This paper systematically summarizes previous measuring methods and observational instruments for the magnitude of dewfall on land surface, analyzes the characteristics of common observational instruments for land sur...This paper systematically summarizes previous measuring methods and observational instruments for the magnitude of dewfall on land surface, analyzes the characteristics of common observational instruments for land surface dewfall, and describes several basic dewfall measurement methods. Moreover, the basic principles of these methods and instruments are interpreted, and their advantages, disadvantages, and applicability are analyzed. Recommendations for the further improvement of these observational instruments and the development of dewfall measuring methods are presented, and new technologies and scientific proposals for exploiting dewfall are elucidated.展开更多
Observation-based method for O_(3)formation sensitivity research is an important tool to analyze the causes of ground-level O_(3)pollution,which has broad application potentials in determining the O_(3)pollution forma...Observation-based method for O_(3)formation sensitivity research is an important tool to analyze the causes of ground-level O_(3)pollution,which has broad application potentials in determining the O_(3)pollution formation mechanism and developing prevention and control strategies.This paper outlined the development history of research on O_(3)formation sensitivity based on observational methods,described the principle and applicability of the methodology,summarized the relative application results in China and provided recommendations on the prevention and control of O_(3)pollution in China based on relevant study results,and finally pointed out the shortcomings and future development prospects in this field in China.The overview study showed that the O_(3)formation sensitivity in some urban areas in China in recent years presented a gradual shifting tendency from the VOC-limited regime to the transition regime or the NO_(x)-limited regime due to the implementation of the O_(3)precursors emission reduction policies;O_(3)pollution control strategies and precursor control countermeasures should be formulated based on local conditions and the dynamic control capability of O_(3)pollution control measures should be improved.There are still some current deficiencies in the study field in China.Therefore,it is recommended that a stereoscopic monitoring network for atmospheric photochemical components should be further constructed and improved;the atmospheric chemical mechanisms should be vigorously developed,and standardized methods for determining the O_(3)formation sensitivity should be established in China in the near future.展开更多
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytica...The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.展开更多
Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vi...Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.展开更多
In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error...In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.展开更多
Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.Howev...Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
The element-free Galerkin(EFG)method,which constructs shape functions via moving least squares(MLS)approximation,represents a fundamental and widely studied meshless method in numerical computation.Although it achieve...The element-free Galerkin(EFG)method,which constructs shape functions via moving least squares(MLS)approximation,represents a fundamental and widely studied meshless method in numerical computation.Although it achieves high computational accuracy,the shape functions are more complex than those in the conventional finite element method(FEM),resulting in great computational requirements.Therefore,improving the computational efficiency of the EFG method represents an important research direction.This paper systematically reviews significant contributions fromdomestic and international scholars in advancing the EFGmethod.Including the improved element-free Galerkin(IEFG)method,various interpolating EFG methods,four distinct complex variable EFG methods,and a series of dimension splitting meshless methods.In the numerical examples,the effectiveness and efficiency of the three methods are validated by analyzing the solutions of the IEFG method for 3D steadystate anisotropic heat conduction,3D elastoplasticity,and large deformation problems,as well as the performance of two-dimensional splitting meshless methods in solving the 3D Helmholtz equation.展开更多
RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performa...RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.展开更多
Understanding the wind power potential of a site is essential for designing an optimal wind power conditioning system. The Weibull distribution and wind speed extrapolation methods are powerful mathematical tools for ...Understanding the wind power potential of a site is essential for designing an optimal wind power conditioning system. The Weibull distribution and wind speed extrapolation methods are powerful mathematical tools for efficiently predicting the frequency distribution of wind speeds at a site. Hourly wind speed and direction data were collected from the National Aeronautics and Space Administration (NASA) website for the period 2013 to 2023. MATLAB software was used to calculate the distribution parameters using the graphical method and to plot the corresponding curves, while WRPLOTView software was used to construct the wind rose. The average wind speed obtained is 3.33 m/s and can reach up to 5.71 m/s at a height of 100 meters. The wind energy is estimated to be 1315.30 kWh/m2 at a height of 100 meters. The wind rose indicates the prevailing winds (ranging from 3.60 m/s to 5.70 m/s) in the northeast-east direction.展开更多
