This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identificat...This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output data.Based on the bilinear state observer,a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost function.The gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise disturbance.Furthermore,to improve the performance of the proposed algorithm,a dynamicmoving window is designed which can update the dynamical data by removing the oldest data and adding the newestmeasurement data.A numerical example of identification of bilinear systems is presented to validate the theoretical analysis.展开更多
An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction ste...An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.展开更多
Online monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide appl...Online monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide applications in process performance analysis, monitoring and fault diagnosis using existing rich historical database.In this paper, we propose a simple and straight forward multivariate statistical modeling based on a moving window MPCA (multiway principal component analysis) model along the time and batch axis for adaptive monitoring the progress of batch processes in real-time. It is an extension to minimum window MPCA and traditional MPCA.The moving window MPCA along the batch axis can copy seamlessly with variable run length and does not need to estimate any deviations of the ongoing batch from the average trajectories. It replaces an invariant fixed-model monitoring approach with adaptive updating model data structure within batch-to-batch, which overcomes the changing operation condition and slows time-varying behaviors of industrial processes. The software based on moving window MPCA has been successfully applied to the industrial polymerization reactor of polyvinyl chloride (PVC) process in the Jinxi Chemical Company of China since 1999.展开更多
The urban-rural integrated area in Sanshui District of Foshan City was selected for research, and the impact of landscape pattern around the No.269 provincial highway was analyzed based on the land-use data in 2014 us...The urban-rural integrated area in Sanshui District of Foshan City was selected for research, and the impact of landscape pattern around the No.269 provincial highway was analyzed based on the land-use data in 2014 using the spatial analysis in GIS and the moving window method. The results showed that:(1) within the scope of a 2 km-range buffer zone, with a low degree of heterogeneity, land for construction use and water area were the dominant land-use types, while with a high degree of fragmentation, cultivated land, wooded land, grassland, garden land, land for other farm uses, and land unused were scattered;(2) the 250-m square moving window could well detect the change characteristics of landscape pattern on both sides of the road;(3) the gradient analysis of landscape pattern in urban-rural integrated area, which was conducted with the aid of a 750-m transect on both sides of the road, indicated that there were significant differences between landscape indexes both in the urban-rural integrated area and on both sides of the road;(4) the road that had an obvious cutting and fragmentation impact on the landscape was an important factor leading to the increasing fragmentation and heterogeneity to regional landscapes.展开更多
The incorporation of weather variables is crucial in developing an effective demand forecasting model because electricity demand is strongly influenced by weather conditions.The dependence of demand on weather conditi...The incorporation of weather variables is crucial in developing an effective demand forecasting model because electricity demand is strongly influenced by weather conditions.The dependence of demand on weather conditions may change with time during a day.Therefore,the time stamped weather information is essential.In this paper,a multi-layer moving window approach is proposed to incorporate the significant weather variables,which are selected using Pearson and Spearman correlation techniques.The multi-layer moving window approach allows the layers to adjust their size to accommodate the weather variables based on their significance,which creates more flexibility and adaptability thereby improving the overall performance of the proposed approach.Furthermore,a recursive model is developed to forecast the demand in multi-step ahead.An electricity demand data for the state of New South Wales,Australia are acquired from the Australian Energy Market Operator and the associated results are reported in the paper.The results show that the proposed approach with dynamic incorporation of weather variables is promising for day-ahead and week-ahead load demand forecasting.展开更多
In this paper a method for modelling and forecasting of a class of nonstationary time series with Kalman filter using moving window is proposed. The procedure of the method is as follows: in terms of parameter estimat...In this paper a method for modelling and forecasting of a class of nonstationary time series with Kalman filter using moving window is proposed. The procedure of the method is as follows: in terms of parameter estimation during recursive process by using LSM, the state space equation is constructed, then the Kalman filter using moving window is made to get the data with reduced level of observation noise. Finally, the precise parameter estimation can be obtained by using the LSM again. The algorithm is carried on recursively. Good results for estimating and forecasting are shown by simulation, examples. The algorithm of Kalman filter using moving window proposed by us is introduced in this paper, which can guarantee the precision and convergence of Kalman filter.展开更多
Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes.These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity,phyto-sociology,bounda...Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes.These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity,phyto-sociology,boundary detection and even impact of change in land use pattern(anthropogenic activity).The most accepted and widespread technique called as Moving Split Window(MSW) technique is used for detection of vegetation and environmental boundaries at four different sites in the lesser stratum of north-west Himalaya.All the four sites were at different distances from the nearest human inhabited area.Anthropogenic activities like grazing,herb collection,wood collection etc.were common at proximal sites.Such activities have led to the change in land use pattern.In this study,we have tried to work out the impact of the change in land use pattern(human interference) on the vegetation and basic environmental parameters like soil pH,electrical conductivity and moisture on forestgrassland ecotone in north-west Himalaya.Data on mountain steepness was also collected and analyzed.The dissimilarity profile using the statistical tool Squared Euclidian Distance(SED) indicated that species turnover locations increase with the increase in distance of ecotones from human settlements.The ecotones at distant locations from human villages are characterized with blunt as well as sharp peaks for vegetation data,however,conditions are reverse in case of the proximal sites.The study also reveals that as the distance between the ecotone and human settlements increases,the complex conditions like multiple vegetation boundaries prevails on the transitions.In this regard,land use induced blurring of forest-grassland transition in north-west Himalaya is summed up in the study.展开更多
A fully digital data acquisition system based on a field-programmable gate array(FPGA) was developed for a CsI(Tl) array at the external target facility(ETF) in the Heavy Ion Research Facility in Lanzhou(HIRFL). To pr...A fully digital data acquisition system based on a field-programmable gate array(FPGA) was developed for a CsI(Tl) array at the external target facility(ETF) in the Heavy Ion Research Facility in Lanzhou(HIRFL). To process the CsI(Tl) signals generated by γ-rays and light-charged ions, a scheme for digital pulse processing algorithms is proposed. Every step in the algorithms was benchmarked using standard γ and α sources. The scheme, which included a moving average filter, baseline restoration, leading-edge discrimination, moving window deconvolution, and digital charge comparison, was subsequently implemented on the FPGA. A good energy resolution of 5.7% for 1.33-MeV γ-rays and excellent α-γ identification using the digital charge comparison method were achieved, which satisfies CsI(Tl) array performance requirements.展开更多
Cotton is a revenue source for cotton-producing countries;as the second-largest crop in Pakistan,it significantly contributes to its economy.Over the past few decades,cotton productivity has become unstable in Pakista...Cotton is a revenue source for cotton-producing countries;as the second-largest crop in Pakistan,it significantly contributes to its economy.Over the past few decades,cotton productivity has become unstable in Pakistan,and climate change is one of the main factors that impact cotton yield.Due to climate change,it becomes very important to understand the change trend and its impact on cotton yield at the regional level.Here,we investigate the relationship of standardized cotton yield variability with the variability of climate factors using a 15-yr moving window.The piecewise regression was fitted to obtain the trend-shifting point of climate factors.The results show that precipitation has experienced an overall decreasing trend of–0.64 mm/yr during the study period,with opposing trends of–1.39 mm/yr and 1.52 mm/yr before and after the trend-shifting point,respectively.We found that cotton yield variability increased at a rate of 0.17%/yr,and this trend was highly correlated with the variability of climate factors.The multiple regression analysis explains that climate variability is a dominant factor and controlled 81%of the cotton production in the study area from 1990 to 2019,while it controlled 73%of the production from 1990 to 2002 and 84%from 2002 to 2019.These findings reveal that climate factors affact the distinct spatial pattern of changes in cotton yield variability at the tehsil level.展开更多
We construct recurrence plots(RPs)and conduct recurrence quantification analysis(RQA)to investigate the dynamic properties of the new Center for Financial Stability(CFS)Divisia monetary aggregates for the United State...We construct recurrence plots(RPs)and conduct recurrence quantification analysis(RQA)to investigate the dynamic properties of the new Center for Financial Stability(CFS)Divisia monetary aggregates for the United States.In this study,we use the lat-est vintage of Divisia aggregates,maintained within CFS.We use monthly data,from January 1967 to December 2020,which is a sample period that includes the extreme economic events of the 2007–2009 global financial crisis.We then make comparisons between narrow and broad Divisia money measures and find evidence of a nonlinear but reserved possible chaotic explanation of their origin.The application of RPs to broad Divisia monetary aggregates encompasses an additional drift structure around the global financial crisis in 2008.Applying the moving window RQA to the growth rates of narrow and broad Divisia monetary aggregates,we identify periods of changes in data-generating processes and associate such changes to monetary policy regimes and financial innovations that occurred during those times.展开更多
