### Table 16 Locomotive Groups for Current Fleet

2004

"... In PAGE 28: ... The number following the initial YS or LH designation is based on an ordering of the locomotives in order of increasing rated horsepower. The initial data columns in Table16 show the individual locomotive designations that were included in each group, the total of number of locomotives in the group, the rated power of individual locomotives in the group, and the total rated power of all locomotives in the group. In several cases the individual locomotives in the group had slightly different power ratings.... In PAGE 30: ... Despite these limitations, it is important to remember that for purposes of computing average emission rates, it is only the fraction of each locomotive type that is required. The emissions data reference column in Table16 is an abbreviation that is used in Tables 17 and 18 to present the emissions data and is used in Table 19 to provide the specific reference to the data and any additional adjustments that were done to the emissions data. The final three columns in Table 16 show the cycle average power and the percent of the total fleet power represented by the locomotive groups.... In PAGE 30: ... The emissions data reference column in Table 16 is an abbreviation that is used in Tables 17 and 18 to present the emissions data and is used in Table 19 to provide the specific reference to the data and any additional adjustments that were done to the emissions data. The final three columns in Table16 show the cycle average power and the percent of the total fleet power represented by the locomotive groups. Two different measures of the relative power were used: the percent of the rated power and the percent of the cycle average power.... In PAGE 30: ... The latter is based on the average power requirement during the appropriate EPA cycle. The cycle power in Table16 is based on the line-haul cycle for line-haul locomotives and on the yard/switch cycle for locomotives used for the yard service distribution. As noted later, the use of these two different distributions made a negligible difference on the fleet average emission factors.... ..."

### TABLE1 Partial correlations of human datawith contingency measures

### Table 1. Biological Concepts of Legged Locomotion Control

"... In PAGE 2: ... 2. Adaptive Dynamic Walking based on Biological Concepts Methods for legged locomotion control are classified into zero moment point (ZMP) based control and limit-cycle-based control ( Table1 ). ZMP is the extension of the center of grav- ity considering inertia force and so on.... ..."

### Table 1. Biological Concepts of Legged Locomotion Control

"... In PAGE 3: ... 2. Adaptive Dynamic Walking based on Biological Concepts Methods for legged locomotion control are classified into zero moment point (ZMP) based control and limit-cycle-based control ( Table1 ). ZMP is the extension of the center of grav- ity considering inertia force and so on.... ..."

### Table 3. Time, space and number of errors measurements. Rep. Err. is the number of errors re- ported by the analysis, and Act. Err. is the number of errors that indicate real problems. Time and space measurements for non-terminating benchmarks are prefixed with gt; to indicate the mea- surements taken when the analysis timed out. The number of reported errors is the same for both the analysis based on the powerset heap abstraction and the analysis based on partial-isomorphism heap abstraction on all (terminating) benchmarks. For benchmarks that did not terminate with the powerset heap abstraction, the numbers are taken from the analysis based on partial-isomorphism heap abstraction

2004

"... In PAGE 10: ... We compared partial isomorphism to the full powerset abstraction in terms of time and space performance and precision. The results of the analyses are shown in Table3 . In all the benchmarks the analysis based on the partial-isomorphism heap abstraction achieved the same precision as the analysis based on the powerset heap abstraction, and other TVLA users reported the same phenomena.... In PAGE 12: ...Implementation Independent Results Although the results shown in Table3 measure the time and space consumption of anal- yses using different abstractions, they are also influenced by the various implementation details of the abstractions. In Table 4, we supply implementation independent measurements.... ..."