Purpose–For the commonly used concrete mix for railway tunnel linings,concrete model specimens were made,and springback and core drilling tests were conducted at different ages.The springback strength was measured to...Purpose–For the commonly used concrete mix for railway tunnel linings,concrete model specimens were made,and springback and core drilling tests were conducted at different ages.The springback strength was measured to the compressive strength of the core sample with a diameter of 100mm and a height-to-diameter ratio of 1:1.By comparing the measured strength values,the relationship between the measured values under different strength measurement methods was analyzed.Design/methodology/approach–A comparative test of the core drilling method and the rebound method was conducted on the side walls of tunnel linings in some under-construction railways to study the feasibility of the rebound method in engineering quality supervision and inspection.Findings–Tests showed that the rebound strength was positively correlated with the core drill strength.The core drill test strength was significantly higher than the rebound test strength,and the strength still increased after 56 days of age.The rebound method is suitable for the general survey of concrete strength during the construction process and is not suitable for direct supervision and inspection.Originality/value–By studying the correlation of test strength of tunnel lining concrete using two methods,the differences in test results of different methods are proposed to provide a reference for the test and evaluation of tunnel lining strength in railway engineering.展开更多
Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the nume...Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.展开更多
As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and s...As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.展开更多
Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure...Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.展开更多
Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of un...Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of unsteady flows.To enhance computational efficiency,we propose the Implicit-Explicit Two-Step Runge-Kutta(IMEX-TSRK)time-stepping discretization methods for unsteady flows,and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods.The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency.Compared to implicit and explicit Runge-Kutta(RK)schemes,the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations.Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency.Specifically,in high Reynolds number flows,the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude,and that of implicit RK schemes several times over.展开更多
In this paper,a new technique is introduced to construct higher-order iterative methods for solving nonlinear systems.The order of convergence of some iterative methods can be improved by three at the cost of introduc...In this paper,a new technique is introduced to construct higher-order iterative methods for solving nonlinear systems.The order of convergence of some iterative methods can be improved by three at the cost of introducing only one additional evaluation of the function in each step.Furthermore,some new efficient methods with a higher-order of convergence are obtained by using only a single matrix inversion in each iteration.Analyses of convergence properties and computational efficiency of these new methods are made and testified by several numerical problems.By comparison,the new schemes are more efficient than the corresponding existing ones,particularly for large problem sizes.展开更多
Ribonucleic Acid(RNA)contact prediction holds great significance for modeling RNA 3D structures and further understanding RNA biological functions.The rapid growth of RNA sequencing data has driven the development of ...Ribonucleic Acid(RNA)contact prediction holds great significance for modeling RNA 3D structures and further understanding RNA biological functions.The rapid growth of RNA sequencing data has driven the development of diverse computational methods for RNA contact prediction,and a benchmark evaluation of these methods remains essential.In this work,we first classified RNA contact prediction methods into statistical inference-based and neural networkbased ones.We then evaluated eight state-of-the-art methods on three test sets:a sequencediverse set,a structurally non-redundant set and a CASP RNA targets set.Our evaluation shows that for identifying non-local and long-range contacts,neural network-based methods outperform statistical inference-based ones,with SPOT-RNA-2D achieving the best performance,followed by CoCoNet and RNAcontact.However,for identifying the long-range tertiary contacts,which are vital for stabilizing RNA tertiary structure,statistical inference-based methods exhibit superior performance with GREMLIN emerging as the top performer.This work provides a comprehensive benchmarking of RNA contact prediction methods,highlighting their strengths and limitations to guide further methodological improvements and applications in RNA structure modeling.展开更多
