Precision Analysis of the Local Group Acceleration

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Knowledge based approach to consonant recognition

KNOWLEDGE BASED APPROACH TO CONSONANT RECOGNITIONA. SamouelianDepartment of Electrical and Computer Engineering, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia.ara@.auABSTRACTThis paper presents a knowledge based approach to consonant recognition. In traditional knowledge based systems, the expert is the linguist/phonetician who attempts to describe and quantify the acoustic events, in the form of production rules into phonetic description. This paper proposes to alter the expert's role so that the expert only needs to provide the basic structure of the phonetic classification. The knowledge itself can then be induced from examples in the agreed structure. Thus the acoustic-phonetic rules are moved from the expert's head to the machine memory via the language of examples rather than via the language of explicit articulation. Recognition results on three broad phonetic classes, namely plosives, semi_vowels and nasals, for a combination of feature sets, for speaker dependent and independent recognition, are presented.1.INTRODUCTIONOne of the major difficulties in automatic speech recognition (ASR) is the extreme variability of the speech signal at the speaker and acoustic-phonetic level. Pattern recognition approaches can handle this variability to some extend by being data driven, but generally ignore acoustic-phonetic features. The use of knowledge/rule based approach to continuous speech recognition has been proposed by several researchers and applied to speech recognition [1], spectrogram reading [2, 3] and speech understanding systems [4]. In general, the production rules are in the form of IF condition THEN action. In speech recognition, there is always the need to generate additional rules to handle exceptions. Very quickly, the number and complexity of the rules increases to such an extent that it is very difficult, for human experts, to generate heuristically, a large number of interrelated rules, from empirical linguistic knowledge or from the observations of the speech data. To overcome this problem, Aikawa [5] proposes an automatic rule generation approach for rule-based consonant discrimination. The rules are generated automatically from the database.Inductive systems have been widely used for collection of classification knowledge from large databases and collections of examples. The essence of induction is to use___________________This work was carried out at the Speech Technology Research Laboratory, Department of Electrical Engineering, The University of Sydney.a known set of examples to a theory that explains both these examples and, hopefully, other unseen examples as well [6]. Since the most successful recognition systems are data driven, where the structure and characteristics of the speech signal is captured implicitly from the training data, this paper proposes a data driven knowledge-based approach to consonant recognition in continuous speech. The system is based on automatic generation of production rules from examination of hand segmented and labelled database by the use of an induction system (C4.5) [7]. The approach is based on two assumptions. First, it assumes that data driven methodology is the way to solve the problem of inter and intra speaker speech variability. Second, it assumes that inductive learning has the ability to generalise the characteristics of the speech signal explicitly from the database.The motivation here is to develop a flexible ASR system that allows the generation of production rules from any number of different feature combinations, including traditional acoustic-phonetics, speech specific or spectrally based features or parameters.Section 2 introduces the training and recognition strategy. Recognition results for a relatively small database are presented for the consonant class recognition in section 3. The performance evaluation of the recognizer using four different feature extraction modules are shown in section 4. Section 5 discusses the advantages of inductive systems for speech recognition with section 6 concluding this paper.2.TRAINING AND RECOGNITION STRATEGY 2.1 DatabaseThe speech database consisted of 195 Australian accented English phrases and included all the permissible sounds of the language in all possible combinations by class. The phrases were collected from two females and one male speaker, each reading the phrases from prepared text, only once. The phrases were devised and collected by National Acoustic Laboratories as part of the GLASS project. The recordings were made in an anechoic room. The speech was sampled at 40 kHz, and digitised into 16-bit samples. The speech was down sampled to 16 kHz for final analysis by the feature extraction modules. The database was hand segmented and phonetically labelled by The University of Sydney as part of the same project. Table 1 shows the classification of the speakers in the database.Table 1. The classification of the speakers in the database.The consonant classes of plosives , semi_vowels and nasals were selected for investigation since these tend to be more difficult to recognize. Table 2 shows the number of phonetic class tokens for each speaker. These tokens are according to the hand labelled transcription by the phonetician.Table 2. Number of phonetic class tokens for each speaker.2.2 TrainingA block schematic of the training and recognition strategy is shown in Figure 1. Four different feature extraction modules have been used to train and test the recognition system.The first feature extraction module (MFCC) generates MFCC coefficients. The second module (DCT) is an auditory front end [8] based on the Generalised Synchrony Detector (GSD)proposed by Seneff [9] and modified so that the synchrony output is transformed by Discrete Cosine Transform (DCT)function to produce a set of coefficients similar to MFCC.Both of these modules generate 12 MFCC/DCT, 12 delta MFCC/DCT and an energy term. The third modules(TRAJ) extracts formant and formant transition informationfrom the output of the auditory model. The final module (FEATURE) extracts from the speech signal, various time domain features such as root mean square (rms), maximum amplitude, zero crossing rate, voicing, energy, envelope, AC peak to peak, difference between maximum and minimum values in the positive and negative halves of the signal and auto-correlation peak. Modules 1 and 4 extract features in the time domain, while modules 2 and 3 extract features from the auditory model in the frequency domain.The feature extraction framework allows the collection of attributes used to describe the phonetic class. These attributes are of two kinds: those whose possible values form a small discrete set, and those whose values were real numbers. For example, the value of attribute F1 trajectory can have values in R, L, F indicating rising, level and falling F1 trajectory,while the value of F1 can be any (positive) real number.Attributes of either kind may have unknown values for a particular phonetic class, and these are designated with a question mark (?).During the training phase, the feature extraction framework extracts features or parameters from the continuous speech on a frame by frame basis. The time aligned phonetically labelled files are then used to associate each frame with its corresponding label and generate a training data file. This data file is constructed on the basis of the training samples, which contain labelled examples in the form (X,α), where X is a feature vector and α is the corresponding class.This data file is then used by the C4.5 program to generate a decision tree.Table 3 shows the feature set for the four different feature extraction modules, namely MFCC, DCT, FEATURE and TRAJ that were used to test the recognition system.Recognition PhaseFigure 1. Block schematic of training and recognition strategyTable 3. The feature set used in the various featureextraction modules.2.3 RecognitionThe recognition was performed at the frame level and the performance was evaluated by comparing each classified frame against the reference frame derived from the hand labelled data. This procedure allowed the correct identification of substitutions and insertions per frame. An inference engine (written in Prolog) was used to execute the decision tree [10].2.4 Combination of FeaturesTo evaluate the significance of the features combinations in improving or degrading the recognition performance, the features initially selected for the TRAJ module were augmented with a selection of features from the FEATURE module. This resulted in four new feature modules, namely t1_TRAJ, t2_TRAJ, t3_TRAJ and t4_TRAJ. Table 4 shows the combination of features used for each variation on TRAJ.3.RECOGNITION RESULTSTables 5 and 6 show the overall performance, for speakerTable 4. The combination of feature set used forvariations on TRAJ feature extraction module.dependent and independent recognitions respectively, for speakers 1, 2 & 3 in % correct, for the various feature extraction modules. For speaker dependent recognition, the system was trained and tested on the same speaker, while for speaker independent recognition, the system was trained on one speaker and tested on the other two in turn.Table 5. Speaker dependent recognition results, for consonant class recognition, for various feature extraction modules,for speakers 1, 2 & 3 .Table 6. Speaker independent recognition results, for consonant class recognition, for various feature extraction modules,for speakers 1, 2 & 3.Tables 7 and 8 show the overall performance, for speaker dependent and independent recognitions respectively, for speakers 1, 2 & 3 in % correct, for the variations on TRAJ feature extraction module.Table 7. Speaker dependent recognition results, for consonant class recognition, for variations on TRAJ feature extractionmodule, for speakers 1, 2 & 3 .Table 8. Speaker independent recognition results, for consonant class recognition, for variations on TRAJ feature extractionmodule, for speakers 1, 2 & 3 .4.PERFORMANCE EVALUATIONThe implementation of the proposed approach was evaluated at the speech frame level, on a relatively small corpora of Australian accented English database. Across the three speakers (2 Females and 1 Male), this approach produced an average consonant class recognition accuracy, for the speaker dependent mode in the range of 80.0% to 94.8%, and for the speaker independent mode in the range of 61.0% to 69.0%, depending on the feature extraction module. For speaker dependent recognition, the best performing features were MFCC and DCT, with an average recognition rate of between 94% to 95.3% between the three consonant classes. The average recognition rate between all of the feature extraction modules was between 87% to 90.1%. For the speaker independent recognition, the best performing feature was FEATURE, with an average recognition rate of between 62.0%-76.3%. The average recognition rate between all of the feature extraction modules was between 51.5% to 76%.It can be seen from table 7 that the performance of the recognizer for the speaker dependent mode can be improved by the choice of the feature combinations. By the inclusion of features zcr and rms, a minimum recognition improvement of 10% (plosives) and 9% (semi_vowels) was achieved. By th einclusion of a further two features, envelope and auto_peak, the recognition improved by a further 1-2% (plosives), 4-5% (semi_vowels) and 9% (nasals). Similar performance improvements were obtained for speaker independent mode as can be seen from table 8.The performance evaluation indicates that for speaker dependent recognition, spectrally based features such as MFCC and DCT coefficients perform better than the features based on acoustic-phonetics. This may be due to the fact that these features were probably not optimum for the task on hand. For speaker independent recognition, the performance of all the feature modules were similar. One possible explanation may be that since each decision tree was trained on a single speaker and tested on the other two, the decision tree could not be classified to be truly speaker independent. The performance results also indicate that the feature combination does play a significant role in improving the recognition accuracy.5.DISCUSSIONTraditional knowledge/rule based ASR systems rely on the expert to describe and quantify the acoustic events, in the form of production rules into phonetic description. The data driven rule based approach using inductive learning from examples helps to eliminate the bottle-neck in transferring knowledge from the expert to the system developer. In addition, inductive learning can quantify from the parameters a set of rules that can reliably identify a class of sound. A further advantage is that a large database can be used to extract the knowledge automatically and generate a decision tree which is derived according to the parameters or features that provide most information about a classification. Thus only those parameters are used as discriminating features. This also helps to optimise the size of the feature set that needs to be extracted.6.CONCLUSIONThis paper demonstrated a data-driven knowledge/rule based approach to broad consonant classification, namely plosives, semi_vowels and nasals, for a combination of feature sets using inductive learning to generate the production rules in the form of decision trees and an inference engine to classify the firing of the rules. The experimental results indicate the ability of this approach to solve the problem of inter and intra speaker speech variability by the use of a large speech database, and the ability to generate decision trees using any combination of features (parametric or acoustic-phonetic). This paves the way for the true integration of features from existing signal processing techniques that have proven to produce good results in stochastic modelling with acoustic-phonetic features, including the incorporation of speech specific knowledge into the decision tree.7.REFERENCES[1] Bulot, R. and Nocera, P., "Explicit Knowledge and Neural Networks for Speech Recognition", Eurospeech 89, Paris, France, Vol. 2, pp. 533-536, September 1989.[2] Komori, Y., Hatazaki, K., Tanaka, T., Kawabata, T. and Shikano, K., "Phoneme Recognition Expert System Using Spectrogram Reading Knowledge and Neural Networks", Eurospeech 89, Paris, France, Vol. 2, pp. 549-552, September 1989.[3] Zue, V. W. and Lamel, L. F. "An Expert Spectrogram Reader: A Knowledge-Based Approach to Speech Recognition", Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, Tokyo, Japan, pp. 1197-1200, April 1986.[4] De Mori, R. and Kuhn, R., "Speech Understanding Strategies Based on String Classification Trees", Proc. ICSLP 92, Vol. 1, pp. 441-459, Canada, 1992.[5] Aikawa, K., "Automatic Generation of Consonant Discrimination Rules", Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, Tokyo, Japan, pp. 2755-2758, April 1986 [6] Quinlan, J. R., "Discovering Rules by Induction from Large Collections of Examples", Machine Learning, Vol. 1, No. 1, 1979.[7] Quinlan, J. R., "Induction of Decision Trees", in Expert Systems in Micro Electronic Age, D. Mitchie, ed. Edinburgh: Edinburgh University Press, 1986.[8] Samouelian, A., "Speech Recognition Front-End Using Auditory Model", Int. Conf. on Signal Proc. '90, Beijing, China, pp 337-340, October, 1990.[9] Seneff, S., "A Joint Synchrony/Mean Rate Model of Auditory Speech processing", Journal of Phonetics, Vol. 16, No. 1, pp77-91, 1988.[10]Horn K. A., "RD-ID3: A System for Knowledge Acquisition and maintenance Employing Induction with Ripple Down Rules", OTC Technical Report, OTC R&D, December, 1991.。

基于单点多盒检测器的全局-局部层级的域适应目标检测

2021⁃02⁃10计算机应用,Journal of Computer Applications 2021,41(2):517-522ISSN 1001⁃9081CODEN JYIIDU http ：//基于单点多盒检测器的全局-局部层级的域适应目标检测蒋宁1，2，方景龙1*，杨庆3（1.杭州电子科技大学计算机学院，杭州310018；2.宁波城市职业技术学院信息与智能工程学院，浙江宁波315110；3.南京工程学院计算机工程学院，南京211167）（∗通信作者电子邮箱fjl@ ）摘要：在目标检测领域里通常希望在拥有大量标记的场景中训练好的模型能够应用在无标记的其他场景中，但是不同的域分布往往是不同的，这样往往导致域迁移时模型性能的急剧下降。

为了提高域迁移时模型的目标检测性能，通过两个层级来解决域迁移问题，包括全局层级迁移和局部层级迁移。

这两种层级迁移分别对应不同的特征对齐方式，即全局层级采用选择性对齐方式，局部层级采用完全对齐方式。

所提域迁移框架基于单点多盒检测器（SSD ）模型，在全局和局部层级分别配置相应的域适配器以减少域间差异，通过对抗网络算法实现具体训练，再通过一致性正则化来进一步提高模型的域迁移性能。

通过大量实验验证了提出的域迁移模型的有效性，结果表明同目前常见的域适应-快速区域卷积（DA -FRCNN ）模型、对抗识别域适应（ADDA ）模型以及动态对抗适应网络（DAAN ）模型等三种域迁移模型相比，该模型在不同数据集上的均值平均精度（mAP ）可以提高5%~10%。

关键词：目标检测；域适配器；域迁移；对抗训练；特征对齐；卷积层；损失函数；单点多盒检测器中图分类号：TP391.9文献标志码：AGlobal -local domain adaptive object detection based on single shot multibox detectorJIANG Ning 1，2，FANG Jinglong 1*，YANG Qing 3（1.School of Computer Science and Technology ，Hangzhou Dianzi University ，Hangzhou Zhejiang 310018，China ；2.School of Information and Intelligent Engineering ，Ningbo City College of Vocational Technology ，Ningbo Zhejiang 315110，China ；3.School of Computer Engineering ，Nanjing Institute of Technology ，Nanjing Jiangsu 211167，China ）Abstract:In the field of object detection ，it is hoped that the model trained in the domain with a lot of labels can beapplied to other domains without labels ，but different domain distributions are always different to each other ，such difference will result in a sharp decline of model performance in domain transfer.To improve the model performance of object detection in domain transfer ，the domain transfer was addressed on two levels ，including the global -level transfer and the local -level transfer ，which were corresponding to different feature alignment methods ，that is ，the global -level adopted selective alignment and the local -level adopted full alignment.The proposed domain transfer framework was constructed based on Single Shot MultiBox Detector （SSD ）model and was disposed of two domain adaptors corresponding to global and local level respectively for the purpose of alleviating the domain difference.The specific training was implemented by the adversarial network algorithm ，and the consistency regularization was used to further improve the domain transfer performance of the model.The effectiveness of the proposed domain transfer model was verified by many experiments.Experimental results show that on various datasets ，the proposed model outperforms the existing common domain transfer models such as Domain Adaptation -Faster Region -based Convolutional Neural Network （DA -FRCNN ），Adversarial Discriminative Domain Adaptation （ADDA ），Dynamic Adversarial Adaptation Network （DAAN ）by 5%-10%in term of mean Average Precision （mAP ）.Key words:object detection;domain adaptor;domain transfer;adversarial training;feature alignment;convolutionlayer;loss function;Single Shot MultiBox Detector (SSD)0引言目标检测是机器学习中一个热点问题，它包括对图像进行分类和定位两种检测。

研究生英语综合教程(下)-全部答案及解析

Question 3
The correct answer is A. The interviewer asks about the best way to learn a new language, and the guest recommendations introduction
Listening Analysis
VS
Answer to Question 2
The correct answer is C. The author suggestions that improve their writing skills, students should read a variety of materials, write regularly, and seek feedback from peers and teachers
Analysis of tutorial characteristics
The tutorial is designed to be highly interactive and student-centered, encouraging active participation and discussion
Question 2
The correct answer is C. The speaker advice that to improve memory, one should exercise regularly, eat a balanced die, and practice relaxation techniques
Analysis 3
The interview is conducted in a case and conversational style, with the interviewer asking insightful questions and the guest offering practical tips on language learning The language used is accessible and engaging

