Copper matrix composites doped with ceramic particles are known to effectively enhance the mechanical properties,thermal expansion behavior and high-temperature stability of copper while maintaining high thermal and e...Copper matrix composites doped with ceramic particles are known to effectively enhance the mechanical properties,thermal expansion behavior and high-temperature stability of copper while maintaining high thermal and electrical conductivity.This greatly expands the applications of copper as a functional material in thermal and conductive components,including electronic packaging materials and heat sinks,brushes,integrated circuit lead frames.So far,endeavors have been focusing on how to choose suitable ceramic components and fully exert strengthening effect of ceramic particles in the copper matrix.This article reviews and analyzes the effects of preparation techniques and the characteristics of ceramic particles,including ceramic particle content,size,morphology and interfacial bonding,on the diathermancy,electrical conductivity and mechanical behavior of copper matrix composites.The corresponding models and influencing mechanisms are also elaborated in depth.This review contributes to a deep understanding of the strengthening mechanisms and microstructural regulation of ceramic particle reinforced copper matrix composites.By more precise design and manipulation of composite microstructure,the comprehensive properties could be further improved to meet the growing demands of copper matrix composites in a wide range of application fields.展开更多
Applications based on Wireless Sensor Networks(WSN)have shown to be quite useful in monitoring a particular geographic area of interest.Relevant geometries of the surrounding environment are essential to establish a s...Applications based on Wireless Sensor Networks(WSN)have shown to be quite useful in monitoring a particular geographic area of interest.Relevant geometries of the surrounding environment are essential to establish a successful WSN topology.But it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes(SN)in a WSN is always a challenging task.In this research paper,Distance Matrix and Markov Chain(DM-MC)model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the node.The method further employs a Markov Chain Model(MCM)for energy optimization and interference reduction.Experiments are performed against two well-known models,and the results demonstrate that the proposed algorithm improves performance by using less network resources when compared to the existing models.Transition probability is used in the Markova chain to sustain higher energy nodes.Finally,the proposed Distance Matrix and Markov Chain model decrease energy use by 31%and 25%,respectively,compared to the existing DV-Hop and CSA methods.The experimental results were performed against two proven models,Distance VectorHop Algorithm(DV-HopA)and Crow Search Algorithm(CSA),showing that the proposed DM-MC model outperforms both the existing models regarding localization accuracy and Energy Consumption(EC).These results add to the credibility of the proposed DC-MC model as a better model for employing node localization while establishing a WSN framework.展开更多
Traditional data driven fault detection methods assume that the process operates in a single mode so that they cannot perform well in processes with multiple operating modes. To monitor multimode processes effectively...Traditional data driven fault detection methods assume that the process operates in a single mode so that they cannot perform well in processes with multiple operating modes. To monitor multimode processes effectively,this paper proposes a novel process monitoring scheme based on orthogonal nonnegative matrix factorization(ONMF) and hidden Markov model(HMM). The new clustering technique ONMF is employed to separate data from different process modes. The multiple HMMs for various operating modes lead to higher modeling accuracy.The proposed approach does not presume the distribution of data in each mode because the process uncertainty and dynamics can be well interpreted through the hidden Markov estimation. The HMM-based monitoring indication named negative log likelihood probability is utilized for fault detection. In order to assess the proposed monitoring strategy, a numerical example and the Tennessee Eastman process are used. The results demonstrate that this method provides efficient fault detection performance.展开更多
Objective With the development of analytic technologies, in-situ dating on U-bearing oxide minerals （e.g., cassiterite, rutile and baddeleyite） has been widely used in geological chronological researches and has at...Objective With the development of analytic technologies, in-situ dating on U-bearing oxide minerals （e.g., cassiterite, rutile and baddeleyite） has been widely used in geological chronological researches and has attracted remarkable attention to explore evolution of the earth and obtain age information of various geological processes. Matrix effect related studies are especially important during in-situ U- Pb dating based on Laser Ablation Multiple Collector Inductively Coupled Plasma Mass Spectrometry （LA-MC- ICPMS）. However, to our knowledge, only few thorough and systematical matrix effect study of U-bearing oxide minerals has been reported. In this study, we systematically analyzed the matrix effect of U-bearing oxide minerals in order to take place the standards which are difficult to prepare with available standards.展开更多
Regeneration in the central nervous system （CNS） is limited, and CNS damage often leads to cognitive impairment or permanent functional motor and sensory loss. Impaired regenerative capacity is multifactorial and in...Regeneration in the central nervous system （CNS） is limited, and CNS damage often leads to cognitive impairment or permanent functional motor and sensory loss. Impaired regenerative capacity is multifactorial and includes inflammation, loss of the blood-brain barrier, and alteration in the extracellular matrix （ECM）. One of the main problems is the formation of a glial scar and the production of inhibitory ECM, such as proteoglycans, that generates a physical and mechanical barrier, impeding axonal regrowth （Figure 1A）.展开更多
基金supported by National Natural Science Foundation of China(No.51971101)Science and Technology Development Program of Jilin Province,China(20230201146G X)Exploration Foundation of State Key Laboratory of Automotive Simulation and Control(asclzytsxm-202015)。
文摘Copper matrix composites doped with ceramic particles are known to effectively enhance the mechanical properties,thermal expansion behavior and high-temperature stability of copper while maintaining high thermal and electrical conductivity.This greatly expands the applications of copper as a functional material in thermal and conductive components,including electronic packaging materials and heat sinks,brushes,integrated circuit lead frames.So far,endeavors have been focusing on how to choose suitable ceramic components and fully exert strengthening effect of ceramic particles in the copper matrix.This article reviews and analyzes the effects of preparation techniques and the characteristics of ceramic particles,including ceramic particle content,size,morphology and interfacial bonding,on the diathermancy,electrical conductivity and mechanical behavior of copper matrix composites.The corresponding models and influencing mechanisms are also elaborated in depth.This review contributes to a deep understanding of the strengthening mechanisms and microstructural regulation of ceramic particle reinforced copper matrix composites.By more precise design and manipulation of composite microstructure,the comprehensive properties could be further improved to meet the growing demands of copper matrix composites in a wide range of application fields.
