Optimal System of Loops on an Orientable Surface

Optimal Operation of Multireservoir Systems:State-of-the-Art ReviewJohn badie,M.ASCE 1Abstract:With construction of new large-scale water storage projects on the wane in the U.S.and other developed countries,attention must focus on improving the operational effectiveness and efficiency of existing reservoir systems for maximizing the beneficial uses of these projects.Optimal coordination of the many facets of reservoir systems requires the assistance of computer modeling tools to provide information for rational management and operational decisions.The purpose of this review is to assess the state-of-the-art in optimization of reservoir system management and operations and consider future directions for additional research and application.Optimization methods designed to prevail over the high-dimensional,dynamic,nonlinear,and stochastic characteristics of reservoir systems are scrutinized,as well as extensions into multiobjective optimization.Application of heuristic programming methods using evolutionary and genetic algorithms are described,along with application of neural networks and fuzzy rule-based systems for inferring reservoir system operating rules.DOI:10.1061/͑ASCE ͒0733-9496͑2004͒130:2͑93͒CE Database subject headings:Reservoir operation;State-of-the-art reviews;Optimization models;Stochastic models;Linear programming;Dynamic programming;Nonlinear programming.IntroductionAccording to the World Commission on Dams ͑WCD 2000͒,many large storage projects worldwide are failing to produce the level of benefits that provided the economic justification for their development.This may be due in some instances to an inordinate focus on project design and construction,with inadequate consid-eration of the more mundane operations and maintenance issues once the project is completed.Performance related to original project purposes may also be undermined when new unplanned uses arise that were not originally considered in the project au-thorization and development.These might include municipal/industrial water supply,minimum streamflow requirements for environmental and ecological concerns,recreational enhance-ment,and accommodating shoreline encroachment and develop-ment.Although there may exist some degree of commensurability among these diverse project purposes,there is more often conflict and competition,particularly during pervasive drought condi-tions.In addition,performance of publically owned reservoir sys-tems is often restricted by complex legal agreements,contracts,federal regulations,interstate compacts,and pressures from vari-ous special interests.With construction of new large-scale water storage projects at a virtual standstill in the U.S.and other developed countries,along with an increasing mobilization of opposition to large stor-age projects in developing countries,attention must focus on im-proving the operational effectiveness and efficiency of existing reservoir systems for maximizing the beneficial uses of these projects.In addition,many of the adverse impacts of large storage projects on aquatic ecosystems can be minimized through im-proved operations and added facilities,as demonstrated by the Tennessee Valley Authority ͑TV A ͒͑Higgins and Brock 1999͒.Construction of bottom outlets or selective withdrawal structures can pass sediments downstream and improve water quality con-ditions.Unfortunately,many existing reservoir operational poli-cies fail to consider a multifacility system in a fully integrated manner,but rather emphasize operations for individual projects.However,the need for integrated operational strategies confronts system managers with a difficult task.Expanding the scope of the working system for more integrated analysis greatly multiplies the potential number of alternative operational policies.This is further complicated by conflicting objectives and the uncertainties associated with future hydrologic conditions,including possible impacts of climate change.Optimal coordination of the many facets of reservoir systems requires the assistance of computer modeling tools to provide information for rational operational puter simula-tion models have been applied for several decades to reservoir system management and operations within many river basins.Many models are customized for the particular system,but there is also substantial usage of public domain,general-purpose mod-els such as HEC 5͑Hydrologic Engineering Center 1989͒,which is being updated as HEC RESSIM to include a Windows-based graphical user interface ͑Klipsch et al.2002͒.Spreadsheets and generalized dynamic simulation models such as STELLA ͑High Performance Systems,Inc.͒are also popular ͑Stein et al.2001͒.Other similar system dynamics simulation models include POW-ERSIM ͑Powersim,Inc.͒applied by Varvel and Lansey ͑2002͒,and VENSIM ͑Ventana Systems,Inc.͒applied by Caballero et al.͑2001͒.These simulation or descriptive models help answer what if questions regarding the performance of alternative operational strategies.They can accurately represent system operations and1Professor,Dept.of Civil Engineering,Colorado State Univ.,Ft.Collins,CO 80523-1372.E-mail:labadie@Note.Discussion open until August 1,2004.Separate discussions must be submitted for individual papers.To extend the closing date by one month,a written request must be filed with the ASCE Managing Editor.The manuscript for this paper was submitted for review and pos-sible publication on August 22,2002;approved on November 27,2002.This paper is part of the Journal of Water Resources Planning and Management ,V ol.130,No.2,March 1,2004.©ASCE,ISSN 0733-9496/2004/2-93–111/$18.00.D o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y D A L I A N U N I VE R S I T Y OF o n 06/04/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .are useful for Monte Carlo analysis in examining long-term reli-ability of proposed operating strategies.They are ill-suited,how-ever,to prescribing the best or optimum strategies when flexibil-ity exists in coordinated system operations.Prescriptive optimization models offer an expanded capability to systemati-cally select optimal solutions,or families of solutions,under agreed upon objectives and constraints.The purpose of this paper is to assess the state-of-the-art in reservoir system optimization models and consider future direc-tions.This is an update of a review that appeared in Water Re-sources Update published by The Universities Council on Water Resources ͑UCOWR ͒͑Labadie 1997͒.The focus is primarily on optimization of systems of reservoirs,rather than a single reser-voir.This is not meant to imply that single reservoir optimization is unimportant,but rather the substantial technological challenges and rewards abide with integrated optimization of interconnected reservoir systems.Optimization methods designed to prevail over the high-dimensional,dynamic,nonlinear,and stochastic charac-teristics of reservoir systems are scrutinized,as well as extensions into multiobjective optimization.Heuristic programming methods using evolutionary and genetic algorithms are described,along with the application of artificial neural networks and fuzzy rule-based systems for inferring reservoir system operating policies.Overcoming Hindrances to Reservoir System OptimizationDespite several decades of intensive research on the application of optimization models to reservoir systems,authors such as Yeh ͑1985͒and Wurbs ͑1993͒have noted a continuing gap between theoretical developments and real-world implementations.Pos-sible reasons for this disparity include:͑1͒many reservoir system operators are skeptical about models purporting to replace their judgment and prescribe solution strategies and feel more comfort-able with use of existing simulation models;͑2͒computer hard-ware and software limitations in the past have required simplifi-cations and approximations that operators are unwilling to accept;͑3͒optimization models are generally more mathematically com-plex than simulation models,and therefore more difficult to com-prehend;͑4͒many optimization models are not conducive to in-corporating risk and uncertainty;͑5͒the enormous range and varieties of optimization methods create confusion as to which to select for a particular application;͑6͒some optimization methods,such as dynamic programming,often require customized program development;and ͑7͒many optimization methods can only pro-duce optimal period-of-record solutions rather than more useful conditional operating rules.Optimal period-of-record solutions are criticized in the Engineer Manual on Hydrologic Engineering Requirements for Reservoirs ͑U.S.Army Corps of Engineers 1997;pp.4–5͒,where it is stated that ‘‘...the basis for the system operation are not explicitly defined.The post processing of the results requires interpretation of the results in order to develop an operation plan that could be used in basic simulation and applied operation.’’Many of these hindrances to optimization in reservoir system management are being overcome through ascendancy of the con-cept of decision support systems and dramatic advances in the power and affordability of desktop computing hardware and soft-ware.Several private and public organizations actively incorpo-rate optimization models into reservoir system management through the use of decision support systems ͑Labadie et al.1989͒.Incorporation of optimization into decision support systems has reduced resistance to their use by placing emphasis on optimiza-tion as a tool controlled by reservoir system managers who bear responsibility for the success or failure of the system to achieve its prescribed goals.This places the focus on providing support for the decision makers,rather than overly empowering computer programmers and modelers.An example of an optimization model incorporated into a de-cision support system ͑DSS ͒is the MODSIM river basin network flow model ͑Labadie et al.2000͒,which is currently being used by the U.S.Bureau of Reclamation for operational planning in the Upper Snake River Basin,Idaho ͑Larson et al.1998͒.The Windows-based graphical user interface ͑GUI ͒in MODSIM al-lows the user to create any reservoir system topology by simply clicking on various icons and placing system objects in any de-sired configuration on the screen.Data structures embodied in each model object on the screen are controlled by a database management system,with formatted data files prepared interac-tively and a network flow optimization model automatically ex-ecuted from the interface.Results of the optimization are pre-sented in useful graphical plots,or even customized reports available through a scripting language included with MODSIM .Complex,non-network constraints on the optimization in MOD-SIM are incorporated through an iterative procedure using the embedded PERL scripting language.RiverWare ͑Zagona et al.1998͒affords similar DSS functionality with an imbedded pre-emptive goal programming model providing the optimization ca-pabilities.RiverWare has been successfully applied to the TV A system for operational planning ͑Biddle 2001͒.Although lacking a generalized Windows-based graphical user interface,CALSIM has been developed by the California Depart-ment of Water Resources to allow specification of objectives and constraints in strategic reservoir systems planning and operations without the need for reprogramming ͑Munevar and Chung 1999͒.Similar to the use of PERL script in MODSIM,CALSIM employs an English-like modeling language called WRESL ͑Water Re-sources Engineering Simulation Language ͒that allows planners and operators to specify targets,objectives,guidelines,con-straints,and associated priorities,in ways familiar to them.Simple text file output,along with time series and other data read from relational data bases,are passed to a mixed integer linear programming solver for period by period solution.CALSIM II replaces the DWRSIM and PROSIM models that required con-tinual reprogramming as new objectives and constraints were specified,for coordinated operation of the Federal Central Valley and California State Water Projects.OASIS ͑HydroLogics,Inc.͒is a similar modeling package to CALSIM that uses an Operations Control Language ͑OCL ͒for developing linear programming models for multiobjective analysis of water resource systems.The explosion of readily available information through the In-ternet has increased the availability of advanced optimization methods and provided freely accessible software and data re-sources for successful implementation.Many powerful optimiza-tion software packages are available through the Internet,such as from the Optimization Technology Center ͑Northwestern Univer-sity and Argonne National Laboratory,Argonne,Illinois ͒at ͗/otc/otc.html ͘.In addition,several spreadsheet software packages available on desktop computers include linear and nonlinear programming solvers in their numeri-cal toolkits.The generalized dynamic programming package CSUDP ͑Labadie 1999͒facilitates the use of dynamic program-ming models,avoiding the need to develop new code for each application.CSUDP software is freeware and can be downloaded at ͗ftp:///distrib/͘.D o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y D A L I A N U N I VE R S I T Y OF o n 06/04/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .The power and speed of the modern desktop computer have reduced the degree of simplifications and approximations in res-ervoir system optimization models required in the past,and opened the door to greater realism in optimization modeling.The primacy of the system manager over the model is also empha-sized in the incorporation of knowledge-based expert systems into reservoir system modeling which recognize the value of the in-sights and experience of reservoir system operators.Despite these advances,optimization of the operation of an integrated system of reservoirs still remains a daunting task,particularly with attempts to realistically incorporate hydrologic uncertainties.Reservoir System Optimization Problem Objective FunctionAccording to the ASCE Task Committee on Sustainability Crite-ria ͑1998͒,‘‘Sustainable water resource systems are those de-signed and managed to fully contribute to the objectives of soci-ety,now and in the future,while maintaining their ecological,environmental and hydrological integrity.’’Objective functions used in reservoir system optimization models should incorporate measures such as efficiency ͑i.e.,maximizing current and future discounted welfare ͒,survivability ͑i.e.,assuring future welfare ex-ceeds minimum subsistence levels ͒,and sustainability ͑i.e.,maxi-mizing cumulative improvement over time ͒.Loucks ͑2000͒states that ‘‘sustainability measures provide ways by which we can quantify relative levels of sustainability...One way is to express relative levels of sustainability as separate weighted combinations of reliability,resilience and vulnerability measures of various cri-teria that contribute to human welfare and that vary over time and space.These criteria can be economic,environmental,ecological,and social.’’The strategy of shared vision modeling ͑Palmer 2000͒is useful for enhancing communication among impacted stakeholders and attaining consensus on planning and operational goals.A generalized objective function for deterministic reservoir system optimization can be expressed asmax ͑or min ͒r͚t ϭ1T␣t f t ͑s t ,r t ͒ϩ␣T ϩ1␸T ϩ1͑s T ϩ1͒(1)where r t ϭn -dimensional set of control or decision variables ͑i.e.,releases from n interconnected reservoirs ͒during period t ;T ϭlength of the operational time horizon;s t ϭn -dimensional state vector of storage in each reservoir at the beginning of period t ;f t (s t ,r t )ϭobjective to be maximized ͑or minimized ͒;␸T ϩ1(s T ϩ1)ϭfinal term representing future estimated benefits ͑or costs ͒be-yond time horizon T ;and ␣t ϭdiscount factors for determining present values of future benefits ͑or costs ͒.The dynamic nature of this problem reflects the need to repre-sent an uncertain future for sustainable water management;i.e.,‘‘...a future we cannot know,but which we can surely influence’’͑Loucks 2000͒.The time step t used in this formulation may be hourly,daily,weekly,monthly,or even seasonal,depending on the nature and scope of the reservoir system optimization prob-lem.Hierarchical strategies may also be pursued whereby results from long-term monthly or seasonal studies provide input to more detailed short-term operations over hourly or daily time periods ͑Becker and Yeh 1974;Divi and Ruiu 1989͒.The objective function may be highly nonlinear,such as for maximizing hydropower generationf t ͑s t ,r t ͒ϭ͚i ϭ1nK •e i ͑s it ,s i ,t ϩ1,r it ͒•h ¯it ͑s it ,s i ,t ϩ1͒•r it •⌬t it (2)where e i ϭoverall powerplant efficiency at reservoir i as a func-tion of average head and discharge during period t ;h ¯it ϭaveragehead as a function of beginning and ending period storage levels ͑calculated from the reservoir mass balance or system dynamics equation ͒,as well as possibly the discharge if tailwater effects are included;K ϭunit conversion factor;and ⌬t it ϭnumber of on-peak hours related to the load factor for powerplant i .This is a highly nonconvex function characterized by many local maxima ͑Tauxe et al.1980͒,and may be discontinuous and nondifferentiable if loading of individual turbines in the powerplant is considered.Other objective functions related to vulnerability criteria may at-tempt to minimize deviations from ideal target storage levels,water supply deliveries,discharges,or power capacities.If eco-nomic benefit and cost estimates are available for these uses,then the objective may be to maximize total expected net benefits from operation of the system,but with consideration of long-term sus-tainability.ConstraintsThe system dynamics or state-space equations are written as fol-lows,based on preservation of conservation of mass throughout the system:s t ϩ1ϭs t ϩCr t ϩq t Ϫl t ͑s t ,s t ϩ1͒Ϫd t͑for t ϭ1,...,T ͒(3)where s t ϭstorage vector at the beginning of time t ;q t ϭinflow vector during time t ;C ϭsystem connectivity matrix mapping flow routing within the system;l t ϭvector combining spills,evaporation,and other losses during time t ;and d t ϭrequired de-mands,diversions,or depletions from the system.In some formu-lations,diversions are treated as decision variables and included in the objective function as related to benefits of supplying water.Accurate calculation of evaporation and other water losses in the term l t (s t ,s t ϩ1)creates a set of nonlinear implicit equations in s t ϩ1which can be difficult to evaluate and constitute a nonconvex feasible set.Initial storage levels s 1are assumed known and all flow units in Eq.͑3͒are expressed in storage units per unit time.Spatial connectivity of the reservoir network is fully described by the routing or connectivity matrix C .For the example reservoir system of Fig.1,the connectivity matrixisFig.1.Example reservoir system configurationD o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y D A L I A N U N I VE R S I T Y OF o n 06/04/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .C ϭͫϪ10000Ϫ1000ϩ1Ϫ10ϩ1ϩ1Ϫ1ͬAdditional state variable nodes with zero storage capacity may represent nonstorage locations where inflows and diversions occur.For more complex system configurations that are nonden-dritic,such as bifurcating systems and off-stream reservoirs,a more complex link-node connectivity matrix is gged routing of flows can be considered by replacing the term Cr t inEq.͑3͒with ͚␶ϭ0kC ␶r t Ϫ␶,where elements of the routing matrices C ␶may be fractions representing lagging and attenuation of downstream releases.Explicit lower and upper bounds on storage must be assigned for recreation,providing flood control space,and assuring mini-mum levels for dead storage and powerplant operation.s t ϩ1,min рs t ϩ1рs t ϩ1,max͑for t ϭ1,...,T ͒(4)Limits on reservoir releases are specified asr t ,min рr t рr t ,max͑for t ϭ1,...,T ͒(5)These limits maintain minimum desired downstream flows for water quality control and fish and wildlife maintenance,as well as protection from downstream flooding.In some cases,it may be necessary to specify these limits as functions of head where al-lowable discharges depend on reservoir storage levels.Additional constraints may be imposed on the change in release from one period to the next to provide protection from scouring of down-stream channels.When evaluating long term historical or syn-thetic hydrologic sequences,or multiple short-term sequences,difficulties may arise in finding feasible solutions that satisfy these constraints.In these cases,it may be necessary to relax these as explicit constraints and indirectly consider them through use of weighted penalty terms on violation of these constraints in the objective function.Other constraints may represent alternative objectives that must be maintained at desired target levels ␧:f ¯͑s ,r ͒у␧(6)Example targets might include annual water supply requirements or power capacity maintenance.These targets may be adjusted parametrically to compute tradeoff relations between the primary objective of Eq.͑1͒and secondary objectives as a means of pro-viding multiple objective solutions ͑Cohon 1978͒.The optimization model defined in Eqs.͑1͒–͑6͒is challenging to solve since it is dynamic,potentially nonlinear,and nonconvex;and large-scale.In addition,unregulated inflows,net evaporation rates,hydrologic parameters,system demands,and economic pa-rameters should often be treated as random variables,giving rise to a complex large-scale,nonlinear,stochastic optimization prob-lem.In this formulation,it is assumed that calibration and verifi-cation studies have been carried out to assure the model is capable of reasonably reproducing historical energy production,storage levels,and flows throughout the system.This review explores several solution strategies,including implicit stochastic optimiza-tion,explicit stochastic optimization,real-time optimal control with forecasting,and heuristic programming methods.For more detailed treatment of these topics,the reader is referred to a num-ber of important books written over the years dealing with opti-mization of water resource systems in general,and optimal opera-tion of reservoirs in particular.These include:Maass et al.͑1962͒;Hall and Dracup ͑1970͒;Buras ͑1972͒;Loucks et al.͑1981͒;Mays and Tung ͑1992͒;Wurbs ͑1996͒;and ReVelle ͑1999͒.Implicit Stochastic OptimizationThe solution of Eqs.͑1͒–͑6͒may be accomplished by implicit stochastic optimization ͑ISO ͒methods,also referred to as Monte Carlo optimization,which optimize over a long continuous series of historical or synthetically generated unregulated inflow time series,or many shorter equally likely sequences ͑Fig.2͒.In this way,most stochastic aspects of the problem,including spatial and temporal correlations of unregulated inflows,are implicitly in-cluded and deterministic optimization methods can be directly applied.The primary disadvantage of this approach is that optimal operational policies are unique to the assumed hydrologic time series.Attempts can be made to apply multiple regression analy-sis and other methods to the optimization results for developing seasonal operating rules conditioned on observable information such as current storage levels,previous period inflows,and/or forecasted inflows.Unfortunately,regression analysis may result in poor correlations that invalidate the operating rules,and at-tempting to infer rules from other methods may require extensive trial and error processes with little general applicability.Linear Programming ModelsSince ISO models can be extremely large-scale,covering a lengthy time horizon,it is critical that only the most efficient optimization methods are applied.One of the most favored opti-mization techniques for reservoir system models is thesimplexFig.2.Implicit stochastic optimization ͑ISO ͒procedureD o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y D A L I A N U N I VE R S I T Y OF o n 06/04/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .method of linear programming and its variants ͑Nash and Sofer 1996͒.These models require all relations associated with Eqs.͑1͒–͑6͒to be linear or linearizable.The advantages of linear pro-gramming ͑LP ͒include:͑1͒ability to efficiently solve large-scale problems;͑2͒convergence to global optimal solutions;͑3͒initial solutions not required from the user;͑4͒well-developed duality theory for sensitivity analysis;and ͑5͒ease of problem setup and solution using readily available,low-cost LP solvers.Recent al-ternatives to the simplex method,such as the affine scaling and interior projection methods ͑Terlaky 1996͒,are particularly attrac-tive for solving extremely large-scale problems.Hiew et al.͑1989͒applied ISO using LP to the eight-reservoir Colorado-Big Thompson ͑C-BT ͒project in northern e of a 30year historical hydrologic record of monthly unregu-lated inflows to the system resulted in a linear programming prob-lem with 12,613variables and 5,040constraints.Multiple regres-sion analysis was applied to the LP model results to produce optimal lag-one storage guide curves:s t ϩ1ϭA ¯s t*ϩB ¯q t Ϫ1ϩc ¯(7)where s t *ϭoptimal storage levels obtained from the linear pro-gramming solution;q t ϭobserved hydrologic inflows;and corre-lation matrices A ¯,B ¯and vector c ¯are calculated from multiple regression analysis performed on the LP results.Coefficients of determination obtained from this analysis ranged from 0.795to 0.996for the larger reservoirs,with the remaining reservoirs ei-ther small or with water levels only allowed to vary a few feet per year.Simulation of the system operations using the optimal stor-age guide curves of Eq.͑7͒confirmed their validity.This study was successful because of the ability of linear models to accu-rately represent the system behavior,along with the fortunate cal-culation of high correlation coefficients obtained from the mul-tiple regression analysis.For other systems,these advantages may not be in evidence.Other extensions of linear programming into binary,integer,and mixed-integer programming may be valuable for representing highly nonlinear,nonconvex terms in the objective function and constraints ͑e.g.,Trezos 1991͒,but these methods are consider-ably less efficient computationally and would likely be intractable for use in ISO.Needham et al.͑2000͒applied mixed integer lin-ear programming to deterministic flood control operations in the Iowa and Des Moines Rivers,but noted the potential for exces-sive computer times when extended to stochastic evaluation.This study came to the rather counterintuitive conclusion that coordi-nated operation of reservoir systems does not necessarily improve performance,which stands in stark contrast with other studies that have shown just the opposite ͑e.g.,Shim et al.2002͒.Piecewise linear approximations of nonlinear functions are often used in separable programming applications and solved with various extensions of the simplex method,although problem size can become excessive in some cases.Functions of more than one variable can be approximated using multilinear interpolation methods over a multidimensional grid.For minimization prob-lems,these functions must be convex;otherwise,more time con-suming restricted basis entry simplex algorithms must be applied which fail to guarantee convergence to global optima.Crawley and Dandy ͑1993͒applied separable programming to the multi-reservoir Metropolitan Adelaide water supply system in Australia.Network Flow Optimization ModelsIt is evident from Fig.1that an interconnected reservoir system can be represented as a network of nodes and links ͑or arcs ͒.Nodes are storage or nonstorage points of confluence or diver-sion,and links represent reservoir releases,channel or pipe flows,carryover storage,and evaporation and other losses.If all rela-tions in Eqs.͑1͒–͑5͒are linear,then the following dynamic,mini-mum cost network flow problem results:minimize͚t ϭ1T͚ᐉ෈Ac ᐉt x ᐉt(8)subject to͚j ෈O ix jt Ϫ͚k ෈I ix kt ϭ0͑for all i ෈N ;for all t ϭ1,...,T ͒(9)l ᐉt рx ᐉt рu ᐉt ͑for all ᐉ෈A ;for all t ϭ1,...,T ͒(10)where A ϭset of all arcs or links in the network;N ϭset of nodes;O i ϭset of all links originating at node i ͑i.e.,outflow links ͒;I i ϭset of all links terminating at node i ͑i.e.,inflow links ͒;x ᐉt ϭflow rate in link ᐉduring period t ;c ᐉt ϭcosts,weighting factors,or priorities per unit of flow rate in link ᐉduring period t ;and l ᐉt and u ᐉt ϭlower and upper bounds,respectively,on flow in link ᐉ.Fig.3illustrates a fully dynamic network where the horizontal arcs represent carryover storage ͑i.e.,s t )in the same physical reservoir from one period to the next,whereas the vertical arcs are flows,releases,and diversions ͑i.e.,r t )during the current period.Eqs.͑8͒–͑10͒define a pure network formulation where all network data can be represented by a set of arc parameters ͓l ᐉt ,u ᐉt ,c ᐉt ͔.For fully circulating networks,additional artificial nodes and links must be added for satisfying overall mass balance throughout the entire parative studies by Kuczera ͑1993͒and Ardekaaniaan and Moin ͑1995͒have shown the dual coordinate ascent RELAX algorithm ͑Bertsekas and Tseng 1994͒to be the most efficient network solver,as compared to primal-based algorithms and variations on the out-of-kilter method ͑Ford and Fulkerson 1962͒.Several network algorithms allow designation of node supply and demand ͓i.e.,entry of values other than zero on the right-hand side of Eq.͑9͔͒without requiring specification of artificial nodes and links,although this is only possible when no demand shortages occur.For so-called networks-with-gains ,Eq.͑9͒must be adjusted with coefficients not equal to Ϫ1,0,or ϩ1to allow for channel losses,evaporation losses,and return flows.Further extensions into generalized networks allow inclusion of side con-straints ͓i.e.,Eq.͑6͔͒that violate the pure network structure.All of these deviations from the pure network format exact acompu-Fig.3.Illustration of dynamic network showing carryover storagearcsD o w n l o a d e d f r o m a s c e l i b r a r y .o r g b y D A L I A N U N I VE R S I T Y OF o n 06/04/14. C o p y r i g h t A S C E . F o r p e r s o n a l u s e o n l y ; a l l r i g h t s r e s e r v e d .。