Objective Observational studies have found associations between inflammatory bowel disease(IBD)and the risk of dementia,including Alzheimer’s dementia(AD)and vascular dementia(VD);however,these findings are inconsist...Objective Observational studies have found associations between inflammatory bowel disease(IBD)and the risk of dementia,including Alzheimer’s dementia(AD)and vascular dementia(VD);however,these findings are inconsistent.It remains unclear whether these associations are causal.Methods We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia.Mendelian randomization(MR)analysis based on summary genome-wide association studies(GWASs)was performed.Genetic correlation and Bayesian colocalization analyses were used to provide robust genetic evidence.Results Ten observational studies involving 80,565,688 participants were included in this metaanalysis.IBD was significantly associated with dementia(risk ratio[RR]=1.36,95%CI=1.04-1.78;I2=84.8%)and VD(RR=2.60,95%CI=1.18-5.70;only one study),but not with AD(RR=2.00,95%CI=0.96-4.13;I^(2)=99.8%).MR analyses did not supported significant causal associations of IBD with dementia(dementia:odds ratio[OR]=1.01,95%CI=0.98-1.03;AD:OR=0.98,95%CI=0.95-1.01;VD:OR=1.02,95%CI=0.97-1.07).In addition,genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia.Conclusion Our study did not provide genetic evidence for a causal association between IBD and dementia risk.The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.展开更多
The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of t...The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of this methodology are to decouple a system of ODEs of second order into a set of uncoupled ODEs of second order;next,an eigen-dependent method is proposed to approximate the solution of each uncoupled ODE of second order.It is vital to transform all eigen-dependent methods to a problem-dependent method to bypass an Eigen analysis.The development of an eigen-dependent method plays a key role in this methodology so that slow eigenmodes can be accurately integrated while there is no instability or excessive amplitude growth in fast eigenmodes.This can explain why a problem-dependent method can simultaneously combine the explicitness of each step and A-stability.Consequently,huge computational efforts can be saved for solving nonlinear stiff problems.A new family of problem-dependent methods is developed in this work so that the feasibility of the proposed methodology can be affirmed.It has almost the same performance as that of the HHT-αmethod.However,it can save more than 99.5%of CPU demand in approximating a solution for a system of 1000 nonlinear second order ODEs.展开更多
基金supported by the National Science Foundation of China (Grant Nos. 40830957 and 40575006)
文摘This paper systematically summarizes previous measuring methods and observational instruments for the magnitude of dewfall on land surface, analyzes the characteristics of common observational instruments for land surface dewfall, and describes several basic dewfall measurement methods. Moreover, the basic principles of these methods and instruments are interpreted, and their advantages, disadvantages, and applicability are analyzed. Recommendations for the further improvement of these observational instruments and the development of dewfall measuring methods are presented, and new technologies and scientific proposals for exploiting dewfall are elucidated.
基金supported by the National Research Program for Key Issues in Air Pollution Control(No.DQGG202121)the Beijing Municipal Science&Technology Commission(No.Z181100005418015)+1 种基金National Natural Science Foundation of China(No.42075094)the National Research Program for Key Issue in Air Pollution Control(No.DQGG2021101)。
文摘Observation-based method for O_(3)formation sensitivity research is an important tool to analyze the causes of ground-level O_(3)pollution,which has broad application potentials in determining the O_(3)pollution formation mechanism and developing prevention and control strategies.This paper outlined the development history of research on O_(3)formation sensitivity based on observational methods,described the principle and applicability of the methodology,summarized the relative application results in China and provided recommendations on the prevention and control of O_(3)pollution in China based on relevant study results,and finally pointed out the shortcomings and future development prospects in this field in China.The overview study showed that the O_(3)formation sensitivity in some urban areas in China in recent years presented a gradual shifting tendency from the VOC-limited regime to the transition regime or the NO_(x)-limited regime due to the implementation of the O_(3)precursors emission reduction policies;O_(3)pollution control strategies and precursor control countermeasures should be formulated based on local conditions and the dynamic control capability of O_(3)pollution control measures should be improved.There are still some current deficiencies in the study field in China.Therefore,it is recommended that a stereoscopic monitoring network for atmospheric photochemical components should be further constructed and improved;the atmospheric chemical mechanisms should be vigorously developed,and standardized methods for determining the O_(3)formation sensitivity should be established in China in the near future.
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金supported by the National Natural Science Foundation of China(12172023).
文摘The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.
基金funded by the National Natural Science Foundation of China(No.41962016)the Natural Science Foundation of NingXia(Nos.2023AAC02023,2023A1218,and 2021AAC02006).
文摘Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.
文摘In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.
基金Supported by the National Natural Science Foundation of China(Nos.52222904 and 52309117)China Postdoctoral Science Foundation(Nos.2022TQ0168 and 2023M731895).
