Humans rely on a finely tuned ability to recognize and adapt to socially relevant patterns in their everyday face-to-face interactions. This allows them to anticipate the actions of others, coordinate their behaviors, and create shared meaning-to communicate. Social robots must likewise be able to recognize and perform relevant social patterns, including interactional synchrony, imitation, and particular sequences of behaviors. We use existing empirical work in the social sciences and observations of human interaction to develop nonverbal interactive capabilities for a robot in the context of shadow puppet play, where people interact through shadows of hands cast against a wall. We show how information theoretic quantities can be used to model interaction between humans and to generate interactive controllers for a robot. Finally, we evaluate the resulting model in an embodied human-robot interaction study. We show the benefit of modeling interaction as a joint process rather than modeling individual agents.

Annular pancreas is a rare embryonal abnormality. Its manifestation in adulthood is often pinpointed with a substantial delay, which is most often attributed to pancreatitis, biliary pathology or dyspepsia. We present a case of a 28-year-old woman who had exacerbating symptoms of high bowel obstruction from 20th week of pregnancy, progressing after premature delivery. Diagnostic work-up revealed partial annular pancreas compressing the duodenum. Despite attempts of conservative treatment, her state deteriorated to such an extent that surgery was indicated and gastrojejunal bypass created. Her postoperative recovery was uneventful. In cases in which symptoms of high bowel obstruction in pregnancy persist and prostration occurs, we suggest close monitoring and a more thorough diagnostic approach. The question remains whether annular pancreas presents a cause of pathologic findings, a cofactor, or a mere accidental diagnosis in the development of superposed pathologies.

Among other symptoms, multiple sclerosis can also produce symptoms of affective and cognitive disorders. The majority of patients have certain cognitive dysfunctions, and the' most common affective disorder is reactive depression. The aim of the study was to determine the correlation of the Mini-Mental State (MMS) and Beck Depression Inventory (BDI) scale scores with the Expanded Disability Status Scale (EDSS) score in patients with multiple sclerosis treated at University Department of Neurology, Sarajevo University Clinical Center in Sarajevo. We evaluated 50 randomly selected patients with various types of multiple sclerosis using the MMS, BDI and EDSS instruments. The study included 33 women and 17 men (66% : 34%), mean age 40.74 years (SD 9.236). The mean value of EDSS score was 3.98, ranging from 1.0 to 8.5 in women and from 1.0 to 6.5 in men. BDI scale scores showed a mean value of 12.56. The mean MMS score in baseline sample was 26.88. Statistically significant positive correlation was found between age and EDSS score, and negative correlation between EDSS and MMS, as well as between BDI and MMS. Study results indicated older patients with multiple sclerosis to have a higher EDSS score with more pronounced cognitive disturbances. There was no statistically significant correlation between EDSS score and depression.

In this work, microcalorimetric technique was used to analyze Pb(II) toxic action on the metabolic activities of Candida humicola and Bacillus subtilis. The experimental results revealed that Pb(II) had a stimulating effect on C. humicola and B. subtilis growth at a relatively low concentration (10.0 g·mL−1); while, C. humicola and B. subtilis were inhibited completely when the concentrations were up to 320.0 and 160.0 g·mL−1, respectively, and the relationships between growth rate constant (k) and doses of Pb(II) were approximately linear for the two microbes at certain concerntrations. At the same time, their cell dry weight and turbidity (OD600) during growth were also obtained. Their thermogenic curves of the growth coincided well with their turbidity curves, elucidating that the microcalorimetric method agreed with the routine microbiology methods. All of these corroborate the validity and sensitivity of the microcalorimetric technique to investigate the toxic effect of Pb(II) on soil microorganisms.

In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513.