到9月9日，社保基金正式进入股市整整3个月，按照有关规定，社保基金必须通过基金管理公司在三个月内完成建仓，并且其持仓市值要达到投资组合总市值80%的水平。

与此前大受追捧的QFII概念相比，社保基金及其所持有的股票显然低调得多，但是在西南证券分析师田磊看来，至少就目前来看，社保基金无论是在资金规模，还是在持股数量上明显都强于境外投资者，其投资理念和行为更可能给市场带来影响。

基金操作的社保基金的选股思路并不侧重某个行业，而更看重企业本身的发展和成长性，并且现阶段的企业经营业绩和走势也不是基金重点考虑的方面。

目前入市的社保基金都是委托南方、博时、华夏、鹏华、长盛、嘉实6家基金管理公司管理。

社保基金大致是被分为14个组合由以上6家管理公司分别管理，每个组合都有一个三位数的代码，第一位代表投资方向，其中“1”指股票投资、“2”指债券投资；第三位数字则代表基金公司名称，其中“1”为南方、“2”为博时、“3”为华夏、“4”为鹏华、“5”为长盛、“6”为嘉实；另有107、108组合主要运作社保基金此前一直持有的中石化股票，分别由博时与华夏基金公司管理。

在许多社保基金介入的股票中经常可以看到开放式基金的身影，例如在被社保基金大量持有的安阳钢铁(600569)的前10大股东中，其第2、6、7、8、9大股东均为开放式基金，而社保基金则以持股500多万股位列第3大股东。

类似的情况也出现在社保基金103组合所持有的华菱管线(000932)上，其第二大股东即为鹏华行业成长证券投资基金，社保基金则以200多万股的持仓量位列第7大股东，此外，在其前10大股东中还有5家是封闭式基金。

对此，某基金公司人士解释说，在获得社保基金管理人资格后，6家基金公司成立了专门的机构理财部门负责社保基金的投资管理，但是其研究、交易系统等则与公募基金共用一个平台，因此社保基金和开放式基金在选股时才会如此一致。

针对“社保概念股”的走势，国盛证券的分析师王剑认为，虽然社保基金此次委托入市资金超过百亿元，但大部分投向是债券，而且由于社保基金的特殊地位，因此基金管理公司对社保基金的操纵策略应该是以“集中持股，稳定股价”为主，不大可能博取太高的收益。

第26卷第5期2007年9月热带海洋学报J OU RNAL OF TROPICAL OCEANO GRA P H YVol 126,No.5Sep .,2007 收稿日期:2007201215;修订日期:2007203206。

孙淑杰编辑 基金项目:国家重点基础研究发展规划项目(2001CB409708);广东省自然科学基金重点项目(06105018) 作者简介:杨锦坤(1980—)男,河北省沧县人,硕士研究生,主要从事海洋水色遥感研究。

E 2mail :yangjk80529@1261com 珠江口二类水体水色三要素的优化反演杨锦坤,陈楚群(中国科学院南海海洋研究所热带海洋环境动力学重点实验室,广东广州510301)摘要:根据2003年1月珠江口实测资料获得的相关参数,建立了适用于该海域的二类水体水色三要素优化反演模型,同步优化反演得到了与2003年1月25—26日实测站点相对应的2003年1月29日的SeaWiFs 图像像元点的水色三要素,反演与实测水色三要素的平均相对误差分别为:叶绿素1419%,悬浮泥沙1211%,黄色物质1316%。

研究结果说明本研究建立的优化反演模型比较适用于珠江口二类水体水色三要素的反演,且具有较高的反演精度。

关键词:二类水体;优化反演;水色要素;正演模型;大气校正;珠江口中图分类号:TP79文献标识码:A文章编号:100925470(2007)0520015206An optimal algorithm for retrieval of chlorophyll ,suspended sediments andgelbstoff of case Ⅱw aters in Zhujiang River estuaryYAN G Jin 2kun ,C H EN Chu 2qun(L ED ,S out h Chi na S ea I nstit ute of Oceanolog y ,Chinese A cadem y of S ciences ,Guangz hou 510301,China )Abstract :An optimal algorit hm for t he retrieval of chlorop hyll ,suspended sediment s and gelbstoff of caseⅡwaters in t he Zhujiang River est uary was established wit h t he optical parameters derived f rom t he in 2sit u data obtained in J an 12003in t he same area.And t hen ,t he chlorop hyll ,suspended sediment s and gelbstoff of t he SeaWi FS pixels on J an.29,2003corresponding to t he in 2sit u sites of J an.25and 26,2003were synchronously ret rieved ,wit h average relative errors of 1419%,1211%and 1316%for chlorop hyll ,sus 2pended sediment s and gelbstoff ,respectively.The research result s indicated t hat t he optimal ret rieval al 2gorit hm established here was relatively fit for t he retrieval of t he chlorop hyll ,suspended sediment s and gelbstoff of case Ⅱwaters in t he Zhujiang River est uary ,and had quite good retrieval accuracy.K ey w ords :case Ⅱwaters ;optimal ret rieval ;ocean color constit uent ;forward model ;at mo sp heric correc 2tion ;Zhujiang River est uary 叶绿素、黄色物质和悬浮泥沙是通常所称的“水色三要素”,是影响近岸二类水体光学性质的4种物质中的3种[1],另外一种是纯水分子。

高中英语选必四Unit5逐词英语释义1.bounce: 弹跳，反弹move quickly up, back, or away from a surface after hitting it, move in an energetic and buoyant manner2.bounce around: 四处走动，跳来跳去move or travel from place to place without any particular purpose or direction3.aptitude: 才能，天资a natural ability or skill, talent4.head start: 先发优势，领先的开始an advantage or improvement that someone has over another person or group at the beginning of something5.scenario: 情景，场景a sequence of events that is imagined or suggested, a possible situation or sequence of eventswyer: 律师，法律专家a person who practices or studies law; an attorney or a counselor7.assemble: 组装，集合fit together the separate component parts of (a machine or other object), gather together in one place for a common purpose8.drawer: 抽屉a boxlike storage compartment without a lid, made to slide horizontally in and out of a desk, chest, or other piece of furniture9.a chest of drawers: 衣柜，抽屉柜a piece of furniture consisting of a set of drawers in a frame, used for storing clothes or other items10.breast: 胸部the front surface of a person's or animal's body between the neck and the abdomen, the seat of a person's emotions and feelings11.hydrogen: 氢the chemical element of atomic number 1, a colorless gas that is the lightest and most abundant element in the universe12.radium: 镭the chemical element of atomic number 88, a rare radioactive metal of the alkaline earth series13.wrist: 手腕the joint connecting the hand with the forearm14.bridegroom: 新郎a man on his wedding day or just before and after the event15.geometry: 几何学the branch of mathematics that deals with the properties and relations of points, lines, surfaces, solids, and higher-dimensional analogs16.debt: 债务，欠款something, typically money, that is owed or due17.categorize: 分类，归类place in a particular class or group, assign to a category18.profile: 侧面，轮廓an outline of something, especially a person's face, as seen from one side19.participant: 参与者，参赛者a person who takes part in or becomes involved in a particular activity or event20.code: 代码，密码a system of words, letters, figures, or other symbols substituted for other words, letters, etc., especially for the purposes of secrecy21.orient: 定位，适应align or position (something) relative to the points of a compass or other specified positions22.detective: 侦探，刑警a person, typically a member of a police force, who investigates crimes and obtains evidence or information23.graphic: 图形的，图表的relating to visual art, especially involving drawing, engraving, or lettering24.estate: 地产，房地产a property consisting of houses, land, buildings, or other assets25.(real) estate agent: 房地产经纪人，房产中介a person who arranges the buying, selling, or renting of properties for clients26.accountant: 会计师a person whose job is to keep financial accounts of a business or person27.spy: 间谍，间谍活动a person who secretly collects and reports information about the activities, movements, and plans of an enemy or competitor28.justice: 正义，法官just behavior or treatment, a judge or magistrate, in particular, a judge of the Supreme Court of a country or state29.accuse: 指责，控告claim that (someone) has done something wronge to a conclusion: 得出结论，作出决定make a decision or form an opinion after considering all the relevant facts or evidence31.greedy: 贪婪的，贪心的having or showing an intense and selfish desire for something, especially wealth or power32.entrepreneur: 企业家a person who sets up a business or businesses, taking on financial risks in the hope of profit33.receptionist: 接待员，前台接待a person employed in an office or other establishment to answer the telephone, deal with clients, and greet visitors34.CV (NAmE résumé): 简历a brief account of a person's education, qualifications, and previous experience, typically sent with a job application35.socialist: 社会主义者a person who advocates or supports socialism, a political and economic theory of social organization that advocates for public or community ownership and control of the means of production and distributionmunist: 共产主义者a person who supports or advocates communism, a political ideology and socio-economic system that advocates for the common ownership of the means of production and the absenceof social classes37.dedicate: 奉献，致力于devote (time, effort, or oneself) to a particular task or purpose38.fox: 狐狸，狡猾的人a carnivorous mammal of the dog family with a pointed muzzle and bushy tail, or a person who is clever, cunning, or sly39.council: 委员会，议会a group of people who meet regularly to discuss matters of common interest, a local administrative or advisory body40.canal: 运河，水道an artificial waterway constructed to allow the passage of boats or ships inland or to convey water for irrigation40.canal: 运河，水道an artificial waterway constructed to allow the passage of boats or ships inland or to convey water for irrigation41.attend to: 注意，照料give attention to or deal with (someone or something)42.supervise: 监督，管理oversee (a process, work, workers, etc.) during its course, ensuring that it is done correctly or according to regulations43.handwriting: 笔迹，书法the character or style of a person's writing by hand; penmanship44.disk: 磁盘，光盘a flat, thin, round object or plate, typically made of metal, plastic, or rubber, that is used as a container for storing or playing music or data45.parking: 停车the action or practice of leaving a vehicle temporarily in a particular place46.camel: 骆驼a large, long-necked ungulate mammal of the desert or plains, with characteristic humps on its back and long legs, used as a domestic draft and milk animal and as a beast of burden47.fry: 煎，油炸cook (food) in hot fat or oil, typically in a shallow pan48.purse: 钱包，小提包a small pouch of leather or other flexible material, used for carrying money, cards, and personal identification49.sew: 缝，缝制join, fasten, or repair (something) by making stitches with a needle and thread ora sewing machine50.knit: 编织，针织make (a garment, blanket, etc.) by interlocking loops of wool or other yarn with knitting needles or on a machine51.wool: 羊毛the fine, soft curly or wavy hair forming the coat of a sheep, goat, or similar animal, especially when shorn and prepared for use in making cloth or yarn52.intermediate: 中级的，中间的coming between two things in time, place, order, character, etc.53.priority: 优先权，重点the fact or condition of being regarded or treated as more important than others54.proficiency: 熟练，精通a high degree of competence or skill; expertise55.cage: 笼子a structure of bars or wires in which birds, animals, or prisoners are confined56.collar: 领子，项圈the part around the neck of a shirt, blouse, jacket, or coat, either upright or turned over and generally shaped to fit closely57.flea collar: 杀虱项圈a collar worn by pets that contains insecticides to kill or repel fleas58.finance: 财务，金融the management of large amounts of money, especially by governments or large companies59.receipt: 收据，收条a written acknowledgment that something has been received, typically including the date, the amount of money, or the goods received60.certificate: 证书an official document attesting a certain fact, proficiency, or completion of a program or course of study61.employer: 雇主a person or organization that employs people62.desert: 沙漠，荒漠a barren area of land, especially one with little precipitation, extreme temperatures, and sparse vegetation63.acquire: 获得，取得buy or obtain (an asset or object) for oneself64.Marie Curie: 玛丽·居里a Polish-born French physicist and chemist who conducted pioneering research on radioactivity and was the first woman to win a Nobel Prize65.The Communist Manifesto: 《共产党宣言》a political pamphlet written by Karl Marx and Friedrich Engels, first published in 1848, that presents the goals and principles of communism66.Olivia: 奥利维亚a feminine given name of Latin origin, meaning "olive tree"67.PETS (Public English Test System): 公共英语考试系统a standardized English language proficiency test administered in China。

