Oxidative stress has been associated with a number of physiological problems in swine,including reduced production efficiency.Recently,although there has been increased research into regulatory mechanisms and antioxid...Oxidative stress has been associated with a number of physiological problems in swine,including reduced production efficiency.Recently,although there has been increased research into regulatory mechanisms and antioxidant strategies in relation to oxidative stress-induced pig production,it remains so far largely unsuccessful to develop accurate models and nutritional strategies for specific oxidative stress factors.Here,we discuss the dose and dose intensity of the causes of oxidative stress involving physiological,environmental and dietary factors,recent research models and the antioxidant strategies to provide theoretical guidance for future oxidative stress research in swine.展开更多
The exploration of Mars would heavily rely on Martian rocks mechanics and engineering technology.As the mechanical property of Martian rocks is uncertain,it is of utmost importance to predict the probability distribut...The exploration of Mars would heavily rely on Martian rocks mechanics and engineering technology.As the mechanical property of Martian rocks is uncertain,it is of utmost importance to predict the probability distribution of Martian rocks mechanical property for the success of Mars exploration.In this paper,a fast and accurate probability distribution method for predicting the macroscale elastic modulus of Martian rocks was proposed by integrating the microscale rock mechanical experiments(micro-RME),accurate grain-based modeling(AGBM)and upscaling methods based on reliability principles.Firstly,the microstructure of NWA12564 Martian sample and elastic modulus of each mineral were obtained by micro-RME with TESCAN integrated mineral analyzer(TIMA)and nanoindentation.The best probability distribution function of the minerals was determined by Kolmogorov-Smirnov(K-S)test.Secondly,based on best distribution function of each mineral,the Monte Carlo simulations(MCS)and upscaling methods were implemented to obtain the probability distribution of upscaled elastic modulus.Thirdly,the correlation between the upscaled elastic modulus and macroscale elastic modulus obtained by AGBM was established.The accurate probability distribution of the macroscale elastic modulus was obtained by this correlation relationship.The proposed method can predict the probability distribution of Martian rocks mechanical property with any size and shape samples.展开更多
As the core component of energy conversion for large wind turbines,the output performance of doubly-fed induction generators (DFIGs) plays a decisive role in the power quality of wind turbines.To realize the fast and ...As the core component of energy conversion for large wind turbines,the output performance of doubly-fed induction generators (DFIGs) plays a decisive role in the power quality of wind turbines.To realize the fast and accurate design optimization of DFIGs,this paper proposes a novel hybriddriven surrogate-assisted optimization method.It firstly establishes an accurate subdomain model of DFIGs to analytically predict performance indexes.Furthermore,taking the inexpensive analytical dataset produced by the subdomain model as the source domain and the expensive finite element analysis dataset as the target domain,a high-precision surrogate model is trained in a transfer learning way and used for the subsequent multi-objective optimization process.Based on this model,taking the total harmonic distortion of electromotive force,cogging torque,and iron loss as objectives,and the slot and inner/outer diameters as parameters for optimizing the topology,achieve a rapid and accurate electromagnetic design for DFIGs.Finally,experiments are carried out on a 3MW DFIG to validate the effectiveness of the proposed method.展开更多
Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly ...Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly optimized topologies.But the key problems arise:how to compress a network to best enhance its compactness,and what the compression limit of the network reflects?We abstract the topological compression of complex networks as a dynamic process of making them more compact and propose the local compression modulus that plays a key role in effective compression evolution of networks.Subsequently,we identify topological compressibility-a general property of complex networks that characterizes the extent to which a network can be compressed-and provide its approximate quantification.We anticipate that our findings and established theory will provide valuable insights into both dynamics and various applications of complex networks.展开更多
Recently,an approach for the rapid detection of small oscillation faults based on deterministic learning theory was proposed for continuous-time systems.In this paper,a fault detection scheme is proposed for a class o...Recently,an approach for the rapid detection of small oscillation faults based on deterministic learning theory was proposed for continuous-time systems.In this paper,a fault detection scheme is proposed for a class of nonlinear discrete-time systems via deterministic learning.By using a discrete-time extension of deterministic learning algorithm,the general fault functions(i.e.,the internal dynamics)underlying normal and fault modes of nonlinear discrete-time systems are locally-accurately approximated by discrete-time dynamical radial basis function(RBF)networks.Then,a bank of estimators with the obtained knowledge of system dynamics embedded is constructed,and a set of residuals are obtained and used to measure the differences between the dynamics of the monitored system and the dynamics of the trained systems.A fault detection decision scheme is presented according to the smallest residual principle,i.e.,the occurrence of a fault can be detected in a discrete-time setting by comparing the magnitude of residuals.The fault detectability analysis is carried out and the upper bound of detection time is derived.A simulation example is given to illustrate the effectiveness of the proposed scheme.展开更多
