Two-level DEA approaches in research evaluation
DEA负值处理外文文献(李老师推荐)
Decision Support
A variant of radial measure capable of dealing with negative inputs and outputs in data envelopment analysis
Gang Cheng a, Panagiotis Zervopoulos b,⇑, Zhenhua Qian c,⇑
In this paper, we develop a variant of the traditional radial model whereby original values are replaced with absolute values as the basis to quantify the proportion of improvements to reach the frontier. The new radial measure is units invariant and can deal with all cases of the presence of negative data. In addition, the variant of the radial measure (VRM) preserves the property of proportionate improvement of a traditional radial model, and provides the exact same results in the cases that the traditional radial model can deal with. Examples show the advantages of the new approach.
英语教研活动主题发言稿(3篇)
第1篇Good morning/afternoon! It is my great honor to stand before you today to deliver a speech on the theme of "Enhancing English Language Teaching and Learning in Our School." As educators dedicated to the field of English language teaching, we are constantly striving to improve our skills, update our methodologies, and create a conducive learning environment for our students. Today, I would like to discuss some key areas where we can focus our efforts to enhance the quality of English language education in our school.IntroductionThe importance of English language proficiency in today's globalized world cannot be overstated. English has become the lingua franca in international communication, business, science, and technology. Therefore, it is our responsibility as educators to equip our students with the necessary skills to thrive in an increasingly interconnected world. To achieve this goal, we must be proactive in identifying areas of improvement and adopting innovative teaching strategies.1. Understanding the Needs of Our StudentsThe first step towards enhancing English language teaching and learning is to understand the diverse needs of our students. We must recognize that our students come from various linguistic backgrounds, with different learning styles and abilities. By conducting thorough needs assessments and individualized learning plans, we can tailor our teaching methods to cater to these unique requirements.- Linguistic Proficiency: We should assess the students' current level of English proficiency and identify areas where they need additional support. This could include grammar, vocabulary, listening, speaking, reading, and writing skills.- Learning Styles: We should be aware of the different learning styles present in our classrooms, such as visual, auditory, and kinesthetic learners. By incorporating a variety of teaching techniques, we can cater to these diverse needs and enhance engagement.- Cultural Sensitivity: It is essential to foster cultural sensitivity and awareness among our students. This can be achieved by incorporating culturally relevant materials and activities into our lessons.2. Updating Teaching MethodologiesTo keep up with the rapidly evolving field of English language teaching, we must continuously update our methodologies. The following strategies can help us achieve this goal:- Technology Integration: We should embrace technology as a tool to enhance our teaching. This could involve using educational apps, online resources, and multimedia materials to make our lessons more interactive and engaging.- Project-Based Learning: Project-based learning encourages students to apply their knowledge in real-world contexts. By working on group projects, students can develop critical thinking, problem-solving, and collaborative skills.- Flipped Classroom: The flipped classroom model allows students to watch instructional videos at home and spend class time on activities that promote deeper understanding and application of the content.3. Professional DevelopmentContinuous professional development is crucial for educators to stay abreast of the latest trends and best practices in English language teaching. The following activities can contribute to our growth:- Workshops and Seminars: Participating in workshops and seminars on topics such as curriculum development, assessment strategies, and classroom management can provide us with valuable insights and practical tools.- Peer Observation: Peer observation sessions allow us to learn from each other's strengths and identify areas for improvement. By providing constructive feedback, we can support each other in our professional growth.- Research: Engaging in educational research can help us understand the underlying principles of effective teaching and learning. By staying informed about the latest research findings, we can make evidence-based decisions in our classrooms.4. Creating a Supportive Learning EnvironmentA supportive learning environment is essential for students to feel confident and motivated to learn English. The following measures can help create such an environment:- Positive Attitudes: We should foster a positive attitude towards English language learning by encouraging students to embrace challenges and celebrate their progress.- Classroom Management: Effective classroom management strategies can help maintain a conducive learning atmosphere, where students feel safe and respected.- Parental Involvement: Encouraging parental involvement can help reinforce learning outside the classroom. Regular communication with parents can provide us with valuable feedback on students' progress and needs.ConclusionIn conclusion, enhancing English language teaching and learning in our school requires a multifaceted approach that addresses the diverse needs of our students, incorporates innovative teaching methodologies, promotes continuous professional development, and creates a supportive learning environment. By working together as a team and remaining committed to our shared goals, we can make significant strides in preparing our students for success in the global community.Thank you for your attention, and I look forward to engaging in a lively discussion on how we can further improve our English language programs. Let us continue to strive for excellence in teaching and learning, and together, we will make a positive impact on the lives of our students.Thank you.第2篇Good morning/afternoon! It is my great honor to stand before you today to share my thoughts on the theme of our English teaching and research activity: "Enhancing Student Engagement and Language Proficiency in the English Classroom."As educators, we are always striving to improve our teaching methods and strategies to ensure that our students receive the best possible education. The theme of today's activity resonates deeply with me, as it focuses on two crucial aspects of language learning: student engagement and language proficiency. In this speech, I will discuss the importance of these two aspects, explore some effective strategies to enhance them, and propose ways in which we can collaborate as a team to achieve our goals.Firstly, let us delve into the significance of student engagement. Engaged students are more likely to be motivated, participate activelyin class, and ultimately achieve better academic outcomes. When students are engaged, they are more likely to develop a genuine interest in the subject matter and cultivate a lifelong love for learning. On the other hand, disengaged students may feel disconnected from the learning process, leading to lower achievement and a negative impact on their overall well-being.To foster student engagement in the English classroom, we can employ several strategies:1. Interactive Learning Activities: Incorporate interactive activities such as role-plays, group discussions, and games that encourage students to actively participate in the learning process. These activities not only make the lessons more enjoyable but also help students to practice their language skills in a real-life context.2. Technology Integration: Utilize technology tools such as interactive whiteboards, educational apps, and online platforms to create an engaging and dynamic learning environment. Technology can providestudents with a variety of resources and opportunities for self-directed learning.3. Student-Centered Approaches: Shift the focus from teacher-centered to student-centered instruction. Encourage students to take ownership of their learning by setting goals, making decisions, and reflecting ontheir progress.4. Differentiated Instruction: Recognize that students have different learning styles, abilities, and interests. Adapt your teaching methodsto cater to these diverse needs, ensuring that all students feel valued and challenged.5. Authentic Resources: Incorporate authentic materials such as newspapers, podcasts, and videos into your lessons. This not only exposes students to real-world language use but also makes the learning experience more relevant and meaningful.Moving on to language proficiency, it is essential to understand that proficiency is not just about mastering grammatical rules and vocabulary; it is also about the ability to communicate effectively in real-life situations. Enhancing language proficiency requires a combination of targeted instruction and practical application.Here are some strategies to improve language proficiency in the English classroom:1. Speaking and Listening Practice: Allocate time in each lesson for speaking and listening activities. Encourage students to engage in conversations, presentations, and debates, which will help them to develop their oral skills.2. Writing Assignments: Assign writing tasks that require students to express their thoughts and ideas in written form. This will enhancetheir ability to organize their thoughts and use language accurately.3. Collaborative Projects: Encourage students to work on group projects that require them to communicate and collaborate effectively. This willnot only improve their language skills but also foster teamwork and critical thinking.4. Language Immersion: Create an immersive English-speaking environment in the classroom by encouraging students to speak English as much as possible. This can be achieved through activities such as English-only days or designated "English corners."5. Continuous Assessment: Implement a system of ongoing assessment that provides constructive feedback and allows students to track their progress. This will help them to identify their strengths and weaknesses and work towards improving their language proficiency.As educators, we have a collective responsibility to create a supportive and conducive learning environment that promotes both student engagement and language proficiency. To achieve this, we must collaborate and share our experiences, insights, and resources.Here are some ways in which we can work together as a team:1. Professional Development: Attend workshops, seminars, and conferences to stay updated on the latest trends and best practices in English language teaching.2. Peer Observation: Arrange for peer observation sessions where we can observe each other's teaching methods and provide constructive feedback.3. Resource Sharing: Create a shared resource bank where we can store and access teaching materials, activities, and assessments.4. Team Planning: Collaborate on lesson planning to ensure that our teaching strategies are aligned and support our students' learning goals.5. Continuous Communication: Maintain open lines of communication with our colleagues to share ideas, concerns, and successes.In conclusion, the theme of today's English teaching and research activity, "Enhancing Student Engagement and Language Proficiency in the English Classroom," is of paramount importance. By focusing on these two aspects and implementing the strategies discussed, we can create a moreengaging and effective learning environment for our students. Let us work together as a team, share our knowledge and experiences, and continue to evolve as educators, ultimately helping our students to achieve their full potential in English language learning.Thank you for your attention, and I look forward to a productive and insightful session ahead.Best regards,[Your Name]第3篇Good morning/afternoon! It is my great honor to stand before you today to deliver a speech on the theme of our English teaching and research activities. The topic of our discussion today is "Innovative Teaching Strategies for Enhancing English Language Acquisition in the 21st Century."As we all know, English has become a global lingua franca, and the demand for English proficiency is increasing in various fields, such as education, business, and technology. Therefore, it is our responsibility as educators to provide our students with the best possible English language education. In this regard, the aim of our教研活动 is toexplore innovative teaching strategies that can enhance English language acquisition in the 21st century.Firstly, let us discuss the importance of adopting innovative teaching strategies. In the past, traditional teaching methods focused on rote memorization and repetition, which often led to students being disengaged and uninterested in learning. However, with the rapid development of technology and globalization, students now have access to a vast array of information and resources. To keep up with this pace, we must embrace innovative teaching strategies that can stimulate students' curiosity, creativity, and critical thinking skills.One such strategy is the integration of technology in English language teaching. The use of digital tools and resources can greatly enhance thelearning experience for students. For instance, interactive whiteboards, educational apps, and online platforms can make lessons more dynamic and engaging. By incorporating these tools, teachers can create a more interactive and collaborative learning environment, where students can actively participate in the learning process.Another important strategy is the implementation of project-based learning (PBL). PBL encourages students to work on real-world problems and projects, which helps them develop critical thinking, problem-solving, and communication skills. In an English language classroom, PBL can be used to create scenarios where students can practice speaking, listening, reading, and writing in context. For example, students can work on a project about cultural exchange, where they research different countries, create presentations, and engage in discussions with their peers.Furthermore, the incorporation of authentic materials is essential for enhancing language acquisition. Authentic materials, such as newspapers, magazines, and videos, provide students with exposure to the natural use of language in real-life situations. By using these materials, teachers can help students understand the nuances of language and culture, which is crucial for effective communication.In addition to these strategies, it is important to consider the individual learning styles of students. Every student has a unique way of learning, and it is our duty as educators to cater to these differences. One way to achieve this is by incorporating diverse teaching methods, such as visual, auditory, and kinesthetic learning styles. By using a variety of teaching techniques, we can ensure thatall students are able to engage with the material and achieve their learning goals.Furthermore, the role of the teacher in fostering a positive learning environment cannot be overstated. Teachers should be role models for their students, demonstrating enthusiasm, patience, and a willingness to learn. By creating a supportive and inclusive classroom atmosphere, teachers can encourage students to take risks and express themselves freely.Now, let us delve into some specific innovative teaching strategies that we can implement in our English classrooms:1. Flipped Classroom: This approach involves students watching instructional videos or reading materials at home, and then coming to class to engage in activities, discussions, and projects. This allowsfor more hands-on learning and interaction in the classroom.2. Gamification: Incorporating game elements into language learning can be a fun and motivating way to engage students. This can be done through educational games, quizzes, and challenges that reward students fortheir achievements.3. Collaborative Learning: Pairing students with different abilities or assigning group projects can promote teamwork, communication, and mutual support. This approach also encourages students to learn from eachother's strengths and weaknesses.4. Peer Review: Encouraging students to review and provide feedback on each other's work can improve their writing and speaking skills, as well as their ability to evaluate and analyze language use.5. Socratic Seminars: This method involves students engaging in structured discussions, guided by a teacher, to explore complex ideas and concepts. It promotes critical thinking and deep understanding of the subject matter.In conclusion, as educators, we must continuously seek innovative teaching strategies to enhance English language acquisition in the 21st century. By embracing technology, implementing project-based learning, incorporating authentic materials, considering individual learning styles, and fostering a positive learning environment, we can provide our students with the tools and skills they need to succeed in an increasingly interconnected world.Let us work together to create a vibrant and dynamic English language classroom, where students are not just learners, but active participants in their own education. Thank you for your attention, and I look forwardto our continued collaboration and growth as a community of English language educators.Thank you.。
Hendrich跌倒风险评估量表对成年住院患者跌倒风险预测效度的Meta分析
.专科研究•Hendrich跌倒风险评估量表对成年住院患者跌倒风险预测效度的Meta分析*唐文，马梦宁，刘宇，刘佳琳，吕思漫，冯晓玉，倪翠萍(中国医科大学护理学院，辽宁沈阳,110122)［摘要］目的通过对诊断性研究进行Meta分析，评价Hendrich跌倒风险评估量表(Hendrich fall risk model,HFRM)预测住院患者跌倒风险的有效性。
方法系统检索中英文数据库(包括中国知网.PubMed.Web Of Science等10个数据库)，选择使用HFRM评估住院患者跌倒风险的诊断性研究。
由两名研究者共同检筛符合纳入与排除标准的文献，并进行资料提取，利用诊断性研究质量评价工具对纳入的文献进行质量评价。
使用Review Man5.3和Meta Disc1.4软件进行Meta分析。
结果最终纳入13篇文献，共238455例患者。
纳入的文献间存在阈值效应(r=0.775,P=0.002)o进行Meta回归，将文献按地区分为发展中国家组和发达国家组，发展中国家组的合并灵敏度、特异度、阳性似然比、阴性似然比、诊断比值比、AUC值、Q指数分别为0.73(95%C&0.66~0.79)、0.81(95%C/=0.80~0.83)、3.19(95%C&2.15~4.72)、0.34(95%C& 0.21-0.54).10.45(7.03~15.50)、0.83、0.77；发达国家组拟合SROC曲线，合并AUC值为0.716.Q指数为0.666o结论HFRM对于成年住院患者跌倒风险的评估具有较高的准确性。
［关键词］Hendrich跌倒风险评估量表；跌倒；成年住院患者；预测效度；Me塢分析［中图分类号］R47［文献标识码］A［文章编号］1671-8283(2021)*0044-08［DOI］10.3969/j.issn.1671-8283.2021.04.008 Predictive validity of Hendrich fall risk model for adult inpatients in risk of falling:a meta-analysis Tang Wen,Ma Mengning,Liu Yu,Liu Jialin,Lv Siman,Feng Xiaoyu,Ni Cuiping//Modem Clinical Nursing,-2021,20(4):44.(School of Nursing,China Medical University,Shenyang,110012,China)[Abstract]Objective To evaluate the effectiveness of the Hendrich Fall Risk Model(HFRM)by diagnostic accuracy study of meta-analysis,in predicting the risk of falling of inpatients.Methods Ten English and Chinese databases were systematically searched including CNKI,PubMed,Web Of Science,etc..Hendrich Fall Risk Model for assessment of the risk of falling among inpatients were selected in the study.The data were extracted from the acquired literatures by two researchers following the inclusion and exclusion criteria.Quality assessment of diagnostic accuracy studies-2(QUADAS-2)was applied to evaluate the quality of the included literatures.Review Man5.3and Meta Disc1.4software were used for meta-analysis.Results A total of13literatures were included, involving238,455patients.The threshold effect among the included literatures was r=0.745(P=0.013).The literatures were divided into a group of developing-country and a group of developed-country according to the results of meta-regression analysis.Of the group of developing-country,the pooled sensitivity,specificity,positive likelihood ratio,negative likelihood ratio,AUC value and Q index were 0.73(95%C/=0.66-0.79),0.81(95%CZ=0.80-0.83),3.19(95%CZ=2.15-4.72),0.34(95%CZ=0.21-0.54),10.45(7.03-15.50)0.83 and0.77,respectively.Of the group of developed-country,the AUC value and Q index were0.716and0.666,respectively.Conclusion［基金项目］*本课题为中国医科大学社科项目，项目编号为XRW20160001；中国医科大学护理学院基金项目，项目编号为2019HL-19o［收稿日期］2020-10-07［作者简介］唐文(1995-),女，四川江油人，硕士在读，主要从事老年护理、社区护理工作。
Undesirable outputs in efficiency valuations
Undesirable outputs in e ciency valuationsHolger ScheelOperations Research und Wirtschaftsinformatik,Universit a t Dortmund,D-44221Dortmund,GermanyReceived 5January 1999;accepted 28April 2000AbstractE ciency measurement is usually based on the assumption that inputs have to be minimized and outputs have to bemaximized.In a growing number of applications,however,undesirable outputs are incorporated into the production model which have to be minimized.In this paper various approaches for treating such outputs in the framework of Data Envelopment Analysis (DEA)are discussed and the resulting e cient frontiers are compared.New radial mea-sures are introduced which assume that any change of the output level will involve both undesirable and desirable outputs.Ó2001Elsevier Science B.V.All rights reserved.Keywords:Data envelopment analysis;Radial e ciency measurement;Undesirable outputs;Linear programming;Pollution1.IntroductionData Envelopment Analysis (DEA)as a non-parametric approach to e ciency measurement does not require any deeper knowledge of the production process of the ``decision making unit''(DMU)to be evaluated.For DEA e ciency val-uations it su ces to choose appropriate inputs and outputs and make some general assumptions about the technology structure concerning con-vexity,disposability and returns to scale.Classical DEA models,as described e.g.in Charnes et al.(1994),rely on the assumption that inputs have to be minimized and outputs have tobe maximized.However,it was mentioned already in the seminal work of Koopmans (1951)that the production process may also generate undesirable outputs like smoke pollution or waste.Motivated by public and governmental environment,ecolog-ical e ciency measurement has recently attracted much interest,cf.the recent literature review by Allen (1999).Undesirable outputs may as well appear in nonecological applications like health care (complications of medical operations)and business (tax payments),cf.Smith (1990).As noted by Allen (1999)a symmetric case of inputs which should be maximized may also occur.For example,the aim of a recycling process is to use maximal quantity of the ``input''waste.This case can be treated analogously whence we ignore it in the sequel for simplicity of presentation.European Journal of Operational Research 132(2001)400±410E-mail address:h.scheel@wiso.uni-dortmund.de (H.Scheel).0377-2217/01/$-see front matter Ó2001Elsevier Science B.V.All rights reserved.PII:S 0377-2217(00)00160-0Introducing the notation used in this paper,let X;Y denote the input output data matrix where each row represents one DMU and each column represents one input or output,respectively.Fol-lowing Banker et al.(1984)we assume that the technology set is estimated byT f x;y j k T X T x;k T Y P y;k P0;k T e 1g;1 where e 1;...;1 T in appropriate dimension. Notice that most of the results are mutatis mu-tandis valid for nonconvex technologies as well.A DMU k or a vector x k;y k is called(Pareto±Koopmans-)e cient if the technology set does not contain any dominating points,i.e.if there is no vector x H;y H P T such that x H T x k and y H P y k with at least one strict inequality.Clearly this is equiv-alent to a zero optimal value of the``additive DEA model''introduced by Charnes et al.