### Table 1 Properties of QIN at each iteration

2007

"... In PAGE 9: ...hen the BM appear to be i.i.d. normal. Table1 illustrates how sampling progresses from iteration to iteration. The Iteration row lists the index of the iteration.... ..."

### Table 1. Properties of QIN at each iteration

2007

"... In PAGE 5: ...M appear to be i.i.d. normal. Table1 illustrates how sam- pling progresses from iteration to iteration. The Iteration row lists the index of the iteration.... ..."

### Table 2: Coverage probabilities and corresponding average lengths of 95% (shown beneath) CI for AUC obtained by BB and other nonparametric methods based on our simulation and the information contained in Qin and Zhou [19]. Our simulation results are based on 10000 simulated data sets and corresponding 1000 resamples. The grid points on [0,1] is chosen with equal interval length 0.005, (m, n) = (50, 50).

"... In PAGE 11: ... We will compare the performance of our BB estimator with these estimators. From simulation results (see Table2 ), we can see BB estimator performs well, especially, the BB intervals tend to be shorter. [Insert Table 2 here] 5 Real data analyses We shall illustrate the BB method to construct credible band of curve estimate and credible interval for AUC estimate using the data set published by Wieand et al.... In PAGE 11: ... From simulation results (see Table 2), we can see BB estimator performs well, especially, the BB intervals tend to be shorter. [Insert Table2 here] 5 Real data analyses We shall illustrate the BB method to construct credible band of curve estimate and credible interval for AUC estimate using the data set published by Wieand et al. [31].... ..."

### Table 1 Parameters and the Quality of the BOLD Function Prediction

"... In PAGE 20: ... This requires estimating parameters a, s, and M that reflect the characteristics of the BOLD function in the particular region. Table1 reproduces those parameter estimates from Qin et al. (2003).... ..."

### Table 2: Recursion for the calculation of base pair probability: Calligraphic symbols denote energy parameters for di erent loop types: hairpin loops H(ij), inte- rior loops, bulges, and stacks I(i; j; k; l); the multi-loop energy is modeled by the linear ansatz M = MC +MI degree+MB unpaired, e.g. (Zuker amp; Sanko 1984). The quan- tities QB ij, QM ij ; Q1;j and Qi;n were calculated in section 5.1 and have to be stored for the backtracking. The base pair (i; j) can be the closing pair of a hairpin, it may close an interior loop (or extend a stack), or it might close a multi-loop. The auxiliary variables PM and PM1 are necessary for handling multi-loops (McCaskill 1990), Restricting the size of interior loops to umax, equ. (25) helps reducing the CPU requirements to O(n3). The rst term, Pcomponent hl

1997

### Table 2. Solar Array Power Calculations in SINDA Logic HEADER ARRAY DATA, ROVER C TEMPERATURE DEPENDENCE OF SOLAR ARRAY POWER GENERATION C IN DEGREES C AND % (FRACTION) EFFICIENCY 200 = 28., 0.18, 120., 0.143

in SUMMARY

"... In PAGE 13: ... Table2 . Solar Array Power Calculations (con apos;t) HEADER OUTPUT CALLS,ROVER C C CALCULATE POWER GENERATION IN SOLAR ARRAYS C Qgen = Qin * 80% area / alpha Q in already in W C Qreal = Qgen * % EFFICIENCY C XK301 = Q301 * 0.... ..."

### Table 1 shows the cases for which the mathematical model was evaluated:

"... In PAGE 15: ...8 0.9 1 time time time cumula tive pr obability cumula tive pr obability cumula tive pr obability Figure 7: Cumulative RTD function for cases 1 to 3 in Table1 , showing the e ects of the through ow (Qin/A) and bubbling intensity (U-Umf) . and an out ow tQW (x + x).... In PAGE 15: ... Table1 : List of cases for which the mathematical model was evaluated. The rst three cases are ctive, chosen to test the qualitative variation of the predicted RTD-... In PAGE 17: ...5 1 1.5 Intensity curve P2 time time time intensity intensity intensity Figure 9: Intensity curves for cases 4 to 9 in Table1 . The curves for cases 6, 8 and 9 exhibit a local maximum.... ..."

### Table 1. Overview of presented operational strategies.

"... In PAGE 8: ... The selected reference case is the following strategy (standard nomenclature, Rx = AS reactor no x): Qw = 210 m3/d (constant, from settler), Qintr = 60000 m3/d (constant, from R5 to R1), Qr = Qin (proportional, into R1), Qcarb = 1 m3/d (constant into R1, COD source of 400000 mg/l), no bypassing or step feed, no use of reject water storage tank (direct flow through), thickener effluent and reject water return to primary clarifier, aeration control based on a DO sensor in R4 (set point 2 mg/l) and identical KLa input into R3 and R5. In Table1 , only the differences in comparison with the reference case are given for the other test cases. Table 1.... ..."

### Table 1. SED intensity factors versus mesh refinement

1999

"... In PAGE 6: ...f each crack. In Fig. 5 the coefficients of SED intensity factors bi at point A (see Fig. 4) are presented as a function of crack orientation angle a for N 40, where bi are de- fined by (Qin, 1998) KI A h0cc33b1 a pc p =k KIII A h0cc11b2 a pc p =k 70 KD A h0cv3bD a pc p =k with c11 c33 v3 8 lt; : 9 = ; C1111 C1133 e311 C1133 C3333 e333 e311 e333 j33 2 4 3 5 a11 a33 k3 8 lt; : 9 = ; 71 Table1 shows the results of SED intensity factors at point A versus mesh refinement for a 0. However, the nu- merical results for such a problem have not been available in the literature yet.... In PAGE 7: ...Table1 shows that the results of SED intensity factors from both BEM and FEM can con- verge to a particular value along with the mesh refinement. It is found from Fig.... ..."

Cited by 3

### Table 3. Resultsa for C13-proteobacterial data sets (real data)

2007

"... In PAGE 6: ..., 2003) to a maximum width of 24 positions. Table3 summarizes the results of the phylogenetic Gibbs sampler centroid alignments for the study set data, averaged over three runs for each of the three configurations (one, two or three motif models). These results are consistent with the results obtained from simulated data, based on a calculation of the weighted average of the PPV (0.... In PAGE 8: ...inds (Jensen et al., 2005; Qin et al., 2003). Our application of the phylogenetic Gibbs sampler centroid algorithm to 72 real C13-proteobacterial promoter sequences, with each promoter analyzed individually using only the orthologous data, showed results consistent with the results from the earlier simulations: PPVs 4 75%, and sensitivities 4 45% ( Table3 ). However, one difficulty in evaluating results from these data is that some promoters have regulatory sites that have not yet been discovered or experimentally validated, and thus some of the apparent false positives may actually be unreported genuine sites.... ..."