwent comprehensive clinical visual function assessments,including evaluations of refractive errors,accommodation(amplitude of accommodation,positive relative accommodation,negative relative accommodation,accommodative accuracy,and accommodative facility),and vergence(phoria,positive and negative fusional vergence,near point of convergence,and vergence facility).Total CVS-Q scores were recorded to explore potential associations between symptom scores and the aforementioned clinical visual function parameters.RESULTS:The cohort included 54 males(38.3%)with a mean age of 23.9±0.58y and 87 age-matched females(61.7%)with a mean age of 23.9±0.53y.The multiple regression model was statistically significant[R²=0.60,F=13.28,degrees of freedom(DF=17122,P<0.001].This indicates that 60%of the variance in total CVS-Q scores(reflecting reported symptoms)could be explained by four clinical measurements:amplitude of accommodation,positive relative accommodation,exophoria at distance and near,and positive fusional vergence at near.CONCLUSION:The total CVS-Q score is a valid and reliable tool for predicting the presence of various nonstrabismic binocular vision anomalies and refractive errors in symptomatic computer users.
基金the support of the National Natural Science Foundation of China(22575230)。
文摘Conventional error cancellation approaches separate molecules into smaller fragments and sum the errors of all fragments to counteract the overall computational error of the parent molecules.However,these approaches may be ineffective for systems with strong localized chemical effects,as fragmenting specific substructures into simpler chemical bonds can introduce additional errors instead of mitigating them.To address this issue,we propose the Substructure-Preserved Connection-Based Hierarchy(SCBH),a method that automatically identifies and freezes substructures with significant local chemical effects prior to molecular fragmentation.The SCBH is validated by the gas-phase enthalpy of formation calculation of CHNO molecules.Therein,based on the atomization scheme,the reference and test values are derived at the levels of Gaussian-4(G4)and M062X/6-31+G(2df,p),respectively.Compared to commonly used approaches,SCBH reduces the average computational error by half and requires only15%of the computational cost of G4 to achieve comparable accuracy.Since different types of local effect structures have differentiated influences on gas-phase enthalpy of formation,substituents with strong electronic effects should be retained preferentially.SCBH can be readily extended to diverse classes of organic compounds.Its workflow and source code allow flexible customization of molecular moieties,including azide,carboxyl,trinitromethyl,phenyl,and others.This strategy facilitates accurate,rapid,and automated computations and corrections,making it well-suited for high-throughput molecular screening and dataset construction for gas-phase enthalpy of formation.
文摘Inborn errors of metabolism(IEM)are rare disorders,most are liver-based with liver transplantation(LT)emerging as an effective cure in the pediatric population.LT has been shown to offer a cure or deter disease progression and provide symptomatic improvement in patients with IEM.Each metabolic disorder is unique,with the missing enzyme or transporter protein causing substrate deficiency or toxic byproduct production.Knowledge about the distribution of deficient enzymes,the percentage of enzymes replaced by LT,and the extent of extrahepatic involvement helps anticipate and manage complications in the perioperative period.Most patients have multisystem involvement and can be on complex dietary regimens.Metabolic decompensation can be triggered due to the stress response to surgery,fasting and other unanticipated complications perioperatively.Thus,a multidisciplinary team’s input including those from metabolic specialists is essential to develop disease and patient-specific strategies for the perioperative management of these patients during LT.In this review,we outline the classification of IEM,indications for LT along with potential benefits,basic metabolic defects and their implications,details of extrahepatic involvement and perioperative management strategies for LT in children with some of the commonly presenting IEM,to assist anesthesiologists handling this cohort of patients.
文摘A digital phase-locked loop （DPLL） based on a new digital phase-frequency detector is presented. The self-calibration technique is employed to acquire wide lock range,low jitter, and fast acquisition. The DPLL works from 60 to 600MHz at a supply voltage of 1.8V. It also features a fraetional-N synthesizer with digital 2nd-order sigma-delta noise shaping, which can achieve a short lock time,a high frequency resolution,and an improved phase-noise spectrum. The DPLL has been implemented in SMIC 0. 18μm 1.8V 1P6M CMOS technology. The peak-to-peak jitter is less than 0. 8% of the output clock period and the lock time is less than 150 times of the reference clock period after the pre-divider.
