How ecological and evolutionary factors affect small mammal diversity in arid regions remains largely unknown.Here,we combined the largest phylogeny and occurrence dataset of Gerbillinae desert rodents to explore the ...How ecological and evolutionary factors affect small mammal diversity in arid regions remains largely unknown.Here,we combined the largest phylogeny and occurrence dataset of Gerbillinae desert rodents to explore the underlying factors shaping present-day distribution patterns.In particular,we analyzed the relative contributions of ecological and evolutionary factors on their species diversity using a variety of models.Additionally,we inferred the ancestral range and possible dispersal scenarios and estimated the diversification rate of Gerbillinae.We found that Gerbillinae likely originated in the Horn of Africa in the Middle Miocene and then dispersed and diversified across arid regions in northern and southern Africa and western and central Asia,forming their current distribution pattern.Multiple ecological and evolutionary factors jointly determine the spatial pattern of Gerbillinae diversity,but evolutionary factors(evolutionary time and speciation rate)and habitat filtering were the most important in explaining the spatial variation in species richness.Our study enhances the understanding of the diversity patterns of small mammals in arid regions and highlights the importance of including evolutionary factors when interpreting the mechanisms underlying large-scale species diversity patterns.展开更多
The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutiona...The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutionary evidence hinders true classification of O.cubicus.To clarify its evolutionary position within Tetraodontiformes,a chromosome-level genome assembly was generated,representing the most contiguous and complete genome to date for this lineage.Notably,O.cubicus possessed the largest genome within the order Tetraodontiformes,primarily due to extensive transposable element expansion.Phylogenetic analysis based on 19 whole genomes and 131 mitochondrial genomes resolved Tetraodontiformes into three major sister groups(Ostraciidae-Molidae,Tetraodontidae,and Balistidae-Monacanthidae).Comparative genomic evidence indicated that O.cubicus diverged early from the common ancestor of modern Tetraodontiformes and retained the highest number of HOX genes among surveyed taxa.Although overall genomic architecture was largely conserved,certain genetic and environmental changes may have contributed to its phenotypic adaptations,including climate cooling during the Miocene-Pliocene Transition,recent DNA and long interspersed nuclear element(LINE)transposon bursts,lineage-specific chromosomal rearrangements,and gene family expansion.Many positively selected genes and rapidly evolving genes were associated with skeletal development,including bmp7,egf7,and bmpr2.Transcriptomic comparisons between carapace and tail skin revealed various candidate genes and pathways related to carapace formation,such as postn,scpp1,and components of the TGF-βsignaling pathway.A derived amino acid substitution in eda,coupled with protein structural modeling,suggested potential molecular convergence in dermal plate formation among teleosts.These findings provide novel insights into the genomic and developmental basis of carapace evolution and coral reef-adaptation in O.cubicus,offering a strong case for evolutionary balance between genomic conservation with regulatory innovation to achieve coral reef specialization.展开更多
The livestock farming is an important pillar of the rural economy in China.To explore the impact of government technical subsidies and pollution penalties on the digital and intelligent transformation of livestock ent...The livestock farming is an important pillar of the rural economy in China.To explore the impact of government technical subsidies and pollution penalties on the digital and intelligent transformation of livestock enterprises,an evolutionary game theoretical model between the government and livestock enterprises is constructed.The interaction mechanism of the game between the government and breeding enterprises is explored,and simulation is conducted.The research results show that the combined strategy of pollution penalties and technical subsidies is the optimal strategy for the government;the system is jointly driven by government subsidies,technical costs of transformation input,public willingness,and enterprise willingness.展开更多
Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function,evolution,and design.In this study,we leveraged emerging microfluidic technology to measure cat...Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function,evolution,and design.In this study,we leveraged emerging microfluidic technology to measure catalytic constants-kcat and KM-for hundreds of diverse orthologs and mutants of adenylate kinase(ADK).We dissected this sequence-catalysis landscape's topology,navigability,and mechanistic underpinnings,revealing catalytically heterogeneous neighborhoods organized by domain architecture.展开更多
The present investigation aims at unveiling the main causes of the recorded disparate phylogeographic patterning among the two highly dispersive coastal crab species Carcinus aestuarii and Pachygrapsus marmoratus in t...The present investigation aims at unveiling the main causes of the recorded disparate phylogeographic patterning among the two highly dispersive coastal crab species Carcinus aestuarii and Pachygrapsus marmoratus in the Mediterranean Sea.For this purpose,available mitochondrial and nuclear data for both species were re-analyzed and investigated for genetic polymorphism and differentiation patterns across three defined geographic scales in their distribution ranges,but also across the same locations in the Mediterranean Sea.The temporal frame of genetic diversification was also determined for both species in order to check whether observed differences in phylogeographic patterns among these coastal decapods could be attributed to different evolutionary histories.The obtained results revealed a more variable and diversified gene pool in the green crab C.aestuarii than the one recorded in the marbled crab P.marmoratus.Lack of significant correlation between pairwise genetic dissimilarities observed among C.aestuarii populations and those detected for P.marmoratus was notably discerned across the same defined Mediterranean locations.This finding indicates that the pattern of pairwise genetic differentiation does not vary in the same way in both examined crab species.Significant outputs of population genetic differentiation,retrieved within both species,were shown to be differently associated with the potential effects of various kinds of isolation processes(related to geography,environment and biogeographic boundary).Evolutionary history reconstruction showed older genetic diversification event in C.aestuarii than the one recorded in P.marmoratus.These recorded temporal frames suggest different modes of genetic diversification in both crab species(glacial vicariance for C.aestuarii and interglacial dispersal for P.marmoratus).They may also provide an explanation for the recorded differences in variation of patterns of population genetic diversity and structure,when integrated with species ecological requirements and life-history traits.展开更多
