To address the limitations of the sand cat swarm optimization(SCSO) algorithm which are slow convergence and low accuracy in complex problems,this study proposes an improved SCSO(ISCSO) algorithm that integrates multi...To address the limitations of the sand cat swarm optimization(SCSO) algorithm which are slow convergence and low accuracy in complex problems,this study proposes an improved SCSO(ISCSO) algorithm that integrates multiple enhancement strategies.Firstly,Kent chaotic mapping initializes the population for uniform distribution.Secondly,somersault foraging strategy is introduced during the search and attack phases,allowing the algorithm to escape local optima by intercepting evasive prey.Simultaneously,an adaptive Lévy flight strategy is incorporated into the attack phase to bolster global exploration.Finally,the vertical and horizontal crossover strategy is implemented to enhance population diversity.The performance of the proposed algorithm is evaluated using 16 benchmark test functions.The experimental results demonstrate that ISCSO significantly outperforms the original SCSO and shows notable advantages over other metaheuristic algorithms.Furthermore,application to a pressure vessel design problem verifies ISCSO's effectiveness in solving practical engineering optimization challenges.展开更多
Psychophysical experiments on human and animal subjects have proven that aged individuals show significantly reduced visual contrast sensitivity compared with young adults.To uncover the possible neural mechanisms,we ...Psychophysical experiments on human and animal subjects have proven that aged individuals show significantly reduced visual contrast sensitivity compared with young adults.To uncover the possible neural mechanisms,we used extracellular single-unit recording techniques to examine the response of V1（primary visual cortex） neurons as a function of visual stimulus contrast in both old and young adult cats（Felis catus）.The mean contrast sensitivity of V1 neurons to visual stimuli in old cats decreased significantly relative to young adult cats,consistent with findings reported in old primates.These results indicate that aging can affect contrast sensitivity of visual cortical cells in both primate and non-primate mammalian animals,and might contribute to the reduction of perceptual visual contrast sensitivity in aged individuals.Further,V1 cells of old cats exhibited increased responsiveness,decreased signal-to-noise ratio,and enlarged receptive field（RF） size compared with that of young adult cats,which indicated that decreased contrast sensitivity of V1 neurons accompanied a reduction of intracortical inhibition during senescence.展开更多
With the large-scale integration of renewable energy sources into the grid,distribution networks are increasingly challenged by issues related to renewable energy accommodation and the mainte-nance of power quality st...With the large-scale integration of renewable energy sources into the grid,distribution networks are increasingly challenged by issues related to renewable energy accommodation and the mainte-nance of power quality stability.To address the challenge that existing partitioning methods are inad-equate for the planning and operation needs of active distribution networks under frequently changing power flow conditions,a three-stage dynamic partitioning approach is proposed based on an im-proved sand cat swarm optimization(ISCSO)algorithm.Firstly,a comprehensive dynamic partitio-ning index is developed by integrating both structural and functional metrics,including modularity,voltage regulation capability,and regional renewable energy accommodation capacity.Secondly,to overcome the limitations of the conventional sand cat swarm optimization,namely its weak global ex-ploration ability and tendency to fall into local optima in the later optimization stages,chaotic map-ping is employed to initialize a uniformly distributed population.A nonlinear sensitivity mechanism is introduced to balance global exploration and local exploitation,alongside the design of a particle encoding and position updating scheme tailored for dynamic partitioning.Furthermore,a‘state re-tention-local adjustment-global reconstruction’partitioning structure is developed.To avoid unnec-essary partition changes under minor source-load fluctuations,the concept of overlapping nodes is introduced,enabling fine-tuned adjustments under such conditions.Finally,two experimental sce-narios are designed to validate the proposed method.Simulation results demonstrate strong electrical coupling performance and show that the method enhances voltage regulation and renewable energy integration capabilities across regions.展开更多
Evolutionary algorithms have been extensively utilized in practical applications.However,manually designed population updating formulas are inherently prone to the subjective influence of the designer.Genetic programm...Evolutionary algorithms have been extensively utilized in practical applications.However,manually designed population updating formulas are inherently prone to the subjective influence of the designer.Genetic programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world problems.This paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human intervention.Partial modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the algorithm.By designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update formula.The Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the CSO.To validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark suite.Furthermore,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking process.The experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.展开更多
Dear editor,As of 2023,the domestic cat population in China reached 65 million,surpassing dogs to become the most numerous companion animal in the country.Feline calicivirus(FCV)infection,one of the three most prevale...Dear editor,As of 2023,the domestic cat population in China reached 65 million,surpassing dogs to become the most numerous companion animal in the country.Feline calicivirus(FCV)infection,one of the three most prevalent infectious diseases in cats,poses a severe threat to feline health.FCV,classified under the Caliciviridae family(genus Vesivirus).展开更多
基金Supported by the National Key R&D Program of China (No.2022ZD0119000)the Natural Science Foundation of Shaanxi Province (No.2025JC-YBMS-736,2025JC-YBMS-343)Shaanxi Province Key Research and Development Project (2025CY-YBXM-061)。
文摘To address the limitations of the sand cat swarm optimization(SCSO) algorithm which are slow convergence and low accuracy in complex problems,this study proposes an improved SCSO(ISCSO) algorithm that integrates multiple enhancement strategies.Firstly,Kent chaotic mapping initializes the population for uniform distribution.Secondly,somersault foraging strategy is introduced during the search and attack phases,allowing the algorithm to escape local optima by intercepting evasive prey.Simultaneously,an adaptive Lévy flight strategy is incorporated into the attack phase to bolster global exploration.Finally,the vertical and horizontal crossover strategy is implemented to enhance population diversity.The performance of the proposed algorithm is evaluated using 16 benchmark test functions.The experimental results demonstrate that ISCSO significantly outperforms the original SCSO and shows notable advantages over other metaheuristic algorithms.Furthermore,application to a pressure vessel design problem verifies ISCSO's effectiveness in solving practical engineering optimization challenges.