Arabidopsis ROP-interactive CRIB motif-containing protein 1(RIC1)positively regulates auxin signalling and negatively regulates abscisic acid (ABA)signalling during root developmentYUNJUNG CHOI 1,YUREE LEE 1,SOO YOUNG KIM 3,YOUNGSOOK LEE 1,2&JAE-UNG HWANG 11POSTECH-UZH Global Research Laboratory,Division of Molecular Life Sciences,Pohang University of Science andTechnology (POSTECH),Pohang 790-784,Korea,2Division of Integrative Bioscience and Biotechnology,POSTECH,Pohang 790-784,Korea and 3Department of Molecular Biotechnology &Kumho Life Science Laboratory,College of Agriculture and Life Sciences,Chonnam National University,Gwangju 500-757,KoreaABSTRACTAuxin and abscisic acid (ABA)modulate numerous aspects of plant development together,mostly in opposite directions,suggesting that extensive crosstalk occurs between the signal-ling pathways of the two hormones.However,little is known about the nature of this crosstalk.We demonstrate that ROP-interactive CRIB motif-containing protein 1(RIC1)is involved in the interaction between auxin-and ABA-regulated root growth and lateral root formation.RIC1expression is highly induced by both hormones,and expressed in the roots of young seedlings.Whereas auxin-responsive gene induction and the effect of auxin on root growth and lateral root formation were suppressed in the ric1knockout,ABA-responsive gene induction and the effect of ABA on seed germination,root growth and lateral root for-mation were potentiated.Thus,RIC1positively regulates auxin responses,but negatively regulates ABA responses.Together,our results suggest that RIC1is a component of the intricate signalling network that underlies auxin and ABA crosstalk.Key-words :hormone crosstalk;lateral root;RIC protein;root growth;ROP GTPase.INTRODUCTIONAuxin and abscisic acid (ABA)are two major plant growth regulators.In general,auxin promotes the growth of vegeta-tive tissues,whereas ABA suppresses proliferation and confers stress resistance.For example,auxin promotes lateral root initiation,whereas ABA inhibits it.Auxin opens stomata,whereas ABA closes them.Such antagonistic effects of two hormones have been reported to regulate numerous stress responses and developmental and physiological pro-cesses in the plant (Gehring,Irving &Parish 1990;Casimiro et al .2003;Tanaka et al .2006).The interaction between auxin and ABA seems to be more complex during early seedlingdevelopment and primary root elongation than later on.Although both auxin and ABA are necessary for early seed-ling development,exogenously applied ABA,which presum-ably is applied at a significantly greater concentration than the endogenous hormone,inhibits growth.Primary root elon-gation is promoted by nanomolar amounts of both auxin and ABA (Gaither,Lutz &Forrence 1975;Mulkey,Kuzmanoff &Evans 1982),but is inhibited by higher concentrations of these hormones (Pilet &Chanson 1981;Mulkey et al .1982;Eliasson,Bertell &Bolander 1989).The observation that the two hormones function together to regulate many responses indicates that the signalling pathways that transduce the primary hormonal signals to downstream responses may intersect at specific points and/or involve common players.Indeed,the expression of ABA INSENSITIVE 3(ABI3)is activated by both auxin and ABA,and ABI3functions as a positive regulator of ABA-mediated inhibition of seed ger-mination and as a negative regulator of auxin-mediated lateral root formation and ABA-mediated inhibition of primary root growth (Brady et al .2003;Zhang,Garreton &Chua 2005).Given the vast array of responses of plants to auxin and ABA,one would expect that many such points of crosstalk exist;however,this aspect of auxin and ABA signal transduction remains largely unexplored.Rho family GTPases act as molecular switches that mediate diverse cellular responses to multiple extracellular signal including hormones (Bos 2000).ROP (Rho of plants;also called RAC)GTPases represent the sole Rho family of Ras-related G proteins in plants (Yang 2002),and the model plant Arabidopsis contains 11ROP GTPases in its genome (Bischoff et al .1999;Winge et al .2000;Zheng &Yang 2000).Several studies have reported that ROP GTPases play impor-tant roles in auxin-and ABA-related responses (Lemichez et al .2001;Tao,Cheung &Wu 2002;Zheng et al .2002;Bloch et al .2005;Tao et al .2005).Auxin treatment increases the amount of activated ROP GTPase in tobacco (Tao et al .2002)and Arabidopsis (Xu et al .2010;Lin et al .2012)seed-lings.Overexpression of wild-type or constitutively active forms of ROP GTPases stimulates auxin-related phenotypes and auxin-responsive gene expression in Arabidopsis and tobacco (Li et al .2001;Tao et al .2002,2005).Activated ROP GTPases promote the 26S proteasome-dependentCorrespondence:Y.Lee.Fax:+82542792199;e-mail:ylee@postech.ac.kr;J-U.Hwang.Fax:+82542792199;e-mail:thecute@postech.ac.krY.L.and J-U.H.contributed equally to the manuscript.Plant,Cell and Environment (2013)36,945–955doi:10.1111/pce.12028©2012Blackwell Publishing Ltd945degradation of auxin/indole-3-acetic acid(AUX/IAA)pro-teins in tobacco and Arabidopsis(Tao et al.2005).ROP GTPase mutations cause defects in auxin-dependent cell expansion(Fu et al.2005,2009;Xu et al.2010).In contrast to the positive role of ROP GTPases in the auxin response, ROP GTPases appear to be negative regulators of ABA responses.ABA treatment reduces the amount of activated ROP GTPase in Arabidopsis suspension cells and seedlings (Lemichez et al.2001).Expression of constitutively active forms of Arabidopsis ROP2and ROP6reduces sensitivity to ABA during seed germination(Li et al.2001)and stomatal closing(Lemichez et al.2001;Hwang et al.2011).The obser-vation that an Arabidopsis mutant that lacks ROP10expres-sion is hypersensitive to ABA,and that ROP10expression is suppressed by ABA,suggests the existence of an interesting feedback regulation loop in the ABA signalling pathway (Zheng et al.2002).RICs(ROP-interactive CRIB motif-containing proteins) are a unique group of interacting partners of activated ROP GTPases.RIC proteins interact with multiple ROP GTPases via their conserved CRIB motif,and link ROP proteins to diverse target molecules that bind to their variable domains (Yang2002).The11RIC genes present in Arabidopsis are categorized into four phylogenetic groups(Wu et al.2001;Gu et al.2005).However,knowledge on RIC functions is limited; RIC3and RIC4have been shown to regulate[Ca2+]cyt and F-actin dynamics during the polar growth of pollen tubes (Wu et al.2001;Gu et al.2005).RIC7is reported to interact with active ROP2in stomatal guard cells and to suppress light-induced stomatal opening(Jeon et al.2008).In epider-mal cells of the leaf and hypocotyl,RIC1suppresses aniso-tropic cell expansion by regulating microtubule(MT) dynamics(Fu et al.2005,2009;Xu et al.2010).RIC1is expressed in a broad range of tissues(Wu et al. 2001).However,the function of RIC1has been analysed mostly in the development of leaf pavement cells(Fu et al. 2005).In this cell type,RIC1is associated with MTs and regulates their assembly.In the lobe-forming regions of pave-ment cells,RIC1is inactivated by active ROP2,which sup-presses MT assembly,but promotesfine F-actin assembly and thereby induces outgrowth of the region.In contrast,in the neck-forming regions of pavement cells,RIC1is activated by active ROP6and then promotes the assembly of MTs,which limits the expansion of the region and results in the forma-tion of a narrow neck.The cortical MTs in the leaf pavement cells of ric1mutants are randomly organized,resulting in pavement cells with wider necks.This ROP6-RIC1-MT sig-nalling pathway seems to function in both hypocotyl elonga-tion and leaf epidermal cell development(Fu et al.2005, 2009).In pollen tubes,however,RIC1is localized to the apical plasma membrane,where MTs are absent,and over-expression of RIC1suppresses the depolarized tube growth induced by ROP1overexpression(Wu et al.2001).Given its broad expression pattern,RIC1may mediate diverse pro-cesses in the growth and development of plants,which have yet to be elucidated.In this work,we established that RIC1positively regulates the auxin effect and negatively regulates the ABA effect during root growth and lateral root development.These results will advance our current limited understanding on the mode of action of RIC1protein during regulation of plant development by auxin and ABA.MATERIALS AND METHODSPlant materials and growth conditionsSeeds of wild-type,ric1,and ric1/RIC1p:GFP:RIC1Arabi-dopsis thaliana plants(ecotype Ws)were surface sterilized, placed at4°C in the dark for2d,and then sown in half-strength Murashige and Skoog(MS)agar medium.Arabi-dopsis seedlings were grown in a growth chamber with a16h light/8h dark cycle at22°C.Isolation of the RIC1knockout mutantsSeeds of T-DNA insertion mutant for RIC1(ric1; FLAG_075E05)were obtained from Institut National de la Recherche Agronomique(INRA)-Versailles Genomic Resource Center(http://www-ijpb.versailles.inra.fr/en/cra/ cra_accueil.htm).Reverse transcriptase(RT)-PCR analysis using gene-specific primers confirmed that this is a null mutant.Primer information used for RT-PCR is available in Supporting Information Table S1.Complementation of ric1with RIC1p:GFP:RIC1For the ric1complementation assay,the RIC1promoter region(~2kb)and the RIC1open reading frame were indi-vidually obtained by PCR amplification.These genomic DNA fragments and GFP coding sequence were sequentially cloned into a pCR®8/GW/TOPO®vector(Invitrogen,Carls-bad,CA,USA),and then transferred into a pMDC100 gateway vector(Curtis&Grossniklaus2003).The RIC1p:GFP:RIC1construct was transformed into ric1plants by the Agrobacterium-mediatedfloral dipping method (Clough&Bent1998).The phenotypes of the T3seedlings of homozygous ric1/RIC1p:GFP:RIC1lines were observed. RIC1p:GUS expression assayThe genomic DNA fragment containing the promoter region (~2kb)andfirst exon of RIC1was amplified by PCR and fused to the GUS-coding region of the pMDC164vector (RIC1p:GUS).The RIC1p:GUS construct was transformed into wild-type Arabidopsis plants using the Agrobacterium-mediatedfloral dipping method(Clough&Bent1998). RIC1p:GUS expression was observed in T3plants from six independently transformed lines.Briefly,the seedlings of RIC1p:GUS were incubated in GUS staining buffer[100m m Na2HPO4(pH7.2),3m m potassium ferricyanide,3m m potas-sium ferrocyanide,10m m ethylenediaminetetraacetic acid (EDTA),0.1%Triton X-100,and2m m5-bromo-4-chloro-3-indolyl-b-D-glucuronide(Duchefa,Haarlem,The Nether-lands)]at37°C for12h.Chlorophyll was extracted in70% ethanol solution.946Y.Choi et al.©2012Blackwell Publishing Ltd,Plant,Cell and Environment,36,945–955Observation of the cellular localizationof GFP:RIC1Wild-type Arabidopsis plants were stably transformed with a GFP:RIC1construct under the control of CaMV35S pro-moter.In multiple independently transformed lines of Arabidopsis,the subcellular localization of GFP:RIC1was observed by using a Zeiss LSM510Meta Laser scanning microscope(Zeiss,/).To investigate the effects of auxin and ABA on the cellular localization of RIC1,7-day-old seedlings that stably express GFP:RIC1 were incubated in half-strength MS medium containing1m m auxin[naphthalene-1-acetic acid(NAA)]or10m m ABA for1h.Quantification of RIC and ABA-orauxin-responsive gene transcript levelsQuantitative real-time RT-PCR(Q-PCR)was used to quan-tify transcript levels of RIC genes,ABA-responsive genes and auxin-responsive genes.Total RNA was extracted from each sample and then reverse transcribed into cDNA. Q-PCR was carried out using a Takara TP800thermal cycler and Takara SYBR RT-PCR Kit(Takara Bio,Kyoto,Japan), following the manufacturer’s instructions.Transcript levels of RIC s,ABA-responsive genes and auxin-responsive genes were normalized against that of tubulin8. Measurement of lateral root formation and primary root growthTo examine the effects of ABA or auxin on lateral root formation and primary root growth,Arabidopsis seedlings were grown for4d under a16h photoperiod and then trans-ferred to fresh half-strength MS agar plates supplemented with the indicated concentrations of ABA or auxin.After an additional5–7d,the net elongation of primary roots was measured and the number of lateral roots was counted using a stereo microscope(Olympus SZX12,Tokyo,Japan). Seed germination assayFor germination assays,the seeds were placed in the dark at 4°C for2d and then sown on MS medium agar plates con-taining1%sucrose in the presence or absence of0–1.5m m concentrations of ABA.The seeds were incubated under a 16h photoperiod at22°C.Germinated seeds(as determined by cotyledon greening or radicle emergence)were scored every12h for6d.Germination ratio refers to the number of germinated seeds as a proportion of the total number of seeds tested.RESULTSRIC1expression is induced by both auxinand ABAMembers of the ROP small GTPase family are reported to mediate ABA and auxin responses(Li et al.2001;Zheng et al.2002;Tao et al.2005).We hypothesized that RIC proteins might serve an important intermediary in the ROP-mediated ABA and auxin signalling pathways.If this hypothesis was true,then the level of the RIC proteins may be substantially regulated by ABA and auxin.Thus,we tested the effect of auxin and ABA on the expression of10out of the11Arabi-dopsis RIC genes(Fig.1).Arabidopsis seedlings were grown on half-strength MS medium for7d and then treated with 1m m NAA or10m m ABA for1h.Total RNA was isolated from these seedlings and RIC gene transcript levels were examined using quantitative real-time PCR(Q-PCR).Upon NAA and ABA treatment,the transcript level of many RIC s (RIC2,3,4,5,7,9and11)increased,but the increase in RIC1 was the highest.Therefore,we chose to focus our analysis on RIC1.Loss of RIC1expression alters gene induction by auxin and ABAAuxin and ABA induce the expression of sets of genes, which are known as auxin-responsive and ABA-responsive genes,respectively(Brady et al.2003;Zhang et al.2005;Li et al.2009).To examine the involvement of RIC1in auxin and ABA signal transduction,we evaluated the effect of RIC1knockout(ric1)on the expression levels of typical auxin-and ABA-responsive genes.ric1,a T-DNA insertion mutant(Stock No.FLAG_075E05),was obtained from INRA-Versailles Genomic Resource Center(http://www-ijpb.versailles.inra.fr/en/cra/cra_accueil.htm).RT-PCR analy-sis confirmed that the T-DNA insertion into the fourth exon completely blocked the expression of RIC1in ric1(Fig.2a). The small auxin-up RNAs(SAURs)encode short tran-scripts that accumulate rapidly upon auxin treatment(Li et al.2009).IAA6and IAA19are members of INDOLE-3-ACETIC ACID/AUXIN(IAA/AUX)genes andtheir Figure1.Expression of RIC genes were induced by auxin and abscisic acid(ABA).Seven-day-old Arabidopsis seedlings were treated without or with1m m auxin[naphthalene-1-acetic acid (NAA)]or10m m ABA for1h,and total RNA was isolated from seedlings for Q-PCR analysis.The transcript levels of RIC genes were normalized against the transcript level of Tubulin8,which served as the internal control,and are presented as values relative to the untreated control.Data are meansϮSEM of three to eight biological replicates.Asterisks indicate values that are statistically significantly different from the untreated control(***P<0.005;**P<0.001;*P<0.05).RIC1regulates root development947©2012Blackwell Publishing Ltd,Plant,Cell and Environment,36,945–955948Y.Choi et al.©2012Blackwell Publishing Ltd,Plant,Cell and Environment,36,945–955expressions are induced by auxin(Abel,Nguyen&Theologis 1995;Tatematsu et al.2004).Using Q-PCR analysis,we com-pared the transcript levels of SAUR and IAA genes in ric1 seedlings with those in wild-type seedlings(Fig.2b).Under control conditions without NAA treatment,the transcript levels of these genes in ric1seedlings were similar to or slightly higher than those in wild-type seedlings(Fig.2b).In 7-day-old wild-type seedlings,treatment with1m m NAA for 1h induced a two-to fourfold increase in SAUR gene expres-sion(Fig.2b).Interestingly,however,the induction of SAUR genes by1m m NAA was suppressed in ric1seedlings (Fig.2b);SAUR9transcript level increased3.3Ϯ0.1-fold in the wild type,but1.7Ϯ0.1-fold in ric1(t-test,P<0.005); SAUR15transcript level increased3.9Ϯ0.6-fold in the wild type,but1.8Ϯ0.2-fold in ric1(t-test,P<0.01);SAUR23 transcript level increased3.0Ϯ0.3-fold in the wild type,but 1.4Ϯ0.2-fold in ric1(t-test,P<0.005);SAUR62transcript level increased2.5Ϯ0.2-fold in the wild type but1.4Ϯ0.2-fold in ric1(t-test,P<0.001);and SAUR66transcript level increased3.9Ϯ0.4-fold in the wild type,but1.7Ϯ0.2-fold in ric1(t-test,P<0.001).Similarly,induction of IAA6and IAA19upon NAA treatment was suppressed by ric1(Fig.2b bottom panel),whereas the transcript level of IAA6 increased21.9Ϯ1.3-fold in the wild type,but only11.3Ϯ0.2-fold in ric1(P<0.05),and the transcript level of IAA19 increased27.1Ϯ3.3-fold in the wild type,but only13.1Ϯ1.9-fold in ric1(P<0.05).These results indicate that RIC1is involved in the control of the auxin signalling pathway.ABI3,ABI5,responsive to ABA18(RAB18),and respon-sive to dehydration29A(RD29A)and29B(RD29B)are well-characterized ABA-responsive genes that play critical roles in ABA signalling(Parcy et al.1994;Finkelstein& Lynch2000;Lopez-Molina&Chua2000;Hoth et al.2002; Kang et al.2010).To analyse the involvement of RIC1in ABA signalling,we gauged the effects of ABA on expres-sions of these genes in the roots of wild-type and ric1seed-lings(Fig.2c).Seven-day-old seedlings were incubated in half-strength liquid MS medium in the presence or absence of0.5m m ABA for1h.Under control conditions(i.e.in the absence of ABA),transcript levels of ABI3,ABI5,RD29A, RD29B and RAB18were slightly higher in ric1seedlings than in wild-type seedlings,and this difference was further increased after ABA treatment(Fig.2c).Upon ABA treat-ment,ric1seedlings exhibited much higher transcript levels of thosefive ABA-responsive genes,compared with wild-type seedlings(Fig.2c);ABI3transcript level increased 2.4Ϯ0.5-fold in the wild type,but 5.5Ϯ0.9-fold in ric1 (P<0.01);ABI5transcript level increased5.9Ϯ0.4-fold in the wild type,but12.9Ϯ1.9in ric1(P<0.005);RD29A tran-script level increased12.3Ϯ3.9-fold in the wild type,but 17.4Ϯ6.6-fold in ric1(P<0.06);RD29B transcript level increased5.5Ϯ1.2-fold in the wild type,but10.9Ϯ0.8-fold in ric1(P<0.05);and RAB18transcript level increased 4.6Ϯ1.1-fold in the wild type,but8.0Ϯ1.3-fold in ric1 (P<0.01).In summary,RIC1knockout suppressed the induction of auxin-responsive genes by auxin,but promoted the induction of ABA-responsive genes by ABA.These results suggest that RIC1exerts opposite regulatory functions in the auxin and ABA signalling pathways.RIC1is expressed in the roots ofyoung seedlingsTo identify which auxin-and ABA-mediated processes are regulated by RIC1,wefirst determined the tissue-specific and developmental stage-specific expression of RIC1.The genomic DNA region containing the RIC1promoter(~2kb) and thefirst exon was fused to the GUS-coding region (RIC1p:GUS),and introduced into wild-type plants. RIC1p:GUS expression was observed in T3seeds and seed-lings from six independently transformed Arabidopsis lines (Fig.3a,b).In germinating seeds and young seedlings,the RIC1p:GUS signal was evident in roots.In germinating seeds,RIC1p:GUS signal was limited to the embryonic root tip(Fig.3a,left),and in seedlings at1–3d after sowing,RIC1p:GUS extended the expression to other parts of root including differentiation zone,root hairs and root–shoot junction(Fig.3a,right).In the roots of2-week-old plants,RIC1p:GUS signal was detected in root tips and also in maturation zone,where lateral roots grow out(Fig.3b).RIC1p:GUS signal was strongly detected in columella cells from the root tip, (Fig.3b-d).In maturation zone of root,cells surrounding emerged lateral root(Fig.3b-b)and epidermal cells at the base of lateral roots(Fig.3b-c)showed clear RIC1p:GUS signals.These RIC1expression patterns indicate that RIC1is likely to be involved in the regulation of seed germination, early seedling development and root development.In addition to being expressed in the roots,RIC1p:GUS was also expressed in the hypocotyls,petioles,and weakly in the leaves of young seedlings(Fig.3a,b).In Arabidopsis plants of later development stages,expression of RIC1p:GUS was weak except inflowers,where RIC1expression was pre-viously reported(Wu et al.2001;Fu et al.2005,2009;Xu et al.Figure2.ric1knockout mutation altered induction of auxin-and abscisic acid(ABA)-responsive genes.(a)Schematic structure of theRIC1gene(left).The triangle indicates the T-DNA insertion site in ric1.Exons are represented as boxes and introns as lines.RT-PCR analysis using a RIC1-specific primer set(RT-F and RT-R)shows that ric1is a true null mutant(right).Tubulin8was used as an internal control.(b)Expression of SAUR9,SAUR15,SAUR23,SAUR62,SAUR66,IAA6and IAA19in plants treated or not with1m m auxin [naphthalene-1-acetic acid(NAA)].(c)Expression of ABI3,ABI5,RD29A,RD29B and RAB18in plants treated or not with0.5m m ABA.Q-PCR analyses of transcripts of auxin-and ABA-responsive genes were performed using total RNA isolated from the roots of8-day-old seedlings after1h of treatment without or with auxin or ABA.Data were normalized using Tubulin8as an internal control,and are presented as values relative to the untreated wild type(WT).Data are meansϮSEM of four independent experiments.Asterisks indicate values that are significantly different from those of the WT(***P<0.005;**P<0.01;*P<0.05;#P<0.06).RIC1regulates root development949©2012Blackwell Publishing Ltd,Plant,Cell and Environment,36,945–9552010);RIC1p:GUS signal was strongly observed in the anthers and mature pollen grains (Supporting Information Fig.S1).RIC1knockout suppresses the effect of auxin on lateral root formation and primary root elongationAs RIC1is expressed in root (Fig.3)and RIC1expression is up-regulated by auxin (Fig.1),we examined whether auxin-dependent root growth and lateral root formation were affected in the ric1mutant (Fig.4).Arabidopsis seedlings were grown on half-strength MS medium for 4d and then transferred to fresh half-strength MS medium supplemented with various concentrations (0–100n m )of NAA.After 5d,the number of lateral roots (including newly emerged ones)was counted.Auxin promoted the formation of lateral roots in different genotypes,including the wild type,ric1,and ric1/RIC1p:GFP:RIC1(complementation lines,C1and C2;Fig.4a);however,this effect was significantly less in ric1than in the wild type and complementation lines (Fig.4b).InFigure 3.RIC1expression in Arabidopsis plants.(a)One dayafter sowing (DAS),an embryo exhibited RIC1p::GUS signal at the root tip (left,indicated by arrow).Seed coat was removed after GUS staining for observation.A young seedling that had justgerminated but had not yet undergone cotyledon expansion (right;1–3DAS)exhibited relatively stronger RIC1p::GUS signal in the root tip and differentiation zone of the root including the root hairs.Bar =300m m.(b)A 2-week-old seedling displayed RIC1p::GUS signal in the root tip and maturation zone withemerged lateral roots,and,weakly,in the shoot.(b-a )Bar =1cm.(b-b ),(b-c )and (b-d )are enlarged images of maturation zone with an emerged lateral root,a lateral root with GUS staining at the base,and a root tip with GUS staining in columellacells.Figure 4.Auxin responses were reduced in ric1plants.Arabidopsis seedlings were grown vertically on half-strength Murashige and Skoog (MS)medium for 4d,transferred to fresh half-strength MS medium supplemented or not with 0–100n m auxin [naphthalene-1-acetic acid (NAA)],and grown for anadditional 5–7d.(a)Levels of RIC1transcript in wild-type (WT),ric1,and ric1/RIC1p:GFP:RIC1(lines C1and C2)plants.RIC1expression in seedlings was quantified using Q-PCR and presented values relative to that of WT.Data are means ϮSEM of four independent experiments.(b)Number of lateral roots formed in the absence or presence of NAA (means ϮSEM of 28seedlings from four independent experiments),measured 5d after transfer to medium supplemented with or without NAA.Asterisks indicate values that are significantly different from those of the WT atP <0.05.(c)Relative values of lateral root number (mean ϮSEM,n =28).Values in (b)were normalized to the values of non-treated controls.Asterisks indicate values that are significantly different from those of the WT (***P <0.005).(d)Primary root elongation in the absence or presence of NAA (means ϮSEM of 28seedlings from four independent experiments).The net primary root growth was measured 7d after transfer to medium supplemented with or without NAA.Asterisks indicate values that are significantly different from those of the WT (**P <0.05;*P <0.1).(e)Relative values of net primary root elongation (mean ϮSEM,n =28).Values in (d)were normalized to the values ofnon-treated controls.Asterisks indicate values that are significantly different from those of the WT (***P <0.005;*P <0.05).950Y.Choi et al .©2012Blackwell Publishing Ltd,Plant,Cell and Environment,36,945–955the absence of exogenous auxin(0n m NAA),ric1plants produced more lateral roots than did the wild type and ric1 complementation lines(n=28,N=4,P<0.05;Fig.4b). However,in the presence of auxin,lateral root number was less in ric1plants than in the wild type(Fig.4b,P<0.05). Whereas80and100n m NAA increased the number of lateral roots per unit length(cm)of primary root in wild-type seedlings to734and920%of non-treated control values, respectively,the same concentration of NAA increased this number in ric1to466and613%of control values,respec-tively(Fig.4c).This alteration in lateral root formation in ric1 plants was completely reversed by the expression of RIC1 driven by its native promoter(ric1/RIC1p:GFP:RIC1).In two independent ric1/RIC1p:GFP:RIC1lines(C1and C2), lateral root formation was recovered to wild-type levels both in the absence and presence of NAA(Fig.4b,c).The effect of RIC1knockout on primary root elongation was also examined(Fig.4d,e).Seven days after transfer to half-strength MS medium supplemented or not with NAA, the net elongation of primary roots was measured.In medium lacking NAA,ric1mutants had reduced primary root elongation compared with wild-type plants(n=28, N=4,P<0.05);the net primary root elongation of wild-type seedlings was4.9Ϯ0.16cm,while that of ric1seedlings was 4.3Ϯ0.22cm(Fig.4d).NAA(50–100n m)inhibited primary root elongation in both ric1and wild-type seedlings (Fig.4d,e).However,ric1seedlings were less sensitive than the wild type to NAA(n=28,N=4,P<0.1);whereas100n m NAA reduced primary root elongation in wild-type seedlings by34.4%(to3.2Ϯ0.16cm),it inhibited that in ric1seedlings by only19.4%(to3.5Ϯ0.13cm).Primary root elongation in the complementation lines(C1and C2)was similar to that in the wild type,in both the absence and presence of NAA (Fig.4d,e).These results suggest that RIC1participates in auxin-regulated lateral root development and primary root elongation.RIC1knockout enhances the effect of ABA on seed germination,lateral root formation and primary root elongationWe then tested whether RIC1knockout also altered the plant’s response to ABA by comparing seed germination and root development in ric1and wild-type plants treated with ABA(Figs5&6).Seeds were sown on half-strength MS medium after2d of stratification.In the presence of0.5m m ABA,seed germination,as gauged by cotyledon greening, was delayed to a greater extent in ric1than in wild-type seeds (Fig.5a,b);whereas only25%of ric1seedlings exhibited cotyledon greening84h after sowing,66%of wild-type seed-lings exhibited greening(Fig.5b).Similar enhanced sensitiv-ity to ABA in inhibition of seed germination was observed when germination rate was analysed based on radicle emer-gence(Supporting Information Fig.S2).Seed germination rates in the ric1/RIC1p:GFP:RIC1lines were restored to wild-type levels in the presence of0.5m m ABA,confirming that loss of RIC1expression was responsible for the enhanced suppression of seed germination by ABA(Fig.5b).The delayed germination of ric1seeds in the presence of ABA was not due to a defect in seed development,because the germination rate of ric1seeds in the absence of ABA was not significantly different from that of wild type(Fig.5c and Supporting Information Fig.S2b).ABA was reported to inhibit root elongation and lateral root development(Pilet&Chanson1981).We compared primary root elongation and lateral root number in ric1and wild-type plants in the presence and absence ofexogenous Figure5.Inhibition of seed germination by abscisic acid(ABA) was enhanced in the ric1mutant.(a)Representative photographs showing young seedlings of wild type(WT),ric1,and the tworic1/RIC1p:GFP:RIC1lines(C1and C2)in the presence of0.5m m ABA(taken96h after sowing).(b)Seed germination rate in the presence of0.5m m ABA,measured as a percentage of seedlings with green cotyledons at the indicated time points after sowing on half-strength Murashige and Skoog(MS)medium supplemented with ABA.Data are meansϮSEM of three independent experiments.(c)Seed germination rate in the absence of ABA. There was no significant difference between genotypes.RIC1regulates root development951©2012Blackwell Publishing Ltd,Plant,Cell and Environment,36,945–955。

