A fluid-structure interaction approach is proposed in this paper based onNon-Ordinary State-Based Peridynamics(NOSB-PD)and Updated Lagrangian Particle Hydrodynamics(ULPH)to simulate the fluid-structure interaction pro...A fluid-structure interaction approach is proposed in this paper based onNon-Ordinary State-Based Peridynamics(NOSB-PD)and Updated Lagrangian Particle Hydrodynamics(ULPH)to simulate the fluid-structure interaction problem with large geometric deformation and material failure and solve the fluid-structure interaction problem of Newtonian fluid.In the coupled framework,the NOSB-PD theory describes the deformation and fracture of the solid material structure.ULPH is applied to describe the flow of Newtonian fluids due to its advantages in computational accuracy.The framework utilizes the advantages of NOSB-PD theory for solving discontinuous problems and ULPH theory for solving fluid problems,with good computational stability and robustness.A fluidstructure coupling algorithm using pressure as the transmission medium is established to deal with the fluidstructure interface.The dynamic model of solid structure and the PD-ULPH fluid-structure interaction model involving large deformation are verified by numerical simulations.The results agree with the analytical solution,the available experimental data,and other numerical results.Thus,the accuracy and effectiveness of the proposed method in solving the fluid-structure interaction problem are demonstrated.The fluid-structure interactionmodel based on ULPH and NOSB-PD established in this paper provides a new idea for the numerical solution of fluidstructure interaction and a promising approach for engineering design and experimental prediction.展开更多
Natural convection is a heat transfer mechanism driven by temperature or density differences,leading to fluid motion without external influence.It occurs in various natural and engineering phenomena,influencing heat t...Natural convection is a heat transfer mechanism driven by temperature or density differences,leading to fluid motion without external influence.It occurs in various natural and engineering phenomena,influencing heat transfer,climate,and fluid mixing in industrial processes.This work aims to use the Updated Lagrangian Particle Hydrodynamics(ULPH)theory to address natural convection problems.The Navier-Stokes equation is discretized using second-order nonlocal differential operators,allowing a direct solution of the Laplace operator for temperature in the energy equation.Various numerical simulations,including cases such as natural convection in square cavities and two concentric cylinders,were conducted to validate the reliability of the model.The results demonstrate that the proposed model exhibits excellent accuracy and performance,providing a promising and effective numerical approach for natural convection problems.展开更多
Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring ...Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring and health management.However,there still exist gaps in the seamless integration of DT and PHM,as well as in the development of DT multi-field coupling modeling and its dynamic update mechanism.When the product experiences long-period degradation under load spectrum,it is challenging to describe the dynamic evolution of the health status and degradation progression accurately.In addition,DT update algorithms are difficult to be integrated simultaneously by current methods.This paper proposes an innovative dual loop DT based PHM framework,in which the first loop establishes the basic dynamic DT with multi-filed coupling,and the second loop implements the PHM and the abnormal detection to provide the interaction between the dual loops through updating mechanism.The proposed method pays attention to the internal state changes with degradation and interactive mapping with dynamic parameter updating.Furthermore,the Independence Principle for the abnormal detection is proposed to refine the theory of DT.Events at the first loop focus on accurate modeling of multi-field coupling,while the events at the second loop focus on real-time occurrence of anomalies and the product degradation trend.The interaction and collaboration between different loop models are also discussed.Finally,the Permanent Magnet Synchronous Motor(PMSM)is used to verify the proposed method.The results show that the modeling method proposed can accurately track the lifecycle performance changes of the entity and carry out remaining life prediction and health management effectively.展开更多
Cancer is a major public health issue in most of countries, including China. Accurate and valid information on cancer incidence, mortality, survival and relevant factors is irreplaceable for cancer prevention and cont...Cancer is a major public health issue in most of countries, including China. Accurate and valid information on cancer incidence, mortality, survival and relevant factors is irreplaceable for cancer prevention and control. Since the national program of cancer registry was launched by the Ministry of Health of China in 2008, the National Central Cancer Registry （NCCR） has been releasing the cancer incidence and mortality based on the data collected from cancer registries supported by the program. The cancer statistics provide current data from registered areas and aims to accurately reflect the cancer burden and epidemic in China. In 2014, the NCCR collected data for calendar year 2011 from 234 registries. After comprehensive quality＇ evaluation, data from 177 registries have been selected as sources of the reports reflecting cancer incidence and mortaliD, in the registration areas in 2011. These reports are the updated cancer statistics so far, covering much more registries and a hig population.展开更多
