Identity and authenticity in destination image construction Abstract The aim of this paper is to establish a clear distinction between the often misused concepts of identity and authenticity as related to place and also to examine the role that both concepts play in constructing destination image. The basic hypothesis of this theoretical approach is that the concepts of identity and authenticity are fundamentally different in terms of the tourist element they are related to, from the point of view of destination image construction. Identity is a concept basically related to the tourist object and projected image. Authenticity, a more ambiguous term, is basically related to the tourist subject and perceived image. A model is built to understand both tourism identity and authenticity in a holistic conception of destination image construction. Keywords authenticity; authentication; identity; destination image; image construction INTRODUCTION The aim of this st

原文： Multivariable Optimization The practical problems associated with locating the global optimum of a function of several variables are similar in many ways to those discussed in the preceding section. Additional complications arise because of the dimension of the problem. Graphical techniques are not available in dimensions n gt; 3,and solving ▽f= 0 becomes more complicated as the number of independent variables increases. Constrained optimization is also more difficult because the geometry of the feasible region can be more complicated. Example 3.2. A suburban community intends to replace its old fire station with a new facility. The old station was located at the historical city center.City planners intend to locate the new facility more scientifically. A statistical analysis of response-time data yielded an estimate of 3.2 1.7 minutes required to respond to a call r miles away from the station. (The derivation of this formula is the subject of Exercises 17 a

英语原文共 12 页， 附录B 译文 时间序列概要 时间序列是一组按照时间发生先后顺序进行排列的数据点序列。通常一组时间序列的时间间隔为一恒定值（如1秒，5分钟，12小时，7天，1年），因此时间序列可以作为离散时间数据进行分析处理。时间序列广泛应用于数理统计、信号处理、模式识别、计量经济学、数学金融、天气预报、地震预测、脑电图、控制工程、航空学、通信工程以及绝大多数涉及到时间数据测量的应用科学与工程学。 内涵 时间序列是用时间排序的一组随机变量，国内生产毛额（GDP）、消费者物价指数（CPI）、加权股价指数、利率、汇率等等都是时间序列。 时间序列的时间间隔可以是分秒（如高频金融数据），可以是日、周、月、季度、年、甚至更大的时间单位。 时间序列是计量经济学所研究的三大

英语原文共 8 页， 附录A 外文翻译 运动定律 直观地应用牛顿运动定律来看待这两只大角羊互相争夺统治权。它们在阻止它们滑动的摩擦力的帮助下。通过腿部的肌肉运动向地面施加压力。地面对它们的反作用力作用在它们的身上，使得它们向前相互顶撞。目的是为了让对方失去平衡。 经典力学描述了在我们的日常世界中被发现的物体的运动和作用在它们身上的力的关系。只要研究的系统中不包括与一个原子大小相当或者运动速度接近于光速的物体，经典力学就能很完美地描述自然界。 本章介绍牛顿运动三大定律以及万有引力定律。牛顿运动三大定律简单明了。牛顿第一定律指出，为了改变一个物体的速度，必须给物体施加一个力。改变一个物体的速度代表着给它加速，这代表了力与加速度之间的关系。这种关系，用牛�

英语原文共 10 页， 激光直写技术实现III-V族半导体的周期性纳米结构的制备 Yuan-qing Huang1，2, Rong Huang3, Qing-lu Liu2, Chang-cheng Zheng4, Ji-qiang Ning3, Yong Peng1and Zi-yang Zhang2* *通信地址：zyzhang2014@sinano.ac.cn 中华人民共和国，苏州215123，中国科学院苏州纳米技术和纳米仿电子学研究所的纳米器件与应用重点实验室 文章末尾有完整的作者信息列表 摘要 本文证明了利用激光直写技术（LDW）在III-V族 GaAs衬底上制备一维（1D）和二维（2D）周期性纳米结构。选择金属薄膜（Ti）和相变材料（Ge2Sb2Te5（GST）和Ge2Sb1.8Bi0.8Te5（GSBT））作为光刻胶在半导体材料上得到较小特征尺寸的纳米结构。在光刻胶上获得了约50 nm的最小特征尺寸，其宽度约为光学衍射极限的四分之一。并在GaAs衬底上成功地获得了最小宽度为150 nm的一维III-V族半导体纳米片，这

