Wrapping Up in .NET

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8. Click the drawing Close box, which is just below the application Close box. Because you haven t saved the changes to the drawing, a message asks if you want to save them. 9. Click Yes. AutoCAD or AutoCAD LT saves and closes the drawing. 10. Click the application s Close box (X) to close AutoCAD or AutoCAD LT.
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For nearby objects z 1 and so d1um ~ dphys. i.e. the objects really are just as far away as they look. But more distant objects appear further away (dl um > d phys ) than they really are. If the geometry is not flat, this gives an additional effect which can either enhance this trend (hyperbolic geometry) or oppose it (spherical geometry) - see Problem A2.2. Provided there is no cosmological constant, there are useful analytic forms for the luminosity distance as a function of redshift, related to an equation known as the Mattig equation, but once a cosmological constant is introduced calculations have to be done numerically. A detailed account can be found in Peacock's textbook (see Bibliography). Before we can use the luminosity distance in practice, there is a problem to overcome. The luminosity we have described is the total luminosity of the source across all wavelengths (called the bolometric luminosity), but in practice a detector is sensitive only to a particular range of wavelengths. The redshifting of light means that the detector is seeing light emitted in a different part of the spectrum, as compared to nearby objects. If enough is known about the emission spectrum of the object, a correction can be applied to allow for this. which is known as the K-correction, though often its application is an uncertain business. The luminosity distance depends on the cosmological model we have under discussion. and hence can be used to tell us which cosmological model describes our Universe. In particular. we can plot the luminosity distance against redshift for different cosmologies, as in Figure A2.3 (see Problem A2A to find out how to obtain these curves). Unfortunately, however, the observable quantity is the radiation flux density received from an object, and this can only be translated into a luminosity distance if the absolute luminosity of the object is known. There are no distant astronomical objects for which this is the case. This problem can however be circumvented if there are a population of objects at different distances which are believed to have the same luminosity: even if that luminosity is not known, it will appear merely as an overall scaling factor. Such a population of objects is Type Ia supernovae. These are believed to be caused by the core collapse of white dwarf stars when they accrete material to take them over the Chandrasekhar limit. Accordingly. the progenitors of such supernovae are expected to be very similar, leading to supernovae of a characteristic brightness. This already gives a
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Before editing any preexisting files, back them up. The new system of editing menus and toolbars in a dialog box helps to protect your system from errors that you might make when customizing, but if you want to undo all of your changes, you need a backup. You should back up in three stages: Back up the original file as it came out of the box. Keep a disk with all of the customizable files that you might ever edit in their original form. After you edit the file, back it up before each editing session. This way you always have your most recent version of the file. If you make a mistake, it s easy to copy that file on top of the one with the mistake and put everything back to normal. After you edit a file, back it up again so that you have it in case your hard drive crashes, or you need to reinstall AutoCAD or AutoCAD LT.
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It is often convenient to speak of the emittance for a particular particle distribution in terms of the rms transverse beam size. As an example, we will consider a beam in a synchrotron in which the particles follow a Gaussian distribution in one transverse degree of freedom. This is the natural choice for electron storage rings, since synchrotron radiation ensures that the equilibrium distributions are Gaussian provided that particle losses are insignificant. The Gaussian distribution function is also a reasonable approximation for proton beams as well, in most instances. Suppose that the distribution in the transverse coordinate x normalized to one particle is given by the density function
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Figure 6.39. Scattering of X-rays by electrons. (a) Coherent scattering. The beam of X-rays induces an oscillation in the electron (e) which has the same frequency as the incident radiation. This results in emission of secondary radiation which is 180 out of phase with incident radiation. (b) Anomalous scattering. When the frequency of the incident beam (v) corresponds or is close to a naturally-occurring frequency in the electron, this results in emission of radiation known as anomalous scattering.
21: Creating QuickTime Movies in GoLive . . . . . . . . . . 703
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Once a clearinghouse or vendor has done sufficient testing and analysis to confirm that what s being reported is heretofore unknown malware and can document its workings, the word on new malware will usually begin to spread. Most anti-virus software vendors are pretty good at responding to new infections in 24 hours or less; seldom will you find that it takes them more than 48 hours not just to get the word out, but also to update their software to fend off such newly discovered attacks (either by eliminating vulnerabilities, denying access to vulnerable parts, or other techniques to repair weaknesses or avoid infection). Given the pace of new malware discoveries, and the increasing level of their severity, most vendors issue daily virus notifications and downloadable software updates. Most will issue automatic software updates when more dangerous malware is discovered, but also issue automatic updates on a regular (usually weekly) schedule. What you ll find in a typical virus bulletin, alert, or report usually includes the following ingredients: Some kind of standardized name for the malware The Common Vulnerabilities and Exposures (CVE) center at defense contractor MITRE (www.cve.mitre.org) has been set up to establish a common naming convention and common names for malware to help make identification consistent across multiple clearinghouses and vendor reports (not all vendors currently support CVE names, though most now routinely include links to CVE documents in their reports, and many are moving to that nomenclature as I write this book). I explain how malware is named in a sidebar entitled Naming Malware later in this chapter. Many vendors include as many other names as are known when they write their reports, in the interests of quick identification, recovery, and repair (where needed). Detailed description of the malware This includes any or all of e-mail subjects, From addresses, message text, file or attachment names, infection and propagation methods, vulnerabilities exploited, and so forth. Methods of infection are often covered step by step, as are specific changes or updates needed to prevent them. The idea here is to help people recognize symptoms or look for telltale signs of infection, so more information is better than less, and as much such information as is available will usually be provided. Threat or risk assessment As discussed earlier in this chapter, most vendors and some clearinghouses rate malware according to their estimation of the threat it poses to those who interact with the Internet. This may not be exactly the same from multiple sources, but will generally provide a pretty good idea about how serious a threat may be, how much damage it can cause, and how fast it can spread. Repair or recovery tools and techniques Most vendor reports will include pointers to download removal or recovery tools, when available, but will also include step-by-step instructions for manual repair and recovery if it should not prove possible or feasible to download and use automated tools. This also ends up providing a very detailed description of what parts of a system malware affects, and how those effects can be reversed or repaired.
that is, the vector of the time-domain voltages at all ports. The latter is computed from the voltage phasors by means of an inverse Fourier transform: v(t) =
Figure 3-5: If the font is not installed or not embedded, font substitution is used. With script fonts, the substitution is less accurate than with serif and sans serif fonts.
5. Click Close to return to your drawing.
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