Zur quantitativen Auswertung von Mikro-Autoradiogrammen mit dem Densitron

Die vorliegende Arbeit beschāftigt sich mit der Answertung von Autoradiogrammen inhomogen markierter mikroskopischer Strukturen am Densitron. Dazu fertigten wir von herkömmlichen Stripping-Filmen (z. B. ORW O K 106) Mikro-Stufengraukeile an und bestimmten die Schwärzung S_ijeder Stufe photometrisch. Graukeile geeigneten Schwärzungsumfangs dienten dann zur Einstellung der Farbtrigger des Densitrons, so daß sich die bei dieser Einstellung gemessenen Farbflächen F_i des jeweiligen Objektes bestimmten Schwärzungswerten zuordnen ließen.

Als Modellobjekte verwendelen wir erstens Autoradiogramme von ³H-Thymidin-markierten Tumorzellen. Vergleichsmessungen an unterschiedlich lange exponierten, sonst aber identischen Präparaten ergaben eine gute Reproduzierbarkeit der Meßergebnisse. Als zweites Testobjekt dienlen Autoradiogramme einer nur schwach markierten Struktur im Gehirn von Fröschen. Die an diesem Grenzfall erhaltenen Ergebnisse werden mit Meßwerten verglichen, die vom gleichen Objekt mittels Scanning-Photometrie an einem. Mikroskop-Photometer SMP 01 (OPTON, Oberkoches, BRD) gewonnen wurden.     

Adaptive selection of parameters for precise computation of matrix exponential based on padé approximation

讨论了基于Pad\'{e}逼近的矩阵指数精细积分方法中加权系数N 和展开项数q的自适应选择问题. 参数(N,q)的选择直接影响到矩阵指数计算的精度和效 率. 采用矩阵函数逼近理论，研究了参数N和q的增加对精度的影响程度，据此，提出了 参数(N,q)优化组合的递推自适应选择方法. 该方法可以根据矩阵本身的性态选择合适的参 数(N,q),而参数选择的计算量与矩阵指数的计算量相比几乎可以忽略，这对于增强矩阵指 数精细积分方法的适应性和提高计算效率是很有益处的. 算例验证了该方法的正确性和有效性.     

Dynamic optimization of chemical cleaning in dead-end ultra filtration

In this paper a control strategy is formulated that minimizes the costs for a single chemical cleaning of a dead-end ultra filtration membrane. From the process model, the performance index and the constraints it can be derived that dynamic optimization will lead to a ‘maximum effort control problem’, in which the controls (cleaning flow and cleaning agent concentration) are either zero or maximum. The change from maximum to zero is called the switching point. This switching point depends on the overall cleaning time and the requested cleaning effectiveness. From the calculated optimal control strategy it follows that cleaning time can be significantly reduced, compared to conventional cleaning.     

Structural fluctuations in ensembles of nanoparticles

Caused by the interaction between the particles, structural fluctuations influence thermodynamics and order of transformation of an ensemble of nanoparticles. A stringed thermodynamic analysis revealed that, in fluctuating ensembles, the ratio of particle numbers in the equilibrium over the one in the non-equilibrium phase is independent of any metastable in between. Structural transformations in such ensembles, connected to latent heat, are of infinite order. These findings are summarized in a set of theorems ruling structural fluctuations. Finally, the consequences of fluctuations are demonstrated by an example.     

A new difference scheme with high accuracy and absolute stability for solving convection–diffusion equations

In this paper, we use a semi-discrete and a padé approximation method to propose a new difference scheme for solving convection–diffusion problems. The truncation error of the difference scheme is O(h⁴+τ⁵). It is shown through analysis that the scheme is unconditionally stable. Numerical experiments are conducted to test its high accuracy and to compare it with Crank–Nicolson method.     

Updating beliefs about variables given new information on how those variables relate

Bayesian techniques specify how to update beliefs about a variable given information on that variable or related variables. In many cases, statistical analyses also provide information about the relationship between variables, but the Borel Paradox prohibits many natural ways of updating beliefs conditioned on information about a relationship. This paper presents a method by which beliefs can be updated without violating the Borel Paradox under certain circumstances. We apply our approach to relationships specified by a statistical model (i.e., regression), and relationships described by statistical simulation.