Multiple Sclerosis（MS） is a major cause of neurological disability in adults and has an annual cost of approximately $28 billion in the United States. MS is a very complex disorder as demyelination can happen in a v...Multiple Sclerosis（MS） is a major cause of neurological disability in adults and has an annual cost of approximately $28 billion in the United States. MS is a very complex disorder as demyelination can happen in a variety of locations throughout the brain; therefore, this disease is never the same in two patients making it very hard to predict disease progression. A modeling approach which combines clinical, biological and imaging measures to help treat and fight this disorder is needed. In this paper, I will outline MS as a very heterogeneous disorder, review some potential solutions from the literature, demonstrate the need for a biomarker and will discuss how computational modeling combined with biological, clinical and imaging data can help link disparate observations and decipher complex mechanisms whose solutions are not amenable to simple reductionism.展开更多
Multiple wave is one of the important factors affecting the signal-to-noise ratio of marine seismic data.The model-driven-method(MDM)can effectively predict and suppress water-related multiple waves,while the quality ...Multiple wave is one of the important factors affecting the signal-to-noise ratio of marine seismic data.The model-driven-method(MDM)can effectively predict and suppress water-related multiple waves,while the quality of the multiple wave contribution gathers(MCG)can affect the prediction accuracy of multiple waves.Based on the compressed sensing framework,this study used the sparse constraint under LO norm to optimize MCG,which can not only reduce the false in the prediction and improve the image accuracy,but also saves computing time.At the same time,the MDM-type method for multiple wave suppression can be improved.The unified prediction of multiple types of water-related multiple waves weakens the dependence of conventional MDM on the adaptive subtraction process in suppressing water-related multiple waves,improves the stability of the method,and simultaneously,reduces the computational load.Finally,both theoretical model and practical data prove the effectiveness of the present method.展开更多
In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community ca...In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.展开更多
Soil mineralized nitrogen(N)is a vital component of soil N supply capacity and an important N source for rice growth.Unveiling N mineralization(Nm)process characteristics and developing a simple and effective approach...Soil mineralized nitrogen(N)is a vital component of soil N supply capacity and an important N source for rice growth.Unveiling N mineralization(Nm)process characteristics and developing a simple and effective approach to evaluate soil Nm are imperative to guide N fertilizer application and enhance its efficiency in various paddy soils with different physicochemical properties.Soil properties are important driving factors contributing to soil Nm differences and must be considered to achieve effective N management.Nevertheless,discrepancies in Nm capacity and other key influencing factors remain uncertain.To address this knowledge gap,this study collected 52 paddy soil samples from Taihu Lake Basin,China,which possess vastly different physicochemical properties.The samples were subjected to a 112-d submerged anaerobic incubation experiment at a constant temperature to obtain the soil Nm characteristics.Reaction kinetics models,including one-pool exponential model,two-pool exponential model,and effective cumulative temperature model,were employed to compare characteristic differences between Nm potential(Nmp)and short-term accumulated mineralized N(Amn)processes in relation to soil physicochemical properties.Based on these relationships,simplified Nmp prediction methods for paddy soils were established.The results revealed that the Nmp values were 145.18,88.64,and 21.03 mg kg-1 in paddy soils with pH<6.50,6.50≤pH≤7.50,and pH>7.50,respectively.Significantly,short-term Amn at day 14 showed a good correlation(P<0.01)with Nmp(R2=0.94),indicating that the prevailing short-term incubation experiment is an acceptable marker for Nmp.Moreover,Nmp correlated well with the ultraviolet absorbance value at 260 nm based on NaHCO3 extraction(Na260),further streamlining the Nmp estimation method.The incorporation of easily obtainable soil properties,including pH,total N(TN),and the ratio of total organic carbon to TN(C/N),alongside Na260 for Nmp evaluation allowed the multiple regression model,Nmp=58.62×TN-23.18×pH+13.08×C/N+86.96×Na260,to achieve a high prediction accuracy(R2=0.95).The reliability of this prediction was further validated with published data of paddy soils in the same region and other rice regions,demonstrating the regional applicability and prospects of this model.This study underscored the roles of soil properties in Nm characteristics and mechanisms and established a site-specific prediction model based on rapid extractions and edaphic properties of paddy soils,paving the way for developing rapid and precise Nm prediction models.展开更多
The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the pre...The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.展开更多
A novel method is presented to evaluate the complicated fatigue behavior of gears made of20Cr2Ni4 A.Fatigue tests are conducted in a high-frequency push-pull fatigue tester,and acoustic emission（AE）technique is used...A novel method is presented to evaluate the complicated fatigue behavior of gears made of20Cr2Ni4 A.Fatigue tests are conducted in a high-frequency push-pull fatigue tester,and acoustic emission（AE）technique is used to acquire metal fatigue signals.After analyzing large number of AE frequency spectrum,we find that：the crack extension can be expressed as the energy of specific frequency band,which is abbreviated as F-energy.To further validate the fatigue behavior,some correlation analysis is applied between F-energy and some AE parameters.Experimental results show that there is significant correlation among the Fenergy,root mean square（RMS）,relative energy,and hits.The findings can be used to validate the effectiveness of the F-energy in predicting fatigue crack propagation and remaining life for parts in-service.F-energy,as a new AE parameter,is first put forward in the area of fatigue crack growth.展开更多
