In solving many-objective optimization problems(MaO Ps),existing nondominated sorting-based multi-objective evolutionary algorithms suffer from the fast loss of selection pressure.Most candidate solutions become nondo...In solving many-objective optimization problems(MaO Ps),existing nondominated sorting-based multi-objective evolutionary algorithms suffer from the fast loss of selection pressure.Most candidate solutions become nondominated during the evolutionary process,thus leading to the failure of producing offspring toward Pareto-optimal front with diversity.Can we find a more effective way to select nondominated solutions and resolve this issue?To answer this critical question,this work proposes to evolve solutions through line complex rather than solution points in Euclidean space.First,Plücker coordinates are used to project solution points to line complex composed of position vectors and momentum ones.Besides position vectors of the solution points,momentum vectors are used to extend the comparability of nondominated solutions and enhance selection pressure.Then,a new distance function designed for high-dimensional space is proposed to replace Euclidean distance as a more effective distancebased estimator.Based on them,a novel many-objective evolutionary algorithm(MaOEA)is proposed by integrating a line complex-based environmental selection strategy into the NSGAⅢframework.The proposed algorithm is compared with the state of the art on widely used benchmark problems with up to 15 objectives.Experimental results demonstrate its superior competitiveness in solving MaOPs.展开更多
Understanding the factors shaping species＇ distributions is a key longstanding topic in ecology with unresolved issues. The aims were to test whether the relative contribution of abiotic factors that set the geograph...Understanding the factors shaping species＇ distributions is a key longstanding topic in ecology with unresolved issues. The aims were to test whether the relative contribution of abiotic factors that set the geographical range of freshwater fish species may vary spatially and/or may depend on the geographical extent that is being considered. The relative contribution of factors, to discriminate between the conditions prevailing in the area where the species is present and those existing in the considered extent, was estimated with the instability index included in the R pack- age SPEDInstabR. We used 3 different extent sizes： 1） each river basin where the species is present （local）; 2） all river basins where the species is present （regional）; and 3） the whole Earth （global）. We used a data set of 16,543 freshwater fish species with a total of 845,764 geographical records, together with bioclimatic and topographic variables. Factors associated with tempera- ture and altitude show the highest relative contribution to explain the distribution of freshwater fishes at the smaller considered extent. Altitude and a mix of factors associated with temperature and precipitation were more important when using the regional extent. Factors associated with precipitation show the highest contribution when using the global extent. There was also spatial variability in the importance of factors, both between species and within species and from region to region. Factors associated with precipitation show a clear latitudinal trend of decreasing in importance toward the equator.展开更多
IBC Advanced Technologies’ Molecular Recognition Technology(MRT) SuperLig products selectively and rapidly bind with target species enabling their selective removal from solutions.The MRT process can produce a high p...IBC Advanced Technologies’ Molecular Recognition Technology(MRT) SuperLig products selectively and rapidly bind with target species enabling their selective removal from solutions.The MRT process can produce a high purity separation product of maximum added value at a competitive cost.SuperLig products have high selectivity for many target species which can include metal ions,anions,and neutral molecules.In operation,the SuperLig product is first placed in a packed column.A solution containing a mixture of the target species and other chemical species is then passed through the column.The target species is removed selectively by the SuperLig product,the column is washed to remove residual feed solution,and the target species is recovered by a minimal quantity of eluent.The result is a pure and concentrated species that can be kept for its value or disposed of safely.The process is environmentally and ecologically friendly with no organic solvents being used.This paper provides a review of some examples of applications of MRT to separations of interest to the Chinese metallurgical industry.Included are several applications of MRT,including Pd separations from Pt metal refinery streams and low-grade spent catalyst wastes,Rh recovery from spent auto catalyst and other feeds,Re removal from selected impurity ions,Cd removal from Co electrolyte,Bi removal from Cu electrolyte,In and Ge separations from difficult matrices,and removal of bivalent first transition series and other metal ions from acid mine drainage(Berkeley Pit,Montana).Finally,the potential application of MRT to separations involving the recovery of rare earth metals and Li from low-level waste solutions and end-of-life products is discussed.展开更多
Artificial Bee Colony(ABC)algorithm is a classical Swarm Intelligence Optimization Algorithm(SIOA),which has been widely used to solve various optimization problems.However,these problems mainly focus on single-object...Artificial Bee Colony(ABC)algorithm is a classical Swarm Intelligence Optimization Algorithm(SIOA),which has been widely used to solve various optimization problems.However,these problems mainly focus on single-objective and ordinary Multi-objective Optimization Problems(MOPs).For Many-objective Optimization Problems(MaOPs),ABC shows some difficulties:(1)the selection pressure based on Pareto dominance degrades severely;and(2)it is not easy to balance convergence and population diversity.In this paper,a new Many-Objective ABC variant with Hybrid Strategies(namely HSMaOABC)is proposed to deal with MaOPs.Firstly,the fitness function is redefined based on objective values and cosine similarity to handle multiple objectives.Then,a new selection method is designed on the basis of the new fitness function.In order to enhance convergence,an elite set guided search strategy is utilized for the employed bee stage,and dimensional learning is incorporated for the onlooker bee stage.Finally,a modified environmental selection strategy is employed based on Penalty-based Boundary Intersection(PBI)distance.To evaluate the performance of HSMaOABC,the DTLZ and MaF benchmarks with 3,5,8,and 15 objectives are used.Experimental results demonstrate that HSMaOABC obtains competitive performance when compared with nine other well-known approaches.展开更多