CALYPSO教程

U s e r' s G u i d eCALYPSO version 1.3.0October 28, 2011Written by Yanming Ma, Yanchao Wang, Jian Lv and Li zhuState Key Laboratory of Superhard Materials, Jilin University, Changchun 130012, China Please contact with Yanchao Wang (wyc09@), Jian Lv (jianlv10@), Li Zhu (zhuli10@) and Yanming Ma (mym@) for any technical questions or any bugs./YanmingMa/mym.htmCopyright © 2011 Jilin University. All Rights Reserved.CONTENTS1. INTRODUCTION (3)2. COMPILATION (4)3. EXECUTION OF THE PROGRAM (4)4. INPUT FILE (5)5. OUTPUT FILES (11)6. THE RESULTS ANALYSIS (12)7. SOME PUBLICATIONS FROM USE OF CALYPSO (13)8. FUTURE DEVELOPMENT (13)9. ACKNOWLEDGMENTS (13)1.INTRODUCTIONCALYPSO (Crystal structure AnaLYsis by Particle Swarm Optimization) is a package for crystal structure prediction through particle swarm optimization algorithm. The approach requires only chemical compositions for a given compound to predict stable or metastable structures at given external conditions (e.g., pressure and temperature), thus the CALYPSO package can be used to identify/determine the crystal structure and design the multi-functional materials. Its main characteristics are:z The Crystal Structure Prediction uses no experimental information, with just the chemical compositions and external conditions.z The symmetry constraint is imposed in the structure generation.z A particularly devised geometrical structure parameter is implemented to enhance the structure search efficiency.z Incorporation of partial structural information is possible, e.g., fixed experimental cell parameters, fixed space group or fixed partial atomic positions.z It is written in Fortran 95 and memory is allocated dynamically.It routinely provides:z crystal structure predictionz molecular crystal structure predictionz cluster structure predictionz2-dimensional structure predictionFor more details on the formalism, see the reference cited below.Reference:“Crystal structure prediction via particle-swarm optimization” Yanchao Wang, Jian Lv, Li Zhu and Yanming Ma*, Phys. Rev. B 82, 094116 (2010).PILATIONFor CALYPSO installation, basic UNIX knowledge is required. The user should be acquainted with the tar, gzip, awk, sed and make commands of the UNIX environment. To install CALYPSO, you need:z A minimal UNIX/LINUX environment.z Fortran-95(Intel Fortran Compiler) compilers.z VASP should be installed on your computer. There are development interfaces with other codes (SIESTA and GULP ).If you want to compile the program, please simply use the following commands.$ tar zvxf Calypso_*.tar.gz$ cd CALYPSO_*$ sh install.shA new folder "Workspace" will be built for CALYPSO run.3.EXECUTION OF THE PROGRAMA fast way to check your installation of CALYPSO code can be found in the directory of “Tests”. Please simply run the commands.$ cd CALYPSO_*/Tests$ ./calypso.x > log &Other examples are provided in the “path-to-package/Examples” directory. This directory contains basic input.dat and shell scripts for running CALYPSO.We describe here in details how to run crystal structure prediction on Silicon. It is advisable to create independent directories for each job, so that everything is clean and neat. Please go to your working directory and:$ mkdir Si$ cd Si$ cp path-to-package/Examples/Si/* ./ .The working directory should contain the following necessary files:(1)The CALYPSO input file: input.dat(2)The executable file: calypso.x(3) Some executable shell scripts: submit.sh, getenth.py, contcar.py.(4)The VASP input files: INCAR and POTCAR.Now you are ready to run the program:./calypso.x >log &After a successful run of the program, you should have several VASP output files and a new directory named results in your working directory.This new directory includes several files:1.CALYPSO.log2.CALYPSO_input.dat3.similar.dat4. pso_ini_*5. pso_opt_*6. pso_sor_*4.INPUT FILEThe main input file named as input.dat, contains all the necessary parameters for the simulation. This file is written in a special format, which allows data to be given in any order, or to be omitted in favor of default values. Here we offer a glimpse of the specific settings:z The syntax is “data label” = “value1 value2 value3 …”. Values that are not specified in the input.dat file are assigned a default value.z The labels are case sensitive.z All text following the # character is taken as comment.z Logical values can be specified as T, true, F, false.There are several examples for the input.dat file in the Examples folder.We here take 2-dimensional as an example:________________________________________________________________________ # System Name default=CALYPSOSystemName = BN-2D# the number of elementsNumberOfSpecies = 2# the name of element (The order is the same as POTCAR)NameOfAtoms = B N# the number of elementsNumberOfAtoms = 1 1# atomic numbureAtomicNumber = 5 7# the max step of iterationMaxStep =50# Use to predict the 2-dimensional structure(testing now)2D = T#The area of 1 f.u.(unit=angstrom^2)Area = 6#The shortest distance between atoms in plane.LAtom_Dis =1.1# the volume of 1 f.u. unit=angstrom^3Volume=32@DistanceOfIon1.0 1.01.0 1.0@end# the ratio of survive to do PSOPsoRatio = 0.6# The algorithmIalgo = 3# It determines which code should be interface to optimize the structure in the simulation. Icode= 1# How many times to do local optimizationNumberOfLocalOptim= 3# The KPOINTS DistanceKgrid = 0.1 0.07# The command to submit the job (change it according to your computers)Command = sh submit.sh# The number of formula in the unit cellNumberOfFormula = 1 1# The Population sizePopSize =20# Use to predict the molecular structure(testing now)Mol=F# only used to continue a previous calculation.PickUp= F#which step shall the previous calculation be picked upPickStep =5#fixed the space group#SpeSpaceGroup = 23 48# only used for cluster (testing now)Cluster= F#Parallel = T#NumberOfParallel = 4________________________________________________________________________Here follows a description of the variables that you can define in your CALYPSO input file (input.dat), with their data types and default value.SystemName (string): A string of one or several words contain a descriptive name of the system (max. 40 characters).Defualt value: CALYPSONumberOfSpecies (integer): Number of different atomic species in the simulation. Default value: There is no default. You must supply this variable.NameOfAtoms (string): Element symbols of the different chemical species.Default value: There is no default. You must supply this variable.AtomicNumber (integer): Atomic Number of each chemical species.Default value: There is no default. You must supply this variable.NumberOfAtoms (integer): Number of atoms for each chemical species in one formula unit.Default value: There is no default. You must supply this variable.NumberOfFormula (integer): The range of formula unit per cell in your simulation. The first number is the minimum number of formula unit, and the second number is the maximum number of formula unit. In the above MgSiO3 example, “NumberOfFormula = 4 4” means using 4 formula units in your simulation. If use the default value “1 4”, you will perform calculations with 1, 2, 3, 4 formula units, i.e., four different CALYPSO calculations.Default value: 1 4Volume (real): The volume per formula unit. Unit is in angstrom^3. The volume can guess by the volume of elementary substance. If it is zero, the program will automatically guess the volume through the radius of ions.Default value: 0@DistanceOfIon (real): Minimal distance between atoms of each chemical species. Unit is in angstrom. The matrix of parameters (order of the matrix) are determined by “ NumberOfSpecies”. For example, it should be set as follows for “NumberOfSpecies=2” d11 d12d21 d22@endDefault value: 0.7 ÅIalgo (integer): It determines which algorithm should be adopted in the simulation.1: local PSO algorithm2: Hybrid PSO (implemented, testing now)3: global PSO algorithm.Default value: 3ICode (integer): It determines which code should be interface to optimize the structure in the simulation.1: VASP2: SIESTA3: GULPDefault value: 1NumberOfLocalOptim(integer): It determines how many times a structure is optimized in the simulation. Our tests indicate that three times are the best choice. The file of INCAR should be adjusted according to this parameter. The details can be found in examples.Default value: 4PsoRatio(real): The proportion of the structures generated by PSO, and the other structures will be generated randomly.Default value: 0.6PopSize(integer): The population size. Normally, it has a larger number for larger systems.Default value: 30Kgrid(real): The precision of the K-point sampling for local optimization (VASP or SIESTA). The Brillouin zone sampling uses a grid of spacing×2πKgrid Å-1. The firstvalue controls the precision of the first three local optimizations, and the second value with denser K-points controls the last optimization. The smaller value normally gives finer optimization results.Default value: 0.12 0.06Command (string): The command to perform optimization on your computer.Default value: There is no default.Mol (logical): If True, a molecular structure prediction is performed. (Testing now) Default value: falseD2(logical): If True, 2-dimensional structure prediction is performed.Default value: falseArea(real): The Area for the 2-dimensional structure.Default value: There is no default.LAtom_Dis(real): The shortest distance of atoms in 2-dimensional structure.Default value: There is no default.SpeSpaceGroup (integer): The specified space group for the initial structures.Default value: 0 0 (Don’t specify space group)Cluster (logical): If True, a cluster structure prediction is performed. (Testing now) Default value: falseMaxStep (integer): The maximum number of PSO iterations. It has a larger value for a larger system.Default value: 50PickUp(logical): If True, a previous calculation will be continued.Default value: falsePickStep(integer): At which step the previous calculation will be picked up.Default value: There is no default. If PickUp=True, you must supply this variable.MaxTime(integer): The maximum time of one local structure optimization. If the time beyond MaxTime, the optimization will be killed and start to optimize a new structure. Default value: 7200 secondsParallel (logical): If Ture, the parallel calculations will be performed (Testing now). In current version, VASP code is the only interface to optimize the structure. Note that you must run the CALYPSO code in remote mode in this case. And we only tested the torque resource manager. If you want to perform calypso in this mode, you must modify the server name of your remote supercomputer and the ssh port in ‘submitremote.sh’ file. Furthermore, the pbs script to submit the vasp job must be renamed as ‘vasp.pbs’. Default value: falseNumberOfParallel (integer): The number of parallel calculations will be performed. Default value: 4The INCAR (INCAR_*), POTCAR and vasp.pbs (if Parallel = T) are needed for local optimization (VASP).The input files of SIESTA (sinput_*) and pseudo potential files (*.psf) are needed for local optimization (SIESTA).The input files of GULP (ginput_*) are needed for local optimization (GULP).5.OUTPUT FILESThe main outputs of CALYPSO run are in the “results” folder:CALYPSO_input.dat: It includes the information in input file.CALYPSO.log: It includes the information of the structures (the space group number,the volume, the number of atoms, etc.).similar.dat: It includes the geometrical structure parameters of predicted structures.pso_ini_*: It includes the information of the initial structure of the *-th iteration step. pso_opt_*: It includes the enthalpy and structural information after local optimization of the *-th iteration.pso_sor_*: The enthalpy sorted in ascending order of the *-th iteration step.6.THE RESULTS ANALYSISTo analyze the results, you can1.Install ISOROPY package (/isotropy.html) on your computer.2.Copy path-to-packag e/Tools/pos2find.py and CALYPSO_ANALYSIS.py to your$PATH (eg: /usr/local/bin/, $HOME/bin/).3.Go to the results folder and typeIf VASP is used to optimize the structures, please type$ CALYPSO_ANALYSIS.py [Value1] [Value2]Value1(integer): The number of low enthalpy structure. We suggest a number of 100.Value2(integer): The Tolerance to identify the space group for ISOROPY.Tolerance=(10-Value2). We suggest to use 1.0If SIESTA is used to optimize the structures, please type$ siesta.py [Value1] [Value2]Value1(integer): The number of low enthalpy structure. We suggest a number of 100.Value2(integer): The Tolerance to identify the space group for ISOROPY.Tolerance=(10-Value2). We suggest to use 1.All structures generated by CALYPSO will be analyzed.The main output file named as “Analysis_Output.dat” contains three column numbers. The first column is the index of the structure sorted by enthalpies in ascending order. The second column is the number of space group, and the third column is the value of enthalpy of the particular structure. The structural information of each structure is writtenin cif format. The file name is X_Y.cif. The “X” is the number of structure and the “Y” is the number of space group.7.SOME PUBLICATIONS FROM USE OF CALYPSO1.Predicted novel high-pressure phases of lithiumPhys. Rev. Lett.106, 015503 (2011)2.Substitutional Alloy of Bi and Te at High PressurePhys. Rev. Lett. 106, 145501 (2011)3.Crystal Structures and Exotic Behavior of Magnesium under PressureJ. Phys. Chem. C 114, 21745 (2010)4.Predicting Two-Dimensional Boron–Carbon Compounds by the GlobalOptimization MethodJ. Am. Chem. Soc., 2011, 133 (40), 16285–162905. Three Dimensional Carbon-Nanotube PolymersACS Nano, 2011, 5 (9), 7226–72346.Metallic and superconducting gallane under high pressurePhys. Rev. B 84, 064118 (2011)7.Novel High-Pressure Phase of RhB: First-Principles CalculationsJ. Phys. Chem. C, 2011, 115 (40), 19910–199158.FUTURE DEVELOPMENTSz Prediction of stable crystal structures at given temperature conditions(implementing) z Prediction of nano structures(implementing)z Prediction of surface and interface structure(implementing)z Prediction of large system(implementing)9.ACKNOWLEDGMENTSWe gratefully acknowledge the suggestions of Hongjun Xiang, Yunlong Liao, Sabino Maggi and Idoia G. de Gurtubay and the support of all the CALYPSO-er.。

