115 research outputs found
Maintaining Nursing Knowledge Using Bibliographic Management Software
No full textKEY POINTS• To engage in evidence-based practice, perioperative nurses should be regularlyaccessing literature on pertinent practice subjects.• Use of bibliographic management software can help nurses sift through databases tofind literature content that meets their needs.NOTICE: this is the author’s version of a work that was accepted for publication in Perioperative Nursing Clinics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Perioperative Nursing Clinics vol. 7, no. 2 (June 2012), doi:10.1016/j.cpen.2012.02.004.Peer reviewe
Selected motivational aspects of medicinal plants names’ in Polish and Russian: names of plants motivated by environmental conditions
No full textWanda Stec, GdańskThe paper refers to the issue of medicinal plants, their names and motivation.
Linguistic nomination of the discussed group – with environmental conditions as
motivational factors – is illustrated with numerous Polish and Russian examples
(both botanical and common names), as well as Latin ones (scientific names). The
author believes that the choice of a nomination model is not fortuitous. Specific
features of plants and places where they grow influence word formation processes
and provide information about the plant species in [email protected]
„Mylące” nazwy roślin leczniczych w języku polskim i rosyjskim
No full textWanda Stec
Uniwersytet Gdański, Gdańsk, Poland
[email protected]
Наименования лекарственных растений обычно обладают четкой семантической мотивацией, указывающей на отличительные черты десигнатов. информация, содер-жащаяся в наименованиях, по принципу, должна соответствовать истине, т.е. отражать наблюдаемые и именуемые реалии внеязыковой действительности. однако названия могут вводить в заблуждение, вызывая ошибочные представления о географическом происхождении растений, или наводя на неверную мысль об их полезных свойствах, в том числе о воздействии, оказываемом на человека. наименования также могут ошибочно ассоциироваться с точки зрения современного состояния языка, либо по-разному истолковываться этимологами. повсеместное использование типичными носителями языка некоторых названий по отношению к определенным видам рас-тений не исключает их «неверности» с точки зрения ботаники. в статье на примерах «вводящих в заблуждение» (иногда с виду) наименований на польском и русском, а также латинском языках, представлено явление и предпринята попытка установить причины «правды»/«неправды» в языковой номинации лекарственных растений.
The names of medicinal plants are usually distinguished by clear semantic motivation, thus indicating their characteristic features. The information contained in the names of medicinal plants should, as a matter of principle, comply with the concept of truth: i.e. conform to an observable and denominated reality. Nevertheless, such names may be misleading, resulting in erroneous views regarding the geographical origins of a plant or its useful characteristics (including its influence upon people). These names may also give rise to inappropriate as-sociations from the perspective of contemporary language, and be interpreted in different ways by etymologists. Although average language users may name certain plant species in a particular way, these names may nonetheless be ‘untrue’ from a botanical standpoint. This article attempts to outline the ‘true/untrue’ aspect of medicinal plants’ linguistic nomination, as well as to determine the reasons for this phenomenon. Various Polish, Russian and Latin names (which are ‘misleading’, but sometimes only apparently), are used for the purpose of the discussion
Innovation in European Union Countries
No full textThe paper sets out to evaluate the innovativeness of European Union member states and determine Poland’s standing in a league table of EU economies in terms of innovation. The analysis is based on innovation indices reported by the European Commission, specifically the European Innovation Scoreboard (EIS) for 2004-2008 and the Summary Innovation Index (SII). The author determines the innovation scores of individual countries by calculating a 2004-2008 summary innovation index for EU members using a method based on Z. Hellwig’s development model.The results are compared against those quoted in European Commission reports. The research showed that both the method proposed by the European Commission and the Hellwig development model can be used to measure innovation in EU countries, Stec says. This is confirmed by a high level of correlation between the results as reflected by Spearman’s rank correlation coefficient. The author compares Poland with other EU economies in terms of innovation. This comparison reveals that the Polish economy is still at an early stage of innovation, Stec says. In the EIS, Poland was classified among catching-up economies, and in Hellwig’s method it was grouped together with countries with a low level of innovation. The author also analyzes the strengths and weaknesses of the Polish economy in terms of innovation