In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential r...In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential reasoning(ER)methodology.The proposed approach uses q-RLDFS in order to represent the evaluating values of the alternatives corresponding to the attributes.DE optimization is used to obtain the optimal weights of the attributes,and ER methodology is used to compute the aggregated q-rung linear diophantine fuzzy values(q-RLDFVs)of each alternative.Then the score values of alternatives are computed based on the aggregated q-RLDFVs.An alternative with the maximum score value is selected as a better one.The applicability of the proposed approach has been illustrated in COVID-19 emergency decision-making system and sustainable energy planning management.Moreover,we have validated the proposed approach with a numerical example.Finally,a comparative study is provided with the existing models,where the proposed approach is found to be robust to perform better and consistent in uncertain environments.展开更多
As a key component of the plant antioxidant enzymatic system,superoxide dismutase(SOD)can efficiently protect cells from oxidative stress and maintain redox homeostasis.Currently,there are few studies related to SOD g...As a key component of the plant antioxidant enzymatic system,superoxide dismutase(SOD)can efficiently protect cells from oxidative stress and maintain redox homeostasis.Currently,there are few studies related to SOD genes in various taxa of algae,and the specific functions and evolutionary patterns of these family members remain unclear.In this study,comprehensively evolutionary analysis of SOD gene family in the bladed Bangiales was carried out.A total of 9,10,and 12 SOD genes were identified from three species of Pophyra umbilicalis,Pyropia haitanensis,and Pyropia yezoensis,respectively.Based on phylogenetic analysis,SOD gene members within the same subfamily exhibited similar motif patterns as well as conserved domains,which could be attribute to Cu/Zn-SOD and Fe/Mn-SOD.The promoter regions of SOD genes were rich in hormone-responsive,stress-responsive,and growth cis-acting elements,with variations and similarities observed among different species of other red algae and subfamilies.According to subcellular location prediction,it is suggested that Cu/Zn-SOD was predominantly located in chloroplasts,while Fe/Mn-SOD was primarily located in mitochondria.Also,the two subfamilies differed significantly in the two-/three-dimensional protein structures.In terms of gene evolution,the strongest collinearity relationship was shown between Pyropia haitanensis and Pyropia yezoensis,with all the 1꞉1 orthologous gene pair being subjected to a purifying selection(Ka/Ks<1,Ka:non-synonymy rate;Ks:synonymy rate).Moreover,12 SOD genes underwent positive selection during the evolutionary process.Furthermore,gene expression analysis based on transcriptomic data from Pyropia haitanensis showed that the expression patterns of SOD genes varied under different stress conditions.Together,this study revealed the evolutionary pattern of SOD genes in three bladed Bangiales species,which will lay the foundation for subsequent studies on the function of SOD genes.展开更多
In recent years,the development of new types of nuclear reactors,such as transportable,marine,and space reactors,has presented new challenges for the optimization of reactor radiation-shielding design.Shielding struct...In recent years,the development of new types of nuclear reactors,such as transportable,marine,and space reactors,has presented new challenges for the optimization of reactor radiation-shielding design.Shielding structures typically need to be lightweight,miniaturized,and radiation-protected,which is a multi-parameter and multi-objective optimization problem.The conventional multi-objective(two or three objectives)optimization method for radiation-shielding design exhibits limitations for a number of optimization objectives and variable parameters,as well as a deficiency in achieving a global optimal solution,thereby failing to meet the requirements of shielding optimization for newly developed reactors.In this study,genetic and artificial bee-colony algorithms are combined with a reference-point-selection strategy and applied to the many-objective(having four or more objectives)optimal design of reactor radiation shielding.To validate the reliability of the methods,an optimization simulation is conducted on three-dimensional shielding structures and another complicated shielding-optimization problem.The numerical results demonstrate that the proposed algorithms outperform conventional shielding-design methods in terms of optimization performance,and they exhibit their reliability in practical engineering problems.The many-objective optimization algorithms developed in this study are proven to efficiently and consistently search for Pareto-front shielding schemes.Therefore,the algorithms proposed in this study offer novel insights into improving the shielding-design performance and shielding quality of new reactor types.展开更多
Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi...Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi-firmware comparison method based on evolutionary algorithms and trusted base points.We first model the multi-firmware comparison as a multi-sequence matching problem.Then,we propose an adaptation function and a population generation method based on trusted base points.Finally,we apply an evolutionary algorithm to find the optimal result.At the same time,we design the similarity of matching results as an evaluation metric to measure the effect of multi-firmware comparison.The experiments show that the proposed method outperforms Bindiff and the string-based method.Precisely,the similarity between the matching results of the proposed method and Bindiff matching results is 61%,and the similarity between the matching results of the proposed method and the string-based method is 62.8%.By sampling and manual verification,the accuracy of the matching results of the proposed method can be about 66.4%.展开更多