文摘Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金supported by the National Natural Science Foundation of China(Grant No.12271341).
文摘The element-free Galerkin(EFG)method,which constructs shape functions via moving least squares(MLS)approximation,represents a fundamental and widely studied meshless method in numerical computation.Although it achieves high computational accuracy,the shape functions are more complex than those in the conventional finite element method(FEM),resulting in great computational requirements.Therefore,improving the computational efficiency of the EFG method represents an important research direction.This paper systematically reviews significant contributions fromdomestic and international scholars in advancing the EFGmethod.Including the improved element-free Galerkin(IEFG)method,various interpolating EFG methods,four distinct complex variable EFG methods,and a series of dimension splitting meshless methods.In the numerical examples,the effectiveness and efficiency of the three methods are validated by analyzing the solutions of the IEFG method for 3D steadystate anisotropic heat conduction,3D elastoplasticity,and large deformation problems,as well as the performance of two-dimensional splitting meshless methods in solving the 3D Helmholtz equation.
基金supported by grants from the National Science Foundation of China(Grant Nos.12375038 and 12075171 to ZJT,and 12205223 to YLT).
文摘RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.
文摘Understanding the wind power potential of a site is essential for designing an optimal wind power conditioning system. The Weibull distribution and wind speed extrapolation methods are powerful mathematical tools for efficiently predicting the frequency distribution of wind speeds at a site. Hourly wind speed and direction data were collected from the National Aeronautics and Space Administration (NASA) website for the period 2013 to 2023. MATLAB software was used to calculate the distribution parameters using the graphical method and to plot the corresponding curves, while WRPLOTView software was used to construct the wind rose. The average wind speed obtained is 3.33 m/s and can reach up to 5.71 m/s at a height of 100 meters. The wind energy is estimated to be 1315.30 kWh/m2 at a height of 100 meters. The wind rose indicates the prevailing winds (ranging from 3.60 m/s to 5.70 m/s) in the northeast-east direction.
文摘Purpose–For the commonly used concrete mix for railway tunnel linings,concrete model specimens were made,and springback and core drilling tests were conducted at different ages.The springback strength was measured to the compressive strength of the core sample with a diameter of 100mm and a height-to-diameter ratio of 1:1.By comparing the measured strength values,the relationship between the measured values under different strength measurement methods was analyzed.Design/methodology/approach–A comparative test of the core drilling method and the rebound method was conducted on the side walls of tunnel linings in some under-construction railways to study the feasibility of the rebound method in engineering quality supervision and inspection.Findings–Tests showed that the rebound strength was positively correlated with the core drill strength.The core drill test strength was significantly higher than the rebound test strength,and the strength still increased after 56 days of age.The rebound method is suitable for the general survey of concrete strength during the construction process and is not suitable for direct supervision and inspection.Originality/value–By studying the correlation of test strength of tunnel lining concrete using two methods,the differences in test results of different methods are proposed to provide a reference for the test and evaluation of tunnel lining strength in railway engineering.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.42122034,42075043,42330609)the Second Tibetan Plateau Scientific Expedition and Research program(2019QZKK0103)+2 种基金Key Talent Project in Gansu and Central Guidance Fund for Local Science and Technology Development Projects in Gansu(No.24ZYQA031)the Youth Innovation Promotion Association of Chinese Academy of Sciences(2021427)West Light Foundation of the Chinese Academy of Sciences(xbzg-zdsys-202215)。
文摘Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grants(52275471 and 52120105008)the Beijing Outstanding Young Scientist Program,and the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.
文摘Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.
基金supported by the National Natural Science Foundation of China(No.92252201)the Fundamental Research Funds for the Central Universitiesthe Academic Excellence Foundation of Beihang University(BUAA)for PhD Students。
文摘Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of unsteady flows.To enhance computational efficiency,we propose the Implicit-Explicit Two-Step Runge-Kutta(IMEX-TSRK)time-stepping discretization methods for unsteady flows,and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods.The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency.Compared to implicit and explicit Runge-Kutta(RK)schemes,the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations.Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency.Specifically,in high Reynolds number flows,the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude,and that of implicit RK schemes several times over.
