Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different sources.The identification of SDEs governing a sy...Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different sources.The identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system’s dynamics.The practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data resources.This study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning(SBL)technique to search for a parsimonious,yet physically necessary representation from the space of candidate basis functions.More importantly,we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series data.The effectiveness of the proposed framework is demonstrated using real data on stock and oil prices,bearing variation,and wind speed,as well as simulated data on well-known stochastic dynamical systems,including the generalized Wiener process and Langevin equation.This framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences,economics,and engineering fields for analysis,prediction,and decision making.展开更多
The problem of fixed-time group consensus for second-order multi-agent systems with disturbances is investigated.For cooperative-competitive network,two different control protocols,fixed-time group consensus and fixed...The problem of fixed-time group consensus for second-order multi-agent systems with disturbances is investigated.For cooperative-competitive network,two different control protocols,fixed-time group consensus and fixed-time eventtriggered group consensus,are designed.It is demonstrated that there is no Zeno behavior under the designed eventtriggered control.Meanwhile,it is proved that for an arbitrary initial state of the system,group consensus within the settling time could be obtained under the proposed control protocols by using matrix analysis and graph theory.Finally,a series of numerical examples are propounded to illustrate the performance of the proposed control protocol.展开更多
Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurren...Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurrences of heatwaves between the grid cells in East Asia and Eastern Europe,even though they are geographically far away from each other.By further composite analysis,this study revealed that hot events first occurred in Eastern Europe,typically with a time lag of3-4 days before the East Asian heatwave events.An eastward propagating atmospheric wave train,known as the circumglobal teleconnection(CGT)pattern,bridged the sequent occurrences of extreme events in these two remote regions.Atmospheric blockings,amplified by surface warming over Eastern Europe,not only enhanced local heat extremes but also excited a CGT-like pattern characterized by alternative anomalies of high and low pressures.Subsequent downstream anticyclones in the middle and upper troposphere reduced local cloud cover and increased downward solar radiation,thereby facilitating the formation of heatwaves over East Asia.Nearly half of East Asian heatwave events were preceded by Eastern European heatwave events in the 10-day time range before East Asian heatwave events.This investigation of heatwave teleconnection in the two distant regions exhibits strong potential to improve the prediction accuracy of East Asian heatwaves.展开更多
Highly dispersed palladium nanoparticles were synthesized in the presence of immobilized ionic liquid on mesoporous silica SBA-15.PdNPs(2.4 nm)_me-Im@SBA-15 catalyst was prepared by the reduction using NaBH_4 as the r...Highly dispersed palladium nanoparticles were synthesized in the presence of immobilized ionic liquid on mesoporous silica SBA-15.PdNPs(2.4 nm)_me-Im@SBA-15 catalyst was prepared by the reduction using NaBH_4 as the reducing agent with controlled feed rate and has been investigated as ligand-free catalyst for Suzuki–Miyaura cross-coupling reaction at room temperature in aqueous solution under air.PdNPs catalyst was also prepared in situ from PdCl4_me-Im@SBA-15 during the reaction and demonstrated high activity and stability towards nitrobenzene hydrogenation at high temperature. Both catalysts were reusable at least for four recycle processes without significant loss in activity with simple procedure. The catalysts were characterized by TEM, EXAFS, FTIR and XPS.展开更多
Arbitrary‐oriented object detection is widely used in aerial image applications because of its efficient object representation.However,the use of oriented bounding box aggravates the imbalance between positive and ne...Arbitrary‐oriented object detection is widely used in aerial image applications because of its efficient object representation.However,the use of oriented bounding box aggravates the imbalance between positive and negative samples when using one‐stage object detectors,which seriously decreases the detection accuracy.We believe that it is the anchor learning strategy(ALS)used by such detectors that needs to take the responsibility.In this study,three perspectives on ALS design were summarised and ALS—Performance Releaser with Smart Anchor Learning(PRSAL)was proposed.Performance Releaser with Smart Anchor Learning is a dynamic ALS that utilises anchor classification ability as an equivalent indicator to anchor box regression ability,this allows anchors with high detection potential to be filtered out in a more reasonable way.At the same time,PRSAL focuses more on anchor potential and it is able to automatically select a number of positive samples that far exceed that of other methods by activating anchors that previously had a low spatial overlap,thereby releasing the detection performance.We validate the PRSAL using three remote sensing datasets—HRSC2016,DOTA and UCAS‐AOD as well as one scene text dataset—ICDAR 2013.The experimental results show that the proposed method gives substantially better results than existing models.展开更多
