Journal of Manufacturing Systems 29 (2010) 173–181

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Journal of Manufacturing Systems

journal homepage: www.elsevier.com/locate/jmansys

Technical paper

Development of a collaborative virtual maintenance environment with agenttechnologyXinhua Liu a,∗, Gaoliang Peng b, Xiumei Liu a, Youfu Hou a

a School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou, Chinab School of Mechanics and Electronics, Harbin Institute of Technology, Harbin, China

a r t i c l e i n f o

Article history:Received 17 March 2010Received in revised form23 September 2010Accepted 3 February 2011Available online 3 March 2011

a b s t r a c t

This paper proposed a virtual environment with agent technology to facilitate the integration andcooperation of product maintenance process. The agent-based system framework, in which variousintelligent agents worked together to perform product maintenance tasks in an autonomous andcollaborative way, is addressed. The functional definition of each intelligent agent is presented and theagent internal structure is designed. Moreover, ontology-based agents communication mechanism andagents co-operation model are proposed, and an intelligent algorithm based on fuzzy comprehensiveevaluation is designed to solve competition conflicts among the agents. Finally, the prototype systemis developed and the algorithm is proved feasible and efficient.

© 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

1. Introduction

Maintenance refers to work carried out a restore degeneratedperformance of a system, equipment or product to a level that isclose to a so-called as good as new condition [1]. As a vital processin product life cycle,maintenance decideswhether the product canbe used with long time, high quality, low cost and managementrisk.

In order to realize high efficiency and visualization of productmaintenance process, virtual reality technology is applied to theproduct maintenance process and virtual maintenance has beenan active research since the late 1990s [2,3]. Many researchershave worked on the problem and proposed different solutions.To deliver a robust solution applicable to practical problems, afew researchers combined two or more factors in an integratedapproach for the product maintenance process. To automaticthe process of product maintenance with high efficiency andintelligence, some researchers apply agent technology to theproduct maintenance process.

The product maintenance process is composed of many taskssuch as maintainability evaluation, maintenance sequence plan-ning, maintenance process simulation andmaintenance operation,etc. Driven by factors such as increasing competition and shortertime-to-market, moremaintenance domain experts and engineersare now required to collaborate and concurrently execute thesevarious tasks. Moreover, multi-agent technology has become one

∗ Corresponding author. Tel.: +86 516 83884512; fax: +86 516 83884512.E-mail address: l_xinhua_2006@126.com (X. Liu).

0278-6125/$ – see front matter© 2011 The Society of Manufacturing Engineers. Publidoi:10.1016/j.jmsy.2011.02.002

of the most important areas of research in the last decades andits various applications have been reported in many engineeringfields [4,5]. The benefits of applying multi-agent technology to theproduct maintenance process include distributed system architec-ture, easy interaction, resourcemanagement, reactivity to changes,interoperation among heterogeneous systems, and intelligent de-cision making, etc.

Bearing the above observations in mind, we present a virtualenvironment based on multi-agent technology to product mainte-nance process and the rest of this paper is organized as follows.In Section 2, some related works are outlined based on the litera-ture. Section 3 presents an agent-based system framework for theproduct maintenance process and proposes the functional defini-tion of individual agents and agent internal structure. Section 4describes the ontology-based communication mechanism andthe co-operation model among the agents. Section 5 designs anintelligent algorithm based on fuzzy comprehensive evaluationto resolve the competition conflicts among the agents. Section 6develops a prototype system based on the above-mentioned keytechnologies. Finally, Section 7 concludes with some advantagesand limitations of our agents supported collaborative virtualmain-tenance environment and points out some future work.

2. Literature review

Recent publications relevant to this paper aremainly concernedwith two research streams: virtual maintenance and multi-agenttechnology. In this section, we try to summarize the relevantliterature.

shed by Elsevier Ltd. All rights reserved.

174 X. Liu et al. / Journal of Manufacturing Systems 29 (2010) 173–181

2.1. Virtual maintenance

For virtual maintenance, lots of research has been done sincethe late 1990s, and most of them can be classified into twocategories: virtual maintenance system and its key technologies.

