Brown spot(BS)of rice,caused by Bipolaris oryzae,is a serious concern that not only causes quantitative losses but also affects grain quality.To manage this disease,the use of resistant genetic sources and QTLs is an ...Brown spot(BS)of rice,caused by Bipolaris oryzae,is a serious concern that not only causes quantitative losses but also affects grain quality.To manage this disease,the use of resistant genetic sources and QTLs is an eco-friendly and economical option.In the current study,F_(3) progenies derived from a cross of susceptible parent PMS-18-B(PAU 10845-1-1-1-1)×resistant parent RP Path 77(RP patho-17)were used to identify potential QTLs linked to BS resistance and to associate this resistance with a temporal spike in defense-related enzymes.展开更多
Patients with cheiro-oral syndrome(COS) often present with minor perioral and upper extremity sensory disturbances,which can be easily overlooked in busy emergency departments(EDs).^([1]) COS,a rare spectrum of stroke...Patients with cheiro-oral syndrome(COS) often present with minor perioral and upper extremity sensory disturbances,which can be easily overlooked in busy emergency departments(EDs).^([1]) COS,a rare spectrum of stroke syndromes,necessitates expeditious and aggressive modification of risk factors.展开更多
Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model...Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.展开更多
Modal analysis,which provides modal parameters including frequencies,damping ratios,and mode shapes,is essential for assessing structural safety in structural health monitoring.Automated operational modal analysis(AOM...Modal analysis,which provides modal parameters including frequencies,damping ratios,and mode shapes,is essential for assessing structural safety in structural health monitoring.Automated operational modal analysis(AOMA)offers a promising alternative to traditional methods that depend heavily on human intervention and engineering judgment.However,estimating structural dynamic properties and managing spurious modes remain challenging due to uncertainties in practical application conditions.To address this issue,we propose an automated modal identification approach comprising three key aspects:(1)identification of modal parameters using covariance-driven stochastic subspace identification;(2)automated interpretation of the stabilization diagram;(3)an improved self-adaptive algorithm for grouping physical modes based on ordering points to identify the clustering structure(OPTICS)combined with k-nearest neighbors(KNN).The proposed approach can play a crucial role in enabling real-time structural health monitoring without human intervention.A simulated 10-story shear frame was used to verify the methodology.Identification results from a cable-stayed bridge demonstrate the practicality of the proposed method for conducting AOMA in engineering practice.The proposed approach can automatically identify modal parameters with high accuracy,making it suitable for a real-time structural health monitoring framework.展开更多
With the data of daily precipitation and daily evaporation,dynamic drought index was calculated and compared with the identification standard of drought grade to qualify the severity of drought.According to the dynami...With the data of daily precipitation and daily evaporation,dynamic drought index was calculated and compared with the identification standard of drought grade to qualify the severity of drought.According to the dynamic drought index,a regional drought identifying system was developed for the watershed between the reach of the Yangtze River and Huaihe River in Anhui Province by using VC++ working platform and Access database.This drought identifying system would be very useful to forecast and early warn the happening of drought in this area.展开更多
基金supported by Punjab Agricultural University,Ludhiana,India,for providing the infrastructure and other facilities for conducting experiments.All other forms of support and financial assistance are duly acknowledged.
文摘Brown spot(BS)of rice,caused by Bipolaris oryzae,is a serious concern that not only causes quantitative losses but also affects grain quality.To manage this disease,the use of resistant genetic sources and QTLs is an eco-friendly and economical option.In the current study,F_(3) progenies derived from a cross of susceptible parent PMS-18-B(PAU 10845-1-1-1-1)×resistant parent RP Path 77(RP patho-17)were used to identify potential QTLs linked to BS resistance and to associate this resistance with a temporal spike in defense-related enzymes.
文摘Patients with cheiro-oral syndrome(COS) often present with minor perioral and upper extremity sensory disturbances,which can be easily overlooked in busy emergency departments(EDs).^([1]) COS,a rare spectrum of stroke syndromes,necessitates expeditious and aggressive modification of risk factors.
基金supported by the National Natural Science Foundation of China(62473020).
文摘Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.
基金supported by the National Natural Science Foundation of China(No.52408200)the Natural Science Foundation of Jiangsu Province(No.BK20240996)+1 种基金China,the Suzhou Science and Technology Plan(Basic Research)Project(No.SJC2023002)China,and the Natural Science Research Projects of Colleges and Universities in Jiangsu Province(No.24KJB560022),China.
文摘Modal analysis,which provides modal parameters including frequencies,damping ratios,and mode shapes,is essential for assessing structural safety in structural health monitoring.Automated operational modal analysis(AOMA)offers a promising alternative to traditional methods that depend heavily on human intervention and engineering judgment.However,estimating structural dynamic properties and managing spurious modes remain challenging due to uncertainties in practical application conditions.To address this issue,we propose an automated modal identification approach comprising three key aspects:(1)identification of modal parameters using covariance-driven stochastic subspace identification;(2)automated interpretation of the stabilization diagram;(3)an improved self-adaptive algorithm for grouping physical modes based on ordering points to identify the clustering structure(OPTICS)combined with k-nearest neighbors(KNN).The proposed approach can play a crucial role in enabling real-time structural health monitoring without human intervention.A simulated 10-story shear frame was used to verify the methodology.Identification results from a cable-stayed bridge demonstrate the practicality of the proposed method for conducting AOMA in engineering practice.The proposed approach can automatically identify modal parameters with high accuracy,making it suitable for a real-time structural health monitoring framework.
基金Supported by Special Fund for Public Welfare Meteorology Industry (GYHY201106029)
文摘With the data of daily precipitation and daily evaporation,dynamic drought index was calculated and compared with the identification standard of drought grade to qualify the severity of drought.According to the dynamic drought index,a regional drought identifying system was developed for the watershed between the reach of the Yangtze River and Huaihe River in Anhui Province by using VC++ working platform and Access database.This drought identifying system would be very useful to forecast and early warn the happening of drought in this area.