Performance implications of capital structure evidence from quoted UK

Performance Implications of CapitalStructure:Evidence from Quoted UKOrganisations with Hotel Interests PAUL A.PHILLIPS and MEHMET A.SIPAHIOGLU The objective of this article is to foster research on the relation-ship between capital structure and corporate performance withhotel ing data collected from43UK quoted organ-isations which possess an interest in owning and managing hotels,Modigliani and Miller’s(1958)capital structure irrelevancytheorem is tested.Empirical analysis revealed no signiﬁcantrelationship between the level of debt found in the capitalstructure andﬁnancial performance.These results are consistentwith Modigliani and Miller’s theorem.Results also highlight thatlow levels of returns on equity are a feature of the sample.Thislatter point appears to an important issue for hotel investment,as hotel companies are continually looking to raise externalﬁnance to fund expansion.Theﬁndings of the study suggest thatChief Financial Ofﬁcers of the sample organisations need toidentify novel ways of expanding the business without increasingthe levels of debt.The article concludes by providing examples ofhow some Chief Financial Ofﬁcers are responding to thechallenges of capital structure.INTRODUCTIONThe ideology that states that an Englishman’s home is his castle permeated through to the UK hotel sector and was much in evidence during the1980s and1990s.The resulting growth in asset values was used to increase debt capacity,which in turn was used to fund expansion.Hotel companies with a high level of property assets in their portfolios beneﬁt from property revaluation Professor Paul A.Phillips is Deputy Director and Professor of Strategic Management at Kent Business School,Canterbury,Kent,CT27PE,UK.Mehmet A.Sipahioglu is a former MSc student at University of Surrey,UK.The Service Industries Journal,Vol.24,No.5,September2004,pp.31–51ISSN0264-2069print=1743-9507onlineDOI:10.1080=0264206042000276829#2004Taylor&Francis Ltd.32THE SERVICE INDUSTRIES JOURNAL in two ways.First,with no change in the level of borrowings,the debt-to-equity ratio is reduced and debt capacity is expanded.Second,in publicly listed com-panies,as the stock value increases,so does the net asset value of the company, resulting in an increase in share price.However,when asset values plummeted during the early1990s the majority of the major hotel chains sought to expand via less riskyﬁnancial routes.When UK interest rates reached15per cent many hotel groups sought to restructure their balance sheets.In theﬁrst instance,hoteliers sought to use sale and leaseback agreements to remove hotel buildings from the balance sheet.However,it was felt by some accountants that there should be a difference between the‘recognition and derecognition’ofﬁxed assets.The Financial Reporting Standard(FRS)5was published in April 1994in an attempt to improve reporting of the substance of the transaction. FRS5affected the accounting of sale and leaseback transactions where the risks and rewards of ownership were not substantially transferred to the lessor.In these instances the leasing arrangements were regarded as aﬁnancial lease and hotels were brought back onto the balance sheet.In addition,due to the more demanding hurdle rates incorporated into discounted cashﬂows(DCF)calculations,hoteliers were having to expand via alternative modes of afﬁliation with emphasis on the resources required (see Table1)and the level of risk.There are arguably four broad categories ofﬁnancing:debt-typeﬁnancing, equity-linked/hybridﬁnancing;minority interests and common equityﬁnance [Copeland,Koller and Murrin,1996].The focus of this study is on debt-type ﬁnancing.Given that a hotel group’s choice of capital structure can signiﬁ-cantly affect its cost of capital,an enhanced understanding of the impact of capital structure on economic performance should enable managers to enhance shareholder wealth.The purpose of this article is to examine the relationship between capital structure and corporate performance in quoted UK organisations with hotelTABLE1RELATIONSHIP BETWEEN MODE OF AFFILIATION,RESOURCES REQUIRED ANDLEVEL OF RISKMode of afﬁliation Resources required Level of risk Wholly/owned built from scratch Very high6High Wholly/owned purchased(conversion)High5Joint venture(technology based)Moderate to high4 Strategic alliance Moderate3 Management contract Low2 Franchising Very low1LowPERFORMANCE IMPLICATIONS OF CAPITAL STRUCTURE33 interests.The topic of capital structure is important to both academics and practitioners,as there is a paucity of academic research and Chief Financial Ofﬁcers(CFOs)are currently looking at alternative ways to fund property growth.In this article,empirical evidence is provided to demonstrate the relationship between capital structure and corporate performance.The lack of hotel‘pure plays’together with the impact of non-hotel operations made us use for the empirical study43UK quoted organisations that possess an interest in owning and managing hotels.A cross-sectional approach is used to test Modigliani and Miller’s[1958]capital structure irrelevancy theorem.The article is organised as follows:the next section brieﬂy reviews prior capital structure literature;this is followed by the research methodology and results.The article concludes with a discussion,conclusions and implications with emphasis on the ways hoteliers are attempting to improve increased shareholder value and returns for shareholders.LITERATURE REVIEWResearch on the theory of capital structure was pioneered by the seminal work of Modigliani and Miller[1958].Modigliani and Miller demonstrated that if a company’s investment policy is taken as given,then in a perfect world–a world without taxes,perfect and credible disclosure of all infor-mation and no transaction costs associated with raising money or going bankrupt–the extent of debt in a company’s capital structure does not affect theﬁrm’s value[Rajan and Zingales,1998].Four decades later a com-pany’s capital structure is based upon well-known capital structure theories, which include corporate taxes,ﬁnancial distress,agency costs,trade-off and signalling.The tax-based model hypothesises that organisations select their capital structure by trading off the beneﬁts from tax reduction on interest payments against the cost ofﬁnancial distress due to the accumulation of more debt. Figure1indicates that when there is no equity,the manager’s incentive’s to exploit the outside equity is at a minimum since the changes in the value of the total equity are equal to the changes in his equity[Jensen and Meckling, 1976].It was postulated,that when the costs ofﬁnancial distress and agency costs are introduced,ﬁrms choose an appropriate(optimal)level of debt,based on a trade-off between beneﬁts and costs of debt.Trade-off theory rationalises moderate borrowing in a way that can easily be understood. Nevertheless,closer analysis ofﬁnancial distress gives a testable prediction from the trade-off theory since these costs should be most serious forﬁrms with valuable intangible assets and growth opportunities[Myers,1990]. Brealey and Myers[2000]state that the theory recognises that target debtratios may vary from ﬁrm to ﬁrm.If trade-off models are correct,then target structures should be found in order to maximise the ﬁrm’s value.Further,it should be noted that ﬁrms within a given industry will have similar capital structures as such ﬁrms face the same type of business risk and will have similar levels of assets and proﬁtability [Brigham,Gapenski and Daves,1999].Myers [1990]argues that (i)investors regard almost all lever-age-increasing security issues as good news and leverage-decreasing trans-actions as bad news,and (ii)there exists a negative correlation between proﬁtability and ﬁnancial leverage.Trade-off theory explains neither fact and is at best a weak guide to average behaviour.‘Asymmetric information’is a term used to indicate when managers’know more about their companies’prospects,risks and values than outside investors.This affects the choice between internal and external ﬁnancing and between new issues of debt and equity securities.This leads to a pecking order,which was ﬁrst highlighted by Donaldson [1961].The pecking order theory explains why equity issues reduce stock price but debt issues do not.If the probability of default is low,then asymmetric information is not a major concern to potential buyers of a debt issue.Myers [1984]found an inconsistency between Donaldson’s ﬁndings and the trade-off models.He pointed out that equity is raised in two ways;retained earnings and new stock and that retained earnings are at the top of the pecking order,while new common stock is at the bottom.This indicates that if retained earnings are high relative to investment requirements the equity ratio will increase,whereas if they are insufﬁcient,the ﬁrm will borrow rather than issue stock,causing the debt ratio to increase.The trade-off models,on the other hand,assume that equity from the sale of stock is equivalent to that from retained earnings,and they suggest that the debt/equity ratio should remain constant over time (Brigham,Gapenski and Daves,1999).FIGURE 1TOTAL AGENCY COSTS AND THE OPTIMAL CAPITAL STRUCTURESource:Jenson and Meckling [1976].34THE SERVICE INDUSTRIES JOURNALPERFORMANCE IMPLICATIONS OF CAPITAL STRUCTURE35 Empirical Capital Structure StudiesEmpirical capital structure studies have covered a variety of topics and can be summarised as follows.Industrial Class.Modigliani and Miller’s risk-class statement in their prop-osition I challenged economists to study this subject.Studies by Scott [1972]and Scott and Martin[1976]suggest that there is a relationship between a company’s industry class and itsﬁnancial structure.Theseﬁndings have been supported by Ferri and Jones[1979],Bradley,Jarrell and Kim [1984]and Titman and Wessels[1988].Size.Firm size is associated with accessibility to capital markets and econom-ies of scale,which indicate an expected positive relationship betweenﬁrm size and the proportion of debtﬁnance.Size may also be a proxy for the degree of information asymmetry between managers and investors,since largerﬁrms are likely to have greater information transparency[Farrar and Tucker, 1999].These observations have been supported by Scott and Martin[1976], Ferri and Jones[1979],Marsh[1982]and Titman and Wessels[1988]. Growth.As mentioned in agency theory,ﬁrms have a tendency to expropriate wealth from bondholders.The cost associated with this form of agency relation-ship is likely to be higher forﬁrms in growing industries,which have moreﬂexi-bility in their choice of future investments.Expected future growth should be negatively correlated to long-term debt levels.Munro[1996]and Jung,Kim and Stultz[1996]found thatﬁrms issuing equity had better investment oppor-tunities than those issuing debt.However,Titman and Wessels[1988]found no evidence to support the negative correlation view.Proﬁtability.According to the pecking order theory of Myers and Majluf [1984],ﬁrms prefer to use internally generated funds toﬁnance new invest-ment,and prefer to issue debt rather than equityﬁnance if internally generated funds are insufﬁcient.On this basis,ﬁrms with a recent history of high proﬁt-ability would be more likely to issue debt at the margin.High cashﬂows associated with high proﬁtability would be expected to lead to a preference for debtﬁnance at the margin[Farrar and Tucker,1999].Despite these argu-ments Titman and Wessels[1988]found a negative relationship between prof-itability and long-term debtﬁnance.Capital Structure and Risk.Excessive gearing levels can lead to an increased risk of bankruptcy and therefore increasesﬁnancial risk.Theoretically,there should be a negative relationship between measures of gearing ratio and the36THE SERVICE INDUSTRIES JOURNAL issue of debt.Marsh[1982]found thatﬁrms with greater bankruptcy risk were more likely to issue equity.Likewise,Walsh and Ryan[1997]also found a negative relationship between earnings volatility and the probability of a debt issue.Nevertheless,Jung,Kim and Stultz[1996]found that equity issuingﬁrms had higher levels of risk and higher earnings volatility, which did not support the negative relationship between gearing and the issue of debt.Asset Structure.The type of assets owned by aﬁrm can inﬂuence its capital structure choice.Scott[1977]and Myers and Majluf[1984]suggest that ﬁrms mayﬁnd it advantageous to sell secured debt.Their model demonstrates that there may be costs associated with issuing securities,as the managers have better information than outside shareholders.Issuing debt secured by property with known values avoids these costs.For this reason,ﬁrms with assets that can be used as collateral may be expected to issue more debt to take advantage of this opportunity.The higher the level ofﬁxed assets,the higher is the collat-eral to support debtﬁnancing.Research by Marsh[1982],Munro[1996]and Walsh and Ryan[1997]draw attention to the fact that a company with a higher proportion ofﬁxed assets in its portfolio is more likely to issue debt. ing results from Delphi panellists,Singh and Kwansa[1999] observed that the fate of the hotel industry rests on operators being efﬁcient and developers being prudent in their activities.If this is achieved the industry will remain attractive for both debt and equity investors.The conventional determinants of capital structure have been shown to explain leverage behaviour in the hotel sector[Sheel,1994].Further evidence of theﬁnancial risks of oper-ating with high levels of debt in the hotel and restaurant sector has been demon-strated by McEvoy[1995].The relatively low explanatory power of the results indicate that there maybe some industry speciﬁc variables to explain the beha-viour.In a study of restaurantﬁrms Kwansa and Cho[1995]noted that the indir-ect cost of bankruptcy is substantial in absolute terms and that the size of the bankruptcy cost can outweigh the tax saving prior to bankruptcy.Although looking at share price reactions to the announcement of new equity issues by hospitalityﬁrms,Bryd,Borde and Atkinson[1998]observed that debt issues were treated more favourable by the markets than equity issues. METHODOLOGYThe Research ProblemThe thrust of this study is to assess whether theﬁrm’s level of debt(capital structure)is associated withﬁnancial performance.PERFORMANCE IMPLICATIONS OF CAPITAL STRUCTURE37 HypothesisThe trade-off theory speciﬁes thatﬁrms within the same industry should have similar capital structure since they have comparable types of assets,business risks and proﬁtability.Furthermore,agency and asymmetric information the-ories suggest that the use of debtﬁnancing is preferred to equityﬁnancing because of its ability to create superior performance.This study will identify if there is a relationship between the levels of debt and performance in UK quoted organisations which possess an interest in owning and managing hotels.Taking into account the research question the hypothesis is formulated as:There is no signiﬁcant relationship between the level of debt found in the capital structure of UK quoted organisations which possess an interest in owning and managing hotels and theirﬁnancial performance.The SampleSecondary data was obtained through the Bloomberg Company Information Database and collected during June/July2000.The proxy for selecting organ-isations for this study was:.Companies who had particular interest in owning and managing hotels. .Companies whose shares were traded on a UK stock exchange..Companies whose last year’sﬁnancial data was available in Bloomberg Company Information Database.The criteria for selecting companies were satisﬁed by48companies in the Bloom-berg database,but relevantﬁnancial data were only available for43companies. According to Sekaran[2000],the generalised scientiﬁc guideline states that if the known population size is50,then a sample of44will be sufﬁcient to conduct the study.Therefore,a sample of43companies out of48seems reasonable.The sample includes the largest hotels in the UK,Granada Group plc, Whitbread plc,Thistle Hotels plc,Bass plc,Hilton Group plc and Stakis plc,which at the time of the study have a combined market capitalisation of £27.5million.Interestingly,the market capitalisation for the entire sample of43companies was£37.4million.Turnoverﬁgures cited in Table2 should be treated with caution,as theﬁgure includes signiﬁcant turnover from businesses other than hotels in the case of Granada,Bass and Whitbread. The impact of non-hotel business is illustrated by the fact that at the time of the research,the hotel businesses within Granada,Bass and Whitbread were not even the largest contributors to the company.Matters are also not helped by the different approaches by hotel companies in recognising revenue.For example,Bass reports gross management contract and franchise fee income, whereas Granada reports fees net as a positive cost as a single line item in the proﬁt and loss.38THE SERVICE INDUSTRIES JOURNALTABLE2PROFILE OF SOME OF THE MAJOR HOTEL GROUPSCompanies Group turnover(£m)Year endGranada Group plc.4,102.0September1999Bass plc(now Six Continents).4,687.7September1999Whitbread plc.2,951.4February2000Thistle Hotels plc.304.7December1999Hanover International plc.19.9December1999(Source:/UK/)Operational MeasuresThe following variables were used in this study.Independent Variables.The independent variables were debt to assets and the gearing ratio.Debt to assets ratio¼total debt/total assetsGearing ratio¼total debt/shareholders’equityGearing ratio is a measure of total debt to shareholders equity,whereas debt to assets ratio is a broader measure since it measures the proportion of debt to total assets.Dependent Variables.The two dependent variables were returns on total assets(ROA)and return on equity(ROE).Return on assets ratio¼net income available to shareholders/total assets Return on equity ratio¼net income available to shareholders/shareholders’equityReturn on equity is a proﬁtability ratio that is used to measure the return on shareholders’investment,whereas return on assets is a ratio used to measure a company’s efﬁciency to create funds from all available resources. Data MeasurementThe variables were measured using a ratio scale,which is extremely useful for statistical analysis[Hussey and Hussey,1997].In order to conduct the tests it was necessary to re-code the independent and the dependent variables into quartiles,as illustrated in Table3.PERFORMANCE IMPLICATIONS OF CAPITAL STRUCTURE39TABLE3RE-CODING VARIABLES INTO QUARTILESVariables1st quartile2nd quartile3rd quartile4th quartileDebt to assets ratio,19.3519.35–27.3427.34–32.43.32.43 Gearing ratio,29.7329.73–43.1343.13–69.95.69.95 Return on assets,3.06 3.06–3.95 3.95–6.48.6.48 Return on equity,4.54 4.54–7.157.15–10.44.10.44Figures are percentages.Reliability and ValiditySince the measures used in this study are generally accepted indicators of gearing and performance this lessens the threat of validity.In addition to this,the sample size is sufﬁcient to make generalisations about the population. RESULTSThe statistical analysis procedure begins by presenting the descriptive statistics for each of the variables that are used in this study.Normality and homogeneity of variances tests were then conducted to determine whether to use a parametric test or a non-parametric test to analyse the mean differ-ences.The Statistical Package for the Social Sciences(SPSS)was used to perform the data analysis.Descriptive StatisticsTable4shows that the mean and the median of debt to assets ratio are similar and that the distribution is slightly skewed towards the right indicating aTABLE4DEBT-TO-ASSETS RATIO DESCRIPTIVESTATISTICSNValid43Missing0Mean26.6500Median27.3400Mode19.35Skewness20.390Standard error of skewness0.361Standard deviation9.9955Variance99.9094Range44.78Percentiles2519.35005027.34007532.4300negative skewness.There are no extreme values and one-quarter of the companies are gathered in the 27.34per cent and 32.43per cent range.Figure 2demonstrates a comparison between the sample distribution and the normal curve.Although the range of gearing ratios of the sample are between 0per cent and 139.41per cent,descriptive statistics indicate that 75per cent of the sample had gearing ratios that are less than 69.95per cent (Table 5).There is a broad range of gearing levels with the standard deviation higher than the debt to assets ratio.The mean is greater than the median and the distri-bution is slightly positively skewed (Figure 3).Figure 4shows that the return on assets ratio range varies between 215per cent and þ15per cent.However,it can be observed from Table 6that 75per cent of returns on assets are less than 6.48per cent.Nevertheless,the mean is less than the median value and the distribution is negatively skewed (Table 6).Table 7shows the broad values for return on equity results.However,the histogram demonstrates that the returns are highly concentrated around 10per cent.50per cent of the companies’returns are between the4.54per cent and 10.44per cent range.In addition to this,the median value is higher than the mean value and the distribution is negatively skewed (Figure5).FIGURE 2DEBT TO ASSETS RATIO FREQUENCY 40THE SERVICE INDUSTRIES JOURNALNormality and Variability TestsDescriptive statistics conducted in the previous section present an insight into the position,variability and skewness of the variables.However,in order to determine whether to use a parametric or a non-parametric test for theTABLE 5GEARING RATIO DESCRIPTIVE STATISTICS NValid43Missing0Mean51.8795Median43.1300Mode0.04a Skewness0.863Standard error of skewness0.361Standard deviation30.2185Variance913.1549Range139.41Percentiles2529.73005043.13007569.9500a Multiple modes exist.The smallest value isshown.FIGURE 3GEARING RATIO FREQUENCYPERFORMANCE IMPLICATIONS OF CAPITAL STRUCTURE41purposes of this study,tests for normal distribution and variability were per-formed.The tests conducted were used to determine whether to use parametric analysis of variance or a non-parametric test (Kruskal–Wallis).Summaries of the results are presented in Table 8.The normality testsreveal that the independent variables tested are normally distributedsinceFIGURE 4RETURN ON ASSETS RATIO FREQUENCYTABLE 6RETURN ON ASSETS DESCRIPTIVESTATISTICSNValid43Missing0Mean3.6251Median3.9500Mode5.26Skewness21.553Standard error of skewness0.361Standard deviation5.5589Variance30.9008Range30.47Percentiles253.0600503.950075 6.480042THE SERVICE INDUSTRIES JOURNALtheir signiﬁcant levels are over 0.05.However,it can be observed that proﬁt-ability ratios cannot be accepted as normally distributed,since their p-values are 0.01.The Levene’s tests show that the variances in all groups are unequal,thus representing a wide difference in variances.Overall,we conclude thatTABLE 7RETURN ON EQUITY DESCRIPTIVESTATISTICS NValid43Missing0Mean4.8981Median7.1500Mode252.06a Skewness21.294Standard error of skewness0.361Standard deviation15.5284Variance241.0207Range102.18Percentiles254.5400507.15007510.4400a Multiple modes exist.The smallest value isshown.FIGURE 5RETURN ON EQUITY RATIO FREQUENCYPERFORMANCE IMPLICATIONS OF CAPITAL STRUCTURE4344THE SERVICE INDUSTRIES JOURNALTABLE8SUMMARY OF NORMALITY AND VARIABILITY TESTSTests Debt ratio Performance ratio Signiﬁcant if p,0.05 Test of normality Debt to assets0.618Gearing0.074ROA0.010ROE0.010 Levene’s test Debt to assets ROA0.009Debt to assets ROE0.005Gearing ROA0.000Gearing ROE0.000 neither test of normality nor Levene’s test satisﬁed the criteria to use a para-metric test in this study.The results of the Kruskal–Wallis test are illustrated in Tables9and10.They show the number of cases and the chi-square statistic and its signiﬁcance level corrected for rank ties.The signiﬁcance level for the ratios are greater than0.05,thus representing no signiﬁcant difference in the means of the independent and dependent variables.DISCUSSION OF RESULTSThe results obtained from Kruskal–Wallis test fail to reject the null hypothesis and lead to the conclusion that no signiﬁcant relationship exists between the level of debt andﬁnancial performance.This result supports the Modigliani and Miller theorem that aﬁrm’s value is independent of its capital structure.It is clear from the descriptive statistics the sample includes organisations operating with relatively high levels of debt,which are not associated with higher levels of performance.This result contrasts with earlier research [Modigliani and Miller.1963;Miller and Modigliani,1966],which states that there is a positive relationship between the level of debt and the value of theﬁrm.The research is consistent with Miller’s[1977]model where he concluded that the advantages to corporate tax will be offset by the personal income tax,implying leverage irrelevancy to any givenﬁrm.Hotel companies have high proportion ofﬁxed assets in their asset portfolios and according to Marsh[1982],Munro[1996]and Walsh and Ryan[1997],companies carrying a higher proportion ofﬁxed assets would take advantage of issuing debt. High debt levels observed in this study may reﬂect this fact.In addition, high levels of debt found within the capital structures of the sample may also be an indication that companies are trying to attract investors as stated by the asymmetric information theory.Nevertheless,Myers and Majluf’s [1984]theory,which state that there is a positive relationship between theTABLE9KRUSKAL–WALLIS TEST COMPARING ROA AND ROE BETWEEN DEBT TO ASSETS GROUPSReturn on assets Return on equity1234Total1234Total Ntiles ofd/a ratioN11101111431110111143 Mean rank22.4526.8520.8218.3221.9125.4021.2719.73Test statisticsChi-square 2.550 1.131 df33 Asymp.Sig.0.4660.770TABLE10KRUSKAL–WALLIS TEST COMPARING ROA AND ROE BETWEEN GEARING GROUPSReturn on assets Return on equityNtiles of gearing1234Total1234TotalN10111111431011111143 Mean rank24.0021.7326.9515.5023.4019.9127.9116.91Test statisticsChi-square 4.920 4.674 df33 Asymp.Sig.0.1780.197PERFORMANCE IMPLICATIONS OF CAPITAL STRUCTURE47 long-term debt levels and the proﬁtability of a company,could not be estab-lished in this study.Measuring performance is a conceptually challenging activity for man-agers.For example,Phillips[1999]suggests that performance can be judged in terms of how well stakeholders’expectations are realised.He draws attention to the potential conﬂict between the employees,customers and shareholders,where high service requirements by customers would lead to low proﬁts with a lower dividend payout to shareholders.This is consistent with the agency theory,which also explains that borrowing hastens the separ-ation between the stockholders and the lenders to become greater as well as the separation between theﬁrm and its customers and employees.Higher borrow-ing levels associated with higher bankruptcy risks may cause potential inves-tors to look elsewhere.Given the relatively low levels of performance,it is easy to understand a rational investor’s decision not to invest in the sample. It should therefore be well understood by CFOs within the sample that borrow-ing does not necessarily lead to higher performance as stated in the asym-metric information theory,but could actually contribute to low performance as stated in agency theory.CONCLUSIONS AND IMPLICATIONSOne of the most perplexing issues facing hospitalityﬁnancial managers is that of capital structure.High operating leverage,which is a feature for those hoteliers who own and lease hotels,has important implications for managers.For example,a small change in revenue can result in a signiﬁcant change in per-formance[Phillips,1994].While much has been written about capital structure in theﬁnance literature,there has been a paucity of empirical evidence relating to organisations with hotel interests.Despite the study providing some useful insights,many of the results are tentative and less than deﬁnitive.Nevertheless, this article attempts to partially address the needs of the hospitality sector and also contribute to the broaderﬁnance literature,which was a challenge issued by Harris and Brander Brown[1998]in their review of the research and devel-opment in hospitality accounting andﬁnancial management.This research also provides empirical evidence for the relationship between proﬁtability and long-term debt levels.Myers and Majluf’s[1984] suggestion that a positive relation exists between the debt and proﬁtability of aﬁrm could not be accepted.This study contributes to the literature by providing evidence against both the positive and negative relationships that exist between the proﬁtability and long-term debt levels.Changes taking place in accounting practice due to FRS15[see Adams, 2001]could ultimately lead to further performance differentials between suc-cessful and unsuccessful hotels.FRS15sets out new accounting requirements。

如何提出好的问题英语作文

As a high school student, Ive always been fascinated by the power of a wellcrafted question. Its not just about asking something its about sparking curiosity, stimulating thought, and driving meaningful conversations. Heres my take on how to ask good questions, based on my experiences and observations.The Art of InquiryAsking a good question is an art. It requires a blend of curiosity, empathy, and a deep understanding of the subject matter. In my school projects, Ive found that the most engaging discussions often stem from questions that are openended and thoughtprovoking.OpenEnded QuestionsOpenended questions are the cornerstone of good inquiry. They invite elaboration and discourage simple yesorno answers. For instance, in a history class, instead of asking, Was the American Revolution successful? which could be answered with a simple yes, I might ask, How did the American Revolution shape the nations identity and values? This question opens up a broader discussion and encourages classmates to consider multiple perspectives.Context MattersUnderstanding the context is crucial. A good question is one that is relevant to the situation and the audience. During a science fair, I onceasked, What are the implications of your research on future environmental policies? This question was not only pertinent to the project being presented but also connected it to a larger, realworld issue.Clarity and SpecificityClarity is key. A question should be clear and specific to avoid confusion. In a literature class, I learned the importance of precision when I asked, How does the use of symbolism in To Kill a Mockingbird contribute to the novels exploration of innocence and prejudice? This specific question led to a deep analysis of the text, rather than a vague discussion about the books themes.Encouraging Critical ThinkingA good question should challenge assumptions and encourage critical thinking. In a debate club, I once posed the question, Do the benefits of social media outweigh the potential risks to mental health? This question stimulated a lively debate, with participants examining both the positive and negative aspects of social media use.Reflecting on Personal ExperiencesSometimes, the best questions come from personal experiences. When I volunteered at a local community center, I asked, What can we do to better support the needs of our community members? Drawing from my firsthand observations, this question led to actionable ideas and initiatives.Research and PreparationBefore asking a question, its important to do your homework. Research the topic thoroughly to ensure your question is informed and insightful. For a school presentation on renewable energy, I spent hours reading up on the latest technologies and trends, which allowed me to ask, How can we overcome the current barriers to widespread adoption of solar power?Listening and AdaptingA good question is also about listening and adapting. In a group discussion, I learned to listen carefully to the responses and refine my questions accordingly. If a classmates answer hinted at a deeper issue, I would follow up with a more probing question to delve further into the topic.Embracing ComplexityFinally, a good question embraces complexity. It acknowledges that there are often no easy answers. In a philosophy class, I asked, Can absolute truth exist in a world of diverse perspectives? This question sparked a rich, nuanced conversation about the nature of truth and knowledge.In conclusion, asking good questions is a skill that can enhance learning, foster understanding, and promote meaningful dialogue. Its about being curious, empathetic, and thoughtful. By asking questions that areopenended, contextually relevant, clear, and thoughtprovoking, we can unlock new insights and perspectives. As I continue my academic journey, I strive to refine this skill, recognizing its power to shape the way we think, learn, and engage with the world around us.。

