Proceedings of the 2004 Winter Simulation Conference

Proceedings of the 2004 Winter Simulation Conference

R .G. Ingalls, M. D. Rossetti, J. S. Smith, and B. A. Peters, eds.

ABSTRACT

We present a model to explain the effects of the long time between blood stem cell divisions and rapid cascades of progenitor cell divisions on the mitochondrial DNA drift. We allow four stochastic events in the system namely, mtDNA replication and degradation, cell division and death. To implement the conceptual model, we design two simulation models; one for a limited number of stem cells (20,000) over very long time scale (100 years) and another for the cell divisions of a progenitor cell resulting in a large number of blood cells (~10 million) over a shorter time span (25 days). Iterative enhancement with incremental builds constitutes the modeling methodology. We adopt the activity scanning conceptual framework for the model im-plementation. Initial transient and memory issues are re-solved. By output data analysis, we conclude that the varia-tion in mutation level occurs significantly due to time and less so due to cell divisions.

1 INTRODUCTION

For the reader unfamiliar with cell biology, we include some basic definitions.

Mitochondria: Cellular organelles responsible for en-ergy production. Hence, they are called the power house of the cell. Mitochondria are unusual because they contain their own DNA molecules (mtDNA), separate from the DNA in the cell nucleus.

Stem cell: An unspecialized cell with self renewing capabilities that gives rise to a specific specialized cell.

Hematopoietic stem cell: A small population of un-differentiated cells in the bone marrow which give rise to the mature differentiated blood cells.

Blood progenitor cell: The ancestor cell for all types of blood cells originating directly from a stem cell division in the bone marrow.

Symmetric cell division: Always results in two iden-tical daughter cells (Figure 1). For example, progenitor cells in our model are known to follow such divisions (Marley et al., 2003).

Asymmetric cell division: results in two daughter cells that are not be identical (Figure 1).

Mixed cell division: results in two daughter cells that may or may not be identical (Figure 1).

Synchronous cell division: all cells in a colony divide at the same time (Figure 2).

Asynchronous cell division: cells divide independ-ently, at different times (Figure 2).

time

-stem

cell

- progenitor cell asymmetric

Figure 1: Symmetric, Asymmetric and Mixed Cell Di-visions

A blood stem cell is an undifferentiated cell in the bone marrow that divides about once a year to yield two daughter cells. The divisions are asymmetric and result in the formation of two stem cells, two progenitor cells or one of each type.

A SIMULATION METHODOLOGY IN MODELING CELL DIVISIONS WITH STOCHASTIC EFFECTS

Harsha K. Rajasimha

David C. Samuels Virginia Bioinformatics Institute Bioinformatics Facility I (0477)

Virginia Tech Blacksburg, VA 24061, U.S.A.

Richard E. Nance

660 McBryde Hall (0106)

Department of Computer Science

Virginia Tech

Blacksburg, VA 24061, U.S.A. 2032

-cell

synchronous

asynchronous time

Figure 2: Synchronous and Asynchronous Cell Divisions

Progenitor cells undergo rapid cascades of cell divisions yielding millions of blood cells every day. In the following sections, we describe the system, the model, the model ob-jectives and the requirements of the simulation study. The modeling methodology is described giving attention to the conceptual framework and the verification and validation (V&V) techniques employed. An initial transient problem is resolved and we comment on the indications of scalabil-ity and memory limitations from the preliminary results. We close with an observation regarding model insensitivity and offer several extensions that would incorporate more system features in future experimentation. 2 THE SYSTEM

The system to be modeled belongs in the domain of cell bi-ology. The system consists of a number of human blood stem cells in the bone marrow. Each cell has a number of mitochondrial DNA (mtDNA) molecules (a few thousand). Each mtDNA molecule can be of either a wild-type mtDNA (W: The normal type we would expect in a cell), or a mu-tant-type mtDNA (M: abnormal due to insertion, deletion, or substitution of nucleotides). Each mtDNA molecule under-goes a process of replication wherein it creates a copy (repli-cate) of itself. Let N = W+M be the total number of mtDNA in a cell. Typically, a normal cell would contain all W mtDNA. The state where both W and M type mtDNA occur in the same cell is known as heteroplasmy. mtDNA are de-graded with a half life (T 1/2). Under normal conditions, the cell replicates its mtDNA at a rate Ro to compensate for the loss of mtDNA by degradation. With both mtDNA replica-tion and degradation events, and cell division and cell death events occurring independently in this stochastic system, the average mutation level (M/N) in the cell population drifts over time. The effect of this drift needs to be studied over a human life span. We observe the variation in the M/N level in a population of cells starting at different initial mutation levels over time. The effect of cell divisions are studied over a cascade of cell divisions leading to millions of cells. The

literature supports the assumption that blood stem cells un-dergo cell division about once a year. These divisions are asymmetric and asynchronous, resulting in both blood pro-genitor cells and stem cells. A blood progenitor cell, once formed, undergoes a series of rapid cell divisions (approxi-mately once a day) to yield mature blood cells after about 18-20 levels of cell divisions (Figure 3). In each cell divi-sion, random division determines the number of M or W type mtDNA that go into each of the daughter cells.

Figure 3: Cell Division Model for Blood Stem Cells

3 STUDY OBJECTIVES

Important in the understanding of the mtDNA mutation load on the blood cells are the relative contributions of two factors; the length of the interval separating divisions of the stem cell and the rate of the cascade of cell divisions among the progenitor cells. The objectives of this simula-tion study are:

1. How does the mutation level of mtDNA

(M/(W+M)) drift over a time span of 100 years? 2. How does the mutation level of mtDNA drift over

rapid cascades of cell division resulting in at least 220 (a million) blood cells?

3. How does the drift in mutation level in the stem

cells compare with that occurring in the progeni-tor cell division cascade? 4 THE MODEL

The model we develop will represent the above system with the following assumptions:

1. During cell division, roughly 50% of total

mtDNA is distributed to each daughter cell.

2. A cell dies and is removed from the population

only if its mutation level exceeds the set threshold level (~90%).

3. mtDNA replication, mtDNA degradation, cell di-vision and cell death are the only events that af-fect the mtDNA mutation load in the cell.

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4. The progenitor cells in Figure 3 divide to produce

several specialized cell types. However, the model treats all these cells as the same type. 4.1 MODEL EQUATIONS

Table 1: Table of Model Parameters and Equations Description Para- meter

Set to value

The target total mtDNA population in a cell

Nt ~5000 The time between cell divisions D 1 year (stem cells) 1 day (progenitor

cells)

The number of wild-type mtDNA in a cell W W =

pp*Nt The number of wild-type mtDNA in a cell M M = (1-pp)*Nt

Half life of mtDNA T 1/2 10 days (from litera-ture)

The wild-type mtDNA level in a cell pp set to a value be-tween 10% to 90% The simulation time step ?t 1 hour (for both

stem and progenitor cell models) The probability of a cell division occurring in time ?t

ln(2) * ?t / D

The mtDNA destruction coefficient τ τ = T 1/2 / ln(2)

The mtDNA replication rate

Ro Ro =Nt/τ+ln(2)*Nt/D The mean value parame-ter for the poisson sub-routine

xm xm = Ro * ?t

The probability of a cell death event occurring in a time interval (t, t+?t) = (number of living cells at time t)*?t/(D*Nt) 4.2 MODEL PARAMETERS TO BE SET MAXCELLS:

Maximum number of cells that could ex-ist at anytime

MAXDIV: Maximum number of cell division cas-cades in the synchronous model

MAXHOUR: Maximum number of hours that the

simulation should run

THRESHOLD: A cell dies and is removed from the

population if its mutation level exceeds the set threshold level (~90%) 5 MODELING METHODOLOGY

Iterative enhancement with incremental builds constitutes the methodology of model development. Different perspec-tives are offered in the literature (Balci 2001, Sargent 2001). While we do not use a specific methodology, the simulation model is developed with careful consideration to the meth-odology and CF. To achieve the objectives and meet the re-quirements, we design two simulation models; one for a lim-ited number of stem cells (20,000) over very long time scale (100 years) and another for the cascaded cell divisions of a progenitor cell resulting in a large number of blood cells (10 million) over a shorter time span (25 days). Separating the programmed stem cell model from the progenitor cell model is the strategy adopted to overcome memory and time limita-tions of the PC. The RNG and probability distribution sub-routines are verified, first, the stem cell model with synchro-nous cell divisions is implemented and results verified. The next step is to extend stem cell model to asynchronous divi-sions. We then build the synchronous and asynchronous cell division versions of the blood progenitor cell model. This is followed by design and execution of simulation experiments and output data analysis.