Cited by 15

### Table 3. Time, space and number of errors measurements. Rep. Err. is the number of errors re- ported by the analysis, and Act. Err. is the number of errors that indicate real problems. Time and space measurements for non-terminating benchmarks are prefixed with gt; to indicate the mea- surements taken when the analysis timed out. The number of reported errors is the same for both the analysis based on the powerset heap abstraction and the analysis based on partial-isomorphism heap abstraction on all (terminating) benchmarks. For benchmarks that did not terminate with the powerset heap abstraction, the numbers are taken from the analysis based on partial-isomorphism heap abstraction

2004

"... In PAGE 10: ... We compared partial isomorphism to the full powerset abstraction in terms of time and space performance and precision. The results of the analyses are shown in Table3 . In all the benchmarks the analysis based on the partial-isomorphism heap abstraction achieved the same precision as the analysis based on the powerset heap abstraction, and other TVLA users reported the same phenomena.... In PAGE 12: ...Implementation Independent Results Although the results shown in Table3 measure the time and space consumption of analyses using different abstractions, they are also influenced by the various implemen- tation details of the abstractions. In Table 4, we supply implementation independent measurements.... ..."

Cited by 15

### Table 3. Time, space and number of errors measurements. Rep. Err. is the number of errors re- ported by the analysis, and Act. Err. is the number of errors that indicate real problems. Time and space measurements for non-terminating benchmarks are prefixed with gt; to indicate the mea- surements taken when the analysis timed out. The number of reported errors is the same for both the analysis based on the powerset heap abstraction and the analysis based on partial-isomorphism heap abstraction on all (terminating) benchmarks. For benchmarks that did not terminate with the powerset heap abstraction, the numbers are taken from the analysis based on partial-isomorphism heap abstraction

"... In PAGE 10: ... We compared partial isomorphism to the full powerset abstraction in terms of time and space performance and precision. The results of the analyses are shown in Table3 . In all the benchmarks the analysis based on the partial-isomorphism heap abstraction achieved the same precision as the analysis based on the powerset heap abstraction, and other TVLA users reported the same phenomena.... In PAGE 12: ...Implementation Independent Results Although the results shown in Table3 measure the time and space consumption of anal- yses using different abstractions, they are also influenced by the various implementation details of the abstractions. In Table 4, we supply implementation independent measurements.... ..."

### Table 2 Kimura 2-parameter distances expressed as percentage base substitutions for selected parts of the dataset

1998

"... In PAGE 7: ... This apparent contradiction is true because the unknowns we encountered and tested turned out to be members of groups that were well sampled and strongly supported by phylogenetic analyses. The strong support is due to the fact that very few sequence differences occur within most major mycorrhizal lineages sampled, while sequence variation between these groups and other taxa is moder- ate to large ( Table2 ). Indeed, many closely related species and genera have identical or nearly identical sequences in this region.... In PAGE 12: ... To access internal confidence we have used bootstrap analysis (Felsenstein 1985), but this may not be necessary to use each time a new unknown is ana- lysed. From the analyses we report here it seems safe to say that placements of unknowns will be strongly sup- ported within any of the groups listed in Table2 if their sequence differences from other members of the group fall within the range listed. The suilloid group is a minor exception; placements into this group are likely to be only moderately supported by bootstrap but, as discussed above, are very likely to be correct.... ..."

Cited by 3

### Table 3. Ordinal Logit Model Estimating Quota Liberalization Dependent variable: 0=no change, 1=partial change, 2=major change Variable Estimate S.E. (z statistic)

"... In PAGE 18: ... However, the data which I have presented in this paper are insufficient to make any firm conclusions about the relationship between LDP strength and agriculture liberalization. Fit of the model At least as a first cut in the analysis, the overall model from Table3 provides considerable leverage for explaining the variation in liberalization outcomes. The independent variables improve prediction for liberalization scale outcomes by 77 percent over that which one would guess based on only the marginal distributions in a classification table.... ..."

### Table 3. Summary of ANOVAs with Factors Condition and Time for the First and Second Level Analysis of the Theta Effecta

"... In PAGE 7: ...vs. second) calculated for the mid-frontal ROI (see Table3 for F and p values as well as for effect size measures partial eta squared Z2 p and omega squared o2). Furthermore, theta power increased significantly toward the end of the musical pieces of both categories as statistically confirmed by a significant main effect of Time.... In PAGE 7: ... In this second level analysis, theta power increased only during the second half of pleasant pieces compared to base- line and remained unchanged in the course of unpleasant ex- cerpts. This was statistically supported by a significant two-way interaction (see Table3 ) in an ANOVA with factors Condition (pleasant vs. unpleasant) and Time (first vs.... ..."