(1985): minÀe T sÀÀe T s ;s:t:k T X sÀ x k;k T YÀs y k;k T e 1;k;s ;sÀP0:2The optimal value of this linear program is zero if and only if the optimal value of its dualmax q T y k wÀp T x k;s:t:Yq wÀXp T0;p;q P e;is zero.It follows that DMU k is e cient if and only if there is a positive weight vector p;q such thatq T y kÀp T x k P q T y`Àp T x` 3 for every observed DMU`.This inequality pro-vides an elegant price interpretation of e ciency which is used later.Indeed,DMU k is e cient with respect to T if and only if there exists a price system such that DMU k gains maximal pro®t compared to all observed DMUs;see also Banker and Maindiratta(1998).The paper is organized as follows.In Section2 several approaches for incorporating undesirable outputs in DEA models are compared.In partic-ular,we shall®gure out the connections between the resulting classi®cations of DMUs as e cient or ine cient,and discuss corresponding e ciency measures.In Section3these existing measures are complemented by a new concept which takes into account that changes of the output level will in-volve both desirable and undesirable outputs. Section4illustrates this concept by means of an empirical example.Section5concludes.2.Incorporating undesirable outputs in DEA2.1.E ciency classi®cationsIn the literature several approaches for incor-porating undesirable outputs in DEA are proposed. We may classify them as indirect and direct ap-proaches.Indirect approaches transform the values of the undesirable outputs by a monotone decreas-ing function f such that the transformed data can be included as``normal''(desirable)outputs in the technology set T(since after retransformation in-creasing these values means decreasing the unde-sirable outputs).In contrast,direct approaches use the original output data but modify the assumptions about the structure of the technology set in order to treat the undesirable outputs appropriately. Notice that up to this point we have not made any assumptions about the sign of the data.In the sequel,however,we assume X P0.Moreover,let U P0denote the matrix of undesirable output data where each row represents one DMU and each column one undesirable output.Analogously V P0denotes the matrix of desirable output data. We assume that X,U and V do not contain any vanishing rows or columns.In the presence of undesirable outputs DMU k is e cient if there is no vector x H;u H;v H in the technology set such that x H T x k,u H T u k and v H P v k with at least one strict inequality.An indirect way of incorporating undesirable outputs is based on a transformation which we call the additive inverse,i.e.incorporating the undesirable outputs U as desirable outputs withH.Scheel/European Journal of Operational Research132(2001)400±410401values f U ÀU.This approach which we refer to as[ADD]was suggested by Koopmans(1951) and applied,e.g.by Berg et al.(1992).It generates the same technology set as incorporating undesir-able outputs U as inputs(referred to as[INP]);the only di erence is the sign of the undesirable out-puts.The classi®cation of DMUs as e cient or ine cient is thus the same for both approaches [ADD]and[INP].Notice that by using approach [INP]one abstracts from the underlying input±output structure which is usually de®ned by the nature of the production process.Instead,the only information needed is whether the data have to be minimized or maximized,whence approach[INP] allows the application of elegant goal program-ming models,cf.Liu and Sharp(1999).The classi®cation resulting from[ADD]and [INP]is preserved if the values of undesirable outputs are translated in the sense of Ali and Seliford(1990).This approach[TR b]means add-ing to the additive inverse of the undesirable out-put i a su ciently large scalar b i such that the resulting output values f k i U Àu k i b i are pos-itive for each DMU k.The well-known translation invariance of the e ciency classi®cation with re-spect to the translation vector b(cf.Pastor,1996) can easily be derived from(3).Another frequently used data transformation is the multiplicative inverse[MLT]suggested by Go-lany and Roll(1989)and applied,e.g.by Lovell et al.(1995)or Athanassopoulos and Thanassoulis (1995).By this approach each undesirable output is incorporated as desirable output using the val-ues f k i U 1=u k i.Surprisingly,there is the fol-lowing relation between this approach and the three equivalent approaches[ADD],[INP]and [TR b]:If a DMU is e cient using[MLT],then it is e cient as well when,e.g.[ADD]is used to in-corporate the undesirable outputs.In fact,assuming without loss of generality that there is only one undesirable output which may be scaled such that u k 1,e ciency of DMU k using [MLT]means in view of(3)that there exists a positive weight vector p;q such that the inequality1 q T v kÀp T x k P 1u`q T v`Àp T x`holds for every DMU`.Hence,we have À1 q T v kÀp T x k PÀ21u`q T v`Àp T x`PÀu` q T v`Àp T x`;where the latter inequality follows from the non-negativity of the term1=u` 1Àu` 2.In view of(3) we conclude that DMU k is e cient using ap-proach[ADD]as well.Notice that the reverse implication is not true in general as can be illustrated by the following ex-ample.Consider three DMUs with one input equal to one and two outputs given byU;V101017203030@1A; 4where the®rst output is undesirable.It is illustrated in Fig.1that DMU2is ine cient using[MLT]but e cient using[ADD].[MLT]can thus be viewed as a more``restrictive''approach than[ADD]and its equivalents,since it is more di cult to become ef-®cient under[MLT]than under[ADD]. Whereas the indirect approaches assume that the transformed data have their own meaning (consider for example the undesirable output ``mortality rate''and its translated additive inverse ``survival rate''),the direct approach uses the original output data assuming that it is impossible to reduce undesirable outputs without reducing desirable outputs at the same time.Recall that outputs are called strongly disposable if x;y P T implies that x;y H P T for every y H T y and weakly disposable if x;y P T implies that x;l y P T for 0T l<1.The direct approach suggested by F a re et al.(1989)replaces strong disposability of out-puts by the assumption that outputs are weakly disposable while only the subvector of desirable outputs is strongly disposable.The resulting vari-able returns to scale technology set under weakly disposable outputs[WD]is given byT WD f x;u;v j k T X T x;lk T U u;lk T V P v;k P0;k T e 1;0T l T1g: 5 Weak disposability requires that a proportional reduction of desirable and undesirable outputs is globally possible.However,if l becomes very402H.Scheel/European Journal of Operational Research132(2001)400±410small it may be impossible in some applications to reduce the undesirable outputs further since a minimal threshold value may be necessary to produce any desirable paring T WD with the technology set T ADD resulting from ap-proach [ADD],it turns out that approach [ADD]imposes less disposability assumptions about the technology structure than [WD]and may be viewed thus as a more pessimistic estimator of the ``true''production possibility set.In fact,due to their negative sign,the strongly disposable outputs in T ADD are not necessarily weakly disposable,since the strong disposability has to be interpreted in the input sense,i.e.,it is possible to produce more undesirable outputs without cost.Fig.2shows the e cient frontier of [WD]constructed by the example data (4).Comparing this frontier with Fig.1it turns out that in general the [WD]frontier di ers from the [ADD]and [MLT]frontier.However,any DMU which is ef-®cient in T WD is e cient in T ADD as well.In fact,suppose that x ;Àu ;v is dominated by ^x;À^u ;^v P T ADD with corresponding ^k de®ned in (1),thenthe vector ^x;^k T U ;^v is contained in T WD setting l 1,whence x ;u ;v is dominated in T WD as well.Table 1displays the approaches for incorpo-rating undesirable outputs we have discussed.The connections between these approaches which have been proved in this section are summarized in the following theorem.Theorem 1.Let E à denote the set of DMUs which appear efficient when undesirable outputs are incorporated by approach à .For arbitrary data and for every translation vector b the following in-clusions hold :E WDE MLT9=;E ADD E TR b E INP :2.2.E ciency measuresFor our study of e ciency measures we focus on the technology set T de®ned in (1)which can be interpreted as a pessimistic convex estimator of the production possibility set.Frequently used nonparametric e ciency measures in the DEA literature are the additive measure which isde®nedFig.1.E cient frontier using approach (a)[MLT]and (b)[ADD].H.Scheel /European Journal of Operational Research 132(2001)400±410403as the optimal value of program(2),and radial measures based on the work of Farrell(1957).It follows immediately from(2)that additive measures are independent from the location of the technology set relative to the origin,whence the e ciency score is the same using any of the ap-proaches[ADD],[TR b]or[INP]for incorporating the undesirable outputs.Hence,if the optimal value of the additive model(2)has a satisfactory economical interpretation it may be used as an e ciency measure in the presence of undesirable outputs.It will turn out to be less sensitive to the chosen approach of incorporating undesirable outputs into the model than radial measures which we shall now discuss in detail.The classical radial e ciency measure is de®ned as the optimal value of the linear programh k y max/s:t:k T X T x k;k T Y P/y k;k T e 1;k P0;6also known as``output oriented BCC model''in-troduced by Banker et al.(1984).Notice that a score larger than one of an in-e cient DMU indicates the proportional increase in outputs that is necessary to become e cient. Thus using approach[TR b]an increase of the whole output vector means simultaneously in-creasing the desirable and reducing the undesir-able outputs.Moreover,the e ciency scores resulting from[TR b]can be manipulated by the choice of b.In fact,it was noted by Ali and Seliford(1990) that while E TR b remains constant for every b the radial e ciency score may change.Interpreting the optimal value of(6)as a function of the translation vector b,i.e.for each DMU`the output vector y`is replaced by y` b,we can make a more precise assertion about this change.Proposition1.If b P^b then h k y b T h k y ^b .More-over,if b>^b and h k y b >1then h k y b <h k y ^b . Proof.Let k;/ be the optimal solution of(6)for the translation vector b,i.e.for every output j the inequalityX`k` y`j b jX`k`y`j b j P/ y k j b jholds.This inequality holds clearly for every ^bjT b j as well,whence the optimal value h k y ^b cannot be smaller than/.Moreover,if^b exceeds b in each component we haveP`k`y`j ^b j> / y k j ^b j for every j which implies the second assertion.ÃIt can be analogously shown that given any su ciently small number/>1there is a transla-tion vector b such that DMU k achieves an e -ciency score of/.Notice that even the order of the DMUs with respect to the BCC score may change under translation as illustrated by the following example.Example1.Consider three DMUs with one input equal to one for each DMU and two outputs, where the original outputs are given byY30201010125@1ATable1Approaches for incorporating undesirable outputsApproach Transformation De®nition of technology set [ADD]f k i U Àu k i T ADD :(1)with Y f U ;V TR b f k i U Àu k i b i T TR b :(1)with Y f U ;V [INP]±T INP :(1)with X X;U [MLT]f k i U 1=u k i T MLT :(1)with Y f U ;V [WD]±T WD :(5)404H.Scheel/European Journal of Operational Research132(2001)400±410and the translation vector b 10;0 .We have h2 2:0<h3 2:5while with translated outputs h2 2:0>h3 1:8holds.We conclude from this example and Proposi-tion1that the output oriented BCC score after translation of outputs is not very meaningful ex-cept for translations which yield an output that is meaningful in itself.The remaining e ciency measures in the pres-ence of undesirable outputs are thus based on approaches[ADD]or[INP].While we shall dis-cuss[ADD]in the following section,the latter was applied,e.g.by Tyteca(1997).He suggested to use the following measure which is oriented to unde-sirable outputsg k u min f h j x k;h u k;v k P T INP g: 7 Notice that this measure does not assume that a simultaneous improvement of both undesirable and desirable outputs is possible.However,it still separates these output categories since it assumes that undesirable outputs can be minimized holding the desirable outputs constant.3.Nonsepar ating e ciencymeasur esIn this section we propose e ciency measures which take into account that decreasing undesir-able outputs will decrease desirable outputs as well,i.e.they do not separate between those out-put categories.Hence,they are closely connected to the idea of weak disposability.It should be emphasized,however,that it is not necessary to assume weak disposability for the technology set. On the technology set T ADD the measures can be de®ned as natural extensions to the Farrell(1957) measure in the presence of undesirable outputs.De®nition1.We call/min min f/j x;/y P T ADD g the min-e ciency and/max max f/j x;/y P T ADD g the max-e ciency of a vector x;y P T ADD ,respectively.We call x;y min-ef-®cient if/min 1and max-e cient if/max 1. x;y is called universally e cient if x;y is both max-and min-e cient.The min-e ciency is oriented to the undesirable outputs.It yields the amount of radial reduction of undesirable outputs which is su cient to become (radially)e cient,taking into account that the de-sirable outputs will decrease as well.Symmetrically, max-e ciency is oriented to the desirable outputs. In Fig.1(b)DMU1is min-e cient,DMU3is max-e cient,and DMU2is universally e cient. These e ciency concepts can be interpreted similarly to the concept``most productive scale size''introduced by Banker(1984).An universally e cient DMU has reached a``balanced''position where radial improvements of desirable or unde-sirable outputs are impossible.In contrast,a DMU which is only min-e cient could increase its desirable outputs radially.Although then the un-desirable outputs increase as well,the proportions of this increase could be smaller than for the de-sirable outputs,i.e.,there exist positive scalars 1<b<a such that x k;b u k;a v k P T ADD .Sym-metrically,a max-e cient DMU can reduce its undesirable outputs by a larger factor than it has to decrease the desirable outputs.Hence,without any additional information one may prefer universally e cient DMUs since the ratio of desirable to undesirable outputs cannot be improved further.However,if it is known that small undesirable(large desirable)outputs are more``important''for the decision maker,then one may prefer min-e cient(max-e cient)DMUs. In the DEA literature usually nonnegativity of input output data is assumed.In order to construct e ciency measures on T ADD where the undesir-able outputs are incorporated as outputs negative in sign,it is necessary to study®rst some technical properties of the linear programs used for com-putation,i.e.program(6)for/k max and program min/;s:t:k T X T x k;k T Y P/y k;k T e 1;k P0;8for/k min which di ers from program(6)only in the objective function.The following results need no assumptions about the sign of the data.H.Scheel/European Journal of Operational Research132(2001)400±410405Lemma1./k max P1.Proof.Setting k k 1and k j 0for j k we conclude that/ 1is a feasible solution,whence /k max P1.ÃThe following lemma gives a necessary and su cient condition for bounded optimal values.Lemma2./k max is bounded if and only if DMU k produces at least one output in positive quantity.Proof.To prove the``if''part,let y k i be thepositive output quantity of DMU k.Note that b max f k T y i j k T e 1;k P0g is®nite,since k is bounded.If/is feasible for(6),then b P k T y i P/y k i,and we conclude that/T b=y k i<I.The ``only if''is obtained if we set k k 1and k j 0 for every j k.Then,/k max is unbounded if y k T0.ÃThe above lemma may explain why in the ex-ample presented in Pastor(1996)an unbounded optimal value occurs.However,the condition which ensures®nite optimal values holds whenever there is one desirable output.The following results for program(8)can be proved analogously to Lemmas1and2.Lemma3./k min T1.Lemma4./k min is bounded if and only if DMU k has one output negative in sign.Recall that if the data are positive then radial e ciency measures satisfy some important prop-erties which justify the term``e ciency measure'', cf.Russell(1987).Indication of weak e ciency(WI):The score is equal to one if and only if DMU k is weakly e -cient,i.e.there is no vector x H;u H;v H in the tech-nology set such that x H<x k,u H<u k and v H>v k or, equivalently,there are nonnegative weights p 0 and q 0such that(3)holds.Homogeneity(H):If the output data Àu k;v k of an ine cient DMU k are replaced by c Àu k;v k P T,then the e ciency score h k of DMU k is altered to cÀ1h k.Weak monotony(WM):If the data of DMU k are replaced by data that are dominated by DMU k then e ciency does not increase.The scores/k max and/k min cannot directly be interpreted as an e ciency measure as can be seen from Fig.3.In fact,proportional increases in outputs are possible for DMU1,i.e./1max>1 although DMU1is e cient,and proportional decreases are possible for the e cient DMU5.In order to prepare the next theorem which provides a connection between/k min,/k max and(weak)e -ciency we introduce a regularity property of the input output data which is adopted from Charnes et al.(1996).De®nition2(Stability).DMU k is called stable if either there do not exist nonnegative weight vec-tors p 0and q 0satisfying inequality(3)for every`,or there exist such vectors satisfying each inequality` k strictly.Consequently for an instable DMU k there are weights satisfying(3)which means that it is (weakly)e cient.However,there exist DMUs ` k where(3)is satis®ed by equality,whence a small perturbation of the data can render DMU k ine cient,i.e.,stability means that the status``ef-®cient''or``ine cient''of a DMU is preserved under small data perturbations.Fig.3shows the outputs of seven DMUs as-suming they have identical inputs.The undesirable output is incorporated by approach[ADD].Ob-viously every weight vector satisfying(3)for DMU k 3yields equality in(3)for DMUs` 2;4.ItFig.3.Instable data.406H.Scheel/European Journal of Operational Research132(2001)400±410follows that DMU3is not stable.In fact,it can be seen from the®gure that any arbitrary small de-crease of outputs would render this DMU ine -cient.Notice,however,that this situation is very un-likely for empirical data.It can be shown that every DMU is stable for``almost every''data matrix X;Y in a generic sense,i.e.,stability is preserved under small data perturbations and,if there are some instable DMUs,then an arbitrary small perturbation of the data matrix su ces to render them stable.In fact,if for DMU k there are nonnegative weights p 0and q 0such that inequality(3) holds strictly for every DMU` k,then this in-equality remains valid if the data are slightly per-turbed.Moreover,if(3)cannot be satis®ed strictly for some DMUs then an arbitrary small decrease of their outputs will render these DMUs ine cient whence they become stable.We conclude that stability is a very mild assumption on the data which will be satis®ed for``almost every''data matrix.Moreover,although it may be not neces-sary,it can be easily checked by solving the linear program(2)with an interior point method,using, e.g.the``EMS''DEA software,cf.Scheel(1998). Such methods yield weights satisfying(3)strictly for every DMU` k,provided such weights exist.Theorem2.If/k max 1or/k min 1,then DMU k is weakly efficient.Moreover,if DMU k is stable,then the reverse implication holds as well.Proof.Let/k max 1and suppose that DMU k is not weakly e cient.Then there is a point x H;y H P T such that x H<x k and y H>y k.De®ne / min f y H i=y k i j y k i>0g.Note that in view of Lemma2the minimum exists,and since y H>y k it follows/>1.Furthermore,/y k T y H,whence x k;/y k P T,a contradiction.If/k min 1,de®ne/ max f y H i=y k i j y k i<0g and the assertion follows analogously.To prove the reverse direction of the theorem, suppose that DMU k is weakly e cient and stable. (This implies that DMU k is Pareto±Koopmans-e cient.)Since inequality(3)is satis®ed strictly for nonnegative weight vectors p 0and q 0,this inequality remains valid if q is slightly perturbed such that q T y k 0.De®ne x: q T y kÀp T x k,then q T y kÀxÀp T x k 0;q T y`ÀxÀp T x`T0for each DMU`9hold.Now let l;m;f q T y k À1 p;q;x .Let us ®rst consider the case q T y k>0.It follows from(9) thatm T y kÀfÀl T x k 0;m T y`ÀfÀl T x`T0for each DMU`10hold with m T y k 1.In view of these equations the optimal value of the linear programmax f1ÀfÀl T x k j m T y k 1;Y mÀf eÀX l T0; l;m P0g 11 is0.If we replace the objective function of this linear program by f l T x k and``max''by``min'', then the optimal value is equal to1.Since(6)is the dual of this modi®ed linear program it follows /k max 1.Now we come to the case q T y k<0.Then,the ``T''in(10)must be replaced by``P''.Starting with the programmin f1ÀfÀl T x k j m T y k 1;Y mÀf eÀX l P0; Àl;Àm P0ginstead of(11)it follows analogously to the argu-mentation above that/k min 1.ÃNotice that stability is su cient but not neces-sary to the reverse implication of the theorem. Indeed,in Fig.3we have/5max 1although the e cient DMU5is not stable.Using this result we can de®ne the nonsepa-rating e ciency measures oriented to undesirable and desirable outputsg k uv/k min if/k max>1;1else;(h k uv/k max if/k min<1;1else:(It is easy to see that under the stability assumption both scores are e ciency measures,i.e.they satisfyH.Scheel/European Journal of Operational Research132(2001)400±410407properties(IW),(WM)and(H).Indication of weak e ciency(IW)follows directly from the theorem above.Homogeneity(H)is implied by the de®nition of/k min and/k max,respectively.To see that h k uv satis®es weak monotony(WM)let y k P^y k and /;k be an optimal solution of(6)corre-sponding to y k.Then /;k is feasible for(6)cor-responding to^y k as well,i.e.the e ciency score oriented to the desirable outputs cannot decrease which means that e ciency cannot increase. Analogously it can be shown that replacing the outputs of DMU k by a smaller vector the e -ciency score oriented to the undesirable outputs g k uv may decrease only which again means that e -ciency may only decrease.We conclude that h k uv and g k uv may well be interpreted as e ciency mea-sures.Fig.4illustrates the e ciency measure g k uv and the measure g k u de®ned in(7).Both measures are oriented to undesirable outputs.Notice that in contrast to g k u the e ciency measure g k uv yields a projection onto the e cient frontier which does not dominate x k;y k in every output.Since the measure does not separate desirable and undesir-able outputs,the projection dominates only the subvector of undesirable outputs.Analogously the nonseparating measure h k uv oriented to desirable outputs yields a projection which dominates x k;y k only in the subvector of desirable outputs. Moreover,it follows from the de®nitions thatg k uv T g k u;h k uv P h k v: 12These inequalities show that separating measures may overestimate the e ciency of DMUs which cannot simultaneously improve both desirable and undesirable outputs.4.An illustrative exampleTo complete the paper we apply the e ciency concept of the last section to selected European economies.The number of employees as single input and the gross domestic product(GDP)as desirable output are complemented by the unde-sirable output NO x emissions.The data displayed in Table2are adopted from Statistisches Bunde-samt(1997).Notice that in the short run it is hard to increase the GDP without simultaneously in-creasing the undesirable output,which is also in-dicated by a high correlation between the desirable and undesirable output of95%.Results for radial e ciency measures which are oriented to the undesirable output are displayed in Table3.For each measure the e ciency score and the position in the ranking based on these scores are ing the nonseparating e ciency measure it turns out that DMUs D and SF achieved a max-e ciency value of/k max 1 whence for the corresponding e ciency measure g k uv 1holds.For these DMUs the min-e ciency values/k min which di er from g k uv are thus displayed in brackets.The other columns contain the e ciency scores and rank numbers obtained when the undesirable output was incorporated as an input.It turnsout Fig.4.E ciency measures oriented to undesirable outputs.Table2Data of illustrative exampleDMU Employees GDP(DM)NO x(1000t)B3793385.776D357823457.4612DK2601248.261E12027802.4151F220572204294GB259361579.3456GR3821163.833I199431560.9295IRL126292.224NL6782566.9116P441714424S4134330.978SF2016179.254408H.Scheel/European Journal of Operational Research132(2001)400±410。
