PubMed Health⌕ Search

PubMed · 5683876

The negative exponential with cumulative error.

Abstract

The source did not provide an abstract. Follow the original record for more information.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M B Danford, H M Hughes. 1968. The negative exponential with cumulative error.. https://pubmed.ncbi.nlm.nih.gov/5683876/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

The result of equilibrium-constant calculations strongly depends on the evaluation method used and on the type of experimental errors.

The determination of equilibrium constants is a widespread tool both to understand and to characterize protein-protein interactions. A variety of different methods, among them Scatchard analysis, is used to calculate these constants. Although more than 1000 articles dealing with equilibrium constants are published every year, the effects of experimental errors on the results are often disregarded when interpreting the data. In the present study we theoretically analysed the effect of various types of experimental errors on equilibrium constants derived by three different methods. A computer simulation clearly showed that certain experimental errors, namely inaccurate background correction, inexact calibration, saturation effects, slow kinetics and simple scattering, can adversely affect the result. The analysis further revealed that, for a given type of error, the same data set can produce different results depending on the method used.

Biometry↗

Effect of pH on the heat resistance of spores comparison of two models.

All published models describing the effect of pH on the heat resistance of spores can be regarded either as a linear first degree equation or a linear second degree equation. This work aimed to compare both models from three sets of published data for, Clostridium sporogenes and Bacillus stearothermophilus, respectively. The relative quality of fit of each model with respect to the other depends on the species, the strain and the heating temperature. Parameter estimation was more reliable for the second degree model than for of the simple first degree equation. However, in the case of acidic foodstuffs, predictions obtained from the second degree model are more sensitive toward errors of parameter values. The second degree model is better from the point of view of safety at most frequent ranges of pH of foods. Moreover, for Clostridium botulinum the goodness of fit of this model is clearly higher than that of the first degree equation. If this observation is confirmed by further work, the second degree model in application of standard calculations of heat processes of foods would be preferred.

Biometry↗