Julia Sikorska, Maciej Trojan, Anna Jakucińska and Dominika Farley
Research on prosocial behaviors in primates often relies on the two-choice paradigm. Motoric lateralization is a surprisingly big problem in this field of research research, as it may influence which lever will ultimately be chosen by the actor. The results of lateralization studies on primates do not form a clear picture of that phenomenon, which makes it difficult to address the problem during research. The authors discuss possible ways of managing this confounding variable.
Anna Predko-Maliszewska, Agnieszka Predko-Engel and Maciej Goliński
This article describes methods used in estimating skeletal age based both on the evaluation of skeletal maturation of the palm and the wrist (Greulich and Pyle’s atlas method) and the Cervical Vertebral Maturation method (CVM). The method of evaluating the skeletal age based on the measurement of cervical vertebrae with equations introduced by A. Machorowska-Pieniążek is also mentioned. The article shows results obtained by computer analysis of the age of cervical vertebrae compared to the results gained from the implemented equations provided by A. Machorowska-Pieniążek and the results obtained from the atlas method.
Magda Żołubak, Aleksandra Kawala-Janik, Michał Podpora, Mariusz Pelc and Wojciech Skowron
Chemotherapy is one of the most common treatments used in cancer therapy despite its serious side effects, which remain a huge concern. To the most common side effects (apart from weight and hair loss) include memory and concentration problems as well as changes in taste. This paper presents a very preliminary study (with only one elderly female subject participating) focusing on cognitive dysfunction after chemotherapy in breast cancer. This phenomenon, called Cancer-Related Cognitive Dysfunction (CRCD), is a frequent occurrence. The obtained results prove the impact of chemotherapy on the participant’s ability to concentrate. The QEEG method and digital data analysis were used as the measurement methods.
The aim of this paper is to verify whether step aerobics training (SAT) has an impact on the temperature of deep muscles of the spine of young, healthy subjects and if there exists a relationship between the maximal oxygen uptake (VO2max) and thermal results. The study was conducted in a group of 21 subjects of both sexes, aged 20.2 ± 0.38. The step aerobics training sessions lasted 30 weeks, one training session per week, 60 minutes per session. Thermograms of the spine were taken with the use of an infrared thermographic camera. Instrumental measurements included BMI, vital capacity of the lungs, and maximal oxygen uptake (VO2max). After a 30-weeklong SAT, a statistically significant increase in the average temperature of the muscles of the thoracic and lumbar spine was observed in subjects of both sexes (1.2◦C and 1.28◦C, respectively, p < 0.05). At the same time, VO2max increased from 42.98 ml/kg/min to 43.6 ml/kg/min in male subjects and from 40.4 ml/kg/min to 41.1 ml/kg/min in female subjects (p > 0.05). The relationship between VO2max and temperature of the muscles of the thoracic and lumbar spine after the 30th SAT was not statistically significant (r = - 0.28; p = 0.226; r = - 0.11; p = 0.634, respectively). The study showed that a 30-weeklong step aerobics training (SAT) had a positive impact on thermoregulation of apparently healthy male and female subjects aged 20. Furthermore, it can be safely assumed that thermography may be used as a non-invasive method of examination of the thermoregulation mechanism of SAT participants.
Parkinson’s Disease can be treated with the use of microelectrode recording and stimulation. This paper presents a data stream classifier that analyses raw data from micro-electrodes and decides whether the measurements were taken from the subthalamic nucleus (STN) or not. The novelty of the proposed approach is based on the fact that distances based on raw data are used. Two distances are investigated in this paper, i.e. Normalized Compression Distance (NCD) and Lempel-Ziv Jaccard Distance (LZJD). No new features needed to be extracted due to the fact that in the case of high-dimensional data the process is extremely time-consuming. The k-nearest neighbour (k-NN) was chosen as the classifier due to its simplicity, which is essential in data stream classification. Results obtained from classifiers based on k-NN: k-NN, k-NN were compared with Probabilistic Approximate Window (k-NN with PAW); k-NN with Probabilistic Approximate Window and Adaptive Windowing (k-NN with PAW and ADWIN); and Self Adjusting Memory k-NN (SAM k-NN), which use the proposed distances, with the performance of the same classifiers but using standard Euclidean distance. Prequential accuracy was chosen as the performance measure. The results of the experiments performed with the described approach are in most cases better, i.e. the performance measures for kNN classifiers that use NCD and LZJD distances are better by up to 8.5 per cent and 14 per cent, respectively. Moreover, the proposed approach performs better when compared with other stream classification algorithms, i.e. Hoeffding Tree, Naive Bayes, and Leveraging Bagging. In the discussed case, an improvement of classification rate of up to 17.9 per cent when using Lempel-Ziv Jaccard Distance instead of the Euclidean was noted.
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