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It is indeed a great pleasure to contribute a chapter to this Handbook honoring the work of my old friend Ted Millon, whom I have known since the 1950s, when we were both on the faculty of Lehigh University, where I taught philosophy with emphasis on the philosophy of science. Classical long-term psychoanalytic treatment has fallen on hard times in the United States. But the membership of Division 39 of the American Psychological Association (APA), which is concerned with psychoanalytic psychology, is quite active, and so-called psychoanalytically oriented psychotherapy of shorter duration still needs to be reckoned with in this country. Indeed, I venture to claim that some key Freudian notions remain quite influential in psychotherapeutic practice, though sometimes unbeknown to both the practitioners and their patients. In my essay Critique of Psychoanalysis, which first appeared in the 2002 Freud Encyclopedia (edited by Edward Erwin), I have distilled from my writings a systematic critique of the fundamental hypotheses of the psychoanalytic enterprise, both theoretical and therapeutic, employing a philosophy of science perspective.



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When designing any database, it is always a good idea to first design the database schema. The database schema is the description of the database and the kinds of information it contains. In our example, this simply means describing what properties each of the phone list records will contain, including the data type of each of the properties. If applicable, you would also define the acceptable range of values that each record property can be assigned. In traditional relational database design, the schema would be more complex, including descriptions of the various relational tables that make up the database. Taking the time up front to do this design step can save you from rewriting the database definition and management code in your applications because you overlooked an important piece of information required by your application. The phone list database consists of records that contain these four properties: employee last name, first name, phone number, and department number (Table 7.1). We will allow users of the phone list application to sort the records in the phone list on any of these four properties. PROPERTY Last Name First Name Phone Number Department Number Table 7.1 Phone List Database Record Definition DATA TYPE LPWSTR LPWSTR LPWSTR short





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Essential Windows CE Application Programming by Robert Burdick Wiley Computer Publishing, John Wiley & Sons, Inc. ISBN: 0471327476 Pub Date: 03/01/99

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Obviously, for low- ow conditions which are likely to be sustained solely by groundwater discharge, it is the tail-end of the ow duration curve which is of primary interest. The most common index of low ows derived from scrutiny of ow duration curves is the so-called Q95 value, which is simply the ow equalled or exceeded 95% of the time. The popularity of Q95 as a low- ow index lies in the fact that most ow duration curves will be supported by a suf cient spread of data points to allow accurate reading of Q95, whereas higher percentile values (Q97, Q99 etc) will be far less accurately de ned. If it desired to compare the base ow characteristics of one catchment with another, it will normally be best to prepare an area-normalized ow duration curve. This is achieved simply by dividing all ow records by the catchment area before preparing the cumulative frequency curve, so that the ow rate axis of the resultant ow duration plot will be in units of m3/s per km catchment area or similar. A further useful comparator statistic, which is useful for comparing the degree of groundwater dominance of stream runoff regime between catchments, is to calculate the ratio of Q25/Q75. Low values of this ratio (i.e. 1 < Q25/Q75 2) are typical of very

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