Innowacyjność krajów Unii Europejskiej
No full textThe paper sets out to evaluate the innovativeness of European Union member states and determine Poland’s standing in a league table of EU economies in terms of innovation. The analysis is based on innovation indices reported by the European Commission, specifically the European Innovation Scoreboard (EIS) for 2004-2008 and the Summary Innovation Index (SII). The author determines the innovation scores of individual countries by calculating a 2004-2008 summary innovation index for EU members using a method based on Z. Hellwig’s development model.The results are compared against those quoted in European Commission reports. The research showed that both the method proposed by the European Commission and the Hellwig development model can be used to measure innovation in EU countries, Stec says. This is confirmed by a high level of correlation between the results as reflected by Spearman’s rank correlation coefficient. The author compares Poland with other EU economies in terms of innovation. This comparison reveals that the Polish economy is still at an early stage of innovation, Stec says. In the EIS, Poland was classified among catching-up economies, and in Hellwig’s method it was grouped together with countries with a low level of innovation. The author also analyzes the strengths and weaknesses of the Polish economy in terms of innovation
Postrzeganie trujących roślin leczniczych przez pryzmat ich nazw (na przykładzie nazewnictwa polskiego i rosyjskiego)
No full textBotanical names reflect how people perceive, interpret, and categorize the world of plants from the linguistic point of view. The article aims to demonstrate how the image of plants that are poisonous and, at the same time, used in medicinal treatment is shaped by their denomination. The author analyzes the motivations for nomenclature on the examples of common and folk names in Polish and Russian, against the background of the international Latin botanical nomenclature. In the process of linguistic nomination of poisonous medicinal plants, the criteria which are taken into account are both objective, based on knowledge, observation, and experience, as well as subjective, based on evaluation and associations. The names do not always reflect the plants’ harmful impact on people because their remaining properties might have prevailed during the linguistic nomination process
Interferencja w przekładzie jako skutek wzajemnych oddziaływań języków (na przykładzie tłumaczeń tekstów z zakresu prawa w parze językowej polski–rosyjski)
No full textThis article considers the issue of language transfer in translation. External interference is one of the most common reasons behind the lack of equivalence between the source text and the target text. Negative transfer leads to the lack of linguistic correctness as well as to modifying or altering the meaning of the translated text. In the didactics of translation, the rationale behind identifying and analysing linguistic errors is to develop and improve translation skills. The issue in focus is presented based on translations of legal texts in the Polish–Russian language pair.W tekście przedstawiono zagadnienia transferu językowego w przekładzie. Interferencja zewnętrzna uważana jest za jedną z podstawowych przyczyn zakłócenia ekwiwalencji między tekstem źródłowym a docelowym tłumaczenia. Transfer negatywny przyczynia się do braku poprawności językowej, modyfikacji czy zmiany sensu w przetłumaczonym tekście. W dydaktyce przekładu identyfikacja i analiza błędów służą wyrobieniu i doskonaleniu umiejętności translatorskich. Temat zaprezentowano na materiale tłumaczeń prawniczych w parze językowej polski–rosyjski
Ranking poziomu rozwoju krajów Unii Europejskiej