CV Samples

ANDREW M. ADAMS
153 Spring Mtn. Rd. • Charlottesville, VA • 22902 • (732) 267.3408 • AdamsA05@ EDUCATION Darden Graduate School of Business Administration – University of Virginia Charlottesville, VA Candidate for Masters of Business Administration, May 2005 • Elected to Student Admissions Committee; Selected to co-lead the Alumni Showcase Board • Member of the Consulting Club, Darden Private Equity Network, and Latin American Student Association • GMAT – 720 University of Virginia Charlottesville, VA Bachelor of Arts, Economics, Minor in Astronomy, May 1999 • Semester Abroad (U.K.): University of Lancaster, Management School, Spring 1998 • Financed educational costs by starting and managing a commercial landscaping firm (1994 – 1999) EXPERIENCE Monitor Group (2004) Cambridge, MA Monitor Group is a leading global strategy consulting firm with 29 offices worldwide. Summer Associate Serving as an integral member of the case team, helped a leading international beverage company develop a global marketing platform based on market research analysis and market segmentation techniques • Designed market research instrument and managed selection of market research vendor; presented both to client • Analyzed market research results to help define actionable market segments and understand these segments’ behaviors • Presented case summary and key analytical findings to summer classmates and senior partners Dayton, NJ Sunshine Bouquet Co. (1999 – 2003) An international grower and distributor of fresh- cut flowers, Sunshine Bouquet Co. primarily serves grocery stores throughout the eastern United States and generated revenues of $65 million in 2004. International Operations Management (2002 – 2003) Bogotá, Colombia Promoted to Operations Manager for firm’s most critical production facility; led a five person management team and production workforce of over 200 people • Markedly improved product design, inventory management, production processes and management capability, transforming the Bogotá plant into the firm’s principal production facility • Doubled production capacity within one year by adding over 100 line positions, numerous supervisors and several managers. Expansion reduced U.S. operating costs by over $1.2 million Venture Development (2001) Princeton, NJ Assumed turn-around responsibility for a failing subsidiary (start-up retail venture) • Grew revenues 40% within six months by improving sales development, supply operations, product quality, merchandising and staff (replaced numerous employees and hired two salaried managers) • Enhanced the venture’s brand strength through new marketing campaign (e.g. direct mail, events, in-store activities) • Designed and managed a just-in-time procurement and production process to distribute internationally sourced products to multiple retail locations Marketing & Sales Development (2000) Worked with Chief Operating Officer to implement key marketing initiatives • Created numerous sales proposals that helped reverse declining sales, resulting in a $6 million gain • Authored and designed firm’s new marketing materials and online presence () Dayton, NJ

高中英语学术调研单选题50题

高中英语学术调研单选题50题1. In academic research, it is essential to be precise and ______ in data collection.A. accurateB. approximateC. roughD. casual答案：A。

本题考查形容词词义辨析。

“accurate”意为“精确的，准确的”，在学术研究中，数据收集需要精确准确，A 选项符合语境。

“approximate”表示“大约的，近似的”；“rough”指“粗糙的，粗略的”；“casual”意思是“随便的，偶然的”，这三个选项都不符合学术研究中对数据收集的要求。

2. The scholar spent years conducting ______ studies to prove his theory.A. extensiveB. intensiveC. expensiveD. expansive答案：B。

“intensive”有“集中的，深入的”之意，在学术研究中，进行深入的研究才能证明理论，B 选项符合。

“extensive”侧重于“广泛的”；“expensive”是“昂贵的”；“expansive”意为“广阔的，扩张的”，均不符合本题学术研究的语境。

3. The ______ of this academic paper was highly praised by the experts.A. formatB. contentC. styleD. structure答案：D。

本题考查名词词义。

“structure”表示“结构”，学术论文的结构受到高度赞扬，D 选项恰当。

“format”指“格式”；“content”是“内容”；“style”为“风格”，相比之下，结构更能被整体评价和赞扬。

4. To make the academic research more ______, a large sample size was needed.A. reliableB. unstableC. questionableD. doubtful答案：A。

同学们利用课间时间操场上打乒乓球英语作文)

全文分为作者个人简介和正文两个部分：作者个人简介：Hello everyone, I am an author dedicated to creating and sharing high-quality document templates. In this era of information overload, accurate and efficient communication has become especially important. I firmly believe that good communication can build bridges between people, playing an indispensable role in academia, career, and daily life. Therefore, I decided to invest my knowledge and skills into creating valuable documents to help people find inspiration and direction when needed.正文：同学们利用课间时间操场上打乒乓球英语作文)全文共3篇示例，供读者参考篇1The Ping Pong Playground ProsThere's nothing quite like the sound of bouncing hollow plastic balls and the clack of paddles connecting to get my heart racing during recess. As soon as that final bell rings, a massexodus happens from our classrooms to the playground, where the real fun begins. Sure, some kids just want to run around and burn off energy. But for me and my crew, we make a beeline straight for the ping pong tables.Maybe it's because I was raised in a family of avid basement ping pong players. My parents had an old table set up, and some of my earliest memories are of furious rallies between my dad and uncles, shouting insults at each other in Chinese while the ball zipped back and forth at blistering speeds. I was probably 5 or 6 the first time I held one of those stubby paddles, marveling at how something so light could propel that hollow sphere with such force.From that moment on, I was hooked. My parents nurtured my obsession, signing me up for local youth club sessions to learn proper technique from coaches. By age 8, I was spinning, chopping, and smashing shots with the best of them in my age group. The summers between school years were spent at ping pong camps, my hands slowly developing the calloused racquet grip of a veteran.So it's no surprise that as soon as I started at this school, with its excellent outdoor ping pong facilities, that I became a daily fixture at the tables during recess and lunch periods. At first, Ihad to compete with the usual ball hogs and spot mongers who think they own the tables by sheer size and willingness to bulldoze any opposition. But once they saw the level of my loops, drives, and placements shots, a certain respect emerged.Now, a core group of us specialists assemble each free period, separating into intense singles games or engaging in ultra-competitive doubles battles. The slams, the near-misses celebrating with upward face fist pumps, the light-speedback-and-forth exchanges - it's a high-octane show that draws a crowd of gawkers each day.Tommy is our undisputed king, a spinning dervish who seems to levitate around the table, his feet operating from muscle memory as creative sidespin and back-spin shots bend my brain. He picked up the game only last year from YouTube videos but has honed his tools to surgeon-like levels. The dude's a savant, I swear.Then there's Alexa, whose compact stroke might not seem overpowering, but her consistency and shrewd tactical placement wears you down over a grueling match. Getting into a sustained rally against her patient, cerebral style is like trying to blitz a castle at full strength. Her humble "aw shucks" routine is just a big feint.Last but not least, there are the international crew - Yusuf from Turkey, Maria the Greek gandhi, a South Korean kid named Jinho who was basically born looping forehand topspin screamers. Their far-flung styles just add to the cosmopolitan flair of our lunchtime battles. On any given day, you'll hear a bazaar's worth of language combat alongside the hollow plastic spheres.For while the games are intensely competitive, a spirit of camaraderie rules the day too. We'll pause for analysis from spectators, offering tactical advice or dissecting ametuer errors from both sides. The heckling is always kept light and humorous. Part of being a true ping pong obsessive is appreciating the artistic merits of a stellar shot or rally, no matter who is producing the magic.When that warning bell rings, signaling just a few precious minutes remain, that's when the comedy kicks into high gear. Imagine five or six balls being batted around in a spontaneous multi-game, shouting and laughter echoing across the playground. Ping pong has become a beloved shared language for us outcasts, geeks, and misfit toys to live out our passion and find a brief escape from the social stratas of the schoolyard.Part of me feels like I found my forever crew here. No one looks at me as that quiet Chinese kid anymore. In this realm, I'm one of the masters, slinging forehands with the confidence of someone who can back it up. Every ounce of respect was earned through the wizardry of my wrist and well-timed footwork. Out here, we're all just appreciators of the same beautiful, silly game.When we're forced to pack it in for the day and head back to class, there are always those few minutes of laughter andwar-story recapping before the academic grind reasserts itself. I'll continue living for those little slices of freedom where I can just be me, doing what I love best with people who have become so much more than just campus acquaintances. The ping pong playground is our home base, our clubhouse sanctuary from the stresses of teenage life. No matter what dramas occur in the classroom, we know we can return here each day and achieve total transcendence through aerodynamic orbs and ourwell-worn paddles.篇2Sure, here's a 2000-word essay in the voice of a student describing how their classmates play ping-pong during recess on the school playground, written in English:Ping-Pong Passion on the PlaygroundRecess at our school is a whirlwind of energy and excitement, a brief respite from the confines of the classroom where we can let loose and indulge in our favorite pastimes. For many of my classmates, this sacred hour is dedicated to one pursuit above all others – the fast-paced, adrenaline-fueled game of ping-pong.As soon as the bell rings, signaling the start of our recess, a flurry of activity erupts on the playground. Tables are hastily unfolded, and a gaggle of eager students converges, paddles in hand, ready to battle it out on the makeshift ping-pong arenas. The air is thick with anticipation, as challengers size each other up, mentally preparing for the volleys to come.At the heart of this ping-pong frenzy lies a core group of aficionados, a tight-knit fraternity of devotees who live and breathe the sport. They are the undisputed kings and queens of the playground, their reputations forged through countless matches and an unwavering dedication to their craft.Take Jake, for instance, a whirlwind of a player whose lightning-fast reflexes and impeccable technique have earned him a near-mythical status among our ranks. With a flick of his wrist, he can send the ball hurtling across the table at dizzying speeds, leaving his opponents scrambling in a desperate attemptto return the shot. His mastery of spin and placement isawe-inspiring, and his celebratory fist pumps after awell-executed rally have become a familiar sight on the playground.Then there's Emily, a force to be reckoned with in her own right. Her style is a study in precision and control, every shot carefully calculated and executed with surgical precision. She's a master of the defensive game, capable of returning even the most blistering of smashes with a graceful, almost effortless ease. Her prowess has earned her a legion of admirers, and whispers of her exploits often echo through the halls of our school.But ping-pong on the playground isn't just about the stars; it's a true celebration of the sport's democratic spirit. Amidst the flurry of activity, you'll find players of all skill levels, fromwide-eyed novices to seasoned veterans, each reveling in the simple joy of batting that little white ball back and forth.There's something truly magical about the camaraderie that blossoms on the ping-pong tables. Rivalries are forged and friendships cemented, as players trade good-natured banter and offer words of encouragement to their opponents. The sound of paddles connecting with the ball becomes a rhythmic backdrop to the laughter and chatter that fills the air.For those moments, the stresses of academia melt away, replaced by a singular focus on the game at hand. Textbooks and homework assignments are forgotten, as the only thing that matters is the next volley, the next opportunity to showcase one's skill and determination.Of course, not every match is a masterpiece of strategic brilliance. There are moments of hilarity, too, as errant shots go sailing off the table, eliciting raucous laughter from the spectators. Players scramble to retrieve the wayward ball, their faces flushed with exertion and mirth, only to resume their battle with renewed vigor.As the minutes tick by, the intensity on the playground reaches a fever pitch. Tables are occupied by a rotating cast of players, each determined to etch their name into the annals of playground ping-pong lore. Spectators gather in clusters, offering advice and encouragement to their favored competitors, while others engage in spirited debates over the finer points of technique and strategy.Then, all too soon, the bell rings once more, signaling the end of our recess revelry. The paddles are reluctantly set aside, and the tables are folded up, ready to be stowed away until the next opportunity for ping-pong glory arises.But even as we trudge back to our classrooms, our minds are already turning to the next recess, the next chance to immerse ourselves in the fast-paced world of playground ping-pong. For in those fleeting moments of friendly competition, we find a sense of joy and camaraderie that transcends the confines of the schoolyard, forging bonds that will endure long after the final ball has been struck.Ping-pong on the playground is more than just a game; it's a celebration of passion, skill, and the indomitable spirit of youth. And as we return to our studies, we carry with us the memories of those hard-fought battles, ready to defend our reputations and continue the never-ending quest for ping-pong supremacy.篇3Ping Pong Mania on the PlaygroundThe shrill sound of the morning bell signals the start of our first class of the day. I shuffle into homeroom, stifling a yawn as I take my usual seat by the window. Mrs. Thompson drones on about algebraic equations, but my mind has already drifted elsewhere – to the rapidly approaching recess period.You see, recess at Oakwood Middle School isn't just a time to goof off and relax. No, it's become an arena for one of thefiercest sporting competitions our school has ever witnessed. An obsession, if you will, that has gripped everyone from the brainy math whizzes to the athletically-gifted jocks. I'm talking, of course, about the game of ping pong.It all started a few months back when the school invested in some new outdoor ping pong tables for the playground area. At first, they didn't get much use beyond a few kids batting a ball around halfheartedly. But then word started spreading about how fun and addicting the game could be. The real spark was lit by Daniel Chan and his crew of buddies from the asian culture club.Now, I'm not trying to engage in any stereotypes here, but Daniel and his friends were essentially ping pong savants. They grew up playing it at family gatherings and locally in their communities. When they first picked up those paddles and started rallying back and forth, it was like watching masters at work. Their skilled hand-eye coordination, tactical spins, and blazing speeds were frankly intimidating.Naturally, the rest of us were in awe. Crowds started gathering during breaks just to watch these guys go at it. The rivalries and showdowns were intense, accompanied by cheers and jeers from the audience. You could feel the competitiveelectricity crackling in the air. It was only a matter of time before the craze caught on in full force.Within a couple weeks, those ping pong tables became the hottest commodity on campus. Getting a chance to play required meticulous timing and good old-fashioned savagery. Groups would start lining up and squatting by the tables like campers before Black Friday, guarding their spots viciously.When that recess bell finally did ring, a stampede would erupt as kids flockedfrom all directions. The first few to the tables would rapidly set up their chosen sides of the net, palming their paddles with a vice-like grip. Then the games would be on –intense, sweat-soaked battles of wits and reflexes punctuated by raucous laughter and trash talking.For we were all still new to this whole ping pong phenomenon. Errant shots would go sailing over heads and bouncing crazily in every direction. Tables became988。