Conventional fractional slot concentrated winding three-phase axial flux permanent magnet machines have an abundance of armature reaction magnetic field harmonics which deteriorate the torque performance of the machin...Conventional fractional slot concentrated winding three-phase axial flux permanent magnet machines have an abundance of armature reaction magnetic field harmonics which deteriorate the torque performance of the machine.This paper presents a double-stator dislocated axial flux permanent magnet machine with combined wye-delta winding.A wye-delta(Y-△)winding connection method is designed to eliminate the 6 th ripple torque generated by air gap magnetic field harmonics.Then,the accurate subdomain method is adopted to acquire the no-load and armature magnetic fields of the machine,respectively,and the magnetic field harmonics and torque performance of the designed machine are analyzed.Finally,a 6 k W,4000 r/min,18-slot/16-pole axial flux permanent magnet machine is designed.The finite element simulation results show that the proposed machine can effectively eliminate the 6 th ripple torque and greatly reduce the torque ripple while the average torque is essentially identical to that of the conventional three-phase machines with wye-winding connection.展开更多
We investigate theoretically the ionization properties of the valence electron for the alkali metal atom Na in an intense pulsed laser field by solving numerically the time-dependent Schrodinger equation with an accur...We investigate theoretically the ionization properties of the valence electron for the alkali metal atom Na in an intense pulsed laser field by solving numerically the time-dependent Schrodinger equation with an accurate l-dependent model potential.By calculating the variations of the ionization probabilities with laser peak intensity for wavelengths ranging from 200 nm to 600 nm,our results present a dynamic stabilization trend for the Na atom initially in its ground state（3 s） and the excited states（3 p and 4 s） exposed to an intense pulsed laser field.Especially a clear ＂window＂ of dynamic stabilization at lower laser intensities and longer wavelengths for the initial state 4 s（the second excited state） is found.By analyzing the time-dependent population distributions of the valence electron in the bound states with the different values of principal quantum number n and orbital quantum number l,we can attribute the dynamic stabilization to the periodic population in the low-excited states since the valence electron oscillates rapidly between the lowly excited states and the continuum states.展开更多
Organic electrochemical transistors(OECTs)combine electron/ionic transport with organic semiconductor flexibility to connect biology and electronics.As they approach industrial use,optimizing performance requires accu...Organic electrochemical transistors(OECTs)combine electron/ionic transport with organic semiconductor flexibility to connect biology and electronics.As they approach industrial use,optimizing performance requires accurate modeling of their structure.This study presents a twodimensional(2D)OECT model based on Nernst-Planck-Poisson equations that explicitly includes volumetric capacitance(CV).Unlike previous models that ignore CV,our model highlights its essential role in OECT operation,allowing us to accurately match the measured output currents of PEDOT:PSS printed OECTs.We studied how parameters like diffusion coefficients of holes and ions,fixed anion concentration,and intrinsic capacitance affect transistor performance.We analyze existing OECT models,noting that different frameworks,despite varying assumptions,can reproduce data.This question relies solely on experimental agreement for validation.We argue that models should also be evaluated on their physical principles.To assist readers,we provide COMSOL.mph files for 1D and 2D OECT models for device design and optimization.展开更多
Accurate and adaptive models of a robot's morphology and kinematics are crucial for reliable planning,precise control,and seamless interaction within dynamic environments.Traditional modeling approaches demand sub...Accurate and adaptive models of a robot's morphology and kinematics are crucial for reliable planning,precise control,and seamless interaction within dynamic environments.Traditional modeling approaches demand substantial human intervention and are prone to degradation over time because of factors such as unforeseen damage or wear.Recent research has increasingly focused on task‐agnostic data‐driven self‐modeling methods,which enhance the robot's ability to operate flexibly across various contexts and tasks.This paper proposes a novel self‐modeling framework that leverages neural radiance fields(NeRF)for partlevel reconstruction and aims to provide both the morphology self‐model and the kinematic self‐model.The framework enables robots to predict their pose at different joint configurations.With the self‐model built by our framework,the robot can generate trajectories by itself to accomplish simple tasks or solve inverse kinematic problems.展开更多
