The Intrinsic Properties of SMMJ14011+0252

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其中，由外界因素引起的故障占据了相当大的比例。

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On interval fuzzy S-implicationsB.C.Bedregal a,*,G.P.Dimuro b ,R.H.N.Santiago a ,R.H.S.Reiser ca Universidade Federal do Rio Grande do Norte,Departamento de Informática e Matemática Aplicada,Campus Universitário,59072-970Natal,BrazilbUniversidade Federal do Rio Grande,Programa de Pós-Graduação em Modelagem Computacional,Campus Carreiros,96201-090Rio Grande,Brazilc Universidade Católica de Pelotas,Programa de Pós-Graduação em Informática,Rua Felix da Cunha 412,96010-000Pelotas,Brazil a r t i c l e i n f o Article history:Received 6March 2008Received in revised form 21August 2009Accepted 21November 2009Keywords:Fuzzy logic Interval mathematicsInterval representationInterval fuzzy implicationInterval S-implicationInterval automorphisma b s t r a c tThis paper presents an analysis of interval-valued S-implications and interval-valued auto-morphisms,showing a way to obtain an interval-valued S-implication from two S-implica-tions,such that the resulting interval-valued S-implication is said to be obtainable .Someconsequences of that are:(1)the resulting interval-valued S-implication satisfies the cor-rectness property,and (2)some important properties of usual S-implications are preservedby such interval representations.A relation between S-implications and interval-valued S-implications is outlined,showing that the action of an interval-valued automorphism on aninterval-valued S-implication produces another interval-valued S-implication.Ó2009Elsevier Inc.All rights reserved.1.IntroductionFuzzy set theory was introduced by Zadeh [76],allowing the development of soft computing techniques centered on the idea that computation,reasoning and decision making should exploit,whenever possible,the tolerance for imprecision and uncertainty [78].Like classical set theory,the corresponding fuzzy logic has been developed as formal deductive systems,but with a com-parative notion of truth that formalizes deduction under vagueness.It provides tools for approximate reasoning and decision making together with a framework to deal with imprecision,uncertainty,incompleteness of information,conflicting infor-mation,partiality of truth and partiality of possibility [79],improving the design of flexible information processing systems[51].It has been applied in several areas,such as control systems [18],decision making [17],expert systems [67],pattern recognition [19,50],etc.On the other hand,fuzzy logic may be viewed as an attempt to formalize/mechanize the human capability to perform a wide variety of physical and mental tasks without any measurements or computations [79].Fuzzy sets were originally defined by membership functions of the form l A :X !½0;1 ,where any membership degree l A ðx Þwas a precise number.However,in some situations,we do not have precise knowledge about the membership function (or the membership degree)that should be taken into account.This consideration has led to some extensions of fuzzy sets,giving rise to type-n fuzzy sets [77],which incorporated uncertainty about membership functions and membership degrees into fuzzy set theory,where the ‘‘precise number”representing a membership degree was generalized to a value carrying its uncertainty.0020-0255/$-see front matter Ó2009Elsevier Inc.All rights reserved.doi:10.1016/j.ins.2009.11.035*Corresponding author.Tel.:+558432153814;fax:+558432153813.E-mail addresses:bedregal@dimap.ufrn.br (B.C.Bedregal),gracaliz@ (G.P.Dimuro),regivan@dimap.ufrn.br (R.H.N.Santiago),reiser@ucpel.tche.br (R.H.S.Reiser).Information Sciences 180(2010)1373–1389Contents lists available at ScienceDirectInformation Sciencesj o u r n a l ho m e p a g e :w w w.e l s e vier.c om/loc ate/ins1374 B.C.Bedregal et al./Information Sciences180(2010)1373–1389Type-2fuzzy sets have been largely applied since the works of Jerry Mendel[48]in the90s,with the increase of the the-oretical research on their properties[49,71].Interval-valued fuzzy sets are a particular case of type-2fuzzy sets with a rich structure provided by Interval Mathematics[52].Interval Mathematics is a mathematical theory that aims at the representation of uncertain input data and parameters, originally interested in the automatic and rigorous control of the errors that arise in numerical computations[37].It has been applied to deal with the uncertainties in the results of numerical algorithms in Engineering and Scientific Computing,with contributions1/interval-comp/.in several areas[40,41],such as electrical power systems[8],mechan-ical engineering[54],chemical engineering[68],artificial intelligence[38],multiagent systems[26]and geophysics[2].Interval mathematics is another form of information theory which is related to,but independent from,fuzzy logic.In one hand,intervals can be considered to be a particular type of fuzzy set.On the other hand,interval membership degrees can be used to represent the uncertainty and the difficulty of an expert to precisely determine the fairest membership degree of an element with respect to a linguistic term,as considered in interval-valued fuzzy sets.In this case,the radius of an interval is used as an error measure[57],providing an estimation of the uncertainty during membership assignment.Interval degrees can also be viewed as summarizing the opinions of several experts about the exact membership degree for an element with respect to a linguistic term.In this case,the left and right interval endpoints are,respectively,the least and the greatest de-grees provided by a group of experts[29,57,70].In both cases,the richness of interval structures provides tools to deal with such notions of uncertainty.Interval-valued fuzzy sets were introduced independently by Zadeh[77]and other authors in the70s(e.g.,[36,39,63]), allowing to deal not only with vagueness(lack of sharp class boundaries),but also with uncertainty(lack of information) [29,45].Since then,the integration of fuzzy theory with interval mathematics has been studied from different viewpoints, as properly pointed out by Lodwick[45],generating several different approaches(as in[21,27–29,33,44,45,53,56,57,71,75]).In this paper,we follow the approachfirst introduced in Bedregal and Takahashi’s works[12,13],which has already been applied in our previous papers,where we provided interval extensions for some fuzzy connectives(see[9,15,25,59])by con-sidering both correctness(accuracy)and optimality aspects of interval methods[37,64].In particular,we are interested in the investigations of interval extensions of the various types of fuzzy implications and their related properties.Fuzzy implications[4–7,11,31,46,47,58,61,62,66,65,74]play an important role in fuzzy logic.In a broad sense,fuzzy implications are important not only because they are used to formalize‘‘If...then”rules in fuzzy systems,but also because they have different meanings(e.g.,S-implications,R-implications,QL-implications,D-implications etc.)to be used in per-forming inferences in approximate reasoning and fuzzy control[46].The role of fuzzy implications on the development of applications also motivates the research in the narrow sense through the investigation of related logical aspects[47].The aim of this work is to introduce an interval generalization for a particular meaning of fuzzy implications,namely,S-implications[5,6,16,47,61,30,31].This generalization,which we call interval S-implication,satisfies the correctness property mentioned above.We present an analysis of interval S-implications and interval automorphisms,showing a way to obtain an interval S-implication from two S-implications,so that the resulting interval S-implication is said to be obtainable.We prove that interval S-implications are closed under the action of the interval-valued automorphisms introduced in[33,34].We also prove that several analogous important properties of S-implications are also valid for interval S-implications,showing their applicability on interval-based fuzzy systems.Thus,this work is an important step towards the fundamentals for the devel-opment of such interval-based fuzzy systems.The paper is organized as follows:Section2discusses the notions of interval representations of real functions providing the related definitions and results.The main results related to the interval extensions of fuzzy t-conorms introduced in pre-vious works[12–14]are presented in Section3.In Section4,we discuss the interval extensions of fuzzy negations.A brief review about fuzzy implications,and,in particular,S-implications,is presented in Section5,where the main properties of S-implications are presented.Section6introduces interval fuzzy implications and the definition of interval S-implications, showing that several analogous properties of S-implications also hold for interval S-implications.The action of an interval automorphism on an interval S-implication is analyzed in Section7.Section8concludes this paper,summarizing its main results,presenting somefinal remarks and pointing out future works.2.Interval representationsConsider the real unit interval U¼½0;1 #R and the set U¼f½a;b j06a6b61g of subintervals of U.The left and right projections of an interval½a;b 2U are given by the functions l;r:U!U,defined,respectively,bylð½a;b Þ¼a and rð½a;b Þ¼b:ð1ÞFor a given interval X2U;lðXÞand rðXÞare also denoted,respectively,by X and X.The following partial orders play important roles in this paper:(i)The product order(also called component-wise order or Kulisch-Miranker order),defined,for all X;Y2U,by:X6Y()X6Y^X6Y;ð2Þ1For a survey on applications of Interval Mathematics,see,e.g.,/interval-comp/.