In [6], Andrea F. Abate et al. presented a better solution com-bination of virtual reality techniques and haptic interaction tosimulate machine assembly maintenance process for aerospaceindustry. In [7,8], virtual reality was applied to remote mainte-nance. In order to improve the performance of manufacturingsystems, Jenab et al. [9] presented a virtual collaborative mainte-nance architecture. In [10] Esqué et al. applied virtual prototypingand simulation to ITER maintenance device development. In [11],Li et al. proposed an object-oriented prototype system calledV-REALISM for maintenance training. Papers [12–14] set up somevirtualmaintenance systems formaintenance task planning,main-tenance planning and maintenance process. In [15], Murray et al.set up an immersive virtual prototyping environment for support-ing the product assembly and maintenance.

In [16], Christiand et al. proposed anovel assembly optimizationframework based on genetic algorithm that allows an operator todetermine an optimal plan for a maintenance process by followingan optimal assembly sequence and considering path planning fac-tors. In [17,18], Lu Zhong et al. presented the maintainability eval-uation model based on fuzzy theory. In [19], optimal maintenancepolicies in incomplete repairmodelswere researched. In [20], TangLi et al. proposed an effective visualization model using object-oriented principles for the virtual maintenance system. In [21], LuXiaojun et al. generated a virtual human’s walking model based onplace/transition Petri Net. In [22], Ishii et al. developed a VR-basedtraining system for teaching disassembling procedures of mechan-ical machines used in nuclear power plant and the Petri net modelwas applied to describe trainees’ plausible actions in the disassem-bling process.

2.2. Multi-agent technology

For multi-agent technology as the other research stream, evenif there is much literature in various areas, we concentrate on theagent-based application in mechanism engineering fields, such asin product design process [23–25], in process planning process[26–28], in fixture design process [29], in production planning andscheduling process [30–33], in product maintenance process [34],in supply chain system [35], in workflow system [36,37] etc. Afew researchers apply agent technology to manufacturing system[38–40], such asmanufacturing resourcemanagement [41],manu-facturing task assignment [42], manufacturing system control [43],manufacturing knowledge management [44], manufacturing sys-tem integration [45] etc.

2.3. Discussion

Although research papers are highly valuable, these solutionsgenerally use an ad hoc approach rather than a systematicapproach and focus only on portions of product maintenanceprocess. To the best of our knowledge, the need for realizingintegrated, cooperative and intelligent product maintenanceenvironment has almost not been dealt with. Based on our pastresearch on product maintenance process and agent technology,this paper tries to tackle this problem.

In this research, we apply agent technology to product main-tenance process and set up an agent-based system framework forcollaborative virtual maintenance environment. Agents structure,agents communicationmechanism, agents cooperationmodel andagents competition conflicts algorithm are elaborated.

Fig. 1. Framework of the proposed agent-based system.

3. Framework of the proposed environment

3.1. System framework

The agent-based collaborative virtual maintenance environ-ment developed in this research consists of manager agent, evalu-ation agent, planning agent, simulation agent, maintenance agent,interface agent,monitor agent and resource agent. The relationshipbetween these agents is illustrated in Fig. 1. In this system, agentsare classified into three categories: manager agent, function agentand information agent. Manager agent acts as a mediator for otheragents and there is only onemanger agent in this system. Functionagents are responsible for carrying out their tasks under the man-agement and supervision of the manager agent through the Inter-net. Information agents also play an important role in the operationof collaborative virtual maintenance environment and they serveas data brokers and provide necessary information to other agentsupon request. These agents can be installed in different comput-ers and distributed geographically in different places. In brief, thissystem has a central control and distributed task operation archi-tecture.

In the agent-based system framework, all the agents performtheir tasks in an Internet environment. Each function agentreceivesmessages from themanager agent, performs its operation,and returns the messages to the manager agent. Manageragent gets necessary message from information agents. Sucharchitecture enables each agent to be independent in its taskexecution, and the breakdown ormalfunction of any agent will notaffect the operations of other agents as long as the manager agentis functioning. In addition, according to the actual needs of theagents, the system can be re-configured so that the manager agentcan only teamupwith several agents to forma sub-entity and servefor the collaborative virtual maintenance environment. The otherunnecessary agents will not be involved in the system operation.