BACKGROUND The Updated Sydney system for visual evaluation of gastric mucosal atrophy viaendoscopic observation is subject to sampling error and interobserver variability.The Kimura-Takemoto classification system was ...BACKGROUND The Updated Sydney system for visual evaluation of gastric mucosal atrophy viaendoscopic observation is subject to sampling error and interobserver variability.The Kimura-Takemoto classification system was developed to overcome theselimitations.AIMTo compare the morphological classification of atrophic gastritis between theKimura-Takemoto system and the Updated Sydney system.METHODSA total of 169 patients with atrophic gastritis were selected according to diagnosisby the visual endoscopic Kimura-Takemoto method. Following the UpdatedKimura-Takemoto classification system, one antrum biopsy and five gastriccorpus biopsies were taken according to the visual stages of the Kimura-Takemoto system. The Updated Kimura-Takemoto classification system was thenapplied to each and showed 165 to have histological mucosal atrophy;theremaining 4 patients had no histological evidence of atrophy in any biopsy. The Updated Kimura-Takemoto classification was verified as a referencemorphological method and applied for the diagnosis of atrophic gastritis. Addingone more biopsy from the antrum to the six biopsies according to the Updated Kimura-Takemoto classification, constitutes the updated combined Kimura-Takemoto classification and Sydney system.RESULTSThe sensitivity for degree of mucosal atrophy assessed by the Updated Sydneysystem was 25% for mild, 36% for moderate, and 42% for severe, when comparedwith the Updated Kimura-Takemoto classification of atrophic gastritis formorphological diagnosis. Four types of multifocal atrophic gastritis wereidentified: sequential uniform (type 1;in 28%), sequential non-uniform (type 2;in7%), diffuse uniform (type 3;in 23%), diffuse non-uniform (type 4;in 24%), and"alternating atrophic – non-atrophic" (type 5;in 18%). The pattern of the spread ofatrophy, sequentially from the antrum to the cardiac segment of the stomach,which was described by the Updated Kimura-Takemoto system, washistologically confirmed in 82% of cases evaluated.CONCLUSIONThe Updated Sydney system is significantly inferior to the Updated Kimura-Takemoto classification for morphological verification of atrophic gastritis.展开更多
A tensor-based updated Lagrangian （UL） formulation for the geometrically nonlinear analysis of 2D beam-column structures is developed by using curvilinear coordinates, which has considered the effects of the deforme...A tensor-based updated Lagrangian （UL） formulation for the geometrically nonlinear analysis of 2D beam-column structures is developed by using curvilinear coordinates, which has considered the effects of the deformed curvature. Between the known configuration C1 and the desired configuration C2, a configuration C2^＊ derived by rigid-body motion of C1 is introduced to eliminate the element-end transverse displacements between C2^＊ and C2. A stiffness matrix is obtained in C2^＊; and then by a transformation defined by the element-end displacements, the stiffness matrix in C2^＊ is transformed into that in CI. Comparing the stiffness matrix with that in the conventional UL formulation for a 2D beam element, the initial displacement stiffness matrix emerges, which results from the deformed curvature within the element. Numerical examples have verified the accuracy and efficiency of the present formulation, and the results show that the deformed curvatures have significant effects when deformations are large.展开更多
Hyperparasitemia is one criterion of severe falciparum malariaby World Health Organization(WHO)for more than two decades[1].Although there is a correlation between density of parasittemiaand severity of malaria,some i...Hyperparasitemia is one criterion of severe falciparum malariaby World Health Organization(WHO)for more than two decades[1].Although there is a correlation between density of parasittemiaand severity of malaria,some individuals with high parasite countsmay not be severely ill,whereas others with low parasitemia mayhave ultimately fatal infections.Hyperparasitemia(more than 5%展开更多
The performance of downlink multiple-input multiple-output (MIMO) cellular networks is limited by co-channel interference (CCI). In this paper, we propose a linear precoding scheme based on signal-to-leakage-and-noise...The performance of downlink multiple-input multiple-output (MIMO) cellular networks is limited by co-channel interference (CCI). In this paper, we propose a linear precoding scheme based on signal-to-leakage-and-noise ratio (SLNR) criteria which can reduce the CCI significantly. Since each user’s SLNR value is corresponding to the largest eigenvalue of the generalized matrix which indicates the channel quality that we propose a scheme to do a dynamic power allocation as an auxiliary way to improve SLNR precoding scheme. We use the perturbation theory to update each user’s SLNR value each time step in time-varying channels rather than directly decompose the channel matrix so as to reduce the amount of calculation. The simulation results show that the proposed scheme offers about 0.3 bps/Hz additional capacity gain and 0.5 dB BER gain over conventional SLNR precoding method with lower computational complexity. And it also obtains about 0.5 bps/Hz additional capacity gain and 1 dB BER gain compared to the scheme only update the preceding vectors.展开更多
