The optimization of functions subject to partial differential equations (PDE) plays an important role in many areas of science and industry. In this paper we introduce the basic concepts of PDE-constrained optimization and show how the all-at-once approach will lead to linear systems in saddle point form. We will discuss implementation details and different boundary conditions. We then show how these system can be solved efficiently and discuss methods and preconditioners also in the case when bound constraints for the control are introduced. Numerical results will illustrate the competitiveness of our techniques.
The polymorphisms of the tumor suppressor gene p53 in exon 4 (p53 BstUI) and in intron 6 (p53 MspI) have been suggested to be associated with the genetically determined susceptibility in diverse types of human cancer. In our hospital-based case-control study, we examined the allele and genotype incidence of these polymorphisms as well as their haplotype combinations in 60 brain tumor patients (27 males and 33 females) and 183 controls without malignancies. The genotype characteristics were determined by the PCR-based RFLP method using DNA extracted from peripheral blood. In this study we show that the p53 BstUI and the p53 MspI polymorphisms are not associated with increased risk of brain tumors. Thus, we conclude that the p53 BstUI and the p53 MspI polymorphic sites within the tumor suppressor gene p53 do not represent genetic determinants of susceptibility to brain tumors., E. Biroš, I. Kalina, A. Kohút, E. Bogyiová, J. Šalagovič, I. Šulla., and Obsahuje bibliografii
Fundamentals of the theory of system alliances are briefly reviewed. An accent is put on interfaces (IFs). The model of IFs consisting of a pair of finite deterministic automata sharing a part of their internal state space is introduced. The presented model of alliance interface can be successfully implemented for the study of typical phenomena in complex heterogeneous objects with a significant degree of uncertainty.
Leaf area estimation is an important biometrical observation recorded for evaluating plant growth in field and pot experiments. In this study, conducted in 2009, a leaf area estimation model was developed for aromatic crop clary sage (Salvia sclarea L.), using linear measurements of leaf length (L) and maximum width (W). Leaves from four genotypes of clary sage, collected at different stages, were used to develop the model. The actual leaf area (LA) and leaf dimensions were measured with a Laser Area meter. Different combinations of prediction equations were obtained from L, W, product of LW and dry mass of leaves (DM) to create linear (y = a + bx), quadratic (y = a + bx + cx2), exponential (y = aebx), logarithmic (y = a + bLnx), and power models (y = axb) for each genotype. Data for all four genotypes were pooled and compared with earlier models by graphical procedures and statistical measures viz. Mean Square Error (MSE) and Prediction Sum of Squares (PRESS). A linear model having LW as the independent variables (y = -3.4444 + 0.729 LW) provided the most accurate estimate (R 2 = 0.99, MSE = 50.05, PRESS = 12.51) of clary sage leaf area. Validation of the regression model using the data from another experiment showed that the correlation between measured and predicted values was very high (R 2 = 0.98) with low MSE (107.74) and PRESS (26.96). and R. Kumar, S. Sharma.
The accurate and nondestructive determination of individual leaf area (LA) of plants, by using leaf length (L) and width (W) measurement or combinations of them, is important for many experimental comparisons. Here, we propose reliable and simple regressions for estimating LA across different leaf-age groups of eight common evergreen broadleaved trees in a subtropical forest in Gutianshan Natural Reserve, eastern China. During July 2007, the L, W, and LA of 2,923 leaves (202 to 476 leaves for each species) were measured for model construction and the respective measurements on 1,299 leaves were used for model validation. Mean L, W, LA and leaf shape (L:W ratio) differed significantly between current and older leaves in four out of the eight species. The coefficients of one-dimension LA models were affected by leaf age for most species while those incorporating both leaf dimensions (L and W) were independent of leaf age for all the species. Therefore, the regressions encompassing both L and W (LA = a L W + b), which were independent of leaf age and also allowed reliable LA estimations, were developed. Comparison between observed and predicted LA using these equations in another dataset, conducted for model validation, exhibited a high degree of correlation (R 2 = 0.96-0.99). Accordingly, these models can accurately estimate the LA of different age groups for the eight evergreen tree species without using instruments. and L. Zhang, L. Pan.