The algorithm used to generate a uniform random number taken from the book “Numerical Recipes in C” is originally proposed by Park and Miller (1988). The subroutines for generating a Poisson distribution and binomial distribution are also taken from the same source. All these subroutines are implemented as ‘C’ functions and included as a header file. A poisson distribution is used to set the number of W and M mtDNA that are degraded during each time step. A binomial distribution is used to set the number of W and M type mtDNA to be copied during a time step based on the current numbers in the cell. 6 CONCEPTUAL FRAMEWORK

For implementing the simulation model, we adopt the Activ-ity Scanning (AS) Conceptual Framework (CF) with fixed increment time flow mechanism (TFM) (Balci 1988). Our objectives require that we perform statistical analysis on the state of the system at specific intervals of time in order to make valid predictions. For example, consider the following questions: Given an initial number of stem cells to start with, what are the number of cells living after 50 years? What are the number of blood cells produced per day? Starting from a given initial mutation level in given number of cells, how does the mutation level decay over a 5, 10, 20 year span? To answer such questions, AS with fixed time increments al-lows a simple and logical design of the program flow. Sec-ond, the simulation termination condition is time based and statistical routines are to be called at regular intervals of time in order to save the system state at those times. Third, since there are only four different events that can occur at each time point namely, cell division, cell death, mtDNA copy, and mtDNA degradation, it is easy to scan them. Lastly, we deal with a large number of cells (millions), and an ES ap-proach would mean scheduling (or queuing) millions of events whenever an event occurs (since several events are expected to at each time step). This would be memory inef-

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ficient (Derrick, Balci, and Nance 1989). AS overcomes this problem by assigning a probability of occurrence of an event in each time step. Also, we do not save all the attributes of the system at every time step, but only those averaged over intervals of time.

7 MODEL V&V TECHNIQUES

We build the model with particular attention to model Verification and Validation. We adopt the following V&V techniques:

Analysis by plot: Individual subroutines such as RNG, Poisson, binomial, cell division, and statistics sub-routines are verified using short programs and plotting the output data. Subroutines derived from published sources such as Park and Miller (1998) are subject to one time veri-fication to eliminate any implementation errors. For the blood cell model, one of the V&V procedure is to analyze the counts of the number of cells living and dying due to mutation threshold (Figure 4). We note that there is no sin-gle cell death in the first twelve days and thereafter the death count raises exponentially as the living cell count does. In addition, the death events are small in number in-dicating that the cascaded cell divisions do not cause many cells to exceed the mutation threshold.

Figure 4: Blood Cell Counts Dying Due to Mutation Threshold Compared with Living Cell Counts over Time Desk checking: Subroutines that are derived from re-liable sources are subjected to a one time desk checking before utilizing them in the simulation. However, the simu-lation programs are subjected to routine desk checking whenever additions or modifications are made.

Figure 5 is used for desk checking purposes to ensure that the data structures for the critical parameters are stor-ing the right data. The validation criteria set for this model are based on the standard expectations or the biological scenario derived from literature. The total number of mtDNA in a cell (N = W+M) should be fairly constant (very little initial variation and then it stabilizes). If the model is implemented right, the average number of W and M type mtDNA in all living stem cells should behave as shown in Figure 5.

Figure 5: A Plot of Mean Values of W, M and N for a Stem Cell Simulation Run Starting at 95% Mutation Level with the Threshold for Cell Death Set to 100%. Nt is Set to 5000 and W and M are Set to 5% and 95% of Nt Respectively

Simulation runs performed for exact parameter set with different random number seeds (idum) serve as a veri-fication procedure.

Simulation/theoretical comparison: The simulation output data is compared to the experimental data sets on blood cells provided by Rahman et al., (2001) that spans over a 19-year time frame and Howell et al., (2000) data spans just about 7 years. We observed a good overlap be-tween the W and M levels in the cells with the experimental values. This served as the major verification procedure for this research. However, not enough data is available on longer time scales; as such experiments are both costly and become infeasible to conduct in one’s lifespan. Despite all this, some experiments are ongoing in this direction using the blood samples at birth and present. If blood samples are saved at birth, comparing the values from those with current values in the same person can give us the data across the kind of time-scales we are looking at. With that, we should be able to provide a standard behavior curve (for each set of initial conditions) using this simulation model for experi-mentalists to compare with.

Subject matter expert: Several of the plots and desk checking procedures are designed based on the experience and intuition of a domain expert.

8 RESULTS

Simulation output data analysis is performed using Origin package from OriginLab.

Stem cell model: From experiments, it is known that cells can survive and even function normally with mutation

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level of up to 85%. Since it is not exactly known what the threshold level for cell death is, we need to test if the exact threshold value affects the model behavior significantly. A simulation experiment is conducted with THRESHOLD set at 100% so that a cell would die only if the mutation level reached 100% in that cell. The result for the two simulation runs starting at 75% and 95% initial M level is shown in Figure 6. Another simulation experiment is setup with THRESHOLD set to 90%. Interestingly, the behavior with 90% THRESHOLD for cell death does not deviate much from the behavior observed at 100% threshold even over a time scale of 100 years (plot not shown).

Figure 6: A Plot of Mean M Level (M/N) versus Time

Progenitor cell model: The results from the cascaded cell division model of progenitor cells shows that the aver-age M level of all cells resulting from a cascade of cell di-visions did not differ from that of the progenitor cell (Fig-ure 7). As shown in Figure 7, the variation in the mean M level in about 10 million cells resulting from a single pro-genitor cell is in the order of 10-3 which is negligible.

Figure 7: Mean M Level of Blood Cells as a Function of Their Cell Count 9 THE PROBLEM OF INITIAL TRANSIENT Figure 6 also shows the problem of initial transient for two simulation runs starting at 75% and 95% mutation levels. The run at 75% mutation level takes longer for individual cells to exceed the set 100% threshold for cell death. While the M level starts to decay after about 10 years in the 75% case, the same starts in less than 5 years for the 95% case. One reason is that in a single simulation run, all cells are ini-tialized to the same initial state, which is not very close to the natural situation. Hence, we allow the first few years of simulation to allow randomization of the initial state of dif-ferent cells. Figure 8 shows the stem cell population distribution for a simulation run starting at year 0 and 70% mutation level, after 6 years and after 60 years. As we can see, the distribution after 6 years is spread around the mean 70% level from 40% to 90%. However, after a span of 60 years, the population has spread the entire spectrum from 0 to 90% with more than 1500 cells fixed at all W type cells. The current procedure to determine the end of transient period is more ad hoc and expert heuristic based. A much cleaner way of handling this issue of initial transient is still of interest.

Figure 8: Stem Cell Population Distribution Based on Their M Level

To check the effects of starting simulation runs on cells with different starting conditions, the initial mutation level is set to a range of values from 20% to 75%. Figure 6 shows the decay in M levels in cell populations starting at different initial M levels (75% and 95%). From the plot, both lines are nearly parallel, i.e., initial condition does not noticeably impact the slopes. The explanation for this is that the amount of time needed for the cells to exceed the M THRESHOLD for cell death is proportional to the initial M level at which each cell starts. In our model, all cells start with the same M level in a particular simulation run. But, the rate at which the M level decays itself does not depend on the initial M level of the cell.

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10 MEMORY AND SCALABILITY ISSUES

One point to mention here is the memory limitation posed by data structure design. With the initial cell class defini-tion, each instance of the cell object has 4 float variables (W and M values for private and public access) and 1boolean variable (cell dead or alive). The maximum num-ber of cells that can be statically declared at the beginning of the program is about half a million because of the lim-ited memory available on the stack. Since the requirement is to simulate at least a million cell objects (~ 220), we con-sider the following improvements:

1. Shift to dynamic memory allocation in which case,

we would have to create a cell object every time a

cell division event occurred and destroy one, every

time a cell death event occurred. Traversing a

linked list of more than a million cells at every time

step is highly inefficient. This shift would be quite

costly in terms of resources and effort.