The fatigue resistance and wear performance of aviation gears under extreme conditions(e.g.,high speed and heavy load)are closely related to tooth surface topography.Establishing an accurate correlation between surfac...The fatigue resistance and wear performance of aviation gears under extreme conditions(e.g.,high speed and heavy load)are closely related to tooth surface topography.Establishing an accurate correlation between surface topography and service performance requires numerous topography samples.Grinding-shot peening(GSP)combined processes are the key processes for manufacturing aviation gears.展开更多
The idea of accurately modeling life within a computer is no longer science fiction;it is becoming a reality through the rise of the virtual cell.Over the past few years,fueled by advances in single-cell and spatial o...The idea of accurately modeling life within a computer is no longer science fiction;it is becoming a reality through the rise of the virtual cell.Over the past few years,fueled by advances in single-cell and spatial omics,artificial intelligence(AI),and high-performance computing,virtual cells have rapidly evolved from abstract concepts into practical tools with the power to reshape biomedical research.Building on earlier,more constrained attempts at integration,today’s virtual cells can merge diverse data streams with sophisticated computational models,enabling comprehensive simulations of cellular structure,function,and behavior.1,2 In doing so,they provide an unprecedented platform for reconstructing and manipulating life and open transformative opportunities for intelligent oncology.The core technical framework,data foundations,and key potential application areas of virtual cells in intelligent oncology are illustrated in Figure 1.展开更多
Security-constrained unit commitment(SCUC)has been extensively studied as a key decision-making tool to determine optimal power generation schedules in the operation of electricity market.With the development of emerg...Security-constrained unit commitment(SCUC)has been extensively studied as a key decision-making tool to determine optimal power generation schedules in the operation of electricity market.With the development of emerging power grids,fruitful research results on SCUC have been obtained.Therefore,it is essential to review current work and propose future directions for SCUC to meet the needs of developing power systems.In this paper,the basic mathematical model of the standard SCUC is summarized,and the characteristics and application scopes of common solution algorithms are presented.Customized models focusing on diverse mathematical properties are then categorized and the corresponding solving methodologies are discussed.Finally,research trends in the field are prospected based on a summary of the state-of-the-art and latest studies.It is hoped that this paper can be a useful reference to support theoretical research and practical applications of SCUC in the future.展开更多
基金supported by Guangzhou Science and Technology Planning Project(2023A04J0131)Special fund for scientific innovation strategyconstruction of high level Academy of Agriculture Science(R2020PY-JG009,R2022PY-QY007,202106TD)+2 种基金China Agriculture Research System-CARS-35the Project of Swine Innovation Team in Guangdong Modern Agricultural Research System(2022KJ126)Special Fund for Rural Revitalization Strategy of Guangdong(2023TS-3),China。
文摘Oxidative stress has been associated with a number of physiological problems in swine,including reduced production efficiency.Recently,although there has been increased research into regulatory mechanisms and antioxidant strategies in relation to oxidative stress-induced pig production,it remains so far largely unsuccessful to develop accurate models and nutritional strategies for specific oxidative stress factors.Here,we discuss the dose and dose intensity of the causes of oxidative stress involving physiological,environmental and dietary factors,recent research models and the antioxidant strategies to provide theoretical guidance for future oxidative stress research in swine.
文摘The exploration of Mars would heavily rely on Martian rocks mechanics and engineering technology.As the mechanical property of Martian rocks is uncertain,it is of utmost importance to predict the probability distribution of Martian rocks mechanical property for the success of Mars exploration.In this paper,a fast and accurate probability distribution method for predicting the macroscale elastic modulus of Martian rocks was proposed by integrating the microscale rock mechanical experiments(micro-RME),accurate grain-based modeling(AGBM)and upscaling methods based on reliability principles.Firstly,the microstructure of NWA12564 Martian sample and elastic modulus of each mineral were obtained by micro-RME with TESCAN integrated mineral analyzer(TIMA)and nanoindentation.The best probability distribution function of the minerals was determined by Kolmogorov-Smirnov(K-S)test.Secondly,based on best distribution function of each mineral,the Monte Carlo simulations(MCS)and upscaling methods were implemented to obtain the probability distribution of upscaled elastic modulus.Thirdly,the correlation between the upscaled elastic modulus and macroscale elastic modulus obtained by AGBM was established.The accurate probability distribution of the macroscale elastic modulus was obtained by this correlation relationship.The proposed method can predict the probability distribution of Martian rocks mechanical property with any size and shape samples.