3.2. Functional definition of individual agents

In this agent-based system, each agent has its specificfunctionality. All the agents co-operate towards a common goalthrough the Internet. The functionality of each agent is given asfollows:

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(1) Manager agent. This is the center of the agent-based systemand it is responsible for interactionsmanagement and conflictsresolution among all other agents. It has a knowledge library inwhich the logics and rules for agent management and conflictsresolution are defined and stored. In addition, when an agententers or leaves this system, it will register or deregister withthe manager agent. Therefore, the manager agent ‘knows’ theagents that available and the function of each agent. Basedon its knowledge of the capabilities of each agent, it requestsor sends the necessary messages from or to other agents tocoordinate their operations.

(2) Evaluation agent. This agent has two functions, one is productmaintainability evaluation and the other is maintenanceresource evaluation. Once the evaluation agent receives thefeature-based product models, it analyzes the configurationsof the product models to determine the features that maycause difficulties in the product maintenance process. Itcan detect and report the maintenance conflicts. If themaintenance operation is feasible, it will determine therequired maintenance resources (e.g. maintenance operators,maintenance machines and maintenance tools, etc.) accordingto the product models and their features.

(3) Planning agent. Given a maintenance product, this agent isresponsible for the generation of an optimal maintenancesequence based on the product features and the maintenanceresources. In development enterprises, the planning agentmaymodify themaintenance sequence according to the feedback ofmaintenance department.

(4) Simulation agent. Given a maintenance product, this agentis responsible for the generation of an optimal maintenancedisassembly route based on the product features, maintenanceresources andmaintenance sequence. The results of evaluationagent and planning agent are verified by the simulation agent,and the video of product maintenance process is provided bythe simulation agent.

(5) Maintenance agent. This agent acts as an effective bridge be-tween the proposed system and the users. In our collab-orative virtual maintenance environment, the maintenanceagent is proposed to help users to carry out maintenancetasks (e.g. checking operation, disassembly operation, testingoperation and assembly operation, etc.) and communicatewithother users.

(6) Interface agent. This agent has two main functions. First,the agent acts as an effective bridge between the proposedsystem and other external systems. The maintenance productmodels are sent to our system through the interface agentfrom the CAD systems and the evaluation results, maintenancesequences and maintenance results will be output to therelevant systems. Second, the interface agent can make thehuman–computer interface more intuitive and encouragetypes of interactions that might be difficult to evoke with aconventional interface.

(7) Monitor agent. This agent detects real-time faults and main-tenance tasks execution status. In our collaborative virtualmaintenance environment, the monitor agent is designed togenerate monitoring plans, collect warning messages, readdiagnostic reports and other relevant information in course ofthe system running.

(8) Resource agent. Given a maintenance product, this agentsearches for suitable resource models and sends them to theevaluation agent for further evaluation. As illustrated in Fig. 1,the resource agent is connected with the enterprise database,which stores all the information of the available maintenanceoperators,maintenancemachines,maintenance tools and theirmaintenance capabilities, etc.

3.3. Agent structure

A generic agent has a set of goals (intentions), certaincapabilities to perform action, and some knowledge (or beliefs)about its environment. To achieve its goals, an agent needs touse its knowledge to reason about its environment (as well asbehaviors of other agents), to generate plans and to execute theseplans. Generally, the behavior of an agent is based on an internalmodel of the agent consisting of a function adapter, a workingengine, a knowledge base and an external interface. According tothe description, the internal structure of an agent can be abstractedas a four-tuple as follows:

Agent = ⟨F , E,K , I⟩

where:F : function adapter. The function adapter executes different

maintenance tasks and provides cooperation with other agents.E: working engine. The working engine is the central control

and action part of an agent. It is usually an important operationalfunction, which provides ameans for applying simple, knowledge-based reasoning to emergence of new facts in the agent’sworld andfor using this reasoning capability to decide what the agent shoulddo next.

K : knowledge base. Knowledge is required by each agent toperform its internal and external activities. It consists of knowledgefor particular tasks, resources status information, and informationabout other agents, etc.

I: external interface. The external interface envelops an agentand provides access to it via a well-defined interface, and it is alsothe primary conduit for communication between agents.

The examples of agent structure are presented in Fig. 2, fromwhich we can take a look at the internal models of the manageagent, planning agent and maintenance agent.

