Data treatment Smoothing methods

The data from the method validation data should be analyzed as the data are obtained and processed to ensure a smooth flow of information. If an experimental error is detected, it should be resolved as soon as possible to reduce any impact it may have on later experiments. Analysis of the data includes visual examination of the numerical values of the data and chromatograms followed by statistical treatment of the data if required. 

Trend tests seek to evaluate whether there is a monotonic tendency in response to a change in treatment. That is, the dose response direction is absolute as dose goes up, the incidence of tumors increases. Thus the test loses power rapidly in response to the occurrences of reversals , for example, a low-dose group with a decreased tumor incidence. There are methods (Dykstra and Robertson, 1983) which smooth the bumps of reversals in long data series. In toxicology, however, most data series are short (that is, there are only a few dose levels). 

First let us compare the librational mode found for ice by Marchi [8] using lattice mode spectroscopy (see Fig. 18) with our smooth water-like absorption dependence illustrated by the right-hand part of Fig. 20a. This spectrum evidently agree much better with the experimental data than the noise-like pattern calculated by the MD method and depicted in the lower part of Fig. 18. It is important that in the work by Marchi [8] the dipole-induced-dipole terms provide the dominant contribution to the total intensities. However, in view of a recently MD modeling of water spectra by Sharma et al. [29], the polarization effects depend on the environment in a strong intermolecular way, which possibly was not taken into account in the cited treatment by Marchi. 

Recently the DFT method combined with SAFT equations of state has been used to predict the interfacial properties of real fluids. LDA methods are accurate enough to treat liquid-liquid and liquid-liquid interfaces where the density profiles are usually smooth functions, and have been used in combination with the SAFT-VR approach to predict the surface-tension of real fluids successfully. The intermolecular model parameters required to treat real substances are determined by fitting to experimental vapour-pressure and saturated liquid density data in the usual way (see section 8.5.1) and the resulting model is found to provide accurate predictions of the surface tension. A local DFT treatment has also been combined with the simpler SAFT-HS approach, but in this case only qualitative agreement with experimental surface tension data is found due to the less accurate description of the bulk properties provided by the SAFT-HS equation. Kahl and Winkelman" have followed a perturbation approach similar to the one proposed with the SAFT-VR equation and have coupled a local DFT treatment with a Lennard-Jones based SAFT equation of state. They predict the surface tension of alkanes from methane to decane and of cyclic and aromatic compounds in excellent agreement with experimental data. 

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