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—In this paper, we introduce a novel approach to time-series prediction realized both at the linguistic and numerical level. It exploits fuzzy cognitive maps (FCMs) along with a recently proposed learning method that takes advantage of real-coded genetic algorithms. FCMs are used for modeling and qualitative analysis of dynamic systems. Within the framework(More)
MOTIVATION Intrinsically disordered proteins play a crucial role in numerous regulatory processes. Their abundance and ubiquity combined with a relatively low quantity of their annotations motivate research toward the development of computational models that predict disordered regions from protein sequences. Although the prediction quality of these methods(More)
Ultrastructural differences between ganglia of the plexus submucosus internus (Meissner; PSI) and plexus submucosus externus (Schabadasch; PSE) are described. Comparison revealed a different glia index (ratio glia per neuron) between the PSE (3:1) and the PSI (1:1), the arrangement of PSI neurons in compartments and the appearance of broad(More)
The presence and topographical distribution of nitrergic neurons in the enteric nervous system (ENS) of the pig small intestine have been investigated by means of nitric oxide synthase (NOS) immunocytochemistry and nicotinamide dinucleotide phosphate diaphorase (NADPHd) histochemistry. Both techniques yielded similar results, thus confirming that within the(More)
Fuzzy cognitive maps (FCMs) are a convenient tool for modeling of dynamic systems by means of concepts connected by cause-effect relationships. The FCM models can be developed either manually (by the experts) or using an automated learning method (from data). Some of the methods from the latter group, including recently proposed Nonlinear Hebbian Learning(More)
Fuzzy cognitive maps (FCMs) are convenient and widely used architectures for modeling dynamic systems, which are characterized by a great deal of flexibility and adaptability. Several recent works in this area concern strategies for the development of FCMs. Although a few fully automated algorithms to learn these models from data have been introduced, the(More)
The stomach, small and large intestine of fetuses at term, of unfed newborns, of suckling, weaning and of adult rats were studied by a combined light (LM) and electron microscope (EM) examination. Neuron-specific enolase was used as a neuronal marker under LM. Zinc-iodide-osmium (ZIO) impregnation was used for a selective staining of neurons and(More)