基金Supported by the National Natural Science Foundation of China(12061048)NSF of Jiangxi Province(20232BAB201026,20232BAB201018)。
文摘In this paper,a new technique is introduced to construct higher-order iterative methods for solving nonlinear systems.The order of convergence of some iterative methods can be improved by three at the cost of introducing only one additional evaluation of the function in each step.Furthermore,some new efficient methods with a higher-order of convergence are obtained by using only a single matrix inversion in each iteration.Analyses of convergence properties and computational efficiency of these new methods are made and testified by several numerical problems.By comparison,the new schemes are more efficient than the corresponding existing ones,particularly for large problem sizes.
基金supported by grants from the National Natural Science Foundation of China(Grant No.12205223 to YLT,Grant No.12375038 to ZJT and Grant No.11605125 to YZS)the Department of Education of Hubei Province(Grant No.Q20221705 to YLT)。
文摘Ribonucleic Acid(RNA)contact prediction holds great significance for modeling RNA 3D structures and further understanding RNA biological functions.The rapid growth of RNA sequencing data has driven the development of diverse computational methods for RNA contact prediction,and a benchmark evaluation of these methods remains essential.In this work,we first classified RNA contact prediction methods into statistical inference-based and neural networkbased ones.We then evaluated eight state-of-the-art methods on three test sets:a sequencediverse set,a structurally non-redundant set and a CASP RNA targets set.Our evaluation shows that for identifying non-local and long-range contacts,neural network-based methods outperform statistical inference-based ones,with SPOT-RNA-2D achieving the best performance,followed by CoCoNet and RNAcontact.However,for identifying the long-range tertiary contacts,which are vital for stabilizing RNA tertiary structure,statistical inference-based methods exhibit superior performance with GREMLIN emerging as the top performer.This work provides a comprehensive benchmarking of RNA contact prediction methods,highlighting their strengths and limitations to guide further methodological improvements and applications in RNA structure modeling.
基金supported by the China Postdoctoral Science Foundation(Grant No.2021M703366)Shenzhen Science and Technology Program(Grant No.KQTD20190929172835662).
文摘Objective Observational studies have found associations between inflammatory bowel disease(IBD)and the risk of dementia,including Alzheimer’s dementia(AD)and vascular dementia(VD);however,these findings are inconsistent.It remains unclear whether these associations are causal.Methods We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia.Mendelian randomization(MR)analysis based on summary genome-wide association studies(GWASs)was performed.Genetic correlation and Bayesian colocalization analyses were used to provide robust genetic evidence.Results Ten observational studies involving 80,565,688 participants were included in this metaanalysis.IBD was significantly associated with dementia(risk ratio[RR]=1.36,95%CI=1.04-1.78;I2=84.8%)and VD(RR=2.60,95%CI=1.18-5.70;only one study),but not with AD(RR=2.00,95%CI=0.96-4.13;I^(2)=99.8%).MR analyses did not supported significant causal associations of IBD with dementia(dementia:odds ratio[OR]=1.01,95%CI=0.98-1.03;AD:OR=0.98,95%CI=0.95-1.01;VD:OR=1.02,95%CI=0.97-1.07).In addition,genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia.Conclusion Our study did not provide genetic evidence for a causal association between IBD and dementia risk.The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.
文摘The feasibility of using a problem-dependent method to solve systems of second order ODEs is corroborated by an eigen-based theory and a methodology to develop such a numerical method is constructed.The key steps of this methodology are to decouple a system of ODEs of second order into a set of uncoupled ODEs of second order;next,an eigen-dependent method is proposed to approximate the solution of each uncoupled ODE of second order.It is vital to transform all eigen-dependent methods to a problem-dependent method to bypass an Eigen analysis.The development of an eigen-dependent method plays a key role in this methodology so that slow eigenmodes can be accurately integrated while there is no instability or excessive amplitude growth in fast eigenmodes.This can explain why a problem-dependent method can simultaneously combine the explicitness of each step and A-stability.Consequently,huge computational efforts can be saved for solving nonlinear stiff problems.A new family of problem-dependent methods is developed in this work so that the feasibility of the proposed methodology can be affirmed.It has almost the same performance as that of the HHT-αmethod.However,it can save more than 99.5%of CPU demand in approximating a solution for a system of 1000 nonlinear second order ODEs.