实验室专业名词翻译

实验室专业名词翻译中文名称英文名称分析名词分析化学analytical chemistry定性分析qualitative analysis定量分析quantitative analysis物理分析physical analysis物理化学分析physico-chemical analysis仪器分析法instrumental analysis流动注射分析法flow injection analysis；FIA顺序注射分析法sequentical injection analysis;SIA 化学计量学chemometrics误差的分析数据处理绝对误差absolute error相对误差relative error系统误差systematic error可定误差determinate error随机误差accidental error不可定误差indeterminate error准确度accuracy精确度precision偏差debiation，d平均偏差average debiation相对平均偏差relative average debiation标准偏差（标准差）standerd deviation;S相对平均偏差relatibe standard deviation;RSD变异系数coefficient of variation误差传递propagation of error有效数字significant figure置信水平confidence level显著性水平level of significance合并标准偏差（组合标准差）pooled standard debiation舍弃商rejection quotient ;Q滴定分析滴定分析法titrametric analysis滴定titration容量分析法volumetric analysis化学计量点stoichiometric point等当点equivalent point电荷平衡charge balance电荷平衡式charge balance equation质量平衡mass balance物料平衡material balance质量平衡式mass balance equation酸碱滴定法酸碱滴定法acid-base titrations质子自递反应autoprotolysis reaction质子自递常数autoprotolysis constant质子条件式proton balance equation酸碱指示剂acid-base indicator指示剂常数indicator constant变色范围colour change interval混合指示剂mixed indicator双指示剂滴定法double indicator titration非水滴定法非水滴定法nonaqueous titrations质子溶剂protonic solvent酸性溶剂acid solvent碱性溶剂basic solvent两性溶剂amphototeric solvent无质子溶剂aprotic solvent均化效应differentiating effect区分性溶剂differentiating solvent离子化ionization离解dissociation结晶紫crystal violet萘酚苯甲醇α-naphthalphenol benzyl alcohol 螯合物chelate compound金属指示剂metal lochrome indcator氧化还原滴定法氧化还原滴定法oxidation-reduction titration碘量法iodimetry溴量法bromimetry溴量法bromine method铈量法cerimetry高锰酸钾法potassium permanganate method条件电位conditional potential溴酸钾法potassium bromate method硫酸铈法cerium sulphate method偏高碘酸metaperiodic acid高碘酸盐periodate亚硝酸钠法sodium nitrite method重氮化反应diazotization reaction重氮化滴定法diazotization titration亚硝基化反应nitrozation reaction亚硝基化滴定法nitrozation titration外指示剂external indicator外指示剂outside indicator重铬酸钾法potassium dichromate method沉淀滴定法沉淀滴定法precipitation titration容量滴定法volumetric precipitation method 银量法argentometric method重量分析重量分析法gravimetric analysis挥发法volatilization method引湿水（湿存水）water of hydroscopicity包埋(藏)水occluded water吸入水water of imbibition结晶水water of crystallization组成水water of composition液-液萃取法liquid-liquid extration溶剂萃取法solvent extration反萃取counter extraction分配系数partition coefficient分配比distribution ratio离子对（离子缔合物）ion pair沉淀形式precipitation forms称量形式weighing forms仪器分析物理分析physical analysis物理化学分析physicochemical analysis仪器分析instrumental analysis电位法及永停滴定法电化学分析electrochemical analysis电解法electrolytic analysis method电重量法electtogravimetry库仑法coulometry库仑滴定法coulometric titration电导法conductometry电导分析法conductometric analysis电导滴定法conductometric titration电位法potentiometry直接电位法dirext potentiometry电位滴定法potentiometric titration伏安法voltammetry极谱法polarography溶出法stripping method电流滴定法amperometric titration化学双电层chemical double layer相界电位phase boundary potential金属电极电位electrode potential化学电池chemical cell液接界面liquid junction boundary原电池galvanic cell电解池electrolytic cell负极cathrode正极anode电池电动势eletromotive force指示电极indicator electrode参比电极reference electroade标准氢电极standard hydrogen electrode一级参比电极primary reference electrode饱和甘汞电极standard calomel electrode银－氯化银电极silver silver-chloride electrode液接界面liquid junction boundary不对称电位asymmetry potential表观PH值apparent PH复合PH电极combination PH electrode离子选择电极ion selective electrode敏感器sensor晶体电极crystalline electrodes均相膜电极homogeneous membrance electrodes非均相膜电极heterog eneous membrance electrodes非晶体电极non- crystalline electrodes刚性基质电极rigid matrix electrode流流体载动电极electrode with a mobile carrier气敏电极gas sensing electrodes酶电极enzyme electrodes金属氧化物半导体场效应晶体管MOSFET离子选择场效应管ISFET总离子强度调节缓冲剂total ion strength adjustment buffer,TISAB永停滴定法dead-stop titration双电流滴定法（双安培滴定法）double amperometric titration光谱分析普朗克常数Plank constant电磁波谱electromagnetic spectrum光谱spectrum光谱分析法spectroscopic analysis原子发射光谱法atomic emission spectroscopy质量谱mass spectrum质谱法mass spectroscopy,MS紫外－可见分光光度紫外－可见分光光度法ultraviolet and visible spectrophotometry;UV-vis 肩峰shoulder peak末端吸收end absorbtion生色团chromophore助色团auxochrome红移red shift长移bathochromic shift短移hypsochromic shift蓝（紫）移blue shift增色效应（浓色效应）hyperchromic effect减色效应（淡色效应）hypochromic effect强带strong band弱带weak band吸收带absorption band透光率transmitance,T吸光度absorbance谱带宽度band width杂散光stray light噪声noise暗噪声dark noise散粒噪声signal shot noise闪耀光栅blazed grating全息光栅holographic graaing光二极管阵列检测器photodiode array detector偏最小二乘法partial least squares method ,PLS 褶合光谱法convolution spectrometry褶合变换convolution transform,CT离散小波变换wavelet transform,WT多尺度细化分析multiscale analysis供电子取代基electron donating group吸电子取代基electron with-drawing group荧光分析荧光fluorescence荧光分析法fluorometryX-射线荧光分析法X-ray fulorometry原子荧光分析法atomic fluorometry分子荧光分析法molecular fluorometry振动弛豫vibrational relexation内转换internal conversion外转换external conversion体系间跨越intersystem crossing激发光谱excitation spectrum荧光光谱fluorescence spectrum斯托克斯位移Stokes shift荧光寿命fluorescence life time荧光效率fluorescence efficiency荧光量子产率fluorescence quantum yield荧光熄灭法fluorescence quemching method散射光scattering light瑞利光Reyleith scanttering light拉曼光Raman scattering light红外分光光度法红外线infrared ray,IR中红外吸收光谱mid-infrared absorption spectrum,Mid-IR 远红外光谱Far-IR微波谱microwave spectrum,MV红外吸收光谱法infrared spectroscopy红外分光光度法infrared spectrophotometry振动形式mode of vibration伸缩振动stretching vibration对称伸缩振动symmetrical stretching vibration不对称伸缩振动asymmetrical stretching vibration弯曲振动bending vibration变形振动formation vibration面内弯曲振动in-plane bending vibration,β剪式振动scissoring vibration,δ面内摇摆振动rocking vibration,ρ面外弯曲振动out-of-plane bending vibration,γ面外摇摆振动wagging vibration,ω蜷曲振动twisting vibration ,τ对称变形振动symmetrical deformation vibration ,δs不对称变形振动asymmetrical deformation vibration, δas 特征吸收峰charateristic avsorption band特征频率characteristic frequency相关吸收峰correlation absorption band杂化影响hybridization affect环大小效应ring size effect吸收峰的强度intensity of absorption band环折叠振动ring prckering vibration原子吸收分光光度原子光谱法atomic spectroscopy原子吸收分光光度法atomic absorption spectrophotometry,AAS 原子发射分光光度法atomic emmsion spectrophotometry,AES原子荧光分光光度法atomic fluorescence spectrophotometry,AFS 核磁共振波谱核磁共振nuclear magnetic resonance,NMR核磁共振波谱NMR spectrum核磁共振波谱法NMR spectroscopy扫场swept field扫频seept frequency连续波核磁共振continuous wave NMR,CW NMRFourier变换NMR PFT-NMR,FT-NMR二维核磁共振谱2D-NMR质子核磁共振谱proton magnetic resonance spectrum,PMR氢谱1H-NMR碳－13核磁共振谱13C-NMR spectrum,13CNMR自旋角动量spin angular momentum磁旋比magnetogyric ratio磁量子数magnetic quantum number,m进动precession弛豫历程relaxation mechanism局部抗磁屏蔽local diamagnetic shielding屏蔽常数shielding constant化学位移chemical shift国际纯粹与应用化学协会IUPAC磁各向异性magnetic anisotropy远程屏蔽效应long range shielding effect结面nodal plane自旋－自旋偶合spin-spin coupling自旋－自旋分裂spin=spin splitting单峰singlet,s双峰doublet,d三重峰triplet,t四重峰quartet五重峰quintet六重峰sextet偕偶geminal coupling邻偶vicinal coupling远程偶合long range coupling磁等价magnetic eqivalence自旋系统spin system一级光谱first order spectrum二级光谱（二级图谱）second order spectrumC-H光谱C-H correlated spectroscopy,C-H COSY质谱分析法mass spectrometry质谱mass spectrum,MS棒图bar graph选择离子检测selected ion monitoring ,SIM直接进样direct probe inlet ,DPI接口interface气相色谱－质谱联用gas chromatography-mass spectrometry,GC-MS高效液相色谱－质谱联用high performance liquid chromatography-mass spectrometry,HPLC-MS电子轰击离子源electron impact source,EI离子峰quasi-molecular ions化学离子源chemical ionization source,CI场电离field ionization,FI场解析field desorptiion,FD快速原子轰击离子源fast stom bombardment ,FAB质量分析器mass analyzer磁质谱仪magnetic-sector mass spectrometer 四极杆质谱仪（四极质谱仪）quadrupole mass spectrometer原子质量单位amu离子丰度ion abundance相对丰度(相对强度)relative avundance基峰base peak质量范围mass range分辨率resolution质谱灵敏度sensitivity信噪比S/N分子离子molecular ion碎片离子fragment ion同位素离子isotopic ion亚稳离子metastable ion亚稳峰metastable peak母离子paren ion子离子daughter含奇数个电子的离子odd electron含偶数个电子的离子even eletron,EE均裂homolytic cleavage异裂（非均裂）heterolytic cleavage半均裂hemi-homolysis cleavage重排rearragement分子量MWα－裂解α-cleavage色谱分析色谱法（层析法）chromatography固定相stationary phase流动相mobile phase超临界流体色谱法SFC高效毛细管电泳法high performance capillary electroporesis,HPEC 气相色谱法gas chromatography,GC液相色谱法liquid cromatography,LC超临界流体色谱法supercritical fluid chromatography,SFC气-固色谱法GSC气-液色谱法GLC液-固色谱法LSC液-液色谱法LLC柱色谱法column chromatography填充柱packed column毛细管柱capillary column微填充柱icrobore packed column高效液相色谱法high performance liquid chromatography,HPLC平板色谱法planar平板色谱法plane chromatography纸色谱法paper chromatography薄层色谱法thin layer chromatography,TLC薄膜色谱法;thiin film chomatography毛细管电泳法capillary electrophoresis,CE分配色谱法partition chromatography吸附色谱法adsorpion chromaography离子交换色谱法ion exchange chromatography,IEC空间排阻色谱法steric exclusion chromatography,SEC亲和色谱法affinity chromatography分配系数distribution cofficient狭义分配系数partition coefficient凝胶色谱法gel chromatography凝胶渗透色谱法gel permeation chromatography,GPC凝胶过滤色谱法gel filtration chromatography,GFC渗透系数permeation coefficien;Kp化学键合相色谱法chemically bonded-phase chromatography分配系数distribution coefficient靛菁绿indocyanine气相色谱－傅立叶变换红外光谱GC-FTIR液相色谱薄层色谱法TLC吸附adsorption活化activation脱活性deactivation交联度degree of cross linking交换容量exchange capacity薄层板thin layer plate展开剂developing solvent ,developer临界胶束浓度criticak micolle concentration ,CMC相对比移值relative Rf, Rr分离度resolution ,R分离数separation number,SN煅石膏Gypsum羧甲基纤维素钠CMC-Na吸收光谱联用TLC-UV薄层色谱－荧光联用TLC-F薄层色谱－红外吸收光谱联用TLC-IR薄层色谱法TLC-MS纸色谱法paper chromatography上行展开ascending development下行法展开descending development双向展开two dimensional develoooment气相色谱气相色谱法gas chromatography前延峰leading peak拖尾峰tailing peak对称因子symmetry factor,fs保留时间retention time保留体积retention volume死时间dead time调整保留时间asjusted retention time半峰宽peak width at half height,W1/2 or Y1/2峰宽peak width,W等温线isotherm理论塔板高度height equivalent to atheoretical plate化学键合相chemically bonded phase丁二酸二乙二醇聚酯polydiethylene glycol succinate,PDEGS,DEGS 高分子多孔微球GDX苯乙烯STY乙基乙烯苯EST二乙烯苯DVB涂壁毛细管柱wall coated open tubular column,WCOT载体涂层毛细管柱supprot coated open tubular column,SCOT热导检测器thermal conductivity detector,TCD氢焰离子化检测器hydrogen flame ionization detector,FID电子捕获检测器electron capture detector ,ECD噪声noise,N漂移drift,d灵敏度sensitivity检测限(敏感度)detectability,D,M分离度resolution归一化法normalization method外标法external standardization高效液相色谱高效液相色谱法high performance liquid chromatography,HPLC高速液相色谱法high speed LC,HSLC高压液相色谱法high pressure LC,HPLC高分辨液相色谱法high resolution LC,HRLC液固吸附色谱法（液固色谱法）liquid-solid adsorption chromatography,LSC液液色谱法liquid-liquid chromatography,LLC正相normal phase,NP反相reversed phase,RP化学键合相色谱法bonded phase chromatography,BPC十八烷基octadecylselyl,ODS离子对色谱法paired ion chromatography,PIC反相离子对色谱法RPIC离子抑制色谱法ion suppression chromatography,ISC离子色谱法ion chromatography,IC手性色谱法chiral chromatography,CC环糊精色谱法cyclodextrin chromatography,CDC胶束色谱法micellar chromatography,MC亲和色谱法affinity chromatography,AC固定相stationary phase化学键合相chemically bonde phase封尾、封顶、遮盖end capping手性固定相chiral stationary phase,CSP恒组成溶剂洗脱isocraic elution梯度洗脱gradient elution紫外检测器ultraviolet detector,UVD荧光检测器fluorophotomeric detector,FD电化学检测器ECD示差折光检测器RID光电二极管检测器photodiode array detector ,DAD三维光谱－波谱图3D-spectrochromatogram蒸发光散射检测器evaporative light scattering detector,ELSD安培检测器ampere detector,AD高效毛细管电泳法high performance capillary electrophoresis,HPCE淌度mobility电泳electrophoresis电渗electroosmosis动力进样hydrodynamic injection电动进样electrokinetic injection毛细管区带电泳法capillary zone electrophoresis,CZE 胶束电动毛细管色谱micellar electrokinetic capillarychromatography,MECC毛细管凝胶电泳capillary gel electrophoresis,CGE 筛分sieving中文名称英文名称色谱图chromatogram 色谱峰chromatographicpeak 峰底peak base 峰高hpeak height 峰宽Wpeak width 半高峰宽Wh/2peak width athalf height 峰面积Apeak area 拖尾峰tailing area 前伸峰leading area 假峰ghost peak 畸峰distorted peak 反峰negative peak 拐点inflection point 原点origin 斑点spot 区带zone 复班multiple spot 区带脱尾zone tailing 基线base line 基线漂移baseline drift 基线噪声Nbase line noise 统计矩moment液相色谱法liquidchromatography，LC 液液色谱法liquid liquidchromatography，LLC 液固色谱法liquid solidchromatography，LSC 正相液相色谱法normal phaseliquid chromatography 反相液相色谱法reversed phaseliquid chromatography，RPLC 柱液相色谱法liquid columnchromatography 高效液相色谱法high performanceliquid chromatography，HPLC 尺寸排除色谱法size exclusionchromatography，SEC 凝胶过滤色谱法gel filtrationchromatography 凝胶渗透色谱法gel permeationchromatography，GPC 亲和色谱法affinitychromatography 离子交换色谱法ion exchangechromatography，IEC 离子色谱法ionchromatography 离子抑制色谱法ion suppressionchromatography 离子对色谱法ion pairchromatography实验室专业名词翻译疏水作用色谱法hydrophobicinteraction chromatography制备液相色谱法preparativeliquid chromatography凝胶薄层色谱法 gel thin layerchromatography离子交换薄层色谱法 ion exchangethin layer chromatography液相色谱仪liquidchromatograph制备液相色谱仪preparativeliquidchromatograph凝胶渗透色谱仪 gel permeationchromatograph 涂布器 spreader点样器 sampleapplicator色谱柱chromatographiccolumn棒状色谱柱 monolith columnmonolithcolumn微粒柱 microparticlecolumn填充毛细管柱 packedcapillary column空心柱 open tubularcolumn微径柱microborecolumn混合柱 mixed column组合柱 coupled column预柱 precolumn保护柱 guard column预饱和柱 presaturationcolumn浓缩柱 concentratingcolumn抑制柱 suppressioncolumn展开室 developmentchamber往复泵 reciprocatingpump注射泵 syringe pump气动泵 pneumatic pump蠕动泵 peristalticpump检测器 detector微分检测器 differentialdetector积分检测器 integraldetector总体性能检测器 bulk propertydetector溶质性能检测器 solute propertydetector(示差)折光率检测器 [differential] refractive indexdetector荧光检测器fluorescencedetector紫外可见光检测器 ultravioletvisible detector 电化学检测器electrochemicaldetector蒸发(激光)光散射检测器 [laser] light scattering detector光密度计 densitometer薄层扫描仪 thin layer scanner 柱后反应器 post-columnreactor体积标记器volume marker记录器 recorder积分仪 integrator馏分收集器fractioncollector工作站 work station固定相stationaryphase固定液 stationaryliquid载体 support柱填充剂 column packing化学键合相填充剂 chemicallybonded phasepacking薄壳型填充剂 pellicularpacking多孔型填充剂 porous packing吸附剂adsorbent离子交换剂ion exchanger基体 matrix载板 support plate粘合剂binder流动相 mobilephasemobile phase洗脱(淋洗)剂eluent展开剂developer等水容剂 isohydricsolvent改性剂 modifier显色剂 color[developing] agent 死时间 t0dead time保留时间 tR retentiontime调整保留时间t''R adjustedretention time死体积 V0dead volume保留体积 vR retentionvolume调整保留体积v''R adjustedretention volume柱外体积 Vext extra-columnvolune粒间体积 V0interstitialvolume(多孔填充剂的)孔体积 VPpore volume of porous packing 液相总体积 Vtol total liquidvolume洗脱体积 ve elutionvolume流体力学体积 vh hydrodynamicvolume相对保留值 ri.s relativeretention value分离因子αseparation factor流动相迁移距离dm mobile phase migration distance流动相前沿 mobile phasefront溶质迁移距离 ds solute migration distance 比移值 Rf Rf value高比移值 hRf high Rf value相对比移值 Ri.s relative Rfvalue保留常数值 Rm Rm value板效能 plateefficiency折合板高 hr reduced plate height分离度 R resolution液相载荷量 liquid phaseloading离子交换容量 ion exchangecapacity 负载容量 loadingcapacity渗透极限 permeabilitylimit排除极限 Vh max，exclusion limit拖尾因子 T tailing factor柱外效应 extra-columneffect管壁效应wall effect间隔臂效应 spacer armeffect边缘效应edge effect归一法 normalizationmethod内标法internalstandard method 外标法external standardmethod 叠加法addition method普适校准(曲线、函数calibration function or curve[function]谱带扩展(加宽) band broadening(分离作用的)校准函数或校准曲线universaluniversal加宽校正 broadeningcorrection加宽校正因子 broadeningcorrection factor 溶剂强度参数ε0solvent strength parameter 洗脱序列 eluotropicseries洗脱(淋洗)elution等度洗脱gradientelution梯度洗脱gradientelution(再)循环洗脱 recycling elution线性溶剂强度洗脱 linear solventstrength gradient程序溶剂programmedsolvent程序压力programmedpressure 程序流速 programmed flow匀浆填充 slurry packing停流进样 stop-flowinjection 阀进样 valve injection柱上富集 on-columnenrichment 流出液eluate柱上检测 on-columndetection 柱寿命 column life柱流失column bleeding显谱 visualization 活化 activation反冲 back flushing 脱气degassing沟流channeling过载 overloading。

临床实验室标本溶血检测与应用专家共识(征求意见稿)

临床实验室标本溶血检测与应用专家共识（征求意见稿）2018年6月28日，在2018中国医师协会检验医师年会检验前规范化管理与中医检验专题论坛、中国医师协会检验医师分会中医检验医学专业委员会（简称中医检验专委会）学术交流会上，中医检验专委会组织研讨了由中医检验专委会、中华中医药学会检验医学分会、北京中医药学会中医检验专委会组织编写的《临床实验室标本溶血检测与应用专家共识（征求意见稿）》（简称《共识》）。

中医检验专委会寿好长主任委员对《共识》的制定与应用做了说明。

临床实验室标本溶血检测与应用专家共识（征求意见稿）标本溶血是临床实验室（简称实验室）最常见的误差来源，是标本拒收的主要原因[1-2]。

因标本溶血发出错误结果报告可能造成误诊误治，重新抽血给患者增加痛苦、报告周期延长，复测造成人力、物力、经济损失[3-5]。

目前国际上已有标本溶血相关检测与应用标准、共识发布[6-8]。

由于经济水平、文化习惯上的差异，国际相关标准、指南难以符合各国的实际需求，有必要制定适合国情的标本溶血检测与临床应用专家共识，以指导相关检验及临床实践[9-11]。

中国医师协会检验医师分会中医检验医学专委会、中华中医药学会检验医学分会、北京中医药学会中医检验专委会组织专家讨论，制定《临床实验室标本溶血检测与临床应用专家共识》，主要基于目前血清(或血浆)标本溶血检测与临床应用的相关研究文献及我国实际，以满足临床需求为导向，对现有资料不足、争议较大问题采用专家共识的方法解决。

本共识的主要目的是利用现有的循证医学依据，为规范临床实验室标本溶血检测及临床应用提供指导和帮助。

随着技术发展、认识深化，本共识将持续更新，以满足检验及临床实践需求。

1标本溶血干扰信息1.1标本溶血干扰检验结果标本溶血红细胞破坏，由于细胞内容物释放、光学干扰、与试剂成分发生化学反应等机制对检验结果产生干扰，可导致检验结果假性升高或降低，对临床诊疗产生不良影响[12-13]。

新世纪高等院校英语专业本科生系列教材《综合教程3》Unit3

children from a friend’s house, where the letter carrier
takes his van up and down every driveway on a street.
Detailed Reading
8 We will go through the most extraordinary contortions to save ourselves from walking. Sometimes it’s almost ludicrous. The other day I was waiting to bring home one of my children from a piano lesson when a car stopped outside a post office, and a man about my age popped out and dashed inside. He was in the post office for about three or four minutes, and then came out, got in the car and drove exactly 16 feet (I had nothing better to do, so I paced it off) to the general store next door.
2. What’s the secret of success of that factory? The product and their manufacturing process are one unit. Automation, technology and skilled human labor combine to build the Porsche 911. And the factory runs like a precision machine.