Since 1894,the Geological Survey of Western Australia(GSWA)has released 14 versions of the‘Geological Map of Western Australia’.The latest in this series,published in December 2015,is the first bedrock geology map
Lithium-ion batteries have become the third-generation space batteries and are widely utilized in a series of spacecraft. Remaining Useful Life （RUL） estimation is essential to a spacecraft as the battery is a criti...Lithium-ion batteries have become the third-generation space batteries and are widely utilized in a series of spacecraft. Remaining Useful Life （RUL） estimation is essential to a spacecraft as the battery is a critical part and determines the lifetime and reliability. The Relevance Vector Machine （RVM） is a data-driven algorithm used to estimate a battery＇s RUL due to its sparse feature and uncertainty management capability. Especially, some of the regressive cases indicate that the RVM can obtain a better short-term prediction performance rather than long-term prediction. As a nonlinear kernel learning algorithm, the coefficient matrix and relevance vectors are fixed once the RVM training is conducted. Moreover, the RVM can be simply influenced by the noise with the training data. Thus, this work proposes an iterative updated approach to improve the long-term prediction performance for a battery＇s RUL prediction. Firstly, when a new estimator is output by the RVM, the Kalman filter is applied to optimize this estimator with a physical degradation model. Then, this optimized estimator is added into the training set as an on-line sample, the RVM model is re-trained, and the coefficient matrix and relevance vectors can be dynamically adjusted to make next iterative prediction. Experimental results with a commercial battery test data set and a satellite battery data set both indicate that the proposed method can achieve a better performance for RUL estimation.展开更多
The interactions between players of the prisoner's dilemma game are inferred using observed game data.All participants play the game with their counterparts and gain corresponding rewards during each round of the ...The interactions between players of the prisoner's dilemma game are inferred using observed game data.All participants play the game with their counterparts and gain corresponding rewards during each round of the game.The strategies of each player are updated asynchronously during the game.Two inference methods of the interactions between players are derived with naive mean-field(n MF)approximation and maximum log-likelihood estimation(MLE),respectively.Two methods are tested numerically also for fully connected asymmetric Sherrington-Kirkpatrick models,varying the data length,asymmetric degree,payoff,and system noise(coupling strength).We find that the mean square error of reconstruction for the MLE method is inversely proportional to the data length and typically half(benefit from the extra information of update times)of that by n MF.Both methods are robust to the asymmetric degree but work better for large payoffs.Compared with MLE,n MF is more sensitive to the strength of couplings and prefers weak couplings.展开更多
Nonlinear model predictive control(NMPC) is an appealing control technique for improving the performance of batch processes, but its implementation in industry is not always possible due to its heavy on-line computati...Nonlinear model predictive control(NMPC) is an appealing control technique for improving the performance of batch processes, but its implementation in industry is not always possible due to its heavy on-line computation. To facilitate the implementation of NMPC in batch processes, we propose a real-time updated model predictive control method based on state estimation. The method includes two strategies: a multiple model building strategy and a real-time model updated strategy. The multiple model building strategy is to produce a series of sim-plified models to reduce the on-line computational complexity of NMPC. The real-time model updated strategy is to update the simplified models to keep the accuracy of the models describing dynamic process behavior. The me-thod is validated with a typical batch reactor. Simulation studies show that the new method is efficient and robust with respect to model mismatch and changes in process parameters.展开更多
Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein...Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently.This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts:reliability index of a single member,identification of dominant failure modes,and system-level reliability analysis for system reliability analysis of truss structures.Firstly,RSM(response surface method)combines with a constrained optimization model to calculate the reliability indices ofmembers.Then theβ-unzipping method is adopted to identify the dominant failuremodes,and the system function in MATLAB,as well as the EKILL command in APDL,is used to facilitate the automatic update of the finite element model and realize load-redistribution.Besides,the differential equivalence recursion algorithmis performed to approximate the reliability indices of failuremodes efficiently and accurately.Eventually,the PNET(probabilistic network evaluation technique)is used to calculate the joint failure probability as well as the system reliability index.Two illustrative examples demonstrate the accuracy and efficiency of the proposed system reliability analysis framework through comparison with corresponding references.展开更多
