Biomedical subjects
Publications and source records attributed to K Kaski.
In this study we have carried out computer simulations of random walks on Watts-Strogatz-type small world networks and measured the mean number of visited sites and the return probabilities. These quantities were found to obey scaling behavior with intuitively reasoned exponents as long as the probability p of having a long range bond was sufficiently low.
Dynamics of fracture is investigated in an anisotropic two-dimensional Born-Maxwell model by numerical simulations. From previous studies it is known that the isotropic model shows crack branching and velocity oscillations of the propagating main crack above a critical velocity, similarly with experimental findings in some brittle materials. Here we present studies in which anisotropy has been introduced to the model system. Anisotropy is found to have significant effects on crack propagation and on the pattern it forms. In the case of symmetric anisotropy (relative to the crack direction) we found changes in velocity oscillation and side branching properties. In the case of asymmetric anisotropy two kinds of periodicities occur and strong anisotropy causes different branch patterns to form at two sides of the main crack. In addition, the role of disorder through distributed spring constants has been studied for both types of anisotropy. Finally a simple exactly solvable model for investigating the initial stages of crack branching has been developed and analyzed.
Retrospective analysis of chemotherapy results of children with nephroblastoma was performed in 220 patients aged from 1 yr to 14 yrs of live in 12 centers. Stage I nephroblastoma was documented in 24.5% but stage II--in 55.3%. Histologically 74.6% cases were diagnosed as medium malignant and 12.7%--high malignant. Therapy results were similar to observed in other centers.
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Nonlinear time series modeling with a multilayer perceptron network is presented. An important aspect of this modeling is the model selection, i.e., the problem of determining the size as well as the complexity of the model. To overcome this problem we apply the predictive minimum description length (PMDL) principle as a minimization criterion. In the neural network scheme it means minimizing the number of input and hidden units. Three time series modeling experiments are used to examine the usefulness of the PMDL model selection scheme. A comparison with the widely used cross-validation technique is also presented. In our experiments the PMDL scheme and the cross-validation scheme yield similar results in terms of model complexity. However, the PMDL method was found to be two times faster to compute. This is significant improvement since model selection in general is very time consuming.
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A mathematical model for describing dynamic phenomena in the olfactory bulb is presented. The nature of attractors and the bifurcation sequences in terms of the lateral connection strength in the mitral layer are studied numerically. Chaotic activity has only been found in the case of strong excitatory coupling. Synaptic modification-induced transition from oscillation to chaos is demonstrated. A model for a simple associative memory is also presented.
Methods based on the neural network techniques are among the most accurate in the secondary structure prediction of globular proteins. Here the same principles have been used for the tertiary structure prediction problem. The map of dihedral phi and psi angles is divided into 10 by 10 squares each spanning 36 by 36 degrees. By predicting the classification of each residue in the protein chain in this map a rough tertiary structure can be deduced. A complete prediction system running on a cluster of workstations and a graphical user interface was developed.
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