基金Supported by National Natural Science Foundation of China(31171082)Natural Science Foundation of Anhui Province(070413138)the Key Research Foundation of Anhui Province Education Department(KJ2009A167)
文摘Psychophysical experiments on human and animal subjects have proven that aged individuals show significantly reduced visual contrast sensitivity compared with young adults.To uncover the possible neural mechanisms,we used extracellular single-unit recording techniques to examine the response of V1（primary visual cortex） neurons as a function of visual stimulus contrast in both old and young adult cats（Felis catus）.The mean contrast sensitivity of V1 neurons to visual stimuli in old cats decreased significantly relative to young adult cats,consistent with findings reported in old primates.These results indicate that aging can affect contrast sensitivity of visual cortical cells in both primate and non-primate mammalian animals,and might contribute to the reduction of perceptual visual contrast sensitivity in aged individuals.Further,V1 cells of old cats exhibited increased responsiveness,decreased signal-to-noise ratio,and enlarged receptive field（RF） size compared with that of young adult cats,which indicated that decreased contrast sensitivity of V1 neurons accompanied a reduction of intracortical inhibition during senescence.
基金Supported by the Technology Project of State Grid Corporation Headquarters(No.5100-202322029A-1-1-ZN)the 2024 Youth Science Foun-dation Project(No.62303006).
文摘With the large-scale integration of renewable energy sources into the grid,distribution networks are increasingly challenged by issues related to renewable energy accommodation and the mainte-nance of power quality stability.To address the challenge that existing partitioning methods are inad-equate for the planning and operation needs of active distribution networks under frequently changing power flow conditions,a three-stage dynamic partitioning approach is proposed based on an im-proved sand cat swarm optimization(ISCSO)algorithm.Firstly,a comprehensive dynamic partitio-ning index is developed by integrating both structural and functional metrics,including modularity,voltage regulation capability,and regional renewable energy accommodation capacity.Secondly,to overcome the limitations of the conventional sand cat swarm optimization,namely its weak global ex-ploration ability and tendency to fall into local optima in the later optimization stages,chaotic map-ping is employed to initialize a uniformly distributed population.A nonlinear sensitivity mechanism is introduced to balance global exploration and local exploitation,alongside the design of a particle encoding and position updating scheme tailored for dynamic partitioning.Furthermore,a‘state re-tention-local adjustment-global reconstruction’partitioning structure is developed.To avoid unnec-essary partition changes under minor source-load fluctuations,the concept of overlapping nodes is introduced,enabling fine-tuned adjustments under such conditions.Finally,two experimental sce-narios are designed to validate the proposed method.Simulation results demonstrate strong electrical coupling performance and show that the method enhances voltage regulation and renewable energy integration capabilities across regions.
文摘Evolutionary algorithms have been extensively utilized in practical applications.However,manually designed population updating formulas are inherently prone to the subjective influence of the designer.Genetic programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world problems.This paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human intervention.Partial modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the algorithm.By designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update formula.The Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the CSO.To validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark suite.Furthermore,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking process.The experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.
基金supported by grants from the National Key Research and Development Program of China(Grant No.2022YFD1800100)National Natural Science Foundation of China(Grant No.32272982)Natural Science Foundation of Shanghai(Grant No.23ZR1477100).
文摘Dear editor,As of 2023,the domestic cat population in China reached 65 million,surpassing dogs to become the most numerous companion animal in the country.Feline calicivirus(FCV)infection,one of the three most prevalent infectious diseases in cats,poses a severe threat to feline health.FCV,classified under the Caliciviridae family(genus Vesivirus).