Although blood lead levels(BLLs)in children have significantly decreased compared to two decades ago,incidents of lead poisoning and elevated BLLs among children continue to occur frequently.This trend suggests that C...Although blood lead levels(BLLs)in children have significantly decreased compared to two decades ago,incidents of lead poisoning and elevated BLLs among children continue to occur frequently.This trend suggests that China's current hygienic regulations are not sufficiently effective in managing children's lead exposure.This study analyzed the revision processes of blood lead reference values(BLRVs)in children from various countries,the current BLLs and their changing trends in China,potential sources of lead pollution and exposure,the requirements for managing and protecting children's health,as well as the national measures and strategies for lead emission management and control.The study also explored the necessity and urgency of updating China's BLRVs in children.Based on the specific conditions in China,a proposed BLRV of 50μg/L was deemed more reasonable and was suggested for implementation,with the potential to yield substantial economic benefits through improved IQ outcomes should the updated BLRV be adopted.展开更多
In this paper,the authors study a class of weighted version of probability density estimator.It is shown that the weighted estimator contains some existing estimators of probability density,no matter they are recursiv...In this paper,the authors study a class of weighted version of probability density estimator.It is shown that the weighted estimator contains some existing estimators of probability density,no matter they are recursive or non-recursive.Some statistical results including weak consistency,strong consistency,rate of strong consistency,and asymptotic normality are established under some mild conditions.Moreover,the random weighted estimator is also investigated.Some numerical simulations and a real data analysis are presented to study the numerical performances of the estimators.展开更多
This paper presents a new framework for producing monthly population maps at the census block level,which are crucial for population-related research and emergency response.Existing population products are outdated(e....This paper presents a new framework for producing monthly population maps at the census block level,which are crucial for population-related research and emergency response.Existing population products are outdated(e.g.,decennial)and at coarse spatial resolution(e.g.,national and global),as they rely on data that is collected and processed with a long lag time.The proposed framework is based on a comprehensive comparison of 34 models that use different methods(housing units,ordinary least squares,and machine learning),variables(social-economic,building,and vegetation),and classifications(7 and 2 classes).We employed the remote sensing Orthoimage,GIS tax parcel data,and SafeGraph home panel data to acquire the necessary variables that can reflect the spatial-temporal dynamics of the census block level populations.The best-performing model uses ordinary least squares with 3 kinds of information:the number of mobile phones,building area,and 7 class classifications(Single family,Two family,Three family,Mix family,Mix commercial family,Apartment,and Non-residential house).The model has a high accuracy(R^(2)=0.82)and can capture the monthly variations of population at the census block level.The framework is easy to implement and replicate by stakeholders,as it uses intuitive methods and readily available datasets.It can also reveal the detailed population patterns of cities over time,which can inform urban planning decisions.展开更多
Following the publication of Xu et al.(2022),an error was identified in Figure 1D.Specifically,the top left panel was inadvertently duplicated during figure preparation.To ensure the accuracy and integrity of our publ...Following the publication of Xu et al.(2022),an error was identified in Figure 1D.Specifically,the top left panel was inadvertently duplicated during figure preparation.To ensure the accuracy and integrity of our published work,we request the publication of a corrigendum with the corrected image.We apologize for this oversight and any confusion it may have caused.The amended figure is provided in the updated Supplementary Materials.展开更多
Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays...Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays an imperative role in receiving and transmitting the signals for any sensor network.Among varied antennas,micro strip fractal antenna(MFA)significantly contributes to increasing antenna gain.This study employs a hybrid optimization method known as the elephant clan updated grey wolf algorithm to introduce an optimized MFA design.This method optimizes antenna characteristics,including directivity and gain.Here,the factors,including length,width,ground plane length,height,and feed offset-X and feed offset-Y,are taken into account to achieve the best performance of gain and directivity.Ultimately,the superiority of the suggested technique over state-of-the-art strategies is calculated for various metrics such as cost and gain.The adopted model converges to a minimal value of 0.2872.Further,the spider monkey optimization(SMO)model accomplishes the worst performance over all other existing models like elephant herding optimization(EHO),grey wolf optimization(GWO),lion algorithm(LA),support vector regressor(SVR),bacterial foraging-particle swarm optimization(BF-PSO)and shark smell optimization(SSO).Effective MFA design is obtained using the suggested strategy regarding various parameters.展开更多
基金open foundation of the Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanicsthe Open Foundation of Hubei Key Laboratory of Engineering Structural Analysis and Safety Assessment.