A way around this problem is to declare the array

of objects in the heap instead of on the stack.

i.e., instead of declaring:

// This allocates memory on the stack

Cell cell[MAXCELLS];

declare this way:

// This allocates memory on the heap

Cell *cell;

cell = new Cell[MAXCELLS];

In this case, the number of cell objects (MAXCELLS) is limited only by the amount of

available secondary memory on the computer.

This imposes an additional overhead on the pro-

gram, as it now has to handle more of segmenta-

tion issues than before to get cell objects between

main and virtual memory to perform operations.

2. Reduce the memory requirements of each cell ob-

ject so as to hold many more cells. We achieved

this by eliminating two private float variables to

save W and M values for each cell. The model is

still intact since we have the two public variables

that undergo changes as events occur at every

time step.

11 CONCLUSIONS AND FUTURE WORK Results: We present a simplified model of mtDNA drift in blood stem cells. The main result of the model is that long times between divisions allows the mtDNA mutation levels to increase beyond the threshold for cell death. Hence, such population of cells will show a decrease in mutation level as more and more cells die. On the other hand, the drift in mu-tation level introduced by rapidly dividing progenitor cells yielding millions of blood cells is negligible. All cells result-ing from a single progenitor cell would have nearly identical mutation level i.e., the variation in the M level occurs mainly due to time and not due to rapid cell divisions.

Simulation run times: The current stem and progeni-tor cell simulation models take approximately about 4.5 hours each to complete on a Intel P4 2.4 GHz processor with 256 MB RAM. The stem cell model is set to run for 100 years and the progenitor cell is set to expand to about 12 million cells. We note that the model design is highly amenable to parallelization to achieve faster simulation for even larger numbers of cells for even longer durations.

Model complexities: The cell object can be made more complex to include other cellular compartments and/or the model can be applied to a growing cell culture or an embryo. The blood stem cell model can be extended to include the various types of specialized blood cells that could be produced such as erythrocytes, platelets, etc. The model is easily adaptable to other stem cell types.

Model extensions and applications: Incorporating the actual mtDNA sequence data in the model and apply-ing a particular mutation could be one of the extensions of the model. One question that such a model would help us examine concerns the idea that mtDNA with large deletion mutations would take less time to replicate than wild-type mtDNA since the number of base pairs replicated would be much less. Preimplantation Genetic Diagnostics (PGD) for advising gravid couples regarding genetically inherited mitochondrial diseases (Dean et el., 2003). Since cancer involves uncontrolled proliferation of cells (Byrne and Preziosi 2003), an extension of our current model can be used to examine specific questions about the characteristics of cancer cells and the role of mitochondrial mutations in cancer (Breward, Byrne, and Lewis 2003). Apoptosis or programmed cell death, which has sparked (or renewed) significant interest in the recent past can be studied by ex-tending the current model. Cancer can be thought of as a condition where cell death fails to occur at a reasonable rate with cell proliferation occurring at normal pace. Un-derstanding the two in tandem will give valuable insights into the basic science of apoptosis in cancer cells.

ACKNOWLEDGMENTS

D.C. Samuels and H.K. Rajasimha thank the commonwealth of Virginia for financial support and their mitochondria re-search team at VBI for their valuable inputs. Rajasimha espe-cially thanks Dr. Bradshaw for providing useful suggestions.

REFERENCES

Balci, O. (1988) The Implementation of Four Conceptual Frameworks for Simulation Modeling in High-Level Languages, Proceedings of the Winter Simulation

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Conference, M. Abrams, P. Haigh and J. Comfort (eds), 287-295. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers.

Balci, O. (2001), “A Methodology for Certification of Modeling and Simulation Applications,” ACM Trans-

actions on Modeling and Computer Simulation, 11,

(4): 352-377.

Breward, Christopher J. W., Helen M. Byrne, and Vlaire Lewis (2003) A Multiphase Model Describing Vascu-

lar Tumor Growth, Bulletin of Mathematical Biology 65, 609–640

Byrne, H., and L Preziosi (2003). Modeling solid tumor growth using the theory of mixtures JOURNAL OF THE IMA 20 (4): 341-366

Dean, N.L., Brendan J. Battersby, Asangla Ao, Roger G.

Gosden, Seang LinTan, and Eric A. Shoubridge (2003) Prospect of preimplantation genetic diagnosis for heritable mitochondrial DNA diseases. Molecular Human Reproduction 9(10): 631-638

Derrick, E.J., O. Balci and R.E. Nance (1989) A Compari-son of Selected Conceptual Frameworks for Simula-

tion Modeling, Proceedings of the Winter Simulation Conference, E.A. MacNair, K.J. Musselman and P.

Heidelberger (eds), 711-718. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers. Howell, N., Soumitra S. Ghosh, Eoin Fahy, and Laurence

A. Bindoff (2000) Journal of the Neurological Sci-

ences 172:1-6

Park, S.K., and K.W. Miller, (1988), Communications of the ACM, 31, :1192–1201.

Press W.H., Brian P. Flannery, Saul A. Teukolsky, Wil-liam T. Vetterling. Numerical Recipes in C: The Art of Scientific Computing.

Rahman S., J. Poulton, D. Marchington, and A. Suomalai-nen, (2001) Decrease of 3243 A->G mtDNA Mutation from Blood in MELAS Syndrome: A Longitudinal Study. American Journal of Human Genetics 68:238-

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Peters, J.S. Smith, D.J. Medeiros, and M.W. Rohrer (eds), 106-114. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers.

Marley, S.B, J.L. Lewis and M.Y. Gordon (2003) Progeni-tor cells divide symmetrically to generate new colony-

forming cells and clonal heterogeneity, British Journal of Haematology 121: 643-648.

AUTHOR BIOGRAPHIES

HARSHA K. RAJASIMHA is a research associate at the Virginia Bioinformatics Institute and a masters candidate in the computer science department at Virginia Polytechnic Institute and State University. He received a B.E. (2000) in computer science & engineering from Bangalore Uni-versity, India and briefly worked as a lecturer in computer science in the same college. He gained industry experience interning as a software design engineer in test at Microsoft Corporation, Redmond, WA (Summer 2002). He worked as a graduate research assistant at the Virginia Bioinfor-matics Institute since December 2002 in the mitochondria research group. He intends to pursue doctoral research in bioinformatics. His research interests include biological data integration and modeling & simulation of life systems. He served as the secretary of the computer science gradu-ate student council during the year 2003. He can be reached by email at and his web address is .

DAVID C. SAMUELS, Ph.D., is a research assistant pro-fessor at the Virginia Bioinformatics Institute. He received a B.Sc. degree in physics from Washington University in St. Louis in 1983 and A Ph.D. in physics from the Univer-sity of Oregon in 1990. He was a faculty member in the Department of Mathematics at the University of Newcas-tle-upon-Tyne from 1996-2002. His principal research in-terests are in computational cell biology. Specifically, his group at the Virginia Bioinformatics Institute is currently focused on models of mitochondria, the cellular organelles responsible for the generation of energy. He can be reached by email at and his web address is

RICHARD E. NANCE, Ph.D.,is a professor emeritus of computer science and director of the Systems Research Cen-ter at Virginia Polytechnic Institute and State University. He received B.S. and M.S. degrees from N.C. State University in 1962 and 1996, and Ph.D. degree from Purdue University in 1968. He has served on the faculties of Southern Method-ist University and Virginia Tech, where he was Department Head of Computer Science, 1973-1979. Professor Nance has held research appointments at the Naval Surface Weapons Center and at the Imperial College of Science and Technol-ogy (UK). Within ACM, he has chaired two special interest groups: Information Retrieval (SIDIR), 1970-71 and Simula-tion Activities Board, the Outstanding Service Awards Sub-committee, the ad hoc Conference Procedures Committee and the ad hoc Film Committee that produced “Computers in Life.” He served on the Editorial Panels of Communica-tions of the ACM for research contributions in simulation and statistical computing, and Journal of Operations Re-search and Computer Science for contributions in simula-tion. The author of papers on discrete event simulation, per-formance modeling and evaluation, and computational structures and techniques of Operations Research 1978-82, and as Department Editor for Simulation, Automation and Information Systems of IIE Transaction, 1976-81. He can be reached by email at and his web ad-dress is .

