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3. Choose to embed the entire font set by clicking the All Characters radio button. To embed a partial font set, click the Only button and choose an option. When you choose to embed a partial font set with an input text box, only the embedded characters are passed on to the variable. This is handy when you re accepting numeric input. Limit the maximum number of characters to 5 and embed only numerals, and in the Include These Characters field, type a decimal point (.). By doing this, you limit the maximum value the users can input to 99999 with no decimal point, or 99.99 with a decimal point. 4. Click Done to close the dialog box.
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that the Windows CE application programming interface (API) is a subset of the traditional Win32 API. It is also true that a majority of application programmers who are interested in developing software for Windows CE based devices come to this new platform with some level of Windows programming experience. A detailed introduction to Windows CE programming concepts such as window classes and window procedures would therefore be wasted on programmers with a lot of Win32 experience. On the other hand, not covering these topics at all might alienate those developers whose primary Windows experience is with class libraries such as the Microsoft Foundation Classes (MFC). All of the code samples in this book use the Windows CE API directly in order to promote a solid understanding of Windows CE programming from the most fundamental level. Some coverage of basic concepts is therefore necessary. In order to strike a compromise, this chapter presents a basic Windows CE template application. This application can be used as the boilerplate for any other application that you may wish to write. It does nothing but display a main application window and implement the most rudimentary window procedure. I promise that nowhere in this application will you find words even remotely reminiscent of Hello World ! In fact, the template application presented in this chapter is the foundation of all the other sample applications presented in this book. Each of the applications was written by taking the template source code and adding functionality specific to the topics and techniques under discussion. This chapter serves a dual purpose. In addition to describing the basic framework of all the applications to follow in this book, it also introduces the basic ingredients of a complete Windows CE application. Experienced Win32 API programmers and MFC programmers alike will get something out of the presentation of this template application. For example, the Win32 programmer will benefit from seeing the differences in window styles and window messages between Windows CE and desktop Windows platforms. At the same time, MFC programmers will get a refresher on the underlying mechanics of the Windows programming model.
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64 Weber, S., Hoffmann, P., Ensling, J., Dedik, A.N., Weinbruch, S., Miehe, G., G tlich, P. and Ortner, u H.M. Characterization of iron compounds from urban and rural aerosol sources. Journal of Aerosol Science 2000; 31: 987 997. 65 Jickells, T.D. and Spokes, L.J. Atmospheric iron inputs to the oceans. In: D.R. Turner and K.A. Hunter, eds. The Biogeochemistry of Iron in Seawater. John Wiley, New York: 2001; pp. 85 121. 66 Kieber, R.J., Skrabal, S.A., Smith, C. and Willey, J.D. Redox speciation of copper in rainwater: temporal variability and atmospheric deposition. Environmental Science & Technology 2004; 38: 3587 3594. 67 Kieber, R.J., Hardison, D.R., Whitehead, R.F. and Willey, J.D. Fotochemical production of Fe(II) in rainwater. Environmental Science & Technology 2003; 37: 4610 4616. 68 Deutsch, F., Hoffmann, P. and Ortner, H.M. Analytical characterization of manganese in rainwater and snow samples. Fresenius Journal of Analytical Chemistry 1997; 357: 105 111. 69 Pehkonen, S.O., Erel, Y., Siefert, R.L., Klewicki, K., Hoffmann, M. and Morgan, J.J. The dynamic chemistry of transition metals in the troposphere. Israel Journal of Earth Sciences 1994; 43: 279 295. 70 Herrmann, H., Ervers, B., Jacobi, H.-W., Wolke, R., Nowacki, P. and Zellner, R. CAPRAM2.3: a chemical aqueous phase radical mechanism for tropospheric chemistry. Journal of Atmospheric Chemistry 2000; 36: 231 284. 71 Stumm, W. and Morgan, J.J. Aquatic Chemistry, 3rd edn. John Wiley, New York: 1996. 72 Bolt, G.H. and Bruggenwert, M.G.M. Soil Chemistry: A. Basic Elements. Elsevier, Amsterdam: 1978. 73 Faust, B.C. and Hoign , J. Photolysis of Fe(III)-hydroxy complexes as source of OH radicals in clouds, e fog and rain. Atmospheric Environment 1990; 24: 79 89. 