<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>DSpace Community:</title>
    <link>https://sci.ldubgd.edu.ua/jspui/handle/123456789/69</link>
    <description />
    <pubDate>Sun, 25 Oct 2026 04:54:34 GMT</pubDate>
    <dc:date>2026-10-25T04:54:34Z</dc:date>
    <image>
      <title>DSpace Community:</title>
      <url>http://sci.ldubgd.edu.ua:8080/jspui/retrieve/daa541a0-ad27-4768-9148-d744b9a95bff/кафедра.jpg</url>
      <link>https://sci.ldubgd.edu.ua/jspui/handle/123456789/69</link>
    </image>
    <item>
      <title>Cat tools in teaching specialized translation for civil protection</title>
      <link>https://sci.ldubgd.edu.ua/jspui/handle/123456789/19227</link>
      <description>Title: Cat tools in teaching specialized translation for civil protection
Authors: Kucherenko, Maryna
Abstract: The paper explores the integration of Computer-Assisted Translation (CAT) tools into teaching specialized translation for civil protection. Translators in this field work with documentation from international organizations, such as operational guidelines, emergency response protocols, technical manuals, and safety recommendations, which demands high terminological accuracy and consistency across documents. CAT tools do not replace the translator, unlike machine translation systems. Instead, they help students build professional competencies in terminology management, translation memory use, quality assurance, and post-editing, while strengthening informed translation decision-making. The paper argues for authentic professional materials as the basis for translation tasks, including the IAEA Nuclear Safety and Security Glossary, the WHO Laboratory Biosafety Manual, and NATO documents on CBRN defence. As a practical example, it describes tasks on the MateCat platform: creating a project glossary, working with translation memory matches, and using quality assurance functions to detect terminological inconsistencies. Corpus analysis in Sketch Engine is proposed as a complementary resource for examining terms in context and building reliable termbases. The approach brings classroom instruction closer to real-world translation practice and prepares future translators for work in security-related contexts.</description>
      <pubDate>Sat, 19 Sep 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://sci.ldubgd.edu.ua/jspui/handle/123456789/19227</guid>
      <dc:date>2026-09-19T00:00:00Z</dc:date>
    </item>
    <item>
      <title>Translation transformations in English-Ukrainian rendering of CBRN terminology</title>
      <link>https://sci.ldubgd.edu.ua/jspui/handle/123456789/19226</link>
      <description>Title: Translation transformations in English-Ukrainian rendering of CBRN terminology
Authors: Kucherenko, Maryna
Abstract: The paper examines translation transformations used in the English-Ukrainian rendering of CBRN (chemical, biological, radiological, and nuclear) defense terminology. Its relevance stems from Ukraine’s integration into Euro-Atlantic security structures, which requires harmonizing Ukrainian military-technical terminology with international standards, in particular NATO STANAG. Drawing on Eugene Nida’s distinction between formal correspondence and dynamic equivalence, and on the transformation models of J.-P. Vinay, J. Darbelnet, and V. Karaban, the study analyzes 20 key terminological units selected from the NATO Glossary on CBRN Issues, the FEMA Glossary of Terms, European Commission documentation, and NATO Science for Peace and Security Program reports. The identified shifts are classified into lexical, grammatical, and mixed transformations. Loan translation (calquing) proves to be the dominant technique (40%), driven by interoperability requirements. Direct equivalents account for 20%, descriptive translation for 15%, and transliteration for 10%, while concretization, generalization, and combined transformations each account for 5%. The findings show that adequate rendering of CBRN terminology requires balancing formal accuracy with adaptation to established Ukrainian military terminology.</description>
      <pubDate>Fri, 19 Jun 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://sci.ldubgd.edu.ua/jspui/handle/123456789/19226</guid>
      <dc:date>2026-06-19T00:00:00Z</dc:date>
    </item>
    <item>
      <title>AI-POWERED CHATBOTS AS TEACHING ASSISTANTS IN EFL  CLASSROOMS: OPPORTUNITIES AND CHALLENGES</title>
      <link>https://sci.ldubgd.edu.ua/jspui/handle/123456789/19223</link>
      <description>Title: AI-POWERED CHATBOTS AS TEACHING ASSISTANTS IN EFL  CLASSROOMS: OPPORTUNITIES AND CHALLENGES
Authors: Dobrovolska, Svitlana
Abstract: AI chatbots are neither a revolution nor a threat — they are a tool, and like any &#xD;
tool, their value depends entirely on how thoughtfully they are used. In my &#xD;
experience, the most effective approach is to treat them as preparation for class rather &#xD;
than a replacement for it: students use AI to practice, draft, and explore, and then bring &#xD;
that work into the human space of the classroom for real discussion, critique, and &#xD;
refinement. What is needed now is not more enthusiasm about AI, but more honest, &#xD;
practice-based research — particularly from non-anglophone educational contexts like &#xD;
Ukraine — on what these tools actually produce in terms of long-term language &#xD;
development.
Description: Research and Education in a Globalized world: European integration processes. Contemporary &#xD;
challenges and transformations : Book of papers of the International Forum for Young Researchers, &#xD;
Kharkiv, April 24, 2026 / O. M. Beketov National University of Urban Econоmy in Kharkiv, &#xD;
TESOL-Ukraine [and oth.]. – Kharkiv : O. M. Beketov NUUE in Kharkiv, 2026. – 409 p.</description>
      <pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://sci.ldubgd.edu.ua/jspui/handle/123456789/19223</guid>
      <dc:date>2026-04-24T00:00:00Z</dc:date>
    </item>
    <item>
      <title>THE STRATEGIC DIMENSION OF HOSTILE LANGUAGE: LINGUISTIC  MECHANISMS OF IMPLEMENTATION AND CLASSIFICATION</title>
      <link>https://sci.ldubgd.edu.ua/jspui/handle/123456789/19222</link>
      <description>Title: THE STRATEGIC DIMENSION OF HOSTILE LANGUAGE: LINGUISTIC  MECHANISMS OF IMPLEMENTATION AND CLASSIFICATION
Authors: Dobrovolska, Svitlana
Abstract: The aim of this paper is to take a close look at communicative strategies and &#xD;
tactics as the core tools through which hate speech operates, to review the ways &#xD;
researchers have defined and categorized them, and to make the case for the &#xD;
classification model that works best for practical analysis of hate speech in discourse.</description>
      <pubDate>Fri, 17 Apr 2026 00:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://sci.ldubgd.edu.ua/jspui/handle/123456789/19222</guid>
      <dc:date>2026-04-17T00:00:00Z</dc:date>
    </item>
  </channel>
</rss>

