Interactions, influencing factors

This change is influenced by metaboHc hormone action rarely do any of the hormones or other influencing factors act independent of each other to regulate nutrient partitioning. Complex interactions aHow for integration of influences to accommodate a coordinated chronic regulation of nutrient use for maintenance or growth so that an animal may adapt to its environment (see Feeds AND FEED ADDITIVES). 

In addition to variations in toxin structure, the nature of the binding site and the medium in which binding occurs both influence the observed behavior of the toxins and can be systematically varied to study the toxin/binding site interaction. These factors will not be discussed at length here, but should be remembered as complications in comparing different data sets. 

One of the most crucial influencing factors in planar chromatography is the vapor space and the interactions involved. The fact that the gas phase is present, in addition to stationary and mobile phases, makes planar chromatography different from other chromatographic techniques. Owing to the characteristic of an open system the stationary, mobile, and vapor phases interact with each other until they all are in equihbrium. This equilibrium is much faster obtained if chamber saturation is employed. This is the reason for differences in separation quality when saturated and unsaturated chambers are used. However, the humidity of the ambient air can also influence the activity of the layer and, thus, separation. Especially during sample application, the equihbrium between layer activity and relative humidity of the... 

Because the experimental expenditure increases strongly with the increasing number of influence factors, fractional factorial design FFD (partial factorial design) is applied in such cases. It is not possible to evaluate all the interactions by FFDs but only the main effects. 

Reaction Enthalpy and Polar Interaction as Factors that Influence on Activation Energy of Reaction R02 + Ether (Equation [6.32])... 

We have investigated the influence of diquark condensation on the thermodynamics of quark matter under the conditions of /5-equilibrium and charge neutrality relevant for the discussion of compact stars. The EoS has been derived for a nonlocal chiral quark model in the mean field approximation, and the influence of different form-factors of the nonlocal, separable interaction (Gaussian, Lorentzian, NJL) has been studied. The model parameters are chosen such that the same set of hadronic vacuum observable is described. We have shown that the critical temperatures and chemical potentials for the onset of the chiral and the superconducting phase transition are the lower the smoother the momentum dependence of the interaction form-factor is. 

Quantification of possible interactions between the influencing factors by eliminating hypotheses of independence of the factors and of the additivity of their effects postulated in the screening step. 

The NMR chemical shift, the most prevalent parameter in NMR spectroscopy, carries a wealth of information regarding the environment and the local electronic structure in the vicinity of the nucleus under study.(i). For example, one normally finds a different chemical shift for the Ca nucleus of each alanine residue in a protein. Ideally, a thorough analysis of the NMR chemical shift can yield information regarding the structure and interactions in the vicinity of the nucleus concerned. To achieve this, a detailed understanding of how geometrical factors and intermolecular interactions influence the chemical shift is crucial. The development and validation of the methods towards this end have combined powerful and efficient ab initio quantum mechanical techniques, which have been... 

The coefficients (associated with variables) are proportional to the so-called main effects and the interaction effects if more than one variable is involved. The identification of such effects is important in evironmental research. Of special interest may be the interaction of influencing factors in the sense of synergistic or antagonistic effects. An illustrative example from the field of environmental research is given in Section 10.2. 

As mentioned before, people tend intuitively to turn to the one-variable-at-a-time technique for its conceptual simplicity, and ignore the possible interaction between independent variables. A good example of the interaction between factors is that between enzyme concentration (E) and reaction temperature (T). Assuming E and T are the chosen factors for optimization, one possible interaction will be that T tends to influence the way E affects the conversion yield and vice versa. Since reaction temperature increased, enzyme activity was suppressed than at low temperature and the rate of enzyme-catalysis is affected by temperature this will inevitably affect conversion yield of the product. Should the interaction be minor or negligible, a one-factor-at-a-time search will give a satisfactory result. 

Quite wide limits are generally chosen for screening quantitative factors. They are then often narrowed for more detailed quantitative study of the influence of factors where interactions between factors them are taken into account and for determining a predictive model for optimization. 

Whereas the purpose of a screening study is to determine which of a large number of factors have an influence on the formulation or process, that of a factor study is to determine quantitatively the influence of the different factors together on the response variables. The number of levels is usually again limited to two, but sufficient experiments are carried out to allow for interactions between factors. 

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