4. Agents communication and co-operation

4.1. Agents communication

As an important aspect on research of multi-agent system, in-teraction among agents is set up on low-level data communica-tion as well as control information with semantic and knowledge.In other words, a collaborative virtual maintenance environmentshould be able to exchange information with each agent or theother systems to bring about a seamless product design andmanu-facturing environment. Generally, there are four categories of com-munication language: FIPA Agent Communication Language (FIPAACL), Knowledge Interchange Format (KIF), Knowledge Query Ma-nipulation Language (KQML) and extensible markup language(XML). In recent years, ontology technologyhas becomean increas-ingly accepted language for agent communication. Ontology is ameta-language, that is, a language used to describe a language.There is enough evidence that the adequate tool for dealing withsemantically heterogeneous data is ontology, and the ontology en-ables the definition of customized markup languages for differentclasses of documents. In compliance with this trend, the messagesin the collaborative virtual maintenance environment can be for-matted in the ontology-based format in order to have a better com-patibility with other Internet or agent-based systems.

The ontology-based communication mechanism betweenagents is shown as Fig. 3. The messages need to be communicatedcan be productmodel, maintenance task, maintenance knowledge,etc. They can be different types and formats in different agents. Ifthe need of message transmission is appeared between agents Aand B, the message in agent A cannot be recognized in agent B atfirst hand. The procedure of message transmission based on main-tenance domain ontology is shown as follows.

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Fig. 2. Agent structure of manage agent, planning agent and maintenance agent.

Fig. 3. Agents communication mechanism based on ontology technology.

First, the message in agent A should be transformed intoontology-based representation through semantic annotation. Sec-ond, the semantic annotatedmessage can be edited through ontol-ogy editor and ontology explorer if necessary. Finally, the message

can be output as format document described by ontology language,such as RDF, OIL, DAML, OWL, KIF etc., and the format documentcan be read in agent B. In our system, the message is output as for-mat document described by ontology language DAML +OIL.

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4.2. Agents cooperation

Communication and cooperation are the different view layersof interaction. Communication allows agents in the decisionprocess to share information and co-operation allows agentsto cooperatively update some shared set of decisions. In thecollaborative virtual maintenance environment, a function agentcannot perform all product maintenance tasks and a productmaintenance plan should be carried out by several agents such asmanage agent, function agent and information agent. Co-operationrequires two ormore agentswho contribute to a common task, anda crucial point for successful cooperation is the manner in whichindividual work is related to the group as a whole. In our system,the co-operation model is designed as follows:Cooperation = ⟨A,G, P, T , S⟩where

A: Co-operation agent. The co-operation agent presents the co-operation goal and plans the co-operation tasks, and it also selectsthe co-operation team. In our system, manage agent is the co-operation agent.

G: Co-operation goal. The co-operation goal presented by co-operation agent is composed of two parts, task and its perfor-mances.

P: Co-operation planning. The co-operation planning is todecide the roles for the co-operation goal and the relationsbetween the roles.

T : Co-operation team, and A ∈ T . The co-operation team isset up by the co-operation agent according to the co-operationplanning and the status of every agent.

S: Co-operation solution, and S ∈ P . The co-operation solutionis the result of the co-operation planning. It is the foundation oftasks execution.

According to the co-operation model, the procedure of agentsco-operation can be divided into six steps shown as follows.

(1) Cooperation agent presents a co-operation goal according tothe product maintenance requirement; (2) co-operation planningand getting the co-operation structure; (3) selecting the co-operation team according to the co-operation structure and thestatus of every agent; (4) selecting the co-operation solution;(5) evaluating the co-operation solution; (6) realizing the co-operation goal and executing the co-operation solution.

5. Algorithm for competition conflicts

As a distributed, heterogeneous and intelligent system, compe-tition among the agents is a common and important problem. Analgorithm based on fuzzy comprehensive evaluation is designed tosolve the competition conflicts and the procedure of the algorithmis described as follows.(1) The manager agent presents a coordination goal G;(2) Themanager agent generates a set of bid agents B and a set of

evaluation agents E , the number of set B is k and the numberof set E is n;

Where the bid agents should be instances of one kindof function agent and evaluation agents can be instances ofany kind of agents such as manage agent, function agent andinformation agent.