Convolutional neural networks(CNNs)exhibit superior performance in image feature extraction,making them extensively used in the area of traffic sign recognition.However,the design of existing traffic sign recognition ...Convolutional neural networks(CNNs)exhibit superior performance in image feature extraction,making them extensively used in the area of traffic sign recognition.However,the design of existing traffic sign recognition algorithms often relies on expert knowledge to enhance the image feature extraction networks,necessitating image preprocessing and model parameter tuning.This increases the complexity of the model design process.This study introduces an evolutionary neural architecture search(ENAS)algorithm for the automatic design of neural network models tailored for traffic sign recognition.By integrating the construction parameters of residual network(ResNet)into evolutionary algorithms(EAs),we automatically generate lightweight networks for traffic sign recognition,utilizing blocks as the fundamental building units.Experimental evaluations on the German traffic sign recognition benchmark(GTSRB)dataset reveal that the algorithm attains a recognition accuracy of 99.32%,with a mere 2.8×10^(6)parameters.Experimental results comparing the proposed method with other traffic sign recognition algorithms demonstrate that the method can more efficiently discover neural network architectures,significantly reducing the number of network parameters while maintaining recognition accuracy.展开更多
In recent years,feature selection(FS)optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification.This work reviews FS and classificati...In recent years,feature selection(FS)optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification.This work reviews FS and classification methods that utilize evolutionary algorithms(EAs)for gene expression profiles in cancer or medical applications based on research motivations,challenges,and recommendations.Relevant studies were retrieved from four major academic databases-IEEE,Scopus,Springer,and ScienceDirect-using the keywords‘cancer classification’,‘optimization’,‘FS’,and‘gene expression profile’.A total of 67 papers were finally selected with key advancements identified as follows:(1)The majority of papers(44.8%)focused on developing algorithms and models for FS and classification.(2)The second category encompassed studies on biomarker identification by EAs,including 20 papers(30%).(3)The third category comprised works that applied FS to cancer data for decision support system purposes,addressing high-dimensional data and the formulation of chromosome length.These studies accounted for 12%of the total number of studies.(4)The remaining three papers(4.5%)were reviews and surveys focusing on models and developments in prediction and classification optimization for cancer classification under current technical conditions.This review highlights the importance of optimizing FS in EAs to manage high-dimensional data effectively.Despite recent advancements,significant limitations remain:the dynamic formulation of chromosome length remains an underexplored area.Thus,further research is needed on dynamic-length chromosome techniques for more sophisticated biomarker gene selection techniques.The findings suggest that further advancements in dynamic chromosome length formulations and adaptive algorithms could enhance cancer classification accuracy and efficiency.展开更多
The green retrofit of existing public buildings is a necessary choice to promote energy conservation,emission reduction,and sustainable development goals in the construction industry,and to advance the implementation ...The green retrofit of existing public buildings is a necessary choice to promote energy conservation,emission reduction,and sustainable development goals in the construction industry,and to advance the implementation of the national"carbon peaking and carbon neutrality"strategy.The effective governance of green retrofit projects for existing public buildings essentially involves a dynamic process of repeated strategic interactions among key stakeholders.From the perspective of project governance,this study clarifies the game-theoretic relationship between ESCO and owners under government guidance,and constructs an evolutionary game model involving the government,ESCO,and owners.The study explores the strategic choices of the core stakeholders in the green retrofit projects of existing public buildings.The aim is to lay a foundation for research on the decision-making coordination and implementation mechanisms between ESCO and owners,thus promoting the efficient and healthy development of green retrofit projects for existing public buildings.展开更多
The recent concurrent emergence of H5N1,H5N6,and H5N8 avian influenza viruses(AIVs)has led to significant avian mortality globally.Since 2020,frequent human-animal interactions have been documented.To gain insight int...The recent concurrent emergence of H5N1,H5N6,and H5N8 avian influenza viruses(AIVs)has led to significant avian mortality globally.Since 2020,frequent human-animal interactions have been documented.To gain insight into the novel H5 subtype AIVs(i.e.,H5N1,H5N6 and H5N8),we collected 6102 samples from various regions of China between January 2021 and September 2022,and identified 41 H5Nx strains.Comparative analyses on the evolution and biological properties of these isolates were conducted.Phylogenetic analysis revealed that the 41 H5Nx strains belonged to clade 2.3.4.4b,with 13 related to H5N1,19 to H5N6,and 9 to H5N8.Analysis based on global 2.3.4.4b viruses showed that all the viruses described in this study were likely originated from H5N8,exhibiting a heterogeneous evolutionary history between H5N1 and H5N6 during 2015–2022 worldwide.H5N1 showed a higher rate of evolution in 2021–2022 and more sites under positive selection pressure in 2015–2022.The antigenic profiles of the novel H5N1 and H5N6 exhibited notable variations.Further hemagglutination inhibition assay suggested that some A(H5N1)viruses may be antigenically distinct from the circulating H5N6 and H5N8 strains.Mammalian challenge assays demonstrated that the H5N8 virus(21GD001_H5N8)displayed the highest pathogenicity in mice,followed by the H5N1 virus(B1557_H5N1)and then the H5N6 virus(220086_H5N6),suggesting a heterogeneous virulence profile of H5 AIVs in the mammalian hosts.Based on the above results,we speculate that A(H5N1)viruses have a higher risk of emergence in the future.Collectively,these findings unveil a new landscape of different evolutionary history and biological characteristics of novel H5 AIVs in clade 2.3.4.4b,contributing to a better understanding of designing more effective strategies for the prevention and control of novel H5 AIVs.展开更多
