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
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
Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environment...Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.展开更多
Though atomic decomposition is a very useful tool for studying the boundedness on Hardy spaces for some sublinear operators,untill now,the boundedness of operators on weighted Hardy spaces in a multi-parameter setting...Though atomic decomposition is a very useful tool for studying the boundedness on Hardy spaces for some sublinear operators,untill now,the boundedness of operators on weighted Hardy spaces in a multi-parameter setting has been established only by almost orthogonality estimates.In this paper,we mainly establish the boundedness on weighted multi-parameter local Hardy spaces via atomic decomposition.展开更多
In this paper,we focus on the problem of joint estimation of DOA,power and polarization angle from sparse reconstruction perspective with array gain-phase errors,where a partly calibrated cocentered orthogonal loop an...In this paper,we focus on the problem of joint estimation of DOA,power and polarization angle from sparse reconstruction perspective with array gain-phase errors,where a partly calibrated cocentered orthogonal loop and dipole(COLD)array is utilized.In detailed implementations,we first combine the output of loop and dipole in second-order statistics domain to receive the source signals completely,and then we use continuous multiplication operator to achieve gain-phase errors calibration.After compensating the gain-phase errors,we construct a log-penalty-based optimization problem to approximate`0 norm and further exploit difference of convex(DC)functions decomposition to achieve DOA.With the aid of the estimated DOAs,the power and polarization angle estimation are obtained by the least squares(LS)method.By conducting numerical simulations,we show the effectiveness and superiorities of the proposed method.展开更多
This editorial is a commentary on the article by Ni et al,which was published in the World Journal of Clinical Cases.The article discusses the diagnostic and therapeutic challenges of melioidosis caused by Burkholderi...This editorial is a commentary on the article by Ni et al,which was published in the World Journal of Clinical Cases.The article discusses the diagnostic and therapeutic challenges of melioidosis caused by Burkholderia pseudomallei.The case study highlights a rare instance of multisystemic melioidosis in a female patient who did not have a travel history,emphasizing the significance of recognizing this condition in non-endemic regions.Diagnostic complexities and therapeutic strategies are addressed,emphasizing the need for heightened clinical suspicion,comprehensive evaluation,and multidisciplinary collaboration.The editorial delves into the clinical presentation,diagnostic dilemmas,therapeutic approaches,and their implications for patient care in managing multi-systemic melioidosis.展开更多
The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of t...The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of the data quality of Chinese GNSS equipment.In this study,data from four representative GNSS sites in different regions of China were analyzed using the G-Nut/Anubis software package.Four main indicators(data integrity rate,data validity ratio,multi-path error,and cycle slip ratio)used to systematically analyze data quality,while evaluating the seismic monitoring capabilities of the network based on earthquake magnitudes estimated from high-frequency GNSS data are evaluated by estimating magnitude based on highfrequency GNSS data.The results indicate that the quality of the data produced by the three types of Chinese receivers used in the network meets the needs of earthquake monitoring and the new seismic industry standards,which provide a reference for the selection of equipment for future new projects.After the B&R GNSS network was established,the seismic monitoring capability for earthquakes with magnitudes greater than M_(W)6.5 in most parts of the Sichuan-Yunnan region improved by approximately 20%.In key areas such as the Sichuan-Yunnan Rhomboid Block,the monitoring capability increased by more than 25%,which has greatly improved the effectiveness of regional comprehensive earthquake management.展开更多
The structural and operational optimization of gas-liquid stirred bioreactors presents both complexity and critical importance for enhancing mass transfer performance. This study proposes a machine learning (ML)-drive...The structural and operational optimization of gas-liquid stirred bioreactors presents both complexity and critical importance for enhancing mass transfer performance. This study proposes a machine learning (ML)-driven approach to identify key features and predict the volumetric mass transfer coefficient (kLa). Four ML models were adopted and compared for kLa prediction in Newtonian and non-Newtonian fluids by evaluative indices, with CatBoost and XGBoost emerging as the optimal models, respectively. Specifically, it is demonstrated that Catboost has higher prediction accuracy (AARD = 18.84%) than empirical equations by effectively incorporating multidimensional features (structural, impeller, and operational), while simultaneously extending applicability to diverse Newtonian fluids. For non-Newtonian fluids, XGBoost outperforms empirical equations by effectively incorporating fluid rheological parameters (consistency coefficient, power-law index), thereby better capturing shear-thinning behavior. Feature importance analysis further identified rotational speed (for Newtonian fluids) and liquid height (for non-Newtonian fluids) as the key features, while 2D partial dependence analysis establishes quantitative optimization ranges. This ML approach provides an efficient predictive tool for gas-liquid stirred bioreactor design and optimization.展开更多