基金This project was funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under Grant No.(RG-91-611-42).The authors,therefore,acknowledge with thanks to DSR technical and financial support.
文摘Applications based on Wireless Sensor Networks(WSN)have shown to be quite useful in monitoring a particular geographic area of interest.Relevant geometries of the surrounding environment are essential to establish a successful WSN topology.But it is literally hard because constructing a localization algorithm that tracks the exact location of Sensor Nodes(SN)in a WSN is always a challenging task.In this research paper,Distance Matrix and Markov Chain(DM-MC)model is presented as node localization technique in which Distance Matrix and Estimation Matrix are used to identify the position of the node.The method further employs a Markov Chain Model(MCM)for energy optimization and interference reduction.Experiments are performed against two well-known models,and the results demonstrate that the proposed algorithm improves performance by using less network resources when compared to the existing models.Transition probability is used in the Markova chain to sustain higher energy nodes.Finally,the proposed Distance Matrix and Markov Chain model decrease energy use by 31%and 25%,respectively,compared to the existing DV-Hop and CSA methods.The experimental results were performed against two proven models,Distance VectorHop Algorithm(DV-HopA)and Crow Search Algorithm(CSA),showing that the proposed DM-MC model outperforms both the existing models regarding localization accuracy and Energy Consumption(EC).These results add to the credibility of the proposed DC-MC model as a better model for employing node localization while establishing a WSN framework.
基金Supported by the National Natural Science Foundation of China(61374140,61403072)
文摘Traditional data driven fault detection methods assume that the process operates in a single mode so that they cannot perform well in processes with multiple operating modes. To monitor multimode processes effectively,this paper proposes a novel process monitoring scheme based on orthogonal nonnegative matrix factorization(ONMF) and hidden Markov model(HMM). The new clustering technique ONMF is employed to separate data from different process modes. The multiple HMMs for various operating modes lead to higher modeling accuracy.The proposed approach does not presume the distribution of data in each mode because the process uncertainty and dynamics can be well interpreted through the hidden Markov estimation. The HMM-based monitoring indication named negative log likelihood probability is utilized for fault detection. In order to assess the proposed monitoring strategy, a numerical example and the Tennessee Eastman process are used. The results demonstrate that this method provides efficient fault detection performance.
基金financially supported by the National Natural Science Foundation of China(grants No.41503052 and 41373053)the National Science and Technology Infrastructure(grant No.DDK14-39)
文摘Objective With the development of analytic technologies, in-situ dating on U-bearing oxide minerals （e.g., cassiterite, rutile and baddeleyite） has been widely used in geological chronological researches and has attracted remarkable attention to explore evolution of the earth and obtain age information of various geological processes. Matrix effect related studies are especially important during in-situ U- Pb dating based on Laser Ablation Multiple Collector Inductively Coupled Plasma Mass Spectrometry （LA-MC- ICPMS）. However, to our knowledge, only few thorough and systematical matrix effect study of U-bearing oxide minerals has been reported. In this study, we systematically analyzed the matrix effect of U-bearing oxide minerals in order to take place the standards which are difficult to prepare with available standards.
文摘Regeneration in the central nervous system （CNS） is limited, and CNS damage often leads to cognitive impairment or permanent functional motor and sensory loss. Impaired regenerative capacity is multifactorial and includes inflammation, loss of the blood-brain barrier, and alteration in the extracellular matrix （ECM）. One of the main problems is the formation of a glial scar and the production of inhibitory ECM, such as proteoglycans, that generates a physical and mechanical barrier, impeding axonal regrowth （Figure 1A）.