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高二《甜美纯净的女声独唱》教案

高二《甜美纯净的女声独唱》教案 一、基本说明 教学内容 1）教学内容所属模块：歌唱 2）年级：高二 3）所用教材出版单位：湖南文艺出版社 4）所属的章节：第三单元第一节 5）学时数： 45 分钟 二、教学设计 1、教学目标： ①、在欣赏互动中感受女声的音域及演唱风格，体验女声的音色特点。 ②、在欣赏互动中，掌握美声、民族、通俗三种唱法的特点，体验其魅力。 ③、让学生能够尝试用不同演唱风格表现同一首歌。 ④、通过学唱歌曲培养学生热爱祖国、热爱生活的激情。 2、教学重点： ①、掌握女高音、女中音的音域和演唱特点。 ②、掌握美声、民族、通俗三种方法演唱风格。 3、教学难点： ①、学生归纳不同唱法的特点与风格。

②、学生尝试用不同演唱风格表现同一首歌。 3、设计思路 《普通高中音乐课程标准》指出：“音乐课的教学过程就是音乐的艺术实践过程。”《甜美纯净的女声独唱》作为《魅力四射的独唱舞台》单元的第一课，是让学生在丰富多彩的歌唱艺术形式中感受出女声独唱以其优美纯净的声音特点而散发出独特的魅力。为此，本课从身边熟悉的人物和情景入手，激发学生学习兴趣，把教学重心放在艺术实践中，让学生在欣赏、学习不同的歌唱风格中，培养自己的综合欣赏能力及歌唱水平。在教学过程中让学生体会不同风格的甜美纯净女声的内涵，感知优美纯净的声音特点而散发出的独特魅力，学会多听、多唱，掌握一定的歌唱技巧，提高自己的演唱水平。为实现以上目标，本人将新课标“过程与方法”中的“体验、比较、探究、合作”四个具体目标贯穿全课，注重学生的个人感受和独特见解，鼓励学生的自我意识与创新精神，强调探究、强调实践，将教学过程变为整合、转化间接经验为学生直接经验的过程，让学生亲身去感悟、去演唱，并力求改变现在高中学生普遍只关注流行歌曲的现状，让学生自己确定最适合自己演唱的方法，自我发现、自我欣赏，充分展示自己的的声音魅力。 三、教学过程 教学环节及时间教师活动学生活动设计意图

The way常见用法

The way 的用法 Ⅰ常见用法： 1)the way+ that 2)the way + in which（最为正式的用法） 3)the way + 省略（最为自然的用法） 举例：I like the way in which he talks. I like the way that he talks. I like the way he talks. Ⅱ习惯用法： 在当代美国英语中，the way用作为副词的对格，“the way+ 从句”实际上相当于一个状语从句来修饰整个句子。 1)The way =as I am talking to you just the way I’d talk to my own child. He did not do it the way his friends did. Most fruits are naturally sweet and we can eat them just the way they are—all we have to do is to clean and peel them. 2）The way= according to the way/ judging from the way The way you answer the question, you are an excellent student. The way most people look at you, you’d think trash man is a monster. 3）The way =how/ how much No one can imagine the way he missed her. 4）The way =because

适合女生KTV唱的100首好听的歌

适合女生KTV唱的100首好听的歌别吝色你的嗓音很好学 1、偏爱----张芸京 2、阴天----莫文蔚 3、眼泪----范晓萱 4、我要我们在一起---=范晓萱 5、无底洞----蔡健雅 6、呼吸----蔡健雅 7、原点----蔡健雅&孙燕姿 8、我怀念的----孙燕姿 9、不是真的爱我----孙燕姿 10、我也很想他----孙燕姿 11、一直很安静----阿桑 12、让我爱----阿桑 13、错过----梁咏琪 14、爱得起----梁咏琪 15、蓝天----张惠妹 16、记得----张惠妹 17、简爱----张惠妹 18、趁早----张惠妹 19、一念之间----戴佩妮 20、两难----戴佩妮 21、怎样----戴佩妮 22、一颗心的距离----范玮琪 23、我们的纪念日----范玮琪 24、启程----范玮琪 25、最初的梦想----范玮琪 26、是非题----范玮琪 27、你是答案----范玮琪 28、没那么爱他----范玮琪 29、可不可以不勇敢----范玮琪 30、一个像夏天一个像秋天----范玮琪 31、听，是谁在唱歌----刘若英 32、城里的月光----许美静 33、女人何苦为难女人----辛晓琪 34、他不爱我----莫文蔚 35、你是爱我的----张惠妹 36、同类----孙燕姿 37、漩涡----孙燕姿 38、爱上你等于爱上寂寞----那英 39、梦醒了----那英 40、出卖----那英 41、梦一场----那英 42、愿赌服输----那英

43、蔷薇----萧亚轩 44、你是我心中一句惊叹----萧亚轩 45、突然想起你----萧亚轩 46、类似爱情----萧亚轩 47、Honey----萧亚轩 48、他和他的故事----萧亚轩 49、一个人的精彩----萧亚轩 50、最熟悉的陌生人----萧亚轩 51、想你零点零一分----张靓颖 52、如果爱下去----张靓颖 53、我想我是你的女人----尚雯婕 54、爱恨恢恢----周迅 55、不在乎他----张惠妹 56、雪地----张惠妹 57、喜欢两个人----彭佳慧 58、相见恨晚----彭佳慧 59、囚鸟----彭羚 60、听说爱情回来过----彭佳慧 61、我也不想这样----王菲 62、打错了----王菲 63、催眠----王菲 64、执迷不悔----王菲 65、阳宝----王菲 66、我爱你----王菲 67、闷----王菲 68、蝴蝶----王菲 69、其实很爱你----张韶涵 70、爱情旅程----张韶涵 71、舍得----郑秀文 72、值得----郑秀文 73、如果云知道----许茹芸 74、爱我的人和我爱的人----裘海正 75、谢谢你让我这么爱你----柯以敏 76、陪我看日出----蔡淳佳 77、那年夏天----许飞 78、我真的受伤了----王菀之 79、值得一辈子去爱----纪如璟 80、太委屈----陶晶莹 81、那年的情书----江美琪 82、梦醒时分----陈淑桦 83、我很快乐----刘惜君 84、留爱给最相爱的人----倪睿思 85、下一个天亮----郭静 86、心墙----郭静

The way的用法及其含义(二)

The way的用法及其含义（二） 二、the way在句中的语法作用 the way在句中可以作主语、宾语或表语： 1.作主语 The way you are doing it is completely crazy.你这个干法简直发疯。 The way she puts on that accent really irritates me. 她故意操那种口音的样子实在令我恼火。The way she behaved towards him was utterly ruthless. 她对待他真是无情至极。 Words are important, but the way a person stands, folds his or her arms or moves his or her hands can also give us information about his or her feelings. 言语固然重要,但人的站姿,抱臂的方式和手势也回告诉我们他(她)的情感。 2.作宾语 I hate the way she stared at me.我讨厌她盯我看的样子。 We like the way that her hair hangs down.我们喜欢她的头发笔直地垂下来。 You could tell she was foreign by the way she was dressed. 从她的穿著就可以看出她是外国人。 She could not hide her amusement at the way he was dancing. 她见他跳舞的姿势，忍俊不禁。 3.作表语 This is the way the accident happened.这就是事故如何发生的。 Believe it or not, that's the way it is. 信不信由你, 反正事情就是这样。 That's the way I look at it, too. 我也是这么想。 That was the way minority nationalities were treated in old China. 那就是少数民族在旧中

