Since 1996, the Turopolje pig is recognised as a Croatian autochthonous extensive pig breed and was include in program of "in situ" preservation. The purpose of this paper was to analyze the changes in breeding population of Turopolje pig in relation to re productive traits and brucellosis outbreaks. 529 liters from 388 sows were analysed in the period from 2000 to 2 009. In average 1.2 liters/sow/year were observed with 4.21 and 3.90 piglets born alive and weaned per litter, respectively. Mortality rate during the weaning period was close to 20%. In the period from 1996 to 2009 the size of breeding population was increased more than ten times in the number of sows and five times in the number of boars. In 2008, the numbers of sows and boars decreased about 21% in relation to 2 007, primarily due to an outbreak of brucellosis. In average 44.2% and 30.1% of tested pigs during 2008 and 2009 were serologically positive to Brucella suis infection and were excluded from population. These results suggest requirements to increase the number of litters per year and survival of pigs born alive due to changes in Turopolje pig production system and development of a health monitoring program.

This study aims to quantify the heterogeneity of tumour enhancement in dynamic contrast-enhanced MRI (DCE-MRI) using texture analysis methods. The suitability of the coherence and the fractal dimension to monitor tumour response was evaluated in 18 patients with limb sarcomas imaged by DCE-MRI pre- and post-treatment. According to the histopathology, tumours were classified into responders and non-responders. Pharmacokinetic (Ktrans) and heuristic model-based parametric maps (slope, max enhancement, AUC) were computed from the DCE-MRI data. A substantial correlation was found between the pharmacokinetic and heuristic model-based parametric maps: ρ = 0.56 for the slope, ρ = 0.44 for maximum enhancement, and ρ = 0.61 for AUC. From all four parametric maps, the enhancing fraction, and the heterogeneity features (i.e. coherence and fractal dimension) were determined. In terms of monitoring tumour response, using both pre- and post-treatment DCE-MRI, the enhancing fraction and the coherence showed significant differences between the response group and the non-response group (i.e. the highest sensitivity (91%) for Ktrans, and the highest specificity (83%) for max enhancement). In terms of treatment prediction, using solely the pre-treatment DCE-MRI, the enhancing fraction and coherence discriminated between responders and non-responders. For prediction, the highest sensitivity (91%) was shared by Ktrans, slope and max enhancement, and the highest specificity (71%) was achieved by Ktrans. On average, tumours that responded showed a high enhancing fraction and high coherence on the pre-treatment scan. These results suggest that specific heterogeneity features, computed from both pharmacokinetic and heuristic model-based parametric maps, show potential as a biomarker for monitoring tumour response.

In this paper the probability density function of the Switch and Stay Combiner (SSC) output signal at one time instant and the joint probability density function of the SSC combiner output signal at two time instants, in the presence of log-normal fading, are determined in the closed form expressions. The results are shown graphically for different variance values and decision threshold values. If the digital telecommunication systems work on the manner described in this paper, the error probability will be significantly reduced. Ill. 6, bibl. 24 (in English; abstracts in English and Lithuanian). http://dx.doi.org/10.5755/j01.eee.109.3.161