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This minimizes the sum of the squares of deviation of |Fhkl calc | from |Fhkl obs | for the whole structure However if the model, though largely correct, is incorrect in parts, the least squares procedure can become trapped in a local energy minimum (Figure 657) This is because the computer algorithms which carry out the least squares re nement generally only make small alterations to the model on each iteration To rescue the model from a local energy minimum may require extensive revision of the model In such situations a procedure called simulated annealing is used This simulates the effect of heating the molecule to give each atom much greater freedom of movement The net effect of this is that the model can explore a much greater range of possible conformations and thus arrive at a global energy minimum.

1 presented a variety of network topologies. In this chapter, we will attempt to provide further information concerning the implementation and use of these topologies in the creation of a LAN. Figure 2-11 illustrates a very basic network map. The purpose is to demonstrate that even a simple network can and probably will use a variety of media, protocols, and network devices. The media shown on this network topology is a combination of wired systems, which include both ring and bus network topologies, along with a network segment that is connected using wireless network technology. Users are connected to the network either hard-wired to a bus or ring LAN segment or through a wireless LAN access point.

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The range of R factors estimated for biomacromolecules are signi cantly larger (12 20%) than are obtained in small molecule crystallography (3 5%) A major reason for this is the dif culty of modelling the relatively high water content of protein and DNA crystals (which can be up to 50%) One successful approach to this problem is to model water in layers approaching the biomacromolecule with the solvation shell having the highest order and lowest mobility..

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281

Particulates (mg/m3)

x+ct 1 1 [f (x + ct) + f (x ct)] + g(s) ds. 2 2c x ct 12.8. In (12.11) suppose that L L H x L d , x +d d 2 2 2 f (x) = H L L L , d x d x 2 +d , 2 2 0, elsewhere

(3.25b) (3.25c)

approaches and indicators of likelihoods and consequences described in 5 can be extended in their application to tender evaluation.

Actually, I think the psychology of malware is a little less clear-cut than this definition suggests, but I m not about to argue on behalf of misguided (but sometimes intelligent and gifted) programmers who appear to tackle writing malware like mountain climbers tackle formidable peaks like Mount Everest. The interesting thing about this particular definition is that it introduces a number of important constituent elements namely viruses, worms, and Trojan horses, which I explore in the sections that follow.

By scouring the Web and various publications I ve put together a small collection of anti-spam software and anti-spam service offerings, along with a highly ranked and highly rated offering that can only be characterized as a hybrid, since it requires users to install an Outlook plug-in on their PCs, but also communicates over the Internet with the vendor s continuously updated spam database. All of these items are presented in Table 9-1, and include brief descriptions, along with name, type, and URL information. Before you look at Table 9-1, perhaps some explanation of its terminology will be helpful. In that table, Type can take three values: SW This indicates a software-based antispam package that operates on the user s desktop, either as a plug-in to his or her e-mail package, or as an intermediary program.

86 PROACTIVE AND REACTIVE PLANNING In this section we explain the differences between proactive planning and reactive planning, and we show that both planning processes can be supported by applying mathematical models So far, we assumed that the planning process starts completely from scratch That is, before starting the planning process, no plans or partial plans are available yet Also the models that we described so far aimed at generating plans completely from scratch, not taking into account earlier generated plans In this case, we talk about a proactive planning process In this case, the planning process may be triggered by the fact that the plans are to be updated with a certain xed frequency For example, a public transport company usually updates his basic logistic plans at least once per year.

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