改进的 QuEChERS 方法用于鱼肉中孔雀石绿、隐色孔雀石绿、结晶紫和隐色结晶紫的快速检测

改进的 QuEChERS 方法用于鱼肉中孔雀石绿、隐色孔雀石绿、结晶紫和隐色结晶紫的快速检测朱程云;魏杰;董雪芳;郭志谋;刘名扬;梁鑫淼【摘要】孔雀石绿（MG）和结晶紫（CV）具有抗菌等活性，常被违法用于水产养殖业。

但 MG、CV 及其代谢产物隐色孔雀石绿（LMG）、隐色结晶紫（LCV）具有致癌性。

所以水产品中染料的残留检测是食品安全分析的重要问题。

由于水产品基质复杂，样品前处理尤为重要。

本文发展了一种基于 QuEChERS 技术与高效液相色谱联用的方法，用于鱼肉中4种染料的同时检测。

对 QuEChERS 方法中提取剂体积、提取次数以及分散固相萃取材料进行了优化。

结果表明反相/强阴离子交换材料（C18SAX）能有效提高回收率。

在最优条件下，4种染料在0.5~100mg / L 范围内线性良好，相关系数均大于0.998。

该方法在鱼肉中的回收率为73％~91％，RSD 为0.66％~5.41％。

结果表明该方法简单、高效，适合于鱼肉中染料的快速检测。

%Triphenylmethane dyes malachite green(MG)and crystal violet(CV)have been used as antimicro-bial,antiparasitic and antiseptic agents in aquaculture. However,MG and CV,as well as their metabolitesleu-comalachite green( LMG)and leucocrystal violet( LCV)are potential mutagens and carcinogens. Thus,the efficient determination of dye residues is of great concern. Considering the complexity of the aquatic products, the sample pretreatment is significant for decreasing matrix interference and improving detection sensitivity. In this study,a simple and rapid QuEChERS procedure was developed and combined with HPLC analysis for the simultaneous determination of the four dyes in fish tissue. An XCharge C18 column was applied in HPLC analy-sis to achieve goodpeak shape and selectivity. The pretreatment method involved the extraction of dyes from fish tissue and further clean-up with dispersive solid phase extraction(d-SPE)material. The extraction volume, extraction time as well as d-SPE materials were systematically optimized. The results indicated that reversed-phase / strong anion exchange(C18SAX)adsorbent in the d-SPE procedure could effectively improve the recov-ery compared with conventional C18 or C18 incorporated with primary secondary amine(PSA)material. Under optimized conditions,good linearity was achieved in the concentration range of 0. 5-100 mg / L with R 2 greater than 0. 998. The recoveries were 73% -91% and the precisions were 0. 66% -5. 41% . The results demonstrated the feasibility and efficiency of QuEChERS procedure incorporated with HPLC for dye monitoring.【期刊名称】《色谱》【年(卷),期】2014(000)004【总页数】7页(P419-425)【关键词】QuEChERS;高效液相色谱;孔雀石绿;隐色孔雀石绿;结晶紫;隐色结晶紫;鱼肉组织【作者】朱程云;魏杰;董雪芳;郭志谋;刘名扬;梁鑫淼【作者单位】大连交通大学环境与化学工程学院，辽宁大连 116028; 中国科学院大连化学物理研究所分离分析化学重点实验室，辽宁大连 116023;中国科学院大连化学物理研究所分离分析化学重点实验室，辽宁大连 116023;中国科学院大连化学物理研究所分离分析化学重点实验室，辽宁大连 116023;中国科学院大连化学物理研究所分离分析化学重点实验室，辽宁大连 116023;大连交通大学环境与化学工程学院，辽宁大连 116028; 中国科学院大连化学物理研究所分离分析化学重点实验室，辽宁大连 116023;中国科学院大连化学物理研究所分离分析化学重点实验室，辽宁大连 116023【正文语种】中文【中图分类】O658Malachite green(MG)and crystal violet(CV)，which are triphenylmethane dyes，have been widely used in aquaculture as antimicrobial，antiparasitic and antiseptic agents in the past decades［1，2］.The major metabolites of MG and CV，leucomalachite green(LMG)and leucocrystalviolet(LCV)possess similar biological characteristics［3］.Owing to their potential carcinogenicity，the addition of MG and CV in aquaculture is nowadays absolutely forbidden［1，4］.However，illegal utilization of dyes still exists because they are cheap and efficient［5］.Thus，multi-residues determination of dyes in aquatic products is of great significance. Considering the complexity of the matrix in aquatic products，sample pretreatment for decreasing or eliminating matrix interference and improving the detection sensitivity is of great concern.Numerous sample pretreatment methods have been established in previous reports［6-11］.Traditional liquid-liquid extraction method can be easily realized although it consumes large volume of solvents［6］.Enzyme-linked immune sorbent assay(ELISA)［12-14］exhibits good selectivity，but itsuffers from false positive results.Solid phase extraction(SPE)is a time-consuming method although the matrix interference can be efficiently removed ［15，16］.Molecularly imprinted solid phaseextraction(MISPE)for sample preparation reveals good specificity.However，the preparation of MISPE materials is difficult［17，18］.QuEChERS，representing the abbreviation of“quick，easy，cheap，effective，rugged and safe”，has been acknowledged as a rapid and efficient pretreatment method for the determination of hydrophobic pesticides［19-23］as well as veterinary drug residues［24，25］.The QuEChERS procedure involves two steps:(i)extraction/partitioning basedon the use of NaCl and MgSO4for salting out，and(ii)dispersive solid phase extraction(d-SPE)for clean-up.In consideration of the hydrophobicity of MG，LMG，CV and LCV，the introduction of QuEChERS for sample preparation is advantageous via extracting dye into the organic layer and cleaning-up by d-SPE procedure.By optimizing the extraction volume，extraction time and d-SPE materials，a specific pretreatment method was developed which greatly simplified the sample preparation and increased the throughput.With the combination of the proposed QuEChERS procedure and HPLC method based on XCharge C18 column，thesimultaneous determination ofMG，LMG，CV and LCV in fish tissues was successfully realized.1 Experimental1.1 Chemicals and materialsMalachite green(MG)，crystal violet(CV)and leucocrystal violet(LCV)werepurchased from Sigma-Aldrich(St.Louis，MO，USA)；leucomalachite green(LMG)was obtained from Dr Ehrenstorfer GmbH(Augsburg，Germany).Acetonitrile(ACN)of HPLC grade was purchased fromMerck(Darmstadt，Germany).Ammonium formate(NH4FA)and formicacid(FA)were purchased from J＆K Scientific(Beijing，China).Water for HPLC mobile phase was purified with a Milli-Q system(Millipore，Billerica，MA，USA).All other reagents were of analytical grade and used without further purification.Reversedphase/strong anion-exchange mixed-mode material(C18SAX)(40-75 μm，particle size)described in our previous report ［26］was selected as d-SPE adsorption material.C18，primary secondary amine(PSA)materials and XCharge C18 column(3.0 mm×100 mm i.d.，5μm particles)were from Acchrom Corp.(Beijing，China).1.2 HPLC conditionsA Hitachi Chromaster HPLC system(Tokyo，Japan)consisting of 5110 quaternary pump，5210 auto sampler，5310 column oven and 5430 diode array detector(DAD)was employed for HPLC analysis.The separation was performed on an XCharge C18 column.The column temperature was set at 40℃and flow rate was1 mL/min.The injection volume was20 μL.The mobile phase composed of ACN(A)，water(B)and 100 mmol/L ammonium formate(pH 3.0，C).The elution condition was 0-3 min，40%A-65%A；3-8 min，65%A-75%A，while mobile phase C was kept constant at 20%to obtain a buffer concentration of 20 mmol/L.Each dye was determined atthe maximum absorption wavelength:620 nm for MG，590 nm for CV，263 nm for LCV and LMG.1.3 Sample preparationCod fish was from local supermarket(Dalian，China).The skin and bone were removed.Then the fish was cut into strips and homogenized.The homogenized sample was stored at-20℃in the refrigerator until sample pretreatment.Fig.1 Structures of malachite green(MG)，crystal violet(CV)，leucomalachite green(LMG)and leucocrystal violet(LCV)The homogenized cod sample(2 g)was weighed into a 15 mL polypropylene tube.Then，2 mL of ammonium formate(100 mmol/L，pH 3.0)and 3 mL of ACN were added.The sample was shook vigorously to extract the analytes from the matrix.Then 2 g of sodium chloride was added into the solution for partitioning.The sample was mixed for about 2 min and centrifuged at 6000 r/min for 5 min.After that，1 mL of supernatant and 50 mg of C18SAX material were transferred into a 2.5 mL polypropylene tube.The polypropylene tube was shook and kept in ultrasonic bath for 1 min.The mixtu re was filtered through 0.22 μm membrane.The resulting filtrate was mixed with ammonium formate(100 mmol/L，pH 3.0)in the ratio of 4∶1(sample solution∶ammonium formate，v/v).The prepared solution was injected into the HPLC system for analysis. 1.4 Standard and reagent solutionsThe mixed stock solution with mass concentration of 100 mg/L was dissolved by ACN.It was stored at 4℃and protected against light for less than two weeks.The working solution was prepared through diluting the stock solution with the ini tial mobile phase(ACN∶water∶100 mmol/Lammonium formate=40∶40∶20，v/v/v).The concentrations of working solution were diluted at 0.5，1，5，10，25，50 μg/mL.2 R esults and discussion2.1 Establishment of chromatographic methodsThe resolution of MG，CV，LCV and LMG dyes(structures shown in Fig.1)which are basic compounds with good selectivity and peak shape is difficult on traditional C18 columns，especially for LCV and LMG ［6，27］.According to the previous studies of our group［28，29］，XCharge C18 column displayed great superiority in the separation of basic compounds.Therefore，XCharge C18 column was selected for the development of the analytical method and the mobile phase conditions was optimized.As shown in Fig.2a，the compounds could not be well resolved with 0.1%(v/v)FA/H2O in the mobile phase and LMG was not eluted within 10 min.Since the utilization of buffer solution is advantageous for improving peak shape and selectivity，100 mmol/L ammonium formate with pH 5.1 was employed as the mobile phase additive.The peak shapes were improved，but LCV and LMG were not well separated(Fig.2b).When the pH value of ammonium formate was changed to 3.0，the resolution of the four dyes was successfully achieved in 8 min with good peak shapes(Fig.2c).2.2 Establishment of pretreatment methodFig.2 Dyes separated on XCharge C18 column with different mobile phasesMobile phase conditions:a.ACN/(0.1%FA/water)；b.ACN/water/100 mmol/L NH4FA，pH 5.1；c.ACN/water/100 mmol/L NH4FA，pH 3.0.The QuEChERS procedure is flexible as it provides a template for sample preparation.The solvent and sorbent can be optimized according to the property of the target analytes.Mostly，the organic solvent used for extraction and partitioning is acetonitrile，which can easily generate phase separation with the addition of sodium chloride.In this work，the volume of extraction solvent and the kind of adsorption sorbent were systematically optimized to obtain best recovery and sensitivity.2.2.1 Optimization of extraction and partitioningThe volume of extraction solvent in QuEChERS procedure directly affects the sensitivity and recovery.The insufficient solvent would cause incomplete extraction，resulting in poor recovery，while excessive extraction solvent severely dilutes the analytes，leading to low detection sensitivity.To balance the recovery and sensitivity，the volume of acetonitrile for extraction was optimized from 2 mL to 7 mL.As shown in Fig.3，the peak areas of four dyes increased from 2 mL to 3 mL，and then slightly decreased from 3 mL to 7 mL.The results indicated that 3 mL of acetonitrile was optimal for the extraction of dyes in 2 g of homogenized fish tissue.More acetonitrile could not improve the extraction efficiency but reduce the detection sensitivity due to the dilution of analytes.Thus the volume of extraction solvent was determined to be 3 mL.Then the extraction time was verified.The homogenized fish tissue(2 g)was first extracted by 2 mL of acetonitrile，and then 1 mL of acetonitrile for re-extraction.The supernatants were merged and detected.The results showedno obvious differences(results not shown).So the fish tissue was extracted once with 3 mL of acetonitrile.Fig.3 Influence of extraction volume on the peak areas of dyesIn QuEChERS procedure，partitioning was achieved by the use of sodium chloride and magnesium sulfate.In this case，the recovery of the dyes was obviously deteriorated when magnesium sulfate was used.Therefore only sodium chloride was used for partitioning.In order to drive water from acetonitrile layer，excess sodium chloride(2 g)was added.Hardly any dyes were detected in aqueous layer.And the acetonitrile layer was transferred into a polypropylene tube for d-SPE clean-up before HPLC analysis.2.2.2 Selectivity of adsorption sorbentAfter the extraction/partitioning，dyes and some nonpolar interferences were partitioned into the acetonitrile layer.In order to remove the interferences and clean-up the sample，d-SPE with a proper adsorptive material was performed.C18 and PSA(structures shown in Fig.4)are commonly used materials for adsorption ［30，31］.C18 mainly adsorbs fat，lipid and some other non-polar interferences，while PSA adsorbs fatty acids and organic acids，etc.In this experiment，C18 and PSA were first employed as adsorbents.As shown in Table 1，the recoveries of dyes were about 70%-90%with C18 as d-SPE material.If PSA was used together with C18，the recoveries reduced to about 40%-80%.The color of the sorbents after d-SPE was shown in Fig.5.In Fig.5a(C18 material)andFig.5b(C18 and PSA materi-als)，the sorbents were obviously changed to blue or violet，further demonstrating the adsorption of MG and CV.As thefour dyes were all hydrophobic and basic compounds，the electrostatic attraction between dyes and silanol groups on C18 material together with the original hydrophobic interaction led to low recoveries.When PSA was added，the alkaline PSA enhanced the ionization of silanols both on C18 and PSA，resulting in poor recoveries.Fig.4 Structures of C18，PSA and C18SAX materialsFig.5 Color of adsorbents in lower layers after d-SPE procedurea.C18；b.C18 and PSA；c.C18SAX.Table 1 R ecoveries of the four dyes after d-SPE with different adsorbentsAdsorbent Recoveries/%MG CV LCVLMG C18(50.0 mg) 86.8 84.8 73.6 87.7 C18(50.0 mg)and PSA(50.0 mg)46.0 40.6 78.0 83.7C18SAX(50.0 mg) 101.4 102.2 83.5 87.6In a previous work［26］，we developed a reversedphase/strong anion-exchange mixed-mode stationary phase(named C18SAX，Fig.4)based on polar-copolymerized approach.The C18SAX material possesses C18 and quaternary ammonium groups，which can provide hydrophobic and electrostatic interaction simultaneously.With C18SAX as d-SPE material，the nonpolar and acidic interferences in the acetonitrile layer were adsorbed by the sorbent.Meanwhile，the quaternary ammonium group provided electrostatic repulsion interaction against the basic dyes.As shown in Table 1 and Fig.5c，the recoveries were in the range of 83.51%-102.19% for the four dyes，and the C18SAX material was still white after the adsorption.Consequently，C18SAX mixed-mode material is superior to the mechanically mixed C18 and PSA materials in cleaning-up the sampleand avoiding adsorption of dyes.Based on the above discussions，this method was easily streamlined in the determination of dye residues in aquatic products.As shown in Fig.6，Part I concerns the extraction/partitioning，while PartⅡ involves the clean-up of the sample with d-SPE material，and PartⅢis for HPLC analysis.2.3 Method validationThe performance of the optimized approach for the determination of MG，CV，LCV and LMG dyes was validated with respect to the linearity，recovery，intraday and inter-day precisions as well as limit ofdetection(LOD)and limit of quantitation(LOQ).The calibration was performed with the use of matrix-matched standards.As shown in Table 2，the four dyes expressed good linearities in the range of 0.5-100 mg/L，with correlation coefficients all above 0.998.In the spiked range from 5 to 25 mg/L，the recoveries were between88.63%and 110.62%，with intra-day and inter-day precisions of 0.7%-3.5%and 1.6%-5.4%，respectively.The LODs(calculated by signal to noise ratio of 3)were 3.2 μg/kg for MG，Fig.6 Flowchart of dye determination:extraction/partitioning(part I)，clean-up by dispersive solid phase extraction material(part II)and HPLCanalysis(part III)Table 2 Matrix matched calibrations and validation data for fish tissueAnalyte Linear range/(mg/L)Correlation coefficientSpiked/(mg/L)Recovery/%RSD/%Intra-day(n=5)Inter-day(n=15)Sensitivity LOD/(μg/kg)LOQ/(μg/kg)MG 0.5-100.0 0.999 5 88.6 1.7 2.3 3.2 9.610 97.91.72.825 103 1.5 1.6 CV 0.5-100.0 0.999 5 96 0.7 2.1 1.9 5.710 105.4 1.22.325 110.6 0.8 1.8 LCV 0.5-100.0 0.998 5 95.8 1.4 4.2 23.4 70.210 96.3 1.6 1.925 101.2 34.2 LMG 0.5-100.0 0.999 5 94.1 3.5 3.1 24.1 72.310 92.8 0.7 3.125 110.7 3.55.42.4 Sample analysisThe optimized method was applied to detect MG，CV，LCV and LMG in fish samples which were bought from local supermarket.The results of two batches of cod samples were negative.3 ConclusionsThe present study demonstrated the simplicity and high-efficiency of QuEChERS pretreatment method combined with HPLC for the fast analysis of triphenylmethane dyes in fish tissue.XCharge C18 was applied in the separation of MG，LMG，CV and LCV with good selectivity and peak shape.The extraction/partitioning and d-SPE procedure in QuEChERS were systematically investigated.A C18SAX mixed-mode adsorbent was employed in the d-SPE procedure，exhibiting better recovery than conventional adsorbents.Method validation data showed satisfactory recoveries and precisions.On the other hand，the limitation of the present method also exists.The detection sensitivity cannot meet the demand ofthe minimum required performance limit(MRPL)for the dyes.In future work，MS detector will be applied for the improvement of the sensitivity. References:［1］Arroyo D，Ortiz M C，Sarabia L A，et al.J Chromatogr A，2009，1216(29):5472［2］Zhang Z，Zhou K，Bu Y Q，et al.Anal Methods，2012，4(2):429 ［3］Ascari J，Dracz S，Santos F A，et al.Food Addit Contam，2012，29(4):602［4］Andersen W C，Turnipseed S B，Karbiwnyk C M，et al.Anal Chim Acta，2009，637(1/2):279［5］Lee J B，Kim H Y，Jang Y M，et al.Food Addit Contam，2010，27(7):953［6］Chen G Y，Miao S.J Agric Food Chem，2010，58(12):7109［7］Tarbin J A，Chan D，Stubbings G，et al.Anal Chim Acta，2008，625(2):188［8］An L，Deng J，Zhou L，et al.J Hazard Mater，2010，175(1):883 ［9］Tsai C H，Lin J D，Lin C H.Talanta，2007，72(2):368［10］Hurtaud-Pessel D，Couedor P，Verdon E.J Chromatogr A，2011，1218(12):1632［11］Fux E，Rode D，Bire R，et al.Food Addit Contam，2008，25(8):1024［12］Shen Y D，Deng X F，Xu Z L，et al.Anal Chim Acta，2011，707(1/2):148［13］Xing W W，He L，Yang H，et al.J Sci Food Agric，2009，89(13):2165［14］Durnez L，Bortel W V，Denis L，et al.Malar J，2011，10:195 ［15］Deng J C，Li L H，Yang X Q，et al.Food Science，2012，33(14):150 ［16］Stubbings G，Tarbin J，Cooper A，et al.Anal Chim Acta，2005，547(2):262［17］Lian Z R，Wang J T.Mar Pollut Bull，2012，64(12):2656［18］Li Y H，Yang T，Qi X L，et al.Anal Chim Acta，2008，624(2):317 ［19］Chen W，Ren Y D，Liu H，et al.Journal of Henan Agricultural Sciences，2011，40(2):111［20］Paya P，Anastassiades M，Mack D，et al.Anal Bioanal Chem，2007，389(6):1697［21］Zhang Z Y，Gong Y，Shan W L，et al.Chinese Journal of Chromatography，2012，30(1):91［22］Huang Y C，Ding W W，Zhang Z M，et al.Chinese Journal of Chromatography，2013，31(7):613［23］Chen X S，Bian Z Y，Yang F，et al.Chinese Journal of Chromatography，2013，31(11):1116［24］Aguilera-Luiz M M，Vidal J L M，Romero-Gonzalez R，et al.J Chromatogr A，2008，1205(1/2):10［25］Stubbings G，Bigwood T.Anal Chim Acta，2009，637(1/2):68 ［26］Wei J，Guo Z M，Zhang P J，et al.J Chromatogr A，2012，1246:129［27］Stella C，Rudaz S，Veuthey J L，et al.Chromatographia，2001，53:S-113［28］Wang C R，Guo Z M，Long Z，et al.J Chromatogr A，2013，1281:60［29］Zhang J C，Wei J，Zhong H M，et al.Chinese Journal of Chromatography，2013，31(1):79［30］Lehotay S J，Son K A，Kwon H，et al.J Chromatogr A，2010，1217(16):2548［31］Walorczyk S.J Chromatogr A，2008，1208(1/2):202。