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Applied Economics Letters,2006,13,569–574Club convergence inEuropean regionsRita De Siano a and Marcella D’Uva b,*a Department of Economic Studies,University of Naples‘Parthenope’,Via Medina40,80133Naples,Italyb Department of Social Sciences,University of Naples L’Orientale,Largo S.Giovanni Maggiore30,80134Naples,ItalyThis study investigates the‘club convergence’hypothesis applying the stochastic notion of convergence to groups of European regions.In order to avoid the group selection bias problem,the innovative regression tree technique was applied to select endogenously the most important variables in achieving the best identification of groups on the base of per capita income and productive specialization.Tests on stochastic convergence in each group evidences a strong convergence among the wealthiest regions of the European Union and a trend of weak convergence among the remaining groups,confirming Baumol’s hypothesis of convergence.I.IntroductionOver the past decade many authors have explored the evolution of output discrepancies,at both national and regional levels.In particular,starting with Baumol(1986)it has been widely hypothesized that convergence may hold not for all economies but within groups of them showing similar characteristics (Azariadis and Drazen,1990).This evidence is referred to as the‘club convergence’hypothesis which implies that a set of economies may converge with each other,in the sense that in the long run they tend towards a common steady state position, but there is no convergence across different sets. In seeking to test the club convergence hypothesis (Qing Li,1999;Feve and Le Pen,2000;Su,2003,for example)two main questions arise:(a)which frame-work of convergence to use,and(b)how to identify the economies belonging to each club.Initially,a cross-section notion of convergence was used in order to verify the existence of a negative relationship between initial per capita income and its growth rate. In contrast with this notion a stochastic definition of convergence(Carlino and Mills,1993)was proposed and explored by using time series analyses. According to this framework there is stochastic convergence if per capita income disparities between economies follow a stationary process.Bernard and Durlauf(1996)found that when economies show multiple long run equilibria,cross-sectional tests tend to spuriously reject the null hypothesis of no convergence and,as a consequence,represent a weaker notion of convergence than that of the time series.As regards the second point,two methods can be used in order to create different groups of economies.The first sorts of economies follows some a priori criteria(initial level of GDP,education, technology,capital accumulation,etc.)while the second follows an endogenous selection method (Durlauf and Johnson,1995).Finally,the switching regression with the contribution of additional infor-mation on the sample separation followed by Feve and Le Pen(2000)can be mentioned as an intermediate method in modelling convergence clubs. This study investigates the‘club convergence’hypothesis applying the stochastic notion of conver-gence to groups of European regions sorted accord-ing to their initial levels of per capita income and*Corresponding author.E-mail:mduva@unior.itApplied Economics Letters ISSN1350–4851print/ISSN1466–4291onlineß2006Taylor&Francis569/journalsDOI:10.1080/13504850600733473productive specialization(De Siano and D’Uva, 2004,2005)through the application of an innovative methodology known as Classification and Regression Tree Analysis(CART).Unlike other partitioning methods,CART allows a regression to be performed together with a classification analysis on the same ‘learning’dataset,without requiring particular speci-fication of the functional form for the predictor variables which are selected endogenously.The importance of similarities in the initial productive specialization has been highlighted by several theore-tical contributions(Jacobs,1969;Marshall,1980; Romer,1986;Lucas,1988;Helg et al.,1995;Bru lhart, 1998;Ottaviano and Puga,1998)which found that it can be crucial in determining both the nature and size of responses to external shocks.The paper is organized as follows:Section II introduces the methodology of the empirical analysis, Section III displays the dataset,Section IV shows the results of econometric analysis and Section V concludes.II.MethodologyThe empirical analysis is carried out in two parts:first regions are grouped through the classification and regression tree analyses(CART),then convergence is tested within‘clubs’using the time series analysis. CART methodology(Breiman et al.,1984)provides binary recursive partitioning using non-parametric approaches in order to construct homogeneous groups of regions using splitting variables which minimize the intra-group‘impurity’as predictors. The final outcome is a tree with branches and ‘terminal nodes’,as homogeneous as possible,where the average value of the node represents the predicted value of the dependent variable.In this analysis the regression is carried out through the least squares method using the regional GDP growth rate as dependent variable and initial GDP and specializa-tion indexes as explicative variables.In the second part of the study Carlino and Mills(1993)notion of stochastic convergence is applied in each group identified by CART methodology.It follows that if the logarithm of a region’s per capita income relative to the group’s average does not contain a unit root,the region converges.The model(Ben-David, 1994;Qing Li,1999)is the following:y j i,t ¼ iþ i tþ’y i,tÀ1þ"i,tð1Þwhere y j i,t is the log of region i per capita income inyear t,j is the region’s group and"is white noise errorwith0mean.Summing Equation1over j for eachgroup and dividing the outcome by the number ofregions within the group,the following equation isobtained:"y t¼" þ" tþ’"y tÀ1þ"tð2Þwhere"y t is the group’s average per capita incomein year t(the group superscript is suppressed).Subtracting Equation2from Equation1one has:RI i,t¼AþBtþ’RI i,tÀ1þ"tð3Þwhere RI i,t is the logarithm of region i per capitaincome relative to the group’s average at time t(y j i,tÀ"y t).For each region of the sample we apply theAugmented Dickey–Fuller(ADF)test(Dickey andFuller,1979)using the ADF regression ofEquation3:ÁRI t¼ þ tþ RI tÀ1þX kj¼1c jÁRI tÀjþ"tð4ÞAt this point,considering the low power of the ADFtest in the case of short time series,we run alsothe Kwiatkowski et al.(1992)test(KPSS)for trendstationarity.The null hypothesis of the KPSS test isthe trend stationarity against the unit root alter-native.If the KPSS statistic is larger than the criticalvalues the null hypothesis is rejected.The combinedanalysis of KPSS and ADF tests results leads on thefollowing possibilities(Qing Li,1999):.rejection by ADF tests and failure to reject byKPSS!strong convergence;.failure to reject by both ADF and KPSS!weakconvergence;.rejection by KPSS test and failure to rejectADF!no convergence;.rejection by both ADF and KPSS tests invitesto perform further analyses.III.Data DescriptionThis section presents the dataset used both to groupthe sample regions and to run the econometricanalysis.Data for GDP and employment are fromthe Eurostat New Cronos Regio database at NUTS2level.1Annual values for GDP per inhabitant in termsof Purchasing Power Parity(PPP)and the number of1According to EC Regulation No.1059/2003.570R.De Siano and M.D’Uvaemployees in the NACE92productive branches from1981to 2000are used.The sample consists of 123regions belonging to nine countries:11Belgian,8Dutch,29German,222French,20Italian,18Spanish,5Portuguese,2Greek,38British.4For each region (i )the following initial productivespecialization indexes (SP)were built for all theconsidered branches 5(j ):SP ij ¼E ij P n j ¼1ij P m i ¼1E ij P n j ¼1P mi ¼1ijð5Þwhere E indicates the number of employees.IV.Empirical ResultsThe main purpose of the study is to test the ‘clubconvergence’hypothesis across the European regions.In particular,the study aims to investigate whethera region’s per capita income converges to the averageof the group to which it belongs.In order to avoidthe group selection bias problem,the regressiontree technique was applied to select endogenouslythe most important variables in achieving thebest identification of groups (De Siano and D’Uva,2005).If the majority of regions in a groupconverges,the group may be considered a conver-gence ‘club’.The CART method allowed a tree to be built withfour terminal nodes including regions showing a morehomogeneous behaviour of per capita GDP growthrate and productive specialization.Results of CARTanalysis together with the stochastic convergence tests for each group are presented in what follows.The first group consists of 11regions (from Spain,Greece and Portugal)characterized by:the highest estimated mean value of GDP growth rate (126.08%)despite the lowest initial income level (average equal to 4144.3);strong specialization in the agriculture sector (the highest and equal to 3.75),construction branch (2.09)and food and beverages compartment (1.93);the minimum specialization in chemical,energy,and machinery branches and the highest in food-beverages-tobacco,mineral and construction.More than 80%of these regions display ‘weak’convergence while remaining regions show ‘strong’convergence (Table 1).The second group includes 23regions (mainly from Belgium,Spain,Italy and the United Kingdom)characterized by:an average GDP growth rate equal to 111.36%and the second highest initial income level (5788.78);strong specialization in agriculture (2.68)sector,food and beverage (1.26),construction (1.52)and energy (1.20)compartments;the highest specialization in chemical products (0.98);the second highest level of specialization in agricul-ture construction and energy.Almost all these regions present ‘weak’convergence (Table 2).The third group is formed by 21regions from Belgium,France,Germany,the Netherlands,Spain,the UK and Italy (only Abruzzo)characterized by:an estimate for the GDP growth rate of 106%and an average initial level of income equal to 6920.6;main specializations in manufacturing (1.03),mineral products (1.13),construction (1.22),food and beverage (1.45)and energy (1.21);the highest 2The analysis starts from 1984due to the lack of data in the respective regional labour statistics.3During the period 1983–1987there has been a different aggregation of Greek regions at NUTS2level.Kriti and Thessalia are the only regions which presents data for the period 1984–2000.4The geographic units for UK are at NUTS1level of Eurostat classification because of the lack of data for NUTS2units.5Agricultural-forestry and fishery,manufacturing,fuel and power products,non-metallic minerals and minerals,food-beverages-tobacco,textiles-clothing-leather and footwear,chemical products,metal products,machinery-equipment and electrical goods,various industries,building and construction,transport and communication,credit and insurance services.Table 1.Convergence test results of group 1Regions group 1ADF statistics KPSS statistics l ¼4Regions group 1ADF statistics KPSS statistics l ¼4Castilla-la ManchaÀ2.9780.099gr 43Kriti À4.05ÃÃ0.080ExtremaduraÀ3.320.097Pt11Norte À4.03ÃÃ0.126AndaluciaÀ2.630.094Pt12Centro (P)À2.290.123Ceuta y MelillaÀ1.770.123Pt14Alentejo À2.770.104CanariasÀ1.940.121Pt15Algarve À2.010.086ThessaliaÀ1.760.137Notes :ÃÃdenote statistical significance using unit root critical values at the 5%(À3.645).Club convergence in European regions571specialization in energy and manufacturing branches.Except for Abruzzo and Noord Brabant,which donot converge,all the other regions ‘weakly’convergeto the group’s average (Table 3).The fourth group contains 68regions (almost allGerman,French and Italian (North-Centre)andsome Belgian and Dutch)characterized by thelowest estimation of the GDP growth rate (97.8%),despite their highest initial GDP level (8893.9);thehighest specialization in the branches of the servicessector (1.16and 1.07,respectively)and in machinery(1.01);the lowest specialization in agriculture,foodand beverages,textile and construction activities.These regions present the highest percentage of‘strong’convergence to the group’s average (morethan 60%,Table 4).Table 5presents the summary of convergence testsresults (percentage are in parentheses).The main outcome of this study is the evidence of strong convergence among the wealthiest regions of the European Union.Besides,it appears that there is a trend of weak convergence also among the remaining groups (percentages are considerably over 80%).Therefore,Baumol’s hypothesis of conver-gence within clubs showing similar characteristics is confirmed.V.Conclusion This study tests the ‘club convergence’hypothesis applying the stochastic notion of convergence to groups of European regions.In order to avoid the group selection bias problem,the innovative regression tree technique was applied to selectTable 3.Convergence test results of group 3Regions group 3ADF statistics KPSS statistics l ¼4Regions group 3ADF statistics KPSS statistics l ¼4LimburgÀ1.680.116Abruzzo 2.600.153ÃÃHainautÀ0.800.091Friesland À3.620.142NamurÀ1.840.094Noord-Brabant À2.590.148ÃÃNiederbayernÀ1.270.104Limburg (NL)À2.980.128OberpfalzÀ1.400.097Yorkshire and The Humber À1.610.085TrierÀ1.430.119East Midlands À2.190.091Comunidad Foral de NavarraÀ2.750.071West Midlands À1.920.080La RiojaÀ1.770.119East Anglia À2.150.134BalearesÀ2.960.108South West À1.950.091LimousinÀ2.410.083Scotland 2.220.093Languedoc-RoussillonÀ3.390.105Notes :ÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146).Table 2.Convergence test results of group 2Regions group 2ADF statistics KPSS statistics l ¼4Regions group 2ADF statistics KPSS statistics l ¼4Vlaams BrabantÀ1.220.100Murcia À1.530.124Brabant WallonÀ1.600.111Molise À2.170.078Luxembourg1.190.122Campania À3.220.078Lu neburgÀ0.280.114Puglia À2.820.115GaliciaÀ1.690.140Basilicata À2.100.140Principado de AsturiasÀ1.550.146ÃÃCalabria À5.07ÃÃÃ0.106CantabriaÀ1.080.133Sicilia À2.980.142Aragon À1.580.142Sardegna À2.210.141Comunidad de MadridÀ1.380.091Lisboa e Vale do Tejo À2.620.141Castilla y Leon À2.580.138Wales À2.120.098Cataluna À1.550.097Northern Ireland À1.790.120Comunidad Valenciana À1.420.105Notes :ÃÃand ÃÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146)and 1%level (0.216)respectively,using unit root critical values at the 5%(À3.645)and 1%(À4.469).572R.De Siano and M.D’Uvaendogenously the most important variables inachieving the best identification of groups.Testson stochastic convergence in each group identifiedby CART evidence strong convergence among thewealthiest regions of the European Union and atrend of weak convergence among the remaininggroups.References Azariadis,C.and Drazen,A.(1990)Threshold externalities in economic development,Quarterly Journal of Economics ,105,501–26.Baumol,W.J.(1986)Productivity growth,convergence and welfare:what the long run data show,AmericanEconomic Review ,76,1072–85.Table 5.Convergence test resultsGroupsNo.of regions Strong convergence Weak convergence No convergence 1112(18,19)9(81,81)2231(4.35)21(91.3)1(4.35)32119(90.48)2(9.52)46843(63.23)20(29.41)4(5.88)Table 4.Convergence test results of group 4Regions group 4ADF statistics KPSS statistics l ¼4Regions group 4ADF statistics KPSS statistics l ¼4RegionBruxelles capitale À2.650.112Haute-Normandie À4.11ÃÃ0.102AntwerpenÀ2.770.102Centre (FR)À5.13ÃÃÃ0.099Oost-VlaanderenÀ3.150.078Basse-Normandie À3.86ÃÃ0.101West-VlaanderenÀ3.030.097Bourgogne À5.03ÃÃÃ0.113Licge À3.060.089Nord-Pas-de-Calais À4.37ÃÃ0.130StuttgartÀ4.22ÃÃ0.123Lorraine À4.41ÃÃ0.139KarlsruheÀ4.51ÃÃÃ0.088Alsace À4.13ÃÃ0.094FreiburgÀ5.11ÃÃÃ0.092Franche-Comte À5.20ÃÃÃ0.145Tu bingenÀ4.94ÃÃÃ0.104Pays de la Loire À4.34ÃÃ0.116OberbayernÀ4.17ÃÃ0.094Bretagne À4.41ÃÃ0.124MittelfrankenÀ3.79ÃÃ0.089Poitou-Charentes À4.74ÃÃÃ0.102UnterfrankenÀ0.420.140Aquitaine À3.290.104SchwabenÀ4.11ÃÃ0.084Midi-Pyre ne es À5.48ÃÃÃ0.103BremenÀ3.76ÃÃ0.121Rho ne-Alpes À4.93ÃÃÃ0.104HamburgÀ3.350.097Auvergne À4.43ÃÃ0.135DarmstadtÀ3.150.125Provence-Alpes-Co te d’Azur À5.10ÃÃÃ0.109GießenÀ3.020.088Corse À2.560.166ÃÃKasselÀ3.0120.094Piemonte À3.460.112BraunschweigÀ3.82ÃÃ0.116Valle d’Aosta À4.36ÃÃ0.080HannoverÀ3.96ÃÃ0.083Liguria À4.26ÃÃ0.117Weser-EmsÀ3.400.084Lombardia À4.04ÃÃ0.101Du sseldorfÀ3.94ÃÃ0.097Trentino-Alto Adige À3.84ÃÃ0.109Ko lnÀ3.96ÃÃ0.084Veneto À3.68ÃÃ0.106Mu nsterÀ4.04ÃÃ0.087Friuli-Venezia Giulia À4.20ÃÃ0.116DetmoldÀ4.06ÃÃ0.099Emilia-Romagna À3.120.136ArnsbergÀ3.98ÃÃ0.096Toscana À3.190.121KoblenzÀ3.88ÃÃ0.113Umbria À3.560.146ÃÃRheinhessen-PfalzÀ4.18ÃÃ0.107Marche À3.250.136SaarlandÀ4.35ÃÃ0.090Lazio À3.96ÃÃ0.098Schleswig-HolsteinÀ3.360.089Drenthe À1.850.134Pais VascoÀ3.630.159ÃÃUtrecht À2.400.155ÃÃI le de FranceÀ4.61ÃÃÃ0.110Noord-Holland À1.990.137Champagne ArdenneÀ3.79ÃÃ0.157ÃÃZuid-Holland À2.200.138Picardie À4.44ÃÃ0.142Zeeland À3.78ÃÃ0.093Notes :ÃÃand ÃÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146)and 1%level (0.216)respectively,using unit root critical values at the 5%(À3.645)and 1%(‘4.469).Club convergence in European regions573Ben-David, D.(1994)Convergence clubs and diverging economies,unpublished manuscript,University of Houston,Ben-Gurion University and CEPR. Bernard, A. B.and Durlauf,S.N.(1996)Interpreting tests of the convergence hypothesis,Journal of Econometrics,71,161–73.Breiman,L.,Friedman,J.L.,Olshen,R.A.and Stone,C.J.,(1984)Classification and Regression Trees,Wadsworth,Belmont,CA.Bru lhart,M.(1998)Economic geography,industrial location and trade:the evidence,World Economy,21, 775–801.Carlino,G.A.and Mills,L.O.(1993)Are US regional incomes converging?A time series analysis,Journal of Monetary Economics,32,335–46.De Siano,R.and D’Uva,M.(2004)Specializzazione e crescita:un’applicazione alle regioni dell’Unione Monetaria Europea,Rivista Internazionale di Scienze Sociali,4,381–98.De Siano,R.and D’Uva,M.(2005)Regional growth in Europe:an analysis through CART methodology, Studi Economici,87,115–28.Dickey,D.A.and Fuller,W.A.(1979)Distribution of the estimators for autoregressive time series with a unit root,Journal of The American Statistical Association, 74,427–31.Durlauf,S.N.and Johnson,P.A.(1995)Multiple regimes and cross-country growth behaviour,Journal of Applied Econometrics,10,365–84.Feve,P.and Le Pen,Y.(2000)On modelling convergence clubs,Applied Economic Letters,7,311–14.Helg,R.,Manasse,P.,Monacelli,T.and Rovelli,R.(1995) How much(a)symmetry in Europe?Evidence from industrial sectors,European Economic Review,39, 1017–41.Jacobs,J.(1969)The Economy of Cities,Jonathen Cape, London.Kwiatkowski, D.,Phillips,P. C. B.,Schmidt,P.and Shin,Y.(1992)Testing the null hypothesis of stationarity against the alternative of a unit root:how sure are we that economic time series have a unit root?,Journal of Econometrics,54, 159–78.Lucas,R. E.(1988)On the mechanics of economic development,Journal of Monetary Economics,22, 3–42.Marshall,A.(1980)Principles of Economics,Macmillan, London.Ottaviano,I.and Puga,D.(1998)Agglomeration in the global economy:a survey of the‘new economic geography’,World Economy,21,707–31.Qing,L.(1999)Convergence clubs:some further evidence, Review of International Economics,7,59–67. Romer,P.M.(1986)Increasing returns and long run growth,Journal of Political Economy,94, 1002–37.Su,J.J.(2003)Convergence clubs among15OECD countries,Applied Economic Letters,10,113–18.574R.De Siano and M.D’Uva。
DEFINITION
DEFINITIONDEA♦ DEA is a non-parametric approach based on mathematical program for estimatingproductive units ’ performance.♦ The efficiency frontiers of DEA are constructed through the envelopment of thedecision-making units (DMUs): from data in a sample including inputs and outputs of different DMUs.♦ Each DMU is assigned a single efficiency score, hence allowing ranking among the DMUs in asample.♦ In diagram, for banks efficiency measurement, each point represents a bank. Point on thefrontier represents an efficient bank. Points below the frontier represent banks which are inefficient. The distance to the frontier is the efficiency measure.♦ DEA take into consideration of ‘return to scale ’ in calculating efficiency. This allows forincreasing or decreasing efficiency based on size and output level.SFA♦ SFA is a regression approach that specifies a function for cost and profit or production inorder to determine the frontier.♦ And it typically includes a normally distributed error and an inefficiency componentassumed to follow cost frontier functions.♦ SFA is a widely used approach to obtain technical efficiency that is defined as the ratio ofobserved output to maximum feasible output.♦ SFA deals with stochastic noise through decomposing the error term.Basic cost function()it it it u w ,y f C += take logarithms ()()it it it it it u ln w ,y C ln C ln +=then it i it v ln x ln u ln +=As shown above, where the component InV it is assumed to be symmetrically distributed around a zero mean but lnX i is assumed to be non-negative. Therefore, lnX i represents the deviations above the minimum cost frontier (X-inefficiency) associated with either technical inefficiency or allocative inefficiency.♦SFA also accounts for data noise such as data errors and omitted variables.Frontier approach♦Frontier efficiency approach is an objective quantitative measure which is independent with effect of other exogenous factors, such as market prices, by exploiting an econometric method to control for the effects.♦Non-frontier efficiency, on the contrary, is influenced by input and output prices, firm sizes and other exogenous factors, which prevent the ratios from reaching closer estimates of the managers’ true performance.♦There are several frontier approaches that have been developed to ①determine 'scale efficiency' and 'x-efficiency' of banks, ② obtaining an insight into optimal size of banks and the allocation of resources by managers.♦They are parametric econometric approach --Stochastic Frontier Approach (SFA) and Distribution-free Approach (DFA), and non-parametric linear approach --Data Envelopment Analysis (DEA). These approaches differ in the existence of the error term, efficient frontier, separation inefficiency from random errors and etc.Technical efficiency♦Technical efficiency is the effectiveness with which a given set of inputs is used to produce an output. A firm is said to be technically efficient if a firm is producing the maximum output from the minimum quantity of inputs, such as labor, capital and technology.♦According to Farrell (1957), total economic efficiency (EF) can be decomposed as technical efficiency (TE) and allocative efficiency (AE).♦AE measures the effectiveness that resources are allocated in such a way that consumer are most satisfied.♦ A measure of technical efficiency under the assumption of constant returns-to-scale (CRS) is known as a measure overall technical efficiency (OTE).♦technical efficiency of the bank is its ability to transform multiple resources into multiple financial services.CRS♦ A production function exhibits constant returns to scale if changing all inputs by a positive proportional factor has the effect of increasing outputs by that factor.♦ A bank is scale efficient if it operates at constant returns-to-scale (CRS).♦CRS DEA model also known as CCR model- A measure of technical efficiency under the assumption of constant returns-to-scale (CRS) is known as overall technical efficiency (OTE).-The OTE measure helps to determine inefficiency due to the input/output configuration as well as the size of operations.-Model: for each DMU we would like to obtain a measure of ratio of all outputs over all inputs, such as u’yi/v’xi’Note: u is an M*1 vector of output weights; v is a K*1 vector of input weights.In order to select the optimal weight, we specify:VRS♦VRS means an increase in inputs does not result in a proportional change in the outputs.♦ a model which allows variable returns to scale (VRS) in DEA is BCC (developed by Banker, Charnes and Cooper (1984)).♦estimating the efficient frontier under the assumption of variable returns-to-scale gives PTE. ♦It is a measure of technical efficiency without scale efficiency and purely reflects the managerial performance to organize the inputs in the production process. Thus, PTE measure has been used as an index to capture managerial performance.♦This approach forms a frontier which envelope the data points more tightly than the CRS frontier and thus provides technical efficiency scores which are greater than or equal to those obtained using the CRS model.PTE♦In DEA, the OTE can be decomposed into two mutually exclusive and non-additive components: pure technical efficiency (PTE) and scale efficiency (SE).♦This decomposition allows an insight into the source of inefficiencies.♦The PTE measure is obtained by estimating the efficient frontier under the assumption of VRS. It is a measure of TE devoid of these SE effects, and purely reflects the managerial performance to organize the inputs in the production process.♦Thus, PTE measure has been used as an index to capture managerial performance.SE♦In DEA, the OTE can be decomposed into two mutually exclusive and non-additive components: pure technical efficiency (PTE) and scale efficiency (SE).♦The ratio of OTE to PTE provides SE measure.♦The measure of SE provides the ability of the management to choose the optimum size of resources, i.e., to decide on the bank’s size or in other words, to choose the scale of production that will attain the expected production level.♦Inappropriate size of a bank (too large or too small) may sometimes be a cause of technical inefficiency.decreasing returns-to-scale/ increasing returns to scale♦The measure of SE provides the ability of the management to choose the optimum size of resources, i.e., to deci de on the bank’s size♦scale inefficiency and takes two forms: decreasing returns-to-scale (DRS) and increasing returns-to-scale (IRS).♦Decreasing returns-to-scale (also known as diseconomies of scale) implies that a bank istoo large to take full advantage of scale and has supra-optimum scale size.♦ a bank experiencing increasing returns-to-scale (also known as economies of scale) is too small for its scale of operations and, thus, operates at sub-optimum scale size.♦ A bank is scale efficient if it operates at constant returns-to-scale (CRS).。