(ii)The inclusion order,defined,for all X ;Y 2U ,by:X #Y ()X P Y ^X 6Y :ð3ÞThese partial orders can be naturally extended to U n .For example,considering the product order defined in Eq.(2),forany ~X ¼ðX 1;...;X n Þ;~Y ¼ðY 1;...;Y n Þ2U n ,one has that ~X 6~Y ()X 16Y 1^ÁÁÁ^X n 6Y n :ð4ÞAn interval function F :U n !U is said to be strictly increasing if,for each ~X ;~Y 2U n ,whenever ~X <~Y (that is,~X 6~Y and ~X –~Y )it holds that F ð~X Þ<F ð~Y Þ.The notion of interval correctness plays a very important role in numerical computations [64].A correct interval method can always guarantee that if x 2X then f ðx Þ2F ðX Þ,where F is the interval method that evaluates a real function f .In [64],the notion of correctness is formalized by the so-called Interval Representation ,considering that interval methods are represen-tations of punctual methods.In what follows,we reproduce such definition,but,instead of considering the set of real num-bers R ,we consider the set U ¼½0;1 #R .Definition 1[64].An interval X 2U is said to be a representation for a real number a if a 2X .Considering two interval representations X and Y for a real number a ;X is said to be a better interval representation of a than Y ,denoted by Y v X ,if X #Y .The notion of better interval representation can also be easily extended for n -tuples of intervals.Definition 2[64].A function F :U n !U is said to be an interval representation of a real function f :U n !U if,for each ~X 2U n and ~x 2~X ;f ð~x Þ2F ð~X Þ.F is also said to be correct with respect to f .An interval function F :U n !U is said to be a better interval representation of a real function f :U n !U than an intervalfunction G :U n !U ,denoted by G v F ,if F ð~X Þ#G ð~X Þ,for each ~X 2U n [64].In [64],the notion of optimality of interval methods was formalized by the so-called canonical interval representations of real functions,also known by the best interval representations [12]of real functions:Definition 3[64].The best interval representation of a real function f :U n !U is the interval function b f :U n !U ,defined byb f ð~X Þ¼½inf f f ð~x Þj ~x 2~X g ;sup f f ð~x Þj ~x 2~X g :ð5ÞNotice that the interval function b f is well defined and it is clearly an interval representation of f .Moreover,for any other interval representation F of f ,F v b f .This means that b f always returns a narrower interval than the intervals produced by any other interval representation of f .Thus,b f has the optimality property of interval algorithms mentioned by Hickey et al.[37],when it is seen as an algorithm to compute a real function f .Observe that if the real function f is continuous in the usual sense then,for each ~X 2U n ,one has thatb f ð~X Þ¼f f ð~x Þj ~x 2~X g ¼f ð~X Þ;ð6Þthat is,the best interval representation b f of a real function f coincides with its range [64].Definition 4.An interval function F :U n !U is obtainable if there exist projections P 1;...;P 2n :U !U ,where P i 2f l ;r g ,for i ¼1;...;2n ,and functions f 1;f 2:U n !U such that,for each X 1;...;X n 2U ,it holds thatF ðX 1;...;X n Þ¼½f 1ðP 1ðX 1Þ;...;P n ðX n ÞÞ;f 2ðP n þ1ðX 1Þ;...;P 2n ðX n ÞÞ :ð7ÞThe concept of obtainable function generalizes the notion of representable function,as proposed by Deschrijver et al.[22–24,32]in the context of interval t-norms.On the other hand,observe that every obtainable interval function F is an interval representation of some real function f (at least f 1and f 2).However,the converse is not true.For example,the interval functionF :U n !U ,defined by F ðX Þ¼½max ð0;X ÀX Þ;min ð1;X þX 10Þ ,is an interval representation of the identity on U ,id U ðx Þ¼x ,but F is not obtainable.An interval function F :U n !U preserves degenerate intervals ,if it maps degenerate intervals into degenerate intervals,that is,if,for each x 1;...;x n 2U ,there exists y 2U such that F ð½x 1;x 1 ;...;½x n ;x n Þ¼½y ;y .Notice that the best interval representation of any real function is #-monotonic (inclusion-monotonic),obtainable and preserves degenerate intervals.In this paper,we adopt the following notions of continuity defined on the set U of subintervals of ½0;1 :(i)Moore continuity [52]:is defined as an extension of the continuity on the set of the real numbers by considering themetric given by the distance between two intervals X ;Y 2U ,which is defined by:d ðX ;Y Þ¼max fj X ÀY j ;j X ÀY jg .(ii)Scott continuity:is defined as an extension of the continuity on the set of the real numbers,considering the quasi-met-ric q ðX ;Y Þ¼max f Y ÀX ;X ÀY ;0g defined over U ,introduced in [1,64].An alternative way to define the Scott continu-ity on U is to consider the set U with the reverse inclusion order as a continuous domain [35],and a function B.C.Bedregal et al./Information Sciences 180(2010)1373–138913751376 B.C.Bedregal et al./Information Sciences180(2010)1373–1389f:ðU; Þ!ðU; Þis said to be Scott-continuous if it is monotonic and preserves the least upper bound of directed sets[35].2The main result in[64]can be adapted to our context,considering the set U instead of R,as shown in the following: Theorem5.Let f:U n!U be a real function.The following statements are equivalent:(i)f is continuous;(ii)b f is Scott-continuous;(iii)b f is Moore-continuous.3.Interval t-conormsA triangular conorm(t-conorm for short)is a function S:U2!U that is commutative,associative,monotonic and has an identity‘‘0”,generalizing the classical disjunction.Among several t-conorms,in this paper,we consider the maximum t-con-orm S M:U!U,defined asS Mðx;yÞ¼max f x;y g:ð8ÞAn interval generalization of t-conorms was introduced in[13],applying the principles discussed in Section2.The so-called interval t-conorm is defined as an interval representation of a t-conorm.This generalizationfits the idea of interval member-ship degrees as approximations of exact degrees.Definition6[13].A function S:U2!U is an interval t-conorm,whenever it is commutative,associative,monotonic with respect to the product and inclusion orders,and½0;0 is the identity element.In the following,the main results related to interval t-conorms are presented.Proposition7[13,Theorems5.1and5.2].If S is a t-conorm,then its best interval representation b S:U2!U is an interval t-conorm.For example,the supremum interval t-conorm S M:U2!U,defined byS MðX;YÞ¼sup f X;Y g;ð9Þis the best interval representation of the maximum t-conorm S Mðx;yÞ,given in Eq.(8),that is,S M¼c S M.3Proposition8[14,Corollary 5.3].The function S:U2!U is an interval t-conorm if,and only if,the real functions S;S:U2!U,defined bySðx;yÞ¼lðSð½x;x ;½y;y ÞÞand Sðx;yÞ¼rðSð½x;x ;½y;y ÞÞ;ð10Þare t-conorms andSðX;YÞ¼½SðX;YÞ;ð;;ð11Þwhere l and r are,respectively,the left and right projections defined in Eq.(1).Therefore,one has that interval t-conorms are obtainable.The following result is immediate:Corollary9.Let S:U2!U be an interval t-conorm and S:U2!U be a t-conorm.If S represents S then S6S6S. Given a t-conorm S,the interval t-conorm b S can be expressed by:b SðX;YÞ¼½SðX;YÞ;SðX;YÞ :ð12Þ4.Interval fuzzy negationsLike t-conorms,fuzzy negations generalize the classical negations.A function N:U!U is a fuzzy negation ifN1:Nð0Þ¼1and Nð1Þ¼0;N2:If x P y then NðxÞ6NðyÞ;8x;y2U.Fuzzy negations satisfying the involutive property N3are called strong fuzzy nega-tions[16,43]:N3:NðNðxÞÞ¼x;8x2U.In addition,a continuous fuzzy negation is strict whenN4:If x>y then NðxÞ<NðyÞ;8x;y2U.2A directed set ofðU; Þis a non-empty subset S#U such that every pair of intervals in S has an upper bound in S.3sup denotes the supremum related to the Kulisch-Miranker or product order.B.C.Bedregal et al./Information Sciences180(2010)1373–13891377As is well known,all strong fuzzy negations are strict.An element e2U is said to be an equilibrium point of a fuzzy negation N whenever NðeÞ¼e.If N is a strict fuzzy negation, then there exists a unique equilibrium point e N2U and it holds that NðxÞP e N,for all x6e N.Conversely,one has that NðxÞ6e N,for all x P e N.Definition10.An interval function N:U!U is an interval fuzzy negation if,for all X;Y in U,the following properties hold: N1:Nð½0;0 Þ¼½1;1 and Nð½1;1 Þ¼½0;0 ;N2a If X P Y then NðXÞ6NðYÞ;N2b If X#Y then NðXÞ#NðYÞ.If N also satisfies the involutive property N3,then it is said to be a strong interval fuzzy negation:N3:NðNðXÞÞ¼X;8X2U.A Moore and Scott-continuous interval fuzzy negation N is strict if it also satisfies the following properties:N4a If X<Y then NðYÞ<NðXÞ;N4b If X&Y then NðXÞ&NðYÞ.The concepts of interval representation and obtainability show their strength on the context of fuzzy negations in the fol-lowing results.We show that those concepts guarantee that punctual properties are preserved by the interval generalization of fuzzy negations.Let N:U!U be a fuzzy negation.The interval function b N can be expressed as:b NðXÞ¼½NðXÞ;NðXÞ :ð13ÞThe proofs of the next propositions in this section can be found in[10].Proposition11.A function N:U!U is a(strict)interval fuzzy negation if,and only if,the functions N;N:U!U,defined, respectively,byNðxÞ¼lðNð½x;x ÞÞand NðxÞ¼rðNð½x;x ÞÞ;ð14Þare(strict)fuzzy negations andNðXÞ¼½NðXÞ;NðXÞ ;ð15Þwhere l and r are,respectively,the left and right projections defined in Eq.