The Output from GRID

The GRID method was explicitly designed in order to get selective information about binding sites, and the output can be used in two quite distinct ways  

To prepare GRID maps which are intuitively easy to understand, and can therefore provide a focal point for discussions between people with backgrounds in different fields of science, and indeed for people with little formal scientific training. 

To generate matrices of numerical data which can be analysed statistically. 

This article is not the place in which to consider statistical methods in detail, but the use of GRID maps to interpret interesting features of molecular structures will now be described. 

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It must be relatively easy for anybody working in the field to interpret the output from GRID. 

These solar plants are being tested to evaluate their desirability. One area of concern is how the output from the plants can be integrated into the electric power grid. The midday peak of production does not mesh well with the peak demand that occurs late in the afternoon. On some days, clouds prevent any operation. On other days the power drops quickly when clouds drift in fiont of the collectors and comes back abruptly when the clouds drift on past. These transients cause dramatic thermal expansion and contraction shocks to the system. Accommodating for these shocks produces design challenges and reduces the system lifetime. 

The primary wave function output data from the Herman-Skillman program are the products rR r), which are known as the numerical radial functions. The radial wave function itself can be recovered on division by the radial distance, r, and approximately near the origin by extrapolating to avoid the infinity. There is one other detail. For the purposes of the numerical integration procedure in the Herman-Skillman procedure the radial data are defined on a non-uniform grid, x, known as the Thomas-Fermi mesh (4). These are converted, in the output from hs.exe, to radial arrays specific to each atom, with... 

In practice, elimination of axial current flow requires relatively fine segmentation, eg, 1—2 cm, between electrodes, which means that a utihty-sized generator contains several hundred electrode pairs. Thus, one of the costs paid for the increased performance is the larger number of components and increased mechanical complexity compared to the two-terrninal Faraday generator. Another cost is incurred by the increased complexity of power collection, in that outputs from several hundred terminals at different potentials must be consoHdated into one set of terminals, either at an inverter or at the power grid. 

The water-oil ratio is a complex time-dependent function of the state variables since a well can produce oil from several grid cells at the same time. In this case the relationship of the output vector and the state variables is nonlinear of the form y(t,)=h(x(t,)). 

Although not denoted explicitly, we have seen in Section 6.8 that this estimate will depend on the grid spacing M and the number of particles Nv. In addition to the mean composition, the output data from the PDF code will usually be various composition statistics estimated at grid-cell centers. We will thus need accurate and efficient statistical estimators for determining particle fields given the ensemble of Nv notional particles. 

Figure 7.17 Moore s hardware implementation of Land s algorithm (Reproduced by permission of IEEE. Moore A and Allman J and Goodman RM 1991 A real-time neural system for color constancy. IEEE Transactions on Neural Networks, IEEE, 2(2), 237-247, March). The output of the camera is smoothed using three separate resistive grids (a). A single resistive grid is shown in (b). The smoothed image is then subtracted from the original image.

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