### Table 11 Phase space and parameter coordinates for three selected points along the Hopf curve for the LP equation. Also shown is the complete spectrum for each selected point. 1 2 3 4

1996

"... In PAGE 21: ... The Hopf branch arises at a Takens- Bogdanov point and leaves the parameter regime of physiological interest. Table11 shows parameter coordinates for four selected points along the Hopf branch described above. Also listed are values for the phase space variables and the com- plete spectrum.... In PAGE 25: ... Notice that each column may be adjusted independently, so if m gt; gt; (n ? m) and n is of moderate size, this step can be performed in parallel. Numerical continuation was begun at selected point 2 of Table11 using gNa as the continuation parameter, and proceeded toward the Takens-Bogdanov point at the beginning of the branch (near point 1). The 7-dimensional de ating subspace of Table 12 was used and updated at each corrector step.... ..."

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### Table 1 Spectrum of sizes for maximal partial ovoids of W (q), for small values of q. For q = 2; 3; 4; 5, the complete spectrum was obtained by exhaustive search. For larger values of q, the results are obtained by heuristic search. For q = 5; 7, the size of the largest partial ovoid was determined by exhaustive search.

"... In PAGE 8: ... 4.1 Maximal partial ovoids in W (q) In Table1 , we give results for maximal partial ovoids in W (q). For each value of q, we list the sizes for which the heuristic search found maximal partial ovoids of that given size.... In PAGE 8: ... Note that the largest value found for W (5) and W (7) is indeed the size of the largest maximal partial ovoid { this was conflrmed by exhaustive search. The results in Table1 conflrm the result from Theorem 2.1 that the smallest maximal partial ovoids have size q + 1.... ..."

### Table 2. Statistical results on the quality of the generated tags. No. of tags per spectrum shows the average number of tags generated per spectrum. No. of complete correct per spectrum measures the average number of tags identified that are completely correct (i.e. identified with 100% precision). Complete correct accuracy is the ratio of completely correct tags to number of tags on average. The recall and precision results are obtained from tags by the GST-SPC algorithm.

in AN ACCURATE AND EFFICIENT ALGORITHM FOR PEPTIDE AND PTM IDENTIFICATION BY TANDEM MASS SPECTROMETRY

"... In PAGE 7: ... We measured the ratio of completely correct tags in the results, as well as recall and precision of the tags. Results are shown in Table2 . Note that we had only analyzed the quality of tags on ISB spectra in our previous study [11].... In PAGE 7: ...SB 995 19.37 6.19 4.61 0.74 0.36 0.32 From Table2 , we observed that more than 1/3 of the amino acids in real peptide sequences (recall) can be correctly identified by tags. Also, when the tags are generated, more than 70% of the tags are completely correct, meaning that the tags generated are reliable.... In PAGE 8: ... This is reasonable since de novo algorithms do not utilize any information from databases. But even when comparing their results with the quality of tags generated by our algorithm ( Table2 ), we notice that the quality of tags generated by our algorithm is better than peptide identification results by Lutefisk, and comparable with that by PepNovo. Although InsPecT has higher precision, our results outperform InsPecT in recall.... ..."

### Table 2. The concordance of focal localization with chaotic analysis compared with power spectrum, MRI and SPECT. complete partial complete concordance concordance discordance total chaos and spectrum 11(34%) 11(34%) 10(32%) 32

"... In PAGE 4: ... All of the 28 patients taking SPECT examination showed hypoperfusion in either unilateral (12 patients on left, and 10 on right) or bilateral (6 patients) temporal lobes. The chaotic analysis agreed with power spectrum, MRI and SPECT completely or partially in 22(68%), 20(74%) and 20(71%) patients, respectively(See Table2... ..."

### Table 2 Spectrum of sizes for maximal partial ovoids of Q(4; q), for small values of q. For q = 3; 5, the complete spectrum was obtained by exhaustive search. For larger values of q, the results are obtained by heuristic search. For q = 7; 9, the non-existence of maximal partial ovoids of certain sizes was conflrmed by exhaustive search.

"... In PAGE 10: ... 4.2 Maximal partial ovoids in Q(4; q), q odd In Table2 , we give results for maximal partial ovoids in Q(4; q), q odd. For each value of q, we list the value of the lower bound (LB) from Theorem 3.... ..."

### Table 2. A spectrum of refinement planners

"... In PAGE 43: ... Step 3 in the algorithm splits a planset into k components. Depending upon the value of k, as well as the type of refinement strategy selected in step 2, we can get a spectrum of refinement planners, as shown in Table2 . In particular, the traditional refinement planners that do complete splitting can be modeld by choosing k to be equal to the number of components of the planset.... ..."

### Table 4. Revised KM Spectrum and Applications

2003

"... In PAGE 11: ... Since asset improvement is normally done using computer-based statistical techniques, but does not transform the asset into a different form, it belongs to the left of Asset Management but to the right of Analytical KM in the spectrum. On the basis of this, we suggest a revised version of the KM spectrum ( Table4 ). We also suggest revisions to Table 2 and Table 3, which are presented in list form below.... In PAGE 13: ... The implications of this are various: we see that Binney has not tried to develop any new knowledge about KM approaches, but has simply analysed existing ones. This might imply that there are more KM approaches waiting to be identified or developed; however, the fact that one or other of the approaches covers nearly all the KM approaches identified in Section 2 suggests that the set of approaches in the KM spectrum (or at least, in the revised spectrum shown in Table4 ) is nearly or fully complete. We also see that the applications, technologies, and mappings to knowledge management strategies identified in Tables 2-4 are crucial to the task of selecting an appropriate KM strategy.... ..."

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### Table 3. Decomposition of the spectrum obtained on the HYMAP dataset with the Polyline Algorithm.

"... In PAGE 8: ...uite stable between runs. The most common partition is indicated in Table 3. Completely adapted to the physionomy of the signatures, this decomposition seems very helpful for the purpose of interpretation. The hierarchy constructed for the partition of spectrum given in Table3 is presented in Figure 3 and the... ..."

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### Table 3. Decomposition of the spectrum obtained on the HYMAP dataset with the Polyline Algorithm.

"... In PAGE 8: ...uite stable between runs. The most common partition is indicated in Table 3. Completely adapted to the physionomy of the signatures, this decomposition seems very helpful for the purpose of interpretation. The hierarchy constructed for the partition of spectrum given in Table3 is presented in Figure 3 and the... ..."

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