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Research background: E-commerce is developing rapidly, especially during the Covid19 pandemic. This fact can benefit individuals who want to sell their already used goods. Importantly, for sellers, it is not always a priority to get the highest price, but sometimes it is simply effective to get rid of the goods at a satisfactory price.

This paper considers feature selection as a problem of an aggregation of three state-of-the-art filtration methods: Pearson’s linear correlation coefficient, the ReliefF algorithm and decision trees. A new wrapper method is proposed which, on the basis of a fusion of the above approaches and the performance of a classifier, is capable of creating a distinct, ordered subset of attributes that is optimal based on the criterion of the highest classification accuracy obtainable by a convolutional neural network. The introduced feature selection uses a weighted ranking criterion. In order to evaluate the effectiveness of the solution, the idea is compared with sequential feature selection methods that are widely known and used wrapper approaches. Additionally, to emphasize the need for dimensionality reduction, the results obtained on all attributes are shown. The verification of the outcomes is presented in the classification tasks of repository data sets that are characterized by a high dimensionality. The presented conclusions confirm that it is worth seeking new solutions that are able to provide a better classification result while reducing the number of input features.

The aim of the article is to evaluate changes in the perception of advantages and disadvantages of contactless payments by a specific group of users. Young and well-educated people were considered to be an interesting research group. The presented analysis was made from the perspective of three points in time the first point was the end of 2011, the second turn of 2015/2016, and finally the third beginning of 2018. The research tool was an online survey. The research material was subjected to statistical assessment. The conducted research has shown that within a decade from the introduction of contactless payments in Poland, these payments became something obvious for a group of young people and more importantly something they regularly use. The knowledge about the concept of contactless payments is supported by the relatively high general knowledge of the technical aspect of making payments. Interestingly, gaps in knowledge correspond perfectly with security concerns there are still serious concerns about not only the act of making contactless payments, but also those related to the storage of the payment instrument.

Artificial Intelligence (AI) and Internet of Things (IoT) are those which will bring a bright future for sustainable development by reducing an unsustainability that disturbs societies, environment, and natural resources. The rapid and multidisciplinary AI and IoT evolution, the relative novelty of the concept itself and little literature concerning their role in sustainable development goals achieving, present an area for further research. Our aim is to research AI and IoT potential and risk for reaching sustainable development, focusing on a job market. We conducted a bibliometric analysis concerning these technologies impact on sustainable development goals achieving, especially technical factors and labor market impact. Results proved that AI and IoT massive deployment brings real threats, still, opportunities and possible benefits that are sought overbalance potential risks.

The anatomy, function and embryonic development of the heart have been of interest to clinicians and researchers alike for centuries. A beating heart is one of the key criteria in defining life or death in humans. An understanding of the multitude of genetic and functional elements that interplay to form such a complex organ is slowly evolving with new genetic, molecular and experimental techniques. Despite the need for ever more complex molecular techniques some of our biggest leaps in knowledge come from nature itself through observations of mutations that create natural defects in function. Such a natural mutation is found in the Mexican axolotl, Ambystoma mexicanum. It is a facultative neotenous salamander well studied for its ability to regenerate severed limbs and tail. Interestingly it also well suited to studying segmental heart development and differential sarcomere protein expression due to a naturally occurring mendelian recessive mutation in cardiac mutant gene “c”. The resultant mutants are identified by their failure to beat and can be studied for extended periods before they finally die due to lack of circulation. Studies have shown a differential expression of tropomyosin between the conus and the ventricle indicating two different cardiac segments. Tropomyosin protein, but not its transcript have been found to be deficient in mutant ventricles and sarcomere formation can be rescued by the addition of TM protein or cDNA. Although once thought to be due to endoderm induction our findings indicate a translational regulatory mechanism that may ultimately control the level of tropomyosin protein in axolotl hearts.