Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.展开更多
[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of...[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.展开更多
Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often comple...Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.展开更多
Taiji-2 project is the second step of Taiji program,which is to verify the required technology for Taiji-3 mission.The feasibility study of Taiji-2 is successfully finished,and some of the main progress is introduced ...Taiji-2 project is the second step of Taiji program,which is to verify the required technology for Taiji-3 mission.The feasibility study of Taiji-2 is successfully finished,and some of the main progress is introduced here.展开更多
The Chinese Meridian Project(CMP)is a major national science and technology infrastructure constructed in two steps.The first phase of the CMP has been operating for more than a solar cycle.From 2022 to 2023,utilizing...The Chinese Meridian Project(CMP)is a major national science and technology infrastructure constructed in two steps.The first phase of the CMP has been operating for more than a solar cycle.From 2022 to 2023,utilizing the monitoring data collected by the CMP,scientists made major breakthroughs in fields of ionosphere,middle and upper atmosphere,and coupling between layers.The construction of the second phase of the CMP is nearly finished,and the project is expected to operate as a whole in 2025 after national acceptance of the second phase.The whole project was built in an architecture of so-called“One Chain,Three Networks and Four Focuses”.It is promising to make a three-dimensional observation of the whole solar-terrestrial space.The science community is looking forward to the great contribution of the CMP to space weather and space physics research.展开更多
As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decompos...As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.展开更多
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
文摘[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.
基金supported by the National Natural Science Foundation of China(72101263).
文摘Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.
基金Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA15021100)the National Natural Science Foundation of China(12147103)the Fundamental Research Funds for the Central Universities。
文摘Taiji-2 project is the second step of Taiji program,which is to verify the required technology for Taiji-3 mission.The feasibility study of Taiji-2 is successfully finished,and some of the main progress is introduced here.
基金Supported by National Major Science and Technology Infrastructure Construction Project:the Chinese Meridian Project(2017-000052-73-01-002390)。
文摘The Chinese Meridian Project(CMP)is a major national science and technology infrastructure constructed in two steps.The first phase of the CMP has been operating for more than a solar cycle.From 2022 to 2023,utilizing the monitoring data collected by the CMP,scientists made major breakthroughs in fields of ionosphere,middle and upper atmosphere,and coupling between layers.The construction of the second phase of the CMP is nearly finished,and the project is expected to operate as a whole in 2025 after national acceptance of the second phase.The whole project was built in an architecture of so-called“One Chain,Three Networks and Four Focuses”.It is promising to make a three-dimensional observation of the whole solar-terrestrial space.The science community is looking forward to the great contribution of the CMP to space weather and space physics research.
基金supported by the National Natural Science Foundation of China(62273354,61673387,61833016).
文摘As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system.
