Assessment meaningful

Spray Correlations. One of the most important aspects of spray characterization is the development of meaningful correlations between spray parameters and atomizer performance. The parameters can be presented as mathematical expressions that involve Hquid properties, physical dimensions of the atomizer, as well as operating and ambient conditions that are likely to affect the nature of the dispersion. Empirical correlations provide useful information for designing and assessing the performance of atomizers. Dimensional analysis has been widely used to determine nondimensional parameters that are useful in describing sprays. The most common variables affecting spray characteristics include a characteristic dimension of atomizer, d Hquid density, Pjj Hquid dynamic viscosity, ]ljj, surface tension. O pressure, AP Hquid velocity, V gas density, p and gas velocity, V. ... 

In modern methods of profitability assessment, cash flows are more meaningful than profits, which tend to be rather loosely defined. The net annual cash flow after tax is given by... 

This report is by Battelle Columbus Division to the Line Pipe Research Supervisory Committee of the American Gas Association. It presents an analysis of statistical data obtained from reports of lea)c or rupture (service) incidents and test failures in natural gas transmission and gathering lines over the 14.5 year period from 1970 through June, 1984. All gas transmission companies were required to notify the Office of Pipeline Safety Operations in the event of a "reportable" incident, as defined by the Code of Federal Regulations. The purpose of the study is to organize the reportable incident data into a meaningful format from which the safety record of the industry can be assessed. 

In addition to high sensitivity, a requirement for any acceptable analytical method is high specificity because at very low levels few confirmatory procedures can be used to establish the identity of a particular compound. A method which uniquely combines high sensitivity with high specificity is high resolution mass spectrometry. We have used this method as the basis for an approach which we believe will make possible a meaningful assessment of TCDD levels in the environment. 

In concluding, we point out an essential role of vibrational spectra In theoretical studies. Total energy calculations yield quantities of much Interest, like equilibrium geometries and binding energies, which are not accessible In a direct experimental way. Only the vibrational quantities can be meaningfully compared with experiment and provide a way to assess the adequacy of these calculations. 

The major technical problem was the inability to define subsurface geohydrologic conditions with the initial data. Expertise in the area of geohydrology was clearly needed. A lack of specific analytical techniques precluded meaningful environmental and risk assessments. Cleanup efforts were complicated because poltiners are not regulated under RCRA but are regulated under state law. In the middle of the cleanup effort, the site became involved in Superfund activities, and to date this involvement has not been clarified. Project management has become very difficult because of the many players and laws involved. As a result, public confidence has been affected. 

Assessment of spatial distributions of pollutant concentrations is a very specific problem that requires more than blind mapping of these concentrations. Not only must the criterion of estimation be chosen carefully to allow zooming on the most critical values (the high concentrations), but also the evaluation of the potential error of estimation calls for a much more meaningful characteristic than the traditional estimation variance. Finally, the risks a and p of making wrong decisions on whether to clean or not must be assessed. 

Quantitative assessment of enzyme affinity for various members of these chemical series is critical for development of a meaningful understanding of SAR and ultimately for compound optimization for clinical use. 

With respect to method application, once validation has been satisfactorily completed, there is little question that use of the analytical method in worker safety and re-entry studies falls under the full requirements of the GLP Standards. In addition, there should be an adequate level of quality control measurements taken in conjunction with the specimens so as to provide for a meaningful assessment of accuracy and precision, as well as verification of freedom from artifactual interferences. Along with these measurements there needs to be reasonably rigid data acceptance criteria in place (usually established during validation) which are consistently applied during the course of the specimen analytical phase of the study. 

Mueler et al. and Gottschalk et al. [43, 44] presented a model for predicting concentrations of nanoparticles including nano-Ag, nano-Ti02, nano-ZnO, fullerenes, and carbon nanotubes (CNT) in different environmental compartments. The results of this study demonstrated that modeling is a meaningful utility to carry out quantitative risk assessment of nanoparticles. 

As it has been shown in this chapter knowing the concentrations of chemicals in the environment is a key aspect in order to carry out meaningful hazard and risk assessment studies. Predicting concentrations of chemicals can serve as a quick and robust way to produce an acceptable screening level assessment however if further precision is desired, the complexity of real environmental scenarios can make it a cumbersome and unaffordable task. Models improvement requires not only refining their computation algorithms but also and more important, implementing new inputs and processes in order to better describe real scenarios. 

The utilisation of RCP as secondary raw material has to find a quantitative risk assessment in the future to establish meaningful limit values as basis for the development of e.g. elimination processes or barrier coatings. 

In almost every problem of meaningful scale, the number of possible classifiers is far too large for rule-culling to be feasible instead, a dynamic algorithm is required that can run the CS, assess the quality of the classifiers, remove the poor ones, and create new, potentially valuable replacements. This is accomplished by using a genetic algorithm (Chapter 5) to evolve the classifier list. 

Although basic scientific research deals with variation and its sources, the results of research work are mainly described and compared in terms of mean values supplemented with information about whether specific factors have a significant impact or not. Most research studies focus on individual factors in isolation and there are limited data in the literature on the interaction of a number of factors, particularly in relation to on-farm production practice. Consequently, the meaningfulness of previous results is often limited and often does not allow general conclusions to be drawn. As the relevance of the various factors changes between different production systems it is even more difficult to assess the ranking position of each factor within each production system in relation to the variation of product and process quality traits. 

All equipment has limitations, for example, the amount of a substance it can detect or the accuracy with which it can make a measurement. If you attempt to make the equipment perform beyond its capabilities, it does not matter how carefully the equipment is operated, it will not be possible to get meaningful results. In terms of a particular instrument, fitness for purpose is interpreted as having appropriate performance capability to do the work required. This applies to all equipment, large or small. For example, a stirrer needs to perform the intended task satisfactorily while remaining essentially inert. There is a formal process for assessing the suitability of equipment to perform a given task - this is called Equipment Qualification or Equipment Validation. This is dealt with in Section 5.6.3. 

It is clear from (5.56c) that q can be chosen to give Vcoui any desired value, i.e., to make (5.56c) work for a chosen cluster species. Thus, it is meaningful only to compare how a single value of q fits two or more different clusters, in order to assess how well Vcoui describes Vtrue. 

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