As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosys...As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosystem security.This study employs a coupled PLUS-InVEST modeling framework to analyze land-use changes and habitat quality dynamics from 2000 to 2020,projecting ecological outcomes under three development scenarios for 2030.Key findings reveal:(1)A persistent bimodal habitat distribution pattern,with high-quality areas concentrated in the central forest zone and degraded areas in coastal peripheries,exhibiting a continuous decline over the 20-year period.(2)Accelerated urbanization between 2010 and 2020 resulted in the conversion of ecological land to construction use,correlating strongly with habitat fragmentation intensity.(3)Baseline projections for 2030 indicate that construction land will dominate new conversions.(4)Ecological protection scenarios demonstrate recoverable habitat potentials,particularly within coastal buffer zones.These findings provide empirical validation of scenario-driven land-use planning as a viable tool for island ecosystems,highlighting the critical need to balance tourism infrastructure development with coastal conservation imperatives in tropical island sustainability management.This methodology advances spatial decision-making for balancing island economic growth with biodiversity preservation,offering replicable strategies for global island ecosystems facing similar sustainability challenges.展开更多
Nitrogen(N)and phosphorus(P)are mineral nutrients essential for plant growth and development,playing a crucial role throughout the plant life cycle.Cotton,a globally significant textile crop,has a particularly high de...Nitrogen(N)and phosphorus(P)are mineral nutrients essential for plant growth and development,playing a crucial role throughout the plant life cycle.Cotton,a globally significant textile crop,has a particularly high demand for N fertilizer across its developmental stages.This review explores the effects of adequate or deficient N and P levels on cotton growth phases,focusing on their influence on physiological processes and molecular mechanisms.Key topics include the regulation of N-and P-related enzymes,hormones,and genes,as well as the complex interplay of N-and P-related signaling pathways from the aspects of N-P signaling integration to regulate root development,N-P signaling integration to regulate nutrient uptake,and regulation of N-P interactions—a frontier in current research.Strategies for improving N and P use efficiency are also discussed,including developing high-efficiency cotton cultivars and identifying functional genes to enhance productivity.Generally speaking,we take model plants as a reference in the hope of coming up with new strategies for the efficient utilization of N and P in cotton.展开更多
Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the fail...Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.展开更多
The value range of the failure threshold will generate an uncertain influence on the prediction results for the remaining useful life(RUL) of equipment. Most of the existing studies on the RUL prediction assume that t...The value range of the failure threshold will generate an uncertain influence on the prediction results for the remaining useful life(RUL) of equipment. Most of the existing studies on the RUL prediction assume that the failure threshold is a fixed value,as they have difficulty in reflecting the random variation of the failure threshold. In connection with the inadequacies of the existing research, an in-depth analysis is carried out to study the effect of the random failure threshold(RFT) on the prediction results for the RUL. First, a nonlinear degradation model with unit-to-unit variability and measurement error is established based on the nonlinear Wiener process. Second, the expectation-maximization(EM) algorithm is used to solve the estimated values of the parameters of the prior degradation model, and the Bayesian method is used to iteratively update the posterior distribution of the random coefficients. Then, the effects of three types of RFT constraint conditions on the prediction results for the RUL are analyzed, and the probability density function(PDF) of the RUL is derived. Finally,the degradation data of aero-turbofan engines are used to verify the correctness and advantages of the method.展开更多
Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics.These features have an uncertain effect on the remaining useful life(RUL)prediction of the equipmen...Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics.These features have an uncertain effect on the remaining useful life(RUL)prediction of the equipment.The current data-driven RUL prediction method has not systematically studied the nonlinear hidden degradation modeling and the RUL distribution function.This paper uses the nonlinear Wiener process to build a dual nonlinear implicit degradation model.Based on the historical measured data of similar equipment,the maximum likelihood estimation algorithm is used to estimate the fixed coefficients and the prior distribution of a random coefficient.Using the on-site measured data of the target equipment,the posterior distribution of a random coefficient and actual degradation state are step-by-step updated based on Bayesian inference and the extended Kalman filtering algorithm.The analytical form of the RUL distribution function is derived based on the first hitting time distribution.Combined with the two case studies,the proposed method is verified to have certain advantages over the existing methods in the accuracy of prediction.展开更多
