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Abstract

This paper examines the drivers and the size of the shadow economies of the Czech Republic, Hungary and Poland. It also investigates the tax losses associated with these shadow economic activities in all three countries. The Multiple Indicators and Multiple Causes (MIMIC) model is applied and uses time series data covering the period 1990–2019. The key findings show that the sizes of the shadow economies of the Czech Republic, Hungary and Poland are 10.44, 11.18 and 20.47% respectively. The results also show that the average size of the shadow economies between 1990–2019 was 14.92% in the Czech Republic, 18.72% in Hungary and 22.85% in Poland. The Czech Republic loses 3.13% of tax revenue from goods and services and 2.83% from incomes and profits as a result of the shadow economy, while Hungary loses 5.05% of tax revenue from goods and services and 1.68% from incomes and profits. Poland loses 5.25% of tax revenue from goods and services and 4.34% from incomes and profits.

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This article offers an overview of the birth and the publication output of Across Languages and Cultures: A Multidisciplinary Journal for Translation and Interpreting Studies spanning the period between 2000 and the present day. It presents the circumstances and the aims of its creation and, based on the results of a thorough bibliometric analysis, it reveals how the journal has evolved into a Q1 international journal of Translation Studies through publishing individual as well as collaborative research conducted internationally. The analyses present the activity of the journal dominantly (but not exclusively) in figures, relating to the number and the lengths of the articles it publishes, its authorship, the countries where its authors work and its citations. The second part of the study reveals the main focuses, themes and languages of inquiry as reflected by the most frequently used words and expressions in the titles, abstracts and the lists of keywords of the articles. The paper ends by demonstrating the ways in which the journal has contributed to furthering and shaping translation research in Hungary, Europe and worldwide.

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Abstract

Infections caused by carbapenem-resistant Enterobacterales (CRE) present an important therapeutic problem, as there are limited number of effective therapeutic alternatives available. In this study, phenotypic and genotypic methods were used to characterize carbapenemase-production and other resistance-determinants (AmpC and ESBL-production, efflux pump-overexpression) in 50 isolates (Klebsiella spp. n = 35, Escherichia coli n = 12 and Enterobacter cloacae complex n = 3) collected at the Albert Szent-Györgyi Clinical Center (University of Szeged) between 2014 and 2017. Minimum inhibitory concentrations of meropenem, sulfamethoxazole/trimethoprim, tigecycline, amikacin, moxifloxacin, colistin and fosfomycin were also determined. 24% of isolates were AmpC-producers, while 30% carried bla CTX-M ESBL-genes. Carbapenemase-genes were detected in 18 (36%) of the tested isolates: in 2 isolates bla NDM, in 6 isolates bla OXA-48-like and in 12 isolates, bla VIM was detected by PCR. The species-distribution for isolates positive for carbapenemase-genes was the following: Klebsiella pneumoniae n = 11, Klebsiella oxytoca n = 1, E. coli n = 5, E. cloacae complex n = 1. Efflux pump-overexpression based on the PAβN-screening agar was shown in n = 3 of the tested strains. In nine isolates (18%), carbapenemase and ESBL-genes were detected simultaneously. Highest levels of resistance were noted for fosfomycin (74%) and moxifloxacin (70%), while all isolates were susceptible to colistin. Among applied phenotypic tests in this study the modified carbapenem inactivation method (mCIM) proved to be the most accurate one compared to that of PCR results.

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This study seeks to find a correlation between silent pauses (SPs) in source text and the fluent delivery in target text during these pauses in simultaneous interpreting from Chinese to English. Experiments have been carried out to home in on SPs by speakers to examine exactly what is going on while silences last. Two speech styles of formal speech and spontaneous speech are then taken into consideration to see whether stylistic difference yields different results in the SP–fluency correlation. Two indicators are identified as the factors pointing to the dual effect of SPs: the rate of fluent interpreting during SPs (Indicator One), and the rate of SP-included sentences being successfully interpreted (Indicator Two). Both the concurrent and the continuing effects are proved tenable by looking at the relations between the two indicators and different SP positions and durations. Results indicate that the possibility of both indicators is significantly higher during speakers’ pauses at grammatical junctures; Indicator One is more pronounced during pauses of medium length while Indicator Two is more pronounced during pauses of longer length. A negative correlation between SP duration and Indicator One is found while a positive correlation between SP duration and Indicator Two is confirmed. Furthermore, this study concludes that speech style does make a difference in the correlation between SP positions and the two indicators: formal speech interpreting shows clearly better regularity than spontaneous speech interpreting.

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This paper is concerned with the following question: to what extent does neural machine translation (NMT) – a relatively new approach to machine translation (MT), which can draw on richer contextual information than previous MT architectures – perform explicitation shifts in translation and how are these shifts realised in linguistic terms? In order to answer this question, the paper attempts to identify instances of explicitation in the machine-translated version of a research report on carbon dioxide capture and storage. The machine-translated text was created using the publicly available generic NMT system DeepL. The human translation of the research report was analysed in a prior research project for instances of explicitation and implicitation (Krüger 2015). After a brief quantitative di scussion of the frequency and distribution of explicitation shifts identified in the DeepL output as compared to the shifts identified in the human translation of the research report, the paper analyses in detail several examples in which DeepL performed explicitation shifts of various kinds. The quantitative and qualitative analyses are intended to yield a tentative picture of the capacity of state-of-the art neural machine translation systems to perform explicitation shifts in translation. As explicitation is understood in this article as an indicator of translational text–context interaction, the explicitation performance of NMT can – to some extent – be taken to be indicative of the “contextual awareness” of this new MT architecture.

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Acta Oeconomica
Authors: Mirjana Gligorić Matić, Biljana Jovanović Gavrilović and Nenad Stanišić

Abstract

After Second World War (WWII) a true evolution in understanding of economic development happened, which affected the ways of measuring prosperity, i.e. perceiving changes in people’s welfare. Numerous indicators have been created, which go ‘beyond GDP’ and cover different aspects of development and well-being. The aim of this paper is to analyse prosperity convergence in 32 European countries with a composite indicator – Legatum Prosperity Index (LPI). LPI is more complete than other indicators used in convergence analysis and reflects multidimensional nature of modern development and prosperity. Our research of absolute beta convergence is based on cross-sectional and panel data. Results indicate the existence of convergence in the overall index and its constitutive parts – dimensions and pillars, with different convergence speed regarding LPI and its segments for the total sample of countries, as well as for the countries of Eastern and Western Europe.

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