文摘A capacitor self-calibration circuit used in a successive approximation analog-to-digital converter （SA-ADC） is presented. This capacitor self-calibration circuit can calibrate erroneous data and work with the ADC by adding an additional clock period. This circuit is used in a 10 bit 32 Msample/s time-interleaved SA- ADC. The chip is implemented with Chart 0. 25 μm 2. 5 V process and totally occupies an area of 1.4 mm× 1.3 mm. After calibration, the simulated signal-to-noise ratio （SNR） is 59. 586 1 dB and the spurious-free dynamic range （SFDR） is 70. 246 dB at 32 MHz. The measured signal-to-noise and distortion ratio （SINAD） is 44. 82 dB and the SFDR is 63. 760 4 dB when the ADC samples a 5.8 MHz sinusoid wave.
基金This study is partially supported by the Program of Outstanding Overseas Youth Chinese Scholar,the National Natural Science Foundation of China (No. 40528003)partially supported by USA National Science Foundation.
文摘On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the methods are not suited to directly integrate dynamic production data, such as, hydraulic head and solute concentration, into the study of conductivity distribution. These data, which record the flow and transport processes in the medium, are closely related to the spatial distribution of hydraulic conductivity. In this study, a three-dimensional gradient-based inverse method--the sequential self-calibration （SSC） method--is developed to calibrate a hydraulic conductivity field, initially generated by a geostatistical simulation method, conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one, measured by its mean square error （MSE）, is reduced through the SSC conditional study. In comparison with the unconditional results, the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve, and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further, the reduction of uncertainty is spatially dependent, which indicates that good locations, geological structure, and boundary conditions will affect the efficiency of the SSC study results.
基金Projects(60775049,60805033) supported by the National Natural Science Foundation of ChinaProject(2007AA704317) supported by the National High Technology Research and Development Program of China
文摘To overcome the influence of on-orbit extreme temperature environment on the tool pose(position and orientation) accuracy of a space robot,a new self-calibration method based on a measurement camera(hand-eye vision) attached to its end-effector was presented.Using the relative pose errors between the two adjacent calibration positions of the space robot,the cost function of the calibration was built,which was different from the conventional calibration method.The particle swarm optimization algorithm(PSO) was used to optimize the function to realize the geometrical parameter identification of the space robot.The above calibration method was carried out through self-calibration simulation of a six-DOF space robot whose end-effector was equipped with hand-eye vision.The results showed that after calibration there was a significant improvement of tool pose accuracy in a set of independent reference positions,which verified the feasibility of the method.At the same time,because it was unnecessary for this method to know the transformation matrix from the robot base to the calibration plate,it reduced the complexity of calibration model and shortened the error propagation chain,which benefited to improve the calibration accuracy.
基金National Natural Science Foundation of China(Nos.41571410,41977067,42171422)。
文摘In this study,the problem of bundle adjustment was revisited,and a novel algorithm based on block matrix Cholesky decomposition was proposed to solve the thorny problem of self-calibration bundle adjustment.The innovation points are reflected in the following aspects:①The proposed algorithm is not dependent on the Schur complement,and the calculation process is simple and clear;②The complexities of time and space tend to O(n)in the context of world point number is far greater than that of images and cameras,so the calculation magnitude and memory consumption can be reduced significantly;③The proposed algorithm can carry out self-calibration bundle adjustment in single-camera,multi-camera,and variable-camera modes;④Some measures are employed to improve the optimization effects.Experimental tests showed that the proposed algorithm has the ability to achieve state-of-the-art performance in accuracy and robustness,and it has a strong adaptability as well,because the optimized results are accurate and robust even if the initial values have large deviations from the truth.This study could provide theoretical guidance and technical support for the image-based positioning and 3D reconstruction in the fields of photogrammetry,computer vision and robotics.
文摘A key problem that plagues camera self-calibration, namely that the classical self-calibration algorithms are very sensitive to the initial values of the camera intrinsic parameters, is analyzed and a practical solution is provided. The effect of the camera intrinsic parameters, mainly the principal point and the skew factor is first discussed. Then a practical method via a controlled motion of the camera is introduced so as to obtain an accurate estimation of these parameters. Feasibility of this approach is illustrated by carrying out comprehensive experiments using synthetic data as well as real image sequences. Unreasonable initial values can often make self-calibration impossible, yet a precise initialization guarantees a better and successful reconstruction. Trying to obtain a more reasonable initialization is worthwhile the effort in camera self-calibration.
基金the National Natural Science Foundation of China (No.60675048)Science and Technology Research Project of the Ministry of Education (No.204181).