(1).Remark12.If N¼N,then NðXÞ¼b NðXÞ¼b NðXÞ.Therefore,one has that(strict)interval fuzzy negations are obtainable.Proposition13.A function N:U!U is a strong interval fuzzy negation if,and only if,there exists a strong fuzzy negation N such that N¼b N.From Eq.(13)and Remark12,if the conditions of Proposition13hold,then it follows that N¼N¼N.From Propositions11and13,it is immediate that:Corollary14.Let N:U!U be a fuzzy negation.Then b N is an interval fuzzy negation.In addition,if N is a strong(strict)fuzzy negation then b N is a strong(strict)interval fuzzy negation.An interval E2U is an equilibrium point of an interval fuzzy negation N if NðEÞ¼E.Trivially,½0;1 is an equilibrium point of any interval fuzzy negation.Thus,if an equilibrium interval E is such that E–½0;1 then E is said to be a non-trivial equi-librium point.Proposition15.If N is a strong interval fuzzy negation,then N has a degenerate equilibrium.Moreover,it is the unique non-trivial equilibrium point.5.Fuzzy implications and S-implicationsSeveral definitions for fuzzy implications together with related properties have been given(see, e.g.,[4–7,16,30,31,46,47,58,61,60,62,66,65,72–74]).However,there is just one consensus on what a fuzzy implication should be, namely:‘‘a fuzzy implication should present the behavior of the classical implication when the crisp case is considered”[47].In other words,a function I:U2!U is a fuzzy implication whenever it satisfies the minimal boundary conditions:Ið1;1Þ¼Ið0;1Þ¼Ið0;0Þ¼1and Ið1;0Þ¼0:ð16ÞSeveral reasonable properties may be required for fuzzy implications,among them we consider the following: I1:If x6z then Iðx;yÞP Iðz;yÞ(first place antitonicity);I2:If y6z then Iðx;yÞ6Iðx;zÞ(second place isotonicity);I3:Ið1;xÞ¼x(left neutrality principle);I4:Iðx;Iðy;zÞÞ¼Iðy;Iðx;zÞÞ(exchange principle);I5:Iðx;yÞ¼Iðx;Iðx;yÞÞ(iterative boolean-like law);I6:Iðx;NðxÞÞ¼NðxÞ,where N is a strong fuzzy negation;I7:NðxÞ¼Iðx;0Þis a strong fuzzy negation;I8:Iðx;1Þ¼1(dominance of truth of consequent);I9:Iðx;yÞP y;I10:Iðx;yÞ¼IðNðyÞ;NðxÞÞ,where N is a strong fuzzy negation(contra-positive);I11:Ið0;xÞ¼1(dominance falsity).Some relations between classical implications and negations can be recovered for the fuzzy case.For example,if I:U2!U is a fuzzy implication satisfying the Property I1,then there is a fuzzy negation N I:U!U that can be defined by[6,Lemma2.1]:N IðxÞ¼Iðx;0Þ:ð17ÞAnother relation between negation and implication follows the opposite direction,showing that it is possible to define a fuz-zy implication from a fuzzy negation.Let S be a t-conorm and N be a fuzzy negation.An S-implication[5,6,16,30,31,47,61]is a fuzzy implication I S;N:U2!U defined byI S;Nðx;yÞ¼SðNðxÞ;yÞ:ð18ÞIn some texts(e.g.,[16,30,31]),the definition of an S-implication requires a strong fuzzy negation.Such S-implications are called here strong S-implications.Similar definitions can be introduced for continuous S-implications and strict S-implications.Trillas and Valverde[69,Theorem3.2](see also[30,Theorem1.13]and[6,Theorem1.6])provided the following char-acterization for strong S-implications:a function I:U2!U is a strong S-implication if,and only if,it satisfies the Properties I1–I4,and tely,Baczynsky and Jayaram[6,Theorem2.6])introduced a new characterization of strong S-implications, considering properties I1,I4and I7.Strong S-implications also satisfy the properties I8–I11and the following two extra properties below:I12:Iðx;yÞP N IðxÞ;I13:Iðx;yÞ¼0if,and only if,x¼1and y¼0.Notice that any S-implication I S;N satisfies the properties I1–I3,I8,I9,and I11.If a fuzzy implication I is an S-implication then N I,as given in Eq.(17),is the underlying negation of I,that is: N IS;NðxÞ¼I S;Nðx;0Þ¼SðNðxÞ;0Þ¼NðxÞ:ð19ÞTherefore,N I is a strict fuzzy negation if,and only if,I is a strict S-implication.Baczynsky and Jayaram[6,Theorem5.2]provided a characterization for strict S-implications,where an S-implication I S;N is strict if and only if N IS;Nis strict and the properties I1and I10also hold.If a fuzzy implication I:U2!U is a strong S-implication,then I satisfies I6if,and only if,the underlying t-conorm of I isthe maximum t-conorm S M,given in Eq.(8),and,therefore,one has I¼I SM;N ,where N is a strong fuzzy negation.The strong S-implication I SM ;Nalso satisfies the properties I1–I11.Moreover,it is the only S-implication satisfying I6.Given an equilibriumpoint e N,if x2U and x P e N then one has that I SM;Nðx;xÞ¼x.6.Interval fuzzy implicationsSince real numbers may be identified with degenerate intervals in the context of interval mathematics,the boundary con-ditions that must be satisfied by the classical fuzzy implications can be naturally extended to interval fuzzy degrees,when-ever degenerate intervals are considered.Then,a function I:U2!U is said to be an interval fuzzy implication if the following interval-based boundary conditions hold:(i)Ið½1;1 ;½1;1 Þ¼Ið½0;0 ;½0;0 Þ¼Ið½0;0 ;½1;1 Þ¼½1;1 ;(ii)Ið½1;1 ;½0;0 Þ¼½0;0 .The properties presented in Section5can then also be naturally extended to an interval-based approach:I1:If X6Z then IðX;YÞP IðZ;YÞ(first place antitonicity);I2:If Y6Z then IðX;YÞ6IðX;ZÞ(second place isotonicity);1378 B.C.Bedregal et al./Information Sciences180(2010)1373–1389I 3:I ð½1;1 ;X Þ¼X (left neutrality principle);I 4:I ðX ;I ðY ;Z ÞÞ¼I ðY ;I ðX ;Z ÞÞ(exchange principle);I 5:I ðX ;Y Þ¼I ðX ;I ðX ;Y ÞÞ(iterative boolean-like law);I 6:N ðX Þ¼I ðX ;N ðX ÞÞ,where N is a strong interval fuzzy negation;I 7:N ðX Þ¼I ðX ;½0;0 Þis a strong interval fuzzy negation;I 8:I ðX ;½1;1 Þ¼½1;1 (dominance of truth of consequent);I 9:I ðX ;Y ÞP Y ;I 10:I ðX ;Y Þ¼I ðN ðY Þ;N ðX ÞÞ,where N is a strong interval fuzzy negation (contra-positive);I 11:I ð½0;0 ;X Þ¼½1;1 (dominance falsity).It is always possible to canonically obtain an interval fuzzy implication from any fuzzy implication.The interval fuzzy implication satisfies the optimality property and preserves the properties satisfied by the corresponding fuzzy implication.Proposition 16.If I is a fuzzy implication then b I is an interval fuzzy implication.Proof.It is straightforward.hIn the next results,we adopt a canonical way to construct,under some conditions,interval fuzzy implication from fuzzy implication and vice-versa.The properties of fuzzy implications presented in Section 5are related with the respective prop-erties of interval fuzzy implications enrolled above.Theorem 17.Let I 1and I 2be fuzzy implications satisfying the Properties I1and I2and such that I 16I 2.If I 1and I 2satisfy a Property Ik ,for k ¼1;...;6;8;...;11,then I :U 2!U ,defined byI ðX ;Y Þ¼½I 1ðX ;Y Þ;I 2ðX ;Y Þ ;ð20Þsatisfies the Property I k .Proof.Since I 16I 2and by the Properties I1and I2,one has that I 1ð;Y Þ6I 1ðX ;Y Þ6I 2ðX ;Y Þ6I 2ðX ;,and,therefore,I is well defined.It follows that:I 1:Let X ;Y ;Z 2U such that X 6Z .Since X 6Z ;X 6Z ,and I 1and I 2satisfy Property I1,then it holds that I 1ðZ ;Y Þ6I 1ðX ;Y Þand I 2ðZ ;6I 2ðX ;Þ.So,by Eq.(20),it follows that I ðZ ;Y Þ6I ðX ;Y Þ.I 2:Let X ;Y ;Z 2U such that Y 6Z .Since Y 6Z ;Y 6Z ,and I 1and I 2satisfy Property I2,then it holds that I 1ðX ;Y Þ6I 1ðX ;Z Þand I 2ðX ;Y Þ6I 2ðX ;Z Þ.Then,by Eq.(20),it follows that I ðX ;Y Þ6I ðX ;Z Þ.I 3:It holds that I ð½1;1 ;X Þ¼½I 1ð1;X Þ;I 2ð1;¼½X ; ¼X .I 4:By Property I4,it follows that:I ðX ;I ðY ;Z ÞÞ¼I ðX ;½I 1ð;Z Þ;I 2ðY ;Þ Þ¼½I 1ðI 1ðZ ÞÞ;I 2ðX ;I 2ðY ;¼½I 1ð;I 1ð;Z ÞÞ;I 2ðY ;I 2ðX ;ÞÞ ¼I ðY ;I ðX ;Z ÞÞ:I 5:By Property I5,it follows that:I ðX ;Y Þ¼½I 1ðX ;Y Þ;I 2ðX ;Y Þ ¼½I 1ðX ;I 1ðX ;Y ÞÞ;I 2ðX ;I 2ðX ;Y ÞÞ ¼I ðX ;½I 1ðX ;Y Þ;I 2ðX ;Y Þ Þ¼I ðX ;I ðX ;Y ÞÞ:I 6:Let N be a strong interval fuzzy negation.By Proposition 13,there exists a strong fuzzy negation N such thatN ðX Þ¼½N ðX Þ;N ðX Þ .It follows that:I ðX ;N ðX ÞÞ¼I ðX ;½N ð;N ðX Þ Þ¼½I 1ðN ðÞÞ;I 2ðX ;N ðX ÞÞ ¼½N ð;N ðX Þ ðby Property I6Þ¼N ðX Þ:I 8:One has that I ðX ;½1;1 Þ¼½I 1ðX ;1Þ;I 2ðX ;1Þ ¼½1;1 .I 9:By Property I9,it holds that I 1ðX ;Y ÞP Y and I 2ðX ;Y ÞP Y .Then,it follows that I ðX ;Y Þ¼½I 1ðX ;Y Þ;I 2ðX ;Y Þ P Y .I 10:Let N be a strong interval fuzzy negation.By Proposition 13,there exists a strong fuzzy negation N such thatN ðX Þ¼½N ðX Þ;N ðX Þ .So,by Property I10,it follows that:I ðX ;Y Þ¼½I 1ðY Þ;I 2ðX ;Þ ¼½I 1ðN ðY Þ;N ðÞÞ;I 2ðN ð;N ðX ÞÞ ¼I ð½N ð;N ðY Þ ;½N ðÞ;N ðX Þ Þ¼I ðN ðY Þ;N ðX ÞÞ:I 11:One has that I ð½0;0 ;X Þ¼½I 1ð0;X Þ;I 2ð0;Þ ¼½1;1 .hRemark 18.According to the conditions stated by Theorem 17,the Property I 7does not hold even if both I 1and I 2satisfy the Property I7.For example,considering I 1ðx ;y Þ¼min f 1Àx þy ;1g and I 2ðx ;y Þ¼min f ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1Àx 2þy p ;1g ,it is immediate that I 1and I 2are fuzzy implications,as they satisfy Eq.(16),and it holds that I 16I 2.Moreover,considering N I 1ðx Þ¼I 1ðx ;0Þ¼1Àx and N I 2ðx Þ¼I 2ðx ;0Þ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffi1Àx 2p ,it is immediate that N I 1is a strong fuzzy negation,and,sinceB.C.Bedregal et al./Information Sciences 180(2010)1373–13891379。