(3) The manager agent proposes a set of evaluation criteria Cdescribed as follows:

C = {c1, c2, c3, . . . , cm}.

(4) The manager agent establishes a set W of weightingcoefficients for the evaluation criteria described as follows:

W = {w1, w2, w3, . . . , wm}

m−1

wi = 1 wi > 0 (i = 1, 2, 3, . . .m).

(5) Each evaluation agent gives its estimation for a bid agentaccording to the evaluation criteria C and a single evaluationmatrix R is generated as follows:

R =

r11, r12, r13, . . . , r1nr21, r22, r23, . . . , r2n. . . . . . . . . . . . . . .rm1, rm2, rm3, . . . , rmn

where rij is the evaluation score that evaluation agent j (j =

1, 2, 3, . . . , n) evaluates the bid agent according to evaluationcriterion i (i = 1, 2, 3, . . . ,m).

(6) According to the weighting coefficients and single evaluationmatrix, a comprehensive evaluation matrix T is generated asfollows:

T = W • R= (w1, w2, w3, . . . , wm)

•

r11, r12, r13, . . . , r1nr21, r22, r23, . . . , r2n. . . . . . . . . . . . . . .rm1, rm2, rm3, . . . , rmn

= (t1, t2, t3, . . . , tn).

(7) According to maximum degree of membership method, thefinal estimation Vi of bid agent i is proposed as followings:

Vi = {vL|vL → maxj

tj}.

(8) Repeat the operations from step (5) to step (7) and getestimations of all bid agents.

(9) Compare with each other and get the optimal solution.(10) End.

6. The collaborative virtual maintenance environment

The collaborative virtual maintenance environment with agenttechnology has been set up and implemented by VC 6.0 shownas Fig. 4. In this section, a product called lunar rover maintenanceexample is proposed to show the running process of our system.

6.1. Agents co-operation process

In the proposed system, interface agent, manager agent, eval-uation agent, planning agent, simulation agent and maintenanceagent work autonomously and collaboratively to perform productmaintenance tasks. The co-operation among these agents is sup-ported by the common goal and shared maintenance knowledge.The sequence diagram of such cooperation is presented through anexample shown as Fig. 5. (1) Production department sends a prod-uct maintenance plan and our system accepts the plan throughthe interface agent. (2) Based on the plan, the interface agent getsthe product models from CAD system and sends them to manageragent. (3) The manager agent assigns a task to evaluation agent toevaluate the product models. (4) The evaluation agent performsits operation and (5) sends the evaluation report to the manageragent. Themanager agentwill checkwhether the evaluation reporthas a conflict. If there is any conflict, (6) the conflict and suggestionwill be output through interface agent. If there is no conflict, (7) themanager agent will decompose the maintenance plan into severaltasks. (8) The manager agent sends maintenance planning task toplanning agent and (9) themaintenance planning result will be fedback to the manager agent. (10) The manager agent sends mainte-nance process simulation task with the maintenance planning re-sult to simulation agent and (11) the simulation result will be fedback to the manager agent. (12) The manager agent sends product

178 X. Liu et al. / Journal of Manufacturing Systems 29 (2010) 173–181

Fig. 4. Collaborative virtual maintenance environment with agent technology.

Fig. 5. Sequence diagram of agents co-operation.

X. Liu et al. / Journal of Manufacturing Systems 29 (2010) 173–181 179

Fig. 6. Information integration interface.

maintenance task with the maintenance planning result and sim-ulation result to maintenance agent, and (13) the maintenance re-sult will be fed back to the manager agent. (14) Themanager agentwill perform task scheduling operation. (15) After all tasks finished,the product maintenance plan will be fed back to the maintenancedepartment with its status and the maintenance data of the givenproduct.

6.2. Example of agents communication

In the process of agents co-operation, product maintenancedata such as product model, maintenance task and maintenanceknowledge are represented as ontology-based format to solvethe problem of information semantic heterogeneity among agentscommunication and the information integration interface is shownas Fig. 6. Information exchange is carried out by the interfaceagent between CAD systems such as Pro/E, UG, AutoCAD, Citia,etc., and the collaborative virtual maintenance environment.In collaborative virtual maintenance environment, informationexchange among the agents is carried out by the external interfaceof agent.