Environmental selection and neutral processes drive diversification and evolution,thereby influencing the biodiversity and biogeography of the microbiome.The deep sea,with its vast and complex geological structures,is...Environmental selection and neutral processes drive diversification and evolution,thereby influencing the biodiversity and biogeography of the microbiome.The deep sea,with its vast and complex geological structures,is ideal for studying microbial biogeography;however,it remains underexplored due to technical limitations.Based on the Anna Karenina principle,we hypothesize that environmental selection induced by complex topography increases community heterogeneity,which further leads to instability of deep-sea microbial communities.To test this,near-bottom water samples were collected from the trench ridge cross-linked zone with complex topography and from the abyssal plain in the western Pacific Ocean.Utilizing next-generation and thirdgeneration sequencing technologies,we analyzed population expansion,ecological niches,and community structure and dynamics,including beta diversity,stability and assembly process,of the deep-sea ciliates.The results indicated that both environmental selection and neutral processes were important factors driving the ciliate communities,while their relative importance varied across different topographies in the deep sea.In the topographically complex region,environmental selection promoted the population expansion of specific ciliate species,indicated by higher haplotype diversity and increased distinct amplicon sequence variants aligning to the same species.This specific population expansion resulted in higher alpha diversity but lower beta diversity.Higher niche breadth and niche overlap values,and more positive interactions,were observed in the cooccurrence network of ciliates in the topographically complex region,leading to higher community stability.In the abyssal plain,however,neutral processes dominated the ciliate community assembly,with limited population expansion,lower alpha diversity but higher community heterogeneity.These findings contradict our hypothesis based on the Anna Karenina principle.Our study challenges the Anna Karenina principle and provides novel insights into the diversity and dynamics of deep-sea ciliate communities under varying topographic complexities from individual species to community-wide scales.展开更多
基金supported in part by the National Natural Science Foundation of China(51775385)the Natural Science Foundation of Shanghai(23ZR1466000)+3 种基金the Shanghai Industrial Collaborative Science and Technology Innovation Project(2021-cyxt2-kj10)the Innovation Program of Shanghai Municipal Education Commission(202101070007E00098)the Innovation Project of Engineering Research Center of Integration and Application of Digital Learning Technology of MOE(1221046)the Program to Cultivate Middle-Aged and Young Cadre Teacher of Jiangsu Province。
文摘In solving many-objective optimization problems(MaO Ps),existing nondominated sorting-based multi-objective evolutionary algorithms suffer from the fast loss of selection pressure.Most candidate solutions become nondominated during the evolutionary process,thus leading to the failure of producing offspring toward Pareto-optimal front with diversity.Can we find a more effective way to select nondominated solutions and resolve this issue?To answer this critical question,this work proposes to evolve solutions through line complex rather than solution points in Euclidean space.First,Plücker coordinates are used to project solution points to line complex composed of position vectors and momentum ones.Besides position vectors of the solution points,momentum vectors are used to extend the comparability of nondominated solutions and enhance selection pressure.Then,a new distance function designed for high-dimensional space is proposed to replace Euclidean distance as a more effective distancebased estimator.Based on them,a novel many-objective evolutionary algorithm(MaOEA)is proposed by integrating a line complex-based environmental selection strategy into the NSGAⅢframework.The proposed algorithm is compared with the state of the art on widely used benchmark problems with up to 15 objectives.Experimental results demonstrate its superior competitiveness in solving MaOPs.
文摘Understanding the factors shaping species＇ distributions is a key longstanding topic in ecology with unresolved issues. The aims were to test whether the relative contribution of abiotic factors that set the geographical range of freshwater fish species may vary spatially and/or may depend on the geographical extent that is being considered. The relative contribution of factors, to discriminate between the conditions prevailing in the area where the species is present and those existing in the considered extent, was estimated with the instability index included in the R pack- age SPEDInstabR. We used 3 different extent sizes： 1） each river basin where the species is present （local）; 2） all river basins where the species is present （regional）; and 3） the whole Earth （global）. We used a data set of 16,543 freshwater fish species with a total of 845,764 geographical records, together with bioclimatic and topographic variables. Factors associated with tempera- ture and altitude show the highest relative contribution to explain the distribution of freshwater fishes at the smaller considered extent. Altitude and a mix of factors associated with temperature and precipitation were more important when using the regional extent. Factors associated with precipitation show the highest contribution when using the global extent. There was also spatial variability in the importance of factors, both between species and within species and from region to region. Factors associated with precipitation show a clear latitudinal trend of decreasing in importance toward the equator.
