Dynamic Individual Selection and Crossover Boosted Forensic-based Investigation Algorithm for Global Optimization and Feature Selection

The advent of Big Data has rendered Machine Learning tasks more intricate as they frequently involve higher-dimensional data.Feature Selection(FS)methods can abate the complexity of the data and enhance the accuracy,generalizability,and interpretability of models.Meta-heuristic algorithms are often utilized for FS tasks due to their low requirements and efficient performance.This paper introduces an augmented Forensic-Based Investigation algorithm(DCFBI)that incorporates a Dynamic Individual Selection(DIS)and crisscross(CC)mechanism to improve the pursuit phase of the FBI.Moreover,a binary version of DCFBI(BDCFBI)is applied to FS.Experiments conducted on IEEE CEC 2017 with other metaheuristics demonstrate that DCFBI surpasses them in search capability.The influence of different mechanisms on the original FBI is analyzed on benchmark functions,while its scalability is verified by comparing it with the original FBI on benchmarks with varied dimensions.BDCFBI is then applied to 18 real datasets from the UCI machine learning database and the Wieslaw dataset to select near-optimal features,which are then compared with six renowned binary metaheuristics.The results show that BDCFBI can be more competitive than similar methods and acquire a subset of features with superior classification accuracy.

Single-atom catalysis for organic reactions

Metal-based catalysis,including homogeneous and heterogeneous catalysis,plays a significant role in the modern chemical industry.Heterogeneous catalysis is widely used due to the high efficiency,easy catalyst separation and recycling.However,the metal-utilization efficiency for conventional heterogeneous catalysts needs further improvement compared to homogeneous catalyst.To tackle this,the pursing of heterogenizing homogeneous catalysts has always been attractive but challenging.As a recently emerging class of catalytic material,single-atom catalysts(SACs)are expected to bridge homogeneous and heterogeneous catalytic process in organic reactions and have arguably become the most active new frontier in catalysis field.In this review,a brief introduction and development history of single-atom catalysis and SACs involved organic reactions are documented.In addition,recent advances in SACs and their practical applications in organic reactions such as oxidation,reduction,addition,coupling reaction,and other organic reactions are thoroughly reviewed.To understand structure-property relationships of single-atom catalysis in organic reactions,active sites or coordination structure,metal atom-utilization efficiency(e.g.,turnover frequency,TOF calculated based on active metal)and catalytic performance(e.g.,conversion and selectivity)of SACs are comprehensively summarized.Furthermore,the application limitations,development trends,future challenges and perspective of SAC for organic reaction are discussed.

Multi-strategies Boosted Mutative Crow Search Algorithm for Global Tasks:Cases of Continuous and Discrete Optimization

Crow Search Algorithm(CSA)is a swarm-based single-objective optimizer proposed in recent years,which tried to inspire the behavior of crows that hide foods in different locations and retrieve them when needed.The original version of the CSA has simple parameters and moderate performance.However,it often tends to converge slowly or get stuck in a locally optimal region due to a missed harmonizing strategy during the exploitation and exploration phases.Therefore,strategies of mutation and crisscross are combined into CSA(CCMSCSA)in this paper to improve the performance and provide an efficient optimizer for various optimization problems.To verify the superiority of CCMSCSA,a set of comparisons has been performed reasonably with some well-established metaheuristics and advanced metaheuristics on 15 benchmark functions.The experimental results expose and verify that the proposed CCMSCSA has meaningfully improved the convergence speed and the ability to jump out of the local optimum.In addition,the scalability of CCMSCSA is analyzed,and the algorithm is applied to several engineering problems in a constrained space and feature selection problems.Experimental results show that the scalability of CCMSCSA has been significantly improved and can find better solutions than its competitors when dealing with combinatorial optimization problems.The proposed CCMSCSA performs well in almost all experimental results.Therefore,we hope the researchers can see it as an effective method for solving constrained and unconstrained optimization problems.

Female preferences for male golden snub-nosed monkeys vary with male age and social context

Age is a key factor affecting sexual selection,as many physical and social traits are age-related.Although studies of primate mate choice often consider particular age-related traits,few consider the collective effects of male age.We tested the hypothesis that female golden snub-nosed monkeys Rhinopithecus roxellana prefer prime aged males(10-15 years)over younger and older males.We examined a habituated,provisioned troop during a 3-year study in the Qinling Mountains,China.Prime age males were more likely to be resident males of 1-male units(OMUs)than males of other ages.Since females are free to transfer between OMUs,the number of females per OMU can be indicative of female preferences.We examined the number of females per OMU,and found that it increased with resident male age up to 7-8 years,and declined after 12 years,such that prime age resident males had more females than other resident males.Females also initiated extra-unit copulations with high-ranking prime age males at significantly higher rates than with other males.Nevertheless,females tended to transfer from OMUs with high-ranking,older resident males to those with low-ranking,younger resident males.Thus,females appear to use different strategies when choosing social mates and extra-unit mates(i.e.,different social contexts).We speculate that females may perceive early signs of aging in males and trade off the benefits and costs of high rank versus male senescence.This study lays the groundwork for future studies that examine possible direct and indirect benefits of such strategies.