Urban sprawl is driven by a myriad of factors, the predominant one of which is the development of residential land. Selecting part of Jinan City for a case study, we use the landscape metric of percent of landscape (P...Urban sprawl is driven by a myriad of factors, the predominant one of which is the development of residential land. Selecting part of Jinan City for a case study, we use the landscape metric of percent of landscape (PLAND) to capture residential land growth and density changes in 1989, 1996 and 2004 to illuminate the dynamic process of residential land development. The results indicate that the moving window method and the landscape metrics method are efficient ways to describe residential land density. The residential land showed the greatest change among the built-up land with 1995.68 ha from 1989 to 2004, which is mainly transformed from agriculture land and green space. The urban center area of study area is primarily covered with medium density residential land, and surrounded by high density residential land. The development pattern of residential land exhibited both fill-in (new growth occurs through infilling the free spaces within the developed area) and sprawl processes, influenced by a series of factors, such as urban development policy, conservation of springs, recreational and aesthetic amenities. The findings of the study will help to guide urban planning with a focus on the management and protection of the environment and resources.展开更多
Geospatial patterns of forest fragmentation over the three traditional giant forested areas of China （Northeastern, southwestern and Southern China） were analyzed comparatively and reported based on a 250-m resoluti...Geospatial patterns of forest fragmentation over the three traditional giant forested areas of China （Northeastern, southwestern and Southern China） were analyzed comparatively and reported based on a 250-m resolution land cover dataset. Specifically, the spatial patterns of forest fragmentation were characterized by combining geospatial metrics and forest fragmentation models. The driving forces resulting in the differences of the forest spatial patterns were also investigated. Results suggested that forests in southwest China had the highest severity of forest fragmentation, followed by south region and northeast region. The driving forces of forest fragmentation in China were primarily the giant population and improper exploitation of forests. In conclusion, the generated information in the study provided valuable insights and implications as to the fragmentation patterns and the conservation of hiodiversity or genes, and the use of the chosen geospatial metrics and forest fragmentation models was quite useful for depicting forest fragmentation patterns.展开更多
International food trade has become a key driving force of agricultural land-use changes in trading countries, which has influenced food production and the global environment. Researchers have studied agricultural lan...International food trade has become a key driving force of agricultural land-use changes in trading countries, which has influenced food production and the global environment. Researchers have studied agricultural land-use changes and related environmental issues across multi-trading countries together, but most studies rely on statistic data without spatial attributes. However, agricultural land-use changes are spatially heterogeneous. Uncovering spatial attributes can reveal more critical information that is of scientific significance and has policy implications for enhancing food security and protecting the environment. Based on an integrated framework of telecoupling （socioeconomic and environmental interactions over distances）, we studied spatial attributes of soybean land changes within and among trading countries at the same time. Three distant countries -- Brazil, China, and the United States -- constitute an excellent example of telecoupled systems through the process of soybean trade. Our results presented the spatial distribution of soybean land changes-- highlighting the hotspots of soybean gain and soybean loss, and indicated these changes were spatially clustered, different across multi-spatial scales, and varied among the trading countries. Assisted by the results, global challenges like food security and biodiversity loss within and among trading countries can be targeted and managed efficiently. Our work provides simul- taneously spatial information for understanding agricultural land-use changes caused by international food trade globally, highlights the needs of coordination among trading countries, and promotes global sustainability.展开更多
