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Potentiometry Conventional non-aqueous pH titrations are useful in detecting and determining acidic and basic impurities. On the other hand, the ion-prove method proposed by Coetzee et al. [9] is convenient in characterizing trace amounts of reactive impurities. The principle of the method was described in Section 6.3.5. In Fig. 10.4, the method is applied to reactive impurities in commercial acetonitrile products. The prove-ion and the ISE were Cd2+ and a Cd2+-selective electrode (CdS Ag2S solid membrane), respectively. The solid line TR is the theoretical relation expected when the ISE responds to Cd2+ in the Nernstian way. The total concentrations of impurities, which were reactive with Cd2+, were estimated to be 4 10 5 M, 8 10 6 M,
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These distributions are also used for g( ) in (5.32). The upper bound M was chosen so that log(M) = log L( |D) + , (5.37)
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realization that they were onto something that was important and perhaps even groundbreaking, they decided to make the move. Thus our two heroes had reached their point of departure and they crossed over from the academic into the business world. As they committed to this new direction, they realized they would need to postpone their educational aspirations, prepare plans for their business concept, develop a working demo of their commercial search product, and seek funding sponsorship from outside investors. Having made this decision, they managed to interest Sun Microsystems founder Andy Bechtolsheim in their idea. As Brin recalls, We met him very early one morning on the porch of a Stanford faculty member s home in Palo Alto. We gave him a quick demo. He had to run off somewhere, so he said, Instead of us discussing all the details, why don t I just write you a check It was made out to Google Inc. and was for $100,000. 7 The check remained in Page s desk uncashed for several weeks while he and Brin set up a corporation and sought additional money from family and friends almost $1 million in total. Having started the new company, lined up investor funding, and possessing a superb product, they realized ultimate success would require a good balance of perspiration as well as inspiration. Nevertheless, at this point Google appeared to be well on the road to success. Page and Brin have been on a roll every since, armed with the great con dence that they had both a superior product and an excellent vision for global information collection, storage, and retrieval. In addition, they believed that coordination and optimization of the entire hardware/software system was important, and so they developed their own Googleware technology by combining their custom software with appropriately integrated custom hardware, thereby fully leveraging their ingenious concept. Google Inc. opened its doors as a business entity in September 1998, operating out of modest facilities in a Menlo Park, California garage. As Page and Brin initiated their journey, they faced many challenges along the way. They matured in their understanding with the help of mentors they encountered such as Yahoo! s Dave Filo. Filo not only encouraged the two in the development of their search technology but also made business suggestions for their project. Following the company start-up, interest in Google grew rapidly. Red Hat, a Linux company, signed on as Google s rst commercial customer. Red Hat was particularly interested in Google because the company realized the importance of search technology and its ability to run on open source systems such as Linux. In addition, the press began to take notice of this new commercial venture and articles began to appear in the media highlighting the Google product that offered relevant search results. The late 1990s saw a spectacular growth in development of the technology industry, and Silicon Valley was awash with investor funding. The timing was
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MR brain scan showing changes in both temporal lobes due to oedema and haemorrhage in herpes simplex encephalitis.
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Figure 1.28 Typical approach to transaction processing
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tidsT (H) = {k D|H T (k)} for every E P(D) and every H P(I). Note that suppcountT (H) = |tidsT (H)| for every item set H P(I). The next statement shows that the mappings itemsT and tidsT form a Galois connection between the partial ordered sets P(D) and P(I) (see the works by Birkhoff [7] and Ganter and Wille [10] for this concept and related results). The use of Galois connections in data mining was initiated in the work by Pasquier et al. [15] and continued in the work by Zaki [19]. Theorem 4 1. 2. 3. 4. Let T : {1, . . . , n} P(I) be a transaction data set. We have
3 To compare and assess treatments that produce short-term bene t against those that produce bene t in the long term. 4 To ensure the most cost-effective use of health service funds. For example, hip replacement operations are said to be more cost-effective in QALY terminology than heart transplants. It was noted that studies at York University had come to the conclusion that heart transplants cost over 5000 per QALY compared with 1000 for coronary by-passes and 750 for hip replacements.96 Since health service funding is nite it was concluded that it is better to channel available funds into hip replacement operations. 5 To ensure the most bene cial distribution, in utilitarian terms, of any available scarce resource renal dialysis or a drug in short supply, for example. 6 To select for treatment those people who might be expected to produce the most QALYs. Such selection is reminiscent of the policy used by armies which treat rst of all those soldiers most likely to return quickly to the battle. 7 To make apparently re ective judgements merely a matter of calculation.
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