Graphical representation of results

A series of runs was made to study the ozonation of cyanide under a variety of conditions. Figures 2 to 5 are graphical representations of results from runs 55 to 83. 

Fig. 9 Graphical representation of results from a nanoindentation experiment. For many solids, an elastic regime at low loads is followed by a discontinuous excursion. For amorphous alloys, a series of staircase deformations occur in response to shear banding.

Figure 6.B.I Graphical representation of results of dry bulk density versus water content at compaction.

Graphic representation of results of simulation experiments will allow understanding of the incidence of failures of individual elements in the range corresponding drawdown of operating units. Parallel equivalent elements are shown graphically. 

GRAPHICAL REPRESENTATION OF RESULTS 8.4.1 Bode plots vs complex plane diagrams... 

Graphical Representation of Results.—The progress of the separation is well seen by mapping the temperatures against the percentage weights of distillate collected, and the curves for the first twelve fractionations are shown in Fig. 28 (a and h). The horizontal lines at the extremities of the later curves represent the methyl and propyl acetates removed in the first portion of the first distillates and in the residues respectively. The presence of ethyl acetate is clearly indicated in the fourth curve but not in the earlier ones. 

In an absorbing medium the wave vector k, the dielectric constant , as well as transmission factors and those arising from boundary conditions are complex (cf. Eqs. (13)-(15)) Thus the graphical representation of resultant harmonic field (cf. Fig. 9) has to be modified in the following manner (cf. Fig. 10). The AM is replace by A M with... 

A siynthestis tree is the graphical representation of the result of a retrosynthetic analysis. The target compound (T) is set to the top of a tree that is turned upside down (Figure 10..3-3.3). 

The process and instrumentation (P I) diagram provides a graphical representation of the control configuration for the process. The P I diagrams illustrate the measurement devices that provide inputs to the control strategy, the actuators that will implement the results of the control calculations, and the function blocks that provide the control logic. 

Also, see Figure 5-9 for a graphical representation of the preliminary results. 

Various algebraic expressions and various graphic representations of the isokinetic relationship offer the possibility of investigating each particular case from different sides and of stating the results and their consequences. A given kind of representation can be useful in a particular case, and no one of them can be considered to be erroneous in itself. 

A plot or graphical representation of the number of samples present in each activity range. Often shown as a population bar chart, it is used to provide an overview of the screening results and typically allows the determination of the overall BACKGROUND signal and threshold for selection of ACTIVE samples. 

Meijer (1993) took the approach of Tjahjadi and Ottino (1991) one step further and reduced all the results to a graphical representation of i drops, Rcrit, and t ow that only depends on the dimensionless parameters p and ficeao/this section indicates how to calculate tbreak using these graphs. 

A graphical representation of the multilevel approach is shown in Fig. 4. All three models are now commonly accepted and are widely used by a number of research groups (both academic and industrial) around the world. In a recent paper, we have given an overview of the three models as they are employed at the University of Twente, together with some illustrative examples (Van der Hoef et al., 2004). In this chapter, we will focus on the technical details of each of the models, much of which has not been published elsewhere. The development of detailed closure relations from the simulations, as indicated in Fig. 3, is still ongoing. Some preliminary results for both the drag-force closures and solid pressure will be presented in the Sections II and III. In this chapter, we will... 

Figure 2. The graphical representation of the solution to the charge neutrality conditions (thick dash-dotted line) and the solution to the gap equation for three different values of the diquark coupling constant (thick solid and dashed lines). The intersection points represent the solutions to both. The thin solid line divides two qualitatively different regions, A < S/i and A > S/i. The results are plotted for fi = 400 MeV and three values of diquark coupling constant Go = r/Gs with i] = 0.5, i] = 0.75, and i] = 1.0.

An appropriate graphical representation of the result is a tree-like dendrogram (Section 6.4). It allows to determine manually the optimal number of clusters as well as to see the hierarchical relations between different groups of objects. 

Deoxygenated It is important to plot this line. At any Paco2, the C02 content will be higher than that of oxy-Hb. This is a graphical representation of the Haldane effect. As a result, the curve is plotted slightly above that of oxy-Hb. Be sure to point this relationship out to the examiner. 

The results for the lead amalgams of the cell in Equation (17.16) are assembled in Table 17.1. The activity coefficients also have been calculated. The graphical representation of In 72 is shown in the body of Figure 17.9. 

One underlying principle of classical statistics is that any observation in nature has an uncertainty associated with it. One extension of this principle is that multiple observations of the same object will result in a distribution of values. One common graphical representation of a distribution of values is the histogram, where the frequency of occurrence of a value is plotted versus the value. Many statistical tools are based on a specific type of distribution, namely the Gaussian, or Normal distribution, which has the following mathematical form ... 

The primary purpose of any quality control scheme is to identify ("flag") significant performance changes. The two-sample quality control scheme described above effectively identifies performance changes and permits separation of random and systematic error contributions. It also permits rapid evaluation of a specific analytical result relative to previous data. Graphical representation of these data provide effective anomaly detection. The quality control scheme presented here uses two slightly different plot formats to depict performance behavior. 

One result from the analysis of the MD simulation was the proposal of a new enzymic pathway for hydrolysis by lysozyme. We begin with a description of the alternative mechanism, and the basis on which it was proposed. The energetics of the individual GlcNAc units in the lysozyme cleft are then presented, followed by a graphical representation of the correlation between the atomic fluctuations of the substrate and those of the enzyme. Of particular interest is the fact that the binding interactions stabilize a bound state conformation for the two glycosides involved in hydrolysis that is optimum for catalysis by the alternative mechanism and which differs from the conformations of the other glycosides. These conformational features are described in the final two sections. 

Figure 10.3 A graphical representation of solvent flattening in real space, (a) represents a one- dimensional solvent mask, (b) is a one-dimensional, unflattened electron density, and (c) is the resulting flattened electron density map that imposes the solvent mask.

Figure 13.19 is a graphical representation of these results in useful form, prepared by combining Eq. 19 and Eq. 5.17, and allows comparison of reactor sizes for plug and dispersed plug flow. 

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