文摘A fluid-structure interaction approach is proposed in this paper based onNon-Ordinary State-Based Peridynamics(NOSB-PD)and Updated Lagrangian Particle Hydrodynamics(ULPH)to simulate the fluid-structure interaction problem with large geometric deformation and material failure and solve the fluid-structure interaction problem of Newtonian fluid.In the coupled framework,the NOSB-PD theory describes the deformation and fracture of the solid material structure.ULPH is applied to describe the flow of Newtonian fluids due to its advantages in computational accuracy.The framework utilizes the advantages of NOSB-PD theory for solving discontinuous problems and ULPH theory for solving fluid problems,with good computational stability and robustness.A fluidstructure coupling algorithm using pressure as the transmission medium is established to deal with the fluidstructure interface.The dynamic model of solid structure and the PD-ULPH fluid-structure interaction model involving large deformation are verified by numerical simulations.The results agree with the analytical solution,the available experimental data,and other numerical results.Thus,the accuracy and effectiveness of the proposed method in solving the fluid-structure interaction problem are demonstrated.The fluid-structure interactionmodel based on ULPH and NOSB-PD established in this paper provides a new idea for the numerical solution of fluidstructure interaction and a promising approach for engineering design and experimental prediction.
基金support from the National Natural Science Foundations of China(Nos.11972267 and 11802214)the Open Foundation of the Hubei Key Laboratory of Theory and Application of Advanced Materials Mechanics and the Open Foundation of Hubei Key Laboratory of Engineering Structural Analysis and Safety Assessment.
文摘Natural convection is a heat transfer mechanism driven by temperature or density differences,leading to fluid motion without external influence.It occurs in various natural and engineering phenomena,influencing heat transfer,climate,and fluid mixing in industrial processes.This work aims to use the Updated Lagrangian Particle Hydrodynamics(ULPH)theory to address natural convection problems.The Navier-Stokes equation is discretized using second-order nonlocal differential operators,allowing a direct solution of the Laplace operator for temperature in the energy equation.Various numerical simulations,including cases such as natural convection in square cavities and two concentric cylinders,were conducted to validate the reliability of the model.The results demonstrate that the proposed model exhibits excellent accuracy and performance,providing a promising and effective numerical approach for natural convection problems.
基金co-supported by the National Natural Science Foundation of China(Nos.U223321251875014)+1 种基金the Beijing Natural Science Foundation,China(No.L221008)the China Scholarship Council(No.202106020001).
文摘Current research on Digital Twin(DT)based Prognostics and Health Management(PHM)focuses on establishment of DT through integration of real-time data from various sources to facilitate comprehensive product monitoring and health management.However,there still exist gaps in the seamless integration of DT and PHM,as well as in the development of DT multi-field coupling modeling and its dynamic update mechanism.When the product experiences long-period degradation under load spectrum,it is challenging to describe the dynamic evolution of the health status and degradation progression accurately.In addition,DT update algorithms are difficult to be integrated simultaneously by current methods.This paper proposes an innovative dual loop DT based PHM framework,in which the first loop establishes the basic dynamic DT with multi-filed coupling,and the second loop implements the PHM and the abnormal detection to provide the interaction between the dual loops through updating mechanism.The proposed method pays attention to the internal state changes with degradation and interactive mapping with dynamic parameter updating.Furthermore,the Independence Principle for the abnormal detection is proposed to refine the theory of DT.Events at the first loop focus on accurate modeling of multi-field coupling,while the events at the second loop focus on real-time occurrence of anomalies and the product degradation trend.The interaction and collaboration between different loop models are also discussed.Finally,the Permanent Magnet Synchronous Motor(PMSM)is used to verify the proposed method.The results show that the modeling method proposed can accurately track the lifecycle performance changes of the entity and carry out remaining life prediction and health management effectively.
文摘Cancer is a major public health issue in most of countries, including China. Accurate and valid information on cancer incidence, mortality, survival and relevant factors is irreplaceable for cancer prevention and control. Since the national program of cancer registry was launched by the Ministry of Health of China in 2008, the National Central Cancer Registry （NCCR） has been releasing the cancer incidence and mortality based on the data collected from cancer registries supported by the program. The cancer statistics provide current data from registered areas and aims to accurately reflect the cancer burden and epidemic in China. In 2014, the NCCR collected data for calendar year 2011 from 234 registries. After comprehensive quality＇ evaluation, data from 177 registries have been selected as sources of the reports reflecting cancer incidence and mortaliD, in the registration areas in 2011. These reports are the updated cancer statistics so far, covering much more registries and a hig population.