Digi Pile TMInfrared Sensing Solu�onsTPiS1T1252B/5058Compact Isothermal ThermopileThe TPiS1T1252B is a thermopile sensor with integrated digitization.It pro-vides as a member of the DigiPile TM family a proprietary low power1-wire dig-ital interface to access the raw data from any micro controller.It features a confinedfield of view in a TO-46package.The package features isothermal materials and constructions which ensure a quick thermal equilibrium along the sensor head.The sensor is uncalibrated.The calibration after packaging into thefinal prod-uct enables highest accuracies like required for medical applications.Instruc-tions for calibration procedures are provided if requested.One typical application is in-ear thermometry or fever screening at the fore-head.Contents1Dimensions and Connections3 2Optical Characteristics42.1Field of View (4)2.2Filter Properties (5)3Absolute Maximum Ratings6 4Device Characteristics6 5Temperature Measurement85.1Measurement Conditions (8)5.2Calculation of the Ambient Temprature (9)5.3Calculation of the Object Temperature (9)6Integration instructions and recommendations106.1Position (10)6.2Soldering (10)7Interface Characteristics117.1Interface Overview (11)7.2Direct Link Interface (12)8Packaging14 9Statements16P r o d u c t S p e c i f i c a t i o nTPiS 1T 1252B /5058Issued:17/01/2022/Revised:16/05/20221Dimensions and ConnectionsFigure 1:Mechanical Dimensions (in mm)and Pin Con figuration.A short description is given in table 1..Table 1:Pin descriptions.Further explanations follow in this document.Pin SymbolPin Name and short Functional Description.Pin Type DL Direct Link:Proprietary 1-wire Interface.Pull-up resistors are not applicable.Input /OutputVSS Ground :The ground (GND)reference for the power supply should be set to the host ground.Power VDDPower Supply :The power supply for the device.Typical operating voltage is 3.3VPowerP r o d u c t S p e c i f i c a t i o nA hot point like heat source radiates is rotated around its sensor plane typical measurement result is shown in figure 3.The result is resulting are depicted in table 2.text.Figure 3:Typical FoV measurement result1.0Table 2:Optical characteristics Parameter Symbol MinTypMaxUnitRemarks /Conditions Field of View FOV84◦at 50%intensityOptical Axis−1010◦0102030405060708090100T r a n s m i t t a n c e [%]TPiS1T1252B/5058Issued:17/01/2022/Revised:16/05/20223Absolute Maximum RatingsTable4:Maximum RatingsParameter Symbol Min Max Unit Remarks/ConditionsOperating Temperature T0−2070◦C Electrical parameters may vary from specifiedvalues in accordance with their temperature de-pendenceStorage Temperature T s−40100◦C Avoid storage in humid environment Supply Voltage VDD−0.33.6VCurrent to any pin−100100mA One pin at a timeStresses beyond the limits listed in table4may cause permanent damage to the device.Exposure to absolute maximum ratings for long time may affect the device reliability and may lead to deterioration of any parameter.4Device CharacteristicsDevice characteristics are given at25◦C ambient temperature unless stated otherwise.Table5:Power SupplyParameter Symbol Min Typ Max Unit Remarks/ConditionsOperating Voltage VDD2.43.33.6VSupply Current IDD8.510.5µA VDD=3.3VTable6:ThermopileParameter Symbol Min Typ Max Unit Remarks/Conditions Sensitive Area A0.26mm2Absorber0.51×0.51mm2 Sensitivity∆counts/∆T240290350counts/K Tobj=40◦C Noise(peak-peak)828counts Tobj=40◦CTime constantτ22ms Addional8Hz LP Filter Power up time250ms TP OBJ and TP AMB stableResolution17BitsSensitivity0.70.80.9µV/countOffset640006450065000countsMax.Object Temp.Tobj max160◦C Full FOV, >99%The TPiS1T1252B temperature measurement is specified for a fullfield-of-view coverage by a black body with more than99%emissivity.The calculation of a temperature has to be performed on the host system and is described in section5. Figure5shows the calculated thermopile raw data TP object as a function of the ambient temperature and objecttemperature based on typical characteristics of TPiS1T1252B.The ASIC typically features a wider dynamic range as compared to the specified values in table6and7.Values out of our specifications are not guaranteed.The measurement of thermopile parameters is described in section5.The performance in the application may vary due to physical constraints.Please consult our local representative for more information.P r o d u c t S p e c i f i c a t i o nFigure 5:Typical temperature dependence of the raw thermopile outputTable 8:Electrical Data.Unless speci fied differently all data refers to 25±3◦C.Parameter SymbolMinTypMaxUnit Remarks/ConditionsDirect Link Input Low Voltage V IL 0.2V DD V Input High Voltage V IH 0.8V DD V DD +0.3VV Input Current I I −11µA Data Setup Time t DS 90200µs Data Clock Low Time t DL 2002000ns Data Clock High Time t DH 2002000ns Data Bit Settling Timet BS 2µs C LOAD <10pF Sample Time t SMPL 3.014.6ms Bit Time t BIT 25µs Update Timet UP 70µsTable 9:Sensors ’s ASIC oscillator propertiesParameter Symbol MinTypMaxUnit Remarks /ConditionsFrequencyF OSC607080kHz Temperature Dependence−10001000ppm/KP r o d u c t S p e c i f i c a t i o nIssued:17/01/2022/Revised:16/05/2022Measurementan uncalibrated sensor.This section discusses a possible calibration method and calibration conditions which were used to determine and specify the sensor properties.5.1Measurement ConditionsThe thermopile output is related to the net IR-radiation.The net IR-radiation can be correlated with the object temperature for a speci fic fixed set-up.The set-up valid for the properties as speci fied is shown in sketch 6.Figure 6:Measurement conditionsA silicon-oil immersed hollow black body with an inner diameter of 55mm and an emissivity of better than 99%has a temperature T obj of 40◦C.A temperature controlled jig with a inner diameter of 35mm has a temperature T amb is at 25.0◦C ±0.5◦C and is coated with a black paint for an emissivity of better than 96%.The jig contains the TPiS 1T 1252B sensor at a distance of 0mm to the black body.Conditions other than described in this document will lead to different properties such as sensitivity and temper-ature range.Please contact our local representative for more details.5.2Calculation of the Ambient TempratureFor a correct object temperature calculation the ambient temperature must be known.The temperature should be calculated in Kelvin and not ◦C.To calculate the ambient temperature out of TP ambient the following formula can be applied.T ambient [K ]=(25+273.15)+(TP ambient −PTAT25)·(1/M )using the calibration constants PTAT25and M.To calibrate the PTAT calibration constants,the sensor must be exposed to 2different ambient temperatures T ambient 1[K]and T ambient 2[K]while reading the corresponding PTAT values TP ambient 1[counts]and TP ambient 2[counts].We recommend an innert fluid bath.The calibration constants are calculated then byM =(TP ambient 2−TP ambient 1)(T ambient 2−T ambient 1)andPTAT25=TP ambient 1+(25◦C −T ambient 1[◦C ])·MThe inverse to calculate an expected PTAT value for a given temperature T amb is given byTP ambient [counts ]=[T amb −(25+273.15)]·M +PTAT255.3Calculation of the Object TemperatureThe thermopile output signal TP object is not only depending on the objects temperature but also on the ambient temperature T ambient as demonstrated in figure 5.To obtain the object temperature T object calculateT object [K ]=FTP object −TP 0k+f (T ambient )where T ambient is obtained as discussed in section 5.2.k is a scaling/calibration factor given byk =TP object 1−TP 0f (T object 1[K ])−f (T ambient 1[K ])and contains the emissivity of the object as well as the field-of-view coverage factor Θ.TP 0is the thermopile offset.It is obtained when the object and ambient temperature are the same (thermal equilibrium).This is for example the case when calibrating the PTAT in an innert fluid.TP object 1is the thermopile output while pointing the sensor at a warm black body with a temperature T object 1.The ambient temperature T ambient 1is the condition while calibrating the thermopile in front of the black body.It should be determined with the sensors PTAT.f (x )is in the simplest case an exponential with the exponent de fined by the sensor type.f (x )=x 3.8It ’s reverse function F (x )is thenF (x )=3.8√xTo predict a thermopile output based on the object temperature T object and ambient temperature T ambient calcu-lateTP object [counts ]=k · f (T object [K ])−f (T ambient [K ])+TP 0Since exponents and roots are heavy operations to be performed on a micro-controller based system,we rec-ommend to implement f (x )as a lookup table.An implementation in Object-C language can be provided upon request.You may contact our local representative for more details.6Integration instructions and recommendations6.1PositionIn order to obtain the highest possible performance it is possible to operate the sensor without a(protecting) front window.To measure an accurate temperature no window between the sensor and the object must be used. Excelitas measurement values are only valid when the bare sensor is exposed to the object.As the device is equipped with a highly sensitive infra-red detector,it is sensitive to any source of heat,direct or indirect.For a proper temperature measurement the device must be at the same temperature as the ambient. Sudden temperature changes will directly affect the behaviour of the sensor’s performance.This device is equipped with a highly sensitive ADC and integrated mon rules of electronics integra-tion apply.We recommend to place strong EMI sources far apart and/or to shield those.6.2SolderingFor the soldering of the detectors within PCBs,the typically applied and recommended process is wave soldering. The recommended soldering temperature shall not exceed300◦C with a maximum exposure time of5s.Other soldering processes are also possible when maintaining similar temperature profiles.Temperatures higher than recommended may affect its performance.Any soldering process should be qualified to avoid damage to the sensor.TPiS 1T 1252B /5058Issued:17/01/2022/Revised:16/05/20227Interface Characteristics7.1Interface OverviewFigure 7:Block DiagramADC TobjDecimator &Low PassSerialInterfaceVoltage ReferenceDecimator& Low PassOscillatorADC TambDigital In/OutVDD VSSTPThe functional diagram 7illustrates the functional blocks of the TPiS 1T 1252B .The thermopile sensing element,generates a voltage,which is proportional to the IR-net-radiation.It is connected to a built-in IC,Thethermopile voltage is digitized with a high resolution and high linearity differential analog-to-digital converter.The PTAT is a linear reference sensor temperature which is proportional to the temperature change.It is digitized with a separate ADC.Both channels are low pass filtered for optimal signal-to-noise performance.The ASIC includes an on-chip oscillator and a voltage reference to make it independent from the voltage supply.A proprietary serial interface called “DIRECT LINK ”is used to read the digitized data.P r o d u c t S p e c i f i c a t i o nADC counts The data represents ADC counts after low-pass filtering and the reference temperature counts.Thelow-pass data is represented as 17bit unsigned integer.The reference temperature data is represented as 14bit unsigned integer.Figure 8:Data Transmission Diagramdriven by host driven by DigiPile ®host sampling Bit stateM Timing The DIRECT LINK interface communication principle is sketched in figure 8.It can be divided into the start condition and the data stream after it.The sensor is expecting the host system to initiate the communication.Forcing DIRECT LINK to HIGH for at least t DS =90µs and then pulling it to LOW will start the communication.The host system can resume with the Readout of Bits .If the host system is not initiating the communication for a period of longer than t SMPL =14.6ms the sensor will pull the line HIGH.This must be avoided by continious readout to avoid unnesseceray heatup of the component.Readout of Bits The readout procedure is started by the forced pulse.The DigiPile TM waits for the next LOW to HIGH transition by the host system.The host system pulls the line HIGH and releases it (high impedance Z).The DigiPile TM will pull the line LOW for a 0bit state or keep it HIGH for a 1bit state.The time t BS which the signal needs to settle to a LOW level depends on the capacitive load(e.g.PCB design)at the DIRECT LINK pin.Hence,it is recommended to start implementing the interface with t BIT close to,but shorter than25µs to ensure proper LOW level settling.In next steps reduce t BIT empirically to optimize for reliable data transmission at maximum transmission speed.After reading the line state by the host system,the host pulls the line again LOW to initiate the next bit readout by a LOW to HIGH transition again.The sequence will be repeated until all bits are shifted out.After the last bit of bit[0]the host controller must force DIRECT LINK pin to LOW for at least t UP=70µs and subsequently releaseDIRECT LINK(High Z).It has to be considered that t BIT must not exceed25µs to avoid data corruption.Under no circumstances DIRECT LINK may be at LOW level for longer than25µs.It is recommended that the total time to readout one data packet should not exceed800µs to ensure always latest values.In order to reduce settling effects,the data packets have to be read continuously with equal sampling intervals.8PackagingThe Excelitas Technologies tube packaging system protects the product from mechanical and electrical damage and is designed for manual unloading.Figure9shows the basic outline.The devices are loaded sequentially andfixed with stoppers.Up to48parts arefilled into one tube.In total up to 40tubes are placed in one paper box.Information labels,ESD labels and bar-code Labels are placed on the box.The label contains the following Infor-mation:•Producer=Excelitas Technologies•Origin•Product Name•Full BAU(unique identification)number•Batch Number•Packaging Datec t S p e c i f i c a t i o n9StatementsQuality Excelitas Technologies is a ISO9001:2015certified manufacturer with established SPC and TQM. Excelitas Technologies is certified for it’s Environmental Management System according to ISO14001:2015andfor the Occupational Safety and Health Management System according to ISO45001:2018.All devices employing PCB assemblies are manufactured according IPC-A-610class2guidelines.The infra-red detection product line is certified for ANSI/ESD S.20.20:2014.Package This IR-detector is sealed to pass a He-leakage test with maximum leak rate of1×10−8mbar l s−1. Cleanliness Avoid touching the detector window.To clean windows,use only ethyl alcohol with a cotton swab when necessary.Do not expose detectors to aggressive detergents such as Freon,trichloroethylene,etc.Tracability The marking of the detector includes the principal type,a4digit number that represents the Exceli-tas identification number.A4digit date code is provided in addition to that.It consists of the production yearand week.The marking is printed on the top or side of the detector.Moisture Sensitivity Level Moisture sensitivity level classification does not apply to TO-can products.Storage at high humidities should be avoided.Electrostatic Discharge Performance All pins pass the electrostatic discharge sensitivity(ESD)test level1 (±2kV)according to IEC61000-4-2.Please make sure not to confuse this norm with other norms such as ANSI/ESDA-JEDEC JS-001-2010(Human Body Model),ESD DS5.3.1(Charge Device Model)or ESD STM5.2(Machine Model).Mechanical Avoid mechanical stress on the housing and especially on the leads.Be careful when cutting or bending leads to avoid damage.Do not bend leads less than5mm from their base.Do not drop detectors on thefloor.RoHS This sensor is a lead-free component and complies with the current RoHS regulations,especially with existing road-maps of lead-free soldering.Liability Policy The contents of this document are subject to change.The details of this document are valid by the specified revision date.Excelitas reserves the right to change at any time total or part of the content of thisspecifications without individual notification.Customers should consult with Excelitas Technologies’representa-tives to ensure updated specifications before ordering.Customers considering the use of Excelitas Technologies devices in applications where failure may cause personal injury or property damage,or where extremely high levels of reliability are demanded,are requested to discuss their concerns with Excelitas Technologies representatives before such use.The Company’s responsibility for damages will be limited to the repair or replacement of defective product.As with any semiconductor device,thermopile sensors or modules have a certain inherent rate of failure.To protect against injury,damage or loss from such failures,customers are advised to incorporate appropriate safety design measures into their product.。

