Yardstick For Comparison Research Articles

Rehabilitation after severe head injury.

123 survivors of severely head injured patients presenting with coma grade III show a decreasing mean duration of coma with increasing age. The numbers and frequency of good recovery decrease, whereas poor recovery increases with age. Increase of the duration of coma grade III produces an increase of the mean latency and time of recovery and of the frequency of poor recovery, regardless of the age of the patients. Increasing age does not increase the mean latency and time of recovery systematically. The important conclusion of this analysis is, that the clinical feature of coma grade III, corresponding to GCS score of 4 and RLS of 6 and 7, indicates a different kind of brain damage at various age groups. It represents a lesser degree of brain damage for younger patients under 20, than for those over 20. In our opinion our observations do not demonstrate a better capacity of recovery of the young patients: but the young patients show a more severe clinical picture than the older patients do, if only the clinical syndrome of coma grade III with extensor rigidity, is considered as a yardstick for comparison.

Geoelectric profiling

The response of the focused surface laterolog system using seven electrodes, for conducting as well as for resistive targets, is equivalent or nearly equivalent to that of the modified unipole having only three electrodes, which in turn can be computed from simple two-electrode measurements. Thus focusing the current down towards the target does not necessarily improve the response measured on the ground surface. As far as conducting vein-shaped targets are concerned, the simplest unfocused two-electrode array has overwhelming advantages over the Wenner, the Schlumberger and the focused systems like the unipole, modified unipole and the surface laterolog in shape and amplitude of anomalies, in depth of detection and in cost of operation. For resistive targets, not one system seems distinctly better than the others, except for cost of operations which would be lowest for the two-electrode array. In comparison with the dipole-dipole array, the two-electrode array spacing to spacing ( L) gives again better response in regard to amplitude and shape of anomaly, depth of detection and cost of operation. But, if the spacing ( L) between the farthest moving active electrodes in an array is not considered as a yardstick for comparison, and the availability of the source power is not a problem in the field, then the dipole array appears better in shape and amplitude. It requires less cable and does not need the infinite cable lay-out. Defining the depth of investigation of an electrode array as the depth of a thin horizontal layer of a homogeneous ground that contributes maximum to the total signal measured on the ground surface, the two-electrode array is found to have the largest depth of investigation. The theoretical analysis on depths of investigation of different electrode arrays has once again brought out the superiority of the two-electrode array over the others, even focused systems. However, the advantage of the two-electrode array in having a high depth of investigation is counterbalanced by its low vertical resolution. It is a matter of intuition that a buried target at the depth of investigation of an electrode array gives more response on the ground surface than when the target is above or below that depth. A modified pseudo-depth section was suggested to obtain by plotting the apparent resistivity and/or apparent polarisability values at the maximum contribution depth of investigation of the array. Model and field studies demonstrate that the pseudo-depth section serves as a convenient tool in prospecting for conducting minerals and in the location of the boreholes. The tool was successfully tested in a virgin area. The results of the field survey were described. For some reason or the other, it is still not uncommon to find that the term, depth of detection, is loosely used by field geophysicists for the depth of investigation of an electrode array. Depth of detection of a target with a given electrode array is defined as the limiting depth below which the target cannot be detected with the array. Following this definition, the dipole array is found to have the greatest depth of detection and the two-electrode array has the least, as far as detection of a sandwiched layer in a horizontally three-layered ground is concerned. The Wenner and/or Schlumberger array is found to have a depth of detection in between those of dipole and the two electrode arrays.

Theoretical comparison of the enhanced variance and twin-gate methods for monitoring plutonium in waste

Certain plutonium-monitoring systems, especially those used for checking and classifying drums of mixed waste, depend on detecting paired neutrons originating from spontaneous fissions of 240Pu. Such neutrons can be detected with reasonable efficiency by suitable counters but, as they are usually accompanied by a high random background of other neutrons, the problem arises of separating the “signal”, i.e. pairs, from the “noise” or random pulses. Various ways of doing this have been devised, e.g. variable dead-time counters 1,2), arrangements of coincidence gates 3) for measurement of the pulse interval distribution 4). A recent suggestion for doing this was to look for deviation from a true Poisson distribution in the actual numbers of counts registered in a large number of equal time intervals. This paper is a theoretical analysis of the counting statistics to determine the nature and amount of the deviation and thus estimate the accuracy of fission-pair rate determinations in a few typical cases. As a yardstick for comparison, we have also analysed a simple form of twin-gate method, in which total counts accumulated via a time-gate triggered by some of the pulses, are compared with counts in another gate triggered after a suitable delay. To simplify the mathematics, we have assumed all the gate-periods are separate and non-overlapping. Results show that the presence of pulse-pairs increases the variance of the distribution above the Poisson value. Using the measured excess variance yields an appreciably more accurate estimate of pair-rate than the twin-gate method, at high total pulse rates (>15 000 pulses/s), but the reverse is true at low rates (∼100 pulses/s). With typical parameters (and a mean interval between pulse pairs of 125 ωs), the cross-over point would be around 1000 pulses/s.

The selective efficiency of a test battery

In industrial acceptance sampling one frequently makes use of operating characteristic curves to describe the discriminating power of a particular sampling plan. Similarly, it is possible to demonstrate the selective efficiency of a test battery in terms of (a) the Applicant's Operating Characteristic (A.O.C.); (b) the Selector's Operating Characteristic (S.O.C.). The A.O.C. determines the chance of selection by means of a test for any given level of true ability. The S.O.C. connects functionally probability of success on the criterion with the predictor scores of a battery. For the case of a normal bivariate distribution the exact mathematical expressions of the OC curves are derived in terms of the correlation coefficientρ, the cut-off points α andβ, and the predictor and criterion scoresX andY (in standard measures). The Efficiency IndexH is defined as the percentage of successful subjects gained by the use of a test battery, taking chance selection as a yardstick for comparison. Its optimum, for fixedρ and α, is derived. The distribution law of the criterion scores of selectees is deduced and its first four moments are shown to depart little from normality for cases usually encountered in practice. A “Quality-Gain” diagram graphically illustrates the improvements secured. Another simple device, the “Cost-Utility” diagram, explains to management the full implications of selecting personnel by means of a test battery. Neither of the diagrams requires an understanding of the correlation coefficient. The confidence belt of the OC curves, the standard error of the mean criterion score of selectees and the standard error of the predicted number of successful applicants are determined. Finally, the full theory is applied in detail to a real test battery.