Six-year old apple trees were selected for field experiment.The objective of this study was to obtain the reasonable arrangement of surge-root irrigation emitters in apple orchards.There were three factors:the buried ...Six-year old apple trees were selected for field experiment.The objective of this study was to obtain the reasonable arrangement of surge-root irrigation emitters in apple orchards.There were three factors:the buried depth H(25,40,55 cm),the horizontal distance L(30,40,60 cm)between the emitters and the trunk of the experimental tree,and the number of the irrigation emitters N(1,2,4).The effect of the arrangement of surge-root irrigation emitters on the growth,yield and irrigation water use efficiency(IWUE)of apple trees were studied in Northern Shaanxi where the irrigation quota takes 60%-75%of the field water capacity.The results showed that the arrangement of emitters for surge-root irrigation had a significant effect on apple tree yield and IWUE,especially,the yield and IWUE reached 28388.17 kg/hm2 and 16.83 kg/m3 in treatment T3,respectively.At the same L and N levels(T1,T2,and T3),the yield and IWUE in treatment T3 were the highest,and the yields in treatments T1 and T2 were decreased by 26.22%and 31.48%,while IWUE is reduced by14.02%and 18.12%compared with T3,respectively.At the same H and N levels(T3,T4,and T5),the yield and IWUE of apple trees were decreased with increasing L level.Especially,when L was 30 cm(T3),the yield and IWUE were the highest.The same L and H levels(T3,T6,and T7)could promote the growth of apple trees when N was 2(T3).Compared with treatment T3,it was found that the increment of new shoots was decreased by 8.07%-18.71%,and the fruit diameter was decreased by 5.41%-9.11%.Therefore,two emitters should be arranged symmetrically on both sides of an apple tree,each was buried at a 40 cm depth and 30 cm away from the trunk of the tree to effectively improve the yield and IWUE of the apple tree in mountainous areas in Northern Shaanxi.展开更多
The application of nitrogen （N） fertilizers in agriculture has been increasing dramatically since 1970s. However, the over-fertilization causes could cause environmental problems, as well as low N use efficiency （...The application of nitrogen （N） fertilizers in agriculture has been increasing dramatically since 1970s. However, the over-fertilization causes could cause environmental problems, as well as low N use efficiency （NUE）. Promoting NUE in plants and minimizing the environmental impacts of N fertilizers had been the focus of the current research. We reviewed the importance of N, N metabolism and plant growth, plant N physiology and the molecular aspect of N metabolism in this paper. The future development of N use and NUE of plants was also discussed.展开更多
Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a n...Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction.展开更多
A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work...A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work modes, system configuration, dynamic probabilities and degeneration of components,as well as spacecraft dynamics and kinematics. By introducing the frame of DFT, the system is classified into several layers, and the problem of state combination explosion is artfully overcome.An improved dynamic reliability model(DRM) based on the Nelson hypothesis is investigated to improve the defect of cumulative failure probability(CFP), which is used to address the failure probability of components in the SHA model. The simulation using the Monte-Carlo method is finally conducted on two satellites, which are deployed with the same multi-gyro subsystem but run on different orbits. The results show that the predicted useful life of the attitude control system(ACS) with consideration of abrupt failure,degradation, and running environment is quite different between the two satellites.展开更多
An adaptive neuro-fuzzy inference system(ANFIS) for predicting the performance of a reversibly used cooling tower(RUCT) under cross flow conditions as part of a heat pump system for a heating mode in winter was demons...An adaptive neuro-fuzzy inference system(ANFIS) for predicting the performance of a reversibly used cooling tower(RUCT) under cross flow conditions as part of a heat pump system for a heating mode in winter was demonstrated.Extensive field experimental work was carried out in order to gather enough data for training and prediction.The statistical methods,such as the correlation coefficient,absolute fraction of variance and root mean square error,were given to compare the predicted and actual values for model validation.The simulation results predicted with the ANFIS can be used to simulate the performance of a reversibly used cooling tower quite accurately.Therefore,the ANFIS approach can reliably be used for forecasting the performance of RUCT.展开更多
Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of th...Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.展开更多
基金National Science and Technology Basic Resources Investigation Program(2022FY101901-2)。
文摘As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosystem security.This study employs a coupled PLUS-InVEST modeling framework to analyze land-use changes and habitat quality dynamics from 2000 to 2020,projecting ecological outcomes under three development scenarios for 2030.Key findings reveal:(1)A persistent bimodal habitat distribution pattern,with high-quality areas concentrated in the central forest zone and degraded areas in coastal peripheries,exhibiting a continuous decline over the 20-year period.(2)Accelerated urbanization between 2010 and 2020 resulted in the conversion of ecological land to construction use,correlating strongly with habitat fragmentation intensity.(3)Baseline projections for 2030 indicate that construction land will dominate new conversions.(4)Ecological protection scenarios demonstrate recoverable habitat potentials,particularly within coastal buffer zones.These findings provide empirical validation of scenario-driven land-use planning as a viable tool for island ecosystems,highlighting the critical need to balance tourism infrastructure development with coastal conservation imperatives in tropical island sustainability management.This methodology advances spatial decision-making for balancing island economic growth with biodiversity preservation,offering replicable strategies for global island ecosystems facing similar sustainability challenges.