A large number of studies have been conducted to find a better fit for city rank-size distributions in different countries. Many theoretical curves have been proposed, but no consensus has been reached. This study arg...A large number of studies have been conducted to find a better fit for city rank-size distributions in different countries. Many theoretical curves have been proposed, but no consensus has been reached. This study argues for the importance of examining city rank-size distribution across different city size scales. In addition to focusing on macro patterns, this study examines the micro patterns of city rank-size distributions in China. A moving window method is developed to detect rank-size distributions of cities in different sizes incrementally. The results show that micro patterns of the actual city rank-size distributions in China are much more complex than those suggested by the three theoretical distributions examined(Pareto, quadratic, and q-exponential distributions). City size distributions present persistent discontinuities. Large cities are more evenly distributed than small cities and than that predicted by Zipf′s law. In addition, the trend is becoming more pronounced over time. Medium-sized cities became evenly distributed first and then unevenly distributed thereafter. The rank-size distributions of small cities are relatively consistent. While the three theoretical distributions examined in this study all have the ability to detect the overall dynamics of city rank-size distributions, the actual macro distribution may be composed of a combination of the three theoretical distributions.展开更多
Gas chromatography-mass spectrometry(GC-MS) and the chemometric resolution method(alternative moving window factor analysis,AMWFA) were used for comparative analysis of volatile constituents in herbal pair(HP) flos lo...Gas chromatography-mass spectrometry(GC-MS) and the chemometric resolution method(alternative moving window factor analysis,AMWFA) were used for comparative analysis of volatile constituents in herbal pair(HP) flos lonicerae-caulis lonicerae(FL-CL) and its single herbs.The temperature-programmed retention index(PTRI) was also employed for the identification of compounds.In total,44,39,and 50 volatile chemical components in volatile oil of FL,CL and HP FL-CL were separately determined qualitatively and quantitatively,accounting for 87.22%,94.54% and 90.08% total contents of volatile oil of FL,CL and HP FL-CL,respectively.The results show that there are 32 common volatile constituents between HP FL-CL and single herb FL,33 common volatile constituents between HP FL-CL and single herb CL,and 10 new constituents in the volatile oil of HP FL-CL.展开更多
To understand the rheology,structure,and tectonics of the lithosphere in the Mariana subduction zone and surrounding regions,we calculated the effective elastic thickness of the lithosphere(Te)in these areas using the...To understand the rheology,structure,and tectonics of the lithosphere in the Mariana subduction zone and surrounding regions,we calculated the effective elastic thickness of the lithosphere(Te)in these areas using the improved moving window admittance technique(MWAT)method.We find that smaller data grid spacing can better reflect Te variations in the subduction zone.The Te of the study region ranges from 0 to 47 km.The Te is reduced from 40 km on the seaward side of the outer-rise region to 1-2 km along the trench axis.The lithospheric breaking distance from the trench axis ranges from 0 to 250 km.We suggest that the intermediate Te values in seamounts and high Te values on the seaward side of the outer-rise region respectively reflect the‘fossil’rheological state and current lithospheric strength of the Pacific plate.The faulting induced by the downward bending of subducting plate not only ruptures the lithosphere but also contributes to the mantle serpentinization,significantly reducing the lithospheric strength.The largest breaking distance of the Ogasawara Plateau may be due to the increase in the mass load of the subducting plate in the Ogasawara Plateau and the significant horizontal bending force in the plate caused by the resistance of seamounts to subduction.Furthermore,a good positive correlation exists between the breaking distance and subduction dip angle along the trench axis.We suggest that the subducting plate with a larger breaking distance is likely to form a larger subduction angle.展开更多
基金funded by the National Natural Science Foundation of China(No.61773182)the 111 Project(B12018).
文摘This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output data.Based on the bilinear state observer,a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost function.The gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise disturbance.Furthermore,to improve the performance of the proposed algorithm,a dynamicmoving window is designed which can update the dynamical data by removing the oldest data and adding the newestmeasurement data.A numerical example of identification of bilinear systems is presented to validate the theoretical analysis.
基金Supported by National High-Tech Program of China (No. 2001AA413110).
文摘An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.
基金国家重点基础研究发展计划(973计划)，国家自然科学基金，the National Natural Science Foundation of China
文摘Online monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide applications in process performance analysis, monitoring and fault diagnosis using existing rich historical database.In this paper, we propose a simple and straight forward multivariate statistical modeling based on a moving window MPCA (multiway principal component analysis) model along the time and batch axis for adaptive monitoring the progress of batch processes in real-time. It is an extension to minimum window MPCA and traditional MPCA.The moving window MPCA along the batch axis can copy seamlessly with variable run length and does not need to estimate any deviations of the ongoing batch from the average trajectories. It replaces an invariant fixed-model monitoring approach with adaptive updating model data structure within batch-to-batch, which overcomes the changing operation condition and slows time-varying behaviors of industrial processes. The software based on moving window MPCA has been successfully applied to the industrial polymerization reactor of polyvinyl chloride (PVC) process in the Jinxi Chemical Company of China since 1999.