Here,we infer the historical biogeography and evolutionary diversification of the genus Lilium.For this purpose,we used the complete plastomes of 64 currently accepted species in the genus Lilium(14plastomes were newl...Here,we infer the historical biogeography and evolutionary diversification of the genus Lilium.For this purpose,we used the complete plastomes of 64 currently accepted species in the genus Lilium(14plastomes were newly sequenced)to recover the phylogenetic backbone of the genus and a timecalibrated phylogenetic framework to estimate biogeographical history scenarios and evolutionary diversification rates of Lilium.Our results suggest that ancient climatic changes and geological tectonic activities jointly shaped the distribution range and drove evolutionary radiation of Lilium,including the Middle Miocene Climate Optimum(MMCO),the late Miocene global cooling,as well as the successive uplift of the Qinghai-Tibet Plateau(QTP)and the strengthening of the monsoon climate in East Asia during the late Miocene and the Pliocene.This case study suggests that the unique geological and climatic events in the Neogene of East Asia,in particular the uplift of QTP and the enhancement of monsoonal climate,may have played an essential role in formation of uneven distribution of plant diversity in the Northern Hemisphere.展开更多
Magnetic sense,or termed magnetoreception,has evolved in a broad range of taxa within the animal kingdom to facilitate orientation and navigation.MagRs,highly conserved A-type iron-sulfur proteins,are widely distribut...Magnetic sense,or termed magnetoreception,has evolved in a broad range of taxa within the animal kingdom to facilitate orientation and navigation.MagRs,highly conserved A-type iron-sulfur proteins,are widely distributed across all phyla and play essential roles in both magnetoreception and iron-sulfur cluster biogenesis.However,the evolutionary origins and functional diversification of MagRs from their prokaryotic ancestor remain unclear.In this study,MagR sequences from 131 species,ranging from bacteria to humans,were selected for analysis,with 23 representative sequences covering species from prokaryotes to Mollusca,Arthropoda,Osteichthyes,Reptilia,Aves,and mammals chosen for protein expression and purification.Biochemical studies revealed a gradual increase in total iron content in MagRs during evolution.Three types of MagRs were identified,each with distinct iron and/or iron-sulfur cluster binding capacity and protein stability,indicating continuous expansion of the functional roles of MagRs during speciation and evolution.This evolutionary biochemical study provides valuable insights into how evolution shapes the physical and chemical properties of biological molecules such as MagRs and how these properties influence the evolutionary trajectories of MagRs.展开更多
Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human ...Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.展开更多
Constrained multi-objective optimization problems(CMOPs)generally contain multiple constraints,which not only form multiple discrete feasible regions but also reduce the size of optimal feasible regions,thus they prop...Constrained multi-objective optimization problems(CMOPs)generally contain multiple constraints,which not only form multiple discrete feasible regions but also reduce the size of optimal feasible regions,thus they propose serious challenges for solvers.Among all constraints,some constraints are highly correlated with optimal feasible regions;thus they can provide effective help to find feasible Pareto front.However,most of the existing constrained multi-objective evolutionary algorithms tackle constraints by regarding all constraints as a whole or directly ignoring all constraints,and do not consider judging the relations among constraints and do not utilize the information from promising single constraints.Therefore,this paper attempts to identify promising single constraints and utilize them to help solve CMOPs.To be specific,a CMOP is transformed into a multitasking optimization problem,where multiple auxiliary tasks are created to search for the Pareto fronts that only consider a single constraint respectively.Besides,an auxiliary task priority method is designed to identify and retain some high-related auxiliary tasks according to the information of relative positions and dominance relationships.Moreover,an improved tentative method is designed to find and transfer useful knowledge among tasks.Experimental results on three benchmark test suites and 11 realworld problems with different numbers of constraints show better or competitive performance of the proposed method when compared with eight state-of-the-art peer methods.展开更多
基金supported by grants from the Third Xinjiang Scientific Expedition Program(Grant No.2022xjkk0205 to Lin Xia,No.2021xjkk0604 to Jilong Cheng)the National Natural Science Foundation of China(32170416 to Qisen Yang,31900325 to Jilong Cheng)+1 种基金the Joint Fund of National Natural Science Foundation of China(U2003203 to Lin Xia)the Key Laboratory of Zoological Systematics and Evolution of the Chinese Academy of Sciences(Y229YX5105 to Qisen Yang).
文摘How ecological and evolutionary factors affect small mammal diversity in arid regions remains largely unknown.Here,we combined the largest phylogeny and occurrence dataset of Gerbillinae desert rodents to explore the underlying factors shaping present-day distribution patterns.In particular,we analyzed the relative contributions of ecological and evolutionary factors on their species diversity using a variety of models.Additionally,we inferred the ancestral range and possible dispersal scenarios and estimated the diversification rate of Gerbillinae.We found that Gerbillinae likely originated in the Horn of Africa in the Middle Miocene and then dispersed and diversified across arid regions in northern and southern Africa and western and central Asia,forming their current distribution pattern.Multiple ecological and evolutionary factors jointly determine the spatial pattern of Gerbillinae diversity,but evolutionary factors(evolutionary time and speciation rate)and habitat filtering were the most important in explaining the spatial variation in species richness.Our study enhances the understanding of the diversity patterns of small mammals in arid regions and highlights the importance of including evolutionary factors when interpreting the mechanisms underlying large-scale species diversity patterns.