基金supported by Supported by National Key Laboratory of Cotton Bio-breeding and Integrated Utilization(CB2023C07)Xinjiang Autonomous Region"Three Agricultural"Backbone Talent Training Program(2022SNGGNT024)Xinjiang Huyanghe City Science and Technology Program(2023C08).
文摘Nitrogen(N)and phosphorus(P)are mineral nutrients essential for plant growth and development,playing a crucial role throughout the plant life cycle.Cotton,a globally significant textile crop,has a particularly high demand for N fertilizer across its developmental stages.This review explores the effects of adequate or deficient N and P levels on cotton growth phases,focusing on their influence on physiological processes and molecular mechanisms.Key topics include the regulation of N-and P-related enzymes,hormones,and genes,as well as the complex interplay of N-and P-related signaling pathways from the aspects of N-P signaling integration to regulate root development,N-P signaling integration to regulate nutrient uptake,and regulation of N-P interactions—a frontier in current research.Strategies for improving N and P use efficiency are also discussed,including developing high-efficiency cotton cultivars and identifying functional genes to enhance productivity.Generally speaking,we take model plants as a reference in the hope of coming up with new strategies for the efficient utilization of N and P in cotton.
基金Projects(51475462,61174030,61473094,61374126)supported by the National Natural Science Foundation of China
文摘Remaining useful life(RUL) estimation based on condition monitoring data is central to condition based maintenance(CBM). In the current methods about the Wiener process based RUL estimation, the randomness of the failure threshold has not been studied thoroughly. In this work, by using the truncated normal distribution to model random failure threshold(RFT), an analytical and closed-form RUL distribution based on the current observed data was derived considering the posterior distribution of the drift parameter. Then, the Bayesian method was used to update the prior estimation of failure threshold. To solve the uncertainty of the censored in situ data of failure threshold, the expectation maximization(EM) algorithm is used to calculate the posteriori estimation of failure threshold. Numerical examples show that considering the randomness of the failure threshold and updating the prior information of RFT could improve the accuracy of real time RUL estimation.
基金supported by the China Postdoctoral Science Foundation(2017M623415)。
文摘The value range of the failure threshold will generate an uncertain influence on the prediction results for the remaining useful life(RUL) of equipment. Most of the existing studies on the RUL prediction assume that the failure threshold is a fixed value,as they have difficulty in reflecting the random variation of the failure threshold. In connection with the inadequacies of the existing research, an in-depth analysis is carried out to study the effect of the random failure threshold(RFT) on the prediction results for the RUL. First, a nonlinear degradation model with unit-to-unit variability and measurement error is established based on the nonlinear Wiener process. Second, the expectation-maximization(EM) algorithm is used to solve the estimated values of the parameters of the prior degradation model, and the Bayesian method is used to iteratively update the posterior distribution of the random coefficients. Then, the effects of three types of RFT constraint conditions on the prediction results for the RUL are analyzed, and the probability density function(PDF) of the RUL is derived. Finally,the degradation data of aero-turbofan engines are used to verify the correctness and advantages of the method.
基金supported by the National Defense Foundation of China(7160118371901216)the China Postdoctoral Science Foundation(2017M623415)
文摘Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics.These features have an uncertain effect on the remaining useful life(RUL)prediction of the equipment.The current data-driven RUL prediction method has not systematically studied the nonlinear hidden degradation modeling and the RUL distribution function.This paper uses the nonlinear Wiener process to build a dual nonlinear implicit degradation model.Based on the historical measured data of similar equipment,the maximum likelihood estimation algorithm is used to estimate the fixed coefficients and the prior distribution of a random coefficient.Using the on-site measured data of the target equipment,the posterior distribution of a random coefficient and actual degradation state are step-by-step updated based on Bayesian inference and the extended Kalman filtering algorithm.The analytical form of the RUL distribution function is derived based on the first hitting time distribution.Combined with the two case studies,the proposed method is verified to have certain advantages over the existing methods in the accuracy of prediction.