英语教学实践法(3篇)
第1篇In the rapidly evolving field of education, the traditional methods of teaching English have been supplemented and sometimes replaced by innovative approaches that leverage technology and emphasize student-centered learning. This article outlines a comprehensive English teaching practice method that integrates technology and student-centered learning to enhance the learning experience for students.I. IntroductionThe English language is a global lingua franca, and the ability to communicate effectively in English is essential in today's interconnected world. However, teaching English effectively requires more than just imparting grammatical rules and vocabulary; it involves engaging students in meaningful activities that foster language acquisition and critical thinking skills. This teaching practice method aims to achieve these goals by incorporating the following key components:1. Technology integration2. Student-centered learning3. Interactive and collaborative activities4. Continuous assessment and feedbackII. Technology IntegrationThe integration of technology in English teaching can provide numerous benefits, including increased engagement, personalized learning, and access to a wealth of resources. Here are some ways to integrate technology into English teaching:1. Interactive Whiteboards and Projectors: Use interactive whiteboards and projectors to display lessons, videos, and other multimedia content. This allows for dynamic and interactive lessons that keep students engaged.2. Educational Software and Apps: Utilize educational software and apps that cater to different learning styles and levels of proficiency. Examples include language learning apps like Duolingo, grammar and vocabulary practice software, and online dictionaries.3. Online Learning Platforms: Create or use existing online learning platforms that provide structured lessons, quizzes, and assignments. These platforms can also facilitate communication and collaboration among students and teachers.4. Social Media and Communication Tools: Encourage students to usesocial media and communication tools like WhatsApp or Slack for language practice, group projects, and peer feedback.5. Virtual Reality (VR) and Augmented Reality (AR): Explore the use of VR and AR to create immersive language learning experiences. For example, students can practice English by interacting with virtual environmentsor by overlaying English language content onto real-world objects.III. Student-Centered LearningStudent-centered learning shifts the focus from the teacher to the student, allowing learners to take an active role in their education. Here are some strategies to implement student-centered learning in English classes:1. Project-Based Learning: Assign projects that require students to research, plan, and present information. This encourages students to use English in real-life contexts and fosters critical thinking and problem-solving skills.2. Flipped Classroom: Use the flipped classroom model, where students watch instructional videos or complete readings at home and use class time for activities and discussions. This allows for more personalized learning and more time for interactive tasks.3. Group Work and Peer Collaboration: Divide students into groups and assign them tasks that require collaboration. This promotes communication skills, teamwork, and mutual support among students.4. Reflective Learning: Encourage students to reflect on their learning experiences through journal entries, discussion, or presentations. This helps students to internalize their learning and set personal goals.5. Choice and Autonomy: Give students a choice in their learning activities, such as selecting topics for presentations or projects, or deciding on the type of assessment they prefer. This empowers students and increases their motivation.IV. Interactive and Collaborative ActivitiesInteractive and collaborative activities are essential for creating a dynamic and engaging learning environment. Here are some examples:1. Role-Playing and Simulations: Use role-playing activities to simulate real-life situations and encourage students to practice English conversationally. Simulations can also be used to teach grammar and vocabulary in context.2. Game-Based Learning: Incorporate educational games and activitiesthat are both fun and effective in teaching English. Examples include word searches, crosswords, and language puzzles.3. Discussion and Debate: Organize class discussions and debates on topics of interest to the students. This helps students to develop their critical thinking and public speaking skills.4. Language Labs: Utilize language labs where students can practice listening, speaking, and pronunciation in a controlled environment.V. Continuous Assessment and FeedbackContinuous assessment and feedback are crucial for monitoring student progress and providing timely guidance. Here are some strategies for effective assessment and feedback:1. Formative Assessment: Use formative assessments, such as quizzes, class discussions, and peer reviews, to gauge student understanding and provide immediate feedback.2. Summative Assessment: Administer summative assessments, such as exams and presentations, to evaluate student learning at the end of a unit or course.3. Self-Assessment and Peer Assessment: Encourage students to assess their own work and provide feedback to their peers. This promotes metacognition and collaborative learning.4. Constructive Feedback: Provide specific, constructive feedback that focuses on strengths and areas for improvement. Feedback should be supportive and encourage students to take ownership of their learning.VI. ConclusionIncorporating technology and student-centered learning into English teaching can significantly enhance the learning experience for students. By leveraging technology, promoting student-centered approaches, engaging students in interactive activities, and providing continuous assessment and feedback, teachers can create a dynamic and effective learning environment that prepares students for success in the globalized world.第2篇Introduction:The field of English language teaching (ELT) is constantly evolving, with new methodologies and techniques being introduced to enhance the learning experience. This paper proposes an effective methodology for English teaching practice that combines various teaching strategies and techniques to cater to the diverse needs of learners. The methodology focuses on student-centered learning, interactive activities, and the integration of technology, ensuring that students not only acquire language skills but also develop critical thinking and cultural awareness.I. Student-Centered Learning1. Needs Analysis:Before implementing any teaching methodology, it is essential to conduct a needs analysis to understand the specific requirements and goals of the students. This involves assessing their current level of English proficiency, identifying their strengths and weaknesses, and determining their learning objectives.2. Personalized Learning Plans:Based on the needs analysis, develop personalized learning plans for each student. These plans should outline the learning goals, activities, and resources tailored to meet the individual needs of each student.3. Active Participation:Encourage active participation in the classroom by involving students in discussions, group activities, and role-plays. This approach promotes engagement, motivation, and a deeper understanding of the language.II. Interactive Activities1. Pair and Group Work:Utilize pair and group work to enhance communication skills and collaboration. Assign tasks that require students to work together, such as role-plays, debates, and problem-solving activities. This fosters teamwork and encourages students to share their thoughts and ideas.2. Games and Simulations:Integrate games and simulations into the teaching process to make learning more enjoyable and memorable. Games such as "Pictionary," "Jeopardy," and "Simon Says" can help reinforce vocabulary, grammar, and pronunciation skills.3. Project-Based Learning:Implement project-based learning activities that require students to research, plan, and present information. This approach promotes critical thinking, research skills, and the application of language in real-life situations.III. Technology Integration1. Online Resources:Utilize online resources such as educational websites, e-books, and interactive learning platforms to provide additional support andpractice opportunities for students. These resources can be accessed both inside and outside the classroom, allowing for flexible and self-paced learning.2. Digital Tools:Incorporate digital tools such as presentation software, video conferencing, and collaborative platforms to facilitate communication and collaboration. These tools can enhance the learning experience by providing interactive and engaging activities.3. Mobile Learning:Encourage mobile learning by developing mobile apps and websites that offer language practice exercises and interactive lessons. This allows students to learn anytime, anywhere, using their smartphones or tablets.IV. Assessment and Feedback1. Formative and Summative Assessment:Implement a balanced assessment strategy that includes both formative and summative assessments. Formative assessments, such as quizzes, class discussions, and peer evaluations, provide ongoing feedback to students and teachers. Summative assessments, such as exams and projects, measure the overall progress and achievement of the students.2. Constructive Feedback:Provide constructive feedback to students, focusing on their strengths and areas for improvement. Feedback should be specific, actionable, and encouraging, helping students to identify their learning goals and develop their skills.3. Self-assessment and Reflection:Encourage students to engage in self-assessment and reflection bysetting personal learning goals and evaluating their progress. This promotes metacognition and helps students become more aware of their learning process.Conclusion:This effective methodology for English language teaching practice combines student-centered learning, interactive activities, and technology integration to create a dynamic and engaging learning environment. By focusing on the needs of the students, promoting active participation, and utilizing innovative teaching techniques, this methodology aims to equip learners with the necessary language skills, critical thinking abilities, and cultural awareness to succeed in the globalized world.第3篇摘要：随着我国英语教育的不断发展，传统的英语教学模式已无法满足新时代对英语教学的需求。
英语组教研活动组长总结(3篇)
第1篇As the leader of the English Group Teaching and Research Activity, I am pleased to present a comprehensive summary of our recent endeavors. This summary aims to reflect on the goals achieved, challenges faced, and future directions for our group. The following report outlines the key aspects of our activities over the past few months.I. IntroductionThe English Group Teaching and Research Activity was initiated with the aim of enhancing the quality of English language teaching and research within our institution. The group consists of dedicated English language teachers, researchers, and enthusiasts who are committed to fostering a collaborative and supportive environment for professional development. Our activities encompass a range of topics, including curriculum development, pedagogical approaches, assessment strategies, and research projects.II. Objectives and Achievements1. Professional Development WorkshopsOur group organized a series of professional development workshops to equip teachers with the latest pedagogical techniques and research findings. These workshops covered topics such as flipped classrooms, project-based learning, and the use of technology in English language teaching. The participants expressed a high level of satisfaction with the workshops, and several teachers have already implemented the new strategies in their classrooms.2. Curriculum DevelopmentThe group collaborated to review and update the English curriculum, ensuring that it aligns with the latest educational standards and meets the needs of our students. We conducted a thorough analysis of the current curriculum and identified areas for improvement. As a result, we have developed a more comprehensive and engaging curriculum that incorporates a variety of teaching methods and resources.3. Pedagogical ApproachesOur group engaged in discussions and research to explore innovative pedagogical approaches that can enhance student learning. We shared best practices and case studies, which led to the adoption of new teaching techniques such as peer teaching, cooperative learning, and the integration of authentic materials into our lessons. These approaches have been positively received by both teachers and students.4. Assessment StrategiesThe group focused on improving assessment strategies to ensure that they effectively measure student learning outcomes. We conducted a review of our current assessment methods and identified areas for improvement. We introduced new assessment tools, such as formative assessments and portfolios, to provide a more holistic view of student progress. These changes have been well-received by teachers and students alike.5. Research ProjectsOur group initiated several research projects aimed at exploring various aspects of English language teaching and learning. These projects included studies on the effectiveness of technology in language learning, the impact of feedback on student performance, and the role of cultural competence in English language education. The findings from these research projects will be presented at upcoming conferences andpublished in academic journals.III. Challenges and Solutions1. Time ConstraintsOne of the main challenges faced by the group was the limited time available for planning and executing our activities. To address this, we established a clear schedule and assigned specific responsibilities to each member, ensuring that tasks were completed efficiently and on time.2. Resource AllocationAccess to resources, such as technology and educational materials, was another challenge. We worked closely with the administration to secure additional resources and sought external funding for research projects. Furthermore, we utilized open-source materials and collaborative platforms to maximize the availability of resources.3. Engagement and MotivationEnsuring that all members of the group remained engaged and motivated was crucial. We organized regular meetings and activities to maintain momentum and encourage participation. Additionally, we recognized and rewarded contributions to the group's success, fostering a sense of belonging and achievement.IV. Future Directions1. Continuous Professional DevelopmentWe plan to continue organizing workshops and seminars to support the ongoing professional development of our teachers. These activities will focus on emerging trends in English language teaching and research.2. Curriculum EnhancementOur group will continue to review and update the English curriculum, ensuring that it remains relevant and effective. We will also explore opportunities for interdisciplinary collaboration to enrich our curriculum.3. Research and PublicationWe aim to expand our research initiatives and encourage more teachers to engage in research activities. The findings from these projects will be shared with the academic community through presentations, publications, and conferences.4. Collaboration with Other InstitutionsWe plan to establish partnerships with other educational institutions to exchange ideas, resources, and best practices. This collaboration willenhance our group's reach and contribute to the broader English language teaching community.V. ConclusionAs the leader of the English Group Teaching and Research Activity, I am proud of the achievements we have made over the past few months. The dedication and commitment of our group members have led to significant improvements in English language teaching and research within our institution. By addressing challenges and focusing on future directions, we are confident that our group will continue to make a positive impact on the quality of English language education. Together, we will strive to create an environment that fosters innovation, collaboration, and excellence in English language teaching and research.第2篇Date: [Date of the Meeting]Location: [Meeting Venue]Attendees: [List of Attendees]Chairperson: [Name of the Group Leader]Minutes Taker: [Name of the Secretary]---I. IntroductionThe English Department Research and Teaching Group meeting was held on [Date of the Meeting] at [Meeting Venue]. The meeting aimed to discuss recent developments in the field of English education, share innovative teaching methods, and address any challenges faced by the department. The meeting was attended by [number] members of the English Department, including teachers, researchers, and administrative staff.II. Welcome and Opening RemarksThe meeting was officially opened by the chairperson, [Name of the Group Leader], who welcomed all attendees and expressed gratitude for theirparticipation. He highlighted the importance of continuous professional development and the exchange of ideas within the department to enhance the quality of education provided.III. Review of Previous Meeting MinutesThe minutes of the previous meeting were reviewed and approved by the group. The chairperson emphasized the importance of adhering to the agreed-upon action points and reminded everyone of the progress made since the last meeting.IV. Reports from Sub-committeesA. Curriculum Development Sub-committee:- The chairperson of the Curriculum Development Sub-committee, [Name], presented a comprehensive report on the progress made in revising the English curriculum. The new curriculum focuses on integrating technology, fostering critical thinking, and enhancing student engagement.- The group discussed the implementation plan and the training required for teachers to effectively utilize the new resources. It was decided that a pilot program would be initiated in the upcoming term to gather feedback and make necessary adjustments.B. Technology Integration Sub-committee:- The chairperson of the Technology Integration Sub-committee, [Name], reported on the initiatives taken to incorporate technology into the teaching process. This includes the introduction of an online learning platform, the development of interactive digital resources, and the training of teachers on how to use these tools effectively.- The group acknowledged the positive impact of technology on student learning and agreed to continue exploring new ways to enhance the learning experience.C. Teacher Development Sub-committee:- The chairperson of the Teacher Development Sub-committee, [Name], shared insights on the professional development opportunities availableto teachers. This includes workshops, seminars, and conferences focused on pedagogical innovation and best practices.- The group discussed the importance of ongoing training and the need to encourage teachers to participate in these opportunities. A schedule of upcoming events was distributed to all members.V. Main Agenda: Discussion on Student PerformanceA. Analysis of Student Performance:- The group engaged in a detailed discussion on the recent student performance data, highlighting areas of strength and areas requiring improvement.- It was noted that while the overall performance was satisfactory, there were concerns regarding the proficiency in writing and critical thinking skills.B. Proposed Solutions:- The group proposed several strategies to address the identified issues, including:1. Implementing a dedicated writing workshop program.2. Integrating critical thinking exercises into the curriculum.3. Providing additional support to struggling students through tutoring and mentoring programs.VI. Feedback and SuggestionsSeveral members shared their feedback and suggestions, which were well-received by the group. Key points included:- The need for more regular feedback sessions with students to understand their challenges better.- The importance of creating a supportive and inclusive learning environment.- The suggestion to organize inter-school English competitions to motivate students and enhance their language skills.VII. AdjournmentThe meeting concluded with a vote of thanks to the chairperson and all attendees for their active participation. The chairperson reminded everyone to stay committed to the goals of the department and to work collaboratively towards achieving them.VIII. Next MeetingThe next English Department Research and Teaching Group meeting is scheduled for [Date of the Next Meeting] at [Meeting Venue]. The agenda for the next meeting includes a follow-up on the implementation of the proposed solutions and a review of the pilot program results.---End of SummaryThis summary provides a comprehensive overview of the English Department Research and Teaching Group meeting, capturing the discussions, decisions, and action points. It serves as a reference for all members and stakeholders involved in the continuous improvement of English education within our department.第3篇Introduction:As the leader of the English group teaching and research activity, it is my pleasure to present a summary of our recent activities. The aim of our group is to enhance the quality of English language education,foster collaboration among teachers, and promote continuous professional development. This summary will highlight the key activities, outcomes, and reflections of our group’s endeavors.I. Overview of Activities1. Introduction of the ActivityOur group’s recent teaching and research activity focused on the theme of "Innovative Teaching Methods in English Language Education." The activity aimed to explore new approaches and strategies that could be implemented in our classrooms to make learning more engaging and effective.2. Participation and CollaborationThe activity was attended by a diverse group of English teachers, including both experienced professionals and beginners. The collaborative nature of the event encouraged sharing of ideas, experiences, and best practices.II. Key Activities and Outcomes1. Workshops and SeminarsWe organized a series of workshops and seminars that covered various topics, such as project-based learning, flipped classrooms, and technology integration in English language teaching. The sessions were conducted by experts in the field, and participants actively engaged in discussions and practical activities.Outcome: Teachers gained a deeper understanding of innovative teaching methods and were equipped with practical tools to implement these strategies in their classrooms.2. Peer Observations and FeedbackTo promote continuous improvement, we implemented a peer observation system where teachers observed each other’s lessons and provided constructive feedback. This process facilitated reflection and allowed teachers to learn from one another’s strengths and areas for improvement.Outcome: Teachers received valuable insights into their teaching practices and were motivated to make positive changes in their classrooms.3. Resource SharingOur group established a platform for sharing resources, including lesson plans, activities, and materials. This enabled teachers to access a wide range of resources and adapt them to suit their specific needs.Outcome: Teachers had access to a wealth of resources that enrichedtheir teaching and facilitated a more dynamic learning environment.4. Research PresentationsSeveral teachers presented their research findings on effective teaching strategies and methods. This allowed the group to stay updated on the latest research in English language education and apply relevantfindings to their practice.Outcome: Teachers were exposed to new research and were encouraged to conduct their own research to contribute to the field.III. Reflections1. Collaboration and NetworkingThe activity highlighted the importance of collaboration and networking among teachers. By working together, we were able to share our knowledge, experiences, and resources, leading to a more supportive andprofessional environment.2. Continuous Professional DevelopmentThe event emphasized the need for continuous professional development in the field of English language education. Teachers recognized the importance of staying updated with the latest trends, research, and teaching methods.3. Student EngagementThe innovative teaching methods explored during the activity were designed to enhance student engagement. Teachers reported positive changes in their students’ motivation and performance, indicating that these strategies are effective in promoting learning.IV. ConclusionThe English group teaching and research activity was a resounding success, as evidenced by the positive feedback and outcomes. The event provided a valuable opportunity for teachers to learn from one another, explore new teaching methods, and enhance their professional growth.Looking forward, we will continue to organize similar activities to foster a culture of collaboration, innovation, and continuous improvement in English language education. Our group remains committed to supporting teachers in their quest to provide the best possible learning experiences for their students.In closing, I would like to express my gratitude to all the participants for their active involvement and dedication. Their contributions have made this event a memorable and rewarding experience for everyone involved. Let us continue to work together to improve the quality of English language education and inspire our students to achieve theirfull potential.Thank you.。
