Влияние уровня образования на неравенство доходов: сравнительный обзор четырнадцати стран Европы

На протяжении десятилетий проблема неравенства доходов и его причин остается в центре внимания исследователей. В данной статье проанализирована связь между неравенством доходов домохозяйств в странах Европы и уровнем образования. Выдвигается гипотеза, предполагающая, что неравенство доходов в разных странах может зависеть от уровня образования семьи. Основная цель данной статьи - объяснить, как уровень образования главы семьи влияет на неравенство доходов в четырнадцати странах Европейского союза. Основными задачами исследования было оценить расхождение в средних доходах выделенных подгрупп домохозяйств и исследовать влияние разницы между этими подгруппами на общее неравенство. Для расчета обобщенной энтропии были проанализированы репрезентативные микроданные, представленные в исследовании «Статистика доходов и условий жизни в EC» (EU-SILC). Полученные результаты свидетельствуют о существенном влиянии уровня образования на неравенство доходов домохозяйств с некоторыми различиями между странами. Исследование также выявило прямую зависимость между долей лиц с самым низким уровнем образования и межгрупповой дифференциацией доходов. Более того, низкий уровень неравенства на границе распределения характерен для большинства стран, в которых высока доля образованных людей. Соответственно, неравенство доходов можно контролировать, развивая систему образования.For years, income inequality and its sources have remained the focus of attention of many researchers. The present article aims to expand and update the knowledge concerning the dimensions of household income inequality in European countries. The paper focuses on the association between the educational attainment and income inequality. It is hypothesised that the different level of income inequality observed in different countries can depend on the educational attainment of the society. Therefore, the main research objective of the article is to explain how the education level of the head of household affects income inequality in fourteen West-EU countries. The analysis also has two empirical aims: to assess the divergence in the mean incomes of the distinguished subgroups of households and to measure how much of the overall inequality can be attributed to the distance between these subgroups rather than to inequalities within them. To this end, the Generalised Entropy measures were applied, using the representative microdata derived from the EU Statistics on Income and Living Conditions (EU-SILC). The obtained results indicate that the education level has a significant impact on the income variability between households, with some differences between countries. The study also revealed that the higher proportion of people with the lowest level of education, the higher inter-group income differentiation. Moreover, the study demonstrates that most countries with a high proportion of well-educated people also show low levels of inequality at the bottom of the distribution.This suggests that income inequality could be controlled through the development of education.Статья подготовлена в рамках исследовательского проекта: Доходы и неравенство доходов европейских домохозяйств (Евростат, № 162/2018-EU-SILC) и основана на данных Евростата, Статистика доходов и условий жизни в EC — EU-SILC CROSS-SECTIONAL UDB 2018 — версия 2019-09. Ответственность за выводы, сделанные на основе данных, полностью лежит на авторах.The article has been prepared as part of the research project: Income and Inequality of Income of European Households (Eurostat, No. 162/2018-EU-SILC) and is based on data from Eurostat, EU Statistics on Income and Living Conditions — EU-SILC CROSS-SECTIONAL UDB 2018 — version 2019-09. The responsibility for all conclusions drawn from the data lies entirely with the authors

Statistical tables ranking algorithm

W artykule przedstawiono algorytm filtrowania danych służący do porządkowania tablic wynikowych. Celem artykułu jest zdefiniowanie miary ilości informacji, tak aby możliwe stało się wyselekcjonowanie takich tablic, które niosą największy ładunek informacyjny - największą ilość informacji. Autorzy skoncentrowali się na badaniu ilości informacji strukturalnej zawartej w tablicach statystycznych. Zadaniem proponowanej miary ilości informacji strukturalnej dostarczanej przez tablice wynikowe jest szeregowanie tych tablic pod względem dostarczanego przez nie ładunku informacyjnego.The proposed article is an attempt to establish an appropriate filtering algorithm. Its purpose is to define the measure or the information amount, so that selection or the tables carrying the largest information load becomes possible. The authors have concentrated on the study of the amount or structural information included in the statistical tables. The purpose of proposed measure or structural information amount is to provide the ranking of the charts as per the supplied information load

Coronaviruses fusion with the membrane and entry to the host cell

Introduction. Coronaviruses (CoVs) are positive-strand RNA viruses with the largest genome among all RNA viruses. They are able to infect many host, such as mammals or birds. Whereas CoVs were identified 1930s, they became known again in 2003 as the agents of the Severe Acute Respiratory Syndrome (SARS). The spike protein is thought to be essential in the process of CoVs entry, because it is associated with the binding to the receptor on the host cell. It is also involved in cell tropism and pathogenesis. Receptor recognition is the crucial step in the infection. CoVs are able to bind a variety of receptors, although the selection of receptor remains unclear. Coronaviruses were initially believed to enter cells by fusion with the plasma membrane. Further studies demonstrated that many of them involve endocytosis through clathrin-dependent, caveolae-dependent, clathrin-independent, as well as caveolae-independent mechanisms. Objectives. The aim of this review is to summarise current knowledge about coronaviruses, focussing especially on CoVs entry into the host cell. Advances in understanding coronaviruses replication strategy and the functioning of the replicative structures are also highlighted. The development of host-directed antiviral therapy seems to be a promising way to treat infections with SARS-CoV or other pathogenic coronaviruses. There is still much to be discovered in the inventory of pro-and anti-viral host factors relevant for CoVs replication. The latest pandemic danger, originating from China, has given our previously prepared work even more of topicality