"... In PAGE 28: ... Reference points were established for Segment 7, but habitat data were not collected; temperature site M7 was located within this reach. Segments 1-3 were lower gradient areas moderately confined within a ravine ( Table9 ). Channel gradient in Segments 4 and 5 increased, with the stream channel becoming increasingly confined within the constricting ravine.... In PAGE 33: ...ravel. Segment 1 had a high percentage of fines (23.3%, Table 10). The lower percent of surface area in pool habitat, decreasing riffle area, and increasing cascade habitat observed in segments 4 and 5 (Table 10) is related to the higher gradient and increased channel confinement ( Table9 ). Pool characteristics (residual pool depth, pool frequency, pool type) were similar to other segments although side channel habitat types in segments 4 and 5 were absent (Table 10).... ..."

"... In PAGE 29: ... Siebert Creek i. Habitat conditions by segment Pool habitat was low ranging from 41% in segment 1 to 29% in segments 2 and 3 ( Table10 ). Segments 1 and 2 contained most of deeper pools, with about half of the pools having a residual depth between 0.... In PAGE 29: ...5m and 1.0m ( Table10 ). Segment 3 was mostly shallow pools with residual depths less than 0.... In PAGE 29: ...epths less than 0.5m. Large woody debris formed few pools in segment 3 but most were formed by flow or boulders (Table 10). The channel was generally a single thread channel with a minor percentage of secondary or side channel habitat ( Table10 ). Large diameter key pieces were observed at low levels in all segments1.... In PAGE 33: ... Habitat Conditions by Segment Habitat conditions within segments 1-3 are relatively similar with low pool surface areas (28%, 36%, and 33%), and small average residual pool depths lt; 0.5m ( Table10 ). Segment 1 had a lower channel gradient (1-2%) and contained a higher percentage of riffle habitat in contrast with segments 2 and 3 (with a channel gradient of 2-4%).... In PAGE 33: ...6%, and 33%), and small average residual pool depths lt; 0.5m (Table 10). Segment 1 had a lower channel gradient (1-2%) and contained a higher percentage of riffle habitat in contrast with segments 2 and 3 (with a channel gradient of 2-4%). Throughout segment 1-6, the channel was composed of a single thread (primary) channel ( Table10 ). Logjam frequency was highest in segments 4 and 5.... In PAGE 33: ... Riparian information was not collected on segment 1. Segments 2 and 3 data indicate a mature riparian forest ( Table10 ) with good canopy closure on segment 3 (Table 12). The landuse within Segments 1 and 2 was predominantly residential, while segment 3 was commercial timberland.... In PAGE 33: ... Segment 1 had a high percentage of fines (23.3%, Table10 ). The lower percent of surface area in pool habitat, decreasing riffle area, and increasing cascade habitat observed in segments 4 and 5 (Table 10) is related to the higher gradient and increased channel confinement (Table 9).... In PAGE 33: ...ravel. Segment 1 had a high percentage of fines (23.3%, Table 10). The lower percent of surface area in pool habitat, decreasing riffle area, and increasing cascade habitat observed in segments 4 and 5 ( Table10 ) is related to the higher gradient and increased channel confinement (Table 9). Pool characteristics (residual pool depth, pool frequency, pool type) were similar to other segments although side channel habitat types in segments 4 and 5 were absent (Table 10).... In PAGE 33: ...ravel. Segment 1 had a high percentage of fines (23.3%, Table 10). The lower percent of surface area in pool habitat, decreasing riffle area, and increasing cascade habitat observed in segments 4 and 5 (Table 10) is related to the higher gradient and increased channel confinement (Table 9). Pool characteristics (residual pool depth, pool frequency, pool type) were similar to other segments although side channel habitat types in segments 4 and 5 were absent ( Table10 ). LWD volume was lower than downstream in segments, indicating the lower retention of wood with increasing stream power created by the higher channel gradient.... In PAGE 33: ... Rotten conifer LWD was commonly found (Appendix A.) A higher percentage of pools were formed by bedrock and boulders in this segment in comparison to downstream segments with lower channel gradients ( Table10 ). The riparian forest is a mixture of coniferous and deciduous tree species in a dense young stand, with the surrounding land use in commercial timber land production.... In PAGE 49: ... Summer and Winter Rearing Conditions Low wood volume and logjam frequency in segments 1-2, along with high percentages of cascades result in low abundance and diminished quality of pool habitat. As a result, the quantity of summer rearing habitat and the quality winter rearing conditions for juvenile coho are low, and may favor cutthroat and steelhead ( Table10 ). McHenry (1992) reported low overall densities of juvenile fish (0.... In PAGE 51: ... Due to the low levels of large woody debris and the steeper channel gradient, bedrock and boulders primarily form pools. The large woody debris present tends to be in moderate or rotten condition, with a fairly high percentage (27%) constituting deciduous species ( Table10 , Appendix B). The low recruitment potential from the riparian zone indicates a situation that will only worsen as the existing wood continues to decay for Segment 5.... ..."

"... In PAGE 32: ... iv. Habitat quality ratings Habitat ratings of Siebert Creek for segments 1 through 3 characterize conditions as ranging from poor to fair ( Table12 ). The exceptions were for in-channel LWD persistence in segments 1 and 2 and canopy closure in segment 3 where the rating was good.... In PAGE 33: ... Riparian information was not collected on segment 1. Segments 2 and 3 data indicate a mature riparian forest (Table 10) with good canopy closure on segment 3 ( Table12 ). The landuse within Segments 1 and 2 was predominantly residential, while segment 3 was commercial timberland.... ..."

"... In PAGE 21: ... If a user network is requested the required processors are used to partition the network. Table2 shows results of partitioning graphs with 320 nodes. The cooling schedule is optimized according to running time.... In PAGE 21: ... The algorithm manages to partition every graph with #14 320 nodes into clusters of size 8 with #14 16 external edges after at most three trials. But as can be seen in Table2 most graphs are partitioned after the #0Crst trial. 8 Conclusions Wehave presented a framework for parallelizing SA on large distributed memory mul- tiprocessor systems.... ..."

"... In PAGE 22: ... If a user network is requested the required processors are used to partition the network. Table2 shows results of partitioning graphs with 320 nodes. The cooling schedule is optimized according to running time.... In PAGE 22: ... The algorithm manages to partition every graph with #14 320 nodes into clusters of size 8 with #14 16 external edges after at most three trials. But as can be seen in Table2 most graphs are partitioned after the #0Crst trial. 8 Conclusions Wehave presented a framework for parallelizing SA on large distributed memory mul- tiprocessor systems.... ..."

"... In PAGE 6: ... The results reported here for English and Czech are comparable to the previous best published num- bers in (McDonald et al., 2005a), as Table3 shows. This table compares McDonald et al.... ..."

"... In PAGE 3: ...able 4: Colors Featured in Logos and Packaging of Advertised Food Products...... 48 Table5 : Calorie Density and Sodium Content of McDonald apos;s Sandwiches and Other Foods .... ..."

"... In PAGE 7: ... In the first experiment, we test our system for processor scalability, using data from the A and B columns. Table2 shows the results of using our system to model either the A or B column, i.e.... In PAGE 8: ...Table2 , the system assigns a value of 1/3996971.35 for B1 and a value of 0.... In PAGE 8: ...72 P) + 0.085 We observe in Table2 that our predictions tend to be a bit low, though all predictions are well within a 10% deviation from the mean of the observations. While our predictions for Class A come very close, the mean of the observations does not fall within the 95% confidence or prediction intervals for the 14 and 16 node predictions.... ..."