文摘BACKGROUND The Updated Sydney system for visual evaluation of gastric mucosal atrophy viaendoscopic observation is subject to sampling error and interobserver variability.The Kimura-Takemoto classification system was developed to overcome theselimitations.AIMTo compare the morphological classification of atrophic gastritis between theKimura-Takemoto system and the Updated Sydney system.METHODSA total of 169 patients with atrophic gastritis were selected according to diagnosisby the visual endoscopic Kimura-Takemoto method. Following the UpdatedKimura-Takemoto classification system, one antrum biopsy and five gastriccorpus biopsies were taken according to the visual stages of the Kimura-Takemoto system. The Updated Kimura-Takemoto classification system was thenapplied to each and showed 165 to have histological mucosal atrophy;theremaining 4 patients had no histological evidence of atrophy in any biopsy. The Updated Kimura-Takemoto classification was verified as a referencemorphological method and applied for the diagnosis of atrophic gastritis. Addingone more biopsy from the antrum to the six biopsies according to the Updated Kimura-Takemoto classification, constitutes the updated combined Kimura-Takemoto classification and Sydney system.RESULTSThe sensitivity for degree of mucosal atrophy assessed by the Updated Sydneysystem was 25% for mild, 36% for moderate, and 42% for severe, when comparedwith the Updated Kimura-Takemoto classification of atrophic gastritis formorphological diagnosis. Four types of multifocal atrophic gastritis wereidentified: sequential uniform (type 1;in 28%), sequential non-uniform (type 2;in7%), diffuse uniform (type 3;in 23%), diffuse non-uniform (type 4;in 24%), and"alternating atrophic – non-atrophic" (type 5;in 18%). The pattern of the spread ofatrophy, sequentially from the antrum to the cardiac segment of the stomach,which was described by the Updated Kimura-Takemoto system, washistologically confirmed in 82% of cases evaluated.CONCLUSIONThe Updated Sydney system is significantly inferior to the Updated Kimura-Takemoto classification for morphological verification of atrophic gastritis.
文摘A tensor-based updated Lagrangian （UL） formulation for the geometrically nonlinear analysis of 2D beam-column structures is developed by using curvilinear coordinates, which has considered the effects of the deformed curvature. Between the known configuration C1 and the desired configuration C2, a configuration C2^＊ derived by rigid-body motion of C1 is introduced to eliminate the element-end transverse displacements between C2^＊ and C2. A stiffness matrix is obtained in C2^＊; and then by a transformation defined by the element-end displacements, the stiffness matrix in C2^＊ is transformed into that in CI. Comparing the stiffness matrix with that in the conventional UL formulation for a 2D beam element, the initial displacement stiffness matrix emerges, which results from the deformed curvature within the element. Numerical examples have verified the accuracy and efficiency of the present formulation, and the results show that the deformed curvatures have significant effects when deformations are large.
基金supported by the Office of the Higher Education CommissionMahidol University under the National Research Universities Initiativethe Faculty of Tropical Medicine,Mahidol University in Thailand
文摘Hyperparasitemia is one criterion of severe falciparum malariaby World Health Organization(WHO)for more than two decades[1].Although there is a correlation between density of parasittemiaand severity of malaria,some individuals with high parasite countsmay not be severely ill,whereas others with low parasitemia mayhave ultimately fatal infections.Hyperparasitemia(more than 5%
文摘The performance of downlink multiple-input multiple-output (MIMO) cellular networks is limited by co-channel interference (CCI). In this paper, we propose a linear precoding scheme based on signal-to-leakage-and-noise ratio (SLNR) criteria which can reduce the CCI significantly. Since each user’s SLNR value is corresponding to the largest eigenvalue of the generalized matrix which indicates the channel quality that we propose a scheme to do a dynamic power allocation as an auxiliary way to improve SLNR precoding scheme. We use the perturbation theory to update each user’s SLNR value each time step in time-varying channels rather than directly decompose the channel matrix so as to reduce the amount of calculation. The simulation results show that the proposed scheme offers about 0.3 bps/Hz additional capacity gain and 0.5 dB BER gain over conventional SLNR precoding method with lower computational complexity. And it also obtains about 0.5 bps/Hz additional capacity gain and 1 dB BER gain compared to the scheme only update the preceding vectors.
