A cooperative Co-evolutional immune algorithm

A co-evolutional immune algorithm for the optimization of a function with real parameters is de-scribed.It uses a cooperative co-evolution of two populations,one is a population of antibodies and theother is a population of successful mutation vectors.These two population evolve together to improve thediversity of the antibodies.The algorithm described is then tested on a suite of optimization problems.The results show that on most of test functions,this algorithm can converge to the global optimum atquicker rate in a given range,the performance of optimization is improved effetely.

Adaptive multicascade attribute reduction based on quantum-inspired mixed co-evolution

Due to the fact that conventional heuristic attribute reduction algorithms are poor in running efficiency and difficult in accomplishing the co-evolutionary reduction mechanism in the decision table, an adaptive multicascade attribute reduction algorithm based on quantum-inspired mixed co-evolution is proposed. First, a novel and efficient self- adaptive quantum rotation angle strategy is designed to direct the participating populations to mutual adaptive evolution and to accelerate convergence speed. Then, a multicascade model of cooperative and competitive mixed co-evolution is adopted to decompose the evolutionary attribute species into subpopulations according to their historical performance records, which can increase the diversity of subpopulations and select some elitist individuals so as to strengthen the sharing ability of their searching experience. So the global optimization reduction set can be obtained quickly. The experimental results show that, compared with the existing algorithms, the proposed algorithm can achieve a higher performance for attribute reduction, and it can be considered as a more competitive heuristic algorithm on the efficiency and accuracy of minimum attribute reduction.

Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

A design problem with deficient information is generally described as wicked or ill-defined.The information insufficiency leaves designers with loose settings,free environments,and a lack of strict boundaries,which provides them with more opportunities to facilitate innovation.Therefore,to capture the opportunity behind the uncertainty of a design problem,this study models an innovative design as a composite solving process,where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems,knowledge,and solutions.Additionally,a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem,solution,and knowledge spaces,to provide designers with a distinct design strategy and method for innovative design.The three spaces interact and co-evolve through iterative mappings,including problem structuring,knowledge expansion,and solution generation.The mappings carry the information processing and decision-making activities of the design,and create the path to satisfying solutions.Finally,a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

Cooperative co-evolution based distributed path planning of multiple mobile robots

This paper proposes novel multiple-mobile-robot collision avoidance path planning based on cooperative co-evolution,which can be executed fully distributed and in parallel. A real valued co-evolutionary algorithm is developed to coordinate the movement of multiple robots in 2D world, avoiding C-space or grid net searching. The collision avoidance is achieved by cooperatively co-evolving segments of paths and the time interval to pass them. Methods for constraint handling, which are developed for evolutionary algorithm, make the path planning easier. The effectiveness of the algorithm is demonstrated on a number of 2Dpath planning problems.

Harmony search algorithm with differential evolution based control parameter co-evolution and its application in chemical process dynamic optimization

A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.

Pathogenetic Consequences of Cytomegalovirus-Host Co-evolution

Co-evolution has been shown to result in an adaptive reciprocal modification in the respective behaviors of interacting populations over time. In the case of host-parasite co-evolution,the adaptive behavior is most evident from the reciprocal change in fitness of host and parasite-manifested in terms of pathogen survival versus host resistance. Cytomegaloviruses and their hosts represent a pairing of populations that has co-evolved over hundreds of years. This review explores the pathogenetic consequences emerging from the behavioral changes caused by co-evolutionary forces on the virus and its host.

Adaptive co-evolution of strategies and network leading to optimal cooperation level in spatial prisoner's dilemma game

We study evolutionary prisoner＇s dilemma game on adaptive networks where a population of players co-evolves with their interaction networks. During the co-evolution process, interacted players with opposite strategies either rewire the link between them with probability p or update their strategies with probability 1 - p depending on their payoffs. Numerical simulation shows that the final network is either split into some disconnected communities whose players share the same strategy within each community or forms a single connected network in which all nodes are in the same strategy. Interestingly, the density of cooperators in the final state can be maximised in an intermediate range of p via the competition between time scale of the network dynamics and that of the node dynamics. Finally, the mean-field analysis helps to understand the results of numerical simulation. Our results may provide some insight into understanding the emergence of cooperation in the real situation where the individuals＇ behaviour and their relationship adaptively co-evolve.