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Universities in Evolutionary Systems of InnovationMarianne van der Steen and Jurgen EndersThis paper criticizes the current narrow view on the role of universities in knowledge-based economies.We propose to extend the current policy framework of universities in national innovation systems(NIS)to a more dynamic one,based on evolutionary economic principles. The main reason is that this dynamic viewfits better with the practice of innovation processes. We contribute on ontological and methodological levels to the literature and policy discussions on the effectiveness of university-industry knowledge transfer and the third mission of uni-versities.We conclude with a discussion of the policy implications for the main stakeholders.1.IntroductionU niversities have always played a major role in the economic and cultural devel-opment of countries.However,their role and expected contribution has changed sub-stantially over the years.Whereas,since1945, universities in Europe were expected to con-tribute to‘basic’research,which could be freely used by society,in recent decades they are expected to contribute more substantially and directly to the competitiveness offirms and societies(Jaffe,2008).Examples are the Bayh–Dole Act(1982)in the United States and in Europe the Lisbon Agenda(2000–2010) which marked an era of a changing and more substantial role for universities.However,it seems that this‘new’role of universities is a sort of universal given one(ex post),instead of an ex ante changing one in a dynamic institutional environment.Many uni-versities are expected nowadays to stimulate a limited number of knowledge transfer activi-ties such as university spin-offs and university patenting and licensing to demonstrate that they are actively engaged in knowledge trans-fer.It is questioned in the literature if this one-size-fits-all approach improves the usefulness and the applicability of university knowledge in industry and society as a whole(e.g.,Litan et al.,2007).Moreover,the various national or regional economic systems have idiosyncratic charac-teristics that in principle pose different(chang-ing)demands towards universities.Instead of assuming that there is only one‘optimal’gov-ernance mode for universities,there may bemultiple ways of organizing the role of univer-sities in innovation processes.In addition,we assume that this can change over time.Recently,more attention in the literature hasfocused on diversity across technologies(e.g.,King,2004;Malerba,2005;Dosi et al.,2006;V an der Steen et al.,2008)and diversity offormal and informal knowledge interactionsbetween universities and industry(e.g.,Cohenet al.,1998).So far,there has been less atten-tion paid to the dynamics of the changing roleof universities in economic systems:how dothe roles of universities vary over time andwhy?Therefore,this article focuses on the onto-logical premises of the functioning of univer-sities in innovation systems from a dynamic,evolutionary perspective.In order to do so,we analyse the role of universities from theperspective of an evolutionary system ofinnovation to understand the embeddednessof universities in a dynamic(national)systemof science and innovation.The article is structured as follows.InSection2we describe the changing role ofuniversities from the static perspective of anational innovation system(NIS),whereasSection3analyses the dynamic perspective ofuniversities based on evolutionary principles.Based on this evolutionary perspective,Section4introduces the characteristics of a LearningUniversity in a dynamic innovation system,summarizing an alternative perception to thestatic view of universities in dynamic economicsystems in Section5.Finally,the concludingVolume17Number42008doi:10.1111/j.1467-8691.2008.00496.x©2008The AuthorsJournal compilation©2008Blackwell Publishingsection discusses policy recommendations for more effective policy instruments from our dynamic perspective.2.Static View of Universities in NIS 2.1The Emergence of the Role of Universities in NISFirst we start with a discussion of the literature and policy reports on national innovation system(NIS).The literature on national inno-vation systems(NIS)is a relatively new and rapidly growingfield of research and widely used by policy-makers worldwide(Fagerberg, 2003;Balzat&Hanusch,2004;Sharif,2006). The NIS approach was initiated in the late 1980s by Freeman(1987),Dosi et al.(1988)and Lundvall(1992)and followed by Nelson (1993),Edquist(1997),and many others.Balzat and Hanusch(2004,p.196)describe a NIS as‘a historically grown subsystem of the national economy in which various organizations and institutions interact with and influence one another in the carrying out of innovative activity’.It is about a systemic approach to innovation,in which the interaction between technology,institutions and organizations is central.With the introduction of the notion of a national innovation system,universities were formally on the agenda of many innovation policymakers worldwide.Clearly,the NIS demonstrated that universities and their interactions with industry matter for innova-tion processes in economic systems.Indeed, since a decade most governments acknowl-edge that interactions between university and industry add to better utilization of scienti-fic knowledge and herewith increase the innovation performance of nations.One of the central notions of the innovation system approach is that universities play an impor-tant role in the development of commercial useful knowledge(Edquist,1997;Sharif, 2006).This contrasts with the linear model innovation that dominated the thinking of science and industry policy makers during the last century.The linear innovation model perceives innovation as an industry activity that‘only’utilizes fundamental scientific knowledge of universities as an input factor for their innovative activities.The emergence of the non-linear approach led to a renewed vision on the role–and expectations–of universities in society. Some authors have referred to a new social contract between science and society(e.g., Neave,2000).The Triple Helix(e.g.,Etzkowitz &Leydesdorff,1997)and the innovation system approach(e.g.,Lundvall,1988)and more recently,the model of Open Innovation (Chesbrough,2003)demonstrated that innova-tion in a knowledge-based economy is an inter-active process involving many different innovation actors that interact in a system of overlapping organizationalfields(science, technology,government)with many interfaces.2.2Static Policy View of Universities in NIS Since the late1990s,the new role of universi-ties in NIS thinking emerged in a growing number of policy studies(e.g.,OECD,1999, 2002;European Commission,2000).The con-tributions of the NIS literature had a large impact on policy makers’perception of the role of universities in the national innovation performance(e.g.,European Commission, 2006).The NIS approach gradually replaced linear thinking about innovation by a more holistic system perspective on innovations, focusing on the interdependencies among the various agents,organizations and institutions. NIS thinking led to a structurally different view of how governments can stimulate the innovation performance of a country.The OECD report of the national innovation system (OECD,1999)clearly incorporated these new economic principles of innovation system theory.This report emphasized this new role and interfaces of universities in knowledge-based economies.This created a new policy rationale and new awareness for technology transfer policy in many countries.The NIS report(1999)was followed by more attention for the diversity of technology transfer mecha-nisms employed in university-industry rela-tions(OECD,2002)and the(need for new) emerging governance structures for the‘third mission’of universities in society,i.e.,patent-ing,licensing and spin-offs,of public research organizations(OECD,2003).The various policy studies have in common that they try to describe and compare the most important institutions,organizations, activities and interactions of public and private actors that take part in or influence the innovation performance of a country.Figure1 provides an illustration.Thefigure demon-strates the major building blocks of a NIS in a practical policy setting.It includesfirms,uni-versities and other public research organiza-tions(PROs)involved in(higher)education and training,science and technology.These organizations embody the science and tech-nology capabilities and knowledge fund of a country.The interaction is represented by the arrows which refer to interactive learn-ing and diffusion of knowledge(Lundvall,Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing1992).1The building block ‘Demand’refers to the level and quality of demand that can be a pull factor for firms to innovate.Finally,insti-tutions are represented in the building blocks ‘Framework conditions’and ‘Infrastructure’,including various laws,policies and regula-tions related to science,technology and entre-preneurship.It includes a very broad array of policy issues from intellectual property rights laws to fiscal instruments that stimulate labour mobility between universities and firms.The figure demonstrates that,in order to improve the innovation performance of a country,the NIS as a whole should be conducive for innovative activities in acountry.Since the late 1990s,the conceptual framework as represented in Figure 1serves as a dominant design for many comparative studies of national innovation systems (Polt et al.,2001;OECD,2002).The typical policy benchmark exercise is to compare a number of innovation indicators related to the role of university-industry interactions.Effective performance of universities in the NIS is judged on a number of standardized indica-tors such as the number of spin-offs,patents and licensing.Policy has especially focused on ‘getting the incentives right’to create a generic,good innovative enhancing context for firms.Moreover,policy has also influ-enced the use of specific ‘formal’transfer mechanisms,such as university patents and university spin-offs,to facilitate this collabo-ration.In this way best practice policies are identified and policy recommendations are derived:the so-called one-size-fits-all-approach.The focus is on determining the ingredients of an efficient benchmark NIS,downplaying institutional diversity and1These organizations that interact with each other sometimes co-operate and sometimes compete with each other.For instance,firms sometimes co-operate in certain pre-competitive research projects but can be competitors as well.This is often the case as well withuniversities.Figure 1.The Benchmark NIS Model Source :Bemer et al.(2001).Volume 17Number 42008©2008The AuthorsJournal compilation ©2008Blackwell Publishingvariety in the roles of universities in enhanc-ing innovation performance.The theoretical contributions to the NIS lit-erature have outlined the importance of insti-tutions and institutional change.However,a further theoretical development of the ele-ments of NIS is necessary in order to be useful for policy makers;they need better systemic NIS benchmarks,taking systematically into account the variety of‘national idiosyncrasies’. Edquist(1997)argues that most NIS contribu-tions are more focused onfirms and technol-ogy,sometimes reducing the analysis of the (national)institutions to a left-over category (Geels,2005).Following Hodgson(2000), Nelson(2002),Malerba(2005)and Groenewe-gen and V an der Steen(2006),more attention should be paid to the institutional idiosyncra-sies of the various systems and their evolution over time.This creates variety and evolving demands towards universities over time where the functioning of universities and their interactions with the other part of the NIS do evolve as well.We suggest to conceptualize the dynamics of innovation systems from an evolutionary perspective in order to develop a more subtle and dynamic vision on the role of universities in innovation systems.We emphasize our focus on‘evolutionary systems’instead of national innovation systems because for many universities,in particular some science-based disciplinaryfields such as biotechnology and nanotechnology,the national institutional environment is less relevant than the institu-tional and technical characteristics of the technological regimes,which is in fact a‘sub-system’of the national innovation system.3.Evolutionary Systems of Innovation as an Alternative Concept3.1Evolutionary Theory on Economic Change and InnovationCharles Darwin’s The Origin of Species(1859)is the foundation of modern thinking about change and evolution(Luria et al.,1981,pp. 584–7;Gould,1987).Darwin’s theory of natural selection has had the most important consequences for our perception of change. His view of evolution refers to a continuous and gradual adaptation of species to changes in the environment.The idea of‘survival of thefittest’means that the most adaptive organisms in a population will survive.This occurs through a process of‘natural selection’in which the most adaptive‘species’(organ-isms)will survive.This is a gradual process taking place in a relatively stable environment, working slowly over long periods of time necessary for the distinctive characteristics of species to show their superiority in the‘sur-vival contest’.Based on Darwin,evolutionary biology identifies three levels of aggregation.These three levels are the unit of variation,unit of selection and unit of evolution.The unit of varia-tion concerns the entity which contains the genetic information and which mutates fol-lowing specific rules,namely the genes.Genes contain the hereditary information which is preserved in the DNA.This does not alter sig-nificantly throughout the reproductive life-time of an organism.Genes are passed on from an organism to its successors.The gene pool,i.e.,the total stock of genetic structures of a species,only changes in the reproduction process as individuals die and are born.Par-ticular genes contribute to distinctive charac-teristics and behaviour of species which are more or less conducive to survival.The gene pool constitutes the mechanism to transmit the characteristics of surviving organisms from one generation to the next.The unit of selection is the expression of those genes in the entities which live and die as individual specimens,namely(individual) organisms.These organisms,in their turn,are subjected to a process of natural selection in the environment.‘Fit’organisms endowed with a relatively‘successful’gene pool,are more likely to pass them on to their progeny.As genes contain information to form and program the organisms,it can be expected that in a stable environment genes aiding survival will tend to become more prominent in succeeding genera-tions.‘Natural selection’,thus,is a gradual process selecting the‘fittest’organisms. Finally,there is the unit of evolution,or that which changes over time as the gene pool changes,namely populations.Natural selec-tion produces changes at the level of the population by‘trimming’the set of genetic structures in a population.We would like to point out two central principles of Darwinian evolution.First,its profound indeterminacy since the process of development,for instance the development of DNA,is dominated by time at which highly improbable events happen (Boulding,1991,p.12).Secondly,the process of natural selection eliminates poorly adapted variants in a compulsory manner,since indi-viduals who are‘unfit’are supposed to have no way of escaping the consequences of selection.22We acknowledge that within evolutionary think-ing,the theory of Jean Baptiste Lamarck,which acknowledges in essence that acquired characteris-tics can be transmitted(instead of hereditaryVolume17Number42008©2008The AuthorsJournal compilation©2008Blackwell PublishingThese three levels of aggregation express the differences between ‘what is changing’(genes),‘what is being selected’(organisms),and ‘what changes over time’(populations)in an evolutionary process (Luria et al.,1981,p.625).According to Nelson (see for instance Nelson,1995):‘Technical change is clearly an evolutionary process;the innovation generator keeps on producing entities superior to those earlier in existence,and adjustment forces work slowly’.Technological change and innovation processes are thus ‘evolutionary’because of its characteristics of non-optimality and of an open-ended and path-dependent process.Nelson and Winter (1982)introduced the idea of technical change as an evolutionary process in capitalist economies.Routines in firms function as the relatively durable ‘genes’.Economic competition leads to the selection of certain ‘successful’routines and these can be transferred to other firms by imitation,through buy-outs,training,labour mobility,and so on.Innovation processes involving interactions between universities and industry are central in the NIS approach.Therefore,it seems logical that evolutionary theory would be useful to grasp the role of universities in innovation pro-cesses within the NIS framework.3.2Evolutionary Underpinnings of Innovation SystemsBased on the central evolutionary notions as discussed above,we discuss in this section how the existing NIS approaches have already incor-porated notions in their NIS frameworks.Moreover,we investigate to what extent these notions can be better incorporated in an evolu-tionary innovation system to improve our understanding of universities in dynamic inno-vation processes.We focus on non-optimality,novelty,the anti-reductionist methodology,gradualism and the evolutionary metaphor.Non-optimality (and Bounded Rationality)Based on institutional diversity,the notion of optimality is absent in most NIS approaches.We cannot define an optimal system of innovation because evolutionary learning pro-cesses are important in such systems and thus are subject to continuous change.The system never achieves an equilibrium since the evolu-tionary processes are open-ended and path dependent.In Nelson’s work (e.g.,1993,1995)he has emphasized the presence of contingent out-comes of innovation processes and thus of NIS:‘At any time,there are feasible entities not present in the prevailing system that have a chance of being introduced’.This continuing existence of feasible alternative developments means that the system never reaches a state of equilibrium or finality.The process always remains dynamic and never reaches an optimum.Nelson argues further that diversity exists because technical change is an open-ended multi-path process where no best solu-tion to a technical problem can be identified ex post .As a consequence technical change can be seen as a very wasteful process in capitalist economies with many duplications and dead-ends.Institutional variety is closely linked to non-optimality.In other words,we cannot define the optimal innovation system because the evolutionary learning processes that take place in a particular system make it subject to continuous change.Therefore,comparisons between an existing system and an ideal system are not possible.Hence,in the absence of any notion of optimality,a method of comparing existing systems is necessary.According to Edquist (1997),comparisons between systems were more explicit and systematic than they had been using the NIS approaches.Novelty:Innovations CentralNovelty is already a central notion in the current NIS approaches.Learning is inter-preted in a broad way.Technological innova-tions are defined as combining existing knowledge in new ways or producing new knowledge (generation),and transforming this into economically significant products and processes (absorption).Learning is the most important process behind technological inno-vations.Learning can be formal in the form of education and searching through research and development.However,in many cases,innovations are the consequence of several kinds of learning processes involving many different kinds of economic agents.According to Lundvall (1992,p.9):‘those activities involve learning-by-doing,increasing the efficiency of production operations,learning-characteristics as in the theory of Darwin),is acknowledged to fit better with socio-economic processes of technical change and innovation (e.g.,Nelson &Winter,1982;Hodgson,2000).Therefore,our theory is based on Lamarckian evolutionary theory.However,for the purpose of this article,we will not discuss the differences between these theo-ries at greater length and limit our analysis to the fundamental evolutionary building blocks that are present in both theories.Volume 17Number 42008©2008The AuthorsJournal compilation ©2008Blackwell Publishingby-using,increasing the efficiency of the use of complex systems,and learning-by-interacting, involving users and producers in an interac-tion resulting in product innovations’.In this sense,learning is part of daily routines and activities in an economy.In his Learning Economy concept,Lundvall makes learning more explicit,emphasizing further that ‘knowledge is assumed as the most funda-mental resource and learning the most impor-tant process’(1992,p.10).Anti-reductionist Approach:Systems and Subsystems of InnovationSo far,NIS approaches are not yet clear and systematic in their analysis of the dynamics and change in innovation systems.Lundvall’s (1992)distinction between subsystem and system level based on the work of Boulding implicitly incorporates both the actor(who can undertake innovative activities)as well as the structure(institutional selection environment) in innovation processes of a nation.Moreover, most NIS approaches acknowledge that within the national system,there are different institu-tional subsystems(e.g.,sectors,regions)that all influence each other again in processes of change.However,an explicit analysis of the structured environment is still missing (Edquist,1997).In accordance with the basic principles of evolutionary theory as discussed in Section 3.1,institutional evolutionary theory has developed a very explicit systemic methodol-ogy to investigate the continuous interaction of actors and institutional structures in the evolution of economic systems.The so-called ‘methodological interactionism’can be per-ceived as a methodology that combines a structural perspective and an actor approach to understand processes of economic evolu-tion.Whereas the structural perspective emphasizes the existence of independent institutional layers and processes which deter-mine individual actions,the actor approach emphasizes the free will of individuals.The latter has been referred to as methodological individualism,as we have seen in neo-classical approaches.Methodological indi-vidualism will explain phenomena in terms of the rational individual(showingfixed prefer-ences and having one rational response to any fully specified decision problem(Hodgson, 2000)).The interactionist approach recognizes a level of analysis above the individual orfirm level.NIS approaches recognize that national differences exist in terms of national institu-tions,socio-economic factors,industries and networks,and so on.So,an explicit methodological interactionist approach,explicitly recognizing various insti-tutional layers in the system and subsystem in interaction with the learning agents,can improve our understanding of the evolution of innovation.Gradualism:Learning Processes andPath-DependencyPath-dependency in biology can be translated in an economic context in the form of(some-times very large)time lags between a technical invention,its transformation into an economic innovation,and the widespread diffusion. Clearly,in many of the empirical case studies of NIS,the historical dimension has been stressed.For instance,in the study of Denmark and Sweden,it has been shown that the natural resource base(for Denmark fertile land,and for Sweden minerals)and economic history,from the period of the Industrial Revolution onwards,has strongly influenced present specialization patterns(Edquist& Lundvall,1993,pp.269–82).Hence,history matters in processes of inno-vation as the innovation processes are influ-enced by many institutions and economic agents.In addition,they are often path-dependent as small events are reinforced and become crucially important through processes of positive feedback,in line with evolutionary processes as discussed in Section3.1.Evolutionary MetaphorFinally,most NIS approaches do not explicitly use the biological metaphor.Nevertheless, many of the approaches are based on innova-tion theories in which they do use an explicit evolutionary metaphor(e.g.,the work of Nelson).To summarize,the current(policy)NIS approaches have already implicitly incorpo-rated some evolutionary notions such as non-optimality,novelty and gradualism.However, what is missing is a more explicit analysis of the different institutional levels of the economic system and innovation subsystems (their inertia and evolution)and how they change over time in interaction with the various learning activities of economic agents. These economic agents reside at established firms,start-upfirms,universities,govern-ments,undertaking learning and innovation activities or strategic actions.The explicit use of the biological metaphor and an explicit use of the methodological interactionst approach may increase our understanding of the evolu-tion of innovation systems.Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing4.Towards a Dynamic View of Universities4.1The Logic of an Endogenous‘Learning’UniversityIf we translate the methodological interaction-ist approach to the changing role of universities in an evolutionary innovation system,it follows that universities not only respond to changes of the institutional environment(government policies,business demands or changes in scientific paradigms)but universities also influence the institutions of the selection envi-ronment by their strategic,scientific and entre-preneurial actions.Moreover,these actions influence–and are influenced by–the actions of other economic agents as well.So,instead of a one-way rational response by universities to changes(as in reductionist approach),they are intertwined in those processes of change.So, universities actually function as an endogenous source of change in the evolution of the inno-vation system.This is(on an ontological level) a fundamental different view on the role of universities in innovation systems from the existing policy NIS frameworks.In earlier empirical research,we observed that universities already effectively function endogenously in evolutionary innovation system frameworks;universities as actors (already)develop new knowledge,innovate and have their own internal capacity to change,adapt and influence the institutional development of the economic system(e.g., V an der Steen et al.,2009).Moreover,univer-sities consist of a network of various actors, i.e.,the scientists,administrators at technology transfer offices(TTO)as well as the university boards,interacting in various ways with indus-try and governments and embedded in various ways in the regional,national or inter-national environment.So,universities behave in an at least partly endogenous manner because they depend in complex and often unpredictable ways on the decision making of a substantial number of non-collusive agents.Agents at universities react in continuous interaction with the learn-ing activities offirms and governments and other universities.Furthermore,the endogenous processes of technical and institutional learning of univer-sities are entangled in the co-evolution of institutional and technical change of the evo-lutionary innovation system at large.We propose to treat the learning of universities as an inseparable endogenous variable in the inno-vation processes of the economic system.In order to structure the endogenization in the system of innovation analysis,the concept of the Learning University is introduced.In thenext subsection we discuss the main character-istics of the Learning University and Section5discusses the learning university in a dynamic,evolutionary innovation system.An evolution-ary metaphor may be helpful to make theuniversity factor more transparent in theco-evolution of technical and institutionalchange,as we try to understand how variouseconomic agents interact in learning processes.4.2Characteristics of the LearningUniversityThe evolution of the involvement of universi-ties in innovation processes is a learningprocess,because(we assume that)universitypublic agents have their‘own agenda’.V ariousincentives in the environment of universitiessuch as government regulations and technol-ogy transfer policies as well as the innovativebehaviour of economic agents,compel policymakers at universities to constantly respondby adapting and improving their strategiesand policies,whereas the university scientistsare partly steered by these strategies and partlyinfluenced by their own scientific peers andpartly by their historically grown interactionswith industry.During this process,universityboards try to be forward-looking and tobehave strategically in the knowledge thattheir actions‘influence the world’(alsoreferred to earlier as‘intentional variety’;see,for instance,Dosi et al.,1988).‘Intentional variety’presupposes that tech-nical and institutional development of univer-sities is a learning process.University agentsundertake purposeful action for change,theylearn from experience and anticipate futurestates of the selective environment.Further-more,university agents take initiatives to im-prove and develop learning paths.An exampleof these learning agents is provided in Box1.We consider technological and institutionaldevelopment of universities as a process thatinvolves many knowledge-seeking activitieswhere public and private agents’perceptionsand actions are translated into practice.3Theinstitutional changes are the result of inter-actions among economic agents defined byLundvall(1992)as interactive learning.Theseinteractions result in an evolutionary pattern3Using a theory developed in one scientific disci-pline as a metaphor in a different discipline mayresult,in a worst-case scenario,in misleading analo-gies.In the best case,however,it can be a source ofcreativity.As Hodgson(2000)pointed out,the evo-lutionary metaphor is useful for understandingprocesses of technical and institutional change,thatcan help to identify new events,characteristics andphenomena.Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing。