文摘Since 1894,the Geological Survey of Western Australia(GSWA)has released 14 versions of the‘Geological Map of Western Australia’.The latest in this series,published in December 2015,is the first bedrock geology map
基金co-supported in part by the National Natural Science Foundation of China (Nos. 61301205 and 61571160)the Natural Scientific Research Innovation Foundation at Harbin Institute of Technology (No. HIT.NSRIF.2014017)
文摘Lithium-ion batteries have become the third-generation space batteries and are widely utilized in a series of spacecraft. Remaining Useful Life （RUL） estimation is essential to a spacecraft as the battery is a critical part and determines the lifetime and reliability. The Relevance Vector Machine （RVM） is a data-driven algorithm used to estimate a battery＇s RUL due to its sparse feature and uncertainty management capability. Especially, some of the regressive cases indicate that the RVM can obtain a better short-term prediction performance rather than long-term prediction. As a nonlinear kernel learning algorithm, the coefficient matrix and relevance vectors are fixed once the RVM training is conducted. Moreover, the RVM can be simply influenced by the noise with the training data. Thus, this work proposes an iterative updated approach to improve the long-term prediction performance for a battery＇s RUL prediction. Firstly, when a new estimator is output by the RVM, the Kalman filter is applied to optimize this estimator with a physical degradation model. Then, this optimized estimator is added into the training set as an on-line sample, the RVM model is re-trained, and the coefficient matrix and relevance vectors can be dynamically adjusted to make next iterative prediction. Experimental results with a commercial battery test data set and a satellite battery data set both indicate that the proposed method can achieve a better performance for RUL estimation.
基金supported by the National Natural Science Foundation of China(Grant Nos.11705079 and 11705279)the Scientific Research Foundation of Nanjing University of Posts and Telecommunications(Grant Nos.NY221101 and NY222134)the Science and Technology Innovation Training Program(Grant No.STITP 202210293044Z)。
文摘The interactions between players of the prisoner's dilemma game are inferred using observed game data.All participants play the game with their counterparts and gain corresponding rewards during each round of the game.The strategies of each player are updated asynchronously during the game.Two inference methods of the interactions between players are derived with naive mean-field(n MF)approximation and maximum log-likelihood estimation(MLE),respectively.Two methods are tested numerically also for fully connected asymmetric Sherrington-Kirkpatrick models,varying the data length,asymmetric degree,payoff,and system noise(coupling strength).We find that the mean square error of reconstruction for the MLE method is inversely proportional to the data length and typically half(benefit from the extra information of update times)of that by n MF.Both methods are robust to the asymmetric degree but work better for large payoffs.Compared with MLE,n MF is more sensitive to the strength of couplings and prefers weak couplings.
基金Supported by the National Natural Science Foundation of China(21136003,21176089)the National Science&Technology Support Plan(2012BAK13B02)+2 种基金the National Major Basic Research Program(2014CB744306)the Natural Science Foundation Team Project of Guangdong Province(S2011030001366)the Fundamental Research Funds for Central Universities(2013ZP0010)
文摘Nonlinear model predictive control(NMPC) is an appealing control technique for improving the performance of batch processes, but its implementation in industry is not always possible due to its heavy on-line computation. To facilitate the implementation of NMPC in batch processes, we propose a real-time updated model predictive control method based on state estimation. The method includes two strategies: a multiple model building strategy and a real-time model updated strategy. The multiple model building strategy is to produce a series of sim-plified models to reduce the on-line computational complexity of NMPC. The real-time model updated strategy is to update the simplified models to keep the accuracy of the models describing dynamic process behavior. The me-thod is validated with a typical batch reactor. Simulation studies show that the new method is efficient and robust with respect to model mismatch and changes in process parameters.
基金support from the National Key R&D Program of China(Grant Nos.2021YFB2600605,2021YFB2600600)the Overseas Scholar Program in the Hebei Province(C20190514)+1 种基金from the State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Project(ZZ2020-20)from the Youth Foundation of Hebei Science and Technology Research Project(QN2018108).
文摘Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently.This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts:reliability index of a single member,identification of dominant failure modes,and system-level reliability analysis for system reliability analysis of truss structures.Firstly,RSM(response surface method)combines with a constrained optimization model to calculate the reliability indices ofmembers.Then theβ-unzipping method is adopted to identify the dominant failuremodes,and the system function in MATLAB,as well as the EKILL command in APDL,is used to facilitate the automatic update of the finite element model and realize load-redistribution.Besides,the differential equivalence recursion algorithmis performed to approximate the reliability indices of failuremodes efficiently and accurately.Eventually,the PNET(probabilistic network evaluation technique)is used to calculate the joint failure probability as well as the system reliability index.Two illustrative examples demonstrate the accuracy and efficiency of the proposed system reliability analysis framework through comparison with corresponding references.
