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Table 4. Minneapolis and St. Paul River Crossing Bicycle Commute Share, 1990-2000

in 4. Title and Subtitle Optimization of Transportation Investment: Guidelines for Benefit-Cost Analysis of Bicycle Facilities: Refining methods for estimating the effect of bicycle infrastructure on use and property values
by Kristen Thompson, Author/s Gavin Poindexter, Kevin J. Krizek, Gary Barnes, Kristen Thompson 2007
"... In PAGE 8: ...able 3. Bicycle Commute Share in Buffer Analysis Areas, 1990-2000 ......................... 10 Table4 . Minneapolis and St.... ..."

Table 3.2: Comparison of Incentive-based Mechanisms (I) Schemes/Authors Yang [19] Paul [41] Frank [46]

in Strategic Pricing to Stimulate Node Cooperation
by Mingmei Li 2007

Table 8 Historical ban analysis in the Steels, Pauls and Dixons Creek system Ban Flow Number of winter-fill ban days

in unknown title
by unknown authors
"... In PAGE 23: ...nvironmental flow levels as described above. It should be noted that this period was particularly dry. Based on historical gauge data, an environmental flow of 5.0ML/day during these months from 1 July to 30 November would have resulted in the bans shown in Table8 below. The winter-fill period lasts for 152 days, so the table highlights the low reliability of supply in the catchments.... ..."

Table 3.4: Mulliken overlap populations calculated from PW pseudopotential calcula- tions, Mulliken and Pauling electronegativity di erences.

in An ab Initio Study of Biological Systems
by Matthew Segall, Matthew Segall

Table 2 #5B4#5D Paul W. K. Rothemund. A DNA and restriction enzyme implementation of Turing Machines.

in Error Correction in DNA Computing: Misclassification and Strand Loss
by Kevin Chen, Erik Winfree

Table 2: Comparison of kinematic constants. in degrees, A and D are in mm. Each is speci ed in terms of the coordinate frames of the cited paper. Param Armstrong Paul81 Tarn

in unknown title
by unknown authors 1994
"... In PAGE 2: ... 2 Comparison of kinematic parame- ters The kinematic models of the 11 sources must be considered to transform the inertial parameters into a single system of coordinates. Five sets of kinematic parameters are compared in Table2 . Each set of pa- rameters must be taken in the context of the axis and angle conventions in the cited paper.... ..."
Cited by 10

Table 4. Variance explained by first eight principal components of landscape or lake morphometry variables for 33 lake watersheds in Minneapolis-St. Paul metropolitan area (n = 38 site-year observations).

in Landscape Ecology vol. 8 no. 1 pp 39-61 (1993)
by Spb Academic Publishing, Naomi E. Detenbeck, Carol A. Johnston, Gerald J. Niemi
"... In PAGE 10: ...O. These eight principal components (PCs) explained 85% of the variance of the 27 original landscape variables ( Table4 ). The first six of these PCs, explaining 76.... ..."

Table 7. Significant correlations between lake water quality variables and water-quality principal components (WQPC) for 28 Min- neapolis/St. Paul metropolitan area sites represented in reduced data matrix (p lt; 0.05, p lt; 0.01).

in Landscape Ecology vol. 8 no. 1 pp 39-61 (1993)
by Spb Academic Publishing, Naomi E. Detenbeck, Carol A. Johnston, Gerald J. Niemi
"... In PAGE 13: ...lained 84.1 Yo of the variance. The first water qual- ity principal component (WQPCl) was related to lake trophic state and was highly correlated posi- tively with total P, total and organic N, and chlo- rophyll a, and negatively associated with Secchi depth (p lt; .05; Table7 ). Diamond and Cynthia Lakes, with high positive WQPCl values, were highly eutrophic (0.... In PAGE 13: ...-11 pg chl a.L- apos;, 3.1-3.2 m Secchi depth). The second PC (WQPC2) was significantly correlated with log NH,, while WQPC3 was significantly cor- related with log (NO, + NO,) ( Table7 ). In the fol- lowing text, WQPCl will be refered to as lake trophic state.... ..."

Table 9. Partial correlations (rp) between lake water-quality variables and original watershed variables for 33 lake watersheds in Minneapolis-St. Paul metropolitan area (n = 38 site-year observations).

in Landscape Ecology vol. 8 no. 1 pp 39-61 (1993)
by Spb Academic Publishing, Naomi E. Detenbeck, Carol A. Johnston, Gerald J. Niemi
"... In PAGE 14: ... and the negative correlation between trophic state and PC5 were explained by the influence of agricul- tural or forested land-use, topography, and wet- land position within the watershed. Lake trophic state was negatively correlated with forested land- use with other PC5-related variables held constant ( Table9 ). Trophic state was positively correlated with agricultural lake-fringe and maximum eleva- tion difference when the number of lakes upstream and wetland extent were held constant.... In PAGE 14: ... Trophic state was positively correlated with agricultural lake-fringe and maximum eleva- tion difference when the number of lakes upstream and wetland extent were held constant. Lake troph- ic state also was positively correlated with wetland distance upstream with other factors influencing PCl held constant ( Table9 ). Conversely, Iakes with proximal wetlands, i.... In PAGE 14: ... The relationship between lake total or organic N and PC2 also was explained by the influence of agricultural land-use. The partial correlation be- tween agricultural lake fringe and organic or total nitrogen was significant with other PCZrelated variables held constant ( Table9 ). Total and organic nitrogen were both negatively correlated with the forest/soils component (PC5) but the effect of original variables related to PC5 could not be sepa- rated through partial correlation analysis.... ..."

Table 4: Frequency of Mood Morphemes used by Paul and Soyen Age Total # M Basic Mood Morphemes Modality-involving Mood -e/a -ta -ci yo ya-tay l-lay kke-ya etc

in Complex Verb Constructions in Child Korean: Overt Markers of Covert Functional Structure
by Meesook Kim, Colin Phillips
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