An approach of stochastically statistical mechanics and a unified molecular theory of nonlinear viscoelasticity with constraints of Nagai chain entanglement for polymer melts have been proposed. A multimode model stru...An approach of stochastically statistical mechanics and a unified molecular theory of nonlinear viscoelasticity with constraints of Nagai chain entanglement for polymer melts have been proposed. A multimode model structure for a single polymer chain with n tail segments and N reversible entanglement sites on the test polymer chain is developed. Based on the above model structure and the mechanism of molecular flow by the dynamical reorganization of entanglement sites, the probability distribution function of the end-to-end vectr for a single polymer chain at entangled state and the viscoelastic free energy of deformation for polymer melts are calculated by using the method of the stochastically statistical mechanics. The four types of stress-strain relation and the memory function are derived from this thery. The above theoretical relations are verified by the experimentaf data for various polymer melts. These relations are found to be in good agreement with the experimental results展开更多
In order to overcome the shortcomings of the previous obstacle avoidance algorithms,an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed.The minimum prediction distance between obstacle...In order to overcome the shortcomings of the previous obstacle avoidance algorithms,an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed.The minimum prediction distance between obstacles and a manipulator was obtained according to the states of obstacles and transformed to escape velocity of the corresponding link of the manipulator.The escape velocity was introduced to the gradient projection method to obtain the joint velocity of the manipulator so as to complete the obstacle avoidance trajectory planning.A7-DOF manipulator was used in the simulation,and the results verified the effectiveness of the algorithm.展开更多
It is shown theoretically that the viscoelasticity of polymer melts is determined by three combining factorst they are the primary molecular weight and its distribution, the number of entanglement sites on polymer cha...It is shown theoretically that the viscoelasticity of polymer melts is determined by three combining factorst they are the primary molecular weight and its distribution, the number of entanglement sites on polymer chain and the sequence distribution of constituent chains in entanglement spacings. A unified quantity for the three combing factors is the average constrained dimensional number of constituent chains in the long entanglement spacings (v). A new relation of v to the primary molecular weight and the number of testing polymers were derived from the multiple entanglement and reptation model, and a new method for determining v was proposed. The dependences of linear viscoelastic functions on the primary molecular weight and its distribution were derived by the statistical method. When Mn=6Me to 18 Me, the values of (v) can range from 3.33 to 3.70. Their values are in a good agreement with the experiment data, and it can slightjy vary with the different species of polymers and the different ranges of molecular weight of polymers展开更多
This work is to develop a blending-based multiple model adaptive explicit predictive control scheme for nonlinear MiMo systems that can handle parametric uncertainties.Here,for each identification model,an explicit no...This work is to develop a blending-based multiple model adaptive explicit predictive control scheme for nonlinear MiMo systems that can handle parametric uncertainties.Here,for each identification model,an explicit nonlinear model predictive control(ENMPC)law is computed in advance for the corresponding model.The generated control inputs from the set of ENMPC controllers are being blended online using a weighting vector that is continuously updated by the proposed adaptive identification schemes.The proposed control scheme is used to govern the tracking of a highly nonlinear helicopter model known as the twin rotor MIMO system(TRMS).Here,an extended Kalman filter(EKF)is used to estimate the unavailable states of the TRMS.Finally,simulation and experimental results are presented to prove that the proposed controller gives better performance than some reported works in the literature.The effectiveness of the proposed controller is demonstrated by experimental studies of the TRMS model.展开更多
文摘Multiple Sclerosis（MS） is a major cause of neurological disability in adults and has an annual cost of approximately $28 billion in the United States. MS is a very complex disorder as demyelination can happen in a variety of locations throughout the brain; therefore, this disease is never the same in two patients making it very hard to predict disease progression. A modeling approach which combines clinical, biological and imaging measures to help treat and fight this disorder is needed. In this paper, I will outline MS as a very heterogeneous disorder, review some potential solutions from the literature, demonstrate the need for a biomarker and will discuss how computational modeling combined with biological, clinical and imaging data can help link disparate observations and decipher complex mechanisms whose solutions are not amenable to simple reductionism.