探索与争鸣191科技资讯 SCIENCE & TECHNOLOGY INFORMATIONDOI：10.16661/ki.1672-3791.2009-5042-1975马克思主义社会科学方法论及其当代价值①吕微(吉林师范大学 吉林长春 130000)摘 要：马克思主义社会科学方法论具有科学性和先进性，在社会科学活动领域，马克思主义也有创造性发展，深层次地理解马克思主义社会科学方法论，了解其特点和意义、当代价值，有利于在当代中国发展过程中，用马克思主义社会科学方法论作为思想武器。

不仅如此，深化理解马克思主义社会科学方法论，还可以更好地直接作用于指导具体的社会科学研究，变成人类改造世界的行动指南。

该文重点探讨了马克思主义社会科学方法论地及其当代价值，以期提供参考借鉴。

关键词：马克思主义 社会科学方法论 基本内涵 当代价值 实践运用中图分类号：G71 文献标识码：A文章编号：1672-3791(2021)02(b)-0191-03Marxist Social Science Methodologyand Its Contemporary ValueLV Wei(Jilin Normal University, Changchun, Jilin Province, 130000 China)Abstract : Marxist social science methodology is scientif ic and advanced. In the f ield of social science activities, Marxism also has creative development. A deep understanding of Marxist social science methodology,understanding of its characteristics, significance, and contemporary value is beneficial to the development process in contemporary China. Marxist social science methodology is used as an ideological weapon.What is more, deepening the understanding of Marxist social science methodology can better direct specific social science research and become a guide for mankind to transform the world. This article focuses on the Marxist social science methodology and its contemporary value in order to provide reference.Key Words : Marxism; Social science methodology; basic connotation; Contemporary value; Practical application①作者简介：吕微（1994—），女，硕士，研究方向为马克思主义哲学。

中国泌尿外科疾病诊断治疗指南2006版第一卷主编中华医学会泌尿外科学分会主任委员那彦群副主编中华医学会泌尿外科学分会副主任委员孙则禹中华医学会泌尿外科学分会副主任委员叶章群中华医学会泌尿外科学分会副主任委员孙颖浩中国泌尿外科疾病诊断治疗指南编辑委员会主编那彦群北京大学泌尿外科研究所副主编孙则禹南京大学医学院附属鼓楼医院叶章群华中科技大学同济医学院附属同济医院孙颖浩第二军医大学第一附属医院（长海医院）编辑委员陈山首都医科大学附属北京同仁医院高居忠北京西山医院贺大林西安交通大学医学院第一附属医院黄翼然上海第二医科大学附属仁济医院孔垂泽中国医科大学附属第一医院李虹四川大学华西医院米振国山西省肿瘤医院那彦群北京大学泌尿外科研究所宋波第三军医大学附属西南医院孙光天津医科大学第二医院孙颖浩第二军医大学第一附属医院（长海医院）孙则禹南京大学医学院附属鼓楼医院王建业卫生部北京医院王晓峰北京大学人民医院王行环广东省人民医院叶章群华中科技大学同济医学院附属同济医院（按姓氏拼音排序，排名不分先后）目录序前言膀胱过度活动症临床诊治指南良性前列腺增生诊断治疗指南肾细胞癌诊断治疗指南前列腺癌诊断治疗指南致谢前言随着医学科学的发展，我国泌尿外科领域各项疾病临床诊断与治疗水平的不断提高给患者带来了众多的利益。

与此同时，我们也清醒地认识到我国泌尿外科大部分疾病的诊断、治疗方法还没有得到相应的规范和统一。

为了不断规范我们的医疗工作，中华医学会泌尿外科学分会组织全国泌尿外科各个领域的专家组成中国泌尿外科疾病诊断治疗指南编辑委员会。

经过前期准备，反复研讨及以循证医学原理为基础的国内外相关资料的分析与评价，指南编辑委员会分别制定了膀胱过度活动症、良性前列腺增生、肾癌和前列腺癌的诊断治疗指南，在征求国内知名老专家的意见后，经中华医学会泌尿外科学分会常务委员会讨论通过。

今后还将陆续推出泌尿外科其它疾病的诊断治疗指南。

这些指南是由泌尿外科学会制定的临床诊疗指南，希望尽快在全国泌尿外科学界得到推广和应用，并在临床应用过程中不断完善之。

Carbon Type Distribution of Petroleum Oils with SVM™ 4001and AbbematRelevant for: Petroleum Industry - Research, production and incoming quality control of base oils, lube oilsand process oils.Measure the required parameters and calculate carbon distribution and ring content of oilsaccording to ASTM D3238 in one go within minutes.1 Why determine carbon type distribution? The carbon type distribution serves to express the gross composition of the heavier fractions of petroleum into paraffinic, naphthenic, and aromatic components. It is one of the most important parameters for the qualification of base oils, lube oils, process oils, or plasticizer because it directly correlates to critical product performance properties. According to the standard ASTM D3238, the carbon distribution and ring content of olefin-free petroleum oils is calculated from measurements of refractive index, density and molecular weight (n-d-M method). The mean molecular weight can be calculated following ASTM D2502 from viscosity measurements at 37.78 °C and 98.89 °C (100 °F and 210 °F).So the following basic parameters are required: •kinematic viscosity at 37.78 °C and 98.89 °C (obtained from SVM™ 4001)•refractive index at 20 °C (obtained from the refractometer)•density at 20 °C (calculated from the measured density values by the SVM™ software)Further, the mean molecular weight is required. It is calculated from kinematic viscosity at 37.78 °C (100 °F) and 98.89 °C (210 °F) according toASTM D2502.From all these parameters, the carbon distribution (C A, C N, C P) and ring content (R T, R A, R N) are deter-mined according to the formulas in ASTM D3238. This report describes specifically how to test petroleum oils with the SVM™ 4001 (according to ASTM D7042, D4052 and D2502) in combination with an Abbemat refractometer to get the carbon type distribution according to ASTM D3238.2 Which instruments are used?For the viscosity and density measurement, theSVM™ 4001 Stabinger Viscometer™ with two measuring cells for simultaneous viscosity measurement at two temperatures is used.For the RI measurement, the Abbemat 550 is used. Connected via CAN interface, it is a module controlled by the SVM™ 4001 as master instrument.Tip: Any other Anton Paar refractometer from the Performance/ Performance Plus Line (300/350 or 500) or from the Heavy Duty line (450/650) can be used.3 Which samples are tested?Five oil samples as listed below were tested:SampleNytro 4000X Severely hydrotreated insulating oilT110 Severely hydrotreated base oil Nyflex 3150 Severely hydrotreated process oil Nypar 315 Severely hydrotreated process oil Samples were kindly provided by Nynas AB, Sweden.4 Sample measurement4.1 Instrument setupMethod: "SVM 4001 VI + Abbemat"SVM™ 4001:According to ASTM D7042, the following settings are predefined by default:•Measuring temperatures:Cell 1: 37.78 °C, Cell 2: 98.89 °C•Precision class "Precise"•RDV limit 0.10 %•RDD limit 0.0002 g/cm³• 5 determinations•Automatic prewetting: yes•Sulfur correction: activated (enter the value if the sulfur content is 0.8 % or higher to improve theaccuracy of the CTC calculation)•Drying time: 150 s (built-in air pump)when using compressed air at 2 bar: 60 s Abbemat refractometer:The method SVM + Abbemat includes the following settings for the refractometer:•Temperature: 20 °C•Measurement accuracy "Most Precise"•Hold time: 1 s•Timeout: 200 s•Wavelength: 589.3 nm (fixed parameter)4.2 CalibrationUse only a calibrated instrument. The calibration shall be performed periodically using certified reference standards. According to ASTM D7042, the reference standards shall be certified by a laboratory, which meets the requirements of ISO/IEC 17025 or a corresponding national standard. Viscosity standards should be traceable to master viscometer procedures. The uncertainty for density standards must not exceed 0.0001 g/cm³. For each certified value the uncertainty should be stated (k = 2; 95 % confidence level). Use one or more standard(s) in the viscosity range of your oil sample(s). If required, apply a calibration correction to improve the reproducibility. To perform calibration (correction), refer to the SVM X001 Reference Guide. For the refractometer perform at least a water check. For checks and adjustments of the Abbemat refer to the documentation of the Abbemat.4.3 Sample preparationIf the sample is not freshly drawn from a production line or else, homogenizing the test specimen may improve the measurement repeatability. For some samples degassing may be required. Refer to the SVM™ X001 Reference Guide.4.4 Filling10 mL single-use syringes are recommended to have enough sample for refills. Never use syringes with rubber seals, as the rubber is chemically not resistant and these syringes tend to draw bubbles.Ensure that the system (measuring cells and hoses) is leak tight, clean and dry. For flow-through filling, inject approx. 4.5 mL as first filling. After prewetting refill at least 1 mL or until the sample in the waste hose is free of bubbles. The typical amount for valid results is approx. 7 mL, where the volume can vary depending on the sample.4.5 Cleaning4.5.1 SolventsEnsure that the solvent starts boiling at a temperature higher than the measuring temperature. Otherwise a lack of cleaning in the hot upper cell may impact the measuring results.Petroleum benzine 100/140 (aliphatic hydrocarbon solvent mixture with a boiling range of 100 to 140 °C respectively 212 to 284 °F) is a universal solvent, suitable for most oils.Some oils may require an aromatic solvent, as they are not completely soluble in petroleum benzine. If so, use toluene or xylene as first solvent and the aliphatic hydrocarbon solvent as drying solvent.Avoid using acetone or ethanol, as these solvents start boiling below the temperature of the upper cell and as they are not suitable for most oils.For details, see the SVM™ X001 Reference Guide. 4.5.2 Cleaning Procedure•Tap the cleaning button to open the cleaning screen. Observe it during cleaning to get infor-mation on the cleaning status of the SVM™. •Remove the sample from the cells (push through using an air-filled syringe).•Fill approx. 5 mL of solvent using a syringe and leave the syringe connected (a 5 mL syringe forworks well for cleaning purposes).•Tap the motor speed button to improve the cleaning performance in the viscosity cell and stop it again.•Move the plunger of the syringe back and forth (motor at filling speed) to improve the cleaningperformance in the cells of SVM™ and Abbemat. •Blow air for some seconds through the cells to remove the sample-solvent-mixture.•Repeat the procedure until the liquid has reached approx. the solvent’s viscosity while the motor isturning at high speed.•Perform a final flush with a drying solvent to remove any residues.•Observe the cleaning screen. Dry the measuring cells until the cleaning value turns green and stays steadily green.•Set a sufficiently long drying time to ensure that also the Abbemat cell (at 20 °C) is completely dry. For details, see the SVM™ X001 Reference Guide.5 ResultsFor this report, the measurement and calculation results obtained from SVM™ 4001 and Abbemat 550 and the reference values on the respective data sheets (PDS, CoA) are compared.Carbon type analysis:Carbon distribution:T110 13.80 34.73 51.40 Nypar 315 0.20 30.55 69.23 Nyflex 3150 9.63 29.03 61.30 Nytro 4000X 2.35 47.30 50.40 Table 1: ASTM D3238 (n-d-M) Carbon distribution (mean of 4measurements)Ring content:T110 3.00 0.68 2.32 Nypar 315 1.58 0.01 1.57 Nyflex 3150 2.95 0.58 2.37 Nytro 4000X 1.96 0.08 1.88 Table 2: ASTM D3238 (n-d-M) Ring content (mean of 4measurements)Carbon distribution, deviations:T110 IR: -1.20D2140: 2.804.28 -1.40 Nypar 315 Fulfilled ** 3.45 4.22Nyflex 3150 IR: 0.63D2140: 2.63-3.98 1.30 Nytro 4000X IR: -1.65 IR: 2.30 IR: -0.60Table 3: Deviation to typical sample values *(dev. in percentage points)* Reference values / typical values were obtained by different methods. Where not mentioned, the value was determined by ASTM D2140.** Value must be < 1.Refractive Index:Sample RI meas. [nD] RI typ. [nD] Dev. [nD] T110 1.5035 1.502 0.0015 Nypar 315 1.4681 1.468 0.0001 Nyflex 3150 1.4949 1.494 0.0009 Nytro 4000X 1.4746 n.a. n.a. Table 4: Refractive Index and deviation to typical values at 20 °C ASTM D2502 Mean Molecular Mass:[g/mol] rangemeets rangevalueT110 399.59 352 ... 408 OKNypar 315 371.59368 ... 392 OKNyflex 3150 494.49 468 ... 505 OKNytro 4000X 273.01 n.a. n.a.Table 5: Mean molecular mass6 ConclusionThe assembly of SVM™ 4001 with Abbemat is perfectly suitable for determining the carbon type analysis of petroleum oils, provided that all requirements according to section 4, "Sample measurement" are fulfilled.Figure 1: SVM™ 4001 with Abbemat 5507 Literature•ASTM D7042: Standard Test Method for Dynamic Viscosity and Density of Liquids by StabingerViscometer (and the Calculation of KinematicViscosity)•ASTM D3238: Standard Test Method for Calculation of Carbon Distribution and Structural Group Analysis of Petroleum Oils by the n-d-MMethod•ASTM D2502: Standard Test Method for Estimation of Mean Relative Molecular Mass ofPetroleum Oils from Viscosity Measurements •Anton Paar Application Report SVM™ 3001 with Abbemat for Transformer Oils Doc. No.D89IA013EN.Contact Anton Paar GmbHTel: +43 316 257-0****************************APPENDIXAppendix A. Carbon type analysisCarbon-type analysis expresses the average amount of carbon atoms which occur in aromatic, naphthenic and paraffinic structures, reporting•the percentage of the carbon atoms in aromatic ring structures (% C A),•the percentage in naphthenic ring structures (% C N) and•the percentage in paraffinic side chains (% C P). There are several physical property correlations for carbon type analysis.In this application report the n-d-M method (refractive index – density – mean relative molecular mass), standardized as ASTM D3238, is described. Besides, a further empiric procedure exists, the VGC-r i method (viscosity gravity constant – refractivity intercept), standardized as ASTM D2140.Why carbon type analysis?Base oils, process oils and other petroleum oils are checked for their carbon type distribution. Oils with specified carbon type distribution are designed for different industries. Carbon type analysis according to ASTM D3238 is further used to determine the quantification of aromatics in diesel fuel.Major groups for this kind of analysis are process oils. To know the carbon type analysis is important to improve product properties, the process efficiency and reliability. Process oils are used in various fields e.g.: •as plasticizer in the rubber and polymer industrye.g. for automotive tires, sealants, footwear orother rubber products. Properties of the ready touse product like elasticity, grip, durability, lowtemperature performance, environmentalsustainability on the one hand, further solvencyand compatibility with the rubber compound during production highly depend on the used process oil.Such oils can be aromatic, naphthenic or paraffinic types.•as textile auxiliary formulations in the production process of yarns. They are used to reducerespectively avoid dust formation, prevent wearand rupture of fibers, electrostatic charging andmore. Such oils should have very low aromatichydrocarbon content and a high viscosity index. •in the production of cosmetics. Such oils need to have very low aromatic hydrocarbon content andmust meet the requirements for medical white oil.Nevertheless, there are also process oils, which are analyzed according to ASTM D2140. ASTM D3238 (n-d-M)“Standard Test Method for Calculation of Carbon Distribution and Structural Group Analysis of Petroleum Oils by the n-d-M Method”This test method covers the calculation of the carbon distribution and ring content of olefin-free petroleum oils from measurements of refractive index, density and mean relative molecular mass.The refractive index and density of the oil are determined at 20 °C. The mean relative molecular mass is estimated from measurements of viscosity at 37.78 °C and 98.89 °C (100 °F and 210 °F).These data are then used to calculatethe carbon distributionpercentage of the total number of carbon atoms that are present in aromatic rings (% C A), naphthenic rings (% C N) and paraffinic chains (% C P) orthe ring analysisproportions of aromatic rings (R A) and naphthenic rings (R N), and paraffinic chains (C P) that would comprise a hypothetical mean molecule.ASTM D2502 - Mean relative molecular mass "Standard Test Method for Estimation of Molecular Weight (Relative Molecular Mass) of Petroleum Oils From Viscosity Measurements”The mean relative molecular mass is a fundamental physical constant that can be used in conjunction with other physical properties to characterize hydrocarbon mixtures.This procedure covers the estimation of the mean relative molecular mass of petroleum oils or hydrocarbon fractions from kinematic viscosity measurements at 37.78 °C and 98.89 °C."SVM™ 4001 VI + Abbemat" MethodBeside the measurement results of the incoming parameters for the carbon type analysis and the analysis results according to ASTM D3238, this method offers a lot of additional useful parameters characterizing your oil:•kinematic viscosity at 40 °C and 100 °C(extrapolated according to ASTM D341) •Viscosity Index (according to ASTM D2270) •Carbon type composition according toASTM D2140 including the viscosity-gravity-constant (VGC) following ASTM D2501 •Density 20 °C•API Spec. Gravity 15.56 °C (60 °F)•Viscosity Gravity Constant according toASTM D2501。