primary research and secondary research
primary research and secondary research Primary research and secondary research are two different approaches used in the research process.Primary research involves collecting data directly from sources, such as through experiments, surveys, interviews, or observations. This type of research is often used to answer specific questions or test hypotheses, and the data collected is considered to be original and firsthand.Secondary research, on the other hand, involves analyzing existing data that has already been collected by others. This can include published research papers, government reports, industry statistics, and online databases. Secondary research is often used to gain a better understanding of a particular topic or to identify gaps in existing knowledge.Both primary and secondary research have their advantages and disadvantages. Primary research allows researchers to collect their own data and answer specific questions, but it can be time-consuming and expensive. Secondary research is less time-consuming and cheaper, but the data may not be as specific or up-to-date as primary research.primary research and secondary research are both important tools in the research process and can be used together to gain a more comprehensive understanding of a particular topic.。
dea方法处理非平衡面板数据
dea方法处理非平衡面板数据Imbalanced panel data is a common issue in social science research, where the number of observations for different groups or entities varies significantly. This can occur due to various reasons such as missing data, attrition, or unequal sample sizes. Dealing with imbalanced panel data requires careful consideration and methodological approaches to ensure accurate and reliable results.非平衡面板数据在社会科学研究中是一个常见问题，不同组或实体的观察数量会显著变化。
这可能是由于数据缺失、减少或样本大小不均等等原因造成的。
处理非平衡面板数据需要认真考虑和方法论方法，以确保准确可靠的结果。
One commonly used method for dealing with imbalanced panel data is the fixed effects model, which helps account for unobserved heterogeneity at the entity level. By including fixed effects for each entity in the panel, this model can control for individual-specific characteristics that may impact the outcome variables. However, a limitation of the fixed effects model is that it assumes time-invariant effects for each entity, which may not always hold true in practice.处理非平衡面板数据的一种常用方法是固定效应模型，它有助于解释实体层面的未观察到的异质性。
数据包络分析的应用拓展及与主成分分析的相关性研究
中文摘要数据包络分析（ＤａｔａＥｎｖｅｌｏｐｍｅｎｔＡｎａｌｙｓｉｓ，简称ＤＥＡ）是著名运筹学家Ａ＋Ｃｈａｍｅｓ和Ｗ．Ｗ．Ｃｏｏｐｅｒ等学者以“相对效率评价”穰念为基础发展越来的一种新的行之有效的系统分析方法。
自１９７８年第一个ＤＥＡ模型—Ｃ２Ｒ模型（也称ＣＣＲ模黧）建立黻来，奢关豹理论研究不断深入，应弱领域日盏广泛。
本文的工作就是数据包络分析的皮用拓展及与主成分分析的相关性研究。
本文的工作分为两大部分。
酋兔本文阐述了ＤＥＡ方法静基本溪论和英藤本模登—ｅ２Ｒ模型，作为探讨ＤＥＡ方法在其它领域中运用的一种尝试，并基于化工试验中反应物、生成耱之阍豹投入、产毒关系，溪ＤＥＡ方法评价了芷交试验设诗得鑫静结果，找出实验的适宜操作条件。
实例分析表明，ＤＥＡ方法用于化工试验设计，具有诗算篱擎，意义渍楚豹将熹，是辩正交试验懿誊簸静充。
笾努，ＤＥＡ方法除了用于判断一组ＤＭＵｓ中有效和无效单元这个基本的用法之外，最避ＤＥＡ方法作灸了ＤＭＵｓ接黟戆一静蒸本模型。
ＪｏｅＺｈｕ在稳熬文章孛提出魄较圭残分分爨（ｐｒｉｎｃｉｐａｌｃｏｍｐｏｎｅｎｔａｎａｌｙｓｉｓ，简记ＰＣＡ）和ＤＥＡ方法用于具有多输入和多输爨戆ＤＭＵｓ搀序，共璺瓣于在｛｜熟豹文章审艨考惑豹数据缎，逶造饕参数绫诗检骏表明由ＤＥＡ方法和ＰＣＡ方法所得到的两组排序相一致。
本文的另一个难要工传就是阐述ＰＣＡ方法的綦本理论及其运舞熬步骤，搔出侵ＤＥＡ方法蟊ＰＣＡ方法产生不一致排序结果的情况，并胤在本文中将研究改进ＰＣＡ方法的程序。
在程黪的改进方霞，鸯§入Ｚｈｕ没有考虑刘的其它重要的狂｝彦因豢。
本文的垦的在于说嘲，当一组ＤＭＵ￥数据中只有一小部分怒有效单元时，Ｚｈｕ所采用的ＰＣＡ方法秘ＤＥＡ穷法在得到的排膨结果中具有一致性；当～维ＤＭＵｓ数攒中有一大部分ＤＭｕｓ是有效单元时，Ｚｈｕ所采用的ＰＣＡ和ＤＥＡ方法产嫩的排序结果不一致，霹改进后的ＰＣＡ方法与ＤＥＡ方法产生的担｝序缋果相一致。
Productivity Growth, Technical Progress and
Productivity Growth,Technical Progress and Efficiency Change in African AgricultureGuy Blaise Nkamleu*Abstract:The paper examines the economic performance of a large number of African countries using an international comparable data set and the latest technique for analysis.The paper focuses on growth in total factor productivity and its decomposition into technical change and efficiency change components.The analysis is undertaken using the data envelopment analysis(DEA).The present study uses data of16countries over the period1970–2001.It was found that,globally,during that period,total factor productivity has experienced a positive evolution in sampled countries.This good performance of the agricultural sector was due to good progress in technical efficiency rather than technical progress.The region suffered a regression in productivity in the1970s, and made some progress during the1980s and1990s.The study also highlights the fact that technical change has been the main constraint of achievement of high levels of total factor productivity during the reference period in sub-Saharan Africa.Contrariwise,in Maghreb coun-tries,technological change has been the main driving force of produc-tivity growth.Finally,the results indicate that institutional factors as well as agro-ecological factors are important determinants of agricultural productivity growth.Re´sume´:L’article analyse la performance e conomique d’un grand nombre de pays africains,en se servant d’une se rie de donne es inter-nationales comparables et de la toute dernie re me thode d’analyse.Il se penche sur la croissance de la productivite globale des facteurs de production et sa de composition en deux volets:e volution technologique et e volution de l’efficience.L’analyse repose sur la me thode dite de Cowbe enveloppe—Data Envelopment Analysis ou DEA(permettant de mesurer l’efficience a partir de donne es re elles).La pre sente e tude utilise les donne es de16pays sur la pe riode1970–2001.Il en ressort que, *University of Yaounde II and International Institute of Tropical Agriculture(IITA/ Cameroun),BP2008,Messa Yaounde,Cameroon.Tel:(237)223–74–34;fax:(237)223–74–37;e-mail:g.b.nkamleu@#African Development Bank2004,Published by Blackwell Publishing Ltd2004,9600Garsington Road,Oxford,OX42DQ,UK and350Main Street,Malden,MA02148,USA.203204G.B.Nkamleu d’une manie re ge ne rale,la productivite globale des facteurs de production ont affiche une bonne e volution dans les pays de l’e chantillon au cours de la pe riode conside re e.Cette bonne performance du secteur agricole e tait pluto t attribuable a une bonne progression de l’efficacite technique et non a des progre s productivite de la re gion a re gresse dans les anne es70,avant de remonter le ge rement dans les anne es80et90. L’e tude souligne e galement que l’e volution technologique a e te le principal obstacle a la re alisation de niveaux e leve s de productivite des facteurs en Afrique subsaharienne durant la pe riode conside re e.Par contre,dans les pays du Maghreb,l’e volution technologique a e te le principal moteur de la croissance de la productivite´.Enfin,les re sultats indiquent que les facteurs institutionnels et agro-e cologiques jouent un ro le de terminant dans la croissance de la productivite agricole.1.Introd uctionIn many parts of Africa,the major challenge facing agriculture is how to increase farm production to meet changing food needs without degrading the natural resource base.The agricultural sector is the most important in African economies employing as much as50–80per cent of the labour force(Johnston,1990).About two-thirds of the627million people living in sub-Saharan Africa(SSA)depend on agriculture or agriculture-related activities for their livelihoods(Ehui and Pender, 2003).It is estimated that throughout the region,there are236million agricultural poor,which represents60per cent of the agricultural population and80per cent of the total number of poor in the region (Dixon et al.,2001).Therefore,agriculture continues to remain import-ant in rural SSA and indicators of rural well-being are closely related to agricultural performance.In most African countries,because of its importance in overall GDP, export earnings and employment as well as its forward and backward linkages to the non-farm sector,growth in the agricultural sector will continue to be the cornerstone of poverty reduction.Increased agricul-tural productivity and growth,driven by technology and investments,has a powerful dynamic effect that benefits the poor throughout the econ-omy:directly through increased agricultural income and employment, and indirectly through increased food availability and lower food prices as well as through the demand created by increased agricultural incomes for non-farm goods and services produced by the very large,employment intensive non-agricultural rural economy.However,importation of food is still needed to curb the increasing gap between food demand and food production.As shown by several studies,one#African Development Bank2004Productivity Growth,Technical Progress and Efficiency Change205 of the most critical problems in Africa today is how to increase agricultural production to meet increasing food demand arising from an increase in population pressure(Mensah,1989;Timberlake,1990;Pretty,1995).The decline in food and agricultural per capita production over the years has become synonymous with the region’s stagnation,social decline and marginalization in the world.Unless renewed measures are taken by the governments and people of the region to dramatically increase agri-cultural production,there will be continued deterioration and stagnation.Given its importance,there is genuine concern among policymakers and researchers about the poor performance of SSA’s agricultural sector. Without exception,studies on developed countries’agriculture have shown substantial productivity increases,whereas the results for less developed countries have consistently shown productivity declines (Fulginiti and Perrin,1997).There is a substantial body of literature measuring agricultural productivity change in the developed countries(Kalirajan et al.,1996; Fare et al.,1994),while in sub-Saharan Africa,empirical studies to system-atically characterize the agricultural productivity in the region are scarce.In light of the general objective of attaining regional self-sufficiency in agricultural products,governments and institutions have sought strategies that would lead to higher levels of production.A key factor for a sustained increase of agricultural production is improvement of productivity,which is carried out through technical change and/or efficiency change.Many African farmers are still using low yielding agricultural technolo-gies,which lead to low productivity and production.Another relevant question for agricultural policymakers is whether the agricultural sector can be made more efficient,by achieving more output with the current input level,or by achieving the current output with less input usage than is currently observed.An important step in answering these questions is to understand the pathway of productivity and its components.The purpose of this study is to explore evolution of total factor productivity and its components in the African agricultural sector, using data envelopment analysis(DEA).The study used panel data on 16selected countries of the region,and is intended to explain the relative performance of the agricultural sector across regions and countries. 2.Theoretical Framework:Malmquist Data Envelopment AnalysisTechnical efficiency has received considerable attention in the economic literature in recent years.A variety of theoretical approaches,particu-larly yield gap and constraints methodologies,have been developed to #African Development Bank2004206G.B.Nkamleu investigate the failure of producers to achieve the same level of efficiency (Battese,1992).Over the past two decades,much progress has been made towards refining the frontier function methodology introduced by Farell in1957 (Farell,1957).Along with several methodological developments,there has been a considerable amount of empirical work,much of which use DEA and stochastic frontier production approaches(Lau and Yotopou-los,1971;Bagi,1982;Kopp and Diewert,1982;Russell and Young,1983; Taylor and Shonkwiler,1984;Huang and Bagi,1984;Dawson and Lingard, 1989;Ali and Chaudhry,1990;Bravo-Ureta and Rieger,1990;Defourny et al.,1992;N’gbo,1994;Kalirajan and Shand,2001;Bakhshoodeh and Thomson,2001;Wilson et al.,2001).More recently,a non-parametric method has been developed that calculates the total factor productivity index using an efficiency measure. This approach,when one has panel data,uses DEA-like linear programs and Malmquist total factor productivity index to measure productivity change,and to decompose this productivity change into technical change and technical efficiency change.In this paper,this method is employed.The method has the advantage that it is parameter free,we do not presuppose a parametric functional form.Specifying a functional form imposes restrictions on the structure of technology,which could give rise to specification error.Malmquist productivity indexes were introduced by Caves et al. (1982),who first developed these measures for varying return to scale (VRS)technologies,assuming overall efficiency and a translog technol-ogy for output distance functions.Though the authors could not provide direct estimates of the Malmquist index(MI),they noticed that the geometric mean of two MI was equivalent to a scaled Tornqvist-Theil productivity index.Subsequently,Fare et al.(1994)developed a non-parametric approach for estimating the Malmquist indexes,and showed that the component distance function could be derived using a DEA-like linear program method.Furthermore,they showed that the resulting total factor productivity indexes could be decomposed into efficiency change and technical change components.The method showed two main advantages. First,no assumption on the functional form of the underlying production technology was required.And second,unlike the Tornqvist TPF indexes, for the Malmquist indexes,data on output and input prices are not indispensable,hence making the method particularly suited for regions where price data are not readily available.The Malmquist TFP index is defined using distance functions. Distance functions allow one to describe a multi-input multi-output production technology without the need to specify a behavioural objective#African Development Bank2004such as cost minimization or profit maximization (Rao and Coelli,1998).One may define input distance functions and output distance functions.An input distance function characterizes the production technology by looking at a minimal proportional contraction of the input vector,given an output vector.An output distance function considers a maximal proportional expansion of the output vector,given an input vector.The output distance function is defined on the output set P (x ),as:d 0ðx ;y Þ¼min f :ðy = Þ2P ðx Þg ;where the output set,P (x )represents the set of all output vectors,y ,which can be produced using the input vector x .Extensive discussion on Malmquist indexes can be found in Fare et al .(1994).Here,we provide a brief summary of the discussion,and suggest interested readers to refer to the references above.Even though the method is easily accommodated to the multi-output,multi-input case,for clarity purposes the exposition is limited to the single-output,single-input and output-oriented case.Following Fare et al .(1994),the MI TFP change between a base period (s )and a period t can be written as:m 0y s ;x s ;y t ;x t ðÞ¼d s 0y t ;x t ðÞd s 0y s ;x s ðÞd s 0y t ;x t ðÞd t 0y t ;x t ðÞd s0y s ;x s ðÞd t0y s ;x s ðÞ 1=2;ð1Þwhere the notation d sy t ;x t ðÞrepresents the distance from the period t observation,to the period s technology.A value of m greater than one will indicate positive TFP growth from period s to period t .In (1),the term outside the square brackets measures the Farrell efficiency change between period s and t ,and the term inside measures technical change,which is the geometric mean of the shift in the technol-ogy between the two periods.Thus,the two terms in equation (1)are:Efficiency change ¼d s 0y t ;x t ðÞd s0y s ;x s ðÞTechnical change ¼d s 0y t ;x t ðÞd t 0y t ;x t ðÞd s 0y s ;x s ðÞd t0y s ;x s ðÞ1=2The efficiency change component is equivalent to the ratio of the Farrelltechnical efficiency in period t to the Farrell technical efficiency in period s ,under the constant return to scale (EFFCH crs ).This efficiency change component can be separated into a scale efficiency and pure technicalProductivity Growth,Technical Progress and Efficiency Change207#African Development Bank 2004208G.B.Nkamleuefficiency change.The pure technical efficiency is obtained by re-computing efficiency change under the variable return to scale(EFFCH vrs).The scale efficiency is therefore the ratio of efficiency under constant return to scale and the same efficiency under variable return to scale(EFFCH crs/ EFFCH vrs).The overall index in(1)represents the productivity of the production point(y t,x t)relative to the point(y s,x s),and a value larger than one depicts positive TFP growth between periods s and t.Empirical appli-cations require the computations of the four distance functions in(1). As suggested by Coelli(1996),the distance functions can be recovered by solving the following DEA-like linear programs:½d t0ðx t;y tÞ À1¼Max ; ;subject toÀ y itþY t !0x itÀX t !00!0;½d tþ1ðx tþ1;y tþ1Þ À1¼Max ; ;subject toÀ y i;tþ1þY tþ1 !0x i;tþ1ÀX tþ1 !00!0;½d t0ðx tþ1;y tþ1Þ À1¼Max ; ;subject toÀ y i;tþ1þY t !0x i;tþ1ÀX t !00!0;½d tþ1ðx t;y tÞ À1¼Max ; ;subject toÀ y itþY tþ1 !0x itÀX tþ1 !00!0;where is a NÂ1vector of constant and is a scalar with1* <1. À1is the proportional increase in outputs that could be achieved by the i th unit,with input quantities held constant.The above programs must be solved for each country in the sample in each period,and an extra three programs for each country to construct#African Development Bank2004the chained index.If we have T time periods,we must calculate(3TÀ2) LPs.Overall,for N firms and T periods,with the decomposition of the technical efficiency N(4TÀ2)LPs are solved(2016LP in this case). 3.Data SpecificationTo estimate the Malmquist indexes of efficiency and total factor produc-tivity,a panel data on16African countries from1970to2001was used. The countries concerned are listed in Table1below.Data consisted of information on agricultural production and means of production in the study countries.Record of agricultural production index(base1989–1991),rural population,number of tractors in use, fertilizer uses,agricultural areas were obtained from FAO statistic database.Specification of output and input in the analysis was as follows: Output*Agricultural production:To construct the output series,we followed the methodology suggested in Rao and Coelli(1998).Output aggre-gated for the year1990was used to compute output series.These1990 aggregated outputs were computed using international average pricesTable1:Sample countries used in the analysisColonial heritage Location Sahelian/non-SahelianHave/Have notexperience major civil warAlgeria French Maghreb Sahelian NoBurkina Faso French West Africa Sahelian NoCameroon French West Africa a Non-Sahelian NoCo te d’Ivoire French West Africa Non-Sahelian NoEgypt French Maghreb Sahelian NoGhana British West Africa Non-Sahelian NoKenya British East Africa Non-Sahelian NoMalawi British Austral Africa Non-Sahelian NoMali French West Africa Sahelian NoMorocco French Maghreb Sahelian NoMozambique Portugal Austral Africa Non-Sahelian YesNigeria British West Africa Non-Sahelian NoSenegal French West Africa Sahelian NoTunisia French Maghreb Sahelian NoUganda British East Africa Non-Sahelian YesZimbabwe British Austral Africa Non-Sahelian Noa Although Cameroon is politically part of Central Africa,it is more common in scientific studies to consider it as part of West Africa.Productivity Growth,Technical Progress and Efficiency Change209 #African Development Bank2004210G.B.Nkamleu (expressed in US dollars)derived using a Geary-Khamis method(see Rao,1993).The aggregates are based on the sum of price-weighted quantities of different agricultural commodities produced after deduc-tion of quantities used as seed and feed weighted in a similar manner.The resulting aggregates represent,therefore,disposable production for any use,except as seed and feed.The1990output series were then extended to cover the study period1970–2001,using the FAO produc-tion index number series.Input*Labour refers to the economically active population in agriculture for each year,in each country.The economically active population in agriculture is defined as all persons engaged or seeking employment in the agriculture,forestry,hunting or fishing sector,whether as employ-ers,own-account workers,salaried employees or unpaid workers.*Agricultural land:the sum of area under arable land(land under temporary crops,temporary meadows for mowing or pasture,land under market and kitchen gardens and land temporarily fallow);permanent crops(land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest,such as cocoa,coffee and rubber);and permanent pastures(land used perman-ently for herbaceous forage crops,either cultivated or growing wild). *Fertilizer:The sum of nitrogen,potash and phosphate content of various fertilizers consumed,measured in thousands of metric tons in nutrient units.*Tractors refer to total wheel and crawler tractors(excluding garden tractors)used for agricultural production.4.ResultsMean overall technical efficiencies(Table2),indicate an overall positive trend over time for the sample countries.However,countries did not have the same performance during the period.Some countries like Malawi and Co te d’Ivoire have experienced a big increase of overall technical efficiency during the period,while Burkina Faso experienced a negative trend.Recall that a value greater than unity represents an improvement of efficiency or productivity.Turning to the component measures(PechC and SechC),it appears that both pure and scale technical efficiency have contributed to the growth of overall efficiency. This suggests that,in the achievement of high levels of technical perform-ance over time,the technical efficiency is not a long-run constraint.