基金supported by the National Natural Science Foundation of China(No.41504102)the High-level Talents Initiation Project of North China University of Water Resources and Electric Power(No.40438)
文摘Multiple wave is one of the important factors affecting the signal-to-noise ratio of marine seismic data.The model-driven-method(MDM)can effectively predict and suppress water-related multiple waves,while the quality of the multiple wave contribution gathers(MCG)can affect the prediction accuracy of multiple waves.Based on the compressed sensing framework,this study used the sparse constraint under LO norm to optimize MCG,which can not only reduce the false in the prediction and improve the image accuracy,but also saves computing time.At the same time,the MDM-type method for multiple wave suppression can be improved.The unified prediction of multiple types of water-related multiple waves weakens the dependence of conventional MDM on the adaptive subtraction process in suppressing water-related multiple waves,improves the stability of the method,and simultaneously,reduces the computational load.Finally,both theoretical model and practical data prove the effectiveness of the present method.
文摘In a prior practice and policy article published in Healthcare Science,we introduced the deployed application of an artificial intelligence(AI)model to predict longer‐term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home(H2H)program that has been operating since 2017.In this follow on practice and policy article,we further elaborate on Singapore's H2H program and care model,and its supporting AI model for multiple readmission prediction,in the following ways:(1)by providing updates on the AI and supporting information systems,(2)by reporting on customer engagement and related service delivery outcomes including staff‐related time savings and patient benefits in terms of bed days saved,(3)by sharing lessons learned with respect to(i)analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants,(ii)balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables,and(iii)the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems,(4)by highlighting how this H2H effort supported broader Covid‐19 response efforts across Singapore's public healthcare system,and finally(5)by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards.For the convenience of the reader,some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.
基金supported by the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.Y201956)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2023QNRC001)the National Key Research and Development Program of China(No.2017YFD200104).
文摘Soil mineralized nitrogen(N)is a vital component of soil N supply capacity and an important N source for rice growth.Unveiling N mineralization(Nm)process characteristics and developing a simple and effective approach to evaluate soil Nm are imperative to guide N fertilizer application and enhance its efficiency in various paddy soils with different physicochemical properties.Soil properties are important driving factors contributing to soil Nm differences and must be considered to achieve effective N management.Nevertheless,discrepancies in Nm capacity and other key influencing factors remain uncertain.To address this knowledge gap,this study collected 52 paddy soil samples from Taihu Lake Basin,China,which possess vastly different physicochemical properties.The samples were subjected to a 112-d submerged anaerobic incubation experiment at a constant temperature to obtain the soil Nm characteristics.Reaction kinetics models,including one-pool exponential model,two-pool exponential model,and effective cumulative temperature model,were employed to compare characteristic differences between Nm potential(Nmp)and short-term accumulated mineralized N(Amn)processes in relation to soil physicochemical properties.Based on these relationships,simplified Nmp prediction methods for paddy soils were established.The results revealed that the Nmp values were 145.18,88.64,and 21.03 mg kg-1 in paddy soils with pH<6.50,6.50≤pH≤7.50,and pH>7.50,respectively.Significantly,short-term Amn at day 14 showed a good correlation(P<0.01)with Nmp(R2=0.94),indicating that the prevailing short-term incubation experiment is an acceptable marker for Nmp.Moreover,Nmp correlated well with the ultraviolet absorbance value at 260 nm based on NaHCO3 extraction(Na260),further streamlining the Nmp estimation method.The incorporation of easily obtainable soil properties,including pH,total N(TN),and the ratio of total organic carbon to TN(C/N),alongside Na260 for Nmp evaluation allowed the multiple regression model,Nmp=58.62×TN-23.18×pH+13.08×C/N+86.96×Na260,to achieve a high prediction accuracy(R2=0.95).The reliability of this prediction was further validated with published data of paddy soils in the same region and other rice regions,demonstrating the regional applicability and prospects of this model.This study underscored the roles of soil properties in Nm characteristics and mechanisms and established a site-specific prediction model based on rapid extractions and edaphic properties of paddy soils,paving the way for developing rapid and precise Nm prediction models.
