929 resultados para Two-Phase Regression


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At head of title: United States Atomic Energy Commission - USAEC. European Atomic Energy Community - EURATOM.

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"Contract AT(30-1)-2789."

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Published polymer distribution data for aqueous poly(ethylene glycol)/dextran mixtures have been reassessed to illustrate the feasibility of their quantitative characterization in terms of the Flory-Huggins theory of polymer thermodynamics. Phase diagrams predicted by this characterization procedure provide better descriptions of the experimental data than those based on an earlier, oversimplified treatment in similar terms. (C) 2003 Wiley Periodicals, Inc.

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The DNA binding fusion protein, LacI-His6-GFP, together with the conjugate PEG-IDA-Cu(II) (10 kDa) was evaluated as a dual affinity system for the pUC19 plasmid extraction from an alkaline bacterial cell lysate in poly(ethylene glycol) (PEG)/dextran (DEX) aqueous two-phase systems (ATPS). In a PEG 600-DEX 40 ATPS containing 0.273 nmol of LacI fusion protein and 0.14% (w/w) of the functionalised PEG-IDA-Cu(II), more than 72% of the plasmid DNA partitioned to the PEG phase, without RNA or genomic DNA contamination as evaluated by agarose gel electrophoresis. In a second extraction stage, the elution of pDNA from the LacI binding complex proved difficult using either dextran or phosphate buffer as second phase, though more than 75% of the overall protein was removed in both systems. A maximum recovery of approximately 27% of the pCU19 plasmid was achieved using the PEG-dextran system as a second extraction system, with 80-90% of pDNA partitioning to the bottom phase. This represents about 7.4 microg of pDNA extracted per 1 mL of pUC19 desalted lysate.

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We extend a meshless method of fundamental solutions recently proposed by the authors for the one-dimensional two-phase inverse linear Stefan problem, to the nonlinear case. In this latter situation the free surface is also considered unknown which is more realistic from the practical point of view. Building on the earlier work, the solution is approximated in each phase by a linear combination of fundamental solutions to the heat equation. The implementation and analysis are more complicated in the present situation since one needs to deal with a nonlinear minimization problem to identify the free surface. Furthermore, the inverse problem is ill-posed since small errors in the input measured data can cause large deviations in the desired solution. Therefore, regularization needs to be incorporated in the objective function which is minimized in order to obtain a stable solution. Numerical results are presented and discussed. © 2014 IMACS.