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A number of methods have been developed for the end-group analysis of polymers (11). Speci c examples of end-group analyses of inorganic polymers include radioactivity measurements of hot-atom fragments appended to end groups, spectroscopic evaluation of at least one end group or modi ed end group, and titration of end groups. The limitations depend on the sensitivity of the method relative to the mass of the polymer being measured. The use of radioactive tracer measurements was quite popular several decades ago, is a very sensitive method, and can be used for insoluble polymers (11). Titration methods are possible for end groups that are acidic or basic; however, the sensitivity of the method is often quite low except for polymers with high solubility and/or moderate molecular mass. Likewise, spectroscopic methods are often not sensitive enough for highmolecular-mass species. However, sometimes a group can be substituted on the end group of a polymer chain that increases the sensitivity of the method, for example, the use of t-butyl groups to enhance the sensitivity of proton magnetic resonance spectroscopy as noted below. The polymeric molecules that result from an A A plus B B step polymerization would be expected to have an equal number of A ends and B ends. This is the case for exact stoichiometry where 50% of the polymeric product molecules have one A end and one B end, 25% have two A ends, and 25% have two B ends. However, for slightly nonstoichiometric ratios the end-group ratios are not 1:1. The mathematical expression for the general case is shown in Eq. 3.31. 1 N0 C 1 A r N0 D Nends D 2 number of molecules B 3.31

(1998) The Java Reliable Multicast Service: A Reliable Multicast Library Technical Report SMLI TR-98-68, Sun Microsystems, Palo Alto, CA [73] Schabanel, N (2000) The Data Broadcast Problem with Preemption LNCS 1770 Proceedings of the 17th International Symposium on Theoretical Aspects of Computer Science (STACS 2000), pp 181 192, Lille, France [74] Shanmugasundaram, J, Nithrakashyap, A, Sivasankaran, R, and Ramamritham, K (1999) Ef cient Concurrency Control for Broadcast Environments ACM SIGMOD International Conference on Management of Data, Sydney, Australia [75] Sigel, E (1980) Videotext: The Coming Revolution in Home/Of ce Information Retrieval, Knowledge Industry Publications, White Plains, New York [76] Stathatos, K, Roussopoulos, N, and Baras, J S (1997) Adaptive Data Broadcast in Hybrid Networks Proceedings 23rd International Conference on Very Large DataBases, pp 326 335, Athens, Greece [77] Su, C J and Tassiulas, L (1997) Broadcast Scheduling for Information Distribution.

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OCCLUSAL INTERFERENCE SEQUELAE Many studies have demonstrated that placing a restoration with an occlusion that is not in

Proceedings of the Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 1997), Kobe, Japan [78] Tanenbaum, A S (1992) Modern Operating Systems, Prentice Hall, Englewood Cliffs, NJ [79] Tassiulas, L and Su, C J (1997) Optimal Memory Management Strategies for a Mobile User in a Broadcast Data Delivery System IEEE Journal on Selected Areas in Communications, 15(7), 1226 1238 [80] Vicisano, L, Rizzo, L, and Crowcroft, J (1998) TCP-Like Congestion Control for Layered Multicast Data Transfer Proceedings of the Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 1998), San Francisco, CA [81] Viswanathan, S, Imielinski, T, and Badrinath, B R (1997) Data On Air: Organization and Access IEEE Transactions on Knowledge and Data Engineering, 9(3), 353 372 [82] Weihl, W E (1987) Distributed Version Management for Read-Only Actions ACM Transactions on Software Engineering, 13(1), 56 64.

where A and B are bounded functions of the pair s and t. A similar expansion for the conditional variances shows that Var(X (s) C), Var(X (t) C) L(s t)2 for some positive constant L. So A+ (u, u) ds dt s,t E X + (s)X + (t) C pX(s),X(t) (u, u) ds dt

[83] Young, N (1998) On-Line File Caching Proceedings of the Ninth Annual ACMSIAM Symposium on Discrete Algorithms, pp 82 91, San Francisco, CA..

What are we going to provide for our customer entity bean then Well, we've decided that we only want three variations: 1. No arguments, so a person can create a new default user that has no data configured. 2. A single integer argument that is interpreted to be the customer ID. This will fetch the details of the nominated customer from the database. 3. Five parameters that correspond to the five columns of the customer database (the customer ID is automatically generated). This allows you to create a new customer with all the details set immediately. The end result looks like this:

When you create a frame window for chatting, the chat bean is in the construction phase. The frame window can be placed either on an IBM Visual Age form or on an HTML form. You can change the background color of the frame window to match the background color of the form. In addition, you can change the

To prove (2.3) we use the inversion formula for the Fourier transform and the form of the Fourier transform of the normal distribution in Rn : (x) = 1 (2 )n

Scatterplots can be used to identify whether any relationship exists between two continuous variables based on the ratio or interval scales. The two variables are plotted on the x- and y-axes. Each point displayed on the scatterplot is a single observation. The position of the point is determined by the value of the two variables. The scatterplot in Figure 4.6 presents many thousands of observations on a single chart. Scatterplots allow you to see the type of relationship that may exist between the two variables. For example, the scatterplot in Figure 4.7 shows that the

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