基金support of the National Natural Science Fundation of China (Nos. 41574105 and 41674118)the National Science and Technology Major Project of China (No. 2016ZX05027-002)the Scientific and Technological Innovation Project financially supported by Qingdao National Laboratory for Marine Science and Technology (No. 2015ASKJ03)
文摘The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.
基金Supported by the National Natural Science Foundation of China(50975030)
文摘A novel method is presented to evaluate the complicated fatigue behavior of gears made of20Cr2Ni4 A.Fatigue tests are conducted in a high-frequency push-pull fatigue tester,and acoustic emission（AE）technique is used to acquire metal fatigue signals.After analyzing large number of AE frequency spectrum,we find that：the crack extension can be expressed as the energy of specific frequency band,which is abbreviated as F-energy.To further validate the fatigue behavior,some correlation analysis is applied between F-energy and some AE parameters.Experimental results show that there is significant correlation among the Fenergy,root mean square（RMS）,relative energy,and hits.The findings can be used to validate the effectiveness of the F-energy in predicting fatigue crack propagation and remaining life for parts in-service.F-energy,as a new AE parameter,is first put forward in the area of fatigue crack growth.
文摘An approach of stochastically statistical mechanics and a unified molecular theory of nonlinear viscoelasticity with constraints of Nagai chain entanglement for polymer melts have been proposed. A multimode model structure for a single polymer chain with n tail segments and N reversible entanglement sites on the test polymer chain is developed. Based on the above model structure and the mechanism of molecular flow by the dynamical reorganization of entanglement sites, the probability distribution function of the end-to-end vectr for a single polymer chain at entangled state and the viscoelastic free energy of deformation for polymer melts are calculated by using the method of the stochastically statistical mechanics. The four types of stress-strain relation and the memory function are derived from this thery. The above theoretical relations are verified by the experimentaf data for various polymer melts. These relations are found to be in good agreement with the experimental results
基金Supported by Ministeral Level Advanced Research Foundation(65822576)Beijing Municipal Education Commission(KM201310858004,KM201310858001)
文摘In order to overcome the shortcomings of the previous obstacle avoidance algorithms,an obstacle avoidance algorithm applicable to multiple mobile obstacles was proposed.The minimum prediction distance between obstacles and a manipulator was obtained according to the states of obstacles and transformed to escape velocity of the corresponding link of the manipulator.The escape velocity was introduced to the gradient projection method to obtain the joint velocity of the manipulator so as to complete the obstacle avoidance trajectory planning.A7-DOF manipulator was used in the simulation,and the results verified the effectiveness of the algorithm.
文摘It is shown theoretically that the viscoelasticity of polymer melts is determined by three combining factorst they are the primary molecular weight and its distribution, the number of entanglement sites on polymer chain and the sequence distribution of constituent chains in entanglement spacings. A unified quantity for the three combing factors is the average constrained dimensional number of constituent chains in the long entanglement spacings (v). A new relation of v to the primary molecular weight and the number of testing polymers were derived from the multiple entanglement and reptation model, and a new method for determining v was proposed. The dependences of linear viscoelastic functions on the primary molecular weight and its distribution were derived by the statistical method. When Mn=6Me to 18 Me, the values of (v) can range from 3.33 to 3.70. Their values are in a good agreement with the experiment data, and it can slightjy vary with the different species of polymers and the different ranges of molecular weight of polymers
文摘This work is to develop a blending-based multiple model adaptive explicit predictive control scheme for nonlinear MiMo systems that can handle parametric uncertainties.Here,for each identification model,an explicit nonlinear model predictive control(ENMPC)law is computed in advance for the corresponding model.The generated control inputs from the set of ENMPC controllers are being blended online using a weighting vector that is continuously updated by the proposed adaptive identification schemes.The proposed control scheme is used to govern the tracking of a highly nonlinear helicopter model known as the twin rotor MIMO system(TRMS).Here,an extended Kalman filter(EKF)is used to estimate the unavailable states of the TRMS.Finally,simulation and experimental results are presented to prove that the proposed controller gives better performance than some reported works in the literature.The effectiveness of the proposed controller is demonstrated by experimental studies of the TRMS model.