Adaptive Co-evolution Model for Multi-agent System

It is important to harmonize effectively the behaviors of the agents in the multi-agent system (MAS) to complete the solution process. The co-evolution computing techniques, inspired by natural selection and genetics, are usually used to solve these problems. Based on learning and evolution mechanisms of the biological systems, an adaptive co-evolution model was proposed in this paper. Inner-population, inter-population, and community learning operators were presented. The adaptive co-evolution algorithm (ACEA) was designed in detail. Some simulation experiments were done to evaluate the performance of the ACEA. The results show that the ACEA is more effective and feasible than the genetic algorithm to solve the optimization problems.

A Co-Evolution Model for Dynamic Social Network and Behavior

Individual behaviors, such as drinking, smoking, screen time, and physical activity, can be strongly influenced by the behavior of friends. At the same time, the choice of friends can be influenced by shared behavioral preferences. The actor-based stochastic models (ABSM) are developed to study the interdependence of social networks and behavior. These methods are efficient and useful for analysis of discrete behaviors, such as drinking and smoking;however, since the behavior evolution function is in an exponential format, the ABSM can generate inconsistent and unrealistic results when the behavior variable is continuous or has a large range, such as hours of television watched or body mass index. To more realistically model continuous behavior variables, we propose a co-evolution process based on a linear model which is consistent over time and has an intuitive interpretation. In the simulation study, we applied the expectation maximization (EM) and Markov chain Monte Carlo (MCMC) algorithms to find the maximum likelihood estimate (MLE) of parameter values. Additionally, we show that our assumptions are reasonable using data from the National Longitudinal Study of Adolescent Health (Add Health).

Hybrid Support Vector Regression with Parallel Co-Evolution Algorithm Based on GA and PSO for Forecasting Monthly Rainfall

Accurate and timely monthly rainfall forecasting is a major challenge for the scientific community in hydrological research such as river management project and design of flood warning systems. Support Vector Regression (SVR) is a very useful precipitation prediction model. In this paper, a novel parallel co-evolution algorithm is presented to determine the appropriate parameters of the SVR in rainfall prediction based on parallel co-evolution by hybrid Genetic Algorithm and Particle Swarm Optimization algorithm, namely SVRGAPSO, for monthly rainfall prediction. The framework of the parallel co-evolutionary algorithm is to iterate two GA and PSO populations simultaneously, which is a mechanism for information exchange between GA and PSO populations to overcome premature local optimum. Our methodology adopts a hybrid PSO and GA for the optimal parameters of SVR by parallel co-evolving. The proposed technique is applied over rainfall forecasting to test its generalization capability as well as to make comparative evaluations with the several competing techniques, such as the other alternative methods, namely SVRPSO (SVR with PSO), SVRGA (SVR with GA), and SVR model. The empirical results indicate that the SVRGAPSO results have a superior generalization capability with the lowest prediction error values in rainfall forecasting. The SVRGAPSO can significantly improve the rainfall forecasting accuracy. Therefore, the SVRGAPSO model is a promising alternative for rainfall forecasting.

Pocket Modification of x-Amine Transaminase AtATA for Overcoming the Trade-Off Between Activity and Stability Toward 1-Acetonaphthone

Amine transaminases(ATAs)catalyze the asymmetric amination of prochiral ketones or aldehydes to their corresponding chiral amines.However,the trade-off between activity and stability in enzyme engineering represents a major obstacle to the practical application of ATAs.Overcoming this trade-off is important for developing robustly engineered enzymes and a universal approach for ATAs.Herein,we modified the binding pocket of co-ATA from Aspergillus terreus(AtATA)to identify the key amino acid residues controlling the activity and stability of AtATA toward 1-acetonaphthone.We discovered a structural switch comprising four key amino acid sites(R128,V149,L182,and L187),as well as the"best"mutant(AtATAD224K/V149A/L182 F/L187F;termed M4).Compared to the parent enzyme AtATAD224K(AtATAPa),M4 increased the catalytic efficiency(k_(cat)/K_(m)^(1-acetonaphthone),where kcatis the constant of catalytic activities and is 10.1 min^(-1),K_(m)^(1-acetonaphthoneis) Michaelis-Menten constant and is 1.7 mmol·L^(-1))and half-life(t1/2)by 59-fold to 5.9 L·min^(-1)·mmol-1and by 1.6-fold to 46.9 min,respectively.Moreover,using M4 as the biocatalyst,we converted a 20 mmol·L^(-1)aliquot of 1-acetonaphthone in a 50 mL scaled-up system to the desired product,(R)-(+)-1(1-naphthyl)ethylamine((R)-NEA),with 78%yield and high enantiomeric purity(R>99.5%)within 10 h.M4 also displayed significantly enhanced activity toward various 1-acetonaphthone analogs.The related structural properties derived by analyzing structure and sequence information of robust ATAs illustrated their enhanced activity and thermostability.Strengthening of intramolecular interactions and expansion of the angle between the substratebinding pocket and the pyridoxal 5’-phosphate(PLP)-binding pocket contributed to synchronous enhancement of ATA thermostability and activity.Moreover,this pocket engineering strategy successfully transferred enhanced activity and thermostability to three other ATAs,which exhibited 8%-22%sequence similarity with AtATA.This research has important implications for overcoming the trade-off between ATA activity and thermostability.