文摘As the core component of energy conversion for large wind turbines,the output performance of doubly-fed induction generators (DFIGs) plays a decisive role in the power quality of wind turbines.To realize the fast and accurate design optimization of DFIGs,this paper proposes a novel hybriddriven surrogate-assisted optimization method.It firstly establishes an accurate subdomain model of DFIGs to analytically predict performance indexes.Furthermore,taking the inexpensive analytical dataset produced by the subdomain model as the source domain and the expensive finite element analysis dataset as the target domain,a high-precision surrogate model is trained in a transfer learning way and used for the subsequent multi-objective optimization process.Based on this model,taking the total harmonic distortion of electromotive force,cogging torque,and iron loss as objectives,and the slot and inner/outer diameters as parameters for optimizing the topology,achieve a rapid and accurate electromagnetic design for DFIGs.Finally,experiments are carried out on a 3MW DFIG to validate the effectiveness of the proposed method.
基金supported inpart by the National Natural Science Foundation of China(Grant No. 12371088)the Innovative Research Group Project of Natural Science Foundation of Hunan Provinceof China (Grant No. 2024JJ1008)in part by the Australian Research Council (ARC) through the Discovery Projects scheme (Grant No. DP220100580)。
文摘Accurately modeling real network dynamics is a grand challenge in network science.The network dynamics arise from node interactions,which are shaped by network topology.Real networks tend to exhibit compact or highly optimized topologies.But the key problems arise:how to compress a network to best enhance its compactness,and what the compression limit of the network reflects?We abstract the topological compression of complex networks as a dynamic process of making them more compact and propose the local compression modulus that plays a key role in effective compression evolution of networks.Subsequently,we identify topological compressibility-a general property of complex networks that characterizes the extent to which a network can be compressed-and provide its approximate quantification.We anticipate that our findings and established theory will provide valuable insights into both dynamics and various applications of complex networks.
基金This work was supported by the National Science Fund for Distinguished Young Scholars(No.61225014)the National Major Scientific Instruments Development Project(No.61527811)+2 种基金the National Natural Science Foundation of China(Nos.61304084,61374119)the Guangdong Natural Science Foundation(No.2014A030312005)the Space Intelligent Control Key Laboratory of Science and Technology for National Defense.
文摘Recently,an approach for the rapid detection of small oscillation faults based on deterministic learning theory was proposed for continuous-time systems.In this paper,a fault detection scheme is proposed for a class of nonlinear discrete-time systems via deterministic learning.By using a discrete-time extension of deterministic learning algorithm,the general fault functions(i.e.,the internal dynamics)underlying normal and fault modes of nonlinear discrete-time systems are locally-accurately approximated by discrete-time dynamical radial basis function(RBF)networks.Then,a bank of estimators with the obtained knowledge of system dynamics embedded is constructed,and a set of residuals are obtained and used to measure the differences between the dynamics of the monitored system and the dynamics of the trained systems.A fault detection decision scheme is presented according to the smallest residual principle,i.e.,the occurrence of a fault can be detected in a discrete-time setting by comparing the magnitude of residuals.The fault detectability analysis is carried out and the upper bound of detection time is derived.A simulation example is given to illustrate the effectiveness of the proposed scheme.
基金supported in part by the National Natural Science Foundation of China Grant No.51877139。
文摘Conventional fractional slot concentrated winding three-phase axial flux permanent magnet machines have an abundance of armature reaction magnetic field harmonics which deteriorate the torque performance of the machine.This paper presents a double-stator dislocated axial flux permanent magnet machine with combined wye-delta winding.A wye-delta(Y-△)winding connection method is designed to eliminate the 6 th ripple torque generated by air gap magnetic field harmonics.Then,the accurate subdomain method is adopted to acquire the no-load and armature magnetic fields of the machine,respectively,and the magnetic field harmonics and torque performance of the designed machine are analyzed.Finally,a 6 k W,4000 r/min,18-slot/16-pole axial flux permanent magnet machine is designed.The finite element simulation results show that the proposed machine can effectively eliminate the 6 th ripple torque and greatly reduce the torque ripple while the average torque is essentially identical to that of the conventional three-phase machines with wye-winding connection.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11465016,11664035,and 11764038)
文摘We investigate theoretically the ionization properties of the valence electron for the alkali metal atom Na in an intense pulsed laser field by solving numerically the time-dependent Schrodinger equation with an accurate l-dependent model potential.By calculating the variations of the ionization probabilities with laser peak intensity for wavelengths ranging from 200 nm to 600 nm,our results present a dynamic stabilization trend for the Na atom initially in its ground state（3 s） and the excited states（3 p and 4 s） exposed to an intense pulsed laser field.Especially a clear ＂window＂ of dynamic stabilization at lower laser intensities and longer wavelengths for the initial state 4 s（the second excited state） is found.By analyzing the time-dependent population distributions of the valence electron in the bound states with the different values of principal quantum number n and orbital quantum number l,we can attribute the dynamic stabilization to the periodic population in the low-excited states since the valence electron oscillates rapidly between the lowly excited states and the continuum states.