Product OverviewThe silicon carbide(SiC)power MOSFET product line from Microsemi increases the performance over siliconMOSFET and silicon IGBT solutions while lowering the total cost of ownership for high-voltage applications.The MSC017SMA120S device is a1200V,17mΩSiC MOSFET in a TO-268(D3PAK)package.FeaturesThe following are key features of the MSC017SMA120S device:•Low capacitances and low gate charge•Fast switching speed due to low internal gate resistance(ESR)•Stable operation at high junction temperature,T J(max)=175°C•Fast and reliable body diode•Superior avalanche ruggedness•RoHS compliantBenefitsThe following are benefits of the MSC017SMA120S device:•High efficiency to enable lighter,more compact system•Simple to drive and easy to parallel•Improved thermal capabilities and lower switching losses•Eliminates the need for external freewheeling diode•Lower system cost of ownershipApplicationsThe MSC017SMA120S device is designed for the following applications:•PV inverter,converter,and industrial motor drives•Smart grid transmission and distribution•Induction heating and welding•H/EV powertrain and EV charger•Power supply and distributionThis section shows the specifications of the MSC017SMA120S device.Absolute Maximum RatingsThe following table shows the absolute maximum ratings of the MSC017SMA120S device.Table1•Absolute Maximum RatingsSymbolParameterRatingsUnitV DSSDrain source voltageV1200Continuous drain current at T C=25°CI DA100Continuous drain current at T C=100°C71I DM280Pulsed drain current1V GSGate-source voltage23to–10VTotal power dissipation at T C=25°CP D357WLinear derating factor3.33W/°CNote:1.Repetitive rating:pulse width and case temperature limited by maximum junction temperature. The following table shows the thermal and mechanical characteristics of the MSC017SMA120S device. Table2•Thermal and Mechanical CharacteristicsCharacteristicMinSymbolTypMaxUnitRθJCJunction-to-case thermal resistance0.280.42°C/W Operating junction temperatureT J–55175°CT STG–55150Storage temperatureT LSoldering temperature for10seconds(1.6mm from case)300WtPackage weight0.14ozg4.0Electrical PerformanceThe following table shows the static characteristics of the MSC017SMA120S device.T J =25°C unless otherwise specified.Table 3•Static CharacteristicsUnit MaxTypMin Test Conditions CharacteristicSymbol V 1200V GS =0V,I D =100µA Drain-source breakdown voltage V (BR)DSS mΩ2217.6V GS =20V,I D =40A Drain-source on resistance 1R DS(on)V 2.71.9V GS =V DS,I D =4.5mA Gate-source threshold voltage V GS(th)mV/°C –4.6V GS =V DS ,I D =4.5mA Threshold voltage coefficient ΔV GS(th)/ΔT J µA100V DS ,=1200V,V GS =0V Zero gate voltage drain currentI DSS500V DS =1200V,V GS =0V T J =125°CnA±100V GS =20V/–10VGate-source leakage currentI GSSNote:1.Pulse test:pulse width <380µs,duty cycle <2%.The following table shows the dynamic characteristics of the MSC017SMA120S device.T J =25°C unless otherwise specified.Table 4•Dynamic CharacteristicsUnit MaxTyp MinTest Conditions Characteristic Symbol pF5280V GS =0V,V DD =1000V V AC =25mV,ƒ=1MHzInput capacitanceC iss 12Reverse transfer capacitance C rss 265Output capacitance C oss nC249V GS =–5V/20V,V DD =800V I D =40ATotal gate charge Q g 63Gate-source charge Q gs 32Gate-drain charge Q gd ns52V DD =800V,V GS =–5V/20V,I D =50A,R g(ext)=4.0Ω,Turn-on delay time t d(on)21Voltage fall time t f Freewheeling diode =MSC017SMA120S (V GS =–5V)49Turn-off delay timet d(off)UnitMax Typ Min Test Conditions Characteristic Symbol 16Voltage rise time t r µJ1677Turn-on switching energy E on 395Turn-off switching energy E off ns49V DD =800V,V GS =–5V/20V,I D =50A,R g(ext)=4.0ΩTurn-on delay time t d(on)19Voltage fall time t f Freewheeling diode =MSC050SDA120B49Turn-off delay time t d(off)14Voltage rise time t r µJ1329Turn-on switching energy E on 429Turn-off switching energy E off Ω0.71f =1MHz,25mV,drain short Equivalent series resistance ESR µs 3V DS =960V,V GS =20V Short circuit withstand time SCWT mJ3500V DS =150V,I D =30AAvalanche energy,single pulseE ASThe following table shows the body diode characteristics of the MSC017SMA120S device.T J =25°C unless otherwise specified.Table 5•Body Diode CharacteristicsUnit MaxTyp MinTest Conditions Characteristic Symbol V 3.5I SD =40A,V GS =0V Diode forward voltageV SDV 3.9I SD =40A,V GS =–5Vns40I SD =50A,V GS =–5V,Drive Rg =4ΩReverse recovery time t rr nC 490Reverse recovery charge Q rr V DD =800V,dl/dt =–2500A/µsA22Reverse recovery currentI RRMTypical Performance CurvesThis section shows the typical performance curves of the MSC017SMA120S device.Figure2•Drain Current vs.V DS Figure1•Drain Current vs.V DSFigure4•Drain Current vs.V DS Figure3•Drain Current vs.V DSFigure5•RDS(on)vs.Junction TemperatureFigure6•Gate Charge CharacteristicsFigure8•I D vs.V DS3rd Quadrant Conduction Figure7•Capacitance vs.Drain-to-Source VoltageFigure10•Switching Energy Eon vs.V DS&I D Figure9•I D vs.V DS3rd Quadrant ConductionFigure11•Switching Energy Eoff vs.V DS&I DFigure12•Switching Energy vs.R gFigure13•Switching Energy vs.TemperatureFigure14•Switching Energy Eon vs.V DS&I DFigure16•Switching Energy vs.R gFigure15•Switching Energy Eoff vs.V DS&I DFigure17•Threshold Voltage vs.Junction Temp.Figure18•Forward Safe Operating AreaFigure19•Maximum Transient Thermal ImpedanceThis section shows the package specification of the MSC017SMA120S device.Package Outline DrawingThe following figure illustrates the TO-268package outline of the MSC017SMA120S device.Figure20•Package Outline DrawingThe following table shows the TO-268dimensions and should be used in conjunction with the package outline drawing.Table6•TO-268DimensionsSymbolMin(mm)Min(in.)Max(mm)Max(in.)4.90A5.100.1930.201B15.850.63816.200.624C18.7019.100.7520.7361.00D1.250.0490.03913.80E14.000.5510.543F13.300.5240.53513.60Min(mm)Min(in.)Max(mm)G2.700.1060.1142.90H1.151.450.0570.045I1.950.0772.210.087J0.940.0550.0371.40K2.400.1060.0942.70L0.400.0240.600.016M1.450.0630.0571.60N0.000.0070.180.00012.40O12.700.4880.500P5.45BSC(nom.)0.215BSC(nom.)GateTerminal1DrainTerminal2SourceTerminal3DrainTerminal4Microsemi's product warranty is set forth in Microsemi's Sales Order Terms and rmation contained in this publication is provided for the sole purpose of designing with and using Microsemi rmation regarding device applications and the like is provided only for your convenience and may be superseded by updates.Buyer shall not rely on any data and performance specifications or parameters provided by Microsemi.It is your responsibility to ensure that your application meets with your specifications.THIS INFORMATION IS PROVIDED "AS IS."MICROSEMI MAKES NO REPRESENTATIONS OR WARRANTIES OF ANY KIND WHETHER EXPRESS OR IMPLIED,WRITTEN OR ORAL,STATUTORY OR OTHERWISE,RELATED TO THE INFORMATION,INCLUDING BUT NOT LIMITED TO ITS CONDITION,QUALITY ,PERFORMANCE,NON-INFRINGEMENT,MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.IN NO EVENT WILL MICROSEMI BE LIABLE FOR ANY INDIRECT,SPECIAL,PUNITIVE,INCIDENTAL OR CONSEQUENTIAL LOSS,DAMAGE,COST OR EXPENSE WHATSOEVER RELATED TO THIS INFORMATION OR ITS USE,HOWEVER CAUSED,EVEN IF MICROSEMI HAS BEEN ADVISED OF THE POSSIBILITY OR THE DAMAGES ARE FORESEEABLE.TO THE FULLEST EXTENT ALLOWED BY LAW,MICROSEMI’S TOTAL LIABILITY ON ALL CLAIMS IN RELATED TO THIS INFORMATION OR ITS USE WILL NOT EXCEED THE AMOUNT OF FEES,IF ANY ,YOU PAID DIRECTLY TO MICROSEMI FOR THIS e of Microsemi devices in life support,mission-critical equipment or applications,and/or safety applications is entirely at the buyer’s risk,and the buyer agrees to defend and indemnify Microsemi from any and all damages,claims,suits,or expenses resulting from such use.No licenses are conveyed,implicitly or otherwise,under any Microsemi intellectual property rights unless otherwisestated.Microsemi2355W.Chandler Blvd.Chandler,AZ 85224USAWithin the USA:+1(480)792-7200Fax:+1(480)792-7277 ©2020Microsemi andits corporate affiliates.All rights reserved.Microsemi and the Microsemi logo aretrademarks of Microsemi Corporation and itscorporate affiliates.All other trademarks andservice marks are the property of theirrespective owners.Microsemi Corporation,a subsidiary of Microchip Technology Inc.(Nasdaq:MCHP),and its corporate affiliates are leading providers of smart,connected and secure embedded control solutions.Their easy-to-use development tools and comprehensive product portfolio enable customers to create optimal designs which reduce risk while lowering total system cost and time to market.These solutions serve more than 120,000customers across the industrial,automotive,consumer,aerospace and defense,communications and computing markets.Headquartered in Chandler,Arizona,the company offers outstanding technical support along with dependable delivery and quality.Learn more at .050-7781|October 2020|Preliminary11050-7781MSC017SMA120S Datasheet RevisionA Legal。

