"... In PAGE 8: ...uces a database -3.5 gigabytes in size. Property pattern searching using Collection objects is considered a strength of MOOSE. One result of this type of search is illustrated in Table5 which summarizes results from a solvent exposure search (Lee and Richards, 1971) performed across the complete PDB. The report indicates the distribution of buried residues with respect to various lengths of primary sequence.... ..."

"... In PAGE 27: ...0 HEALTH AND ENVIRONMENTAL EFFECTS 9.1 Health Effects Many of the solvents have much lower Permissible Exposure Limits (PELs) than CFC 113 ( Table3 ). This could cause problems with personnel working with the solvents while cleaning the LOX injection ring.... ..."

"... In PAGE 28: ...0 HEALTH AND ENVIRONMENTAL EFFECTS 9.1 Health Effects Many of the solvents have much lower Permissible Exposure Limits (PELs) than CFC 113 ( Table3 ). This could cause problems with personnel working with the solvents while cleaning the LOX injection ring.... ..."

"... In PAGE 8: ... The Ti/Ti lap shear specimens of MPEI-5 and MPEI-6 were exposed to aircraft fluids for 14 days according to the HSR Phase I screening test for secondary bonding adhesives. The results are summarized in Table5 . The material exhibited excellent solvent resistance; no significant effect on strengths was observed after soaking in the solvents for two weeks, with the possible exception of toluene soak on MPEI-6.... ..."

"... In PAGE 10: ... If the model is not informative, then none of the variables in the model can be informative. Table2 summarizes informative E-R models with 15% or more of the variance explained by the model, and stratified by the statistical significance of the exposure variable. Exposure variables are non-significant 4.... In PAGE 11: ...39 Another way to assess strength of association and the potential role of incompletely adjusted confounders is to compare the P values of both confounding and exposure variables when only the model R2 is available. Compar- isons shown in Table2 are indicative of the generally weak association of exposure relative to the stronger associations with non-solvent risk factors. In all the tests, where i?2^0.... ..."

"... In PAGE 12: ... 4. A numerical example The data in Table5 A arise from an experiment reported in Bishop and Dudewicz (1978) for studying the bacterial killing ability. The experiment involved testing four types of solvents for their e ects on the ability of a fungicide methyl-2-benzimidazole- carbamate to destroy the fungus Penicillium expansum.... In PAGE 13: ...Xi in (3) can be calculated after the additional Ni 15(i = 1; 2; 3; 4) observations taken at the second stage from solvent i. The summary statistics are given in Table5 C. In this example, ~ X = 97:55 (which came from solvent 4) and the 95% con dence interval for is given by (97:55 2:49p:115; 97:55 + 1:94p:115) = (96:71; 98:21) with interval width being 1.... In PAGE 14: ... Table5 B. Bacterial Killing Ability (Second-Stage Observations) Solvent 1 Solvent 2 Solvent 3 Solvent 4 98.... In PAGE 14: ...43 97.08 Table5 C. Summary Statistics: Statistic Solvent 1 Solvent 2 Solvent 3 Solvent 4 S2 i 2.... In PAGE 15: ... Because of shortage of enough sample data for the two-stage to work, one can, in this situation, apply the one-stage procedure (P 1) as described in this section. Use the rst stage n0 = 15 observations for initial estimation from each solvent to calculate S2 i (see rst row of Table5 C) and the remaining ones for use in the nal calculation. The coe cients Ui and Vi in (13) are, respectively,... ..."

"... In PAGE 12: ... 4. A numerical example The data in Table5 A arise from an experiment reported in Bishop and Dudewicz (1978) for studying the bacterial killing ability. The experiment involved testing four types of solvents for their e ects on the ability of a fungicide methyl-2-benzimidazole- carbamate to destroy the fungus Penicillium expansum.... In PAGE 13: ...Xi in (3) can be calculated after the additional Ni 15(i = 1; 2; 3; 4) observations taken at the second stage from solvent i. The summary statistics are given in Table5 C. In this example, ~ X = 97:55 (which came from solvent 4) and the 95% con dence interval for is given by (97:55 2:49p:115; 97:55 + 1:94p:115) = (96:71; 98:21) with interval width being 1.... In PAGE 14: ...Table5 A. Bacterial Killing Ability Example (First 15 Observations) Solvent 1 Solvent 2 Solvent 3 Solvent 4 96.... In PAGE 14: ... Table5 C. Summary Statistics: Statistic Solvent 1 Solvent 2 Solvent 3 Solvent 4 S2 i 2.... In PAGE 15: ... Because of shortage of enough sample data for the two-stage to work, one can, in this situation, apply the one-stage procedure (P 1) as described in this section. Use the rst stage n0 = 15 observations for initial estimation from each solvent to calculate S2 i (see rst row of Table5 C) and the remaining ones for use in the nal calculation. The coe cients Ui and Vi in (13) are, respectively,... ..."

"... In PAGE 28: ...5 In addition, basic physical property data were collected for each formulation. The optimum composition determined after evaluating test results for candidate formulations is presented in the rightmost column in Table1 . The structures of the solvent components are presented in Fig.... In PAGE 82: ... The twenty-six source volumes and the eighteen detector positions are identified in Figure 1. With the origin as indicated in Figure 1, the detector locations are shown in Table1 . The detectors are located at points where there was expected to be a local maximum in the dose-rate field.... In PAGE 84: ...69 Table1 . Coordinates for detector locations Detector Coordinates (cm) Detector X Y Z 1 76.... ..."