An online subsection cooling method for hot rolling silicon steel was designed to achieve local adjustment of transverse roll gap.Particularly,it was able to meet the requirements of edge drop of the strip by using th...An online subsection cooling method for hot rolling silicon steel was designed to achieve local adjustment of transverse roll gap.Particularly,it was able to meet the requirements of edge drop of the strip by using the features of online thermal crown.First,after the new subsection spray beam was installed at the exit of mill,the special local cooling rules were analyzed for altering the thermal crown of roll according to rolling process parameters.Meanwhile,the dynamic impact of subsection cooling on the local thermal crown could just be obtained according to the measured data.Obviously,the heat transfer coefficient was determined by different subsection cooling curves under varied rolling conditions.Secondly,the rolling rhythm and variable conditions were important dynamic factors of transient roll temperature in practical rolling process.Therefore,real-time calculation and presetting of the thermal crown were carried out to maximize special requirements of load roll gap on local strip crown.By this new method,the transient temperature and the thermal crown of roll could be quantitatively controlled online.And the practical results showed that the predicted temperature was able to match the measured value by more than 95%.Meanwhile,the adjustable range of thermal crown increased by more than 2.5 times.Finally,the qualification rate of strip edge crown has increased from the original 30%to over 70%.展开更多
Nonalcoholic fatty liver disease(NAFLD) is the most common cause of chronic liver disease. NAFLD includes a wide spectrum of liver conditions ranging from simple steatosis to nonalcoholic steatohepatitis and advanced ...Nonalcoholic fatty liver disease(NAFLD) is the most common cause of chronic liver disease. NAFLD includes a wide spectrum of liver conditions ranging from simple steatosis to nonalcoholic steatohepatitis and advanced hepatic fibrosis. NAFLD has been recognized as a hepatic manifestation of metabolic syndrome linked with insulin resistance. NAFLD should be considered not only a liver specific disease but also an early mediator of systemic diseases. Therefore, NAFLD is usually associated with cardiovascular disease, chronic kidney disease, type 2 diabetes, obesity, and dyslipidemia. NAFLD is highly prevalent in the general population and is associated with increased cardiovascular morbidity and mortality. The underlying mechanisms and pathogenesis of NAFLD with regard to other medical disorders are not yet fully understood. This review focuses on pathogenesis of NAFLD and its relation with other systemic diseases.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
To obtain the interaction characteristics between Internal solitary waves(ISWs)and submerged bodies,a three-dimensional numerical model for simulating ISWs was established in the present study based on the RANS equati...To obtain the interaction characteristics between Internal solitary waves(ISWs)and submerged bodies,a three-dimensional numerical model for simulating ISWs was established in the present study based on the RANS equation.The velocity entrance method was adopted to generate the ISWs.First,the reliability of this numerical model was validated by comparing it with theoretical and literature results.Then,the influence of environmental and navigation parameters on interactions between ISWs and a fixed SUBOFF-submerged body was studied.According to research,the hydrodynamic performance of the submerged body has been significantly impacted by the ISWs when the body is nearing the central region of the wave.Besides,the pitching moment(y')will predominate when the body encounters the ISWs at a certain angle between 0°and 180°,and the lateral force is larger than the horizontal force.Additionally,the magnitude of the force acting on the body is mostly affected by the wave amplitude.The variation of the vertical force is the main way that ISWs affect the hydrodynamic performance of the bodies.The investigations and findings discussed above can serve as a guide to forecast how ISWs will interact with submerged bodies.展开更多
A new membrane type Al_2O_3 micromachining material is used.We develop an environmental multi-parameter detection micro-system,which implements the detection to temperature,humidity,wind speed,and CO.The test results ...A new membrane type Al_2O_3 micromachining material is used.We develop an environmental multi-parameter detection micro-system,which implements the detection to temperature,humidity,wind speed,and CO.The test results illustrate that the heat-release unit in micro-system intercross greatly affects other sensing units on the temperature.We study the method of etching process,which formed cavity to reduce the heat exchange efficiency and decrease temperature intercross effect.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
This paper presents a design of new type of multi-parameter wearable medical devices signal processing platform. The signal processing algorithm has a QRS-wave detection algorithm based on LADT, wavelet transformation...This paper presents a design of new type of multi-parameter wearable medical devices signal processing platform. The signal processing algorithm has a QRS-wave detection algorithm based on LADT, wavelet transformation and threshold detection with TMS320VC5509 DSP system. The DSP can greatly increase the speed of QRS-wave detection, and the results can be practical used for multi-parameter wearable device detection of abnormal ECG.展开更多
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 project of 2017 Directional Task of Earthquake Tracking of CEA(Grant No.2017010406)the project of Youth Foundation of CENC(Grant No.QNJJ201603)
文摘Temporal and spatial anomalies associated with the Yushu earthquake, including the Outgoing Longwave Radiation( OLR), the Land Surface Temperature( LST) and surface temperature from the National Center for Environmental Prediction( NCEP) are studied using thermal infrared remote sensing data in this paper. All results confirmed the previous observations of thermal anomalies in the seismic region prior to this earthquake.Among the multi-parameter anomalies, the underground water temperature anomaly appeared first and lasted for the longest time; OLR anomaly,an infrared parameter which indicates the radiation characteristics of the land surface medium,was the first to be detected; LST anomalies appeared later than OLR. NCEP temperature indicates the average atmosphere temperature with a certain vertical thickness; therefore,it was the last detected anomaly. The anomalies of OLR and LST lasted for a similar time length and were all located in the south or southwest of the epicenter.
