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You can find Toolbox settings in the Toolbox menu, by selecting the Configure option. The Configure Data dialog box has four tabs: Content, Settings, Properties, and Smart Fasteners.

It is recommended that you leave Detach Segment on Drag off. Turn it on only when you need it, and then immediately turn it off again. This setting can be hazardous for everyday use, because it enables you to simply drag sketch elements that may be otherwise fully defined.n

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In the highly complex worlds of information technology and information systems, the only constant is change. The more complex and integrated that IT systems become, the more important having change control becomes. Managing change has thus become one of the most important MIS functions in many organizations. If you do not manage change, the unexpected results of an unmanaged change could render you extinct. Processes, routines, functions, algorithms, and the like do not exist in vacuums or some form of digital isolation from the rest of the universe. Just as in life, all processes depend on or are depended on by other routines or processes. If you change the way that a process behaves, you alter its event course. In other words, you alter its destiny. Altering the event course of a process is in itself not the problem. Problems arise if processes dependent on a particular course of events are no longer afforded what they were expecting. Think about how you feel and are inconvenienced when a person that you were going to meet does not turn up or cancels the engagement unexpectedly. In software and computer systems, such events can have catastrophic results. They in turn fail, and their event courses are also altered. Whenever processes begin to crash, an unstoppable domino effect takes place, leading to systems failure and disaster from one end of the system to the other. This is why troubleshooting is such a dif cult exercise: The best troubleshooters are those who look beyond the evidence of failure and seek to discover what caused the problem or what event led up to system failure.

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1. Periodic crystal potential. This is treated quantum-mechanically for bandstructure, E(k), and m* because the De Broglie wavelength of electrons is greater than the periodicity of the lattice potential. 2. Random scattering potential due to impurities and/or defects [V(r)], or phonons [V(rt)]. This is treated quantum-mechanically by time-dependent perturbation theory and the Fermi golden rule. 3. External driving potential due to applied voltages or EM waves: This is treated classically by Newtonian mechanics using the effective mass, assuming spatial variations of external potential are on longer distance scales than the De Broglie wavelength. Otherwise, a quantum treatment is required even for the external forces. In exact analogy with the free-electron case (Eqs. 4.1 Ob, 4.12), the two governing equations of these semiclassical Bloch electrons are 3 ,7 reproduced here as Eqs. (4.30a) and (4.30b):

If you think of the elements of CPO s SIP as machine gun bullets, then the second step is to deliver two identical belts of ammunition to the two divisions, who re them through their own models to produce SIPs of their pro ts, as shown in Figure 43.4. Note that the rst element in each output SIP corresponds to rolling a four in the housing market, the second one a three in the market, and so on. In this example, we have determined the output SIP for each division by running the input SIP through the appropriate column of the table in Figure 43.2, but in general each division s model could be created in a spreadsheet or more sophisticated modeling environment. So, to review, one input SIP went in, and two output SIPs came out. But these aren t just two SIPs anymore. They now form a scenario library unit with relationships preserved (or a SLURP), which maintains the dependence of each division on the housing market. The nal step is just to add the output SIPs of the two divisions together to create the SIP of total pro t, as shown in Figure 43.5. With SLURPs, the simulation of the sum does equal the sum of the simulations because it preserves the interrelationships. In other words, for each element of the output SIP of total pro t, each division faced the same market scenario: four, three, six, etc. If a traditional Monte Carlo simulation had been run on each division, one

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