(完整版)the的用法

定冠词the的用法： 定冠词the与指示代词this ,that同源,有“那(这)个”的意思,但较弱,可以和一个名词连用,来表示某个或某些特定的人或东西. (1)特指双方都明白的人或物 Take the medicine.把药吃了. (2)上文提到过的人或事 He bought a house.他买了幢房子. I've been to the house.我去过那幢房子. (3)指世界上独一无二的事物 the sun ,the sky ,the moon, the earth (4)单数名词连用表示一类事物 the dollar 美元 the fox 狐狸 或与形容词或分词连用,表示一类人 the rich 富人 the living 生者 (5)用在序数词和形容词最高级,及形容词等前面 Where do you live?你住在哪? I live on the second floor.我住在二楼. That's the very thing I've been looking for.那正是我要找的东西. (6)与复数名词连用,指整个群体 They are the teachers of this school.(指全体教师) They are teachers of this school.(指部分教师) (7)表示所有,相当于物主代词,用在表示身体部位的名词前 She caught me by the arm.她抓住了我的手臂. (8)用在某些有普通名词构成的国家名称,机关团体,阶级等专有名词前 the People's Republic of China 中华人民共和国 the United States 美国 (9)用在表示乐器的名词前 She plays the piano.她会弹钢琴. (10)用在姓氏的复数名词之前,表示一家人 the Greens 格林一家人(或格林夫妇) (11)用在惯用语中 in the day, in the morning... the day before yesterday, the next morning... in the sky... in the dark... in the end... on the whole, by the way...

2019-2020年高一音乐 甜美纯净的女声独唱教案

2019-2020年高一音乐甜美纯净的女声独唱教案 一、教学目标 1、认知目标：初步了解民族唱法、美声唱法、通俗唱法三种唱法的风格。 2、能力目标：通过欣赏部分女声独唱作品，学生能归纳总结出她们的演唱 风格和特点，并同时用三种不同风格演唱同一首歌曲。 3、情感目标：通过欣赏比较，对独唱舞台有更多元化的审美意识。 二、教学重点：学生能用三种不同风格演唱形式演唱同一首歌。 三、教学难点：通过欣赏部分女声独唱作品，学生能归纳总结出她们的演唱 风格和特点。 四、教学过程： （一）导入 1、播放第十三界全国青年歌手大奖赛预告片 （师）问：同学们对预告片中的歌手认识吗 （生）答： （师）问：在预告片中提出了几种唱法？ （生）答：有民族、美声、通俗以及原生态四种唱法，今天以女声独唱歌曲重点欣赏民族、美声、通俗唱法，希望通过欣赏同学们能总结出三种唱法的风格和特点。 （二）、音乐欣赏

1、通俗唱法 ①(师)问：同学们平常最喜欢唱那些女歌手的歌呢？能唱唱吗？ （可让学生演唱几句喜欢的歌，并鼓励） ②欣赏几首通俗音乐 视频一：毛阿敏《绿叶对根的情谊》片段、谭晶《在那东山顶上》片段、韩红《天路》片段、刘若英《后来》片段 视频二：超女《想唱就唱唱得响亮》 ①由学生总结出通俗音乐的特点 ②师总结并板书通俗音乐的特点：通俗唱法是在演唱通俗歌曲的基础上发展起来的，又称“流行唱法”。通俗歌曲是以通俗易懂、易唱易记、娱乐性强、便于流行而见长，它没有统一的规格和演唱技法的要求，比较强调歌唱者本人的自然嗓音和情绪的渲染，重视歌曲感情的表达。演唱上要求吐字清晰，音调流畅，表情真挚，带有口语化。 ③指出通俗音乐尚未形成系统的发声训练体系。其中用沙哑、干枯的音色“狂唱”和用娇柔、做作的姿态“嗲唱”，不属于声乐艺术的正道之物，应予以摒弃。 2、民族唱法 ①俗话说民族的才是世界的那么民族唱法的特点是什么呢？ ②欣赏彭丽媛《万里春色满人间》片段 鉴赏提示：这首歌是剧种女主角田玉梅即将走上刑场时的一段难度较大的咏叹调。

“the way+从句”结构的意义及用法

“tｈｅwａｙ+从句”结构的意义及用法 首先让我们来看下面这个句子: Ｒead the foｌloｗｉnｇpassagｅａnd talkａbout ｉt wi ｔh your classmaｔes．Try tｏｔeｌl whaｔyｏu thiｎk ｏf Tom aｎd ｏｆｔhe ｗay the chiｌｄrenｔrｅated ｈim. 在这个句子中，ｔhe waｙ是先行词,后面是省略了关系副词that或in whｉch的定语从句。 下面我们将叙述“the ｗaｙ+从句”结构的用法。 1.tｈe wａy之后，引导定语从句的关系词是tｈat而不是hoｗ,因此，<<现代英语惯用法词典＞＞中所给出的下面两个句子是错误的：Ｔhｉs is ｔｈeｗayｈowｉtｈａppened. This is the way how he ａlwａｙs treats me. 2．在正式语体中,thaｔ可被in which所代替;在非正式语体中，ｔhat则往往省略。由此我们得到theｗay后接定语从句时的三种模式：1) tｈe ｗaｙ＋ｔhａt-从句２）the way +ｉn whiｃh－从句3) the ｗay +从句 例如：Ｔｈe way(in whiｃh ，thａt) ｔhｅｓｅｃomｒade ｓloｏｋａｔｐrobｌems is wrong．这些同志看问题的方法

不对。 Ｔｈｅｗａy(that ,ｉn ｗhiｃh)yoｕ’ｒe doinｇit is comple ｔeｌy crａzy.你这么个干法,简直发疯。 Wｅａdmiｒｅd him for thｅｗay ｉｎｗhｉch he fａｃeｓdiｆficultieｓ． Waｌlａｃe ａｎd Ｄarwiｎｇreed ｏn the way ｉｎwhi ｃh ｄｉfｆｅrｅnt forms ｏf life had ｂegｕn.华莱士和达尔文对不同类型的生物是如何起源的持相同的观点。 Thｉs is ｔｈe ｗaｙ（tｈａｔ) hｅdｉd it. I lｉkeｄｔhe waｙ(ｔhat) ｓｈeｏｒganized ｔhe ｍeetｉng． 3.theｗay(tｈat)有时可以与hｏw(作“如何”解）通用。例如： That’s tｈe ｗaｙ(tｈaｔ) shｅspoke. = Tｈat’s how shｅspoke.

way 用法

表示“方式”、“方法”，注意以下用法： 1.表示用某种方法或按某种方式，通常用介词in(此介词有时可省略)。如： Do it (in) your own way. 按你自己的方法做吧。 Please do not talk (in) that way. 请不要那样说。 2.表示做某事的方式或方法，其后可接不定式或of doing sth。 如： It’s the best way of studying [to study] English. 这是学习英语的最好方法。 There are different ways to do [of doing] it. 做这事有不同的办法。 3.其后通常可直接跟一个定语从句(不用任何引导词)，也可跟由that 或in which 引导的定语从句，但是其后的从句不能由how 来引导。如： 我不喜欢他说话的态度。 正：I don’t like the way he spoke. 正：I don’t like the way that he spoke. 正：I don’t like the way in which he spoke. 误：I don’t like the way how he spoke. 4.注意以下各句the way 的用法： That’s the way (=how) he spoke. 那就是他说话的方式。 Nobody else loves you the way(=as) I do. 没有人像我这样爱你。 The way (=According as) you are studying now, you won’tmake much progress. 根据你现在学习情况来看，你不会有多大的进步。 2007年陕西省高考英语中有这样一道单项填空题： ——I think he is taking an active part insocial work. ——I agree with you_____. A、in a way B、on the way C、by the way D、in the way 此题答案选A。要想弄清为什么选A，而不选其他几项，则要弄清选项中含way的四个短语的不同意义和用法，下面我们就对此作一归纳和小结。 一、in a way的用法 表示：在一定程度上，从某方面说。如： In a way he was right.在某种程度上他是对的。注：in a way也可说成in one way。 二、on the way的用法 1、表示：即将来(去)，就要来(去)。如： Spring is on the way.春天快到了。 I'd better be on my way soon.我最好还是快点儿走。 Radio forecasts said a sixth-grade wind was on the way.无线电预报说将有六级大风。 2、表示：在路上，在行进中。如： He stopped for breakfast on the way.他中途停下吃早点。 We had some good laughs on the way.我们在路上好好笑了一阵子。 3、表示：(婴儿)尚未出生。如： She has two children with another one on the way.她有两个孩子，现在还怀着一个。 She's got five children，and another one is on the way.她已经有5个孩子了，另一个又快生了。 三、by the way的用法

