Electrophoretic migration behavior of DNA fragments in polymer solution

A newly developed polymer coil shrinking theory is described and compared with the existing entangled solution theory to explain electrophoretic migration behaviour of DNA in hydroxypropylmethylcellulose (HPMC) polymer solution in buffer containing 100 mM tris(hydroxymethyl)aminomethane 100 mM boric acid, 2 mm ethylenediaminetetraacetic acid at pH 8.3. The polymer coil shrinking theory gave a better model to explain the results obtained. The polymer coil shrinking concentration, C-s, was found to be 0.305% and the uniform entangled concentration, C+, 0.806%. The existence of three regions (the dilute, semidilute, and concentrated solution) at different polymer concentrations enables a better understanding of the system to guide the selection of the best conditions to separate DNA fragments. For separating large fragments (700/800 bp), dilute solutions (HPMC < 0.3%) should be used to achieve a short migration time (10 min). For small fragments (200/300 bp), concentrated solutions are preferred to obtain constant resolution and uniform separation. The best resolution is 0.6% HPMC due to a combined interaction of the polymer coils and the entangled structure. The possibility of DNA separation in semidilute solution is often neglected and the present results indicate that this region has a promising potential for analytical separation of DNA fragments.

A collision model for DNA separation by capillary electrophoresis in dilute polymer solution

A theoretical description. based on chemical kinetics and electrochemistry, is given of DNA separation in dilute polymer solution by capillary electrophoresis. A self-consistent model was developed leading to predictions of the DNA electrophoretic velocity as a function of the experimental conditions - polymer concentration, temperature, and electric field strength. The effect of selected experimental variables is discussed. The phenomena discussed are illustrated for the example of 100 bp DNA ladder separation in dilute HPMC solution by capillary electrophoresis. This model is the first single model that can fully explain the dependence of DNA electrophoretic velocity on electrophoretic conditions.

Synthesis of NaA zeolite membranes from clear solution

NaA zeolite membranes were successfully synthesized on a porous alpha -Al2O3 support from clear solution. The synthesis parameters, such as surface seeding, synthesis time, synthesis stages, etc. were investigated. Surface seeding can not only accelerate the formation of NaA zeolite on the support surface, but can also inhibit the transformation of NaA zeolite into other types of zeolites. A continuous NaA zeolite membrane formed on the seeded support after 2 h of synthesis. Gas permeation results showed that a synthesis time of 3 h produced the best NaA zeolite membrane. When the synthesis time was longer than 4 h, the NaA zeolite on the support surface began to transform into other types of zeolites, and the quality of the NaA zeolite membrane decreased. The quality of the NaA zeolite membrane can be improved by employing the multi-stage synthesis method. The NaA zeolite membrane with a synthesis time of 2 h after a two-stage synthesis showed the best gas permeation performance. The permeances of H-2, O-2, N-2, and n-C4H10 decreased as the molecular kinetic diameter of the gases increased. which showed the molecular sieving effect of the NaA zeolite membrane. The permselectivities of H-2/n-C4H10 and O-2/N-2 were 19.1 and 1.8, respectively. These values are higher than the Knudsen diffusion ratios of 5.39 and 0.94. However, the permeation of n-C4H10 also indicated that the NaA zeolite membrane had certain defects with diameters larger than the pore size of NaA zeolite. A synthesis model was proposed to clarify the effect of surface seeding. (C) 2001 Elsevier Science B.V. All rights reserved.

Probabilistic Solution of Inverse Problems

In this thesis we study the general problem of reconstructing a function, defined on a finite lattice from a set of incomplete, noisy and/or ambiguous observations. The goal of this work is to demonstrate the generality and practical value of a probabilistic (in particular, Bayesian) approach to this problem, particularly in the context of Computer Vision. In this approach, the prior knowledge about the solution is expressed in the form of a Gibbsian probability distribution on the space of all possible functions, so that the reconstruction task is formulated as an estimation problem. Our main contributions are the following: (1) We introduce the use of specific error criteria for the design of the optimal Bayesian estimators for several classes of problems, and propose a general (Monte Carlo) procedure for approximating them. This new approach leads to a substantial improvement over the existing schemes, both regarding the quality of the results (particularly for low signal to noise ratios) and the computational efficiency. (2) We apply the Bayesian appraoch to the solution of several problems, some of which are formulated and solved in these terms for the first time. Specifically, these applications are: teh reconstruction of piecewise constant surfaces from sparse and noisy observationsl; the reconstruction of depth from stereoscopic pairs of images and the formation of perceptual clusters. (3) For each one of these applications, we develop fast, deterministic algorithms that approximate the optimal estimators, and illustrate their performance on both synthetic and real data. (4) We propose a new method, based on the analysis of the residual process, for estimating the parameters of the probabilistic models directly from the noisy observations. This scheme leads to an algorithm, which has no free parameters, for the restoration of piecewise uniform images. (5) We analyze the implementation of the algorithms that we develop in non-conventional hardware, such as massively parallel digital machines, and analog and hybrid networks.