·指南与共识·中国糖尿病药物注射技术指南（2016年版）纪立农郭晓蕙黄金姬秋和贾伟平李玲陆菊明单忠艳孙子林田浩明翁建平邢秋玲袁莉章秋张明霞周智广朱大龙邹大进中华糖尿病杂志指南与共识编写委员会序根据2010年全国性糖尿病流行病学调查情况汇总，中国18岁以上成人糖尿病估测患病率为11.6%，而接受治疗的糖尿病患者仅有25.8%，其中能够达到有效血糖控制的患者仅约39.7%[1]。

可见，我国糖尿病患病率虽高，但血糖达标率却较低。

尽管有众多因素影响血糖达标，但即使是已使用胰岛素治疗后3个月及6个月的患者其血糖达标率也仅有36.2%及39.9%[2]，而患者对胰岛素注射技术掌握不到位可能是重要原因之一。

胰岛素治疗是实现良好血糖控制的重要手段之一。

胰岛素注射装置、注射技术是使用胰岛素治疗的重要环节。

“2014-2015全球糖尿病患者胰岛素注射技术调查问卷”是第三次全球糖尿病患者胰岛素注射技术近况调查。

该研究从2014年2月持续到2015年6月，共纳入来自41个国家的13298例患者，其中包括3853例中国大陆患者，100例中国台湾患者。

调查结果显示，全球范围内，不规范注射现象普遍存在，而我国糖尿病患者的注射现状更是不容乐观。

与第二次注射技术调查相比，包括注射部位轮换不规范、注射笔用针头的重复使用、注射时手法错误及患者教育不充分等现象依然存在。

这些问题影响了胰岛素治疗的效果，从而导致部分患者血糖控制不达标。

另一方面，在我国，即使是医务人员，对于胰岛素注射技术对血糖控制影响的认识也有限；对于如何规范胰岛素注射，中国的医护工作者和患者在认识上还有较多不足之处。

幸运的是，目前注射技术在糖尿病管理中的重要作用越来越受到全球糖尿病专家的关注。

2015年10月，我有幸参加了在罗马召开的注射与治疗专家推荐论坛，与来自全球54个国家的183名专家共同讨论制订了《胰岛素注射与输注新推荐》[3]，大会围绕在解剖学、生理学、病理学、心理学和注射技术等方面展开讨论。