TECHNICAL BULLETIN 407-20-13316 October 2023MODEL AFFECTED: 407SUBJECT: ENGINE TORQUE, ENGINE OIL PRESSURE, ANDTRANSMISSION OIL PRESSURE INDICATIONSYSTEMS, MODIFICATION OFHELICOPTERS AFFECTED: Part I: Serial numbers 53000 through 53900, 53911through 54166, 54300 through 54752, 54805through 54929.Part II: Serial numbers 54304, 54567, 54805through 54929.[Serial numbers 54930 and subsequent will have theintent of this bulletin accomplished prior to delivery.] COMPLIANCE: At customer’s option.DESCRIPTION:This technical bulletin provides instructions to modify the engine torque transducer (1B7), the engine oil pressure transducer (1G5) and the transmission oil pressure transducer (1G6) wire harness installations to reduce the possibility of water ingress in the transducer connectors.PART I of this technical bulletin provides instructions to replace the connectors MS3116F8-4S with new connectors 160-027-508, and add heat shrink sleeves on each transducer wire harness to fill the gap between the wires and the connector inserts. PART II of this technical bulletin provides instructions to re-orient clamps to improve water drip loops.Applicability of this bulletin to any spare part shall be determined prior to its installation on an affected helicopter.APPROVAL:The engineering design aspects of this bulletin are Transport Canada Civil Aviation (TCCA) approved.CONTACT INFO:For any questions regarding this bulletin, please contact:Bell Product Support EngineeringTel:1-450-437-2862/1-800-363-8023/*****************************MANPOWER:Approximately 12 man-hours are required to complete this bulletin. This estimate is based on hands-on time and may vary with personnel and facilities available.WARRANTY:There is no warranty credit applicable for parts or labor associated with this bulletin.MATERIAL:Required Material:The following material is required for the accomplishment of this bulletin and may be obtained through your Bell Supply Center.Part Number Nomenclature Qty (Note)10-597817-351 Contact 12(1)2530-00246-00 Heat shrink sleeve 1 foot (0.31m)(2)160-027-508 Connector 3(2)NOTES:1. Not required for helicopters serial numbers 53000 through 54012.2. Part number is for quantities sold by the foot. Actual quantity required must bespecified in the order.3. Only required for helicopters serial numbers 53000 through 54012.Consumable Material:The following material is required to accomplish this bulletin, but may not require ordering, depending on the operator’s consumable material stock levels. This material may be obtained through your Bell Supply Center.Part Number Nomenclature Qty (Note) Reference * 2000-00731-00 Insulation tape. 1 Roll (1)(2) C-548PLT2S-C702Y Cable Tie AR C-292* C-XXX numbers refer to the consumables list in the BHT-ALL-SPM, Standard Practices Manual NOTES:1. Quantity indicated is the format that the product is delivered in. Actual quantityrequired to accomplish the instructions in this bulletin may be less than what has been delivered.2. Only required for PART II.SPECIAL TOOLS:11-6782 Insertion tool (or equivalent)11-6900 Extraction tool (or equivalent)45-1987 Wire stripper (or equivalent)HT-900 Raychem heat gun (or equivalent)TH254 Turret/PositionerM22520/1-01 Crimp toolWEIGHT AND BALANCE:Not affected.ELECTRICAL LOAD DATA:Not affected.REFERENCES:407-MM, Maintenance Manual, chapter 95407-MM, Maintenance Manual, chapter 96407-MM, Maintenance Manual, chapter 53BHT-ELEC-SPM, Electrical Standard Practices ManualBHT-ALL-SPM, Standard Practices ManualPUBLICATIONS AFFECTED:407-IPB, Illustrated Parts Breakdown, chapter 95407-MM, Maintenance Manual, chapter 98ACCOMPLISHMENT INSTRUCTIONS:PART I: Replacement of connector and addition of heat shrink sleeve1. Prepare the helicopter for maintenance.2. Make sure all electrical power is removed from helicopter.OBEY ALL THE SAFETY PRECAUTIONS WHEN YOU DOMAINTENANCE ON OR NEAR ELECTRICAL/ELECTRONICEQUIPMENT (407-MM, chapter 96).-NOTE-The engine oil pressure transducer (1G5) is not installed onthe 407GXi. Only the engine torque transducer (1B7) and thetransmission oil pressure transducer (1G6) are affected byPART I for the 407GXi.3. Gain access to the engine torque transducer (1B7), the engine oil pressuretransducer (1G5) and the transmission oil pressure transducer (1G6) connectors on the transmission deck by removing the air inlet cowling assembly (DMC-407-A-53-04-00-02A-520A-A).4. Disconnect the engine torque transducer (1B7), the engine oil pressure transducer(1G5) and the transmission oil pressure transducer (1G6) connectors 1B7P1, 1G5P1 and 1G6P1 (BHT-ELEC-SPM).-NOTE-Mark each wire with the connector pin number beforeextracting the contacts.5. Disassemble the connectors and extract all wires from the connectors 1B7P1,1G5P1 and 1G6P1 (BHT-ELEC-SPM).-NOTE-It could be required to cut and replace the contact for the heatshrink sleeve installation.6. Install and apply heat to the heat shrink sleeve (1, Figure 1), and install a new contact(2) on each wire as shown in Figure 1 (BHT-ELEC-SPM).-NOTE-For helicopter serial numbers 53000 through 54012, It isrequired to replace the connectors 1B7P1, 1G5P1 and1G6P1 with new connectors 160-027-508.7. Insert all wires into the connectors 1B7P1, 1G5P1 and 1G6P1, and assemble theconnectors as removed in step 5 (BHT-ELEC-SPM).8. Connect the connectors 1B7P1, 1G5P1 and 1G6P1 to the engine torque transducer(1B7), the engine oil pressure transducer (1G5) and the transmission oil pressure transducer (1G6) (BHT-ELEC-SPM).9. For helicopter serial number 53000 through 54299. Do a transmission oil pressurefunctional check (DMC-407-A-95-61-08-01A-340A-A).10. For helicopter serial number 54300 and subsequent. Do a transmission oil pressureoperational check (DMC-407-A-95-65-07-01A-320A-A).11. For helicopter serial number 53000 through 54299. Do an engine torque indicationsystem functional check (DMC-407-A-95-61-01-00A-340A-A).12. For helicopter serial number 54300 through-54303, 54305 through 54566 and 54568through 54800. Do an engine torque indication operational check (DMC-407-A-95-65-00-00A-320B-A).13. For helicopter serial number 54304, 54567, 54805 and subsequent. Do an enginetorque indication operational check (DMC-407-A-95-65-00-00A-320C-A).-NOTE-The engine oil pressure functional check is not required for407GXi.14. For helicopter serial number 53000 through 54299. Do an engine oil pressureindication system functional check (DMC-407-A-95-61-07-01A-340A-A).15. For helicopter serial number 54300 through-54303, 54305 through 54566 and 54568through 54800. Do an engine oil pressure operational check (DMC-407-A-95-65-06-01A-320A-A).16. Inspect the transmission deck area and install the air inlet cowling assembly (DMC-407-A-53-04-00-02A-720A-A).17. Make an entry in the helicopter logbook and historical service records indicatingcompliance with Part I of this Technical Bulletin.Part II: Re-orientation of clamps1. Prepare the helicopter for maintenance.2. Gain the access on transmission deck by removing the air inlet cowling assembly(DMC-407-A-53-04-00-02A-520A-A).3. Remove and retain the screw (1, Figure 2), the nut (2), the washers (3) and theclamps (4 and 5) for the transmission oil pressure transducer (1G6) wire harness.4. Re-orient and install the clamps (4 and 5) with the screw (1), the nut (2) and thewashers (3), as shown in Figure 2.5. Remove and retain the screw (6), the nut (7), the washers (8) and the clamps (9 and10) for the engine torque transducer (1B7) wire harness.6. Wrap the insulation tape (11) on the tube. Re-orient and install the clamps (9 and10) with the screw (6), the nut (7) and the washers (8), as shown in Figure 2.7. Inspect the transmission deck area and install the air inlet cowling assembly (DMC-407-A-53-04-00-02A-720A-A).8. Make an entry in the helicopter logbook and historical service records indicatingcompliance with Part II of this Technical Bulletin.Connector RefDes1B7P1 M22520/1-01 TH254 11-6782/ 11-6900 1G6P1 M22520/1-01 TH254 11-6782/ 11-6900 1G5P1 M22520/1-01 TH254 11-6782/ 11-6900Figure 1 – Heat shrink sleeve installation。