Diversity of Sucking Lice on Small Mammals in the Surrounding Areas of Erhai Lake in Yunnan,China

An investigation of sucking lice on the body surface of small mammals was carried out in the surrounding areas of Erhai Lake in Dali, Yunnan from 2003 to 2004. From investigation sites, 3 303 small mammal hosts were captured and identified into 7 families, 15 genera and 21 species in 4 orders （Rodentia, Insectivora, Scandentia and Carnivora）, while t4 635 individuals of sucking lice collected from the body surface of the small mammal hosts are identified into 5 families, 6 genera and 21 species in the Order Anoplura, The sites stand alongside three cordilleras surrounding the Erhai Lake, namely Eastern Wuliang Mountain, Southern Ailao Mountain and Western Cangshan Mountain. The three confined oriented areas are different landscapes within the same zone where the longitude, latitude, altitude and fauna are homologous but isolated by Erhai Lake as inartificial barrier. The aim of this study was to recognize features of the species diversity, abundance, community structure, similarity and distribution of sucking lice in different landscapes within the same zone. The results showed the species diversity of sucking lice was very low with a very simple community structure. The distribution of sucking lice and their corresponding hosts are quite uneven among different oriented areas and this may imply that ecological environment influences the species composition and distribution of sucking lice and their corresponding hosts. A certain species of hosts usually have their fixed louse species. The similarity of sucking louse communities is highly consistent with the affinity of small mammal hosts in taxonomy. Species of sucking lice on the same small mammal host in different oriented areas of Erhai Lake are homologous. The results strongly suggest a close relationship of co-evolution between sucking lice and their hosts.

Helicobacter pylori in human health and disease:Mechanisms for local gastric and systemic effects

Helicobacter pylori(H. pylori) is present in roughly 50% of the human population worldwide and infection levels reach over 70% in developing countries. The infection has classically been associated with different gastro-intestinal diseases, but also with extra gastric diseases. Despite such associations, the bacterium frequently persists in the human host without inducing disease, and it has been suggested that H. pylori may also play a beneficial role in health. To understand how H. pylori can produce such diverse effects in the human host, several studies have focused on understanding the local and systemic effects triggered by this bacterium. One of the main mechanisms by which H. pylori is thought to damage the host is by inducing local and systemic inflammation. However, more recently, studies are beginning to focus on the effects of H. pylori and its metabolism on the gastric and intestinal microbiome. The objective of this review is to discuss how H. pylori has co-evolved with humans, how H. pylori presence is associated with positive and negative effects in human health and how inflammation and/or changes in the microbiome are associated with the observed outcomes.

The arms race between Magnaporthe oryzae and rice: Diversity and interaction of Avr and R genes

Rice blast disease, caused by Magnaporthe oryzae, threatens global food security. The rice blast pathosystem is a longstanding model system for understanding plant-microbe interactions. In order to elucidate the coevolution of the host and pathogen, and provide the appropriate methods for preventing or controlling rice blast disease, researchers have focused on the evolution of virulence factors and resistance genes. Thus far, more than 30 rice blast resistance（R） genes and 12 avirulence（Avr） genes have been cloned. This review summarizes the cloned rice blast R genes, cloned Avr genes of M. oryzae and the interaction between them. This discussion also considers some of the major unanswered questions concerning this pathosystem and the opportunities for future investigations.

Characterization of a novel toxin-antitoxin module,VapBC,encoded by Leptospira interrogans chromosome

Comparative genomic analysis of the coding sequences (CDSs) of Leptospira interrogans revealed a pair of closely linked genes homologous to the vapBC loci of many other bacteria with respect to both deduced amino acid sequences and operon organizations. Expression of single vapC gene in Escherichia coli resulted in inhibition of bacterial growth,whereas co-expression of vapBC restored the growth effectively. This phenotype is typical for three other characterized toxin-antitoxin systems of bacteria, i.e., mazEF[1], relBE[2] and chpIK[3]. The VapC proteins of bacteria and a thermophilic archeae, Solfolobus tokodaii, form a structurally distinguished group of toxin different from the other known toxins of bacteria. Phylogenetic analysis of both toxins and antitoxins of all categories indicated that although toxins were evolved from divergent sources and may or may not follow their speciation paths (as indicated by their 16s RNA sequences), co-evolution with their antitoxins was obvious.