基金supported by the Basic and Applied Basic Research Foundation of Guangdong Province(2020A1515110882)National Science Fund for Distinguished Young Scholars(32225049)。
文摘The yellow boxfish(Ostracion cubicus)exhibits a combination of derived morphological traits specialized for coral reef environments and ancestral characteristics,including a fused dermal plate.Contradictory evolutionary evidence hinders true classification of O.cubicus.To clarify its evolutionary position within Tetraodontiformes,a chromosome-level genome assembly was generated,representing the most contiguous and complete genome to date for this lineage.Notably,O.cubicus possessed the largest genome within the order Tetraodontiformes,primarily due to extensive transposable element expansion.Phylogenetic analysis based on 19 whole genomes and 131 mitochondrial genomes resolved Tetraodontiformes into three major sister groups(Ostraciidae-Molidae,Tetraodontidae,and Balistidae-Monacanthidae).Comparative genomic evidence indicated that O.cubicus diverged early from the common ancestor of modern Tetraodontiformes and retained the highest number of HOX genes among surveyed taxa.Although overall genomic architecture was largely conserved,certain genetic and environmental changes may have contributed to its phenotypic adaptations,including climate cooling during the Miocene-Pliocene Transition,recent DNA and long interspersed nuclear element(LINE)transposon bursts,lineage-specific chromosomal rearrangements,and gene family expansion.Many positively selected genes and rapidly evolving genes were associated with skeletal development,including bmp7,egf7,and bmpr2.Transcriptomic comparisons between carapace and tail skin revealed various candidate genes and pathways related to carapace formation,such as postn,scpp1,and components of the TGF-βsignaling pathway.A derived amino acid substitution in eda,coupled with protein structural modeling,suggested potential molecular convergence in dermal plate formation among teleosts.These findings provide novel insights into the genomic and developmental basis of carapace evolution and coral reef-adaptation in O.cubicus,offering a strong case for evolutionary balance between genomic conservation with regulatory innovation to achieve coral reef specialization.
文摘The livestock farming is an important pillar of the rural economy in China.To explore the impact of government technical subsidies and pollution penalties on the digital and intelligent transformation of livestock enterprises,an evolutionary game theoretical model between the government and livestock enterprises is constructed.The interaction mechanism of the game between the government and breeding enterprises is explored,and simulation is conducted.The research results show that the combined strategy of pollution penalties and technical subsidies is the optimal strategy for the government;the system is jointly driven by government subsidies,technical costs of transformation input,public willingness,and enterprise willingness.
文摘Quantitatively mapping enzyme sequence-catalysis landscapes remains a critical challenge in understanding enzyme function,evolution,and design.In this study,we leveraged emerging microfluidic technology to measure catalytic constants-kcat and KM-for hundreds of diverse orthologs and mutants of adenylate kinase(ADK).We dissected this sequence-catalysis landscape's topology,navigability,and mechanistic underpinnings,revealing catalytically heterogeneous neighborhoods organized by domain architecture.
文摘The present investigation aims at unveiling the main causes of the recorded disparate phylogeographic patterning among the two highly dispersive coastal crab species Carcinus aestuarii and Pachygrapsus marmoratus in the Mediterranean Sea.For this purpose,available mitochondrial and nuclear data for both species were re-analyzed and investigated for genetic polymorphism and differentiation patterns across three defined geographic scales in their distribution ranges,but also across the same locations in the Mediterranean Sea.The temporal frame of genetic diversification was also determined for both species in order to check whether observed differences in phylogeographic patterns among these coastal decapods could be attributed to different evolutionary histories.The obtained results revealed a more variable and diversified gene pool in the green crab C.aestuarii than the one recorded in the marbled crab P.marmoratus.Lack of significant correlation between pairwise genetic dissimilarities observed among C.aestuarii populations and those detected for P.marmoratus was notably discerned across the same defined Mediterranean locations.This finding indicates that the pattern of pairwise genetic differentiation does not vary in the same way in both examined crab species.Significant outputs of population genetic differentiation,retrieved within both species,were shown to be differently associated with the potential effects of various kinds of isolation processes(related to geography,environment and biogeographic boundary).Evolutionary history reconstruction showed older genetic diversification event in C.aestuarii than the one recorded in P.marmoratus.These recorded temporal frames suggest different modes of genetic diversification in both crab species(glacial vicariance for C.aestuarii and interglacial dispersal for P.marmoratus).They may also provide an explanation for the recorded differences in variation of patterns of population genetic diversity and structure,when integrated with species ecological requirements and life-history traits.
文摘In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential reasoning(ER)methodology.The proposed approach uses q-RLDFS in order to represent the evaluating values of the alternatives corresponding to the attributes.DE optimization is used to obtain the optimal weights of the attributes,and ER methodology is used to compute the aggregated q-rung linear diophantine fuzzy values(q-RLDFVs)of each alternative.Then the score values of alternatives are computed based on the aggregated q-RLDFVs.An alternative with the maximum score value is selected as a better one.The applicability of the proposed approach has been illustrated in COVID-19 emergency decision-making system and sustainable energy planning management.Moreover,we have validated the proposed approach with a numerical example.Finally,a comparative study is provided with the existing models,where the proposed approach is found to be robust to perform better and consistent in uncertain environments.