文摘Though atomic decomposition is a very useful tool for studying the boundedness on Hardy spaces for some sublinear operators,untill now,the boundedness of operators on weighted Hardy spaces in a multi-parameter setting has been established only by almost orthogonality estimates.In this paper,we mainly establish the boundedness on weighted multi-parameter local Hardy spaces via atomic decomposition.
基金the National Natural Science Foundation of China under Grant 61171137.
文摘In this paper,we focus on the problem of joint estimation of DOA,power and polarization angle from sparse reconstruction perspective with array gain-phase errors,where a partly calibrated cocentered orthogonal loop and dipole(COLD)array is utilized.In detailed implementations,we first combine the output of loop and dipole in second-order statistics domain to receive the source signals completely,and then we use continuous multiplication operator to achieve gain-phase errors calibration.After compensating the gain-phase errors,we construct a log-penalty-based optimization problem to approximate`0 norm and further exploit difference of convex(DC)functions decomposition to achieve DOA.With the aid of the estimated DOAs,the power and polarization angle estimation are obtained by the least squares(LS)method.By conducting numerical simulations,we show the effectiveness and superiorities of the proposed method.
文摘This editorial is a commentary on the article by Ni et al,which was published in the World Journal of Clinical Cases.The article discusses the diagnostic and therapeutic challenges of melioidosis caused by Burkholderia pseudomallei.The case study highlights a rare instance of multisystemic melioidosis in a female patient who did not have a travel history,emphasizing the significance of recognizing this condition in non-endemic regions.Diagnostic complexities and therapeutic strategies are addressed,emphasizing the need for heightened clinical suspicion,comprehensive evaluation,and multidisciplinary collaboration.The editorial delves into the clinical presentation,diagnostic dilemmas,therapeutic approaches,and their implications for patient care in managing multi-systemic melioidosis.
基金supported by grants from the National Natural Science Foundation of China(No.42004010)the B&R Seismic Monitoring Network Project of the China Earthquake Networks Center(No.5007).
文摘The Belt and Road global navigation satellite system(B&R GNSS)network is the first large-scale deployment of Chinese GNSS equipment in a seismic system.Prior to this,there have been few systematic assessments of the data quality of Chinese GNSS equipment.In this study,data from four representative GNSS sites in different regions of China were analyzed using the G-Nut/Anubis software package.Four main indicators(data integrity rate,data validity ratio,multi-path error,and cycle slip ratio)used to systematically analyze data quality,while evaluating the seismic monitoring capabilities of the network based on earthquake magnitudes estimated from high-frequency GNSS data are evaluated by estimating magnitude based on highfrequency GNSS data.The results indicate that the quality of the data produced by the three types of Chinese receivers used in the network meets the needs of earthquake monitoring and the new seismic industry standards,which provide a reference for the selection of equipment for future new projects.After the B&R GNSS network was established,the seismic monitoring capability for earthquakes with magnitudes greater than M_(W)6.5 in most parts of the Sichuan-Yunnan region improved by approximately 20%.In key areas such as the Sichuan-Yunnan Rhomboid Block,the monitoring capability increased by more than 25%,which has greatly improved the effectiveness of regional comprehensive earthquake management.
基金supported by the National Natural Science Foundation of China(22494713,22178160,22327809 and 22208141)Natural Science Foundation of Jiangsu Province,China(BK20220349).
文摘The structural and operational optimization of gas-liquid stirred bioreactors presents both complexity and critical importance for enhancing mass transfer performance. This study proposes a machine learning (ML)-driven approach to identify key features and predict the volumetric mass transfer coefficient (kLa). Four ML models were adopted and compared for kLa prediction in Newtonian and non-Newtonian fluids by evaluative indices, with CatBoost and XGBoost emerging as the optimal models, respectively. Specifically, it is demonstrated that Catboost has higher prediction accuracy (AARD = 18.84%) than empirical equations by effectively incorporating multidimensional features (structural, impeller, and operational), while simultaneously extending applicability to diverse Newtonian fluids. For non-Newtonian fluids, XGBoost outperforms empirical equations by effectively incorporating fluid rheological parameters (consistency coefficient, power-law index), thereby better capturing shear-thinning behavior. Feature importance analysis further identified rotational speed (for Newtonian fluids) and liquid height (for non-Newtonian fluids) as the key features, while 2D partial dependence analysis establishes quantitative optimization ranges. This ML approach provides an efficient predictive tool for gas-liquid stirred bioreactor design and optimization.