完美正方形与莫比乌斯环的关系英文版The relationship between a perfect square and a Möbius strip is a fascinating concept that explores the interconnectedness of geometry and topology. A perfect square is a shape with four equal sides and four right angles, while a Möbius strip is a surface with only one side and one edge. At first glance, these two shapes may seem unrelated, but upon closer inspection, their relationship becomes clear.To understand the connection between a perfect square and a Möbius strip, we must first examine their properties. A perfect square is a two-dimensional shape that lies flat on a plane, with all four sides meeting at right angles. It has four corners, or vertices, and four sides of equal length. In contrast, a Möbius strip is a three-dimensional shape that twists and turns in a way that creates the illusion of having only one side. It has a single edge that loops around the surface and connects back to itself.The key to understanding the relationship between these two shapes lies in their surfaces. A perfect square has a flat, continuous surface that can be easily visualized and measured. On the other hand, a Möbius strip has a twisted surface that is continuous but non-orientable, meaning it cannot be divided into two distinct sides. This unique property of the Möbius strip allows it to be transformed into a perfect square through a process known as cutting and reattaching.By cutting a Möbius strip along its center line and twisting one of the resulting halves, we can create a perfect square. The twist in the Möbius strip introduces an additional dimension to the shape, transforming it from a two-dimensional surface into a three-dimensional object. This transformation highlights the interconnectedness of geometry and topology, showing how seemingly unrelated shapes can be manipulated and transformed into one another.In conclusion, the relationship between a perfect square and a Möbius strip demonstrates the intricate connections between geometry and topology. By exploring theproperties and transformations of these shapes, we gain a deeper understanding of the fundamental principles that govern the world of mathematics.完美正方形与莫比乌斯环的关系完美正方形和莫比乌斯环之间的关系是一个引人入胜的概念，探讨了几何和拓扑之间的相互关系。

关于粒子群优化的英文摘要范文Particle Swarm Optimization (PSO) is a powerful and widely-used computational method inspired by the social behavior of birds and fish. Developed by Russell Eberhart and James Kennedy in 1995, it falls under the category of swarm intelligence algorithms, which leverage the collective behavior of decentralized systems to solve optimization problems. PSO is particularly effective for continuous optimization tasks, where it seeks to find optimal or near-optimal solutions from a defined search space.The core concept of PSO involves a group of individual entities, referred to as particles, which traverse the solution space by adjusting their positions based on their own experiences and those of their neighbors. Each particle maintains a record of its best-known position, as well as the best-known position of its group. This dual memory guides theparticles in their movement and allows them to iteratively converge towards the optimal solution. The movement of each particle is influenced by two primary components: cognitive and social. The cognitive component draws from the particle's own history, while the social component draws from thegroup's best-known position.A distinctive feature of PSO is its simplicity and ease of implementation, which makes it suitable for a broad range of applications, including function optimization, neural network training, and engineering design problems. The PSO algorithm can be adjusted with parameters such as the number of particles, their velocities, and the coefficients controlling the cognitive and social influences. These parameters can significantly affect the convergence speed and accuracy of the method.Moreover, PSO has been adapted and enhanced through various strategies, such as employing different topologiesfor particle interactions, incorporating constraints for specific problem domains, and hybridizing with other optimization techniques to improve performance. These modifications allow PSO to effectively tackle more complexand multi-dimensional problems.Despite its advantages, PSO has some limitations, such as the potential for premature convergence and sensitivity to parameter settings. Researchers continue to investigate waysto overcome these challenges, leading to the development of improved variants and hybrid methodologies that combine the strengths of PSO with other optimization strategies.In summary, Particle Swarm Optimization represents a significant advancement in the field of optimization algorithms. Its biologically inspired mechanism, adaptability, and versatility have made it a popular choice for solving a wide array of real-world problems across diverse disciplines. As ongoing research continues to refine and enhance PSO, itis poised to remain an essential tool for optimization in the future.。