本科生、分析研究生均可使用《化学》中常见词汇的中英对照

《分析化学》中常见词汇的中英对照第一章绪论分析化学：analytical chemistry定性分析：qualitative analysis定量分析：quantitative analysis物理分析：physical analysis 物理化学分析：physico-chemical analysis仪器分析法：instrumental analysis流动注射分析法：flow injection analysis；FIA顺序注射分析法：sequentical injection analysis。

SIA化学计量学：chemometrics第二章误差的分析数据处理绝对误差：absolute error 相对误差：relative error系统误差：systematic error 可定误差：determinate error 随机误差：accidental error 不可定误差：indeterminate error准确度：accuracy精确度：precision偏差：debiation，d平均偏差：average debiation 相对平均偏差：relative average debiation标准偏差<标准差）：standerd deviation。

S相对平均偏差：relatibe standard deviation。

RSD变异系数：coefficient of variation误差传递：propagation of error有效数字：significant figure 置信水平：confidence level显著性水平：level of significance合并标准偏差<组合标准差）：pooled standard debiation 舍弃商：rejectionquotient 。

Q化学定量分析第三章滴定分析概论滴定分析法：titrametric analysis滴定：titration容量分析法:volumetric analysis化学计量点：stoichiometric point等当点：equivalent point电荷平衡：charge balance电荷平衡式：charge balance equation质量平衡：mass balance物料平衡：material balance 质量平衡式：mass balance equation第四章酸碱滴定法酸碱滴定法：acid-base titrations质子自递反应：autoprotolysis reaction质子自递常数：autoprotolysis constant质子条件式:proton balance equation酸碱指示剂：acid-base indicator指示剂常数：indicator constant变色范围：colour change interval混合指示剂：mixed indicator 双指示剂滴定法：double indicator titration第五章非水滴定法非水滴定法：nonaqueous titrations质子溶剂：protonic solvent 酸性溶剂：acid solvent碱性溶剂：basic solvent两性溶剂:amphototeric solvent无质子溶剂：aprotic solvent 均化效应：differentiating effect区分性溶剂：differentiating solvent离子化：ionization离解：dissociation结晶紫：crystal violet萘酚苯甲醇: α-naphthalphenol benzyl alcohol奎哪啶红：quinadinered百里酚蓝：thymol blue 偶氮紫：azo violet溴酚蓝：bromophenol blue第六章配位滴定法配位滴定法：compleximetry乙二胺四乙酸：ethylenediamine tetraacetic acid,EDTA螯合物：chelate compound金属指示剂：metal lochrome indcator第七章氧化还原滴定法氧化还原滴定法：oxidation-reduction titration碘量法：iodimetry溴量法：bromimetry ]溴量法：bromine method铈量法：cerimetry高锰酸钾法：potassium permanganate method条件电位：conditional potential溴酸钾法：potassium bromate method硫酸铈法：cerium sulphate method偏高碘酸：metaperiodic acid 高碘酸盐：periodate亚硝酸钠法：sodium nitrite method重氮化反应：diazotization reaction重氮化滴定法：diazotization titration亚硝基化反应：nitrozation reaction亚硝基化滴定法：nitrozation titration外指示剂：external indicator 外指示剂：outside indicator 重铬酸钾法：potassium dichromate method第八章沉淀滴定法沉淀滴定法：precipitation titration容量滴定法：volumetric precipitation method银量法：argentometric method 第九章重量分析法重量分析法：gravimetric analysis挥发法：volatilization method引湿水<湿存水）：water of hydroscopicity包埋(藏>水：occluded water 吸入水：water of imbibition 结晶水：water of crystallization组成水：water of composition 液-液萃取法：liquid-liquid extration溶剂萃取法：solvent extration反萃取：counter extraction 分配系数：partitioncoefficient分配比：distribution ratio 离子对<离子缔合物）：ion pair沉淀形式：precipitation forms称量形式：weighing forms 《分析化学》下册仪器分析概述物理分析：physical analysis 物理化学分析：physicochemical analysis仪器分析：instrumental analysis第十章电位法及永停滴定法电化学分析：electrochemical analysis电解法：electrolytic analysis method电重量法：electtogravimetry 库仑法：coulometry 库仑滴定法：coulometric titration电导法：conductometry电导分析法：conductometric analysis电导滴定法：conductometric titration电位法：potentiometry直接电位法：dirext potentiometry电位滴定法：potentiometric titration伏安法：voltammetry极谱法：polarography溶出法：stripping method电流滴定法：amperometric titration化学双电层：chemical double layer相界电位：phase boundary potential金属电极电位：electrodepotential化学电池：chemical cell液接界面：liquid junction boundary原电池：galvanic cell电解池：electrolytic cell 负极：cathrode正极：anode电池电动势：eletromotive force指示电极：indicator electrode参比电极：reference electroade标准氢电极：standard hydrogen electrode一级参比电极：primary reference electrode饱和甘汞电极：standard calomel electrode银－氯化银电极：silver silver-chloride electrode 液接界面：liquid junction boundary不对称电位：asymmetry potential表观PH值：apparent PH复合PH电极：combination PH electrode离子选择电极：ion selective electrode敏感器：sensor晶体电极:crystalline electrodes均相膜电极：homogeneous membrance electrodes非均相膜电极：heterog eneous membrance electrodes非晶体电极：non- crystalline electrodes刚性基质电极：rigid matrix electrode流流体载动电极：electrode with a mobile carrier气敏电极：gas sensing electrodes酶电极：enzyme electrodes金属氧化物半导体场效应晶体管：MOSFET离子选择场效应管：ISFET总离子强度调节缓冲剂：total ion strength adjustment buffer,TISAB永停滴定法：dead-stop titration双电流滴定法<双安培滴定法）：double amperometric titration第十一章光谱分析法概论普朗克常数：Plank constant 电磁波谱：electromagnetic spectrum光谱：spectrum光谱分析法：spectroscopic analysis原子发射光谱法：atomic emission spectroscopy质量谱：mass spectrum质谱法：mass spectroscopy,MS 第十二章紫外－可见分光光度法紫外－可见分光光度法：ultraviolet and visible spectrophotometry。

Dassault Syste

STRUCTURALSIMULATIONPLASTICSIMULATIONFLOWSIMULATIONSIMULATIONENGINEERDESIGNERANALYST SOLIDWORKS PRODUCT DEVELOPMENT SOLUTIONSSOLIDWORKS software provides users with intuitive 3D development environments that help maximize the productivity of yourdesign and engineering resources to create better products faster and more cost-effectively.SOLIDWORKS Simulation comes in several different packages, depending on whether the user is a designer, an analyst, or both.Design for StrengthThermal AnalysisFrequency AnalysisDesign for Endurance(high cycle fatigue)Easy multi-physicsNon-Linear AnalysisDynamic AnalysisMulti-Scale, Non-LinearLarge displacement contactproblemsComplex material problemsHigh and Low Speed fluid flowInternal and External fluid flowINNOVATION BY SIMULATION-DRIVEN DESIGNInnovation starts with someone asking, “What if?” or “Why not?” Answering these questions with any great certaintytypically requires the tim e and expense of physical prototyping and testing. But this can stifle innovation under theweight of an organization’s cost constraints.So, we asked, “What if many of the questions that arise from the painstaking process of designing, testing, refining and testingagain, could be answered before any metal was cut or wiring installed?” The result is SOLIDWORKS® Simulation, a dramatictransformation of the design process, where easy-to-use, yet powerful analysis tools can be employed every step of the way.SOLIDWORK S Simulation provides testing and analysis of parts and products in real-world environments in advance of anymanufacturing work. Teams can work concurrently to develop the design while validating any changes, thus speeding upthe design cycle. SOLIDWORKS Simulation also retains previous analyses and data so that any design changes throughout aproduct’s life can be quickly and easily recalculated ensuring product performance and reliability.As the SOLIDWORKS model is the information master at the center of the design process, the model holds companies’ analysis setupand results, meaning that any changes of a design throughout its lifecycle can be quickly and easily recalculated, ensuring productperformance and reliability. Thousands of companies have taken advantage of these tools, helping many to become leaders intheir markets.SOLIDWORK S Simulation tools deliver actionable results forboth the casual designer or engineer as well as the dedicatedanalyst. They provide a completely integrated design-and-analysis strategy, without ever having to leave the familiarSOLIDWORKS environment. Other benefits include:CONCEPT DESIGN SELECTION• Ensure assembly layout movement range and capabilitywith Sketch Motion.• Test early (incomplete) assemblies using connectors tomimic hardware.• Enable rapid design iteration with fast solvers that canguide design direction.PRODUCT DESIGN REFINEMENT• Determine operational loads and timing with MotionAnalysis.• Discover new design shapes with the Topology study.• Calculate Factor of Safety (FoS) and product performance.• Measure the impact of fluid flow on your designs withFlow Simulation.• Alter your design automatically for optimal strength andstiffness.• Evaluate the impact of complex materials and extreme loadsdefinition with Simulation Engineer.FINAL DESIGN VALIDATION• Test structural performance under extreme and dynamicloading.• Perform a multi-physics test that links fluid, thermal andmotion analysis to a structural test to determine theirimpact on structural performance.• Run a fatigue analysis to ensure product longevity.STREAMLINE DESIGN FOR STRUCTURAL STRENGTH, STIFFNESS AND ENDURANCEEnsuring the required structural strength, rigidity and endurance of a design has traditionally been in the realm of either physical testing or of specialist analysis tools. SOLIDWORKS Simulation delivers powerful analysis capabilities together with the SOLIDWORKS ease of use, resulting in a suite of structural analysis tools that can be used by both the designer and analyst.SOLIDWORKS Simulation can assist in determining a product’s capacity in the face of several factors:• Motion • Linear • Frequency • Fatigue• Thermal Structural • Topology and Optimization • Non-Linear • DynamicSTRUCTURAL SIMULATION ENGINEERUnderstanding product performance under extreme loading and deformation requires a robust non-linear solution. Structural Simulation Engineer from SIMULIA ® enables analysts to tackle the most challenging of static non-linear problems using:• The world class ABAQUS ® Solver • Advanced meshing tools • Comprehensive material models • Robust component contact formulationSTRUCTURAL ANAL YSIS FOR DESIGN“ T he power of the Simulation Engineer product is the ability to come up with solutions rapidly and reliably to complex problems that become part of the design process.”— Laurence Marks, Director Strategic Simulation & AnalysisSOLIDWORKS FLOW SIMULATION Advanced fluid flow simulation made easyUnderstanding the impact of fluid flow in and around your design can be key to evaluating its performance. Consider these design elements:• Internal external liquid and gas flow • Free surface flow • Non-Newtonian flows • Low speed to supersonic flows • Fans and rotating components • Conjugate heat transfer • Electronics cooling module• Pressure and temperature transfer to SOLIDWORK S Simulation for structural analysisSOLIDWORKS PLASTICSThe design of plastic components cannot be complete without an analysis of their manufacturing process and the level of mod performance. SOLIDWORK S Plastics Simulation enables designers and analysts to simulate the plastic injection molding process, including:• Confidence of component fill• Component wall thickness and rib placement evaluation • Weld line visualization• Optimize injection gate location.• Visualize the plastic flow front and check if the part will fill the mold completely.• Determine maximum injection pressure needed to fill the mold.• Optimize gate locations to avoid or at least minimize weld lines.See the full range of SOLIDWORKS software for design, simulation, technical communication and data management visit .。

利益相关分析法范文

利益相关分析法范文英文回答：## Stakeholder Analysis Framework.Introduction.Stakeholder analysis is a critical tool for understanding the interests, needs, and potential impact of different groups on a project or organization. Byidentifying and engaging key stakeholders, organizationscan increase the likelihood of project success and build stronger relationships with those affected by their actions.Steps in Conducting a Stakeholder Analysis.1. Identify stakeholders: Determine who has a stake in the project or organization, including both internal and external stakeholders.2. Analyze stakeholder interests and needs: Identify the specific interests, concerns, and expectations of each stakeholder group.3. Prioritize stakeholders: Assess the relative importance of each stakeholder group based on their power, influence, and legitimacy.4. Develop engagement plan: Determine how to involve stakeholders in the project or organization and how to manage their expectations.5. Monitor and evaluate stakeholder engagement: Track the progress of stakeholder engagement and make adjustments as needed.Benefits of Stakeholder Analysis.Improved decision-making: By understanding stakeholder interests, organizations can make more informed decisions that consider the needs of all affected parties.Increased transparency: Stakeholder analysis helps to ensure that all stakeholders are aware of the project or organization's goals and objectives.Enhanced relationships: By engaging stakeholders early on, organizations can build stronger relationships and foster trust.Reduced risk: Identifying and managing stakeholder concerns can help to mitigate potential risks and ensure project success.Example of a Stakeholder Analysis.A non-profit organization is planning a new program to provide housing assistance to low-income families. The organization conducts a stakeholder analysis to identify the following key stakeholders:Residents: The intended beneficiaries of the program.Board of Directors: Responsible for overseeing theorganization and its programs.Funders: Provide financial support for the program.Community organizations: Partner with the organization to provide services.Local government: Regulates the provision of housing assistance.By understanding the interests and needs of each stakeholder group, the organization can develop a program that meets the needs of the community while ensuring the support of key stakeholders.Conclusion.Stakeholder analysis is a valuable tool for organizations to understand their stakeholders and build stronger relationships. By identifying, prioritizing, and engaging stakeholders, organizations can increase the likelihood of project success and achieve their goals.中文回答：利益相关者分析框架。

英语作文介绍家庭成员的职业和爱好

英语作文介绍家庭成员的职业和爱好全文共3篇示例，供读者参考篇1My Family's Careers and PastimesFamily means everything to me. I have a pretty big family with a variety of personalities and interests. Each person has their own unique career path and hobbies that make them who they are. Let me introduce you to the special individuals that make up my family.Let's start with my dad. He's been working as an electrical engineer for over 20 years at a major technology company. His job involves designing and developing electrical systems and components for things like computers, smartphones, and other electronic devices. It's a challenging career that requires a lot of technical knowledge, problem-solving skills, and attention to detail. Despite the demanding nature of his work, my dad always makes time for his hobbies, which include golfing, reading historical novels, and trying out new recipes in the kitchen. He's an excellent cook and loves experimenting with different cuisines from around the world.My mom, on the other hand, is a high school English teacher. She has a true passion for literature and helping students develop their reading, writing, and analytical skills. Teaching is more than just a job for her – it's a calling. She spends countless hours preparing engaging lesson plans, grading papers, and providing one-on-one support to her students. Her hobbies revolve around the arts, as she enjoys attending theater performances, visiting art museums, and participating in a local book club. Mom also loves gardening and takes great pride in maintaining a beautiful flower garden in our backyard.Then there's my older sister, Emily. She's a rising star in the world of marketing and currently works as a brand manager for a well-known consumer products company. Her job involves developing and executing marketing strategies, managing advertising campaigns, and analyzing consumer trends to ensure her brand stays relevant and appealing to its target audience. Emily is a true creative at heart, and her hobbies reflect that. In her free time, she enjoys painting, sketching, and even dabbling in pottery. She's also an avid photographer and often shares her stunning shots on social media.My younger brother, Michael, is quite different from the rest of us. He's always had a knack for computers and technology,which led him to pursue a career in software development. He currently works as a software engineer for a cutting-edge tech startup, where he spends his days coding, troubleshooting, and collaborating with other developers to create innovative software solutions. Michael's hobbies revolve around gaming –both playing and designing video games. He's part of an online gaming community and even participates in local game development competitions.Aunt Sarah, my mom's sister, is a respected medical doctor specializing in pediatrics. She's been caring for children and their families for over 15 years, providing compassionate medical care and guidance. Aunt Sarah's job can be emotionally draining at times, but she finds solace in her hobbies, which include hiking, yoga, and mindfulness meditation. She's also an avid traveler and tries to take at least one international trip each year to explore new cultures and destinations.Last but not least, there's my grandfather – or "Poppy," as we affectionately call him. He's a retired mechanical engineer who spent his career designing and developing various machinery and equipment for manufacturing plants. These days, Poppy enjoys a more relaxed lifestyle, but he still keeps his mind sharp with his favorite hobbies, such as woodworking, solvingcrossword puzzles, and playing chess with his buddies at the local community center.As you can see, my family is a diverse bunch with different careers and interests. But despite our differences, we share a strong bond and a deep respect for each other's passions and pursuits. Family gatherings are always lively affairs, with everyone sharing stories about their latest projects, challenges, and achievements at work or discussing their latest hobby endeavors.I'm truly fortunate to be surrounded by such a supportive and inspiring group of individuals. Their varied careers have taught me the importance of finding work that you're passionate about and using your unique talents and skills to make a positive impact. And their diverse hobbies have shown me the value of pursuing interests outside of work – activities that nourish the mind, body, and soul.As I navigate my own journey through life, I hope to find a career that fulfills me the way my family members' careers fulfill them. And I aspire to cultivate a range of hobbies that bring me joy, challenge me, and provide a healthy balance to my life, just as their hobbies do for them.Most importantly, I strive to foster the same close-knit family bonds and unwavering support system that have been so instrumental in shaping who I am today. Family is the foundation upon which we build our lives, and I'm grateful for the incredible example set by my loved ones. Their careers and pastimes may differ, but their love, guidance, and encouragement remain constant – and that's what truly matters most.篇2My Family and Their Diverse InterestsHaving a large family means there's never a dull moment in my household. With parents, grandparents, aunts, uncles and cousins galore, our home is a lively hub of varied personalities and pursuits. Let me introduce you to the wonderful individuals who make up my clan and share a bit about their occupations and beloved hobbies.Let's start with my father, the breadwinner and patriarch of our family. Dad is a civil engineer who designs and oversees the construction of bridges, highways and other infrastructure projects. His job requires a great deal of technical knowledge, problem-solving skills and attention to detail. Despite the demanding nature of his career, Dad always makes time for hisfavorite pastimes - playing golf and tending to his vegetable garden. On weekends, you'll likely find him hitting a small white ball across meticulously manicured greens or getting his hands dirty cultivating tomatoes, peppers and other fresh produce.My mother's career is quite different from Dad's. She is an elementary school teacher who shapes young minds and instills a love of learning in her students. Mom's patience, creativity and nurturing spirit make her perfectly suited for this challenging yet rewarding profession. When not busy with lesson plans and grading papers, Mom relaxes by doing yoga, reading historical fiction novels and refinishing second-hand furniture she finds at flea markets and garage sales. Her creative flair and commitment to sustainability really shine through in these uniquely restored pieces.On my dad's side of the family, my grandfather spent his working years as an auto mechanic. Grandpa has an incredible knack for taking apart engines, identifying problems and putting everything back together in proper working order. His decades of experience allow him to diagnose automotive issues with incredible speed and precision. Grandpa's lifelong obsession is undoubtedly restoring classic cars from the 1950s and 60s. His prized possession is a fully refurbished 1957 Chevy Bel Air thatglistens with a flawless candy apple red paint job. Grandpa never misses an opportunity to enter his beloved Bel Air in local car shows and cruise-ins.My paternal grandmother's professional life was dedicated to nursing. As a registered nurse, Grandma worked in hospital maternity wards and nurseries, assisting in the birthing process and caring for newborn infants. Her nurturing spirit, compassion and clinical skills made her ideal for this role. During her retirement, Grandma discovered a talent for painting landscapes and still life scenes. She's an avid member of a local art club that meets weekly to share their works and develop their skills. Her paintings decorate the walls of our family's homes.Switching to my mom's side, my uncle is a talented chef who runs his own restaurant specializing in contemporary American cuisine with French and Italian influences. Uncle Michael's culinary masterpieces are true works of art, with beautiful presentation and perfectly balanced flavors. When not in his restaurant's kitchen, Uncle spends much of his free time gardening and growing fresh herbs, vegetables and edible flowers that he incorporates into his dishes. His home garden is a lush oasis filled with neat rows of plants, handcrafted trellises and garden art pieces.My aunt is a highly successful businesswoman, currently serving as the Chief Marketing Officer for a major national corporation. With a head for strategy, analysis and clear communication, she has helped her company increase brand awareness, drive sales and cultivate customer loyalty. Despite her demanding career, Aunt Linda's true passion is music. She is an accomplished pianist who practices diligently and performs in local recitals and concerts whenever possible. Aunt prefers classical composers like Chopin, Mozart and Beethoven, filling our home with beautiful melodies during her visits.As for me, I'm a high school junior trying to navigate the challenges of adolescence while determining my future path. I love science, especially biology, and am seriously considering a career as a medical researcher, doctor or veterinarian. My hobbies include reading, particularly sci-fi and fantasy novels, as well as playing video games (in moderation, of course!), and caring for my dog Rufus, who is a lovable mutt I adopted from our local animal shelter.As you can see, my family members come from diverse professional backgrounds yet we're all united by our pursuit of interests and hobbies that enrich our lives. From getting our hands dirty in the garden to making beautiful art and music,from working under the hood of an automobile to studying the intricate biology of living organisms, we each find joy and fulfillment in our unique passions outside of work. I feel incredibly fortunate to be surrounded by such hard-working, talented and multi-faceted individuals who model well-rounded lifestyles. Our family dynamic is never boring, that's for sure!篇3My Family - A Diverse Bunch with Unique InterestsWhen people ask me about my family, I always find it hard to know where to start. We are a fairly large and eclectic group, with a wide range of occupations and hobbies that make us a lively, if slightly unconventional, bunch.Let me begin with my father. He's a civil engineer who specializes in bridge construction and maintenance. His job requires a lot of travel to various project sites, both within our home country and internationally. While the long hours and frequent trips can be demanding, Dad absolutely loves his work. There's nothing that gets him more excited than studying blueprints for a new bridge design or inspecting a recently completed overpass. His passion lies in creating these marvels ofinfrastructure that connect communities and enable transportation and commerce.In his free time, Dad is an avid golfer. He first picked up the sport in college and has been hooked ever since. Most weekends you can find him out on the course, focusing intently and perfecting his swing. Mom jokes that golf is Dad's other true love and his "mistress" that he's always running off to spend time with. Still, we're all impressed by his dedication and low handicap. Some of my favorite memories are going to watch Dad compete in local tournaments when I was younger.My mother, on the other hand, could not be more different from Dad in terms of her career and interests. Mom is a talented artist who runs her own small graphic design studio. Her eye for color, form, and composition is really incredible. Whether she's creating a new logo, designing marketing materials, or just doodling in her sketchbook, her artistic flair shines through. Clients rave about her work and often say she has a genius for capturing the essence and personality they want to convey visually.In stark contrast to Dad's love of golf, Mom's biggest hobby is baking. Our kitchen is her canvas where she wields whisks and piping bags like paintbrushes to whip up the most delectablecakes, cookies, pastries, and other confections. The entire house always smells temptingly of fresh bread or sweet treats whenever Mom gets in one of her baking moods. Her specialties are elaborately decorated cakes for birthdays and other celebrations, which are too beautiful to eat (but we always devour them anyway). I've never met anyone with such a natural talent and passion for the art of baking.Next up is my older brother Marcus, who has followed in Mom's creative footsteps in his own way. After getting a film degree, Marcus now works as a freelance videographer and editor. He has a real gift for visual storytelling through the camera lens. Whether he's shooting a corporate promotional video, a short film, or just hobbyist YouTube content, Marcus has an incredible eye for compelling shots and sequences. Editing is where he really shines though - he can take raw footage and mold it into a powerful narrative that evokes certain emotions and keeps viewers engaged.Marcus' hobby is photography, whic。