基金Sponsored by National Natural Science Foundation of China(41671160)
文摘The urban-rural integrated area in Sanshui District of Foshan City was selected for research, and the impact of landscape pattern around the No.269 provincial highway was analyzed based on the land-use data in 2014 using the spatial analysis in GIS and the moving window method. The results showed that:(1) within the scope of a 2 km-range buffer zone, with a low degree of heterogeneity, land for construction use and water area were the dominant land-use types, while with a high degree of fragmentation, cultivated land, wooded land, grassland, garden land, land for other farm uses, and land unused were scattered;(2) the 250-m square moving window could well detect the change characteristics of landscape pattern on both sides of the road;(3) the gradient analysis of landscape pattern in urban-rural integrated area, which was conducted with the aid of a 750-m transect on both sides of the road, indicated that there were significant differences between landscape indexes both in the urban-rural integrated area and on both sides of the road;(4) the road that had an obvious cutting and fragmentation impact on the landscape was an important factor leading to the increasing fragmentation and heterogeneity to regional landscapes.
基金supported by Hong Duc,Thanh Hoa–UOW research scholarship program.
文摘The incorporation of weather variables is crucial in developing an effective demand forecasting model because electricity demand is strongly influenced by weather conditions.The dependence of demand on weather conditions may change with time during a day.Therefore,the time stamped weather information is essential.In this paper,a multi-layer moving window approach is proposed to incorporate the significant weather variables,which are selected using Pearson and Spearman correlation techniques.The multi-layer moving window approach allows the layers to adjust their size to accommodate the weather variables based on their significance,which creates more flexibility and adaptability thereby improving the overall performance of the proposed approach.Furthermore,a recursive model is developed to forecast the demand in multi-step ahead.An electricity demand data for the state of New South Wales,Australia are acquired from the Australian Energy Market Operator and the associated results are reported in the paper.The results show that the proposed approach with dynamic incorporation of weather variables is promising for day-ahead and week-ahead load demand forecasting.
文摘In this paper a method for modelling and forecasting of a class of nonstationary time series with Kalman filter using moving window is proposed. The procedure of the method is as follows: in terms of parameter estimation during recursive process by using LSM, the state space equation is constructed, then the Kalman filter using moving window is made to get the data with reduced level of observation noise. Finally, the precise parameter estimation can be obtained by using the LSM again. The algorithm is carried on recursively. Good results for estimating and forecasting are shown by simulation, examples. The algorithm of Kalman filter using moving window proposed by us is introduced in this paper, which can guarantee the precision and convergence of Kalman filter.
文摘Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes.These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity,phyto-sociology,boundary detection and even impact of change in land use pattern(anthropogenic activity).The most accepted and widespread technique called as Moving Split Window(MSW) technique is used for detection of vegetation and environmental boundaries at four different sites in the lesser stratum of north-west Himalaya.All the four sites were at different distances from the nearest human inhabited area.Anthropogenic activities like grazing,herb collection,wood collection etc.were common at proximal sites.Such activities have led to the change in land use pattern.In this study,we have tried to work out the impact of the change in land use pattern(human interference) on the vegetation and basic environmental parameters like soil pH,electrical conductivity and moisture on forestgrassland ecotone in north-west Himalaya.Data on mountain steepness was also collected and analyzed.The dissimilarity profile using the statistical tool Squared Euclidian Distance(SED) indicated that species turnover locations increase with the increase in distance of ecotones from human settlements.The ecotones at distant locations from human villages are characterized with blunt as well as sharp peaks for vegetation data,however,conditions are reverse in case of the proximal sites.The study also reveals that as the distance between the ecotone and human settlements increases,the complex conditions like multiple vegetation boundaries prevails on the transitions.In this regard,land use induced blurring of forest-grassland transition in north-west Himalaya is summed up in the study.
基金supported by the Open Research Project of CAS Large Research InfrastructuresCAS Key Technology Talent ProgramNational Natural Science Foundations of China (Nos.U2031206 and 12273086)
文摘A fully digital data acquisition system based on a field-programmable gate array(FPGA) was developed for a CsI(Tl) array at the external target facility(ETF) in the Heavy Ion Research Facility in Lanzhou(HIRFL). To process the CsI(Tl) signals generated by γ-rays and light-charged ions, a scheme for digital pulse processing algorithms is proposed. Every step in the algorithms was benchmarked using standard γ and α sources. The scheme, which included a moving average filter, baseline restoration, leading-edge discrimination, moving window deconvolution, and digital charge comparison, was subsequently implemented on the FPGA. A good energy resolution of 5.7% for 1.33-MeV γ-rays and excellent α-γ identification using the digital charge comparison method were achieved, which satisfies CsI(Tl) array performance requirements.