6.3. Example of competition conflicts resolution

Moreover, an experiment example is illustrated to demonstratethat the proposed algorithm in Section 5 is feasible and efficient.In this experiment, two maintenance agent instances (such asmaintenance agent 01 and maintenance agent 02, to be brief, theyare named agents b1 and b2) are registered to compete for a productmaintenance operation task (such as disassembling the trailingwheel). The procedure and parameters of the algorithm is shownas follows:

(1) The co-ordination goal G: maintenance task assignment.

(2) The set of bid agents B : B = {b1, b2} and the set of evaluationagents E:

E = {e1, e2, e3, e4, e5}.

(3) The set of evaluation criteria C :

C = {c1, c2, c3, c4, c5, c6, c7};

wherec1: capability of the bid agent;c2: specialty of the bid agent;c3: load of the bid agent;c4: reliability of the bid agent;c5: priority of the bid agent;c6: cost of the bid agent;c7: status of the bid agent.

(4) The setW ofweighting coefficients for the evaluation criteria:

W = {0.30, 0.25, 0.20, 0.10, 0.05, 0.05, 0.05}.

(5) The set of evaluation referencesV : V = {best, better, good,

bad}.(6) Each evaluation agent gives its estimation for a bid agent

according to the evaluation criteria C and the singleevaluation matrixes R1, R2 of bid agents b1, b2 are generatedas follows:

R1 =

0.55, 0.35, 0.10, 0.000.50, 0.50, 0.00, 0.000.30, 0.40, 0.20, 0.100.40, 0.30, 0.10, 0.200.30, 0.20, 0.10, 0.400.25, 0.25, 0.25, 0.250.30, 0.20, 0.10, 0.40

,

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R2 =

0.35, 0.40, 0.15, 0.100.40, 0.45, 0.05, 0.100.35, 0.20, 0.30, 0.150.20, 0.35, 0.25, 0.200.35, 0.25, 0.20, 0.200.20, 0.25, 0.20, 0.350.25, 0.25, 0.20, 0.30

.

(7) According to the weighting coefficients and single evaluationmatrix, the comprehensive evaluation matrixes T1, T2 of bidagents b1, b2 are generated as follows:

T1 = (0.4325, 0.3725, 0.1025, 0.1225),T2 = (0.3350, 0.3450, 0.1725, 0.1475).

(8) According to maximum degree of membership method, thefinal estimation resultsV1,V2 of bid agents b1, b2 are proposedas follows:

V1 = 0.4325, V2 = 0.3450.(9) The estimation results show that agent b1 is best and agent

b2 is better , so agent b1 wins and gets the maintenance task.(10) End.

7. Conclusions and future work

In this paper, a virtual environment that realizes the integrationand co-operation of product maintenance process is proposed.In the proposed system, the agent-based system framework,functional definition of individual agents and agent internalstructure were presented. The communication mechanism basedon ontology technology and co-operation model among theagents were elaborated. An intelligent algorithm based on fuzzycomprehensive evaluation was designed to solve the competitionconflicts among the agents. The advantages of the proposedsystem can therefore be summarized as follows: (1) autonomymeans that the collaborative virtual maintenance environmentis developed as an independent system. Once developed, it canreadily be integrated into the CAD/CAM system. Each agent isalso treated as an independent and autonomous system. (2)Flexibility permits new technologies and newmethods to be easilyadded into the collaborative virtual maintenance environment.(3) Interoperability permits multiple heterogeneous systems orapproaches to work smoothly together in solving problems.(4) Modularity enables the proposed system to function as anintegration of multiple subsystems. (5) Scalability offers theability to scale the collaborative virtual maintenance environmentarchitecture according to the user’s transaction requirements.

Ongoing and future work will focus on the improvement andextension of our system. Furthermore,more evaluation criteria andother agents such as maintenance knowledge acquisition agentand disassembly sequence optimization agent, etc., may be addedto the system.

Acknowledgements

The support of National Natural Science Foundation of China(No. 51005231, 50905047 and 50975275), National Science Foun-dation for Post-doctoral Scientists of China (No. 20100471408) incarrying out this research is gratefully acknowledged.

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