文摘IBC Advanced Technologies’ Molecular Recognition Technology(MRT) SuperLig products selectively and rapidly bind with target species enabling their selective removal from solutions.The MRT process can produce a high purity separation product of maximum added value at a competitive cost.SuperLig products have high selectivity for many target species which can include metal ions,anions,and neutral molecules.In operation,the SuperLig product is first placed in a packed column.A solution containing a mixture of the target species and other chemical species is then passed through the column.The target species is removed selectively by the SuperLig product,the column is washed to remove residual feed solution,and the target species is recovered by a minimal quantity of eluent.The result is a pure and concentrated species that can be kept for its value or disposed of safely.The process is environmentally and ecologically friendly with no organic solvents being used.This paper provides a review of some examples of applications of MRT to separations of interest to the Chinese metallurgical industry.Included are several applications of MRT,including Pd separations from Pt metal refinery streams and low-grade spent catalyst wastes,Rh recovery from spent auto catalyst and other feeds,Re removal from selected impurity ions,Cd removal from Co electrolyte,Bi removal from Cu electrolyte,In and Ge separations from difficult matrices,and removal of bivalent first transition series and other metal ions from acid mine drainage(Berkeley Pit,Montana).Finally,the potential application of MRT to separations involving the recovery of rare earth metals and Li from low-level waste solutions and end-of-life products is discussed.
基金supported by the National Natural Science Foundation of China(No.62166027)the Jiangxi Provincial Natural Science Foundation(No.20212ACB212004).
文摘Artificial Bee Colony(ABC)algorithm is a classical Swarm Intelligence Optimization Algorithm(SIOA),which has been widely used to solve various optimization problems.However,these problems mainly focus on single-objective and ordinary Multi-objective Optimization Problems(MOPs).For Many-objective Optimization Problems(MaOPs),ABC shows some difficulties:(1)the selection pressure based on Pareto dominance degrades severely;and(2)it is not easy to balance convergence and population diversity.In this paper,a new Many-Objective ABC variant with Hybrid Strategies(namely HSMaOABC)is proposed to deal with MaOPs.Firstly,the fitness function is redefined based on objective values and cosine similarity to handle multiple objectives.Then,a new selection method is designed on the basis of the new fitness function.In order to enhance convergence,an elite set guided search strategy is utilized for the employed bee stage,and dimensional learning is incorporated for the onlooker bee stage.Finally,a modified environmental selection strategy is employed based on Penalty-based Boundary Intersection(PBI)distance.To evaluate the performance of HSMaOABC,the DTLZ and MaF benchmarks with 3,5,8,and 15 objectives are used.Experimental results demonstrate that HSMaOABC obtains competitive performance when compared with nine other well-known approaches.
基金supported by the National Key Research and Development Program of China(No.2022YFC2803804)the National Natural Science Foundation of China(Nos.42376134 and 41930533)+1 种基金the Youth Innovation Promotion Association CAS(No.2022206)Data and samples were collected onboard of R/V"Kexue"implementing the open research cruise NORC2019-09 supported by the NSFC Ship Time Sharing Project(project number:41849909).
文摘Environmental selection and neutral processes drive diversification and evolution,thereby influencing the biodiversity and biogeography of the microbiome.The deep sea,with its vast and complex geological structures,is ideal for studying microbial biogeography;however,it remains underexplored due to technical limitations.Based on the Anna Karenina principle,we hypothesize that environmental selection induced by complex topography increases community heterogeneity,which further leads to instability of deep-sea microbial communities.To test this,near-bottom water samples were collected from the trench ridge cross-linked zone with complex topography and from the abyssal plain in the western Pacific Ocean.Utilizing next-generation and thirdgeneration sequencing technologies,we analyzed population expansion,ecological niches,and community structure and dynamics,including beta diversity,stability and assembly process,of the deep-sea ciliates.The results indicated that both environmental selection and neutral processes were important factors driving the ciliate communities,while their relative importance varied across different topographies in the deep sea.In the topographically complex region,environmental selection promoted the population expansion of specific ciliate species,indicated by higher haplotype diversity and increased distinct amplicon sequence variants aligning to the same species.This specific population expansion resulted in higher alpha diversity but lower beta diversity.Higher niche breadth and niche overlap values,and more positive interactions,were observed in the cooccurrence network of ciliates in the topographically complex region,leading to higher community stability.In the abyssal plain,however,neutral processes dominated the ciliate community assembly,with limited population expansion,lower alpha diversity but higher community heterogeneity.These findings contradict our hypothesis based on the Anna Karenina principle.Our study challenges the Anna Karenina principle and provides novel insights into the diversity and dynamics of deep-sea ciliate communities under varying topographic complexities from individual species to community-wide scales.