#African Development Bank2004The positive evolution of the scale efficiency suggests that the agricul-tural sector succeeded in taking advantage of the growing size of the sector,while the improvement in pure technical efficiency over the study period is a significant finding and suggests that there was a learning process,as predicted by theories of intra-firm diffusion (Kalirajan and Shand,2001).Examining the trend of efficiencies offers another important insight into the performance over time.The evolution trend of the technical efficiency and its component is shown in Figure 1.Scale efficiency has experienced big season-by-season fluctuations,inducing big fluctuations in the overall technical efficiency.This situation may be due to the large difference between countries in performing scale efficiency change (Table 2).Turning to the Malmquist total factor productivity index,Table 3includes mean values of measures of change in total factor productivity index and its components (efficiency change and technical change).Means are given for the sample as a whole as well as by country.Looking at the sample as a whole,the change in total factor productivity of the agricultural sector of the countries studied has been positive.On average,total factor productivity has increased by 0.1per cent annually.An important question is:what is the main cause of that gain of productivity?The agricultural sector can improve the level of total factor productivity either by improving technical efficiency and/or by improvingTable 2:Mean technical efficiencies changeCountriesTechnical efficiency change Pure technical efficiency change Scale efficiency changeEffchCPechC SechC Algeria1.012 1.0190.994Burkina Faso 0.982 1.0000.982Cameroon 1.000 1.000 1.000Co te d’Ivoire 1.018 1.006 1.012Egypt 1.000 1.000 1.000Ghana 1.006 1.006 1.000Kenya 1.009 1.000 1.009Malawi 1.023 1.000 1.023Mali 1.009 1.009 1.000Morocco 1.0000.997 1.004Mozambique 1.002 1.0220.981Nigeria 1.000 1.000 1.000Senegal 1.013 1.000 1.013Tunisia 1.006 1.000 1.006Uganda 1.000 1.000 1.000Zimbabwe 1.009 1.001 1.009Mean1.0061.0041.002Productivity Growth,Technical Progress and Efficiency Change211#African Development Bank 2004technological level(shift in the production frontier).The component meas-ures of total factor productivity,EffchC and TechchC show that efficiency has been the main contributor of the success of total factor productivity. The average technical efficiency change was0.6per cent per year,while the technical change was negative(À0.5per cent per year).Table3:Mean total factor productivity changeCountries Technicalefficiency change TechnologicalchangeTotal factorproductivity changeEffchCTechchCTfpchC Algeria 1.012 1.017 1.030Burkina Faso0.9820.9670.950Cameroon 1.0000.9920.992Co te d’Ivoire 1.0180.993 1.011Egypt 1.0000.9980.998Ghana 1.0060.9920.998Kenya 1.009 1.004 1.013Malawi 1.023 1.002 1.024Mali 1.0090.9810.989Morocco 1.000 1.005 1.006Mozambique 1.002 1.007 1.009Nigeria 1.0000.9640.964Senegal 1.0130.987 1.000Tunisia 1.006 1.008 1.014Uganda 1.000 1.001 1.001Zimbabwe 1.009 1.005 1.014Mean 1.0060.995 1.001212G.B.Nkamleu#African Development Bank2004This suggests that,for the sampled countries,technical change hasbeen the main constraint of achievement of high levels of total factor productivity during the reference period.Also here,countries did not perform similarly.Countries that hadbeen good or average in increasing levels of technical efficiency experi-enced poor technical change.This was the case in countries like Co ted’Ivoire and Senegal.Overall,11out of the16sampled countries had increased efficiency more than technology(Table4).This is useful infor-mation and important in guiding efforts to increase agricultural produc-tion.Figure2shows the trend over time.This trend is characterized by an important season-by-season variation of the two components of the totalfactor productivity index.The technical change component has had more fluctuation,suggesting that promotion of technical change has not been constant during the period.Figures3and4show the rates of change in efficiency,technology and productivity,grouped by decade.It appears that during the1971–80period the region performed well in raising the efficiency of the agricul-tural sector.The average annual growth rate of technical efficiencyduring that period was2.3per cent,while the technical change was negative on average.The situation was reversed during the1980s andthe1990s,with a good score on technical change and a regression of technical efficiency.Table4:Comparison between technical efficiency change and tech-nological change>EffchC Countries EffchC>TechchCTechchC Algeria*Burkina Faso*Cameroon*Co te d’Ivoire*Egypt*Ghana*Kenya*Malawi*Mali*Morocco*Mozambique*Nigeria*Senegal*Tunisia*Uganda*Zimbabwe*Mean**¼YesThe results presented so far do support the notion that there is a difference between countries in performing efficiency and productivity change.It was therefore interesting to investigate the relationship between those changes and countries’particularities.We investigated what potential institutional and socio-political factors have affected the agricultural productivity performance in Africa.The relationship between total factor productivity and some measurable factors that may supposedly impact the productivity were investigated.The factors considered included:*Colonial heritage:countries were grouped according to their colonial heritage.*Political right and civil liberties:indexes of political freedom that ‘freedom house’has published for each sampled country was used.Each year,since1972,based on a series of checklists relating to political rights and civil liberties,freedom house has rated each coun-try as‘free’,‘partly free’or‘not free’.*Geographical location:It is expected that due to a difference in natural resource endowment,geographical location could have an impact on the performance of the agricultural sector.*Conflict:A dummy variable was used to characterize countries that have experienced a major civil war.Two countries were identified in this category(Mozambique and Uganda).However,it is recognized that this categorization is disputable,since the boundary between minor and major conflict has a subjective flavour.A Tobit model of the determinants of efficiency and productivity was run(Table5).Apart from the factors mentioned above,the illiteracy rate,the proportion of irrigated agricultural land,and the agricultural land in each country were also included in the model.Two major results came out of these estimations:1.The illiteracy rate is negatively related to productivity growth.Coun-tries with a high proportion of illiterates were also those performing weakly in productivity growth,suggesting that fighting illiteracy isanother means to push agricultural productivity.T a b l e 5:T o b i t m o d e l o f t h e d e t e r m i n a n t s o f t o t a l f a c t o r p r o d u c t i v i t y c h a n g e i n s a m p l e d c o u n t r i e sV a r i a b l eE f f i c i e n c y c h a n g eT e c h n i c a l c h a n g e T o t a l f a c t o r p r o d u c t i v i t y c h a n g eC o e f f i c i e n t t -s t a t i s t i c s C o e f f i c i e n t t -s t a t i s t i c s C o e f f i c i e n t t -s t a t i s t i c sC o n s t a n t 1.01220.10**1.005416.15**1.009812.98***%o f i r r i g a t e d l a n d À0.0253À0.86À0.0154À0.42À0.0391À0.86I l l i t e r a c y r a t e 0.00020.50À0.0016*À2.61**À0.0015À2.01**A g r i c u l t u r a l a r e a 5.3E –080.126.9E –080.131.5E –070.22D u m m y f o r p o l i t i c a l l y n o t -f r e e c o u n t r i e s À0.0043À0.360.00660.44À0.0009À0.05D u m m y f o r p o l i t i c a l l y f r e e c o u n t r i e s À0.0118À0.430.00500.15À0.0096À0.23D u m m y f o r S a h e l i a n c o u n t r i e s À0.0140À0.570.03371.120.02560.68D u m m y f o r f o r m e r F r e n c h c o l o n i e s À0.0002À0.010.07011.150.08651.14D u m m y f o r f o r m e r B r i t i s h c o l o n i e s À0.0046À0.120.05721.220.06621.13D u m m y f o r c o u n t r i e s w h i c h e x p e r i e n c e d m a j o r w a r À0.0186À0.680.10823.21**0.09352.22**D u m m y f o r M a g h r e b c o u n t r i e s 0.01420.44À0.0087À0.220.00070.01D u m m y f o r W e s t A f r i c a n c o u n t r i e s À0.0153À0.620.00680.23À0.0061À0.160.126030.89**0.155730.89**0.194630.89***L o g l i k e l i h o o d ¼311.41L o g l i k e l i h o o d ¼210.37L o g l i k e l i h o o d ¼103.92T o t a l s a m p l e ¼477T o t a l s a m p l e ¼477T o t a l s a m p l e ¼477*¼s i g n i f i c a n t a t 0.10;**¼s i g n i f i c a n t a t 0.05;***¼s i g n i f i c a n t a t 0.01.。
中学英语教学美篇范文
中学英语教学美篇范文The significance of English language education in secondary schools cannot be overstated. As a global lingua franca, proficiency in English has become a crucial skill for academic and professional success in an increasingly interconnected world. Effective English teaching in secondary schools serves as the foundation for students to develop strong communication abilities, critical thinking skills, and cultural awareness - all of which are essential for their future endeavors. This essay will explore the key elements of exemplary English teaching in secondary schools, highlighting best practices and the positive impact on student outcomes.Firstly, an effective English curriculum in secondary schools should strike a balance between developing students' proficiency in the four core language skills: reading, writing, listening, and speaking. While traditional approaches have often emphasized the mastery of grammar rules and vocabulary, modern pedagogical methods emphasize the importance of integrating these skills in authentic, communicative contexts. This allows students to apply their knowledge and practice language usage in real-world scenarios,fostering a deeper understanding and appreciation for the language.One such approach is the implementation of task-based learning, where students are given meaningful, collaborative tasks that require them to use English to accomplish specific goals. For example, students might be asked to plan a school trip, conduct a market research survey, or create a multimedia presentation on a topic of their choice. By engaging in these task-oriented activities, students not only develop their linguistic abilities but also hone their critical thinking, problem-solving, and teamwork skills - all of which are highly valued in the 21st-century job market.Another crucial aspect of exemplary English teaching is the incorporation of diverse, culturally-relevant materials and resources. Instead of relying solely on traditional textbooks, effective English teachers in secondary schools curate a wide range of authentic texts, such as literature, news articles, films, and podcasts, that reflect the diverse backgrounds and experiences of their students. This not only helps to maintain student engagement and interest but also fosters a deeper understanding and appreciation for different cultures, perspectives, and modes of expression.Furthermore, the use of technology in English language instruction has become increasingly important in the digital age. Savvy English teachers in secondary schools leverage a variety of digital tools andplatforms to enhance the learning experience. This might include the use of interactive whiteboards, language learning apps, virtual reality simulations, or online collaboration platforms. By seamlessly integrating technology into their teaching, these educators are able to create engaging, immersive learning environments that cater to the diverse learning styles and preferences of their students.In addition to the curricular and instructional approaches, the role of the English teacher in secondary schools is also crucial to the success of the program. Exemplary English teachers are not merely content experts; they are skilled facilitators who can create a supportive, inclusive, and intellectually stimulating classroom environment. These educators possess a deep understanding of their students' needs, backgrounds, and learning preferences, and they are able to adapt their teaching strategies accordingly.Effective English teachers in secondary schools also prioritize ongoing professional development, continuously seeking to expand their knowledge, refine their pedagogical skills, and stay up-to-date with the latest research and best practices in the field. This commitment to lifelong learning not only benefits the teachers themselves but also has a direct impact on the quality of instruction and the overall learning outcomes of their students.Moreover, exemplary English teaching in secondary schools extendsbeyond the classroom walls. Successful English teachers actively collaborate with their colleagues, both within the English department and across other subject areas, to ensure a cohesive and integrated approach to language learning. They also engage with the broader school community, including parents and administrators, to foster a shared understanding of the importance of English language proficiency and to garner support for innovative teaching initiatives.The positive impact of exemplary English teaching in secondary schools is manifold. When students are exposed to a well-designed, engaging, and culturally-responsive English curriculum, they not only develop strong language skills but also cultivate a deeper appreciation for diversity, critical thinking, and effective communication. These skills are not only essential for academic success but also serve as a foundation for their future personal and professional endeavors.Furthermore, the benefits of exemplary English teaching extend beyond the individual student level. When a secondary school consistently delivers high-quality English language instruction, it can positively impact the entire school community. Improved English proficiency among students can lead to better academic performance across all subject areas, higher graduation rates, and increased opportunities for post-secondary education and career advancement.In conclusion, the significance of exemplary English teaching in secondary schools cannot be overstated. By prioritizing the development of well-rounded language skills, incorporating culturally-relevant and technology-enhanced instructional approaches, and fostering a supportive and intellectually stimulating learning environment, English teachers in secondary schools can have a profound and lasting impact on their students' academic, personal, and professional trajectories. As the world becomes increasingly interconnected, the importance of cultivating strong English language proficiency in secondary schools will only continue to grow, making it a crucial investment in the future success of our students and our communities.。
水供应服务效率测量和排名：使用混合DEA和PROMETHEE II方法说明书
Efficiency Measurement and Ranking of WaterSupply Service Malaysia by Using Hybrid DEAand PROMETHEE II MethodNur Rasyida Mohd Rashid(B),Dayang Rini Najwa Mohd Huza,Alia Mohamad Naem,and Fatin Ain Sabrina Fauzan Mathematical Sciences Studies,College of Computing,Informatics and Media,Universiti Teknologi Mara(UiTM),Negeri Sembilan Branch,Seremban Campus,Persiaran Seremban Tiga/1,70300Seremban,Negeri Sembilan,Malaysia**************.my,{22019627304,2019415336,2019892286}@.myAbstract.Water is a crucial resource in our daily life and is needed for rapidsocio-economic development worldwide.Therefore,the evaluation of efficiencyfor water supply services is an important aspect to assure that the whole sec-tor works efficiently.Data Envelopment Analysis(DEA)is a linear programmingmethod to measure the efficiency of multiple decision-making units(DMUs)whenthe production process presents a structure of multiple inputs and outputs that canbe applied for water service efficiency.However,the problem with the classi-cal DEA method is that it lacks discrimination power where it fails to rank theefficient DMUs since all efficient DMUs obtained are with an efficiency scoreof one.Thus,this study integrates PROMETHEE II into classical DEA to rankthe DMUs completely.This study aims to measure the efficiency and provide acomplete ranking of water supply services for14states in Malaysia.Firstly,CCRoutput-oriented model is used to measure the efficiency score of the DMUs andthen the PROMETHEE II method was applied to rank those efficient units.Thefindings proved that the proposed DEA-PROMETHEE II method can be success-fully applied to give a complete ranking for all of the DMUs for the14-watersupply service in Malaysia.Keywords:Water Supply Service·DEA·PROMETHEE II·Super Efficiency1IntroductionWater resources provide a wide range of services that are essential for long-term devel-opment which has been greatly driven by population expansion,modernization,and food and energy security which is due to its constant need[1].Moreover,rapid human growth caused the fast expansion of several water supply networks within the last50years,and it is predicted to rise further[2].The expansion of the water supply network has made a huge global concern in improving its efficiency to satisfy the demand for water sup-ply around the world.When analyzing all types of productive activities,efficiency has ©The Author(s)2023N.Annuar et al.(Eds.):ICOFA2023,ASSEHR759,pp.41–49,2023.https:///10.2991/978-2-38476-076-3_542N.R.Mohd Rashid et al.been a major consideration,and study on the topic has resulted in a range of assessment approaches[3].There are several mathematical measurements or quantitative approaches for measuring the relative efficiency of decision-making units(DMUs)where one of the mathematical approaches is Data Envelopment Analysis(DEA)which was introduced by[4]to measure the technical efficiency of the DMUs[5].Much research addressing the management of water supply sectors has been conducted globally since1986with the application of DEA models[6].DEA uses efficiency scores where the score that is equal to one will be considered as efficient DMUs.However,classical DEA models have several weaknesses which is a lack of discrimination power.Therefore,classical DEA fails to rank the efficient DMUs since all efficient DMUs obtained are with an efficiency score of one[7].Thus,the complete ranking of DMUs could not be obtained.PROMETHEE II is a superior strategy method for rating and selecting among a limited number of alternatives while taking into account a variety of competing criteria [8].The application model of integrating the DEA and PROMETHEE II approach will generate the capability of DEA analysis to give a full-ranking result for the DMUs. Thus,in this study,the effectiveness of water supply services in14Malaysian states will be measured using the application of the DEA-PROMETHEE II model by consid-ering inputs which are the total operating costs(OPEX)and the number of employees. Then,the outputs are water consumption and total income for the water supply service. There are three main objectives to be achieved in this study which are to measure the efficiency of water supply service in Malaysia by using the classical DEA method.Next, to contribute a full ranking of water supply service in Malaysia by integrating the DEA-PROMETHEE II method and lastly to compare the full ranking result with another DEA full ranking method which is the Super Efficiency method.2Methodology2.1Data Acquisition and the Determination of Input and OutputThis study involves measuring the efficiency of14states of water supply service in Malaysia where the data on inputs and outputs was collected from the annual report of the Malaysian Water Industry Guide(MWIG)for the year2017as shown in Table1.Three software were used in this research which are LINGO19.0,Efficiency Measurement Software(EMS)and Microsoft EXCEL.2.2Data Envelopment Analysis(DEA)MethodCCR model was proposed by[4]which is a nonparametric mathematical linear pro-gramming technique that allows determining the best practices of the efficient frontier from efficient DMUs with multiple inputs and outputs.This model is also able to guide inefficient DMUs to become efficient.In this study,CCR Output-oriented model has been chosen to measure the efficiency score of the water service providers in Malaysia where the model is as follows:1 E0=Minimize h j=mi=1v i X i0(1)Efficiency Measurement and Ranking of Water Supply Service Malaysia43 Table1.Secondary Data of DMUs for2017State(DMUs)Number ofworkers(Input1)Operationalexpenditure(OPEX)(Input2)Waterconsumption(MLD)(Output1)Total revenue(RM)(Output2)Johor222058792913201139807 Kedah1418296451719307299 Kelantan816101170240115153 buan134256084833034 Melaka805156985413230956 Negeri Sembilan1079212455519275543 Pulau Pinang1332219923826336472 Pahang1655298411582175122 Perak1075227784907392244 Perlis138424808933650 Sabah1064465119582335633 Sarawak2399194552870270875 Selangor4569259608232432094242 Terengganu458101333427134961Such that,sr=1u r Y r0=1m i=1v i X ij− s r=1u r Y rj≥j=1,...,nu r,v i≥ε,r=1,...,s,i=1,...,mwhere:X ij=InputY rj=Outputh j=The relative efficiency of DMU jv i=Weight of inputu r=Weight of outputε=The small positive valuen=Number of statess=Number of outputsm=Number of inputs44N.R.Mohd Rashid et al.2.3Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE II)Since DEA Method could not provide a full ranking for the efficient DMUs,the PROMETHEE II Method which is one of the multi-criteria decision-making methods will be used in this study to generate a complete ranking for water supply services in 14states in Malaysia.The PROMETHEE method is a special type of MCDM tool that was initially developed by Brans in 1986.It is based on pairwise comparisons of all of the alternatives and was designed to handle quantitative and qualitative criteria with discrete alternatives.The PROMETHEE I method allows the partial ranking of the deci-sion alternatives,whereas the PROMETHEE II method can provide the full ranking of the alternatives.This method highlights the importance of every criterion in creating each objective weight of the criterion.The weightage that will be used in step 5is com-puted from Entropy Method before computing the full ranking.There are seven steps in PROMETHEE 11as in [9]:Step 1:Construct the decision matrix.Step 2:Normalize the decision matrix by using Eqs.(2)and (3)for beneficial criteria and non-beneficial criteria,respectively.Rij =X ij −minX ijmax X ij −min X ijfor i =1,2,3,...,m;j =1,2,3,...,n (2)Rij =max (X ij )−X ij max X ij −min X ij for i =1,2,3,...,m;j =1,2,3,...,n (3)Step 3:Calculate the evaluative differences of i th alternative with respect to another alternative,d j (a,b)by usingd j (a ,b )=g j (a )−g j (b )(4)Step 4:Calculate the preference function,P j (a ,b )usingP j (a ,b )=0if R aj ≤R bj such that D (M a −M b )≤0P j (a ,b )=R aj −R bj if R aj >R bj such that D (M a −M b )>0(5)Step 5:Calculate the aggregated preference,π(a ,b )by usingπ(a ,b )= nj =1w j P j (a ,b ) n j =1w jwhere n j =1w j =1(6)Given thatn j =1w j is the sum if the weight for the criteria.Step 6:Determine the leaving and the entering outranking flow using Eq.(7)and (8)respectively.Leaving (positive )flow for a th alternative ,ϕ+(a )=1m −1m b =1π(a ,b )where (a =b )(7)Efficiency Measurement and Ranking of Water Supply Service Malaysia 45Entering (negative )flow for a th alternative ,ϕ−(a )=1(m −1)m (b =1)π(a ,b )where (a =b )(8)Step 7:Calculate the net outranking flow for each alternative usingϕ(a )=ϕ+(a )−ϕ−(a )(9)The ranking of all the considered alternatives depending on the values of ϕ(a ).Thehigher value of ϕ(a ),the better is the alternative.Thus,the best alternative is the one having the highest ϕ(a )value.The result will be compared with another full-ranking method of the DEA Model which is the Super Efficiency Model which also provides a full ranking of the DMUs.2.4Super Efficiency DEA ModelThe best performance of a DMU is reflected by an efficiency score of one in various DEA models where this efficiency score is often shared by multiple DMUs.Many methods have been presented under the label of super-efficiency methods to rank and compare efficient units [10].Reference [11]explained that the basic idea of the Super efficiency model is to compare the unit under evaluation with a linear combination of all other units in the sample where the DMU itself is excluded.Thus,an efficiency score that exceeds unity is obtained for the unit because the maximum proportional increase in inputs preserves efficiency [12].The advantage of the SE-DEA model is that it permits us to rank and provide a super-efficiency rating for efficient units [13].Meanwhile,the efficiency score of the inefficient DMUs remains consistent with the CCR method.The model of Super Efficiency DEA as in [14]where θis a scalar that designates the share of the j th DMU’s input vector,which is required to produce the j th DMU’s output vector within the reference technology and describe as follows:Min θ.Subject to:nk =1k =jv k X k +s −=θX jnk =1k =jv kY k +s −=Y j v k ≥0,k =1,2,...,n s −≥0,s +≥0,Where,k =1,2,3…,n are inputs k =1,2,3…,n are outputs j =1,2,3…,n are DMU’s v k =intensity of the k th unit X j =m -dimensional input vector Y j =s -dimensional output vector46N.R.Mohd Rashid et al.3Result and DiscussionThe result of the efficiency of water supply service in14states in Malaysia is discussed which involved two inputs(number of workers and OPEX)and two outputs(water consumption and total revenue)for the R Output-oriented model attempts to maximize outputs without requiring more of any of the observed input values and PROMETHEE II is one of the MCDM techniques that complete the ranking of efficient DMUs.Both of these models are used in this study as the main mathematical model infinding the rank for the efficiency score of the water supply service provider.The result will be compared with another full-ranking method which is the Super Efficiency Method to validate the effectiveness of the DEA-PROMETHEE II method in providinga complete ranking for water supply service in Malaysia.3.1Efficiency Score and Ranking of DMUsThe results of the efficiency score and rank of the DMUs are shown in Table2.The efficiency score for each DMU is determined by using Eq.