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By default, all cells use the General number format. This format is basically what you type is what you get. But if the cell isn t wide enough to show the entire number, the General format rounds numbers with decimals and uses scientific notation for large numbers. In many cases, the General number format works just fine. But most people prefer to specify a different number format for consistency. The key thing to remember about number formatting is that it affects only how a value is displayed. The actual number remains intact, and any formulas that use a formatted number use the actual number.

1 A. Hocquenghem, Codes correcteurs d"erreurs, ChifFres, Vol. 2, pp. 147-156, 1959. 2 R.C. Bose and D.K. Ray-Chaudhuri, On a class of error-correcting binary group codes, Information and Control, Vol. 3, pp. 68-79, 1960. 3 I.S. Reed and G. Solomon, Polynomial codes over certain finite fields, J. Soc. Indust. Applied Math. Vol. 8, pp. 300 304, 1960. 4 D.C. Gorenstein and N. Zierler, A class of error-correcting codes in pm symbols, J. Soc. Indust. Applied Math. Vol. 9, pp. 207-214, 1961. 5 R.E. Blahut, Theory and Practice of Error Control Codes, Addison Wesley, 1983. 6 G.C. Clark and J.B. Cain, Error-Correction Coding for Digital Communications, Plenum Press, 1981. 7 A.M. Michelson and A.H. Levesque, Error-Control Techniques for Digital Communication, John Wiley & Sons, 1985. 8 S.B. Wicker, Error Control Systems for Digital Communication and Storage, Prentice Hall, 1994. 9 M. Bossert, Channel Coding for Telecommunications, John Wiley and Sons, 1999. 10 Y. Xu, Implementation of Berlekamp-Massey Algorithm without inversion, IEE Proceedings-I, Vol. 138, No. 3, pp. 138-140, June 1991. 11 H-C. Chang and C-S.B. Shung, Method and apparatus for solving key equation polynomials in decoding error correction codes, US Patent US6119262, September 2000.

var selArray = theDOM.getSelection(); alert(selArray);

3. You re prompted to select a location to save the file and to supply a name. I suggest that you name the file Inventory.fp7 and that you save the file to the Documents folder on a Mac or the My Documents folder in Windows. The database is created, its window appears, and the Manage Database for Inventory dialog (shown in Figure 5.2) appears.

This chapter is devoted to the contribution that diffraction and microscopy make in deriving and understanding the structures of biological macromolecules. Without doubt, X-ray crystallography is the pre-eminent technique for the structural characterisation of biological macromolecular structure and has been responsible for the derivation of more atomic-level structures of biological macromolecules than all other techniques put together. Hence, X-ray crystallography appears rst in this chapter. Thereafter, the attention of the chemical biology reader will be drawn towards electron microscopy and then scanning-probe microscopy. Of these, the technique of cryo-electron microscopy has a realistic potential and capacity to rival X-ray crystallography as the pre-eminent technique for the characterisation of biological macromolecular structures. Scanning probe microscopy is in some ways less developed but shows an impressive diversity in the size and morphology of three-dimensional biological macromolecular structures that may be studied under a variety of conditions. This chapter is intended to provide an explanation of the main theories and ideas that underpin the use of diffraction and microscopy in chemical biology research, then thereafter to provide a bridge from these main theories and ideas to actual examples of successful three-dimensional structure characterisation. In 5, we illustrated the concepts of multi-dimensional NMR spectroscopy with reference to data derived from the structural characterisation of one main protein, interleukin-1 (IL-1 ), a key biological messenger of in ammation (see also 7). In this chapter, illustrations for successful structural characterisations are taken from the fascinating world of heat shock/stress protein research (see also 7). There is nothing overstated in saying that much of our current understanding of the molecular workings of biology derives from successful structural characterisations made possible by diffraction and/or microscopy. Therefore, read on!

This formula returns 47.997 (that is, 48 months). The monthly payment was rounded to the nearest penny, causing the minor discrepancy.

type A.dr,st with the value of its variable. The variable indicate the become riuniber of A.dzst messages that node is expecting. Whenever 0, it knows that it has heard from all its neighbors and therefore it knows the neighbor with the least distance. The variable is used for recalculation of the distance. is The main program that invokes and shown in Figure 18.9.

Now, you can finish up this program with Listing 18-17.