With the increase in the aging population,the global number of people with Alzheimer’s disease(AD)progressively increased worldwide.The situation is aggravated by the fact that there is no the efective pharmacologica...With the increase in the aging population,the global number of people with Alzheimer’s disease(AD)progressively increased worldwide.The situation is aggravated by the fact that there is no the efective pharmacological therapy of AD.Photobiomodulation(PBM)is non-pharmacological approach that has shown very promising results in the therapy of AD in pilot clinical and animal studies.However,the mechanisms of therapeutic efects of PBM for AD are poorly understood.In this study on mice,we demonstrate that photodynamic efects of 5-aminolevulenic acid and laser 635 nm cause reduction of network of the meningeal lymphatic vessels(MLVs)leading to suppression of lymphatic removal of beta-amyloid(Aβ)from the right lateral ventricle and the hippocampus.Using the original protocol of PBM under electroencephalographic monitoring of wakefulness and sleep stages in non-anesthetized mice,we discover that the 7-day course of PBM during deep sleep vs.wakefulness provides better restoration of clearance of Aβfrom the ventricular system of the brain and the hippocampus.Our results shed light on the mechanism of PBM and show the stimulating efects of PBM on the brain lymphatic drainage that promotes transport of Aβvia the lymphatic pathway.The efects of PBM on the brain lymphatics in sleeping brain open a new niche in the study of restorative functions of sleep as well as it is an important informative platform for the development of innovative smart sleep technologies for the therapy of AD.展开更多
基金supported by the National Key Research and Development Program of China(2018YFB1701202)the National Natural Science Foundation of China(92167201 and 51975237)the Fundamental Research Funds for the Central Universities,Huazhong University of Science and Technology(2021JYCXJJ028)。
文摘Stochastic differential equations(SDEs)are mathematical models that are widely used to describe complex processes or phenomena perturbed by random noise from different sources.The identification of SDEs governing a system is often a challenge because of the inherent strong stochasticity of data and the complexity of the system’s dynamics.The practical utility of existing parametric approaches for identifying SDEs is usually limited by insufficient data resources.This study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning(SBL)technique to search for a parsimonious,yet physically necessary representation from the space of candidate basis functions.More importantly,we use the analytical tractability of SBL to develop an efficient way to formulate the linear regression problem for the discovery of SDEs that requires considerably less time-series data.The effectiveness of the proposed framework is demonstrated using real data on stock and oil prices,bearing variation,and wind speed,as well as simulated data on well-known stochastic dynamical systems,including the generalized Wiener process and Langevin equation.This framework aims to assist specialists in extracting stochastic mathematical models from random phenomena in the natural sciences,economics,and engineering fields for analysis,prediction,and decision making.
基金Project supported by the Graduate Student Research Innovation Project of Chongqing(Grant No.CYS22482)the National Natural Science Foundation of China(Grant No.61773082)+1 种基金the Science and Technology Research Program of Chongqing Municipal Education Commission(Grant No.KJZD-K202000601)the Research Program of Chongqing Talent,China(Grant No.cstc2021ycjhbgzxm0044).
文摘The problem of fixed-time group consensus for second-order multi-agent systems with disturbances is investigated.For cooperative-competitive network,two different control protocols,fixed-time group consensus and fixed-time eventtriggered group consensus,are designed.It is demonstrated that there is no Zeno behavior under the designed eventtriggered control.Meanwhile,it is proved that for an arbitrary initial state of the system,group consensus within the settling time could be obtained under the proposed control protocols by using matrix analysis and graph theory.Finally,a series of numerical examples are propounded to illustrate the performance of the proposed control protocol.
基金Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004)National Natural Science Foundation of China (42275020)+1 种基金Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (311021001)Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies (2020B1212060025)。
文摘Concurrent extreme weather events in geographically distant areas potentially cause high-end risks for societies.By using network analysis,the present study managed to identify significant nearly-simultaneous occurrences of heatwaves between the grid cells in East Asia and Eastern Europe,even though they are geographically far away from each other.By further composite analysis,this study revealed that hot events first occurred in Eastern Europe,typically with a time lag of3-4 days before the East Asian heatwave events.An eastward propagating atmospheric wave train,known as the circumglobal teleconnection(CGT)pattern,bridged the sequent occurrences of extreme events in these two remote regions.Atmospheric blockings,amplified by surface warming over Eastern Europe,not only enhanced local heat extremes but also excited a CGT-like pattern characterized by alternative anomalies of high and low pressures.Subsequent downstream anticyclones in the middle and upper troposphere reduced local cloud cover and increased downward solar radiation,thereby facilitating the formation of heatwaves over East Asia.Nearly half of East Asian heatwave events were preceded by Eastern European heatwave events in the 10-day time range before East Asian heatwave events.This investigation of heatwave teleconnection in the two distant regions exhibits strong potential to improve the prediction accuracy of East Asian heatwaves.
