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Figure 6.47. Geometric description of diffracted beams for different hkl. Three beams are shown which are out of phase and have different phase angles. The structure factor Fhkl is a resultant vector between the cosine and sine vectors A and B . The angle formed between IFIhkl and the horizontal is hkl . The relationship between the wave description (below) and geometric description (above) is shown.

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are stored in variables so that they can be later tested against the regex. One complication, however, is that the number of words per line of text varies, and it is not known beforehand. This requires the ability to store a variable number of substrings, which is easily done with arrays. An array is an ordered collection of variables with a common name that starts with an Q character. Each variable in an array is indexed by the nonnegative numbers 0, 1, 2, .... Code sample 2.2 gives an example. Since the text "The sun is rising." has three blanks, it splits into four substrings, and "The" is stored in $word [O] , "sun" in $word [I], "is" in $word [ 2 ] , and "rising." in $word [3]. The array Qword refers to this collection of four variables as a single unit. One convenient feature of Perl is that the programmer does not need to specify how big the array is beforehand. So the output of the function split can be stored in an array despite that the number of substrings produced is unknown beforehand.

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3. In the Save As dialog box, change the le location and name if desired. 4. Click Save. A dialog box appears asking whether you want to save every slide in the presentation or the current slide only. 5. Click Every Slide or Current Slide Only, depending on your preference. 6. If you choose Every Slide, a message appears that a folder has been created for the slide les. Click OK. (Each slide is a separate graphic.)

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The previous nine chapters all dealt with planning. The order of these chapters is not arbitrary. In s 2 and 3, Hommel and Hoc discussed theories about humans that plan their own activities. 4 (Jorna), 5 (Gazendam), and 6 (McKay and Wiers) changed focus by studying humans that plan organizational processes. As was noted several times, planning for yourself differs from planning for others. In the subsequent chapters by van Wezel ( 7), Kroon and Zuidwijk ( 8), and Sauer ( 9), the focus again changed. Organizational processes were still the topic, but now the planning entity was not a human but an artifact (software or algorithm). And in 10, Bowling et al. discuss an example of the remaining kind of planning: an arti cial entity (a robot) that plans his own activities. In 18, we will compare and analyze the differences and similarities of these kinds of planning, and the basis for much of the ndings there can be found in the next chapter by Meystel. Meystel focuses on planning as problem solving within intelligent systems. He provides us with a basic framework that is applicable to all intelligent systems, whether they be human or machine. Three basic starting points underlie the analysis of Meystel. First, each intelligent system functions according to the Elementary Loop of Functioning (ELF) consisting of sensing in the external world, making judgments, generating behavior, and implementing the behavior in the external world. Although the background of much of Meystel s observations is in autonomous robots, he claims the ELF holds for all intelligent systems. Second, each system functions hierarchically at multiple levels of resolution in order to handle

where g. is the number of particle degrees of freedom and again fundamental constants have been set to one. Fermions count 7/8 per degree of freedom towards this sum, and bosons 1. Photons have two degrees of freedom (the polarization states), and each of the electron and positron has two states (spin up and spin down). If the epoch of electron-positron annihilation occurs at constant entropy and produces only photons, demonstrate that the photon temperature is raised relative to the neutrino temperature by a factor Vll/4. A3.3. By considering the ratio of the neutrino thermal energy 3k B T to its mass-energy, derive an approximate formula for the redshift at which massive neutrinos first become non-relativistic. Evaluate this redshift for the case of a neutrino hot dark matter candidate with mass-energy m v = 10 eV. Using equation (11.11), estimate the distance (in comoving megaparsecs) that such neutrinos travel while relativistic.

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