基金Supported by the National Key R&D Program of China(No.2023 YFD 2400102)the Guangxi Key Laboratory of Beibu Gulf Marine Biodiversity Conservation,Beibu Gulf University(No.2024 KA 04)。
文摘As a key component of the plant antioxidant enzymatic system,superoxide dismutase(SOD)can efficiently protect cells from oxidative stress and maintain redox homeostasis.Currently,there are few studies related to SOD genes in various taxa of algae,and the specific functions and evolutionary patterns of these family members remain unclear.In this study,comprehensively evolutionary analysis of SOD gene family in the bladed Bangiales was carried out.A total of 9,10,and 12 SOD genes were identified from three species of Pophyra umbilicalis,Pyropia haitanensis,and Pyropia yezoensis,respectively.Based on phylogenetic analysis,SOD gene members within the same subfamily exhibited similar motif patterns as well as conserved domains,which could be attribute to Cu/Zn-SOD and Fe/Mn-SOD.The promoter regions of SOD genes were rich in hormone-responsive,stress-responsive,and growth cis-acting elements,with variations and similarities observed among different species of other red algae and subfamilies.According to subcellular location prediction,it is suggested that Cu/Zn-SOD was predominantly located in chloroplasts,while Fe/Mn-SOD was primarily located in mitochondria.Also,the two subfamilies differed significantly in the two-/three-dimensional protein structures.In terms of gene evolution,the strongest collinearity relationship was shown between Pyropia haitanensis and Pyropia yezoensis,with all the 1꞉1 orthologous gene pair being subjected to a purifying selection(Ka/Ks<1,Ka:non-synonymy rate;Ks:synonymy rate).Moreover,12 SOD genes underwent positive selection during the evolutionary process.Furthermore,gene expression analysis based on transcriptomic data from Pyropia haitanensis showed that the expression patterns of SOD genes varied under different stress conditions.Together,this study revealed the evolutionary pattern of SOD genes in three bladed Bangiales species,which will lay the foundation for subsequent studies on the function of SOD genes.
基金supported by the National Natural Science Foundation of China(Nos.12475174 and 12175101)Yue Lu Shan Center Industrial Innovation(No.2024YCII0108)。
文摘In recent years,the development of new types of nuclear reactors,such as transportable,marine,and space reactors,has presented new challenges for the optimization of reactor radiation-shielding design.Shielding structures typically need to be lightweight,miniaturized,and radiation-protected,which is a multi-parameter and multi-objective optimization problem.The conventional multi-objective(two or three objectives)optimization method for radiation-shielding design exhibits limitations for a number of optimization objectives and variable parameters,as well as a deficiency in achieving a global optimal solution,thereby failing to meet the requirements of shielding optimization for newly developed reactors.In this study,genetic and artificial bee-colony algorithms are combined with a reference-point-selection strategy and applied to the many-objective(having four or more objectives)optimal design of reactor radiation shielding.To validate the reliability of the methods,an optimization simulation is conducted on three-dimensional shielding structures and another complicated shielding-optimization problem.The numerical results demonstrate that the proposed algorithms outperform conventional shielding-design methods in terms of optimization performance,and they exhibit their reliability in practical engineering problems.The many-objective optimization algorithms developed in this study are proven to efficiently and consistently search for Pareto-front shielding schemes.Therefore,the algorithms proposed in this study offer novel insights into improving the shielding-design performance and shielding quality of new reactor types.
文摘Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi-firmware comparison method based on evolutionary algorithms and trusted base points.We first model the multi-firmware comparison as a multi-sequence matching problem.Then,we propose an adaptation function and a population generation method based on trusted base points.Finally,we apply an evolutionary algorithm to find the optimal result.At the same time,we design the similarity of matching results as an evaluation metric to measure the effect of multi-firmware comparison.The experiments show that the proposed method outperforms Bindiff and the string-based method.Precisely,the similarity between the matching results of the proposed method and Bindiff matching results is 61%,and the similarity between the matching results of the proposed method and the string-based method is 62.8%.By sampling and manual verification,the accuracy of the matching results of the proposed method can be about 66.4%.
基金supported by the National Natural Science Foundation of China(No.62066041).
文摘Convolutional neural networks(CNNs)exhibit superior performance in image feature extraction,making them extensively used in the area of traffic sign recognition.However,the design of existing traffic sign recognition algorithms often relies on expert knowledge to enhance the image feature extraction networks,necessitating image preprocessing and model parameter tuning.This increases the complexity of the model design process.This study introduces an evolutionary neural architecture search(ENAS)algorithm for the automatic design of neural network models tailored for traffic sign recognition.By integrating the construction parameters of residual network(ResNet)into evolutionary algorithms(EAs),we automatically generate lightweight networks for traffic sign recognition,utilizing blocks as the fundamental building units.Experimental evaluations on the German traffic sign recognition benchmark(GTSRB)dataset reveal that the algorithm attains a recognition accuracy of 99.32%,with a mere 2.8×10^(6)parameters.Experimental results comparing the proposed method with other traffic sign recognition algorithms demonstrate that the method can more efficiently discover neural network architectures,significantly reducing the number of network parameters while maintaining recognition accuracy.
基金funded by the Ministry of Higher Education of Malaysia,grant number FRGS/1/2022/ICT02/UPSI/02/1.