基金the financial support from the Institute for Quantum Chemical Exploration(IQCE)
文摘Highly dispersed palladium nanoparticles were synthesized in the presence of immobilized ionic liquid on mesoporous silica SBA-15.PdNPs(2.4 nm)_me-Im@SBA-15 catalyst was prepared by the reduction using NaBH_4 as the reducing agent with controlled feed rate and has been investigated as ligand-free catalyst for Suzuki–Miyaura cross-coupling reaction at room temperature in aqueous solution under air.PdNPs catalyst was also prepared in situ from PdCl4_me-Im@SBA-15 during the reaction and demonstrated high activity and stability towards nitrobenzene hydrogenation at high temperature. Both catalysts were reusable at least for four recycle processes without significant loss in activity with simple procedure. The catalysts were characterized by TEM, EXAFS, FTIR and XPS.
基金supported by the National Key R&D Program of China(Grant No.2021YFB3900502)the Scientific Research and Development Program of China Railway(K2019G008)the Tianjin Intelligent Manufacturing Special Fund Project(No.20201198).
文摘Arbitrary‐oriented object detection is widely used in aerial image applications because of its efficient object representation.However,the use of oriented bounding box aggravates the imbalance between positive and negative samples when using one‐stage object detectors,which seriously decreases the detection accuracy.We believe that it is the anchor learning strategy(ALS)used by such detectors that needs to take the responsibility.In this study,three perspectives on ALS design were summarised and ALS—Performance Releaser with Smart Anchor Learning(PRSAL)was proposed.Performance Releaser with Smart Anchor Learning is a dynamic ALS that utilises anchor classification ability as an equivalent indicator to anchor box regression ability,this allows anchors with high detection potential to be filtered out in a more reasonable way.At the same time,PRSAL focuses more on anchor potential and it is able to automatically select a number of positive samples that far exceed that of other methods by activating anchors that previously had a low spatial overlap,thereby releasing the detection performance.We validate the PRSAL using three remote sensing datasets—HRSC2016,DOTA and UCAS‐AOD as well as one scene text dataset—ICDAR 2013.The experimental results show that the proposed method gives substantially better results than existing models.
基金We thank research center“Symbiosis”and immunochemistry laboratory IBPPM RAS for their support with immunofuorescence analysis and confocal microscopy within Project No.GR 121031100266-3SGO,FI,SA,BI,TA,DA,ZM,ED,AV,EA,VV,TA,KV,MM,and MA were supported by grant(No.23-75-30001)+1 种基金the Russian Science Foundation,DA and ED were supported by Grant(No.21-75-10088)the Russian Science Foundation and by Grant from the Russian Ministry of Science and High Education(No.075-15-2022-1094).
文摘With the increase in the aging population,the global number of people with Alzheimer’s disease(AD)progressively increased worldwide.The situation is aggravated by the fact that there is no the efective pharmacological therapy of AD.Photobiomodulation(PBM)is non-pharmacological approach that has shown very promising results in the therapy of AD in pilot clinical and animal studies.However,the mechanisms of therapeutic efects of PBM for AD are poorly understood.In this study on mice,we demonstrate that photodynamic efects of 5-aminolevulenic acid and laser 635 nm cause reduction of network of the meningeal lymphatic vessels(MLVs)leading to suppression of lymphatic removal of beta-amyloid(Aβ)from the right lateral ventricle and the hippocampus.Using the original protocol of PBM under electroencephalographic monitoring of wakefulness and sleep stages in non-anesthetized mice,we discover that the 7-day course of PBM during deep sleep vs.wakefulness provides better restoration of clearance of Aβfrom the ventricular system of the brain and the hippocampus.Our results shed light on the mechanism of PBM and show the stimulating efects of PBM on the brain lymphatic drainage that promotes transport of Aβvia the lymphatic pathway.The efects of PBM on the brain lymphatics in sleeping brain open a new niche in the study of restorative functions of sleep as well as it is an important informative platform for the development of innovative smart sleep technologies for the therapy of AD.