Eco-spatial Structure of Urban Agglomeration

In terms of ecological theory, this paper makes a comprehensive analysis of the mutualism and co- evolutionary mechanism between the eco-spatial structure and socio-economic development of the urban agglomeration, and maps out optimized modes of the eco-spatial structure of the urban agglomeration. The analysis is a case study of the urban agglomeration on different levels of global, national, provincial and local scales, on the basis of those conclusions are drawn: 1) Within the scope of the urban agglomeration, the cities should be reasonably sized and appropriately densified; the spatial combination of the urban agglomeration ought to be orderly, and its eco-spatial structure ought to be optimized and efficient; the relationship between the economic society and eco-spatial environment ought to be that of mutual benefit and co-evolution. 2) “The mode of corridor group network” is a certain trend evoked from the spatial structure of urban agglomeration. 3) The eco-spatial structure of urban agglomeration under “the mode of corridor group network” can further increase the environmental capacity of urban agglomeration, and is in favor of the harmonious relationship between man and nature.

Specificity of Developmental Resistance in Gypsy Moth (Lymantria dispar) to two DNA-Insect Viruses

Gypsy moth （Lymantria dispar） larvae displayed marked developmental resistance within an instar to L dispar M nucleopolyhedrovirus （LdMNPV） regardless of the route of infection （oral or intrahemocoelic） in a previous study, indicating that in gypsy moth, this resistance has a systemic component. In this study, gypsy moth larvae challenged with the Amsacta moorei entomopoxvirus （AMEV） showed developmental resistance within the fourth instar to oral, but not intrahemocoelic, inoculation. In general, gypsy moth is considered refractory to oral challenge with AMEV, but in this study, 43% mortality occurred in newly molted fourth instars fed a dose of 5×10^6 large spheroids of AMEV; large spheroids were found to be more infectious than small spheroids when separated by a sucrose gradient. Developmental resistance within the fourth instar was reflected by a 2-fold reduction in mortality （18%-21%） with 5 X 106 large spheroids in larvae orally challenged at 24, 48 or 72 h post-molt. Fourth instars were highly sensitive to intrahemocoelic challenge with AMEV; 1PFU produced approximately 80% mortality regardless of age within the instar. These results indicate that in gypsy moth, systemic developmental resistance may be specific to LdMNPV, reflecting a co-evolutionary relationship between the baculovirus and its host.

A Hybrid Differential Evolution Algorithm Integrated with Particle Swarm Optimization

To implement self-adaptive control parameters, a hybrid differential evolution algorithm integrated with particle swarm optimization （PSODE） is proposed. In the PSODE, control parameters are encoded to be a symbiotic individual of original individual, and each original individual has its own symbiotic individual. Differential evolution （ DE） operators are used to evolve the original population. And, particle swarm optimization （PSO） is applied to co-evolving the symbiotic population. Thus, with the evolution of the original population in PSODE, the symbiotic population is dynamically and self-adaptively adjusted and the realtime optimum control parameters are obtained. The proposed algorithm is compared with some DE variants on nine functious. The results show that the average performance of PSODE is the best.

Predicting residue contacts for protein-protein interactions by integration of multiple information

Detailed knowledge of interfacial region between interacting proteins is not only helpful in annotating function for proteins, but also very important for structure-based drug design and disease treatment. However, this is one of the most difficult tasks and current methods are constrained by some factors. In this study, we developed a new method to predict residue-residue contacts of two interacting protein domains by integrating information about evolutionary couplings andamino acid pairwise contact potentials, as well as domain-domain interaction interfaces. The experimental results showed that our proposed method outperformed the previous method with the same datasets. Moreover, the method promises an improvement in the source of template-based protein docking.

Strategic Ecological Network Competition in Emerging Markets:Theory and Case Analysis of A GPS Vehicle Navigation Firm

Using the case study methodology, firm＇s competition behavior in strategic network and strategic ecosystems are analyzed. With the ecology view, there is consistency between strategic network and strategic ecosystem. Enterprise should pursue for suitable ecological niche to hold a strategic competitive power.