英语原文共 6 页， 用于三维可堆叠相变存储器的选通管 选通管的高电流密度开关性能已经成功地实现了高密度三维(3D)堆叠相变存储器在英特尔3D Xpoint技术中的商业化。这弥补了动态随机存取存储器(DRAM)和闪存之间巨大的性能差距。与相变存储器类似，选通管使用的是基于硫系化合物的材料，但是相变存储器可以在高电阻非晶相和低电阻晶相之间可逆切换，而选通管的可逆操作始终处于材料的非晶相状态。本文综述了近年来选通管材料及其器件性能的研究进展，特别是电流密度和开关比，讨论了选通管器件在与相变存储器集成中的优点和挑战。我们介绍了用于解释选通管行为理论模型的演变，包括热失控，磁场诱导的成核以及电荷载流子的产生与复合。 引言 计算机不仅深刻地改变了我们的生活，还为社会上一些从分析大数�

英语原文共 6 页， 网络化p型CuO纳米线的生长机理和传感特性的研究 Department of Materials Science and Engineering, Inha University, Incheon 402-751, Republic of Korea 摘 要 通过对铜的加热氧化，在电极垫上生成网络化p型氧化铜纳米线。围绕圆形电极垫生长的垂直排列的氧化铜纳米线互相纠缠最终线与线形成连接点。研究了网络化CuO纳米线对氧化性气体(如NO2、SO2和O2)和还原性气体(如CO、C6H6、C7H8和H2)的传感性能，并与网络化n型SnO2纳米线进行了比较。网络化CuO纳米线对氧化气体的响应不如网络化n型SnO2纳米线。相比之下，对于还原气体，网络化CuO纳米线与网络化n型SnO2纳米线的响应接近。结果表明，网络化CuO纳米线更适用于探测还原性气体而不是氧化性气体。 关键词 气敏传感器；响应机理；氧化铜纳米线；纳米传感器 1.介绍 在工业化社�

A partial least-squares regression approach to land use studies in the Suzhou-Wuxi-Changzhou region ZHANG Yang1,2, ZHOU Chenghu1, ZHANG Yongmin3 1 Introduction Empirical statistical analysis has been proposed for describing land use in quantitative terms and for testing the importance of its influencing factors.(Turner II et al., 1995; Hoshino,1996; Veldkamp and Fresco, 1997; Verburg and Chen, 2000). Various statistical methods, such as multiple linear regressions, canonical correlation analysis and principal component analysis, have been adopted in these studies. They aim at a relatively limited time scale, but are especially useful in regions that are still considerably restricted by biophysical and socio-economic conditions (Hoshino, 1996; Veldkamp and Fresco, 1997; De Koning et al., 1998). However, a problem in applying conventional methods to land use studies lies in their inability to deal with multicollinearity existed in land use types, biophysical and socio-

Multiple Regression and Correlation Analysis Introduction In chapter 13 we described the relationship between a pair of interval- or ratio-scaled variables. We began the chapter by studying the coefficient of correlation, which measures the strength of the relationship. A coefficient near plus or minus 1.00 (-.088 or -0.78, for example) indicates a very strong linear relationship, whereas a value near 0 (-.012 or .18, for example) means that the relationship is weak. Next we developed a procedure to determine a liner equation to express the relationship between the two variables. We referred to this as a regression line. This line describes the relationship between the variables. It also describes the overall pattern of a dependent variables() to a single independent or explanatory variable(). In multiple linear correlation and regression we use additional independent variables (denoted ,...,and so on) that help us better explain or predict the dependent variable (). Alm

Principal component analysis and factor analysis and SPSS software in detail the similarities and differences Abstract: The principal component analysis and factor analysis (R-type) is widely used, but some papers and some textbooks SPSS software (see text) error. This paper points out these errors and their causes, and points out the harm caused by errors, in principle gives the principal component analysis and R-type factor analysis of the detailed mathematical model of similarities and differences between the methods are given to avoid making mistakes, and the SPSS software and made recommendations about textbooks. Keywords: Principal component analysis; factor analysis; SPSS software; error; avoid Let = (X1, ..., XP for the standardized random vector (p ge; 2), R is the correlation coefficient matrix, = (F1, ..., Fm main component vector, = (Z1, ..., Zm for the factor vector, m le; p , for the convenience factor, factor estimates, factor score with the same mark.