(1)of the CCR Model while the rank of the DMUs is set by comparing the efficiency score of each DMUs that was obtained from the calculation.The efficiency score with the highest value will be at the top rank while the lowest efficiency score will be at the lowest rank.Since the CCR model is not a complete ranking model,5DMUs are having an equal efficiency score of1which are Johor,Perak,Sarawak,Selangor and Terengganu.The states with efficiency scores of less than one are Kedah,Kelantan,buan,Melaka,Negeri Sembilan,Pulau Pinang,Perak,Perlis and Sabah with efficiency scores of more than 0.5and Pahang having efficiency value of less than0.5.Therefore,the hybrid DEA-PROMETHEE II approach was used to obtain the complete ranking of the efficient DMUs with Johor at thefirst rank followed by Perak,Terengganu,Sarawak and Selangor respectively.Then,the Super Efficiency method was used to validate the result from the DEA-PROMETHEE II method which then shows similar ranking results as can be seen in Table2.Thus,this shows the capability and practicality of the application of the hybrid DEA-PROMETHEE II method infinding the complete ranking for the water supply service providers in Malaysia.parison of the ranking results between the Hybrid-DEA PROMETHEE II method and the Super Efficiency methodDMUs CCR Model PROMETHEE II Super EfficiencyMethodEfficiency Score Rank EfficiencyScoreRank EfficiencyScore(%)RankJohor 1.000010.08331135.551 Kedah0.607313-1360.7313 Kelantan0.646412-1264.6412(continued)Efficiency Measurement and Ranking of Water Supply Service Malaysia47Table2.(continued)DMUs CCR Model PROMETHEE II Super EfficiencyMethodEfficiency Score Rank EfficiencyScoreRank EfficiencyScore(%)RankF.T Labuan0.686811-1168.6811 Melaka0.81107-781.107 NegeriSembilan0.721910-1072.1910 Pulau Pinang0.92256-692.256 Pahang0.459114-1445.9114 Perak 1.000010.02982111.492Perlis0.73059-973.059 Sabah0.73208-873.208 Sarawak 1.00001-0.04974106.124 Selangor 1.00001-0.05645101.575 Terengganu 1.00001-0.00703110.5034ConclusionThis study aims to measure the efficiency of the water supply service of14states in Malaysia for the year2017.Thefirst method used in this study is the DEA model.In this method,the CCR Output-oriented model is applied to measure the efficiency of the water supply service in Malaysia.However,the efficiency score that was obtained from the DEA-CCR model could not determine the most efficient water supply service in Malaysia as5states are having the same efficiency score of1.Therefore,the hybrid of the DEA-PROMETHEE II method was used to fully rank the efficient DMUs.Evaluating the performance of water supply service is very necessary to determine the level of efficiency of water supply service operators in each state so that demand from consumers can always be met due to increasing population throughout the year,at the same time water supply operators can also improve the quality of their services.It is recommended for future researchers to compare the full ranking results with the SPAN performance indicators to determine the suitability of the DEA model that is discussed in this study as an alternative performance indicator for water supply services in Malaysia by using Spearman’s rank correlation test.At the same time,hybrid models such as the fuzzy-DEA model or network process analysis(ANP)-DEA model can be applied for the next research.48N.R.Mohd Rashid et al.References1.Luna,T.,Ribau,J.,Figueiredo,D.,Alves,R.:Improving energy efficiency in water supplysystems with pump scheduling optimization.Journal of cleaner production213,342-356 (2019).2.Coelho,B.,Andrade-Campos,A.:Efficiency achievement in water supply systems-A review.Renewable and Sustainable Energy Reviews30,59-84(2014).3.Herrala,M.E.,Huotari,H.,Haapasalo,H.J.O.:Governance of Finnish waterworks–A DEAcomparison of selected models.Utilities Policy20(1),64–70(2012).4.Charnes,A.,Cooper,W.W.,Rhodes,E.:Measuring the efficiency of decision-making units.European journal of operational research2(6),429-444(1978).5.Mahmoudi,M.J.,Fathi,B.,Sajadifar,H.,Shahsavari,A.:Measuring efficiency of water andwastewater company:A DEA approach.Research Journal of Applied Sciences,Engineering and Technology4(12),1642–1648(2012).6.Kamarudin,N.,Ismail,W.R.,Mohd,M.A.:Malaysian Water Utilities Performance UsingTwo-Stage DEA.International Journal of Applied Physics and Mathematics5(1),60–66 (2015).7.Alirezaee,M.R.,Afsharian,M.:A complete ranking of DMUs using restrictions in DEAmodels.Applied Mathematics and Computation189(2),1550–1559(2007).8.Abedi,M.,Torabi,S.A.,Norouzi,G.-H.,Hamzeh,M.,Elyasi,G.-R.:PROMETHEE II:A knowledge-driven method for copper puter&Geosciences46,225-263(2012).9.Nor Faradilah,M.,Nur Azlina,A.,A.,F.A.M.A.,J.M.M.:Chapter6:A Hybrid DEA-PROMETHEE ll Method:A Complete Rankings of DMUs.1(November),34–40(2020). 10.Noura,A.A.,Lotfi,F.H.,Jahanshahloo,G.R.,Rashidi,S.F.,Parker,B.R.:A new methodfor measuring congestion in data envelopment analysis.Socio-Economic Planning Sciences 44(4),240-246(2010).11.Wongchai,A.,Tai,C.F.,Peng,K.C.:An application of super-efficiency and tobit method forfinancial efficiency analysis of food industrial companies in Taiwan.In Proceedings of2011 2nd IEEE International Conference on Emergency Management and Management Sciences, 823–26(2011).12.Sun,S.,Lu,W.M.:A cross-efficiency profiling for increasing discrimination in data envel-opment R:Information Systems and Operational Research43(1),51–60 (2005).13.Andersen,P.,Petersen,N.C.:A procedure for ranking efficient units in data envelopmentanalysis.Management science39(10),1261-1264(1993).14.Pan,Z.,Wang,Y.,Zhou,Y.,Wang,Y.:Analysis of the water use efficiency using super-efficiency data envelopment analysis.Applied Water Science10(6),1-11(2020).Efficiency Measurement and Ranking of Water Supply Service Malaysia49 Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0International License(/licenses/by-nc/4.0/), which permits any noncommercial use,sharing,adaptation,distribution and reproduction in any medium or format,as long as you give appropriate credit to the original author(s)and the source, provide a link to the Creative Commons license and indicate if changes were made.The images or other third party material in this chapter are included in the chapter’s Creative Commons license,unless indicated otherwise in a credit line to the material.If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use,you will need to obtain permission directly from the copyright holder.。
专题45 议论文(高考真题+各地模拟题)
备战2022高考考英语完形填空话题分类训练(高考真题+各地模拟题)专题45 议论文（2014·广东·高考真题）Parents feel that it is difficult to live with teenagers. Then again, teenagers have___1___feelings about their parents, saying that it is not easy living with them. According to a recent research, the most common ___2___between parents and teenagers is that regarding untidiness and daily routine tasks. On the one hand, parents go mad over ___3___rooms, clothes thrown on the floor and their children’s refusal to help with the ___4___. On the other hand, teenagers lose their patience continually when parents blame them for ___5___the towel in the bathroom, not cleaning up their room or refusing to do the shopping at the supermarket.The research, conducted by St. George University, shows that different parents have different ___6___to these problems. However, some approaches are more ___7___than others. For example, those parents who yell at their children for their untidiness, but___8___clean the room for them, have fewer chances of changing their children’s ___9___. On the contrary, those who let teenagers experience the ____10____of their actions can do better. For example, when teenagers who don’t help their parents with the shopping don’t find their favorite drink in the refrigerator, they are forced to ____11____their actions. Psychologists say that ____12____is the most important thing in parent-child relationships. Parents should ____13____to their children but at the same time they should lend an ear to what they have to say. Parents may ____14____their children when they are untidy but they should also understand that their room is their own private space. Communication is a two-way process. It is only by listening to and ____15____each other that problems between parents and children can be settled.1．A．natural B．strong C．guilty D．similar 2．A．interest B．argument C．link D．knowledge 3．A．noisy B．crowded C．messy D．locked 4．A．homework B．housework C．problem D．research 5．A．washing B．using C．dropping D．replacing 6．A．approaches B．contributions C．introductions D．attitudes 7．A．complex B．popular C．scientific D．successful8．A．later B．deliberately C．seldom D．thoroughly 9．A．behavior B．taste C．future D．nature 10．A．failures B．changes C．consequences D．thrills 11．A．defend B．delay C．repeat D．reconsider 12．A．communication B．bond C．friendshipD．trust13．A．reply B．attend C．attach D．talk 14．A．hate B．scold C．frighten D．stop 15．A．loving B．observing C．understanding D．praising （2022·山西临汾·二模）“What do you want to be when you grow up?” When I was a kid, I____16____the question. Adults always seemed terribly disappointed that Iwasn't____17____becoming something grand or ____18____,like an astronaut.Now, as an organizational psychologist, my job is to fix other people's jobs, and I've come to____19____that asking youngsters that question does them____20____ My first complaint about the question is that it____21____kids to define themselves in terms of work. If we define ourselves by our jobs, our____22____depends on what we achieve. So when you are____23____what you want to be, it's not socially ____24____to say, “A father”, or, “A mother”, let alone, “A person of integrity”.The second____25____is the implication that there is one calling（使命）out there for everyone. Research shows that____26____one leaves students feeling lostand____27____.After all, not everyone has that talent for grand jobs.If you manage to____28____the above barriers，there is a third hurdle（难关）：Careers rarely live up to your childhood____29____. In one study, looking fora(n)____30____job left college seniors feeling more anxious and less satisfied withthe____31____.As Tim Urban writes, happiness is reality minus expectations. It's clear how expectations____32____our perceived happiness. If you are looking for extreme happiness, you're bound to be____33____Asking kids what they want to be leads them to ____34____a career identity they might never want to earn.____35____ ,invite them to think about the different things they might want to do.16．A．considered B．feared C．explained D．recalled 17．A．dreaming of B．objecting to C．focusing on D．sticking to18．A．average B．humble C．heroic D．romantic 19．A．prefer B．remember C．believe D．anticipate 20．A．harm B．good C．wrong D．honor 21．A．forces B．troubles C．commands D．forbids 22．A．status B．experience C．worth D．fame 23．A．taught B．asked C．guided D．consulted 24．A．rejected B．accurate C．confirmed D．acceptable 25．A．thought B．division C．assumption D．problem 26．A．picking up B．searchingfor C．praying for D．taking over 27．A．bored B．impatient C．intolerant D．confused 28．A．strengthen B．control C．build D．overcome 29．A．efforts B．struggles C．ambitions D．gains 30．A．ideal B．permanent C．ordinary D．specific 31．A．benefit B．outcome C．solution D．truth 32．A．boost B．contain C．guarantee D．affect 33．A．disappointed B．addicted C．delighted D．embarrassed 34．A．refuse B．claim C．keep D．ignore 35．A．Meanwhile B．Otherwise C．Instead D．However （2022·广东·汕头市聿怀中学模拟预测）Do you listen? Do you really listen? Is there more to listening than just hearing?Listening is, by far, one of the most important aspects of communication. So often, you pay attention to your way of speaking, your ____36____ , your dialect, but neglect your ability to listen.It is my ____37____ that people scream out or change the intended purposes of much of what they hear. Too often, we consider listening the ____38____ part of conversation, although it requires our focus, purpose, and active participation.Listening means to give ear to, to pay attention to, to ____39____ , to witness, to hear with thoughtful ____40____ , or to understand.The most basic of all human needs is the need to understand and to be understood. The only way to understand is to ____41____ .Learn to be an active listener. Give off positive body language.____42____ a willingness to socialize. Ask the right questions. Boost your ____43____ so that you can understand moreand achieve effective listening.Listening means we should respond, that we should be touched, that what we hear has a(n)____44____ on us. I believe that history _____45_____ itself only because no one listens the first time.You were given two ears, but only one mouth, which is a gentle hint that we should listen more, because God knew that listening was twice as _____46_____ as talking. Listening is the key building block in effective communications. Good listening skills are crucial, as listening is the fundamental _____47_____ of all information.Isn’t now the time to give the gift of listening to those about you? Given them your_____48_____ attention. Use your God given _____49_____ to become a better listener. For me, I’m going to put into _____50_____ what I believe in my heart and become a better listener.36．A．sounds B．words C．gestures D．movements 37．A．conception B．plan C．purpose D．requirement 38．A．active B．passive C．basic D．useless 39．A．argue B．quarrel C．discuss D．obey 40．A．advice B．attention C．love D．help 41．A．ask B．learn C．try D．listen 42．A．Send B．Present C．Predict D．Design 43．A．courage B．confidence C．energy D．knowledge 44．A．impact B．connection C．emotion D．difference 45．A．makes B．fails C．repeats D．destroys 46．A．interesting B．hard C．much D．long 47．A．resource B．material C．source D．element 48．A．considerate B．wide C．extra D．entire 49．A．information B．talents C．messages D．ideas 50．A．effect B．position C．practice D．service （2022·四川·石室中学模拟预测）China is taking a reform into account on its College Entrance Examination, under which two separate test modes-__51__and academic-will be introduced into the examination. Such reforms are badly needed, as the demand for highly-skilled professionals__52__sharply in the context of the country's economic restructuring.The test for technical mode will mainly__53__the technical skills of those students whoplan to become _54_and mechanical workers while the academic mode attracts those students who prepare to_____55_____an academic career.Calls for reform of the current gaokao regime, under which students are admitted based__56__upon their academic performance instead of practical skills, havebeen__57__high in China in recent years.___58___,the existing system has some merits, as it provides__59__fair opportunities for all students, especially those from the poor areas, to change their__60__through receiving higher education. But it has also been__61__for having churned out college graduates with little practical skills, something that prevented them from__62__decent jobs.Last year, China had 6.99 million college_63_, only 77.4 percent of which have found a position, according to official__64__.__65__,the fact that many college graduates cannot find a proper job doesnot__66__mean China has too many talents. In many sectors, enterprises can't__67__the technicians and skilled workers they need.According to a sample survey of__68__professionals in 40 cities conducted by the the Ministry of Labor and Social Security, technicians and highly skilled workers accountfor__69__4 percent of the labor force, __70__with an average 35 percent in developed countries.51．A．economic B．technical C．combined D．academic 52．A．rises B．falls C．changes D．turns 53．A．act on B．operate on C．reflect on D．focus on 54．A．teachers B．officials C．engineers D．writers 55．A．create B．cultivate C．know D．pursue 56．A．largely B．slightly C．totally D．wholly 57．A．standing B．keeping C．flying D．running 58．A．Admittedly B．Supposedly C．Excitedly D．Repeatedly 59．A．completely B．naturally C．relatively D．reasonably 60．A．past B．origin C．appearance D．fate 61．A．commented B．targeted C．enjoyed D．regarded 62．A．landing B．hiring C．doing D．liking 63．A．students B．graduates C．technicians D．employees 64．A．data B．guess C．media D．instruction65．A．However B．Therefore C．Anyway D．Furthermore 66．A．possibly B．importantly C．necessarily D．generally 67．A．find B．raise C．accept D．support 68．A．talented B．proficient C．retired D．dedicated 69．A．less than B．more than C．rather than D．other than 70．A．connected B．associated C．dealt D．compared （2021·上海普陀·一模）Imagine sitting inside a windowless train that's shooting through a tube at twice the speed of an airplane. Your train has no wheels, produces no____71____ , makes its own electricity, and isn't affected by bad weather. This is the hyperloop, a new vision for the world's ____72____ , safest, and greenest form of transportation. Many have ____73____ this new technology, but others say the hyperloop vision is just a bunch of hot air.Hyperloop developers plan to use the properties of magnets to float, stabilize, and drive the capsules or pods for hundreds of miles through ____74____ tubes. Without air or ground to slow down the vehicles, what was once a five-hour journey would become a half-hour excursion, engineers promise.Supporters of the technology promote additional ____75____ of transporting passengers and cargo by hyperloop. For example, they firmly state that unlike other city-to-city transport that's ____76____ , such as planes or trains, hyperloop vehicles would leave as needed, like Ubers and taxis. While the ____77____ would hold only 28 to 50 passengers each, developers plan for them to depart stations in groups every minute or so which they say could amount to shuttling 50,000 people an hour. That's more than twice the passenger ____78____ of the world's fastest trains.Developers also say that hyperloop tubes would be ____79____ so they wouldn't interfere with other traffic or threaten wildlife. And tubes would be covered with solar panels to power the hyperloop's systems. ______80______ , advocates regard the hyperloop as the transportation choice for the future.But not everyone is on board. Engineers have calculated that the high-speed vehicles will need to make much wider turns than currently envisioned, and otherwise they won't be ______81______ for passengers. This would add several miles to the proposed tube tracks, Engineers also say planners haven't included enough time for vehicles to safely brake and take off at stations. Some engineers believe it will take much longer than claimed to pump the______82______ out of the tubes before each vehicle's departure. Critics thus say hyperloops can't go as fast or serve as many passengers per hour as advertised, making them______83______ existing high-speed transportation options.Hyperloop companies say they're ______84______ these concerns. They claim that they can safely maintain high speeds by having the vehicles bank around the turns as a plane does. And their hyperloops will rely on the split-second reaction times of a computer to______85______ vehicles quickly, frequently, and safely.71．A．pollution B．sound C．energy D．wind 72．A．cleanest B．lightest C．latest D．fastest 73．A．adapted B．exploited C．embraced D．developed 74．A．totally hollow B．nearly airless C．steadily narrow D．highly flexible 75．A．advantages B．costs C．qualities D．situations 76．A．in constant demands B．on strict timetables C．in changeable states D．on essential services77．A．cabins B．lorries C．tubes D．vehicles 78．A．fare B．capacity C．speed D．comfort 79．A．underground B．parallel C．elevated D．shared 80．A．However B．Therefore C．Beside D．Otherwise 81．A．available B．economic C．easy D．safe 82．A．force B．air C．heat D．water 83．A．most popular of B．superior to C．no better thanD．least profitable of84．A．addressing B．causing C．voicing D．releasing 85．A．ride B．pilot C．park D．alert （2021·上海长宁·一模）Hugely ambitious in scope, The Lord of the Rings occupies an uncomfortable position in 20th century literature. This book of J.R.R.Tolkien’s poses a challenge to modern literature and its defenders. (Tolkien on his ___86___: “Some who have read the book, or at any rate have reviewed it, have found it boring, ridiculous, or annoying; and I have no cause to complain, since I have similar opinions of their works, or of the kinds of writing that they evidently ____87____.”) Yet The Lord of the Rings has enjoyed massive and enduring popularity. It would seem that Tolkien’s work supplied something that was____88____ among the formal innovations of 20th century fiction, something for whichreaders were hungry. But what was it, and why was it important?It seems that the key point lies in Tolkien’s wholehearted rejection of modernity and modernism. This is what so powerfully ____89____ some readers, and just as powerfully drives away others. In his book J.R.R.Tolkien: Author of the Century, T.A．Shippey expands on this idea by arguing that Tolkien saw his story of Middle-earth not as fiction or invention, but as the ____90____ of something genuine that had become buried beneath the fairy tale and nursery rhythm.“However fanciful Tolkien’s creation of Middle earth was,” Shippey writes, “he did not think that he was entirely ____91____. He was ‘reconstructing’, he was harmonizing conflicts in his source-texts, sometimes he was supplying entirely new concepts, but he was also reaching back to an imaginative world which he believed had once really ____92____, at least in a collective imagination.”The book is also deeply grounded in Tolkien’s linguistic expertise （语言专长）—he ____93____ whole languages for his characters. Sometimes he became so absorbed in the creation of languages, in fact, that he ____94____ the story itself for months or years at a time, believing he could not continue until some inconsistency（不一致）in his invented world had been resolved. But Tolkien’s great intellect and knowledge is not the source of his ______95______; without his storytelling gift, The Lord of the Rings would be little more than a curiosity. And this gift seems to originate straight from his ______96______ to break from classical and traditional forms.Tolkien himself often spoke of his work as something ‘found’ or ‘discovered’, something whose existence was ______97______ of him. It’s wise to be careful with this sort of interpretation, but it seems ______98______ that he believed his work to be something given, something revealed, which contained a kind of truth beyond measure. ______99______, his details have the weight of reality, and because of this his great sweep of story feels real as well; you might say that his ______100______ castles are built with a certain amount of genuine stone.86．A．books B．critics C．readers D．ambitions 87．A．dislike B．challenge C．review D．prefer 88．A．common B．possible C．missing D．funny 89．A．annoys B．influences C．attracts D．concerns 90．A．recovery B．designing C．analysis D．questioning91．A．taking it down B．making it up C．turning it down D．looking it up 92．A．remained B．struck C．moved D．existed 93．A．spoke B．invented C．neglected D．recalled 94．A．put aside B．set up C．look into D．get along 95．A．style B．tension C．success D．tradition 96．A．decision B．request C．struggle D．refusal 97．A．representative B．independent C．conscious D．thoughtful 98．A．clear B．weird C．unfair D．pitiful 99．A．As a result B．On the contrary C．Even so D．What’s worse 100．A．ancient B．broken C．imaginary D．foreign （2021·四川广安·模拟预测）What will you become in the future depends a lot on what you are doing to yourself now. You don't need a fortune____101____to tell you what your future life will be.You can be brilliant, unforgettable or interesting____102____you believe that you are the____103____of yourself. Once you know what you want to achieve, each little stepyou____104____everyday will bring you closer to your goal. The books you have read, the television programmes that you have____105____to watch and the type of people you have met are what____106____you when you choose to create the type of person youwill____107____in the future.Don't____108____that life is easier. Don't let others get you____109____and stop you from achieving what you_____110_____to achieve. Be in charge ofyourself_____111_____as you move towards your life goal, you will get agreat_____112_____. Don't_____113_____and let luck determine yourfuture._____114_____about life and your surroundings will not earn you_____115_____.Tell yourself that you are in_____116_____and the world will not be able to hold back a person on a_____117_____path. The best golf players always are in the golf field and the best swimmers are always found in the_____118_____. They understand that they are the creators of their own self in the future.Learn to be_____119_____. Go and discover your unique qualities and learn to move away from your _____120_____ zone. Take vigorous(果断的)action.Remember, you are the creator of yourself.101．A．writer B．reporter C．teller D．professional102．A．as long as B．even if C．in case D．as though 103．A．producer B．creator C．supporter D．adviser 104．A．take B．move C．develop D．adjust 105．A．advised B．elected C．chosen D．made 106．A．promote B．represent C．protect D．guide 107．A．follow B．become C．admire D．copy 108．A．hope B．suspect C．imagine D．risk 109．A．up B．down C．off D．away 110．A．set aside B．make out C．set out D．make of 111．A．then B．and C．or D．but 112．A．harvest B．goal C．success D．happiness 113．A．look B．stop C．wait D．sit 114．A．Quarrelling B．Concerning C．Arguing D．Complaining 115．A．something B．anything C．nothing D．everything 116．A．person B．danger C．relief D．charge 117．A．rough B．muddy C．successful D．beautiful 118．A．playground B．pool C．court D．camp 119．A．brave B．intelligent C．grateful D．calm 120．A．effort B．dislike C．attitude D．comfort （2021·河北邯郸·三模）It is almost impossible to be left alone in a digital world, where people are meant to be connected. In this respect, digital technologies have ___121___ our life.The possibility to be connected all the time has brought our personal space to a(n)___122___ as we've known it. People have become so ___123___ in the world of networks that one can often be contacted even if they'd rather not be. Today we can talk, text and e-mail, not only from our ___124___, but from our mobile phones as well.Most people have become ___125___ on digital technology simply because it has become a necessary part of life, and at this point not ___126___ it would make them an social outsider. ___127___, many jobs and careers require people to be connected. From this point of view, being reachable might feel like a ___128___ to those who may not want to be able to be contacted at all times.But solitude(独处) still can be possible for those who ___129___ want it. Computers canbe ____130____ and mobile phones can be turned off. Of course, the choice to be “off” and “on” has many ____131____ as well as disadvantages. When travelers end up ____132____ in mountains, and mobile phones can mean life or death, although they can also make people feel ____133____ and forced to answer unwanted calls.Actually, attitudes towards digital technologies as a society ____134____ widely. Some find them a gift. Others consider them a curse. Whether you like it or not, it's hard to imagine what life would be like without the ____135____ in digital technologies.121．A．reshaped B．respected C．ignored D．preserved 122．A．alarm B．stage C．end D．balance 123．A．sensitive B．intelligent C．considerate D．reachable 124．A．neighbors B．computers C．friends D．monitors 125．A．impressed B．hard C．dependent D．focused 126．A．finding B．using C．protecting D．changing 127．A．Also.B．Instead.C．Otherwise.D．Therefore. 128．A．pleasure B．benefit C．burden D．shame 129．A．slightly B．barely C．merely D．really 130．A．sold out B．broken up C．shut down D．joined in 131．A．aspects B．advantages C．weaknesses D．exceptions 132．A．hidden B．lost C．relaxed D．deserted 133．A．trapped B．excited C．confused D．amused 134．A．vary B．arise C．spread D．exist 135．A．hopes B．tests C．interests D．achievements参考答案：1．D2．B3．C4．B5．C6．A7．D8．A9．A10．C11．D12．A13．D14．B15．C【解析】【分析】本文是一篇议论文。