of Optimal Static Range Reporting in One Dimension Stephen AlstrupGerth S.BrodalTheis RauheITU Technical Report Series2000-3 ISSN1600–6100November2000Copyright c2000,Stephen AlstrupGerth S.BrodalTheis RauheThe IT University of CopenhagenAll rights reserved.Reproduction of all or part of this workis permitted for educational or research useon condition that this copyright notice isincluded in any copy.ISSN1600–6100ISBN87–7949–003–4Copies may be obtained by contacting:The IT University of CopenhagenGlentevej67DK-2400Copenhagen NVDenmarkTelephone:+4538168888Telefax:+4538168899Web www.itu.dkOptimal Static Range Reporting in One Dimension Stephen Alstrup Gerth Stølting Brodal Theis Rauhe24th November2000AbstractWe consider static one dimensional range searching problems.These problems are to build static data structures for an integer set,where,which support various queries for integer intervals of.For the query of reporting all integers in contained within a query interval,we present an optimal data structure with linear space cost and with query time linear in the number of integers reported.This result holds in the unit cost RAM model with word size and a standard instruction set.We also present a linear space data structure for approximate range counting.A range counting query for an interval returns the number of integers in contained within the interval.For any constant,our range counting data structure returns in constant time an approximate answer which is within a factor of at mostof the correct answer.1IntroductionLet be a subset of the universe for some parameter.We consider static data structures for storing the set such that various types of range search queries can be answered for.Our bounds are valid in the standard unit cost RAM with word size and a standard instruction set.We present an optimal data structure for the fundamen-tal problem of reporting all elements from contained within a given query interval.We also provide a data structure that supports an approximate range counting query and show how this can be applied for multi-dimensional orthogonal range searching.In particular,we provide new results for the following query operations.FindAny:Report any element in or if there is no such element. Report:Report all elements in.Count:Return an integer such that. Let denote the size of and let denote the size of universe.Our main result is a static data structure with space cost that supports the query FindAny in constant time.As a corollary,the data structure allows Report in time,where is the number of elements to be reported.Furthermore,we give linear space structures for the approximate range counting prob-lem.That is,for any constant,we present a data structure that supports Count in constant time and uses space.The preprocessing time for the mentioned data structures is expected timematching upper bound of. For linear space cost,these bounds were previously also the best known for the queries Find-Any,Report and Count.However,for superlinear space cost,Miltersen et al.[19]providea data structure which achieves constant time for FindAny with space -tersen et al.also show that testing for emptiness of a rectangle in two dimensions is as hard as exact counting in one dimension.Hence,there is no hope of achieving constant query time for any of the above query variants including approximate range counting for two dimensions using space at most.Approximate data structures Several papers discuss the approach of obtaining a speed-up ofa data structure by allowing slack of precision in the answers.In[17],Matias et al.study an approximate variant of the dynamic predecessor problem,in which an answer to a prede-cessor query is allowed to be within a multiplicative or additive error relative to the correct universe position of the answer.They give several applications of this data structure.In particular,its use for prototypical algorithms,including Prim’s minimum spanning tree al-gorithm and Dijkstra’s shortest path algorithm.The papers[4]and[6]provide approximate data structures for other closely related problems,e.g.,for nearest neighbor searching,dy-namic indexed lists,and dynamic subset rank.An important application of our approximate data structure is the static-dimensional orthogonal range searching problem.The problem is given a set of points in,to computea query for the points lying in a-dimensional box.Known data structures providing sublinear search time have space cost growing exponential with the di-mension.This is known as the“curse of dimensionality”[9].Hence,for of moderate size,a query is often most efficiently computed by a linear scan of the input.A straight-forward optimization of this approach using space is to keep the points sorted by each of the coordinates.Then,for a given query,we can restrict the scan to the dimen-sion,where fewest points in have the th coordinate within the interval.This approach leeds to a time cost of where is the number of points to be scanned and is the time to compute a range counting query for a given -ing the previous best data structures for the exact range counting problem,this approach has a time cost of1.2OrganizationThe paper is organized as follows:In Section2we define our model of computation and the problems we consider,and state definitions and known results needed in our data structures. In Section3we describe our data structure for the range reporting problem,and in Section4 we describe how to preprocess and build it.Finally,in Section5we describe how to extend the range reporting data structure to support approximate range counting queries.2PreliminariesA query Report can be implemented byfirst querying FindAny.If anis returned,we report the result of recursively applying Report,then,and the result of recursively applying Report.Otherwise the empty set is returned.Code for the reduction is given in Figure2.If elements are returned,a straightforward induction shows that there are recursive calls to Report,i.e.at most calls to FindAny, and we have therefore the following lemma.Lemma1If FindAny is supported in time at most,then Report can be supported in time,where is the number of elements reported.The model of computation,we assume throughout this paper,is a unit cost RAM with word size bits,where the set of instructions includes the standard boolean operations on words,the arbitrary shifting of words,and the multiplication of two words.We assume that the model has access to a sequence of truly random bits.For our constructions we need the following definitions and results.Given two words and,we let denote the binary exclusive-or of and.If is a bit word and a nonnegative integer,we let and denote the rightmost bits of the result of shifting bits to the right and bits to the left respectively,i.e.and .For a word,we let denote the most significant bit position in that contains a one,i.e.for.We define. Fredman and Willard in[13]describe how to compute in constant time.Theorem1(Fredman and Willard[13])Given a bit word,the index can be com-puted in constant time,provided a constant number of words is known which only depend on the word size.Essential to our range reporting data structure is the efficient and compact implemen-tation of sparse arrays.We define a sparse array to be a static array where only a limited number of entries are initialized to contain specific values.All other entries may contain ar-bitrary information,and crucial for achieving the compact representation:It is not possible to distinguish initialized and not initialized entries.For the implementation of sparse arrays we will adopt the following definition and result about perfect hash functions.Definition1A function is perfect for a set if is1-1on.A familyis an-family of perfect hash functions,if for all subsets of size there is a function that is perfect for.3The question of representing efficiently families of perfect hash functions has been throughly studied.Schmidt and Siegel[21]described an-family of perfect hash functions where each hash function can be represented by bits.Jacobs and van Emde Boas[16]gave a simpler solution requiring bits in the standard unit cost RAM model augmented with multiplicative arithmetic.Jacobs and van Emde Boas result suffices for our purposes.The construction in[16]makes repeated use of the data structure in[12]where some primes are assumed to be known.By replacing the applica-tions of the data structures from[12]with applications of the data structure from[10],the randomized construction time in Theorem2follows immediately.Theorem2(Jacobs and van Emde Boas[16])There is an-family of perfect hash functions such that any hash function can be represented in words and evaluated in constant time for.The perfect hash function can be constructed in expected time.A sparse array can be implemented using a perfect hash function as follows.Assume has size and contains initialized entries each storing bits of ing a perfect hash function for the initialized indices of,we can store the initialized entries of in an array of size,such that for each initialized entry.If is not initialized,is an arbitrary of the initialized entries(depending on the choice of ).From Theorem2we immediately have the following corollary.Corollary1A sparse array of size with initialized entries each containing bits of infor-mation can with expected preprocessing time be stored using space words,and lookups are supported in constant time,if and.For the approximate range counting data structure in Section5we need the following result achieved by Fredman and Willard for storing small sets(in[14]denoted Q-heaps; these are actually dynamic data structures,but we only need their static properties).For a set and an element we define.Theorem3(Fredman and Willard[14])Let be a set of bit words and an integer,where ing time and space words,a data structure can be constructed that supports queries in constant time,given the availability of a table requiring space and preprocessing time.The result of Theorem3can be extended to sets of size for any constant, by constructing a-ary search tree of height with the elements of stored at the leaves together with their rank in,and where internal nodes are represented by the data structures of Theorem3.Top-down searches then take time proportional to the height of the tree.Corollary2Let befixed constant and a set of bit words and an integer,where ing time and space words,a data structure can be constructed that supports predecessor queries in constant time,given the availability of a table requiring space and preprocessing time.40 Array 12341234567891011121314151011001110011Figure1:The binary tree for the case=4,,and.The set induces the setsand,and the two sparse arrays and.3Range reporting data structureIn this section we describe a data structure supporting FindAny queries in constant time.The basic component of the data structure is(the implicitly representation of)a perfect binary tree with leaves,i.e.a binary tree where all leaves have depth,if the root has depth zero.The leaves are numbered from left-to-right,and the internal nodes of are numbered.The root is thefirst node and the children of node are nodes and,i.e.like the numbering of nodes in an implicit binary heap[11,25].Figure1 shows the numbering of the nodes for the case.The tree has the following properties (see[15]):Fact1The depth of an internal node is,and the ancestor of is,for .The parent of leaf is the internal node,for.For ,the nearest common ancestor of the leaves and is theancestor of the leaves and.For a node in,we let and denote the left and right children of,and we let denote the subtree rooted at and denote the subset of where if,and only if,,and leaf is a descendent of.We let be the subtree of consisting of the union of the internal nodes on the paths from the root to the leaves in,and we let be the subset of consisting of the root of and the nodes where both children are in.We denote the set of branching nodes.Since each leaf-to-root path in contains internal nodes,we have ,and since contains the root and the set of nodes of degree two in the subtree defined by,we have,if both children of the root are in and otherwise.To answer a query FindAny,the basic idea is to compute the nearest common an-cestor of the nodes and in constant time.If,then eitheror is contained in,since is contained within the interval spanned by ,and and are spanned by the left and right child of respectively.Otherwise what-ever computation we do cannot identify an integer in.At most nodes satisfy .E.g.to compute FindAny,we have,,and.By storing these nodes in a sparse array together with and,we obtain a data structure using space words,which supports FindAny5Proc ReportFindAnyif thenReportoutputReportProc FindAnyif thenforif then returnreturnFigure2:Implementation of the queries Report and FindAny.in constant time.In the following we describe how to reduce the space usage of this approach to words.We consider the tree as partitioned into a set of layers each consisting of consecutive levels of,where,i.e..For a node,we let denote the nearest ancestor of, such that.If,then.Since is a power of,we can compute as,i.e.for an internal node,we can compute.E.g.in Figure1,and.The data structure for the set consists of three sparse arrays,,and,each being implemented according to Corollary1.The arrays and will be used tofind the nearest ancestor of a node in that is a branching node.A bit-vector that for each node in with(or equivalently),has if,and only if,there exists a node in with.A vector that for each node in where or stores the distance tothe nearest ancestor in of,i.e..A vector that for each branching node in stores a record with thefields:left,right,and,where and and left(and right respec-tively)is a pointer to the record of the nearest descendent in of in the left(and right respectively)subtree of.If no such exists,then left(respectively right).Given the above data structure FindAny can be implemented by the code in Figure2. If,the query immediately returns.Otherwise the value is computed,and the6nearest common internal ancestor in of the leaves and is computed together with .Using,,and we then compute the nearest common ancestor branching node in of the leaves and.In the computation of an error may be introduced,since the arrays,and are only well defined for a subset of the nodes of.However,as we show next,this only happens when.Finally we check if one of the and values of and is in.If one of the four values belongs to,we return such a value.Otherwise is returned.As an exampled consider the query FindAny for the set in Figure1.Here, ,.Since,we have, and.The four values tested are the and values of and,i.e.,and we return12.Theorem4The data structure supports FindAny in constant time and Report in time, where is the number of elements reported.The data structure requires space words. Proof.The correctness of FindAny can be seen as follows:If,then the algorithm returns,since before returning an element there is a check tofind if the element is contained in the interval.Otherwise.If,then by Fact1the computed is the parent of and.We now argue that is the nearest ancestor node of the leaf that is a branching node.If,then and,and is computed as,which by definition of is the nearest ancestor of that is a branching node.Otherwise,implying and.By definition is then defined such that is the nearest ancestor of that is a branching node.We conclude that the computed is the nearest ancestor of the leaf that is a branching node.If the leaf is contained in the left subtree of,then and.It follows that.Similarly,if the leaf is contained in the right subtree of,then.For the case where and,we have by Fact1that the computed node is the nearest common ancestor of the leaves and,where,and that.Similarly to the case,we have that the computed node is the nearest ancestor of the node that is a branching node.If,i.e.is the nearest common ancestor of the leaves and,then or.If and,thenand.If and,then and. Similarly if,then either or.Finally we consider the case where,i.e.either or.Ifand,then and.Similarly if and,then and. If and,then is either a subtree of or,implying that or respectively.Similarly if and, then either or.We conclude that if,then FindAny returns an element in.The fact that FindAny takes constant time follows from Theorem1and Corollary1,since only a constant number of boolean operations and arithmetic operations is performed plus two calls to and three sparse array lookups.The correctness of Report and thetime bound follows from Lemma1.7The space required by the data structure depends on the size required for the three sparse arrays,,and.The number of internal levels of with is, and therefore the number of initialized entries in is at most.Finally,by definition, contains at most initialized entries.Each entry of,,and requires space:,,and bits respectively,and, ,and have,and at most initialized entries respectively.The total number of words for storing the three sparse arrays by Corollary1is therefore.Theorem5Given an unordered set of distinct integers each of bits,the range reporting data structure in Section3can be constructed in expected timeor with the randomized algorithm of Andersson et al.[5]in expected timeThe information to be stored in the arrays and can by another traversal of be constructed in time linear in the number of nodes to be initialized.Consider an edgein,where is the parent of in,i.e.is the nearest ancestor node of in that is a branching node or is the root.Let be the nodes on the path from to in such that.While processing the edge we will compute the information to be stored in the sparse arrays for the nodes, i.e.the nodes on the path from to exclusive.From the defintion of and we get the following:For the array we store,if),and for all,where and.For the array we store for all whereor or.Finally,we store for the root and.Constructing the three sparse arrays,after having identified the.5Approximate range countingIn this section we provide a data structure for approximate range counting.Let denote the input set,and let denote the size of.The data structure uses space words such that we can support Count in constant time,for any constant.We assume has been preprocessed such that in constant time we can compute FindAny for all.Next we have a sparse array such that we for each element can compute in constant time.Both these data structures use space.Define count.We need to build a data structure which for any computes an integer such that count count.In the following we will use the observation that for,,it is easy to compute the exact value of count.This value can be expressed as and thus the computation amounts to two lookups in the sparse array storing the ranks.We reduce the task of computing Count to the case where either or are in. First,it is easy to check if is empty,i.e.,FindAny returns,in which case we simply return0for the query.Hence,assume is non-empty and let be any element in this set.Then for any integers and such that count count and count count,it holds that count count countcount Hence,we can return Count Count as the answer for Count,where is an integer returned by FindAny. Clearly,both calls to Count satisfy that one of the endpoints is in,i.e.,the integer.In the following we can thus without loss of generality limit ourselves to the case for a query Count with(the other case is treated symmetrically).We start by describing the additional data structures needed,and then how to compute the approximate range counting query using these.Define,and.We construct the following additional data structures (see Figure3).JumpR For each element we store the set JumpR count.9JnodeR For each elementwe store the integer JnodeR being the successor of in .LN For each element we store the set LN JnodeR.120304060274761625063034Figure 3:Extension of the data structure to support Count queries.,,and.Each of the sets JumpR and LN have size bounded by ,and hence using the -heaps from Corollary 2,we can compute predecessors for these small sets in constant time.These -heaps have space cost linear in the set sizes.Since the total number of elements in the structures JumpR and LN is ,the total space cost for these structures is .Furthermore,for the elements in given in sorted order,the total construction of these data structures is also .To determine Count,where ,we iterate the following computation until the desired precision of the answer is obtained.Let JnodeR .If ,return count Pred .Otherwise,,and we increase by count .Let Pred JumpR and JumpR .Now countcount .We increase by .Now count and count .If we return .If ,we are also satisfied and return .Otherwise we iterate once more,now to determine Count .Theorem 6The data structure uses spacewords and supports Count in constant timefor any constant .Proof.From the observations above we conclude that the structure uses space and expected preprocessing time .Each iteration takes constant time,and next we show that the number of iterations is at most .Let ,,after thefirst iteration.In the th iteration we either return count or count ,where .In the latter case we have count .We need to show thatcount .Since count ,we can write .We have .Since and ,we have and the result follows.References[1]P.K.Agarwal.Range searching.In Handbook of Discrete and Computational Geometry,CRC Press .1997.10[2]A.Aggarwal and J.S.Vitter.The input/output complexity of sorting and related prob-munications of the ACM,31(9):1116–1127,September1988.[3]M.Ajtai.A lower bound forfinding predecessors in Yao’s cell probe bina-torica,1988.[4]A.Amir,A.Efrat,P.Indyk,and H.Samet.Efficient regular data structures and algo-rithms for location and proximity problems.In FOCS:IEEE Symposium on Foundations of Computer Science(FOCS),1999.[5]A.Andersson,T.Hagerup,S.Nilsson,and R.Raman.Sorting in linear time?Journalof Computer and System Sciences,57(1):74–93,1998.[6]A.Andersson and O.Petersson.Approximate indexed lists.Journal of Algorithms,29(2):256–276,November1998.[7]A.Andersson and M.Thorup.Tight(er)worst-case bounds on dynamic searching andpriority queues.In STOC:ACM Symposium on Theory of Computing(STOC),2000. 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INTERNATIONAL JOURNAL OF ENERGY RESEARCH Int.J.Energy Res.2009;33:719–727Published online 13January 2009in Wiley InterScience ().DOI:10.1002/er.1507Effect of anode current collector on the performance of passive directmethanol fuel cellsQin-Zhi Lai,Ge-Ping Yin Ã,y ,z and Zhen-Bo WangSchool of Chemical Engineering and Technology,Harbin Institute of Technology,Harbin 150001,ChinaSUMMARYThe effect of anode current collector on the performance of passive direct methanol fuel cell (DMFC)was investigated in this paper.The results revealed that the anode of passive DMFC with perforated current collector was poor at removing the produced CO 2bubbles that blocked the access of fuel to the active sites and thus degraded the cell performance.Moreover,the performances of the passive DMFCs with different parallel current collectors and different methanol concentrations at different temperatures were also tested and compared.The results indicated that the anode parallel current collector with a larger open ratio exhibited the best performance at higher temperatures and lower methanol solution concentrations due to enhanced mass transfer of methanol from the methanol solution reservoir to the gas diffusion layer.However,the passive DMFC with a smaller open ratio of the parallel current collector exhibited the best performance at lower temperatures and higher methanol solution concentrations due to the lower methanol crossover rate.Copyright r 2009John Wiley &Sons,Ltd.KEY WORDS:passive direct methanol fuel cell;current collector;open ratio;methanol concentration;cell temperature1.INTRODUCTIONOver the past decades,the worldwide proliferation of portable electronic devices has created a large and growing demand for energy sources that are compact,lightweight,and powerful.The direct methanol fuel cell (DMFC)has received much attention for its high theoretical energy density,using liquid fuel,employing solid polymer electro-lyte,and working at low temperature,and has presented beneficial opportunities for use as a power source for small mobile devices [1,2].However,these accessorial devices make the fuel cell system complex.Therefore,the passive DMFC with neither liquid pumps nor gas compressors has been proposed and studied.In the passive DMFC,the oxygen diffuses into the cathode side from ambient air without any help of external devices,and the methanol solution stored in the reservoir attaches to the anode current collector and the methanol driven by concentration gradient be-tween the reservoir and anode also diffuses intozProfessor.*Correspondence to:Ge-Ping Yin,School of Chemical Engineering and Technology,Harbin Institute of Technology,Harbin 150001,China.yE-mail:yingphit@ Contract/grant sponsor:Natural Science Foundation of China;contract/grant numbers:20606007,50872027Received 21October 2008Revised 19November 2008Accepted 24November 2008Copyright r 2009John Wiley &Sons,Ltd.the anode catalyst layer.Therefore,the passive DMFC can potentially result in higher reliability, lower cost,higher fuel utilization,and higher energy density,which are in favor of mobile equipments in future electronic devices[3–7].The key component of a passive DMFC system consists of a methanol solution reservoir,anode current collector,membrane electrode assembly (MEA),and cathode current collector.Liu et al.[8] presented that the optimal concentration of methanol solution in passive DMFC was 4.0mol LÀ1.Similar opinions about the effect of methanol concentration on the performance of passive DMFC could also be found in the literature[9–13].The utilizations of highly concentrated fuel of DMFCs with vapor fed had also been reported[14,15].Chen et al.reported a suitable MEA for DMFC[16,17]and optimized theflow-fields[7,18].Lu et al.[19]applied a highly hydrophobic cathode microporous layer(MPL) and a thin membrane to control the water crossover.Thus,the cathodeflooding was avoided by facilitating water backflow to the anode via hydraulic permeation.Yang et al.[20] presented that the micro DMFC with a parallel flow-field at the anode and a perforatedflow-field at the cathode performed the best.Jeong et al.[21] presented the open area of cathode and the relative humidity of the atmosphere on the performance of passive air breathing PEMFCs.Chen et al.[22] found that the cell performance was improved with the increase of cathode and anode open ratios,which resulted in the improvement of mass transport of both methanol and oxygen,although the cell operating temperature decreases slightly with the increase of open ratio.The anode current collector is effective on the PEMFC performance and the methanol crossover flux is very important[23–25].In a passive DMFC, the methanol solution stored in the reservoir attaches to the anode current collector,and the methanol driven by the concentration gradient between the reservoir and the anode diffuses into the anode.The anode current collector is to provide channels for methanol fuel to access the MEA surface.Therefore,the anode current collector had a significant effect on the cell performance.In this paper,we experimentally investigated the effect of the parallel current collector and the perforated current collector on the performance of a passive DMFC.We found that the parallel current collector exhibited a better performance than the perforated current collector. Then we focused on studying the effects of the parallel current collector with different open ratios on the cell performance at different methanol concentrations and cell temperatures.2.EXPERIMENTAL2.1.MEA fabricationAll the electrocatalysts used in this paper were prepared in-house by chemical reduction with formaldehyde of H2PtCl6and RuCl3as precursors [26].The anode catalyst was40wt%PtRu(with an atomic ratio of1:1)/C and the cathode catalyst was 40wt%Pt/C.The gas diffusion layers(GDLs)for the cathode electrodes were wet-proofed Toray carbon papers coated with the MPLs,which comprised Vulcan XC-72carbon black and 10wt%of PTFE.The anode GDLs were the Toray carbon papers coated with the MPLs,which comprised Vulcan XC-72carbon black and 10wt%of Nafion ionomer(DuPont).The loading of carbon black was2mg cmÀ2for both the anode and the cathode.The catalyst powder and5wt% Nafion ionomer solution were ultrasonically mixed in isopropyl alcohol to form a homogeneous catalyst ink.Then the catalyst ink was scraped onto the GDLs,and then the electrodes were dried for2h in the vacuum oven at801C.The Nafion content in both the anode and the cathode was 20wt%and the metal loading(PtRu or Pt)was 2.0mg cmÀ2in each electrode.Nafion117polymer membranes(DuPont) were used to fabricate MEAs.Before being applied to the electrodes,the membranes were pretreated in four steps to eliminate the organic and inorganic contaminants.First,membranes were boiled in3wt%H2O2solution followed by washing in the ultra-pure water.Then,they were boiled in0.5mol LÀ1H2SO4solution.Finally, the membranes were boiled again in the ultra-pure water.Each step took about1h.The pretreated Nafion117membrane was sandwiched betweenI,G.-P.YIN AND Z.-B.WANG 720the anode and the cathode,and then the assembly was hot pressed under a loading of100kg cmÀ2for 90s at1351C.2.2.Single cellfixtureThe prepared MEA was sandwiched between two graphite plates to form an apparent area of approximately9cm2.The graphite plates of the cathode side was machined with many holes for air diffusion and the anode side machined through the graphite plates had channels and large open space for delivering and storing methanol solution, respectively.The oxygen diffused into the cathode side from ambient air without any help of external devices,such as a pump or a fan,and the methanol solution was stored in the reservoir attached to the anode side plate,and the methanol driven by concentration gradient between the reservoir and the anode diffused into the anode.The volume of the methanol reservoir was10cm3.The extension area of the bipolar plates served as a current collector,and a heating tape was attached to the extension area to adjust the operating temperature of passive DMFC to a desired value during the experiments.2.3.Anode current collector designThe geometry areas of current collectors are listed in Table I and Figure 1.As can be seen from Figure1and Table I,the open ratio of the current collector with perforatedflow-fields(perforated current collector)is50%,and the open ratios of current collectors with parallelflow-fields(parallel current collector-1to perforated current collector-3)are from35.5to68.8%.2.4.Electrochemical measurementsThe Fuel Cell Testing System(Arbin Instrument Corp.)connecting with a computer was used to control the conditions of discharge and record the voltage–current curves.For each discharging current point along the I–V curve,a more than 40-s waiting time was used to obtain the stable voltage.A solution of 1.0–8.0mol LÀ1aqueous methanol driven by the concentration gradient between the reservoir and the anode diffused into the anode.The oxygen diffused into the cathode side from ambient air without any help of external devices.Prior to testing the performance of passive DMFC,the MEA was installed in an active cell fixture and activated at801C for about24h. During the activation period,methanol solution of 2.0mol LÀ1was fed at aflow rate of3.0mL minÀ1, while oxygen was supplied under atmospheric pressure at aflow rate of200mL minÀ1.3.RESULTS AND DISCUSSION Figure2shows the performance of passive DMFCs with different anode current collectors. The performance of the passive DMFC with the parallel current collector is better than that with the perforated collector.In the initial discharge process,its performance with the parallel current collector is similar to that with the perforated current collector.However,the performance of the latter evidently decays at higher current densities. This is because the anode of the passive DMFC with the perforated current collector is poor at removing the produced CO2bubbles that block the access of fuel to the active sites and thusTable I.The geometry of the anode current collector.Current collector Perforated currentcollectorParallel currentcollector-1Parallel currentcollector-2Parallel currentcollector-3Channel width(mm)—122Rib width(mm)—221 Aperture(mm)4———Holes–centers distance(mm)5———Depth(mm)2222 Open area(mm2)452319450600 Effective area(mm2)900899900896 Open ratio(%)5035.55068.8 EFFECT OF ANODE CURRENT COLLECTOR ON THE PERFORMANCE OF DMFC721degrade its performance [20,23].On the other hand,the passive DMFC with the parallel current collector exhibits the better performance due to the easier removal of CO 2bubbles from the anode.Figure 3shows that the transient discharging voltage curves of passive DMFCs with different anode current collectors at current density 30mA cm À2at an ambient temperature and a cell temperature of 301C.The passive DMFC with the parallel anode current collector shows the higher transient discharging voltage.In the initial discharge process,the transient discharging voltage of the passive DMFC with the perforated current collector sharply decays to about 0.26V,and then slowly decreases with time.The anode of the passive DMFC with the perforated current collector makes against the removing ofproducedFigure 1.Geometry of the anode current collectors:(a)perforated current collector;(b)parallel current collector-1;(c)parallel current collector-2;and (d)parallel currentcollector-3.Figure parison of the passive DMFC perfor-mance among DMFCs with different anode current collectors (2.0mol L À1methanol solution,cell tempera-ture 301C).I,G.-P.YIN AND Z.-B.WANG722CO 2bubbles.Therefore,its voltage fastly degrades in the initial discharge process.Moreover,we still study the effects of different parallel current collectors as the parallel current collector exhibited a better performance than the perforated current collector.The effects of different open ratios of the parallel current collectors on the cell performance were investigated using collector-1(open ratios:35.5%),collector-2(open ratios:50%),and collector-3(open ratios:68.8%).Figure 4shows the polarization curves and the power density curves of passive DMFCs with the parallel current collector at a methanol concentration of 2.0mol L À1.The maximum power density of the passive DMFC with an open ratio of 50%is the highest.However,three parallel current collectors of passive DMFCs exhibit similar performances.Figure 5shows the polarization curves and the power density curves of passive DMFCs with parallel current collectors at a methanol concentration of 4.0mol L À1.The cell with the parallel current collector with an open ratio of 50%exhibits the best performance.The parallel current collectors with a smaller open ratio (35.5%)and a larger open ratio (68.8%)exhibit the worse cell performances.It is believed that the parallel current collector with a smaller open ratiopresents a smaller effective contact area between the liquid fuel and the MEA,which results in the degradation of the cell performance.On the other hand,the parallel current collector with a larger open ratio presents a larger effective contact area between the liquid fuel and the MEA.However,first of all,the internal resistance of the cell increases with the increase of the open ratio of the parallel current collector [26].Second,the larger methanol permeation area causes a higher methanol crossover rate through the membrane.Figure 6shows the transient discharging voltage curves of passive DMFCs withdifferentFigure 3.Transient discharging voltage–time curves at a current density of 30mA cm À2with a start from the passive DMFC to be fueled with 2.0mol L À1methanol solution (10mL)at passive DMFCs with different anodecurrent collectors (cell temperature 301C).Figure 4.The effect of different open ratios of the parallel current collector on the performance of the cellwith 2.0mol L À1methanol at 301C.Figure 5.The effect of different open ratios of the parallel current collector on the performance of the cellwith 4.0mol L À1methanol at 301C.EFFECT OF ANODE CURRENT COLLECTOR ON THE PERFORMANCE OF DMFC723parallel collectors at a current density of 15mA cm À2.To investigate the fuel utilization,the Faraday efficiency (Z )is adopted for the passive DMFC with different open ratios.The Faradic efficiency is here defined as a ratio of the actual discharge capacity versus the theoretical capacity of fuel used in the fuel cell.It is believed that the Faraday efficiency of the passive DMFC was reduced because of the loss of methanol by crossover and remaining methanol in the reservoir,which cannot be used due to methanol mass transfer limitations.The Faradic efficiency can be calculated with the following equation [8]:Z ¼it6CVFÂ100%ð1Þwhere i (A)is the discharging current,t (s)the time of the discharging process C (mol L À1)the methanol concentration,V (L)the methanol solution volume,F (C)the Faraday constant,and Z the Faradic efficiency.The Faradic efficiencies determined by Equation (1)with different methanol concentrations at a constant current density of 15mA cm À2are given in Table II.The Faradic efficiency decreases from 48.3to 42.0%when the open ratio increased from 35.5to 68.8%.The lower Faradic efficiency is primarily caused by the higher rate of methanol crossover with a higher open ratio.In addition,it can be seen from Figures 4and 5that the highest open-circuit voltage (OCV)is obtained with a parallel current collector-1.It is believed that the gradual decrease of OCVs with the increase of open ratio results from the increase of methanol crossover through the Nafion 117membrane.Figure 7shows that the anode of the passive DMFC with the parallel current collector-3exhibits the best performance with the methanol concentration of 1.0mol L À1.It is believed that the transfer of fuel molecules into the anode catalyst layer is the main factor affecting the cell performance at a lower methanol concentration.Under such a situation,the parallel current collector with a larger open ratio affords a larger effective contact area between the liquid fuel and the GDL,which improves the mass transfer of methanol from the methanol solution reservoir to the catalyst layer.Therefore,the parallel current collector with a larger open ratio tends toyieldFigure 6.Transient discharging voltage at a current density of 15mA cm À2with a start from the passive DMFC to be fueled with 2.0mol L À1methanol solution (10mL)at the passive DMFC with different open ratios (air temperature 201C,the passive DMFCtemperature 301C).Table II.The effect of the open ratio on Faradic efficiencies for the passive DMFC under current density(15.0mA cm À2)discharge.Open ratio (%)i (mA)C (mol L À1)V (ml)Z (%)35.513521048.35013521044.168.813521042.0Figure 7.The effect of different open ratios of the parallel current collector on the performance of the cellwith 1.0mol L À1methanol at 301C.I,G.-P.YIN AND Z.-B.WANG724a better cell performance with a lower methanol solution concentration.Figure 8shows that the parallel current collector-1exhibits the best performance with a methanol concentration of 8.0mol L À1.It is believed that when the cell is operating at a higher methanol solution concentration,the methanol transfer rate becomes faster and the lower performance is primarily caused by the higher rate of methanol crossover and excessive water crossover through the membrane with a higher open ratio [27,28].The experiments were carried out at 20and 401C with the same methanol concentration as in Figures 9and 10,respectively.In Figure 9,the anode of the passive DMFC with the parallel current collector-1exhibits the best performance at a low temperature of 201C.It is believed that there are more methanol molecules in the surface of the anode catalyst layer with a larger open ratio.However,the poor catalytic activity of the anode at a low temperature of 201C leads to a higher methanol crossover rate through the membrane.Therefore,the anode of the passive DMFC with the parallel current collector-1exhibits the best performance.However,as can be seen from Figure 10,at a higher temperature of 401C,the anode of the passive DMFC with the parallel current collector-3exhibits the best performance.It is believed that the catalytic activity of the anode catalyst increases with the increase of temperature,and the higher methanol mass transfer ratebecomes the main factor enhancing the cell performance.On the other hand,the anode of the passive DMFC with smaller open areas means a smaller effective contact area between the liquid fuel and the GDL,which weakens the methanol mass transfer.Therefore,the anode of the passive DMFC with the parallel current collector-3exhibits the best performance.4.CONCLUSIONThe effect of the anode current collector on the performance of the passive DMFCwasFigure 8.The effect of different open ratios of the parallel current collector on the performance of the cellwith 8.0mol L À1methanol at 301C.Figure 9.The effect of different open ratios of the parallel current collector on the performance of the cellwith 2.0mol L À1methanol at 201C.Figure 10.The effect of different open ratios of the parallel current collector on the performance of the cellwith 2.0mol L À1methanol at 401C.EFFECT OF ANODE CURRENT COLLECTOR ON THE PERFORMANCE OF DMFC725investigated.The experimental results show that the passive DMFCs with the perforated current collector are poor at removing the produced CO2 bubbles,which block the access of fuel to the active sites and thus degrade the cell performance, compared with the parallel current collector.Moreover,the effect of different parallel current collectors with various open ratios on performances of the passive DMFCs at different temperatures and different methanol concentrations is also studied.The passive DMFC equipped with a smaller open ratio (35.5%)of the parallel current collector exhibits the best performance at a higher methanol solution concentration and a lower temperature as the methanol mass transfer rate becomes relatively fast,and the best performance is primarily caused by the lowest methanol crossover rate with a smaller open ratio.The experiments also reveal that the passive DMFCs equipped with a larger open ratio(68.8%)of the parallel current collector exhibit the best performance at a lower methanol concentration and a higher temperature.The best performance results primarily from the improvement of the mass transfer of methanol to the GDL due to the larger open ratio.ACKNOWLEDGEMENTSThis work was supported by Natural Science Founda-tion of China(Nos.20606007and50872027).REFERENCES1.Springer TE,Zawodzinski TA,Gottesfeld S.Polymerelectrolyte fuel cell model.Journal of the Electrochemical Society1991;136:2334–2342.2.Fukada S.Analysis of oxygen reduction rate in aprotonexchange membrane fuel 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专利名称：Optimal control system发明人：Russell L. Dailey申请号：US09306900申请日：19990507公开号：US06330483B1公开日：20011211专利内容由知识产权出版社提供专利附图：摘要：An optimal control system is described having multiple aspects. In one aspect,an arrangement is provided for eliminating integrator windup. This aspect includesforming a control difference signal that is a combination of differenced inputs and then subsequently integrating and limiting the control difference signal to form a controlsignal that is provided to the plant. In another aspect, an arrangement is provided for eliminating cross-channel coupling. In this aspect, an error signal is formed as the difference between a commanded signal and a regulator sensor signal. In addition, an injection error signal is combined with the error signal. The injection error is of an amount sufficient to ensure that only an attainable command signal is provided to the plant, without significant cross-channel coupling due to saturation of a control effector. In another aspect, an arrangement is provided for improving output mixing of the control signal between available plant effectors. The aspects of eliminating cross-channel coupling and output mixing rely on an optimization algorithm newly described herein and termed the Dailey L1 Optimization Algorithm.申请人：THE BOEING COMPANY代理机构：Christensen O'Connor Johnson Kindness PLLC更多信息请下载全文后查看。