女生唱的歌曲欢快甜美

女生唱的歌曲欢快甜美 美妙的歌曲能令我们陶醉其中而无法自拨，最激烈的歌曲能令我们的身体不由自主的跟着手舞足蹈起来，下面是小编整理的欢快甜美的歌曲的内容，希望能够帮到您。 欢快甜美的歌曲 1. Talking - 2. 羽毛- 劲歌金曲 3. 为你- 黑龙 4. 我的小时候- 罗艺达 5. 听说爱情回来过 6. 那个男人 7. 夫妻观灯_韩再芬、李迎春- 中国民歌宝典二 8. 往生- 镀飞爱在阳光空气中- 区瑞强- 音乐合辑 9. 说中国- 班- 华语群星 10. 第十八封信- Kent王健 11. 那一夜你喝了酒- 傅薇 12. 最近比较烦- 周华健/李宗盛/品冠- 滚石群星 13. 告白- 张娜拉 14. Talking VIII - 15. my love - 网友精选曲 16. 音乐人民- 音乐合辑 17. 深深深深- 徐誉滕 18. Honkytonk U - Toby Keith 19. 征服- 阿强 20. 我总会感动你- 沙宝亮欢快甜美的歌曲 1. 一千步的距离- 高桐 2. fleeing star - 音乐合辑 3. My Life - 李威杰 4. 小妹听我说- 金久哲 5. 上海滩- 梁玉嵘- 华语群星 6. 爱我多爱一些- 黎姿 7. 恋人未满- 8. 玛奇朵飘浮- 音乐听吧 9. 風- 音乐听吧 10. 七月- 小鸣 11. 滚滚红尘- 罗大佑 12. 张震岳—想要- 华语群星 13. 有梦有朋友- 14. 童年- 拜尔娜 15. 洪湖水，浪打浪- 宋祖英 16. 只爱到一半- 魏晨 17. 风雨人生路- 何静 18. 居家男人- 回音哥如果当时- 许嵩 19. 那个男人的谎言Tae In - 非主流音乐

The way的用法及其含义(一)

The way的用法及其含义（一） 有这样一个句子：In 1770 the room was completed the way she wanted. 1770年，这间琥珀屋按照她的要求完成了。 the way在句中的语法作用是什么？其意义如何？在阅读时，学生经常会碰到一些含有the way 的句子，如：No one knows the way he invented the machine. He did not do the experiment the way his teacher told him.等等。他们对the way 的用法和含义比较模糊。在这几个句子中，the way之后的部分都是定语从句。第一句的意思是，“没人知道他是怎样发明这台机器的。”the way的意思相当于how；第二句的意思是，“他没有按照老师说的那样做实验。”the way 的意思相当于as。在In 1770 the room was completed the way she wanted.这句话中，the way也是as的含义。随着现代英语的发展，the way的用法已越来越普遍了。下面，我们从the way的语法作用和意义等方面做一考查和分析： 一、the way作先行词，后接定语从句 以下3种表达都是正确的。例如：“我喜欢她笑的样子。” 1. the way+ in which +从句 I like the way in which she smiles. 2. the way+ that +从句 I like the way that she smiles. 3. the way + 从句(省略了in which或that) I like the way she smiles. 又如：“火灾如何发生的，有好几种说法。” 1. There were several theories about the way in which the fire started. 2. There were several theories about the way that the fire started.

适合女生唱的各种难度的歌

【适合女生唱的各种难度的歌】以后点歌的时候记得挑战一下自己（哈哈，今天心情高兴，在微博整理下的小东西和大家分享） 1.我不知道--唐笑（特别喜欢的一首歌） 2.那个--文筱芮（特别伤的歌，真的可以听到心里去） 3.一半--丁当（喜欢喜欢，但没能力唱） 4.指望--郁可唯（本来不喜欢她，但她唱歌挺有水平） 5.路人--江美琪（推荐，好听又挺好唱的） 6.过敏--杨丞琳（听听就知道了） 7.大女人--张亚飞（没什么名气的超级女生，这歌挺棒的） 8.一个人的星光--许静岚（绿光森林的主题曲） 9.不要说爱我--许紫涵（高潮真的挺好听，我爱单曲循环，但这歌还没腻） 10.为你我受冷风吹--林忆莲（没那么简单，都是很喜欢的老歌，偶尔听听老歌感觉特别好） 11.一秒也好--卓文萱（她的（爱我好吗）也不错，最近挺喜欢她的歌） 12.你在哪里--张婧（不被太多人知道的歌手） 13.你的背包--莫艳琳（在校内看到一个女孩唱的，觉得挺好听的） 14.原来爱情那么难--泳儿（好听好听，没什么难度，就是在ktv不太好找） 15.在你眼里--同恩（也是到副歌特别吸引人的一首）

16.很久很久以后--梁文音（爱她的歌，她的很多歌都特别好听） 17.知道我们不会有结果--金莎（听着特别有感觉，那些喜欢听悲伤歌的都是因为这种感觉吧） 18.指尖的星光--钟汶（不太好唱的，我就只有听的份了） 19.放不下--龚诗嘉（挺简单的一首，调调挺平的，她的（远远在一起）也不错） 20.灰色的彩虹--范玮琪 21.现在才明白--萧贺硕（不被太多人知道的歌手，有些歌真的很好听，只是需要慢慢挖掘） 22.终点--关心妍（这首歌大多都听过，自己感觉吧） 23.遇到--王蓝茵（旋律让人感觉特舒服的，很爱的一首） 24.一个人--蔡依（她的毅力不是一般人能做到的） 25.婴儿--陈倩倩（这首歌真的凄凉到有点甚人的感觉。“喜欢一个人的心情”--江语晨，因为这歌的词）26.那又怎么样呢--张玉华（我爱听音乐，但一定要是伤感的，虽然不会听到泪流满面，但是那种感觉真的很好） 27.还爱你--景甜（像这样好听，又不被大家熟悉的歌还有很多吧）

way 的用法

way 的用法 【语境展示】 1. Now I’ll show you how to do the experiment in a different way. 下面我来演示如何用一种不同的方法做这个实验。 2. The teacher had a strange way to make his classes lively and interesting. 这位老师有种奇怪的办法让他的课生动有趣。 3. Can you tell me the best way of working out this problem? 你能告诉我算出这道题的最好方法吗？ 4. I don’t know the way (that / in which) he helped her out. 我不知道他用什么方法帮助她摆脱困境的。 5. The way (that / which) he talked about to solve the problem was difficult to understand. 他所谈到的解决这个问题的方法难以理解。 6. I don’t like the way that / which is being widely used for saving water. 我不喜欢这种正在被广泛使用的节水方法。 7. They did not do it the way we do now. 他们以前的做法和我们现在不一样。 【归纳总结】 ●way作“方法，方式”讲时，如表示“以……方式”，前面常加介词in。如例1； ●way作“方法，方式”讲时，其后可接不定式to do sth.，也可接of doing sth. 作定语，表示做某事的方法。如例2，例3；

适合女生KTV唱的100首好听的歌

分享适合女生KTV唱的100首好听的歌别吝色你的嗓音很好学 1、偏爱----张芸京 2、阴天----莫文蔚 3、眼泪----范晓萱 4、我要我们在一起---=范晓萱 5、无底洞----蔡健雅 6、呼吸----蔡健雅 7、原点----蔡健雅&孙燕姿 8、我怀念的----孙燕姿 9、不是真的爱我----孙燕姿 10、我也很想他----孙燕姿 11、一直很安静----阿桑 12、让我爱----阿桑 13、错过----梁咏琪 14、爱得起----梁咏琪 15、蓝天----张惠妹 16、记得----张惠妹 17、简爱----张惠妹 18、趁早----张惠妹 19、一念之间----戴佩妮 20、两难----戴佩妮 21、怎样----戴佩妮 22、一颗心的距离----范玮琪 23、我们的纪念日----范玮琪 24、启程----范玮琪 25、最初的梦想----范玮琪 26、是非题----范玮琪 27、你是答案----范玮琪 28、没那么爱他----范玮琪 29、可不可以不勇敢----范玮琪 30、一个像夏天一个像秋天----范玮琪 31、听，是谁在唱歌----刘若英 32、城里的月光----许美静 33、女人何苦为难女人----辛晓琪 34、他不爱我----莫文蔚 35、你是爱我的----张惠妹 36、同类----孙燕姿 37、漩涡----孙燕姿 38、爱上你等于爱上寂寞----那英 39、梦醒了----那英 40、出卖----那英 41、梦一场----那英 42、愿赌服输----那英