本科毕业论文外文文献及译文文献、资料题目：What is the financial risk management? 文献、资料来源：期刊文献、资料发表（出版）日期：2011.5院（部）：商学院专业：财务管理班级：财务123姓名：任文豪学号：20120913111指导教师：张玉华翻译日期：2016.6.7外文文献：What is the financial risk management?INTRODUCTIONFinancial risk is the inevitable outcome of the modern enterprise in the face of market competition, especially in the development of market economy in China is not sound conditions is inevitable.Sales enterprise financial risk evaluation in this essay, on the basis of the proposed financial early warning mechanism and specific expounds the specific duties of early warning mechanism, finally discusses several measures to strengthen the guard against enterprise financial risk.Key words:Sales of the enterprise;Financial risk management;Avoid adviceThe research backgroundFinancial risk is the inevitable outcome of the modern enterprise in the face of market competition, especially in the development of market economy in China is not sound conditions is inevitable.Financial risk has the objectivity, inevitability and uncertainty, which requires the enterprise owners, operators should clearly realize that the objective existence of the risk.In the past, many enterprises caused by a lack of understanding of financial risk, management does not reach the designated position, the enterprise huge economic losses, even bankruptcy.How to enhance the enterprise risk management consciousness, strengthen the various possible causes of the financial risk of uncertainty scientific analysis and forecasting, from different angles, different levels and take different measures to prevent and avoid all kinds of financial risk become enterprise management priority.The concept of financial risk managementThe connotation of financial risk managementEnterprises in the process of operation and management, because of various uncertain factors, may lead to the enterprise's financial activity in one area or a certain link problems, cause enterprise funds, goods and other materials on the value of property loss, resulting in a loss of corporate profitability and solvency, this possibility is the enterprise financial risk.Under the condition of market economy,financial risk is objective existence, to completely eliminate financial risk and its impact is not realistic.National politics, economy, culture and the external environment and internal environment, such as business people, goods, content of the complexity of the instability of the market price, the uncertainty of supply and demand and the diversity of information determines the market economy under the conditions of enterprise financial risk exists objectively.Williams and was published in 1964, Hans's book "risk management and insurance", said: "the risk management is based on the risk identification, measurement and control, with the lowest cost of the degree of risk to minimize losses caused by management".Refers to the enterprise financial risk management in the full knowledge, on the basis of the financial risk faced by various scientific and effective means and methods, on all kinds of risk prediction, identification, prevention, control and processing, at the lowest cost to ensure the continuity of enterprise capital movement, the stability and profitability of a financial management activities.Financial risk management is the organic combination of risk management and financial management of a new management field, the key lies in the enterprise management departments at all levels in the organization, instruction in financial activities, by identifying, testing, the risk of objective existence in the process of enterprise capital movement, to take effective preventive measures, with the minimum cost for maximum security.The content of the financial risk managementFinancial risk management activities throughout the entire process of financial activities, from the content mainly for funding risk, including interest rate risk, investment risk, liquidity risk, etc.(1) refers to the enterprise financing risk management in the financing activities due to the change of capital supply and demand of market and macroeconomic environment, financing structure and currency structure, term structure and the change of interest rates and other uncertain factors, the possibility of damage to the enterprise.(2) the investment risk management refers to the enterprises in investment activities, due to the influence of various factors is difficult to predict and control, the risks arising from the investment return rate of lessthan anticipated goal.(3) the funding liquidity risk management refers to the enterprise cash flow and cash flow risk which is formed by the inconsistent on time.Main show is cash, accounts receivable collection risks as well as inventory liquidation risk and so on.Sales enterprise financial risk evaluationThe influence factors of enterprise financial risk1, the enterprise financial risk management mechanism is not soundAt present, most of the enterprise financial risk management limited to internal to self analysis and control of various functional departments, there is no set up specialized agencies to enterprise operation and management activities of the financial risk analysis and management, management procedures incomplete, imperfect management mechanism, enterprise can't see the enterprise goals, identify, and reflect the influence of various risk factors, not in time to prevent and control, risk is inevitable.2, enterprise management system of enforcementTo establish and perfect rules and regulations, and constantly optimize, improve the existing system, is the enterprise standard management behavior, improve the management mechanism, effective way to carry out the management responsibility, but also identify risks, risk analysis, the effective ways to avoid risk.Enterprises to establish and perfect the rules and regulations, it is necessary to strengthen execution, if the enforcement, there will be to implement work inspection, does not reach the designated position, will lead to some employees in daily work to replace voluntary, "three violations" behavior is difficult to avoid, the hard to avoid the risk.3, lack of enterprise supervision mechanismIn the real work, caused by a lack of enterprise management personnel risk consciousness, cooperation consciousness is not strong, in daily work, only care about the part of your job, don't care about the operation and management activities of other departments, the enterprise internal lack of mutual supervision and mutual restriction of management mechanism, lead to the generation of financial risk.4, the lack of scientific enterprise financial decisionsScientific financial decision making, is the precondition of avoid financial risk, financial goals.At present, in the aspect of corporate financial decisions, generally there is the phenomenon of subjective or thumb decisions, the resulting decision is unscientific, unreasonable, resulting in a financial risk.5 recovery strategy, enterprise funds, income distribution policy is not standardEnterprise internal between various departments and enterprises and superior between, in fund management and use, profit distribution, as well as unclear responsibilities, management disorder phenomenon, cause low service efficiency of funds, capital of security, integrity cannot be guaranteed, the economic benefit of landslides, or even a loss.Liquidity can not get due compensation and the losses from the enterprise of its own funds and bank loans, unable to meet the growing demand, so we have to continue to expand the scale of loans, short-term loans for long-term investment, short and lend long shots.This aggravated the tension in the enterprise funds, reduces the enterprise anti-risk ability, inevitably cause the enterprise capital turnover difficult, unbecoming loan repayment capacity and scale, produce the financial risk.Enterprise financial risk1, capital structure is unreasonable, the ratio of debt financing is too high In the enterprise capital structure, relative capital source, mainly refers to the enterprise all capital source of equity funds and the proportion of debt capital.Due to reasons such as financing decision is not scientific, the enterprise capital source structure unreasonable phenomenon exists generally, some companies asset-liability ratio is as high as 70% above.Capital source structure is not reasonable that the enterprise's financial burden, a serious shortage of solvency.2, lack of foreign investment decision-making scientific, influence the realization of the expected returnIn the process of foreign investment decisions, as companies the feasibility of investment projects is a lack of thorough system analysis and research, combined with the decision is based on the economic information is not comprehensive, not real and decision-makers decision-making ability is limited, leading to the lack of scientificinvestment decision, make investment project cannot obtain the expected profits, not timely recovery of investment, and even produce huge investment losses.3, sell on credit than major, accounts receivable out of controlAffected by the market supply and demand, some enterprises in order to increase sales and expand market share, a lot of selling products sell on credit way, result in a great increase in corporate accounts receivable.At the same time, as companies in the sales process to understand the customer's credit situation, the debt paying ability is not enough, blind credit sales, cause accounts receivable is out of control, quite a proportion of accounts receivable long-term unable to recover, thereby causing loss to the enterprise loans.4, unreasonable structure of inventory, inventory turnover rate is not high Enterprise liquid assets, the inventory account for a relatively large proportion.Enterprise inventory level structure is unreasonable, inventory turnover rate is not high, the formation of overstock backlog phenomenon.This has occupied much of corporate liquidity on the one hand, on the other hand, enterprises for keeping the inventory must also pay a lot of storage costs, rising business cost level.At the same time, inventory backlog for a long time, also increases the loss of goods storage, bear the resulting from a decline in prices of obsolete stocks losses, makes the enterprise management benefit.In the enterprise financial risk management measures Establish financial early warning mechanism, strengthen the financial risk management1, the financial risk management organization systemIn order to effectively supervise and control the financial risk, the enterprise needs to establish a special responsible for risk management organization, with full-time risk management personnel, the whole process of enterprise risk management to the overall coordination and specific planning, focus on and eliminate the threat to the financial risk of enterprise survival and development.In view of the enterprise scale, structure, and many other factors, within the company may set up "risk management committee (risk management leading group)", is responsible for theorganization and leadership of enterprise financial risk management and coordination.In the risk management committee (risk management leading group set up under the risk management office (located in the finance, the finance director and director of the office), to be responsible for the daily risk management work, main responsibility is responsible for risk management information collection, selection, sorting, analysis, transfer and archive management, and regularly report to the company leadership issues related to risk management.At the same time, the risk management department to work closely with operations, personnel, storage and transportation departments, common standard of enterprise internal financial risk management.2, implements the comprehensive budget management, establish a short-term financial early warning systemUnder the premise of enterprise in determining the long-term strategic planning, should draw up various specific period management goal, according to each phase of the management goal, is the current of all kinds of earnings, cash flow, financial condition and investment plans, etc., expressed in the form of quantification, prepare the current comprehensive budget, implements the comprehensive budget management.Enterprise financial risk management departments to carefully check and analysis of the current budget execution, budget implementation for corporate leaders early warning information, make enterprise can promptly revising the budget target, ensure the scientific nature of the budget, to early take measures to solve the problems existing in the budget implementation, ensure that enterprise management activities do not deviating from the expected target, ensure the smooth conduct business enterprise and the smooth completion of the budget targets.3, establish the index system of financial analysis, establish the financial early warning management system for a long timeFor enterprises, the establishment of short-term financial early warning management system at the same time, also according to the enterprise long-term strategic planning, establishing enterprise assets profitability, solvency, profitability and financial flexibility index system of financial analysis, establish the financialearly warning management system for a long time.Through the inspection, analysis of the index system, timely correcting deviating from the expected goal of enterprise management activities, to ensure that the enterprise long-term strategic target realization.Enterprise financial risk prevention measures1, serious analysis of internal and external changes, improve the enterprise ability to adapt to the financial management environment changes and strain capacity Although the macro environment of financial management in enterprise, the enterprise can't exert influence, but can grasp by analyzing the change trend and regularity, timely adjust the financial management policy, respond in a timely manner.To the enterprise internal financial management environment changes, the enterprise can be achieved by careful analysis research, develop a variety of contingency measures, timely change of financial management, improve the enterprise ability to adapt to the internal financial management environment changes and the strain capacity, harness and grasp earnestly, thus reducing environmental change brings to the enterprise financial risk.2, we will further improve the enterprise management rules and regulations, improve executionEnterprise financial risk exists in all aspects of enterprise management.Therefore, we should conscientiously carry out investigation and study, from different angles, different levels, organizational system leak.By further perfect the enterprise financial management rules and regulations, improve execution, strengthen financial foundation work management, achieve the goal of prevent and control the financial risk.3, establish effective staff training mechanism, strengthen the quality of employees training, on thought, implementation of knowledge, to establish a "people-oriented" management concept, improve staff awareness of risk managementOne is to grasp the leadership, corporate leadership team members to the agenda, the financial risk management work research, form a consensus, improve on thought of risk management and operation and management and economic benefit, riskmanagement and the understanding of the relationship between enterprise development.Second, in view of the possible financial risk, pays special attention to the risk management department and the relevant business units and other key post personnel training education, take conference propaganda, special education, job training, and other forms of effective education, improve the understanding of financial risk management, to strengthen the understanding of the rules and regulations, further clear responsibility.Stimulate staff's work enthusiasm and initiative, and promote the employee in risk management from passive to active participation in management, forms the enterprise internal risk management of the whole situation, effectively reduce the enterprise financial risk.And specific measures to guard against enterprise financial risk1, enterprise of fundraising risk preventionAccording to the enterprise actual situation, establish the reasonable financing plans.With the expansion of the scale of enterprise management, enterprise can according to need and may arrange the right amount of debt, to make reasonable financing plans.In order to guarantee the rationality of the financing plan, the enterprise should use the relevant index to the assessment of solvency of financing plan for testing and evaluation, such as corporate debt, its quick ratio is less than 1, the current ratio is lower than 2.Only in this way, can minimize risk, improve the level of corporate profits.At the same time, the long and short-term borrowing must carry on the reasonable arrangement, make its structure more reasonable, the repayment time, should be determined rationally to prevent financial risks due to the debt collection.Serious analysis of changes in interest rates, reasonable financing arrangements.Enterprises in the capital market financing activities, should seriously study the capital market supply and demand situation, according to the movements of interest rates, grasp its developing trend, and makes the corresponding financing arrangements.In the interest rate at a high level period, less as far as possible to raise funds, or only raise much-needed short-term funds.In interest rates in the period of transition from high to low, should as far as possible to raise funds, to need short-termfunds, should use a floating rate plan breath way.When interest rates low, financing is more favorable.In the interest rate in the period of transition from low to high, should actively raise funds for a long time, and try to adopt the fixed rate plan breath way. 2, the enterprise investment risk preventionSales companies to invest more for construction investment in fixed assets, when making decisions, must set up a scientific system of investment decision, to make scientific investment feasibility analysis, especially the analysis of the return on investment, in the benefit estimation, the use of the data, Stan must through reasoning, ensure that use the data accurately.The conclusion of the project is feasible or not, should grasp the investment payback period, to evoluate key evaluation index, net cash flow, etc.Only in the project feasibility analysis link financial gate effect, to minimize the investment decision-making risk.Intensify coordination with government functional departments, improve the external investment environment, reduce the investment risk.In the construction of fixed assets investment, the enterprise should strengthen the communication with the urban construction planning departments of the government, the coordination work, to ensure that in the realm of investment projects into the government plan to avoid the contradictions between the overall city planning investment projects and the government brought about by the investment risk.Strengthen the cultivation of investment management professionals, improve the financial ability of investors.Investment is inherently has the characteristics of "high risk, high income", the investment subject should have a strong sense of risk management, investment management personnel should be understand technology, understand the financial and understand financial knowledge, understand management, and other inter-disciplinary talent, but also have to have a willingness to take risks, dare to the spirit of innovation.Therefore, the enterprise must strengthen the cultivation of investment management professionals, improve the financial ability of investors, ensure a safe investment.3, enterprise capital recovery risk preventionTo perfect the accounts receivable management system, further standardize thebehavior of credit management.Enterprise in the formulation and implementation of the instalment payment credit policy, must fully consider reducing the number of the account receivable amount as far as possible and the holding time, reduce the management cost of accounts receivable, should choose to marginal profit is greater than the total cost of the management of accounts receivable credit policy, to further standardize the behavior of enterprise credit management, to prevent bad debt losses caused enterprises, strengthen the management of enterprise sales money safe recovery.Enhance sales personnel sense of responsibility and the risk consciousness, establish risk mortgage rates.Enterprise sales people pay a certain percentage of sales revenue of the extraction, part of which can be used to pay sales staff salaries, bonuses, others as risk mortgage rates.In this way, can prompt sales staff for each business transaction is treated with caution, for each customer's credit level and solvent are serious evaluation, sales staff and improve the sense of responsibility, do sell products to, and to ensure the back payment for goods, so as to reduce the accounts receivable, avoid bad debt losses.In short, financial risk management is an important content of modern enterprise financial strategic management not only, also is an important part of the whole enterprise management.Strengthen the management of risk has become a modern enterprise management an important content.Only full and comprehensive attaches great importance to the enterprise financial risk management, set up the correct concept of risk, be good at to the uncertainty of natural and social environment factors in scientific prediction, take various measures to prevent, can effectively avoid all kinds of financial risk, ensure enterprise capital safety.中文译文：什么是财务风险管理？介绍：财务风险是现代企业面对市场竞争的必然产物，尤其是在我国市场经济发育不健全的条件下更是不可避免。