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ESD: RF Technology and Circuits Steven H. Voldman # 2006 John Wiley & Sons, Ltd
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Figure 7-2. This room is equipped with such amenities as a computer and in-room fax to facilitate the business guest s stay. (Photo courtesy of Westin Hotels and Resorts.)
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Sulphur levels were found to be lower in the high Arctic than at the South Pole [86]. Nonsea-salt S was found to be predominantly associated with the ne size fraction, with a median concentration over the pack ice of 25 ng m 3 . NSS sulphur originates from biogenic processes in the Arctic sea, and from anthropogenic sources further south. Their predominance in the ne size fraction indicates a formation from gaseous precursors by gas-to-particle conversion. The ne fraction concentrations of S and sea-salt elements in the open ocean were about ve to ten times larger than for the high Arctic samples. Staebler and co-workers [92] observed ne-mode inorganic aerosol compounds in Ny Alesund to be composed of slightly ammoniated sulphuric acid, which is equivalent to an equal mixture of H2 SO4 and NH4 HSO4 , when the source area was Eurasia. When the air arrived from central northern Russia, NH+ was virtually absent. NSS sulphate was present 4 with 2000 ng m 3 at this station during the AGASP experiment in spring 1989 [93].
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Figure 14-7. Minutes from a safety meeting keep participants on track.
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It applies an extension of conventional vector quantization (VQ) [18] by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental online learning. Plasticity is the ability to adapt to new information, whereas stability is the ability to converge to an optimal solution. This is motivated in the adaptive resonance theory network (ART) approach [11] and is exploited for forming a one-pass incremental and evolving clustering process, called evolving vector quantization (eVQ) [40]. When doing so, it connects a cluster evolution condition and an alternative distance strategy for samplewise winner selection, which is based on the distance calculation to the surface rather than to the centers (as done in conventional VQ). Hence the surface is calculated incrementally synchronously to the centers. Each cluster stands for one rule and the clusters are projected onto the axes in order to form the Gaussian fuzzy sets and the antecedent parts of the rules. It uses recursive local learning by exploiting recursive weighted least squares [39] for the linear consequent parameters in a fuzzy basis function network introduced in [61], that is, a Takagi-Sugeno fuzzy system with Gaussian fuzzy sets and product t-norm as conjunction operator, in the case of C rules de ned as: ^fuz ~ ^fuz y f x
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Figure 10-1
effects of dopamine in mediating CPP induced by other drugs of abuse such as cocaine, amphetamine, and morphine (Hoffman, 1989; Schechter & Calcagnetti, 1993). Various aspects of validity as related to the PC paradigm are summarized in Table 7.1. Preclinical Genetic Models: Insights into Individual Differences in Nicotine-Induced Behavior Animal studies using inbred strains have indicated that there are potential strain differences providing some insight as to why there are individual differences in the development of nicotine addiction in humans. Indeed, when inbred strains of mice are provided with a choice of nicotine or vehicle solutions, the strains differ dramatically in their self-selection of nicotine (Crawley et al., 1997; Meliska, Bartke, McGlacken, & Jensen, 1995; S. Robinson, Marks, & Collins, 1996). Across the different strains, the higher the preference for the nicotine solution, the lower the sensitivity to nicotine-induced seizures (S. Robinson et al., 1996). Thus, the negative toxic actions of nicotine limit nicotine consumption in mice. There are also differences in SA of nicotine by inbred strains of mice, where nicotine can serve as a positive reinforcer in c75BL/6 mice but not in DBA/2 mice (Stolerman et al., 1999). Genetically altered mice with certain targeted gene mutations are also becoming important tools in studying the molecular nature of nicotine addiction (Mohammed, 2000; Picciotto et al., 1998). These knock out mice are mutant mice lacking genetic information encoding speci c nACHR subunits. Because the 2 subunit is widely expressed in the central nervous system and is found in the mesocorticolimbic dopamine system, the reinforcing effects of nicotine have been examined in 2-knockout mice (Picciotto et al., 1998). Picciotto et al. (1998) report that nicotine-induced dopamine release in the ventral striatum is only observed in wild-type mice and not in 2-knockout mice. Furthermore, mesencephalic dopamine neurons are no longer responsive in 2-knockout mice. Similar to their wild-type counterparts, 2-knockout mice learned to self-administer cocaine. However, when nicotine was substituted for cocaine, nicotine SA was attenuated in the 2-knockout mice relative to wildtypes. These ndings suggest that the 2 receptor subtype plays a crucial role in the reinforcing effects of nicotine. Studies using mutant mice provide some insight as to individual differences in tobacco smoking. For example, different expression of nACHR subtypes (i.e., by knocking out various nACHR subunits in animals) can partially account for differences in nicotine effects. Although genetic knockout mice are a powerful tool, research using this technique has not yet reached its full potential. Thus far, the gene of
Year 0004 Amount $29,400 11,208 6,882 2,000 14,700 14,900 $79,090 Percent 37.2% 14.2 8.7 2.5 18.6 18.8 100%
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