43、蔷薇----萧亚轩 44、你是我心中一句惊叹----萧亚轩 45、突然想起你----萧亚轩 46、类似爱情----萧亚轩 47、Honey----萧亚轩 48、他和他的故事----萧亚轩 49、一个人的精彩----萧亚轩 50、最熟悉的陌生人----萧亚轩 51、想你零点零一分----张靓颖 52、如果爱下去----张靓颖 53、我想我是你的女人----尚雯婕 54、爱恨恢恢----周迅 55、不在乎他----张惠妹 56、雪地----张惠妹 57、喜欢两个人----彭佳慧 58、相见恨晚----彭佳慧 59、囚鸟----彭羚 60、听说爱情回来过----彭佳慧 61、我也不想这样----王菲 62、打错了----王菲 63、催眠----王菲 64、执迷不悔----王菲 65、阳宝----王菲 66、我爱你----王菲 67、闷----王菲 68、蝴蝶----王菲 69、其实很爱你----张韶涵 70、爱情旅程----张韶涵 71、舍得----郑秀文 72、值得----郑秀文 73、如果云知道----许茹芸 74、爱我的人和我爱的人----裘海正 75、谢谢你让我这么爱你----柯以敏 76、陪我看日出----蔡淳佳 77、那年夏天----许飞 78、我真的受伤了----王菀之 79、值得一辈子去爱----纪如璟 80、太委屈----陶晶莹 81、那年的情书----江美琪 82、梦醒时分----陈淑桦 83、我很快乐----刘惜君 84、留爱给最相爱的人----倪睿思 85、下一个天亮----郭静 86、心墙----郭静

100首适合女人唱的歌,不要吝惜自己的嗓子

1、偏爱----张芸京 2、阴天----莫文蔚 3、眼泪----范晓萱 4、我要我们在一起---=范晓萱 5、无底洞----蔡健雅 6、呼吸----蔡健雅 7、原点----蔡健雅&孙燕姿 8、我怀念的----孙燕姿 9、不是真的爱我----孙燕姿 10、我也很想他----孙燕姿 11、一直很安静----阿桑 12、让我爱----阿桑 13、错过----梁咏琪 14、爱得起----梁咏琪 15、蓝天----张惠妹 16、记得----张惠妹 17、简爱----张惠妹 18、趁早----张惠妹 19、一念之间----戴佩妮 20、两难----戴佩妮 21、怎样----戴佩妮 22、一颗心的距离----范玮琪 23、我们的纪念日----范玮琪 24、启程----范玮琪 25、最初的梦想----范玮琪 26、是非题----范玮琪 27、你是答案----范玮琪 28、没那么爱他----范玮琪 29、可不可以不勇敢----范玮琪 30、一个像夏天一个像秋天----范玮琪 31、听，是谁在唱歌----刘若英 32、城里的月光----许美静 33、女人何苦为难女人----辛晓琪 34、他不爱我----莫文蔚 35、你是爱我的----张惠妹 36、同类----孙燕姿 37、漩涡----孙燕姿 38、爱上你等于爱上寂寞----那英 39、梦醒了----那英 40、出卖----那英 41、梦一场----那英 42、愿赌服输----那英 43、蔷薇----萧亚轩 44、你是我心中一句惊叹----萧亚轩

45、突然想起你----萧亚轩 46、类似爱情----萧亚轩 47、Honey----萧亚轩 48、他和他的故事----萧亚轩 49、一个人的精彩----萧亚轩 50、最熟悉的陌生人----萧亚轩 51、想你零点零一分----张靓颖 52、如果爱下去----张靓颖 53、我想我是你的女人----尚雯婕 54、爱恨恢恢----周迅 55、不在乎他----张惠妹 56、雪地----张惠妹 57、喜欢两个人----彭佳慧 58、相见恨晚----彭佳慧 59、囚鸟----彭羚 60、听说爱情回来过----彭佳慧 61、我也不想这样----王菲 62、打错了----王菲 63、催眠----王菲 64、执迷不悔----王菲 65、阳宝----王菲 66、我爱你----王菲 67、闷----王菲 68、蝴蝶----王菲 69、其实很爱你----张韶涵 70、爱情旅程----张韶涵 71、舍得----郑秀文 72、值得----郑秀文 73、如果云知道----许茹芸 74、爱我的人和我爱的人----裘海正 75、谢谢你让我这么爱你----柯以敏 76、陪我看日出----蔡淳佳 77、那年夏天----许飞 78、我真的受伤了----王菀之 79、值得一辈子去爱----纪如璟 80、太委屈----陶晶莹 81、那年的情书----江美琪 82、梦醒时分----陈淑桦 83、我很快乐----刘惜君 84、留爱给最相爱的人----倪睿思 85、下一个天亮----郭静 86、心墙----郭静 87、那片海----韩红 88、美丽心情----RURU

the-way-的用法讲解学习

t h e-w a y-的用法

The way 的用法 "the way+从句"结构在英语教科书中出现的频率较高, the way 是先行词, 其后是定语从句.它有三种表达形式:1) the way+that 2)the way+ in which 3)the way + 从句(省略了that或in which),在通常情况下, 用in which 引导的定语从句最为正式,用that的次之,而省略了关系代词that 或 in which 的, 反而显得更自然,最为常用.如下面三句话所示,其意义相同. I like the way in which he talks. I like the way that he talks. I like the way he talks. 一.在当代美国英语中,the way用作为副词的对格,"the way+从句"实际上相当于一个状语从句来修饰全句. the way=as 1)I'm talking to you just the way I'd talk to a boy of my own. 我和你说话就象和自己孩子说话一样. 2)He did not do it the way his friend did. 他没有象他朋友那样去做此事. 3)Most fruits are naturally sweet and we can eat them just the way they are ----all we have to do is clean or peel them . 大部分水果天然甜润,可以直接食用,我们只需要把他们清洗一下或去皮.

适合女生唱的各种难度的歌

婴儿——陈倩倩 这首歌真的凄凉到有点儿甚人的感觉。“喜欢一个人的心情”——江语晨，因为这歌的词。 那又怎么样呢——张玉华 我爱听音乐，但一定要是伤感的，虽然不会听到泪流满面，但是那种感觉真的很好 还爱你——景甜 你可以爱我很久吗——游艾迪 夜夜夜夜——原唱齐秦 爱一直存在——梁文音 有人想找男生唱的，真不常听男生的歌，不过有几首觉得挺不错的。 初雪的忧伤——赵子浩 爱你，离开你——南拳妈妈 说谎——林宥嘉 三人游、爱爱爱——方大同 分开以后——唐禹哲 突然好想你——五月天 还是男生的， 寂寞的季节、暗恋——陶喆 情歌两三首——郭顶 掌纹——曹格 需要人陪——王力宏 王妃——箫敬腾（除了这首，其他几首都是比较安静抒情的。） 挥之不去——殷悦 别再哭了——罗忆诗 前段时间特别喜欢这首歌，听的快吐了，真的挺好听。 热气球——黄淑惠 很特别，超级好听，强烈推荐。 你是爱我的——张惠妹 她的嗓音让我着迷，超级喜欢。 问——粱静茹 老歌了，不过很喜欢。