文摘An improved self-calibrating algorithm for visual servo based on adaptive genetic algorithm is proposed in this paper. Our approach introduces an extension of Mendonca-Cipolla and G. Chesi＇s self-calibration for the positionbased visual servo technique which exploits the singular value property of the essential matrix. Specifically, a suitable dynamic online cost function is generated according to the property of the three singular values. The visual servo process is carried out simultaneous to the dynamic self-calibration, and then the cost function is minimized using the adaptive genetic algorithm instead of the gradient descent method in G. Chesi＇s approach. Moreover, this method overcomes the limitation that the initial parameters must be selected close to the true value, which is not constant in many cases. It is not necessary to know exactly the camera intrinsic parameters when using our approach, instead, coarse coding bounds of the five parameters are enough for the algorithm, which can be done once and for all off-line. Besides, this algorithm does not require knowledge of the 3D model of the object. Simulation experiments are carried out and the results demonstrate that the proposed approach provides a fast convergence speed and robustness against unpredictable perturbations of camera parameters, and it is an effective and efficient visual servo algorithm.
基金Supported by National Science and Technology Major Project of China(No.2012ZX03004008)
文摘An error correction technique to achieve a 14-bit successive approximation register analog-to-digital converter(SAR ADC) is proposed. A tunable split capacitor is designed to eliminate the mismatches caused by parasitic capacitors. The linearity error of capacitor array caused by process mismatch is calibrated by a novel calibration capacitor array that can improve the sampling rate. The dual-comparator topology ensures both the speed and precision of the ADC. The simulation results show that the SAR ADC after calibration achieves 83.07 dB SNDR and 13.5 bit ENOB at 500 kilosamples/s.
文摘In the field of converting simulation surveying and traditional close range photogrammetry, it has been developed so far to survey objects by commercial digital camera and this technique is applied widely in every part of production. In order to get three-dimensional information of objects, commercial digital camera must be examined. For a long time, digital camera has been examined by DLT. Then there must be a high-precision control field. For realizing surveying without control points, a method for self-calibration is proposed.
基金Project supported by the National Natural Science Foundation of China （Grant No.40265001）, and the Science Foundation of Yunnan Province （Grant No.2002C0038M）
文摘Aiming at piezoresistive pressure sensors, this paper studies simulation of standard pressure by using benchmark current source and self-calibration of the sampling data characteristics. A data fusion algorithm for sample set is presented which transforms a surface problem into a curve fitting and interpolation problem. The simulation result shows that benchmark current source simulating pressure is successful and data fusion algorithm is effective. The maximum measurement error is only 0.098 kPa and maximum relative error is 0.92% at 0-45 kPa and -10-45~C.
基金sponsored by the National Natural Science Foundation of China[grant number U2442218]。
文摘Land surface temperature(LST)is the key variable in land-atmosphere interaction,having an important impact on weather and climate forecasting.However,achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging.This is because there is limited knowledge about the cross-component background error covariance(BEC)between LST and atmospheric state variables.This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables,and whether this relationship varies spatially and temporally.To this end,the BEC coupled with atmospheric variables and LST was constructed(LST-BEC),and its characteristics were analyzed based on the 2023 mei-yu season.The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height,and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature.The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background,and also have obvious diurnal variations.These results provide valuable information for strongly coupled land-atmosphere assimilation.
基金supported by the Key R&D Program of Zhejiang Province(Nos.2023C01166 and 2024SJCZX0046)the Zhejiang Provincial Natural Science Foundation of China(Nos.LDT23E05013E05 and LD24E050009)the Natural Science Foundation of Ningbo(No.2021J150),China.
文摘Accuracy allocation is crucial in the accuracy design of machining tools.Current accuracy allocation methods primarily focus on positional deviation,with little consideration for tool direction deviation.To address this issue,we propose a geometric error cost sensitivity-based accuracy allocation method for five-axis machine tools.A geometric error model consisting of 4l error components is constructed based on homogeneous transformation matrices.Volumetric points with positional and tool direction deviations are randomly sampled to evaluate the accuracy of the machine tool.The sensitivity of each error component at these sampling points is analyzed using the Sobol method.To balance the needs of geometric precision and manufacturing cost,a geometric error cost sensitivity function is developed to estimate the required cost.By allocating error components affecting tool direction deviation first and the remaining components second,this allocation scheme ensures that both deviations meet the requirements.We also perform numerical simulation of a BC-type(B-axis and C-axis type)five-axis machine tool to validate the method.The results show that the new allocation scheme reduces the total geometric error cost by 27.8%compared to a uniform allocation scheme,and yields the same positional and tool direction machining accuracies.