专利名称：OPTIMAL CONTROL SYSTEM 发明人：DAILEY, Russell, L.申请号：US2000011482申请日：20000427公开号：WO00/068744P1公开日：20001116专利内容由知识产权出版社提供摘要：An optimal control system is described having multiple aspects. In one aspect, an arrangement is provided for eliminating integrator windup. This aspect includes forming a control difference signal that is a combination of differenced inputs and then subsequently integrating and limiting the control difference signal to form a control signal that is provided to the plant. In another aspect, an arrangement is provided for eliminating cross-channel coupling. In this aspect, an error signal is formed as the difference between a commanded signal and a regulator sensor signal. In addition, an injection error signal is combined with the error signal. The injection error is of an amount sufficient to ensure that only an attainable command signal is provided to the plant, without significant cross-channel coupling due to saturation of a control effector. In another aspect, an arrangement is provided for improving output mixing of the control signal between available plant effectors. The aspects of eliminating cross-channel coupling and output mixing rely on an optimization algorithm newly described herein and termed the Dailey L1 Optimization Algorithm.申请人：THE BOEING COMPANY地址：US国籍：US代理机构：HAMLEY, James, P.更多信息请下载全文后查看。

基于互信息的贝叶斯网络结构学习算法陈一虎【期刊名称】《计算机工程与应用》【年(卷),期】2012(048)013【摘要】结构学习是贝叶斯网络的重要分支之一,而由数据学习贝叶斯网络是NP-完全问题,提出了一个由数据学习贝叶斯网络的改进算法.该算法基于互信息知识构造初始无向图,并通过条件独立测试对无向边添加方向；同时提出了一个针对4节点环和5节点环的局部优化方法来构造初始框架,最后利用贪婪搜索算法得到最优网络结构.数值实验结果表明,改进的算法无论是在BIC评分值,还是在结构的误差上都有一定的改善,并且在迭代次数、运行时间上均有明显降低,能较快地确定出与数据匹配程度最高的网络结构.%Structure learning is one of the most important branches in Bayesian network, while learning Bayesian network structures from data is NP-complete. An improved algorithm is provided for learning Bayesian network structures from data. It constructs the initial undirected graph based on mutual information, and then orients undirected edges by using conditional independence tests, additionally a local optimal method for four-node and five-node loops is proposed to construct the initial draft about the structure, finally greedy search is performed to explore the optimal structure. Numerical experiments show that both the BIC score and structure error have some improvements, and the number of iterations and running time are greatly reduced. Therefore the structure with highestdegree of data matching can be relatively faster determined by the improved algorithm.【总页数】6页(P39-43,52)【作者】陈一虎【作者单位】宝鸡文理学院数学系,陕西宝鸡721013【正文语种】中文【中图分类】TP181【相关文献】1.基于互信息的贝叶斯网络结构学习 [J], 纪厚业;罗倩2.基于互信息的贝叶斯网络结构学习算法 [J], 王越;谭暑秋;刘亚辉3.基于条件互信息和概率突跳机制的贝叶斯网络结构学习算法 [J], 魏中强;徐宏喆;李文;桂小林4.基于MMHC算法的贝叶斯网络结构学习算法研究 [J], 何德琳;程勇;赵瑞莲5.基于混合樽海鞘-差分进化算法的贝叶斯网络结构学习算法 [J], 刘彬;范瑞星;刘浩然;张力悦;王海羽;张春兰因版权原因，仅展示原文概要，查看原文内容请购买。