74 Chebbi, A. and Carlier, P. Carboxylic acids in the troposphere, occurrence, sources, and sinks: a review. Atmospheric Environment 1996; 30: 4233 4249. 75 Kawamura, K., Steiberg, S., Ng, L. and Kaplan, I.R. Wet deposition of low molecular weight monoand di-carboxylic acids, aldehydes and inorganic species in Los Angeles. Atmospheric Environment 2001; 35: 3917 3926. 76 Zuo, Y. and Hoign , J. Formation of hydrogen peroxide and depletion of oxalic acid in atmospheric e water by photolysis of iron(III)-oxalato complexes.Environmental Science & Technology 1992; 26: 1014 1022. 77 Sedlak, D.L. and Hoign , J. The role of copper and oxalate in the redox cycling of iron in atmospheric e waters. Atmospheric Environment 1993; 27A: 2173 2185. 78 Hoign , J., Zuo, Y. and Nowell, L. Photochemical reactions in atmospheric waters; role of dissolved e iron species. In: G. Heltz, R. Zepp and D. Crosby, eds. Aquatic and Surface Photochemistry. Lewis Publishers, Inc., Michigan: 1994; pp. 75 84. 79 Faust, B.C. and Zepp, R.G. Photochemistry of aqueous iron(III)-polycarboxylate complexes: roles in the chemistry of atmospheric and surface waters. Environmental Science & Technology 1993; 27: 2517 2522. 80 Spokes, L.J., Campos, M.L.A.M. and Jickells, T.D. The role of organic matter in controlling copper speciation in precipitation. Atmospheric Environment 1996; 30: 3959 3966. 81 Nimmo, M., Fones, G.R. and Chester, R. Atmospheric deposition: a potential source of trace metal organic complexing ligands to the marine environment. Croatica Chemica Acta 1998; 71: 323 341. 82 Nimmo, M. and Fones, G.R. The potential pool of Co, Ni, Cu, Pb and Cd organic complexing ligands in coastal and urban rain waters. Atmospheric Environment 1997; 31: 693 702. 83 Graedel, T., Mandich, M.L. and Weschler, C.J. Kinetic studies of atmospheric droplet chemistry. 2. Homogeneous transition metal chemistry in raindrops. Journal of Geophysical Research 1986; 91: 5205 5221. 84 Leriche, M., Voisin, D., Chaumerliac, N., Monod, A. and Aumont, B. A model tropospheric multiphase chemistry: application to one cloudy event during the CIME experiment. Atmospheric Environment 2000; 34: 5015 5036. 85 Warneck, P. Chemistry and photochemistry in atmospheric water drops. Berichte der BunsenGesellschaft f r Physikalische Chemie 1992; 96: 454 460. u
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the mean running speed, a + d vs. b + c). This is known as state-dependent learning. In addition to distinguishing between learning and performance, transfer designs with multiple phases have been important for the assessment of what was learned in the rst phase (Rescorla, 1988). Repeated Measures Designs To reduce the effect of individual differences, many investigators typically use repeated measures designs. In a repeated measures design, each of the animals receives each of the conditions. Because of potential carryover effects, different animals receive the conditions in different orders. They may be counterbalanced or randomized. Other potential in uencing variables may also be counterbalanced or randomized. In some cases a mixed design may be used, which is a combination of an independent groups design and a repeated measures design. Single-Subject Designs Some investigators use what is sometimes called singlesubject design (Sidman, 1960). This requires that all of the treatments be given to a single animal. Typically, such research is replicated on two or three other animals to determine the generality of the conclusions. The assumption is that most animals produce similar results, so there is no need for larger samples. But there is also a concern about combining the results of multiple animals because the performance of each of the animals is different. This approach is particularly advocated by the Journal of the Experimental Analysis of Behavior. Although such experiments could be conducted with random ordering of treatments, xed criteria for each phase, and other features of standard experimental designs, the approach actively encourages the decisions of investigators based on the behavior of the animals. This approach is dif cult to distinguish from pilot studies that are often conducted in new situations. In a pilot study an investigator may use a small number of animals and a large number of treatments; the purpose is to develop hypotheses, not to produce convincing and interpretable data. Problems Common to All Experimental Designs There are some common problems for all experimental designs. These include the rationale for determining the number of animals per group, the number of trials in a phase, and the ways in which errors are handled. The number of animals in an experiment is usually based on several considerations. In the independent group designs,
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