Volume 15, Issue 2

The uncanny valley (UV) hypothesis suggests that the observation of almost human-like characters causes an increase of discomfort. We conducted a study using self-report questionnaire, response time measurement, and electrodermal activity (EDA) evaluation. In the study, 12 computer-generated characters (robots, androids, animated, and human characters) were presented to 33 people (17 women) to (1) test the effect of a background context on the perception of characters, (2) establish whether there is a relation between declared feelings and physiological arousal, and (3) detect the valley of the presented stimuli. The findings provide support for reverse relation between human-likeness and the arousal (EDA). Furthermore, a positive correlation between EDA and human-likeness appraisal reaction time upholds one of the most common explanations of the UV – the categorization ambiguity. The absence of the significant relationship between declared comfort and EDA advocates the necessity of physiological measures for UV studies.

Non-stationarity of electroencephalogram (EEG) signals greatly affect classifier performance in brain-computer interface (BCI). To overcome this problem we propose an adaptive classifier model known as extended multi-class pooled mean linear discriminant analysis (EMPMLDA). Here, we update the average class pair co-variance matrix along with pooled mean values. Evaluation of classifiers are done on visual evoked cortical potential data-sets. We demonstrate that EMPMLDA can significantly outperform other static classifiers such as MLDA and adaptive classifiers (MPMLDA). Furthermore an optimal update coefficient can be achieved using different datasets.

Research regarding players’ behavior, choices they make, strategies they employ, and how they communicate with each other during the play is the subject of scientific interest for a long time. This calls for creation of tools that could be used during such a research. Given the increased involvement of serious games in scientific projects, usage of a serious game as a tool for gathering and analyzing a player’s behavioral pattern, appears to be a reasonable choice. This paper describes the development process of a serious game in the form of a two-player strategy, which uses subversive mechanics in order to encourage users to reinterpret their approach to conflict-cooperation strategies. Its further aim is to analyze data regarding players’ choices, gathered by the game, and contents of questionnaires filled by the players participating in the project.

The aim of the work is to assess the use of LEGO-based robotics in the education of medical students. Training on specialized robotic surgery simulators is available only to a small group of specialists. The LEGO Mindstorms was used to create a model of the surgical robot arm. The model is controlled by a specially prepared panel created in the LabVIEW. The functionality of the model of a surgical robot arm allows people who have not been using these robots to become familiar with the basics of their operation. Medical students using the arm will be able to observe structural problems: the stiffness of construction, or its utility, the range of movements and its limitations, motion and force control using different robotic manipulators. The use of a modular computer programming language and a modular building platform problem in LEGO Education contributes to the development of critical thinking and problem solving, and these skills are useful to physicians during their work.

The structural transition from the globular to the amyloid form of proteins requires aggregation-promoting conditions. The protein example of this category is acylphosphatase from the hyperthermophile Sulfolobus solfataricus . This protein represents a structure with a well-defined hydrophobic core. This is why the complexation (including oligomerization) of this protein is of low probability. The chain fragment participating in aggregation in comparison to the status with respect to the fuzzy oil drop model is discussed in this paper.