Model vs. experiment

Total Rates Standard Model vs. Experiment Bahcall-Pinsonneaull 2000... 

Figure 5 Density of TIPnP water models vs. experiment as a function of temperature at 1 atm...

Gu W, Carter RN, Yu PT, Gasteigta- HA (2007) Start/stop and local H2 starvation mechanisms of carbon corrosion model vs. experiment. ECS Trans ll(l) 963-973... 

Carpick, R.W., Enachescu, M., Ogletree, D.F. and Salmeron, M., Making, breaking, and sliding of nanometer-scale contacts. In Beltz, G.E., Selinger, R.L.B., Kim, K.-S. and Marder, M.P., (Eds.), Fracture and Ductile vs. Brittle Behavior-Theory, Modeling and Experiment. Materials Research Society, Warrendale, PA, 1999, pp. 93-103. 

The data analysis chosen by these authors departs from that used by Mogensen and others [17, 18], who fit each ID angular correlation curve to a set of Gaussian functions. The minimum number of Gaussians is used to achieve a good fit, and the width of each is optimized. The momentum components of each 7-ray spectrum are then interpreted in terms of annihilation of core vs. valence electrons without appeal to a preconceived chemical model. The experiment-theory connection can be made if one has an adequate wave function in hand, for then the Doppler profiles or angular correlation curves can be calculated and compared to those measured. 

These cyclopropane vs olefin enthalpy of formation differences do not increase monotonically with the number of substituents. Worse yet, differences are found to be of differing signs. That is, there is no obvious pattern for all of the enthalpies of the cyclopropanation reaction 3. Neglecting any enthalpic contribution from the CH2 or cyclopropanation reagent and considering only un-, mono- and di-substituted olefins and cyclopropanes, we find the enthalpy of reaction 3 is rather coarsely equal to (3 2) kJ moT per alkyl substituent We will now accept this 3 kJ moF per alkyl substituent for reaction 3, where we admit the absence of justification and motivation other than arithmetic and convenience. We are forced to tolerate discrepancies of a few kJmoT per substituent differences between our correlations/models and experiment of several kJmoT must be considered as acceptable for our analysis. ... 

The relationship between the collected data was described by plotting scores of relevant principal components of the PCA model vs. each other as shown in Fig. 5.11. These plots demonstrated that responses of the sensor film to different vapors were well-separated in the PCA space. By plotting PC 1 vs. PC 2, some drift effects were pronounced (Fig. 5.11a). However, the drift effect was removed by plotting PC 1 vs. PC 3 (Fig. 5.11b). The remaining response scatter in regions 1 and 2 of Fig. 5.11b was due to nonequilibrated sensor responses during the kinetic experiments. 

As discussed above, numerical tools now exist that make it possible to rigorously test whether chemical kinetic models and data are quantitatively consistent for many important cases. There is good reason to expect that the numerical methods will continue to improve rapidly, so that these quantitative models vs. data tests will become possible for ever more complex experiments. As discussed in Sections II and III, our capability to construct and solve complex simulations is also improving rapidly. 

For experiments 1—3, in which individual males were simultaneously presented with two models in a choice test, paired, within-subjects chi-square tests were used to compare the frequency of males that clasped female-scented vs. unscented models (Exp. s 1,2) or female-scented vs. male-scented models (Exp. 3 see Snedecor Cochran, 1989). Wil-coxon signed-ranks tests were used to compare the number of clasps per male of scented vs. unscented models. In experiments 4 and 5, chi-square tests were used to compare the frequency of males that clasped models in the different treatment groups. Mann-Whitney U-tests were used to compare the number of clasps per male in the different groups. An alpha level of p <. 05, one-tailed was required for statistical significance. 

L., Ganguly, B., Fuchs, B. (1998). The 1,3,5,7-tetraazadecalins structure, conformation, and stereoelectronics. Theory vs. experiment. Journal of Organic Chemistry, 63, 8850-8859. (b) Ritter, 1., Gleiter, R., Imgartinger, H., Oeser, T. (1997). Conformations of Azacyclodeca-3,8-diynes and l,6-Diazacyclodeca-3,8-diynes and the Generalized Anomeric Effect A Test for Current Conformational Models for Azaheterocycles. Journal of the American Chemical Society, 119, 10599-10607. 

A limitation of the theory is that it is not useful for direct data manipulation. Even so, the ccxnparlson of modeled vs. measured results can strongly influence the interpretation of nonthermal experiments. 

How can we confirm this sacrificial promoter model By simply looking at the r vs t transient behaviour of Figure 4.13 or of any galvanostatic NEMCA experiment upon current interruption (1=0). 

Expert opinion is a source, frequently elicited by survey, that is used to obtain information where no or few data are available. For example, in our experience with a multicountry evaluation of health care resource utilization in atrial fibrillation, very few country-specific published data were available on this subject. Thus the decision-analytic model was supplemented with data from a physician expert panel survey to determine initial management approach (rate control vs. cardioversion) first-, second-, and third-line agents doses and durations of therapy type and frequency of studies that would be performed to initiate and monitor therapy type and frequency of adverse events, by body system and the resources used to manage them place of treatment and adverse consequences of lack of atrial fibrillation control and cost of these consequences, for example, stroke, congestive heart failure. This method may also be used in testing the robustness of the analysis [30]. 

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