好出身英文俚语

IntroductionEnglish slang, an ever-evolving tapestry of colloquial expressions, idioms, and lexical innovations, holds a unique position within the linguistic landscape. It transcends the boundaries of standard English, offering a more intimate glimpse into the cultural psyche, social dynamics, and generational shifts that shape the language. This comprehensive analysis delves into the multifaceted nature of English slang, examining its origins, functions, societal implications, and global reach.1. Origins and Evolution of English SlangSlang, derived from the Dutch word "sling," meaning "to sling words together," has been an integral part of the English language since the 16th century. Its origins can be traced to various sources, including:a) Social subcultures: Slang often emerges from marginalized or underground communities, such as criminal networks, ethnic minorities, or youth subcultures, as a means of covert communication and group identity reinforcement. For instance, terms like "hood" (originating from African American Vernacular English) or "chav" (British working-class youth culture) reflect these subcultural roots.b) Historical events and technological advancements: Significant historical changes, such as wars or technological revolutions, spawn new slang terms. The advent of the internet and social media platforms has given rise to an array of digital slang, such as "LOL" (Laugh Out Loud), "selfie," and "troll."c) Borrowings and linguistic hybridity: English slang is heavily influenced by other languages and cultures, reflecting the language's global spread and multicultural nature. Examples include "hasta la vista" (Spanish), "schmooze" (Yiddish), and "nom nom" (onomatopoeic borrowing from East Asian languages).Over time, slang undergoes a process of popularization, normalization, and eventual obsolescence. Some terms, like "cool" or "dude," become so ingrained in everyday language that they lose their 'slangy' edge, while others fade into obscurity or are replaced by newer expressions.2. Functions and Significance of English Slanga) Expressing informality and intimacy: Slang serves as a linguistic lubricant, fostering a sense of camaraderie and informality in casual conversations. It allows speakers to break down formal barriers and establisha shared, often humorous, communicative space.b) Conveying attitude and emotion: Slang words and phrases often carry emotional overtones or subtle nuances that standard English may lack. For example, "awesome" conveys enthusiasm and awe, whereas "meh" expresses apathy or indifference.c) Subverting authority and norms: By challenging conventional language use, slang can act as a form of linguistic rebellion, particularly among younger generations seeking to assert their independence and critique societal norms.d) Encoding group identity: Slang acts as a badge of belonging for specific social groups, signaling shared experiences, values, and cultural references. It can serve as an exclusionary tool, creating an insiders' code that outsiders may struggle to decipher.3. Societal Implications and CritiquesWhile English slang offers a vibrant and dynamic aspect of language use, it is not without controversy and criticism. Some argue that slang:a) Dilutes language quality: Critics contend that excessive reliance on slang leads to linguistic laziness, hampers clarity, and undermines the precision and richness of standard English.b) Reinforces social divides: The exclusivity of certain slang terms can exacerbate social stratification, as those unfamiliar with the lexicon may feel alienated or excluded from conversations.c) Promotes negative stereotypes: Certain slang terms, when used pejoratively, can perpetuate harmful stereotypes and contribute to discrimination. For instance, the term "ghetto" has been criticized for its racist connotations and reinforcement of class-based prejudices.4. Global Reach and Impact of English SlangAs English assumes the role of a global lingua franca, its slang has permeatedinternational discourse, influencing non-native speakers and being appropriated, adapted, and reinvented in diverse cultural contexts. This globalization of English slang:a) Reflects cultural exchange and hybridity: The adoption and adaptation of English slang in non-native contexts demonstrate linguistic and cultural syncretism, as local languages and cultures imbue borrowed terms with new meanings and associations.b) Challenges linguistic imperialism: The spread of English slang, particularly in digital spaces, empowers non-native speakers to engage with the language on their own terms, subverting the dominance of standard English and asserting local linguistic identities.c) Facilitates cross-cultural understanding: Familiarity with English slang can serve as a bridge between speakers from different linguistic backgrounds, fostering mutual understanding and facilitating smoother communication in multilingual settings.ConclusionEnglish slang, a vibrant and dynamic facet of the language, embodies the essence of cultural identity and communication in the modern era. Originating from diverse social, historical, and linguistic sources, it performs vital functions in informal discourse, expressing attitudes, emotions, and group affiliations. While facing criticisms regarding language degradation, social exclusion, and stereotype reinforcement, English slang also plays a pivotal role in promoting cross-cultural exchange, challenging linguistic hegemony, and reflecting the globalized, interconnected world we inhabit. As it continues to evolve alongside societal changes, English slang remains a testament to the resilience, creativity, and adaptability of human language.。

中国供应商成本优势

中国供应商成本优势中国是世界最大的加工工厂,就一些集团化的大企业来说,平均都会有20%-30%的零部件,原材料是从中国市场采购的.对我们集团来说,我们集团化采购整合刚刚开始，在中国的总采购比例相对比较低，所以我们在中国成立了自己的采购平台去持续开发中国的供应市场，寻找更多的成本节省的机会。

之前我个人一直认为,对于我们集团这种追求高附加值的企业来说,通过从中国采购来降低成本是非常轻松的,中国的供应商相对于欧洲供应商来说应该有绝对的优势. 直到采购平台开始为海外其他工厂询源，做成本节省项目的时候，才发现，我们中国的供应商不是在任何领域都是有绝对的竞争力的。

由于我们采购平台也在起步阶段，对海外工厂的支持目前受人员及供应商资源所限，仅限于塑胶零部件，五金冲压，五金机加工，紧固件，银点及相关零部件，PCB 等. 对比不同BU 的不同项目，有非常大的差别。

同样都是塑胶件，有一些零件我们要国外便宜30%以上，而有的项目国内价格比国外高出25%-50%，以下2个项目为例：项目A 继电器；项目B 开关1.项目A，产品寿命相对年轻，成品的附加值相对较高，数量适中，生产工序较复杂，非完全自动化生产，单个零件结构较复杂，零件更注重在功能实现而不是成本。

针对这类项目的零件（包括塑胶，冲压）我们通常会有至少30%的单个零件成本节省。

2.项目B，产品持续稳定生产超过30年，产品数量非常大6百万件每年，但是成品的附加值相对较小，生产工序少，全自动化组装，对零件的成本敏感度非常高。

对于项目B 中的个别零部件我们的国内价格甚至比国外高出25%。

有几十年生产历史的产品，经过了海外几十年的精益生产及持续的改进，产品已经非常成熟，产品所用的零件本身已经降到利润最低点，降价空间几乎没有，再考虑到我们的运输成本，关税，VMI，想从这类零件中为海外找到节省几乎是不可能。

对于这类项目并不适合单纯为降低成本在中国重新询源。

有什么会影响到中国供应商的成本优势？A．进口原材料B．效率及自动化生产C．汇率波动1.进口原材料客户指定进口原材料，很多只在欧洲或者北美生产及使用，国内供应商的采购周期长，采购价格价格高，还要再加上运输及进口关税，原材料本身就会比国外至少高出15%左右。

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a r X i v :a s t r o -p h /0310895v 1 31 O c t 2003PRECISION ANALYSIS OF THE LOCAL GROUP ACCELERATIONM.J.CHODOROWSKI &P.CIECIELA ¸GCopernicus Astronomical Center,Bartycka 18,00-716Warsaw,PolandWe reexamine likelihood analyses of the Local Group (LG)acceleration,paying particular attention to nonlinear eﬀects.Under the approximation that the joint distribution of the LG acceleration and velocity is Gaussian,two quantities describing nonlinear eﬀects enter these analyses.The ﬁrst one is the coherence function,i.e.the cross-correlation coeﬃcient of the Fourier modes of gravity and velocity ﬁelds.The second one is the ratio of velocity power spectrum to gravity power spectrum.To date,in all analyses of the LG acceleration the second quantity was not accounted for.Extending our previous work,we study both the coherence function and the ratio of the power spectra.With the aid of numerical simulations we obtain expressions for the two as functions of wavevector and σ8.Adopting WMAP’s best determination of σ8,we estimate the most likely value of the parameter βand its errors.As the observed values of the LG velocity and gravity,we adopt respectively a CMB-based estimate of the LG velocity,and Schmoldt et al.’s (1999)estimate of the LG acceleration from the PSCz catalog.We obtain β=0.66+0.21−0.07;thus our errorbars are signiﬁcantly smaller than those of Schmoldt et al.This is not surprising,because the coherence function they used greatly overestimates actual decoherence between nonlinear gravity and velocity.1IntroductionComparisons between the CMB dipole and the Local Group (LG)gravitational acceleration can serve not only as a test for the kinematic origin of the former but also as a constraint on cosmological parameters.A commonly applied method of constraining the parameters by the LG velocity–gravity comparison is a maximum-likelihood analysis,elaborated by several authors (especially by Strauss et al.1,hereafter S92).In a maximum-likelihood analysis,proper objects describing nonlinear eﬀects are the coherence function (CF),i.e.the cross-correlation coeﬃcient of the Fourier modes of the gravity and velocity ﬁelds,and the ratio of the power spectrum of velocity to the power spectrum of gravity.Here,with aid of numerical simulations we model the two quantities as functions of the wavevector and of cosmological parameters.We then combine these results with observational estimates of v LG and g LG ,and obtain the ‘best’value of βand its errors.2Modelling nonlinear eﬀectsWe follow the evolution of the dark matter distribution using the pressureless hydrodynamic code CPPA (Cosmological Pressureless Parabolic Advection,see Kudlicki,Plewa &R´o ˙z yczka 1996,Kudlicki et al.2000for details).It employs an Eulerian scheme with third order accuracy inspace and second order in time,which assures low numerical diﬀusion and an accurate treatment of high density contrasts.Standard applications of hydrodynamic codes involve a collisional ﬂuid;however,we implemented a simpleﬂux interchange procedure to mimic collisionlessﬂuid behaviour.We studied the CF in an earlier paper.2Here we use a diﬀerentﬁtting function,which is more accurate for low values of k:C(k)= 1+(a0k−a2k1.5+a1k2)2.5 −0.2.(1) Parameters a l were obtained for35diﬀerent values ofσ8in the range[0.1,1],and we found the following,power-law,scaling relations:a0=4.908σ0.7508a1=2.663σ0.7348(2)a2=5.889σ0.7148.Theﬁt was calculated for k∈[0,1]h/Mpc,with the imposed constraint C(k=0)=1.We have found that the ratio of the power spectra,R,obtained from simulation can beﬁtted with the following formula:R(k)=[1+(7.071k)4]−α,(3) withα=−0.06574+0.29195σ8for0.3<σ8<1.(4) 3Parameter estimationWe apply our formalism to the PSCz survey.As the value ofσ8we adopt its WMAP’s estimate,σ8=0.84(±0.04;Spergel et al.2003).This speciﬁes the coherence function and the ratio of the power spectrum of velocity to the power spectrum of gravity.Also,this provides a normalization for the power spectrum of density.3.1Parameter dependence of the modelThe likelihood of speciﬁc values ofβand of the linear bias,b,is determined by the following distribution(Juszkiewicz et al.1990,Lahav,Kaiser&Hoﬀman1990):f(g,v)=(1−r2)−3/22(1−r2) ,(5)whereσg andσv are respectively the r.m.s.values of a single Cartesian component of gravity and velocity,(x,y)=(g/σg,v/σv),andψis the misalignment angle between g and v.Finally,r is the cross-correlation coeﬃcient of g m with v m,where g m(v m)denotes an arbitrary Cartesian component of g(v).In this distribution,the observables are g and v,or g,v,and the misalignment angle,ψ.Following Schmoldt et al.3(hereafter S99),we adopt for them the following values:g= 933km·s−1(from the distribution of the PSCz galaxies up to150h−1Mpc),v=627km·s−1 (inferred from the4-year COBE data by Lineweaver et al.1996),andψ=15◦.The theoretical quantities areσg,σv,and r.The variance of a single spatial component of measured gravity,σ2g,is a sum of the cosmological component,σ2g,c,and errors,ǫ2.Since gravity here is inferred from a galaxian,rather than mass,densityﬁeld,we haveσ2g,c=b2s2g,where s2g is the variance of a single component of the true(i.e.,mass-induced)gravity,s2g=1βbFigure1:Likelihood contours for the parametersβand b,corresponding to the conﬁdence levels of68,90and 95%.The maximum of the likelihood function is denoted by a dot.The gravity errors are twofold:due toﬁnite sampling of the galaxy densityﬁeld,and due to the reconstruction of the galaxy densityﬁeld in real space.Therefore,ǫ2=(σ2SN+σ2rec)/3, whereσ2SN andσ2rec are respectively the shot noise(or,sampling)variance and the reconstruction variance.In brief,σ2SN+σ2recσ2g=b2s2g+6π2 ∞0 W2v(k)R(k)P(k)dk.(8) Finally,errors in the estimate of the LG gravity do not aﬀect the cross-correlation between the LG gravity and velocity,but increase the gravity variance.This has the eﬀect of lowering the value of the cross-correlation coeﬃcient.Speciﬁcally,we haver=ρ 1+σ2SN+σ2rec∞0 W2g(k)P(k)dk 1/2 ∞0 W2v(k)R(k)P(k)dk 1/2.(10) Thus,the likelihood depends explicitly on the parameters b andΩm,or on b andβ≡Ω0.6m/b.3.2Joint likelihood forβand bFigure1shows isocontours of the joint likelihood forβand b,corresponding to the conﬁdence levels of68,90and95%.The maximum of the likelihood is denoted by a dot.The corresponding values ofβand b are respectively0.66and0.94.The isocontours of the likelihood are much more elongated along the b-axis than along theβ-axis,making the resulting constraints onΩm00.20.40.60.81 1.2 1.4β00.511.522.53p (β)Figure 2:The marginal distribution for β.The result of marginalizing over all possible values of b (from zero to inﬁnity)is shown as a dashed line.The result of marginalizing over the values of b in the range [0.7,1.1]is shownas a solid line.much weaker than on β.In practice,therefore,from our analysis we cannot say much about bias,or Ωm ,alone.On the other hand,we can put fairly tight constraints on β.To do this,we use the fact that the square root of the variance of the PSCz galaxy countsat 8h −1Mpc is σP SCz 8≃0.75(Sutherland et al.1999).Combined with WMAP’s estimate of σ8,this yields for the bias of the PSCz galaxies the value about 0.9.Therefore,we adopt here a conservative prior for the bias,namely that it is constrained to lie in the range [0.7,1.1].These limits are marked in Figure 1as dashed vertical lines.We marginalize the likelihood over the values of b in this range.The resulting distribution for βis shown in Figure 2as a solid line.We obtain β=0.66+0.21−0.07(68%conﬁdence limits).4Summary and conclusionsThe analysis of the LG acceleration performed by S92and S99was in a sense more sophisticated than ours.Both teams analysed a diﬀerential growth of the gravity dipole in subsequent shells around the LG.Instead,here we used just one measurement of the total (integrated)gravity within a radius of 150h −1Mpc.Nevertheless,the errors on βwe have obtained are signiﬁcantly smaller than those of S92and S99.In particular,S99obtained β=0.70+0.35−0.20at 1σconﬁdence level.It is striking that while our best value of βis close to theirs,our errors are signiﬁcantly smaller.The reason is our careful modelling of nonlinear eﬀects.In a previous paper we showed that the coherence function used by S99greatly overestimates actual decoherence between non-linear gravity and velocity.Tighter correlation between the LG gravity and velocity should result in a smaller random error of β;in the present work we have shown this to be indeed the case.AcknowledgmentsThis research has been supported in part by the Polish State Committee for Scientiﬁc Research grants No.2.P03D.014.19and 2.P03D.017.19.References1.M.A.Strauss,A.Yahil,M.Davis,J.P.Huchra and K.Fisher,ApJ 397,395(1992)(S92)2.M.J.Chodorowski and P.Cieciel¸a g,MNRAS 331,133(2002)3.I.Schmoldt,et al.,MNRAS 304,893(1999)(S99)。