基金supported by Returned Overseas Scholar Foundation of Hebei Province(Grant No.C20210321)Natural Science Foundation of Hebei Province(Grant No.E2021203106)S&T Program of Hebei(Grant No.236Z1019G)。
文摘An online subsection cooling method for hot rolling silicon steel was designed to achieve local adjustment of transverse roll gap.Particularly,it was able to meet the requirements of edge drop of the strip by using the features of online thermal crown.First,after the new subsection spray beam was installed at the exit of mill,the special local cooling rules were analyzed for altering the thermal crown of roll according to rolling process parameters.Meanwhile,the dynamic impact of subsection cooling on the local thermal crown could just be obtained according to the measured data.Obviously,the heat transfer coefficient was determined by different subsection cooling curves under varied rolling conditions.Secondly,the rolling rhythm and variable conditions were important dynamic factors of transient roll temperature in practical rolling process.Therefore,real-time calculation and presetting of the thermal crown were carried out to maximize special requirements of load roll gap on local strip crown.By this new method,the transient temperature and the thermal crown of roll could be quantitatively controlled online.And the practical results showed that the predicted temperature was able to match the measured value by more than 95%.Meanwhile,the adjustable range of thermal crown increased by more than 2.5 times.Finally,the qualification rate of strip edge crown has increased from the original 30%to over 70%.
文摘Nonalcoholic fatty liver disease(NAFLD) is the most common cause of chronic liver disease. NAFLD includes a wide spectrum of liver conditions ranging from simple steatosis to nonalcoholic steatohepatitis and advanced hepatic fibrosis. NAFLD has been recognized as a hepatic manifestation of metabolic syndrome linked with insulin resistance. NAFLD should be considered not only a liver specific disease but also an early mediator of systemic diseases. Therefore, NAFLD is usually associated with cardiovascular disease, chronic kidney disease, type 2 diabetes, obesity, and dyslipidemia. NAFLD is highly prevalent in the general population and is associated with increased cardiovascular morbidity and mortality. The underlying mechanisms and pathogenesis of NAFLD with regard to other medical disorders are not yet fully understood. This review focuses on pathogenesis of NAFLD and its relation with other systemic diseases.
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financially supported by the Shandong Province Taishan Scholars Project (Grant No.tsqn201909172)Fundamental Research Funds for the Central Universities (Grant No.HIT.OCEF.2021037)+1 种基金the University Young Innovational Team Program,Shandong Province (Grant No.2019KJB004)the China Scholarship Council (Grant No.202106120123)。
文摘To obtain the interaction characteristics between Internal solitary waves(ISWs)and submerged bodies,a three-dimensional numerical model for simulating ISWs was established in the present study based on the RANS equation.The velocity entrance method was adopted to generate the ISWs.First,the reliability of this numerical model was validated by comparing it with theoretical and literature results.Then,the influence of environmental and navigation parameters on interactions between ISWs and a fixed SUBOFF-submerged body was studied.According to research,the hydrodynamic performance of the submerged body has been significantly impacted by the ISWs when the body is nearing the central region of the wave.Besides,the pitching moment(y')will predominate when the body encounters the ISWs at a certain angle between 0°and 180°,and the lateral force is larger than the horizontal force.Additionally,the magnitude of the force acting on the body is mostly affected by the wave amplitude.The variation of the vertical force is the main way that ISWs affect the hydrodynamic performance of the bodies.The investigations and findings discussed above can serve as a guide to forecast how ISWs will interact with submerged bodies.
文摘A new membrane type Al_2O_3 micromachining material is used.We develop an environmental multi-parameter detection micro-system,which implements the detection to temperature,humidity,wind speed,and CO.The test results illustrate that the heat-release unit in micro-system intercross greatly affects other sensing units on the temperature.We study the method of etching process,which formed cavity to reduce the heat exchange efficiency and decrease temperature intercross effect.
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.
文摘This paper presents a design of new type of multi-parameter wearable medical devices signal processing platform. The signal processing algorithm has a QRS-wave detection algorithm based on LADT, wavelet transformation and threshold detection with TMS320VC5509 DSP system. The DSP can greatly increase the speed of QRS-wave detection, and the results can be practical used for multi-parameter wearable device detection of abnormal ECG.