基金Under the auspices of National Key Research and Development Program of China (No.2017YFA0604403-3,2016YFA0602301)the Joint Fund of National Natural Science Foundation of China (No.U19A2023)。
文摘Cotton is a revenue source for cotton-producing countries;as the second-largest crop in Pakistan,it significantly contributes to its economy.Over the past few decades,cotton productivity has become unstable in Pakistan,and climate change is one of the main factors that impact cotton yield.Due to climate change,it becomes very important to understand the change trend and its impact on cotton yield at the regional level.Here,we investigate the relationship of standardized cotton yield variability with the variability of climate factors using a 15-yr moving window.The piecewise regression was fitted to obtain the trend-shifting point of climate factors.The results show that precipitation has experienced an overall decreasing trend of–0.64 mm/yr during the study period,with opposing trends of–1.39 mm/yr and 1.52 mm/yr before and after the trend-shifting point,respectively.We found that cotton yield variability increased at a rate of 0.17%/yr,and this trend was highly correlated with the variability of climate factors.The multiple regression analysis explains that climate variability is a dominant factor and controlled 81%of the cotton production in the study area from 1990 to 2019,while it controlled 73%of the production from 1990 to 2002 and 84%from 2002 to 2019.These findings reveal that climate factors affact the distinct spatial pattern of changes in cotton yield variability at the tehsil level.
文摘We construct recurrence plots(RPs)and conduct recurrence quantification analysis(RQA)to investigate the dynamic properties of the new Center for Financial Stability(CFS)Divisia monetary aggregates for the United States.In this study,we use the lat-est vintage of Divisia aggregates,maintained within CFS.We use monthly data,from January 1967 to December 2020,which is a sample period that includes the extreme economic events of the 2007–2009 global financial crisis.We then make comparisons between narrow and broad Divisia money measures and find evidence of a nonlinear but reserved possible chaotic explanation of their origin.The application of RPs to broad Divisia monetary aggregates encompasses an additional drift structure around the global financial crisis in 2008.Applying the moving window RQA to the growth rates of narrow and broad Divisia monetary aggregates,we identify periods of changes in data-generating processes and associate such changes to monetary policy regimes and financial innovations that occurred during those times.
基金Under the auspices of National High Technology Research Development Program of China(No.2009AAA122005)National Natural Science Foundation of China(No.30700097,40701047)
文摘Urban sprawl is driven by a myriad of factors, the predominant one of which is the development of residential land. Selecting part of Jinan City for a case study, we use the landscape metric of percent of landscape (PLAND) to capture residential land growth and density changes in 1989, 1996 and 2004 to illuminate the dynamic process of residential land development. The results indicate that the moving window method and the landscape metrics method are efficient ways to describe residential land density. The residential land showed the greatest change among the built-up land with 1995.68 ha from 1989 to 2004, which is mainly transformed from agriculture land and green space. The urban center area of study area is primarily covered with medium density residential land, and surrounded by high density residential land. The development pattern of residential land exhibited both fill-in (new growth occurs through infilling the free spaces within the developed area) and sprawl processes, influenced by a series of factors, such as urban development policy, conservation of springs, recreational and aesthetic amenities. The findings of the study will help to guide urban planning with a focus on the management and protection of the environment and resources.
基金This research was performed while the lead author held a National Research Council (NRC) Research Associateship Program Award a postdoctoral program sponsored by the NRC in partnership with the U.S. Geological Survey
文摘Geospatial patterns of forest fragmentation over the three traditional giant forested areas of China （Northeastern, southwestern and Southern China） were analyzed comparatively and reported based on a 250-m resolution land cover dataset. Specifically, the spatial patterns of forest fragmentation were characterized by combining geospatial metrics and forest fragmentation models. The driving forces resulting in the differences of the forest spatial patterns were also investigated. Results suggested that forests in southwest China had the highest severity of forest fragmentation, followed by south region and northeast region. The driving forces of forest fragmentation in China were primarily the giant population and improper exploitation of forests. In conclusion, the generated information in the study provided valuable insights and implications as to the fragmentation patterns and the conservation of hiodiversity or genes, and the use of the chosen geospatial metrics and forest fragmentation models was quite useful for depicting forest fragmentation patterns.