基金supported by the National Key Research and Development Program of China(2022YFC3701303,2022YFC3702604)National Natural Science Foundation of China(41977374)Chinese Academy of Engineering Strategic Research and Consulting Project(2024-XZ-42).
文摘Although blood lead levels(BLLs)in children have significantly decreased compared to two decades ago,incidents of lead poisoning and elevated BLLs among children continue to occur frequently.This trend suggests that China's current hygienic regulations are not sufficiently effective in managing children's lead exposure.This study analyzed the revision processes of blood lead reference values(BLRVs)in children from various countries,the current BLLs and their changing trends in China,potential sources of lead pollution and exposure,the requirements for managing and protecting children's health,as well as the national measures and strategies for lead emission management and control.The study also explored the necessity and urgency of updating China's BLRVs in children.Based on the specific conditions in China,a proposed BLRV of 50μg/L was deemed more reasonable and was suggested for implementation,with the potential to yield substantial economic benefits through improved IQ outcomes should the updated BLRV be adopted.
基金supported by the National Natural Science Foundation of China under Grant Nos.12201079,12201004,and 11871072the National Social Science Foundation of China under Grant No.22BTJ059+1 种基金the Natural Science Foundation of Anhui Province under Grant Nos.2108085QA15 and 2108085MA06the“INSA Senior Scientist”scheme at the CR Rao Advanced Institute of Mathematics,Statistics and Computer Science,Hyderabad 500046,India.
文摘In this paper,the authors study a class of weighted version of probability density estimator.It is shown that the weighted estimator contains some existing estimators of probability density,no matter they are recursive or non-recursive.Some statistical results including weak consistency,strong consistency,rate of strong consistency,and asymptotic normality are established under some mild conditions.Moreover,the random weighted estimator is also investigated.Some numerical simulations and a real data analysis are presented to study the numerical performances of the estimators.
文摘This paper presents a new framework for producing monthly population maps at the census block level,which are crucial for population-related research and emergency response.Existing population products are outdated(e.g.,decennial)and at coarse spatial resolution(e.g.,national and global),as they rely on data that is collected and processed with a long lag time.The proposed framework is based on a comprehensive comparison of 34 models that use different methods(housing units,ordinary least squares,and machine learning),variables(social-economic,building,and vegetation),and classifications(7 and 2 classes).We employed the remote sensing Orthoimage,GIS tax parcel data,and SafeGraph home panel data to acquire the necessary variables that can reflect the spatial-temporal dynamics of the census block level populations.The best-performing model uses ordinary least squares with 3 kinds of information:the number of mobile phones,building area,and 7 class classifications(Single family,Two family,Three family,Mix family,Mix commercial family,Apartment,and Non-residential house).The model has a high accuracy(R^(2)=0.82)and can capture the monthly variations of population at the census block level.The framework is easy to implement and replicate by stakeholders,as it uses intuitive methods and readily available datasets.It can also reveal the detailed population patterns of cities over time,which can inform urban planning decisions.
文摘Following the publication of Xu et al.(2022),an error was identified in Figure 1D.Specifically,the top left panel was inadvertently duplicated during figure preparation.To ensure the accuracy and integrity of our published work,we request the publication of a corrigendum with the corrected image.We apologize for this oversight and any confusion it may have caused.The amended figure is provided in the updated Supplementary Materials.
文摘Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays an imperative role in receiving and transmitting the signals for any sensor network.Among varied antennas,micro strip fractal antenna(MFA)significantly contributes to increasing antenna gain.This study employs a hybrid optimization method known as the elephant clan updated grey wolf algorithm to introduce an optimized MFA design.This method optimizes antenna characteristics,including directivity and gain.Here,the factors,including length,width,ground plane length,height,and feed offset-X and feed offset-Y,are taken into account to achieve the best performance of gain and directivity.Ultimately,the superiority of the suggested technique over state-of-the-art strategies is calculated for various metrics such as cost and gain.The adopted model converges to a minimal value of 0.2872.Further,the spider monkey optimization(SMO)model accomplishes the worst performance over all other existing models like elephant herding optimization(EHO),grey wolf optimization(GWO),lion algorithm(LA),support vector regressor(SVR),bacterial foraging-particle swarm optimization(BF-PSO)and shark smell optimization(SSO).Effective MFA design is obtained using the suggested strategy regarding various parameters.