英国中小学国际理解教育课程建设策略
Cover Story封面故事20为了应对全球化时代的挑战，各国都非常重视在全球化背景下来构建学校的课程体系，以培养学生的全球素养。
进入21世纪以来，英国日益强调在中小学推行国际理解教育，颁布了一系列有关国际理解教育课程的政策文件，提供了各种项目支持，并采取了灵活多样的国际理解教育课程实施方式，从而建立起了相对完备的中小学国际理解教育课程体系。
颁布国际理解教育课程政策文件英国推动中小学国际理解教育发展的主要机构有教育与技能部（Department for Education and Skills，简称DfES，后更名为教育部）、国际发展部（Department for International Development，简称DFID）、资格与课程局（Qualification and Curriculum Authority，简称QCA）、发展教育协会（Development Education Association，简称DEA）、英国文化教育协会（British Council）、乐施会（Oxfam）等政府部门及非政府组织。
这些机构围绕着“培养全球公民”这一核心目标，相继颁布了国际理解教育课程相关文件，阐明了国际理解教育的要素及国际理解教育课程的实施和评价方式等，在指导中小学开展国际理解教育方面作用显著。
2000年，教育和技能部、发展教育协会和国际发展部联合颁布《开发学校课程中的全球维度：课程及标准指南》（Developing a Global Dimension in the School Curriculum—Guidance：Curriculum & Standards，以下简称《指南》），并于2005年对《指南》进行了修订，将其分发到英国的所有学校。
《指南》提出，中小学课程要融入八个国际理解教育的关键概念—多样性、全球公民意识、冲突解决、社会公正、价值和观念、可持续发展、相互依存和人权，并阐明了在中小学课程中渗透这些理念的具体途径，以及通过建设校园文化来全方位开展国际理解教育的方法。
初三英语梦想职业规划练习题40题
初三英语梦想职业规划练习题40题1<背景文章>Being a doctor is one of the most noble and challenging professions. Doctors play a crucial role in society by taking care of people's health. A doctor's work involves diagnosing illnesses, prescribing treatments, and providing preventive care.Doctors need to have extensive knowledge of medicine. They study for many years to learn about the human body, diseases, and treatment methods. They also need to have excellent communication skills to explain medical conditions and treatment options to patients.The job of a doctor can be very demanding. They often work long hours, including evenings and weekends. They may have to deal with emergencies and make quick decisions. However, being a doctor also offers many rewards. Doctors have the satisfaction of helping people recover from illnesses and improve their quality of life.The field of medicine is constantly evolving, and doctors need to keep up with the latest research and technologies. This requires continuous learning and professional development. In the future, with the advancement of medical science, there will be even more opportunities for doctors to make a significant impact on people's health.1. What is the main role of doctors?A. Teaching people about health.B. Diagnosing illnesses and prescribing treatments.C. Doing research on diseases.D. Selling medicines.答案：B。
On the Benjamini--Hochberg method
ON THE BENJAMINI–HOCHBERG METHOD
By J. A. Ferreira1 and A. H. Zwinderman
University of Amsterdam
We investigate the properties of the Benjamini–Hochberg method for multiple testing and of a variant of Storey’s generalization of it, extending and complementing the asymptotic and exact results available in the literature. Results are obtained under two different sets of assumptions and include asymptotic and exact expressions and bounds for the proportion of rejections, the proportion of incorrect rejections out of all rejections and two other proportions used to quantify the efficacy of the method.
Research Approach Strategies
Research Approach StrategiesResearch approach strategies are essential for conducting successful and impactful research. There are several different approaches that researchers can take, each with its own strengths and weaknesses. In this response, I will explore various research approach strategies, including quantitative, qualitative, and mixed methods approaches, and discuss the benefits and challenges of each. Additionally, I will examine the importance of selecting the most appropriate research approach based on the research question and objectives, as well as the potential impact of the chosen approach on the research outcomes.Quantitative research approach is a systematic investigation that uses statistical, computational, or mathematical techniques to collect and analyze data. This approach is often used to quantify attitudes, behaviors, and other defined variables, and to generalize results from a larger sample to a population. One of the main strengths of quantitative research is its ability to produce reliable and generalizable findings, which can be particularly useful for making evidence-based decisions in various fields such as medicine, psychology, and sociology. However, a potential challenge of this approach is that it may oversimplify complex phenomena and fail to capture the richness and depth of human experiences.On the other hand, qualitative research approach is a method of inquiry that focuses on understanding and interpreting the meanings of social phenomena. This approach involves collecting and analyzing non-numerical data, such as interviews, observations, and textual analysis, to uncover patterns, themes, and insights. Qualitative research is valuable for exploring complex social issues, understanding individual perspectives, and generating new hypotheses. Nevertheless, one limitation of qualitative research is its potential for subjectivity and lack of generalizability, which may raise concerns about the validity and reliability of the findings.In contrast, mixed methods research approach combines elements of both quantitative and qualitative approaches to provide a more comprehensive understanding of a research problem. By integrating diverse data collection and analysis techniques, mixed methods research can offer a more nuanced and holistic perspective, addressing the limitations ofeach approach while leveraging their respective strengths. However, conducting mixed methods research requires expertise in both quantitative and qualitative methodologies, as well as careful planning to ensure the integration of data and interpretation of results.The selection of the most appropriate research approach depends on the nature of the research question, the objectives of the study, and the context in which the research is conducted. It is crucial for researchers to carefully consider the strengths and limitations of each approach and to align their choice with the specific requirements of their research. Additionally, the impact of the chosen research approach on the research outcomes should be taken into account, as different approaches may lead to different conclusions and implications for practice, policy, or further research.In conclusion, research approach strategies play a pivotal role in shaping the design, implementation, and outcomes of research. Each approach has its own unique strengths and limitations, and the selection of the most appropriate approach should be guided by the research question, objectives, and context. By carefully considering the potential impact of the chosen approach on the research outcomes, researchers can ensure that their research is rigorous, relevant, and impactful.。
蚯蚓生态毒理试验在土壤污染风险评价中的应用_颜增光
蚯蚓生态毒理试验在土壤污染风险评价中的应用颜增光1,何巧力1,2,李发生1*1.中国环境科学研究院土壤污染与控制研究室,北京 1000122.哈尔滨工业大学市政环境工程学院,黑龙江哈尔滨 150090摘要:蚯蚓是评价土壤环境质量的重要指示生物.近年来,蚯蚓生态毒理学取得了快速的发展,诞生了许多新的毒理测试技术和评价方法.概述了当前广泛采用的蚯蚓毒理试验方法,重点介绍毒性试验、种群动态调查、回避试验、生物富集试验、生物标志物试验的原理与特征,论述了各种试验方法在土壤污染环境监测和生态风险评价中的应用,并探讨了蚯蚓生态毒理学未来的发展与应用前景.关键词:蚯蚓;生态毒理学;生态风险评价;土壤污染中图分类号:X53;X17115 文献标识码:A 文章编号:1001-6929(2007)01-0134-09The Use of Earthworm Ecotoxicolo gical Test in Risk Assessmen t of Soil Con taminationYAN Zeng -guang 1,HE Qiao-li 1,2,LI Fa -sheng11.Depart ment of Soil Pollution Control,Chinese Research Academy of Environmental Sciences,Beijing 100012,China2.School of Municipal and Environmental Engineering,Harbin Institute of Technology,Harbin 150090,ChinaA bstract :Earthworm is one of the most important biological indicators of soil qualit y.Earthworm ecotoxicology has made rapid progress in the past years,and a number of test methods and approaches have been developed.The authors provided an overview of establis hed or standardized earth worm tests,including toxicity test,survey of population dynamics,avoidance test,bioaccu mulation test and biomarker test,and gave a brief introduction to their application in monitoring and risk assessment of soil contamination.Moreover,the prospect and future development of earth worm ecotoxicology were discussed.Key words :earthworm;ecotoxicology;ecological risk assessment;soil contamination收稿日期:2006-11-08基金项目:国家重点基础研究发展计划(973)项目(2004CB418501);国家社会公益性专项(2005DIB3J161)作者简介:颜增光(1972-),男,广西横县人,博士后.*责任作者土壤污染是一个世界性的环境问题.土壤的污染程度和污染效应需要通过环境调查和监测来进行评价,其中生态风险评价是评估和表征污染物生物效应的一种常见方法,用于试验的生物包括动物、植物和微生物,蚯蚓便是其中的标准化测试物种之一.蚯蚓属环节动物门寡毛纲(Oligochaeta),是土壤中生物量最大的无脊椎动物,其在地球物质循环和陆地生态系统食物链物质传递中担负着重要功能,是最易受到环境有毒有害物质伤害的土壤生物之一,因而也是开展土壤污染生态风险评价的重要指示生物[1].蚯蚓毒理试验已广泛应用于对土壤生态环境进行监测和评价,尤其在污染土壤环境风险分级、污染物土壤质量标准与基准的制定、特定污染场地环境风险评价、污染场地修复效果评价等方面有重要的应用价值.近年来,蚯蚓生物标志物作为对污染物低剂量暴露效应的早期检测方法也得到了快速的发展,蚯蚓溶酶体、胁迫蛋白、金属硫蛋白、靶标酶、代谢和解毒酶等已成为检测土壤污染的常规生物标志物,单细胞凝胶电泳(彗星电泳)和DNA 加合物分析也已被广泛用于检测土壤污染物潜在的致癌、致畸、致突变效应.为适应蚯蚓生态毒理研究的快速发展,国际上已于1991,1997和2001年分别在英国的谢菲第20卷 第1期环 境 科 学 研 究Research of Environmental SciencesVol.20,No.1,2007DOI ：10.13198/j.res.2007.01.136.yanzg.026尔德、荷兰的阿姆斯特丹和丹麦的奥尔胡斯召开了3次专题学术会议,讨论与交流蚯蚓生态毒理学的研究进展与发展.笔者主要概述蚯蚓生态毒理试验在土壤污染风险评价中的应用,从种群、个体、细胞、生化和分子等多层次、多水平上探讨蚯蚓毒理试验和生物标志物在土壤污染监测、土壤修复效果评价和土壤生态功能诊断上的应用前景和发展方向.1蚯蚓毒性试验在土壤污染监测与修复效果评价中的应用用于土壤生态毒理试验的蚯蚓主要来自后孔寡毛目的正蚓科(Lumbricidae),巨蚓科(Megascolecidae)和真蚓科(E udrilidae),常见的有赤子爱胜蚓(Eisenia fetida),安德爱胜蚓(Eisenia andrei),维尼斯爱胜蚓(Eisenia veneta),红正蚓(Lumbricus rubellus),陆正蚓(Lum bricus terrestris),背暗异唇蚓(Allolobophora caliginosa),Allolobophora chlorotica,Allolobophora tuberculata,Octolasium cyaneum,红丛林蚓(Dendrobaena rubidus),Eudrilus eugeniae,Perionyx ex cavatus,Pheretima posthuma,Octochaetus pattoni,长流蚓(Aporrectodea longa),背暗流蚓(Aporrectodea caliginosa)等10多种.这些蚯蚓是欧洲、北美、非洲、南亚次大陆和亚洲的广布种或本地种,其中最常用的是生活于腐殖质或富含有机质环境中的赤子爱胜蚓(E.fetida)和安德爱胜蚓(E.andrei).国际上已有多种用于开展蚯蚓毒性试验的标准化测试方法,如经济合作与发展组织(OE CD)修订和颁布的试验室测定化学物质对蚯蚓毒性的指导性文件[2)3],国际标准化组织(I SO)制定和颁布的一系列测定蚯蚓急性毒性、亚急性毒性、发育毒性、生殖毒性、回避行为试验、蚯蚓种群野外调查等标准化的试验方法[4)8].其他国家或地区也有自行制定的测试标准,如美国测试与材料学会(ASTM)的/试验室利用蚯蚓开展土壤毒性测试指南0[9],欧洲经济共同体(EE C)的/利用人工土壤测试蚯蚓的毒性0[10].目前,这些方法已被广泛应用于对有毒有害危险性物质的毒性监测和对污染土壤的生态风险评价.蚯蚓急性(致死)毒性和亚急性(亚致死)毒性试验是开发最早、技术最成熟的蚯蚓生态毒理试验.急性毒性试验以蚯蚓14d(或7d)的死亡率为测试终点,用引起蚯蚓半数死亡的致死中浓度(LC50)来表征污染物的毒性;亚急性毒性试验多以蚯蚓的体重(生物量)变化、繁殖量(产茧量)、茧孵化率和幼蚓存活率等作为测试终点,常用引起50%效应的有效中浓度(E C50)来表征污染物的毒性效应,也有用最低可见效应浓度(LOE C)或无可见效应浓度(NOE C)来表征污染物毒性的.这2种毒性试验因具有能够直接反映土壤的污染状况,所需测试设备相对简单,易于操作,耗费较低,有国际标准支撑,有质控程序控制系统的变异性,测试结果具有直接的生态相关性等优点,在土壤污染监测与毒性评价上得到了广泛应用,如对土壤中石油烃污染[11)12]、多环芳烃污染[13]、重金属的单一或复合污染[14)15]、农药污染[16]、爆炸物TNT污染等的监测[17].同时,蚯蚓急性和亚急性毒性试验也普遍用于对污染土壤修复效果进行评价,包括被重金属[18]、石油烃和多环芳烃[19]、农药[20]、爆炸物TNT等物质污染的土壤[21].此外,蚯蚓毒性试验还可用于对污染土壤的潜在生态风险进行归类和分级,也可为土壤质量基准与标准的制定提供基础毒理数据,如美国能源部橡树岭基地根据蚯蚓毒理数据构建了化合物的筛查基准[22],这为土壤污染化学监测与蚯蚓毒性评价的结合应用提供了有力的工具.2蚯蚓群落结构和种群密度对污染土壤生态功能的指示蚯蚓的种群密度调查和群落结构分析也可用于对污染土壤的生态功能进行动态指示,考察的终点包括群落的结构与组成、物种的多样性与丰度、种群的生物量、成P幼蚓比率等.目前已有多种用于蚯蚓野外调查的采样技术与方法,除传统的手拣法外,国际标准化组织还推荐了福尔马林、芥子毒气和电击提取等方法[6,8].利用蚯蚓种群调查评价土壤污染状况的应用实例还相对较少[23)26],用于污染土壤修复效果评价的也不多[27],原因可能是种群水平上的室内模拟试验(如微宇宙试验)或野外调查成本相对较高.由于土壤的异质性和蚯蚓固有的群集习性,使得野外调查或室内模拟试验均需要较大的样本量或重复数,并要求参加野外调查的人员有较高的动物分类学专业知识.目前,蚯蚓微宇宙试验还处于初步研究阶段,大多只局限于对化合物的毒性进行评价,还很少用于对野外污染土壤进行评价.然而,微宇宙试验提供的信息对于暴露评价可能更为真实,并且是可以测试间接毒性的少数几种测试技术之一.利用蚯蚓种群密度评价土壤污染的长期效应较为复杂,其结果受到多种生物和非生物因素的影响,波动性很大,不但个体的死亡可以引起种群密度的降低,蚯蚓达到生殖成熟所需要的时间、繁殖率、个135第1期颜增光等:蚯蚓生态毒理试验在土壤污染风险评价中的应用体的迁移率等都可以影响到特定场地中蚯蚓的种群密度大小[28].污染物对蚯蚓某一生理参数的影响也可能会通过其他参数的变化来发生补偿,如没有死亡的蚯蚓可能会通过增加后代的繁殖量(即增加种群的内禀增长率)来补偿和维持种群的密度.利用年龄结构模型预测蚯蚓的种群动态可能是一种较好的解决方法[29],但是这样的模型仍然需要通过野外调查来确认和优化参数方能奏效.在复杂的生态系统中,有时仅凭形态分类鉴定来描述污染物引起的蚯蚓种群多样性变化或丰度变异还是不够的,若能利用遗传多样性分析来表述种群结构的变化可能更为精确[30].由此可见,要在种群水平上实现对污染土壤的监测与评价,还需要探索和积累更多有关布点策略、采样技术、鉴定方法、监测周期等基本知识,在弄清蚯蚓的物种分布特征、生活史和生活习性、发生世代、繁殖规律、响应机理等的基础上,通过构建合理的评价模型,不断验证和优化评价参数,才能最终实现在种群水平上对特定污染场地进行准确的监测与评价.3蚯蚓回避试验及其在污染土壤生态功能评价中的应用国际标准化组织最近公布了利用蚯蚓回避试验检验土壤质量和化合物对蚯蚓行为效应的测试方法[7],该方法以蚯蚓48h的行为选择反应作为测试终点,评价土壤的栖息功能和蚯蚓对污染物的行为效应,推荐使用的参比化合物为硼酸(H3B O3),测试器具可根据试验需要选择二室或六室行为观测仪.事实上,自然界中的动物普遍利用化学信息来召唤同伴、寻求配偶、寻觅食物和寻找栖息地,同样地,动物也可通过化学信息感知不利的栖息环境或有毒有害物质,除非它们被高剂量毒物瞬时击倒或杀死,否则它们往往会对超出其忍受范围的不利条件和因素表现出回避反应.因此,从功能学的观点来看,动物的回避行为反应可以直接指示土壤质量功能的下降或已受到了限制,间接表明土壤可能已经受到污染或具有潜在的生态风险[31].已有研究证明,蚯蚓回避试验适用于检测土壤中的原油、矿物油、多环芳烃等石油类污染物,功夫菊酯、代森锰锌、本菌灵、多菌灵等农药,锰、锌、铜或其他重金属的混合物,以及TNT,KCl,NH4Cl,胺和乙二醇的混合物、冷凝剂等多种污染物[7],其敏感性高于急性毒性试验,也高于或至少等同于亚急性毒性试验中的生殖毒性试验[32)33],如蚯蚓回避试验对TNT污染土壤的响应质量浓度为29mg P kg[34],而急性毒性试验测定的LC50值为143mg P kg.蚯蚓回避试验已成功应用于对现实污染土壤的环境风险预测[24,35],其结果的稳定性优于跳虫的行为反应[36].此外,蚯蚓的其他行为反应,如爬行和移动、钻蛀和挖掘、取食和清除落叶等行为,也常用于对化合物的毒性和土壤污染进行评价,如在亚致死剂量(015和1mg P kg)吡虫啉(杀虫剂)污染的土壤中,2种蚯蚓Allolobophora icterica和Aporrectodea nocturna的钻蛀行为均有明显的变化[37].然而,由于蚯蚓爬行、钻蛀、取食等行为的复杂性,测试结果变异性大,评价参数(如钻蛀深度、钻蛀频率、钻蛀面积、摆动频率、所挖掘孔洞的形状和结构、取食次数和取食量等)也不易于进行统一定量和准确评价,因此在土壤污染评价中的使用还很有限,而回避行为试验由于成本低廉、易于观测与操作、试验周期短、反应灵敏度高、适于检测的污染物范围广、测试终点具有生态相关性等优点,加之有国际标准的支持,可以预见其在土壤生态功能评价中将是一种很有前途的测试工具[38],未来的工作倾向于筛选和鉴定出更多适于开展回避试验的蚯蚓种群和适于用该方法检测的污染物[39],以及对蚯蚓的化学感受特征和感受机理进行深入的研究.4蚯蚓对污染物的生物富集与污染土壤生态风险预测单纯依靠测定土壤中污染物的总浓度来评价土壤的环境质量并不科学[40].土壤、污染物和生物的相互作用是一个复杂的过程,污染物在土壤中的赋存形态,污染物与土壤的结合残留,生物体对污染物的暴露方式与途径,生物体自身的生理活动与代谢特点等,都可影响到污染物进入生物体的过程和在其中滞留的水平,这可以通过生物富集研究来测定和反映.生物富集(bioaccumulation)是指环境物质进入生物机体或组织,并引起累积、残留、富集等效应的过程.蚯蚓可从土壤中摄取多种有机和无机污染物,它是研究土壤污染物生物有效性的经典动物,其在评价不同形态的重金属生物可利用性上尤为多见[41)42].通过测定蚯蚓整体或特定组织中污染物的浓度,再与土壤中相应污染物的浓度进行比较,可以计算出污染物在蚯蚓体内的生物浓缩因子(BCF)或生物富集系数(BAF),从而确立污染物的生物有效性[43].利用浓缩因子或富集系数,可以对直接测定的土壤污染物浓度进行生物有效性换算和预测污染136环境科学研究第20卷土壤的潜在生态风险,或用于对污染土壤修复效果进行评价[44].目前,已有多种预测模型和仿生技术被开发用于生物富集研究[45)48],如半透性滤膜(SPMD),C18材料,固相微萃取(SPME)技术等,也有人提出利用/临界机体残留(CBR)0方法来评价土壤环境质量[49].美国测试与材料学会(ASTM)已公布了关于试验室开展蚯蚓生物富集试验的标准草案[50],经济合作与发展组织(OECD)也在制定类似的标准[51].除受污染物浓度的直接影响外,污染物的结构和性质[52]、土壤的性质(尤其是pH,有机质含量,阳离子交换力)、蚯蚓的种类和发育阶段[52)53]、生活习性[54)55]、栖居环境与暴露途径等[56],都对污染物的生物富集有很大的影响.尽管生物富集水平与土壤的污染状况有直接的关联,但由于存在物种间响应的差异和污染物提取技术上的多样化,加之生物的耐受能力、解毒能力、排泄速率等的差异,生物富集研究往往具有很大的变异性[57)58].此外,污染物在蚯蚓体内的浓度与其毒性并非总是直接相关,因此生物富集研究只有与毒性测定结合起来进行,才能更为有效地评价污染物的环境行为与生物效应[43],从而对污染土壤的生态风险做出准确的预测.5蚯蚓生物标志物用于土壤污染暴露的早期预警和风险评价近年来,生物标志物的研究得到了迅速的发展,并被强烈推荐用于对环境中污染物的暴露评价或生物效应的检测[59].然而,目前在生态毒理学领域对生物标志物的概念还颇有争议,还没有统一的或被普遍接受的定义,通常生物体在个体或者更为微观的水平上(如组织、细胞、分子)的生理、生化、分子或遗传反应都可视为生物标志物反应(biomarker response).生物标志物最大的优点是可以灵敏地检测到环境中低剂量的潜在污染物,并可通过多项反应指标提供有关环境毒性的综合信息.生物标志物可用作评价土壤污染的早期预警系统[60],部分生物标志物对特定化合物或化学基团还表现出特异的反应,如动物的乙酰胆碱酯酶受抑制往往意味着其对类胆碱功能的农药(如有机磷类、氨基甲酸酯类等)有暴露史,但有的生物标志物可能会对多种结构上并不相关的化合物都有响应,如生物体内广泛存在的多功能氧化酶(MFOs)对外源异生物质就具有普遍反应性.蚯蚓生物标志物是用于检测和评价土壤污染的常用手段之一,尤以溶酶体,金属硫蛋白,热休克蛋白,总免疫力,胆碱酯酶,多功能氧化酶,DNA 损伤等最为常用.蚯蚓体腔细胞溶酶体是应用最多、也是最成熟的蚯蚓生物标志物[61],可以通过判断溶酶体膜的稳定性(利用中性红染料保留时间来判断)来表征蚯蚓受到的污染胁迫.溶酶体是由高尔基体的囊泡发育而成的亚细胞结构(细胞器),内含多种水解和消化酶系,溶酶体可通过吞噬方式消化、溶解部分由于损伤而丧失功能的细胞器和其他细胞质颗粒或经细胞摄入的外源物质.蚯蚓体腔细胞内的溶酶体能很快地吸收、容留和积累中性红染料,当蚯蚓受到污染物的伤害时,其溶酶体膜会变得脆弱和容易发生泄漏,溶酶体摄取的中性红染料就会释放到细胞质中,将细胞染成红色,用溶酶体中性红保留时间(NRRT)即可反映污染物对蚯蚓的毒性效应[62].蚯蚓溶酶体膜稳定性试验已较多用于对重金属污染土壤的监测与评价中[14,23,63)65],对农药,石油烃,多环芳烃,TNT,奥克托金(H MX)等土壤污染物的评价也有报道[12,17,66)68].蚯蚓溶酶体对土壤污染的反应敏感性一般要高于毒性试验中的死亡率、体重变化、产茧量、茧孵化率、幼蚓生还率等测试终点,有时甚至高于免疫活力和酶活性检测[69],且可用于对污染场地进行原位监测[70)71],因而是一种应用潜力巨大的生物标志物[61],但其成本与效益的权衡,以及在预测个体健康状况上的相关性还有待于进一步探究.金属硫蛋白(metallothioneins)具有解毒和调节机体内微量元素平衡的双重功能,其可被多种金属所诱导,因而可作为检测金属污染的生物标志物,具有很强的特异性.蚯蚓金属硫蛋白的表达多采用免疫反应(抗原-抗体反应)进行检测,最近也有报道从基因转录等分子水平上检测金属硫蛋白的表达变化[72].目前,蚯蚓金属硫蛋白已成功应用于对镉、铜、锌等重金属暴露的评价[72)76],证明其适用于对土壤中重金属污染进行特异性诊断.与金属硫蛋白不同,热休克蛋白(heat shock protein,Hsp)可为多种污染物所诱导,其中也包括重金属.热休克蛋白最初是在果蝇的唾液腺中作为一种对热反应的应激蛋白被发现的,后来的研究证明其对多种胁迫因素都有反应[77],因而也是检测土壤污染的生物标志物,最多采用的是Hsp70和Hsp60.蚯蚓热休克蛋白已用于氯乙酰胺,五氯酚,重金属铜、铅、锌、镉、汞等土壤污染物的暴露评价中[75,78],但由于热休克蛋白的应答缺乏特异性,且易于受到各种环境因子的影响,其137第1期颜增光等:蚯蚓生态毒理试验在土壤污染风险评价中的应用在土壤污染诊断上的应用还有待于进一步优化和改进.蚯蚓体内存在多种可受污染物抑制或对污染物的诱导有响应的酶系,包括调控基础代谢与生理活动的功能酶系、对外源物质具有降解作用的解毒或水解酶系,以及其他具有防御功能的酶系如抗氧化酶、溶菌酶等.由于这些酶系在生化水平上能对污染暴露做出敏锐的响应,因而也是检测土壤污染的有益标志物.蚯蚓的乙酰胆碱酯酶(AchE)是有机磷、氨基甲酸酯类农药作用的靶标,污染物的存在可明显抑制蚯蚓乙酰胆碱酯酶的活性,这对于检测农药在土壤中的残留与污染十分有效[79,26],并且是少数几种具有较强特异性的生物标志物之一,不过也有报道重金属(铅和铀)可以抑制蚯蚓的乙酰胆碱脂酶[80],但多环芳烃中的苯并[a]芘似乎对其活性没有影响[81].细胞色素P450酶系是生物体内多功能氧化酶的重要组成部分,在底物的诱导下可快速、大量地表达,催化外源化合物发生氧化降解和解毒,作为生物标志物在环境监测与预报上有重要的意义.蚯蚓P450酶系可用于对土壤中的有机污染物如多环芳烃等进行监测[82],具有敏锐响应和早期预警等功能,缺点是反应没有特异性,蚯蚓的发育阶段和生理状况以及环境因子对酶的活性影响也很大,蛋白的提取纯化技术和测定方法也相对复杂和繁琐,影响酶活性测定的准确性.蚯蚓体内的其他代谢酶如磷酸酯酶,B-半乳糖酶,纤维素酶,NADH和NADPH还原酶等也曾作为生物标志物用于对土壤污染物的监测与评价[16,81,83].污染物的胁迫也会损害或破坏生物体内的代谢平衡,引起代谢产物的积累和活性氧等有害物质的过量产生,生物体对此可启动防御系统如抗氧化酶系等来抵御和清除这些物质,因此抗氧化酶活性的变化可以间接反映环境中污染物的存在,是预测预报污染物生态风险的敏感生物标志物.目前,蚯蚓体内的过氧化氢酶(C AT)、谷胱甘肽-S-转移酶(GST)等已被证实可对多环芳烃、杀虫剂、除草剂、重金属等做出响应[66,74,79,81],预示着蚯蚓抗氧化酶系作为生物标志物具有广阔的应用前景.在种类繁多的生物标志物中,最能真实反映污染物生态风险和真正实现早期预警功能的是表征污染物遗传毒性或突变效应的生物标志物,这在人体健康风险评价中已得到了证实[84].利用蚯蚓细胞研究污染物遗传毒性的常用技术包括单细胞凝胶电泳(彗星电泳)和DNA加合物分析[85)87],二者均可灵敏表征多环芳烃、农药、重金属等污染物潜在的遗传毒性和早期暴露效应[66,87)89].因此,蚯蚓细胞DNA 损伤是检测污染物致癌、致畸、致突变效应的理想生物标志物[89],其在土壤污染遗传毒性分析和环境风险预测中有重要的应用价值.此外,蚯蚓的再生能力、发育历期[12]、伤口愈合[90]、组织病理变化、基因转录变化[91]、游离糖和氨基酸的组成与含量变化等都可用作评价土壤污染的生物标志物[92].好的生物标志物应该满足以下标准:能够反映污染物的剂量效应关系和时间效应关系,测试系统中的干扰因素已得到识别并可实施控制,测试方法简便、经济、可操作性强,测试终点具有生态相关性,测试结果灵敏、稳定、具有化学特异性和物种差异性,且为公众所接受和得到管理阶层的信任[61].然而,目前已大量构建的生物标志物还没有国际通用的标准检验检测方法[51],多数测试结果也没有在生态系统水平上得到确认和验证[51,61],今后还需要不断加强生物标志物反应与个体、种群、群落水平上的效应之间的相关性研究[93],从而使生物标志物研究能够直接外推用于对污染土壤进行风险预警和评价.6结语事实证明,单纯依靠化学分析并不足以全面反映土壤的真实污染状况[93],作为对化学检测方法的一项互补技术,毒理试验具有独到的优点和特点,如直接产生污染土壤对生物的毒性信息,真实反映土壤污染物对生物体多介质、多途径暴露的现实情况,全面提供复合污染的整体毒性效应,灵敏检测低含量的剧毒污染物,持续跟踪污染物的代谢毒性等.目前,蚯蚓毒理试验在污染土壤生态风险评价中的作用倍受瞩目[94],其既可用于对污染物进行前瞻性的毒性预测,也可用于对历史污染场地进行追溯性的风险评价,试验方法和试验技术正在不断走向国际化和标准化,测试终点和评价指标也在种群、个体、细胞、组织、生化、分子、遗传等多层次、多水平上不断得到深化和发展,生物标志物的研究不断得到加强,日益丰富的蚯蚓毒理数据将为污染物定量构效关系(QSAR)的确立和土壤污染环境监测与管理做出新的贡献.我国利用蚯蚓作为毒性测试模型也做了许多探索性的工作,测定了杀虫剂、除草剂、重金属等许多常见土壤污染物的毒性[95)97],并于近年开始从生理138环境科学研究第20卷。
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Received 1 May 2007; accepted 31 December 2007 Available online 12 January 2008
Abstract It is well known that the discrimination power of data envelopment analysis (DEA) models will be much weakened if too many input or output indicators are used. It is a dilemma if decision makers wish to select comprehensive indicators, which often have some hierarchical structures, to present a relatively holistic evaluation using DEA. In this paper we show that it is possible to develop DEA models that utilize hierarchical structures of input–output data so that they are able to handle quite large numbers of inputs and outputs. We present two approaches in a pilot evaluation of 15 institutes for basic research in the Chinese Academy of Sciences using the DEA models. ᭧ 2008 Elsevier Ltd. All rights reserved.
Keywords: Hierarchical structures; Discrimination power; DEA; Research evaluation
1. Introduction Nowadays, performance evaluation and benchmarking become routine practices in performance management. It has also been well recognized that a single indicator may not be sufficient for effective performance management, especially for the performance evaluation of research institutions, which often have multi-dimensional research activities. It is now a usual practice to set or select a set of performance indicators in the performance evaluations of research institutions. For evaluation of decision making units (DMUs) with multiple-inputs and multiple-outputs in public sector, data envelopment analysis (DEA) is now one of the most widely accepted methods to measure the relative
W. Meng et al. / Omega 36 (2008) 950 – 957
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However, the standard DEA models are sensitive to indicator set changes. It was shown that even removal of a highly correlated output (or input) can greatly change the evaluation results [11]. Furthermore removal of highly correlated data may not be rational in the evaluations of research institutions, where it is well accepted that research institutions may have many outputs and their consequences like papers, citations of papers, awards, and invited talks, etc., which are complementary but often highly correlated. Often the DMs wish to include many such correlated indicators in order to present a relatively comprehensive evaluation. It may be difficult to justify removals of the indicators just due to data correlations. It has been observed that in the evaluations of research institutions, often these indicators can be grouped hierarchically, where weights can be assigned to reflect the relative importance of different indicators in overall substitutions within the groups, while no such substitutions can be easily decided among these groups so that they are best considered to be no-substitutable. In this paper, we carry out a pilot study on DEA productivity evaluation of 15 institutes for basic research in the CAS by exploring multi-level data structures. The main purpose of this investigation is to explore the possibility of using DEA for efficiency evaluation of the CAS, where a large numbers of indicators were used so that the standard DEA models have not been able to be applied. 2. Inputs and outputs used in the evaluation of the CAS research institutes One of the main missions of the CAS is “to carry out top level research at the forefront of basic sciences”. Actually, the CAS is a major player in basic research in China. Following the process of Knowledge Innovation Program (KIP) of the CAS, which was launched in 1998, research quantity and quality of basic research have been steadily increased. In the evaluation of sustainability in the comprehensive evaluation system (CES) in 2002, research outcomes were measured from three aspects: objective achievements, quantitative measurements, and social and economic contributions [12]. Objective achievements were evaluated by peer review based on the pre-signed short-term (3 years) research contracts between the CAS administration and its research institutes. Quantitative measurements were based on the three sub-indicators: high quality publications—the number of publications in top research journals in different disciplines; invited talks in top international conferences; important national and
a Institute of Policy and Management, Chinese Academy of Sciences, 100080 Beijing, China b Kent Business School, University of Kent, CT2 7PE Canterbury, Kent, UK