基金support from Advanced Functional Materials at Linköping Universitysupport from Swedish research Council(2024-04449)+1 种基金from the Knut and Alice Wallenberg Foundation(KAW)through the Wallenberg Wood Science Center 3.0(KAW 2021.0313)provided by the National Academic Infrastructure for Supercomputing in Sweden(NAISS)at NSC and PDC.
文摘Organic electrochemical transistors(OECTs)combine electron/ionic transport with organic semiconductor flexibility to connect biology and electronics.As they approach industrial use,optimizing performance requires accurate modeling of their structure.This study presents a twodimensional(2D)OECT model based on Nernst-Planck-Poisson equations that explicitly includes volumetric capacitance(CV).Unlike previous models that ignore CV,our model highlights its essential role in OECT operation,allowing us to accurately match the measured output currents of PEDOT:PSS printed OECTs.We studied how parameters like diffusion coefficients of holes and ions,fixed anion concentration,and intrinsic capacitance affect transistor performance.We analyze existing OECT models,noting that different frameworks,despite varying assumptions,can reproduce data.This question relies solely on experimental agreement for validation.We argue that models should also be evaluated on their physical principles.To assist readers,we provide COMSOL.mph files for 1D and 2D OECT models for device design and optimization.
基金supported by National Natural Science Foundation of China(Grant 62173352).
文摘Accurate and adaptive models of a robot's morphology and kinematics are crucial for reliable planning,precise control,and seamless interaction within dynamic environments.Traditional modeling approaches demand substantial human intervention and are prone to degradation over time because of factors such as unforeseen damage or wear.Recent research has increasingly focused on task‐agnostic data‐driven self‐modeling methods,which enhance the robot's ability to operate flexibly across various contexts and tasks.This paper proposes a novel self‐modeling framework that leverages neural radiance fields(NeRF)for partlevel reconstruction and aims to provide both the morphology self‐model and the kinematic self‐model.The framework enables robots to predict their pose at different joint configurations.With the self‐model built by our framework,the robot can generate trajectories by itself to accomplish simple tasks or solve inverse kinematic problems.
基金supported by the National Natural Science Foundation of China(Grant No.U22B2086)。
文摘The fatigue resistance and wear performance of aviation gears under extreme conditions(e.g.,high speed and heavy load)are closely related to tooth surface topography.Establishing an accurate correlation between surface topography and service performance requires numerous topography samples.Grinding-shot peening(GSP)combined processes are the key processes for manufacturing aviation gears.
文摘The idea of accurately modeling life within a computer is no longer science fiction;it is becoming a reality through the rise of the virtual cell.Over the past few years,fueled by advances in single-cell and spatial omics,artificial intelligence(AI),and high-performance computing,virtual cells have rapidly evolved from abstract concepts into practical tools with the power to reshape biomedical research.Building on earlier,more constrained attempts at integration,today’s virtual cells can merge diverse data streams with sophisticated computational models,enabling comprehensive simulations of cellular structure,function,and behavior.1,2 In doing so,they provide an unprecedented platform for reconstructing and manipulating life and open transformative opportunities for intelligent oncology.The core technical framework,data foundations,and key potential application areas of virtual cells in intelligent oncology are illustrated in Figure 1.
基金supported in part by the National Natural Science Foundation of China(No.51607104)。
文摘Security-constrained unit commitment(SCUC)has been extensively studied as a key decision-making tool to determine optimal power generation schedules in the operation of electricity market.With the development of emerging power grids,fruitful research results on SCUC have been obtained.Therefore,it is essential to review current work and propose future directions for SCUC to meet the needs of developing power systems.In this paper,the basic mathematical model of the standard SCUC is summarized,and the characteristics and application scopes of common solution algorithms are presented.Customized models focusing on diverse mathematical properties are then categorized and the corresponding solving methodologies are discussed.Finally,research trends in the field are prospected based on a summary of the state-of-the-art and latest studies.It is hoped that this paper can be a useful reference to support theoretical research and practical applications of SCUC in the future.