文摘In recent years,feature selection(FS)optimization of high-dimensional gene expression data has become one of the most promising approaches for cancer prediction and classification.This work reviews FS and classification methods that utilize evolutionary algorithms(EAs)for gene expression profiles in cancer or medical applications based on research motivations,challenges,and recommendations.Relevant studies were retrieved from four major academic databases-IEEE,Scopus,Springer,and ScienceDirect-using the keywords‘cancer classification’,‘optimization’,‘FS’,and‘gene expression profile’.A total of 67 papers were finally selected with key advancements identified as follows:(1)The majority of papers(44.8%)focused on developing algorithms and models for FS and classification.(2)The second category encompassed studies on biomarker identification by EAs,including 20 papers(30%).(3)The third category comprised works that applied FS to cancer data for decision support system purposes,addressing high-dimensional data and the formulation of chromosome length.These studies accounted for 12%of the total number of studies.(4)The remaining three papers(4.5%)were reviews and surveys focusing on models and developments in prediction and classification optimization for cancer classification under current technical conditions.This review highlights the importance of optimizing FS in EAs to manage high-dimensional data effectively.Despite recent advancements,significant limitations remain:the dynamic formulation of chromosome length remains an underexplored area.Thus,further research is needed on dynamic-length chromosome techniques for more sophisticated biomarker gene selection techniques.The findings suggest that further advancements in dynamic chromosome length formulations and adaptive algorithms could enhance cancer classification accuracy and efficiency.
基金supported by the National Natural Science Foundation of China(Grant No.71872122)the Late-stage Subsidy Project of Humanities and Social Sciences of the Education Department of China(Grant No.20JHQ095).
文摘The green retrofit of existing public buildings is a necessary choice to promote energy conservation,emission reduction,and sustainable development goals in the construction industry,and to advance the implementation of the national"carbon peaking and carbon neutrality"strategy.The effective governance of green retrofit projects for existing public buildings essentially involves a dynamic process of repeated strategic interactions among key stakeholders.From the perspective of project governance,this study clarifies the game-theoretic relationship between ESCO and owners under government guidance,and constructs an evolutionary game model involving the government,ESCO,and owners.The study explores the strategic choices of the core stakeholders in the green retrofit projects of existing public buildings.The aim is to lay a foundation for research on the decision-making coordination and implementation mechanisms between ESCO and owners,thus promoting the efficient and healthy development of green retrofit projects for existing public buildings.
基金supported by the Science and Technology Program of Guangdong Province(2022B1111010004,2021B1212030015)China Agriculture Research System of MOF and MARA(CARS-41)China National Animal Disease Surveillance and Epidemiological Survey Program(2021–2025)(No.202111).
文摘The recent concurrent emergence of H5N1,H5N6,and H5N8 avian influenza viruses(AIVs)has led to significant avian mortality globally.Since 2020,frequent human-animal interactions have been documented.To gain insight into the novel H5 subtype AIVs(i.e.,H5N1,H5N6 and H5N8),we collected 6102 samples from various regions of China between January 2021 and September 2022,and identified 41 H5Nx strains.Comparative analyses on the evolution and biological properties of these isolates were conducted.Phylogenetic analysis revealed that the 41 H5Nx strains belonged to clade 2.3.4.4b,with 13 related to H5N1,19 to H5N6,and 9 to H5N8.Analysis based on global 2.3.4.4b viruses showed that all the viruses described in this study were likely originated from H5N8,exhibiting a heterogeneous evolutionary history between H5N1 and H5N6 during 2015–2022 worldwide.H5N1 showed a higher rate of evolution in 2021–2022 and more sites under positive selection pressure in 2015–2022.The antigenic profiles of the novel H5N1 and H5N6 exhibited notable variations.Further hemagglutination inhibition assay suggested that some A(H5N1)viruses may be antigenically distinct from the circulating H5N6 and H5N8 strains.Mammalian challenge assays demonstrated that the H5N8 virus(21GD001_H5N8)displayed the highest pathogenicity in mice,followed by the H5N1 virus(B1557_H5N1)and then the H5N6 virus(220086_H5N6),suggesting a heterogeneous virulence profile of H5 AIVs in the mammalian hosts.Based on the above results,we speculate that A(H5N1)viruses have a higher risk of emergence in the future.Collectively,these findings unveil a new landscape of different evolutionary history and biological characteristics of novel H5 AIVs in clade 2.3.4.4b,contributing to a better understanding of designing more effective strategies for the prevention and control of novel H5 AIVs.
基金financially supported by the National Natural Science Foundation of China(31872673)Yunnan Revitalization Talent Support Program“Top Team”Project(202305AT350001)the NSFC-Joint Foundation of Yunnan Province(U1802287)。
文摘Here,we infer the historical biogeography and evolutionary diversification of the genus Lilium.For this purpose,we used the complete plastomes of 64 currently accepted species in the genus Lilium(14plastomes were newly sequenced)to recover the phylogenetic backbone of the genus and a timecalibrated phylogenetic framework to estimate biogeographical history scenarios and evolutionary diversification rates of Lilium.Our results suggest that ancient climatic changes and geological tectonic activities jointly shaped the distribution range and drove evolutionary radiation of Lilium,including the Middle Miocene Climate Optimum(MMCO),the late Miocene global cooling,as well as the successive uplift of the Qinghai-Tibet Plateau(QTP)and the strengthening of the monsoon climate in East Asia during the late Miocene and the Pliocene.This case study suggests that the unique geological and climatic events in the Neogene of East Asia,in particular the uplift of QTP and the enhancement of monsoonal climate,may have played an essential role in formation of uneven distribution of plant diversity in the Northern Hemisphere.
