Dynamical aspects/parameters

The first decision to be made in designing an experiment to measure the motional properties of membrane lipids concerns the type of probe molecule. Too often, this choice is made from the point of view of convenience or tradition rather than suitability, although there is now a considerable range of suitable fluorophores from which to choose. The second consideration is the type of measurement to be made. The most detailed and complete motional information is obtained from a time-resolved fluorescence anisotropy measurement which is able to separate the structural or orientational aspects from the dynamic aspects of fluorophore motion. Steady-state anisotropy measurements, which are much easier to perform, provide a more limited physical parameter relating to both of these aspects. 

We first describe the NMR parameters for the duplex to strand transition of the synthetic DNA poly(dA-dT) (18) with occasional reference to poly(dA-dU) (24) and poly(dA- brdU) and the corresponding synthetic RNA poly(A-U) (24). This is followed by a comparison of the NMR parameters of the synthetic DNA in the presence of 1 M Na ion and 1 M tetramethylammonium ion in an attempt to investigate the effect of counterion on the conformation and stability of DNA. We next outline structural and dynamical aspects of the complexes of poly(dA-dT) with the mutagen proflavine (25) and the anti-tumor agent daunomycin (26) which intercalate between base pairs and the peptide antibiotic netropsin (27) which binds in the groove of DNA. 

If we analyze the fundamental dynamics aspects of the fluids contacting in the laboratory device, we can easily observe that the velocities and other dynamic parameters of the specific phases, could be identical to those of the extended model. If we neglect the wall effects, which, in the case of LM could be important, we can easily conclude that the dimensionless pi terms that characterize the dynamics of the process present the same values for the laboratory plant and for the extended model. Taking these observations into consideration, we can see that LMs do not require a scaling up of the data and information obtained when we want to use them on experimental investigations of a physico-chemical process. This means that the relationships, the curves and the qualitative observations obtained with an LM could be directly applicable to larger devices. 

Volume 47 of Annual Reports on NMR contains egregious accounts of modem applications of NMR spectroscopy in four distinct areas of scientific research. It is my very pleasant responsibility to thank all of the contributors to this volume for their considerable efforts in the production of their timely accounts. The first chapter covers progress in the Application of 207Pb NMR Parameters by B. Wrackmeyer, providing an update on this area of activity which was previously reviewed in volume 22 of this series. Following this, H. Saito, S. Tuzi, M. Tanio and A. Naito review Dynamic Aspects of Membrane Proteins and Membrane-Associated Peptides as Revealed by 13C NMR Lessons from Bacteriorhodopsin as an Intact Protein. Applications of NMR to Food Science is an area of activity last visited in volume 32 of this series, and more recent developments are discussed by E. Alberti, P. S. Belton and A. M. Gil in the third chapter. The final contribution by K. K. Laali and T. Okazaki is on NMR of Persistent Carbocations from Polycyclic Aromatic Hydrocarbons. 

NMR is an extremely versatile spectroscopic tech nique for three reasons (1) It is not a destructive tech nique. Thus, the system may be studied without any perturbation that influences the outcome of the mea surements. The system can be characterized repeatedly with no time-consuming sample preparation in between mns. (2) There is a large number of spectro scopic parameters that may be determined by NMR relating to both static and dynamic aspects of a wide variety of systems. (3) A large number of atomic nuclei... 

A minimal model for interpreting the main features of the static and dynamic aspects of EOM effects [31] is introduced in this section. To reduce complexity, this model does not explicitly consider the anisotropic effect on elastic and viscous properties. More realistic expressions considering the anisotropy [47-50] are available, but the limited experimental data makes it difficult to unambiguously determine a larger set of material parameters. 

Thus, there is clearly a need for a fast, but reliable assessment of I/O-controllability and of potential control structures. This contribution focuses on the dynamic aspects of controllability. It is tacitly assumed that a (possibly crude) performance specification in standard control terms is available, i. e. a set of trajectories, disturbances, parameter variations, and control objectives is specified. This requires knowledge of the process and the factors that determine its optimal operation that has to be acquired in the design process or from the operation of similcir plants. 

Models of coupled nonlinear oscillators act as good candidates to explain the dynamical aspects in the aforementioned cases in a phenomenological manner. Even at the macroscopic level, many more details can be unearthed if we fine-tune the models to include additional factors and parameters, hence making the models closer to real-world systems. Validating the model results with the experimental results will also help fill in the gaps. Attempts are being made in this direction. 

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. ... 

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