No full textThe article compares European Union countries in terms of socioeconomic development and determines Poland’s position in the league table. The author uses 29 statistical indicators characterizing different aspects of socioeconomic development in EU countries. The league table was compiled using various multidimensional comparative analysis methods in accordance with a development model proposed by Z. Hellwig. Poland ranks far behind other EU countries in the league table, 23rd or 24th depending on the adopted analysis method. Poland ranks among the top 10 EU countries only in five socioeconomic indicators. Poland’s main advantages include an unpolluted environment, a well-developed higher education system and high-quality farm produce, Stec says. The country’s weaknesses, on the other hand, include a low GDP per capita level, high unemployment, and the need to export hi-tech products. Among the countries that joined the EU together with Poland in May 2004, the Czech Republic, Malta, Slovenia, Hungary, Estonia and Lithuania rank much higher than Poland in the league table
Prevalence and serotypes of Shiga toxinproducing Escherichia coli (STEC) in dairy cattle from Northern Portugal
No full textThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The prevalence of Shiga toxin (Stx)-producing Escherichia coli (STEC) was determined by evaluating its presence in faecal samples from 155 heifers, and 254 dairy cows in 21 farms at North of Portugal sampled between December 2017 and June 2019. The prevalence of STEC in heifers (45%) was significantly higher than in lactating cows (16%) (p 0.05, Fisher exact test statistic value is 0.00001). A total of 133 STEC were isolated, 24 (13.8%) carried Shiga-toxin 1 (stx1) genes, 69 (39.7%) carried Shiga-toxin 2 (stx2) genes, and 40 (23%) carried both stx1 and stx2. Intimin (eae) virulence gene was detected in 29 (21.8%) of the isolates. STEC isolates belonged to 72 different O:H serotypes, comprising 40 O serogroups and 23 H types. The most frequent serotypes were O29:H12 (15%) and O113:H21 (5.2%), found in a large number of farms. Two isolates belonged to the highly virulent serotypes associated with human disease O157:H7 and O26:H11. Many other bovine STEC serotypes founded in this work belonged to serotypes previously described as pathogenic to humans. Thus, this study highlights the need for control strategies that can reduce STEC prevalence at the farm level and, thus, prevent food and environmental contamination.This study was financially supported by: i) project PhageSTEC (POCI-01-0145 -FEDER-
029628) funded by FEDER through COMPETE2020 (Programa Operacional Competitividade e Internacionalização) and by National Funds thought
FCT (Fundação para a Ciência e a Tecnologia); ii) strategic project UIDB/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by FCT under the scope of the European Regional Development Fund (Norte2020
- Programa Operacional Regional do Norte); iii) project PI16/01477 from Plan Estatal de I+D+I 2013-2016, Instituto de Salud Carlos III (ISCIII), Subdirección General de Evaluación y Fomento de la Investigación, Ministerio de Economía y Competitividad (Gobierno de España) and FEDER; and iv) grant ED431C2017/57 from the Consellería
de Cultura, Educación e Ordenación Universitaria, (Xunta de Galicia) and FEDER; UIDB/AGR/04033/2020 by National Funds thought FCT. Author IGM acknowledges the Consellería de Cultura, Educación e Ordenación Universitaria, Xunta de Galicia for the individual grant ED481A-2015/149 and and author SCFS acknowledges the FPU
programme for the individual grant FPU15/02644from the Secretaría General de Universidades, Spanish Ministerio de Educación, Cultura y Deporte. The funders had no role in study design, data collection and analysis, decision to publish, or
preparation of the manuscript.info:eu-repo/semantics/publishedVersio
Comparison of European Union Countries by Development Level
No full textThe article compares European Union countries in terms of socioeconomic development and determines Poland’s position in the league table. The author uses 29 statistical indicators characterizing different aspects of socioeconomic development in EU countries. The league table was compiled using various multidimensional comparative analysis methods in accordance with a development model proposed by Z. Hellwig. Poland ranks far behind other EU countries in the league table, 23rd or 24th depending on the adopted analysis method. Poland ranks among the top 10 EU countries only in five socioeconomic indicators. Poland’s main advantages include an unpolluted environment, a well-developed higher education system and high-quality farm produce, Stec says. The country’s weaknesses, on the other hand, include a low GDP per capita level, high unemployment, and the need to export hi-tech products. Among the countries that joined the EU together with Poland in May 2004, the Czech Republic, Malta, Slovenia, Hungary, Estonia and Lithuania rank much higher than Poland in the league table
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