Финансовая грамотность людей предпенсионного возраста как инструмент повышения их благосостояния

Объект исследования: социально-экономические процессы, имеющие причинно-следственные связи с финансовой грамотностью граждан предпенсионного возраста. Предмет исследования: система отношений, возникающих в процессе формирования финансовой грамотности граждан предпенсионного возраста. Цель работы: критический анализ современного опыта формирования финансовой грамотности людей предпенсионного возраста и разработка рекомендаций по повышению ее уровня. Практическая значимость работы заключается в перспективах практического применении предлагаемых рекомендаций, направленных на повышение финансовой грамотности граждан предпенсионного возраста.Object of research: are socio-economic processes that have causal relationships with the financial literacy of citizens of pre-retirement age. The subject of the research is: the system of relations arising in the process of forming the financial literacy of citizens of pre-retirement age. The purpose of the final qualification work: a critical analysis of the modern experience in the formation of financial literacy of people of pre-retirement age and the development of recommendations for increasing its level. The practical significance of the work lies in the prospects for the practical application of the proposed recommendations aimed at increasing the financial literacy of citizens

Element specific X-ray fluorescene microtomography

X-ray fluorescence is widely known as an element-specific scanning analytic tool. It is used in many fields of science and technology and has given major new insights into different problems. The relatively large penetration depth of x rays into matter makes them ideally suited for tomography. The combination of x-ray fluorescence analysis and scanning microtomography, hereafter called x-ray fluorescence microtomography, has been further developed and improved in this work. Employing the newly developed refractive x-ray lenses at a third generation synchrotron source the spatial resolution of this technique could be reduce to a micrometer. The fluorescence radiation that leaves the sample and can be detected from outside suffers absorption on its way to the detector. This problem of absorption is treated in this work, too and technical improvements of the setup are outlined. These improvements reduce the absorption of the fluorescence radiation. This in turn improves the signal to noise ratio of the fluorescence radiation and lowers the detection limit. Moreover, a tomographic reconstruction algorithm is described which is especially designed for x-ray fluorescence tomography. This algorithm takes into account the absorption of the fluorescence radiation within the sample. Some example applications are described to illustrate the success and power of this method as well as its advantages over other microanalytic methods. Also, the possible use of x-ray fluorescence microtomography in a laboratory is assessed. Besides this, the work briefly introduces into interactions of x rays with matter, into the concepts of the detectors that were used, and into the working principle of the refractive lenses

Discovering frequent patterns to bootstrap trust

Due to copyright restrictions, the access to the full text of this article is only available via subscription.When a new agent enters to an open multiagent system, bootstrapping its trust becomes a challenge because of the lack of any direct or reputational evidence. To get around this problem, existing approaches assume the same a priori trust for all newcomers. However, assuming the same a priori trust for all agents may lead to other problems like whitewashing. In this paper, we leverage graph mining and knowledge representation to estimate a priori trust for agents. For this purpose, our approach first discovers significant patterns that may be used to characterise trustworthy and untrustworthy agents. Then, these patterns are used as features to train a regression model to estimate trustworthiness. Lastly, a priori trust for newcomers are estimated using the discovered features based on the trained model. Through extensive simulations, we have showed that the proposed approach significantly outperforms existing approaches