基金financial support from the National Science FoundationMichigan State UniversityMichigan AgBio Research,United States
文摘International food trade has become a key driving force of agricultural land-use changes in trading countries, which has influenced food production and the global environment. Researchers have studied agricultural land-use changes and related environmental issues across multi-trading countries together, but most studies rely on statistic data without spatial attributes. However, agricultural land-use changes are spatially heterogeneous. Uncovering spatial attributes can reveal more critical information that is of scientific significance and has policy implications for enhancing food security and protecting the environment. Based on an integrated framework of telecoupling （socioeconomic and environmental interactions over distances）, we studied spatial attributes of soybean land changes within and among trading countries at the same time. Three distant countries -- Brazil, China, and the United States -- constitute an excellent example of telecoupled systems through the process of soybean trade. Our results presented the spatial distribution of soybean land changes-- highlighting the hotspots of soybean gain and soybean loss, and indicated these changes were spatially clustered, different across multi-spatial scales, and varied among the trading countries. Assisted by the results, global challenges like food security and biodiversity loss within and among trading countries can be targeted and managed efficiently. Our work provides simul- taneously spatial information for understanding agricultural land-use changes caused by international food trade globally, highlights the needs of coordination among trading countries, and promotes global sustainability.
基金Under the auspices of Utah Agricultural Experiment Station,Utah State University(No.UTAO 1106)
文摘A large number of studies have been conducted to find a better fit for city rank-size distributions in different countries. Many theoretical curves have been proposed, but no consensus has been reached. This study argues for the importance of examining city rank-size distribution across different city size scales. In addition to focusing on macro patterns, this study examines the micro patterns of city rank-size distributions in China. A moving window method is developed to detect rank-size distributions of cities in different sizes incrementally. The results show that micro patterns of the actual city rank-size distributions in China are much more complex than those suggested by the three theoretical distributions examined(Pareto, quadratic, and q-exponential distributions). City size distributions present persistent discontinuities. Large cities are more evenly distributed than small cities and than that predicted by Zipf′s law. In addition, the trend is becoming more pronounced over time. Medium-sized cities became evenly distributed first and then unevenly distributed thereafter. The rank-size distributions of small cities are relatively consistent. While the three theoretical distributions examined in this study all have the ability to detect the overall dynamics of city rank-size distributions, the actual macro distribution may be composed of a combination of the three theoretical distributions.
基金Project(20976017) supported by the National Natural Science Foundation of China
文摘Gas chromatography-mass spectrometry(GC-MS) and the chemometric resolution method(alternative moving window factor analysis,AMWFA) were used for comparative analysis of volatile constituents in herbal pair(HP) flos lonicerae-caulis lonicerae(FL-CL) and its single herbs.The temperature-programmed retention index(PTRI) was also employed for the identification of compounds.In total,44,39,and 50 volatile chemical components in volatile oil of FL,CL and HP FL-CL were separately determined qualitatively and quantitatively,accounting for 87.22%,94.54% and 90.08% total contents of volatile oil of FL,CL and HP FL-CL,respectively.The results show that there are 32 common volatile constituents between HP FL-CL and single herb FL,33 common volatile constituents between HP FL-CL and single herb CL,and 10 new constituents in the volatile oil of HP FL-CL.
基金This research was supported by the National Natural Science Foundation of China(Nos.41676039 and 4207061006)the Shandong Young Teacher Growth Program.
文摘To understand the rheology,structure,and tectonics of the lithosphere in the Mariana subduction zone and surrounding regions,we calculated the effective elastic thickness of the lithosphere(Te)in these areas using the improved moving window admittance technique(MWAT)method.We find that smaller data grid spacing can better reflect Te variations in the subduction zone.The Te of the study region ranges from 0 to 47 km.The Te is reduced from 40 km on the seaward side of the outer-rise region to 1-2 km along the trench axis.The lithospheric breaking distance from the trench axis ranges from 0 to 250 km.We suggest that the intermediate Te values in seamounts and high Te values on the seaward side of the outer-rise region respectively reflect the‘fossil’rheological state and current lithospheric strength of the Pacific plate.The faulting induced by the downward bending of subducting plate not only ruptures the lithosphere but also contributes to the mantle serpentinization,significantly reducing the lithospheric strength.The largest breaking distance of the Ogasawara Plateau may be due to the increase in the mass load of the subducting plate in the Ogasawara Plateau and the significant horizontal bending force in the plate caused by the resistance of seamounts to subduction.Furthermore,a good positive correlation exists between the breaking distance and subduction dip angle along the trench axis.We suggest that the subducting plate with a larger breaking distance is likely to form a larger subduction angle.