忽略——萧萧 握不住的他，看到萧萧还是会第一个想起这首。 趁早——张惠妹 她有点儿沙哑的声音让我着迷。 幸运草——丁当 早点儿的歌了，喜欢丁当。 哭了——范晓萱 越听越喜欢，。 氧气——范晓萱 小时候喜欢听她的歌，不过随着年龄的增长，喜欢的类型也变了。 温柔的慈悲——阿桑 喜欢她的歌，只是她的声音不能再更新了。 礼物——刘力扬 罗美玲的也还好。。 洋葱——丁当杨宗纬（两个不一样的感觉） 挺难的唱不好，不过喜欢听。 眼泪知道——温岚 喜欢，唱出来特别有激情哈。

类似爱情——萧亚轩 不难又有感觉。 第三者——梁静茹 还好，喜欢这首歌的歌词。 心墙——郭静 “我不想忘记你”，“不药而愈”，“每一天都不同”，都好听喜欢她的歌。 我知道你很难过——蔡依林 唱起来有感觉也不难唱，推荐。 夏伤——SARA 感觉很特别，喜欢。 那天——蓝又时 喜欢她的歌，她的调调，强烈推荐。“秘密”也不错。 礼物——罗美玲 好听有感觉，不过不太好唱。 我比想象中爱你——JS 老歌了一直很喜欢，唱起来有感觉。

高一音乐 甜美纯净的女声独唱教案

魅力四射的独唱舞台 ——甜美纯净的女声独唱 一、教学目标 1、认知目标：初步了解民族唱法、美声唱法、通俗唱法三种唱法的风格。 2、能力目标：通过欣赏部分女声独唱作品，学生能归纳总结出她们的演唱 风格和特点，并同时用三种不同风格演唱同一首歌曲。 3、情感目标：通过欣赏比较，对独唱舞台有更多元化的审美意识。 二、教学重点：学生能用三种不同风格演唱形式演唱同一首歌。 三、教学难点：通过欣赏部分女声独唱作品，学生能归纳总结出她们的演唱 风格和特点。 四、教学过程： （一）导入 1、播放第十三界全国青年歌手大奖赛预告片 （师）问：同学们对预告片中的歌手认识吗 （生）答： （师）问：在预告片中提出了几种唱法？ （生）答：有民族、美声、通俗以及原生态四种唱法，今天以女声独唱歌曲重点欣赏民族、美声、通俗唱法，希望通过欣赏同学们能总结出三种唱法的风格和特点。

（二）、音乐欣赏 1、通俗唱法 ①(师)问：同学们平常最喜欢唱那些女歌手的歌呢？能唱唱吗？ （可让学生演唱几句喜欢的歌，并鼓励） ②欣赏几首通俗音乐 视频一：毛阿敏《绿叶对根的情谊》片段、谭晶《在那东山顶上》片段、韩红《天路》片段、刘若英《后来》片段 视频二：超女《想唱就唱唱得响亮》 ①由学生总结出通俗音乐的特点 ②师总结并板书通俗音乐的特点：通俗唱法是在演唱通俗歌曲的基础上发展起来的，又称“流行唱法”。通俗歌曲是以通俗易懂、易唱易记、娱乐性强、便于流行而见长，它没有统一的规格和演唱技法的要求，比较强调歌唱者本人的自然嗓音和情绪的渲染，重视歌曲感情的表达。演唱上要求吐字清晰，音调流畅，表情真挚，带有口语化。 ③指出通俗音乐尚未形成系统的发声训练体系。其中用沙哑、干枯的音色“狂唱”和用娇柔、做作的姿态“嗲唱”，不属于声乐艺术的正道之物，应予以摒弃。 2、民族唱法 ①俗话说民族的才是世界的那么民族唱法的特点是什么呢？ ②欣赏彭丽媛《万里春色满人间》片段 鉴赏提示：这首歌是剧种女主角田玉梅即将走上刑场时的一段难度较大的咏叹调。

way的用法总结大全

way的用法总结大全 way的用法你知道多少，今天给大家带来way的用法，希望能够帮助到大家，下面就和大家分享，来欣赏一下吧。 way的用法总结大全 way的意思 n. 道路,方法,方向,某方面 adv. 远远地，大大地 way用法 way可以用作名词 way的基本意思是“路,道,街,径”,一般用来指具体的“路,道路”,也可指通向某地的“方向”“路线”或做某事所采用的手段,即“方式,方法”。way还可指“习俗,作风”“距离”“附近,周围”“某方面”等。 way作“方法,方式,手段”解时,前面常加介词in。如果way前有this, that等限定词,介词可省略,但如果放在句首,介词则不可省略。

way作“方式,方法”解时,其后可接of v -ing或to- v 作定语,也可接定语从句,引导从句的关系代词或关系副词常可省略。 way用作名词的用法例句 I am on my way to the grocery store.我正在去杂货店的路上。 We lost the way in the dark.我们在黑夜中迷路了。 He asked me the way to London.他问我去伦敦的路。 way可以用作副词 way用作副词时意思是“远远地,大大地”,通常指在程度或距离上有一定的差距。 way back表示“很久以前”。 way用作副词的用法例句 It seems like Im always way too busy with work.我工作总是太忙了。 His ideas were way ahead of his time.他的思想远远超越了他那个时代。 She finished the race way ahead of the other runners.她第一个跑到终点,远远领先于其他选手。 way用法例句

适合女生唱的100首好听的歌

适合女生唱的100首好听的歌 1、偏爱----张芸京 2、阴天----莫文蔚味道很难把握 3、眼泪----范晓萱还好，张学友版本适合男生 4、我要我们在一起---范晓萱A段超级难唱的，拍子和口气都不好抓 5、无底洞----蔡健雅听起来简单，唱起来很难——这首是典型的例子 6、呼吸----蔡健雅 7、原点----蔡健雅&孙燕姿到哪里找两个好听的女中音呢？ 8、我怀念的----孙燕姿 9、不是真的爱我----孙燕姿 10、我也很想他----孙燕姿 11、一直很安静----阿桑 12、让我爱----阿桑 13、错过----梁咏琪 14、爱得起----梁咏琪为什么没有洗脸？剪发？胆小鬼？ 15、蓝天----张惠妹 16、记得----张惠妹 17、简爱----张惠妹是剪爱吧？ 18、趁早----张惠妹男生可以试试张宇的版本 19、一念之间----戴佩妮 20、两难----戴佩妮 21、怎样----戴佩妮 22、一颗心的距离----范玮琪 23、我们的纪念日----范玮琪 24、启程----范玮琪 25、最初的梦想----范玮琪 26、是非题----范玮琪 27、你是答案----范玮琪 28、没那么爱他----范玮琪 29、可不可以不勇敢----范玮琪 30、一个像夏天一个像秋天----范玮琪范范的歌这么多啊。。。 31、听，是谁在唱歌----刘若英 32、城里的月光----许美静 33、女人何苦为难女人----辛晓琪我一直在找这个歌曲的粤语版，却找不到

34、他不爱我----莫文蔚 35、你是爱我的----张惠妹 36、同类----孙燕姿 37、漩涡----孙燕姿 38、爱上你等于爱上寂寞----那英在KTV点这个歌曲的MTV不是会很尴尬吗？ 39、梦醒了----那英 40、出卖----那英 41、梦一场----那英 42、愿赌服输----那英没有征服？也许是太大众了吧。 43、蔷薇----萧亚轩 44、你是我心中一句惊叹----萧亚轩 45、突然想起你----萧亚轩 46、类似爱情----萧亚轩 47、Honey----萧亚轩 48、他和他的故事----萧亚轩 49、一个人的精彩----萧亚轩 50、最熟悉的陌生人----萧亚轩还记得她第一张专籍里面最喜欢那首《没有人》 51、想你零点零一分----张靓颖 52、如果爱下去----张靓颖 53、我想我是你的女人----尚雯婕 54、爱恨恢恢----周迅 55、不在乎他----张惠妹 56、雪地----张惠妹 57、喜欢两个人----彭佳慧 58、相见恨晚----彭佳慧 59、囚鸟----彭羚 60、听说爱情回来过----彭佳慧 61、我也不想这样----王菲 62、打错了----王菲 63、催眠----王菲 64、执迷不悔----王菲 65、阳宝----王菲 66、我爱你----王菲 67、闷----王菲