基金Supporting founds:National Key R&D Program(2016YFC0400204)Natural Science Foundation of China(51479161,51279157,51779205)。
文摘Six-year old apple trees were selected for field experiment.The objective of this study was to obtain the reasonable arrangement of surge-root irrigation emitters in apple orchards.There were three factors:the buried depth H(25,40,55 cm),the horizontal distance L(30,40,60 cm)between the emitters and the trunk of the experimental tree,and the number of the irrigation emitters N(1,2,4).The effect of the arrangement of surge-root irrigation emitters on the growth,yield and irrigation water use efficiency(IWUE)of apple trees were studied in Northern Shaanxi where the irrigation quota takes 60%-75%of the field water capacity.The results showed that the arrangement of emitters for surge-root irrigation had a significant effect on apple tree yield and IWUE,especially,the yield and IWUE reached 28388.17 kg/hm2 and 16.83 kg/m3 in treatment T3,respectively.At the same L and N levels(T1,T2,and T3),the yield and IWUE in treatment T3 were the highest,and the yields in treatments T1 and T2 were decreased by 26.22%and 31.48%,while IWUE is reduced by14.02%and 18.12%compared with T3,respectively.At the same H and N levels(T3,T4,and T5),the yield and IWUE of apple trees were decreased with increasing L level.Especially,when L was 30 cm(T3),the yield and IWUE were the highest.The same L and H levels(T3,T6,and T7)could promote the growth of apple trees when N was 2(T3).Compared with treatment T3,it was found that the increment of new shoots was decreased by 8.07%-18.71%,and the fruit diameter was decreased by 5.41%-9.11%.Therefore,two emitters should be arranged symmetrically on both sides of an apple tree,each was buried at a 40 cm depth and 30 cm away from the trunk of the tree to effectively improve the yield and IWUE of the apple tree in mountainous areas in Northern Shaanxi.
基金Supported by the National Natural Science Foundation of China(3127219131372091)the Natural Science Foundation of Heilongjiang Province(C200619)
文摘The application of nitrogen （N） fertilizers in agriculture has been increasing dramatically since 1970s. However, the over-fertilization causes could cause environmental problems, as well as low N use efficiency （NUE）. Promoting NUE in plants and minimizing the environmental impacts of N fertilizers had been the focus of the current research. We reviewed the importance of N, N metabolism and plant growth, plant N physiology and the molecular aspect of N metabolism in this paper. The future development of N use and NUE of plants was also discussed.
基金supported by National Natural Science Foundation of China (61703410,61873175,62073336,61873273,61773386,61922089)。
文摘Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction.
基金supported by the Fundamental Research Funds for the Central Universities(2016083)
文摘A useful life prediction method based on the integration of the stochastic hybrid automata(SHA) model and the frame of the dynamic fault tree(DFT) is proposed. The SHA model can incorporate the orbit environment, work modes, system configuration, dynamic probabilities and degeneration of components,as well as spacecraft dynamics and kinematics. By introducing the frame of DFT, the system is classified into several layers, and the problem of state combination explosion is artfully overcome.An improved dynamic reliability model(DRM) based on the Nelson hypothesis is investigated to improve the defect of cumulative failure probability(CFP), which is used to address the failure probability of components in the SHA model. The simulation using the Monte-Carlo method is finally conducted on two satellites, which are deployed with the same multi-gyro subsystem but run on different orbits. The results show that the predicted useful life of the attitude control system(ACS) with consideration of abrupt failure,degradation, and running environment is quite different between the two satellites.
基金Projects(51108165, 51178170) supported by the National Natural Science Foundation of China
文摘An adaptive neuro-fuzzy inference system(ANFIS) for predicting the performance of a reversibly used cooling tower(RUCT) under cross flow conditions as part of a heat pump system for a heating mode in winter was demonstrated.Extensive field experimental work was carried out in order to gather enough data for training and prediction.The statistical methods,such as the correlation coefficient,absolute fraction of variance and root mean square error,were given to compare the predicted and actual values for model validation.The simulation results predicted with the ANFIS can be used to simulate the performance of a reversibly used cooling tower quite accurately.Therefore,the ANFIS approach can reliably be used for forecasting the performance of RUCT.
文摘Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.
