145 research outputs found
Bovine oocytes in secondary follicles grow and acquire meiotic competence in severe combined immunodeficient mice
A rigorous methodology is developed
that addresses numerical and
statistical issues when developing group contribution (GC) based property
models such as regression methods, optimization algorithms, performance
statistics, outlier treatment, parameter identifiability, and uncertainty
of the prediction. The methodology is evaluated through development
of a GC method for the prediction of the heat of combustion (Î<i>H</i><sub>c</sub><sup>o</sup>) for pure components. The results showed that robust regression
lead to best performance statistics for parameter estimation. The
bootstrap method is found to be a valid alternative to calculate parameter
estimation errors when underlying distribution of residuals is unknown.
Many parameters (first, second, third order group contributions) are
found unidentifiable from the typically available data, with large
estimation error bounds and significant correlation. Due to this poor
parameter identifiability issues, reporting of the 95% confidence
intervals of the predicted property values should be mandatory as
opposed to reporting only single value prediction, currently the norm
in literature. Moreover, inclusion of higher order groups (additional
parameters) does not always lead to improved prediction accuracy for
the GC-models; in some cases, it may even increase the prediction
error (hence worse prediction accuracy). However, additional parameters
do not affect calculated 95% confidence interval. Last but not least,
the newly developed GC model of the heat of combustion (Î<i>H</i><sub>c</sub><sup>o</sup>) shows predictions of great accuracy and quality (the most data
falling within the 95% confidence intervals) and provides additional
information on the uncertainty of each prediction compared to other
Î<i>H</i><sub>c</sub><sup>o</sup> models reported in literature
Structural Causes of Right Bundle Branch BlockâTime for a Closer Look?
Right bundle branch block is an electrocardiographic phenomenon with specific criteria
Computer-Aided Solvent Screening for Biocatalysis
A computer-aidedsolventscreening methodology is described and tested for biocatalytic systems composed of enzyme, essential water and substrates/products dissolved in a solvent medium, without cells. The methodology is computationally simple, using group contribution methods for calculating constrained properties related to chemical reaction equilibrium, substrate and product solubility, water solubility, boiling points, toxicity and others. Two examples are provided, covering the screening of solvents for lipase-catalyzed transesterification of octanol and inulin with vinyl laurate. Esterification of acrylic acid with octanol is also addressed. Solvents are screened and candidates identified, confirming existing experimental results. Although the examples involve lipases, the method is quite general, so there seems to be no preclusion against application to other biocatalyst
Reliable Correlation for LiquidâLiquid Equilibria outside the Critical Region
A simple model for binary liquidâliquid equilibrium data correlation is explored. The model describes liquidâliquid equilibrium in terms of Henryâs law and unsymmetrically normalized activity coefficients in each phase. A procedure for parameter estimation including an approach to initial guesses, uncertainty analysis of regression results, obtained parameters, and predicted mole fractions has been formulated. The procedure is applied to three cases: hydrocarbons + water, ionic liquids + water, and nitroethane + hydrocarbons. The model has four parameters in the most basic formulation. Depending upon the available data, this number can be extended in a systematic fashion. We compare results of correlation to results obtained with a four-parameter nonrandom two-liquid (NRTL) equation and COSMO-SAC. In general, the new model does nearly as well as NRTL. Advantages of the presented model are a simple form and a parameter set that can be extended in a systematic fashion with an interpretation in terms of thermodynamic properties. The model may be developed further for validation of experimental data
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