One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are ...One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.展开更多
Wolfgang Amadeus Mozart (born in Salzburg during the period of the Holy Roman Empire from January 27, 1756 to December 5, 1791) was a talented musician. His life was short but brilliant. He created more than 600 instr...Wolfgang Amadeus Mozart (born in Salzburg during the period of the Holy Roman Empire from January 27, 1756 to December 5, 1791) was a talented musician. His life was short but brilliant. He created more than 600 instrumental and vocal works in total. In addition to more than 20 operas, artistic songs and religious vocal music works, his soprano concert aria works also occupy an unusual position in his vast works, leaving precious musical art classics for mankind, which are widely studied by vocal music learners all over the world, especially young soprano singers, to improve their singing skills and performance skills, establish their own unique artistic style, lay a solid foundation for them to better understand and master Mozart's musical style of singing, and are excellent vocal music teaching materials with great training value.展开更多
Stem cell transplantation for the blind is a promising area of research, but it is still in the early stages of development. Our aim in this article is to think about geometric-mathematical tools so that by the flux o...Stem cell transplantation for the blind is a promising area of research, but it is still in the early stages of development. Our aim in this article is to think about geometric-mathematical tools so that by the flux of stem cells into open and curved spaces in the retina of recently blind people and macular degeneration patients, (AMD) patients, we will enable the growth of visual cells in their retinas.展开更多
基金Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration under Grant No.2024B08。
文摘One of the primary tasks of earthquake early warning(EEW)systems is to predict potential earthquake damage rapidly and accurately.Cumulative absolute velocity(CAV),Arias intensity(I_(A)),and spectrum intensity(SI)are important parameters for measuring ground motion intensity and assessing earthquake damage.Due to the limited available information in EEW,CAV,I_(A),and SI cannot be accurately predicted using traditional EEW methods.In this paper,we propose an end-to-end deep learning-based Ground motion Intensity prediction Network(ENGINet)for on-site EEW.The aim of the ENGINet is to predict CAV,I_(A),and SI rapidly and reliably.ENGINet is based on a convolutional neural network and recurrent neural network.The inputs of the network are three-component acceleration records,three-component velocity records,and three-component displacement records obtained by a single station.The results from the test dataset show that at 3 s after the P-wave arrival,compared with the baseline models and other traditional methods,ENGINet has better performance in predicting CAV,I_(A),and SI.Our results indicate that ENGINet can quickly and accurately predict CAV,I_(A),and SI to some extent and has good potential in EEW efforts.
文摘Wolfgang Amadeus Mozart (born in Salzburg during the period of the Holy Roman Empire from January 27, 1756 to December 5, 1791) was a talented musician. His life was short but brilliant. He created more than 600 instrumental and vocal works in total. In addition to more than 20 operas, artistic songs and religious vocal music works, his soprano concert aria works also occupy an unusual position in his vast works, leaving precious musical art classics for mankind, which are widely studied by vocal music learners all over the world, especially young soprano singers, to improve their singing skills and performance skills, establish their own unique artistic style, lay a solid foundation for them to better understand and master Mozart's musical style of singing, and are excellent vocal music teaching materials with great training value.
文摘Stem cell transplantation for the blind is a promising area of research, but it is still in the early stages of development. Our aim in this article is to think about geometric-mathematical tools so that by the flux of stem cells into open and curved spaces in the retina of recently blind people and macular degeneration patients, (AMD) patients, we will enable the growth of visual cells in their retinas.