基金National Natural Science Foundation of China(31640001 and T2350005 to C.X.)Ministry of Science and Technology of China(2021ZD0140300 to C.X.)Presidential Foundation of Hefei Institutes of Physical Science,Chinese Academy of Sciences(Y96XC11131,E26CCG27,and E26CCD15 to C.X.,E36CWGBR24B and E36CZG14132 to T.C.)。
文摘Magnetic sense,or termed magnetoreception,has evolved in a broad range of taxa within the animal kingdom to facilitate orientation and navigation.MagRs,highly conserved A-type iron-sulfur proteins,are widely distributed across all phyla and play essential roles in both magnetoreception and iron-sulfur cluster biogenesis.However,the evolutionary origins and functional diversification of MagRs from their prokaryotic ancestor remain unclear.In this study,MagR sequences from 131 species,ranging from bacteria to humans,were selected for analysis,with 23 representative sequences covering species from prokaryotes to Mollusca,Arthropoda,Osteichthyes,Reptilia,Aves,and mammals chosen for protein expression and purification.Biochemical studies revealed a gradual increase in total iron content in MagRs during evolution.Three types of MagRs were identified,each with distinct iron and/or iron-sulfur cluster binding capacity and protein stability,indicating continuous expansion of the functional roles of MagRs during speciation and evolution.This evolutionary biochemical study provides valuable insights into how evolution shapes the physical and chemical properties of biological molecules such as MagRs and how these properties influence the evolutionary trajectories of MagRs.
基金supported in part by the National Natural Science Foundation of China (NSFC) under Grant No.61976242in part by the Natural Science Fund of Hebei Province for Distinguished Young Scholars under Grant No.F2021202010+2 种基金in part by the Fundamental Scientific Research Funds for Interdisciplinary Team of Hebei University of Technology under Grant No.JBKYTD2002funded by Science and Technology Project of Hebei Education Department under Grant No.JZX2023007supported by 2022 Interdisciplinary Postgraduate Training Program of Hebei University of Technology under Grant No.HEBUT-YXKJC-2022122.
文摘Most of the neural network architectures are based on human experience,which requires a long and tedious trial-and-error process.Neural architecture search(NAS)attempts to detect effective architectures without human intervention.Evolutionary algorithms(EAs)for NAS can find better solutions than human-designed architectures by exploring a large search space for possible architectures.Using multiobjective EAs for NAS,optimal neural architectures that meet various performance criteria can be explored and discovered efficiently.Furthermore,hardware-accelerated NAS methods can improve the efficiency of the NAS.While existing reviews have mainly focused on different strategies to complete NAS,a few studies have explored the use of EAs for NAS.In this paper,we summarize and explore the use of EAs for NAS,as well as large-scale multiobjective optimization strategies and hardware-accelerated NAS methods.NAS performs well in healthcare applications,such as medical image analysis,classification of disease diagnosis,and health monitoring.EAs for NAS can automate the search process and optimize multiple objectives simultaneously in a given healthcare task.Deep neural network has been successfully used in healthcare,but it lacks interpretability.Medical data is highly sensitive,and privacy leaks are frequently reported in the healthcare industry.To solve these problems,in healthcare,we propose an interpretable neuroevolution framework based on federated learning to address search efficiency and privacy protection.Moreover,we also point out future research directions for evolutionary NAS.Overall,for researchers who want to use EAs to optimize NNs in healthcare,we analyze the advantages and disadvantages of doing so to provide detailed guidance,and propose an interpretable privacy-preserving framework for healthcare applications.
基金supported in part by the National Key Research and Development Program of China(2022YFD2001200)the National Natural Science Foundation of China(62176238,61976237,62206251,62106230)+3 种基金China Postdoctoral Science Foundation(2021T140616,2021M692920)the Natural Science Foundation of Henan Province(222300420088)the Program for Science&Technology Innovation Talents in Universities of Henan Province(23HASTIT023)the Program for Science&Technology Innovation Teams in Universities of Henan Province(23IRTSTHN010).
文摘Constrained multi-objective optimization problems(CMOPs)generally contain multiple constraints,which not only form multiple discrete feasible regions but also reduce the size of optimal feasible regions,thus they propose serious challenges for solvers.Among all constraints,some constraints are highly correlated with optimal feasible regions;thus they can provide effective help to find feasible Pareto front.However,most of the existing constrained multi-objective evolutionary algorithms tackle constraints by regarding all constraints as a whole or directly ignoring all constraints,and do not consider judging the relations among constraints and do not utilize the information from promising single constraints.Therefore,this paper attempts to identify promising single constraints and utilize them to help solve CMOPs.To be specific,a CMOP is transformed into a multitasking optimization problem,where multiple auxiliary tasks are created to search for the Pareto fronts that only consider a single constraint respectively.Besides,an auxiliary task priority method is designed to identify and retain some high-related auxiliary tasks according to the information of relative positions and dominance relationships.Moreover,an improved tentative method is designed to find and transfer useful knowledge among tasks.Experimental results on three benchmark test suites and 11 realworld problems with different numbers of constraints show better or competitive performance of the proposed method when compared with eight state-of-the-art peer methods.
