Media has become a common platform for communication as a tool of offense. English language has many insult words which are commonly used in the world of media. This study investigates the socio-pragmatic aspect of insulting in English news. It aims at identifying and analysing insult words and expressions used by news presenters. To specify the problem of the study, language has a harmful power that hurts the addressees and seriously harm their psychological well-being. The insulting words that are an element of all human languages are the source of this abusive power. The study questions sought to find out are if news presenters use insult words, which insult words, and in what social contexts. In this study, the descriptive method is used to describe the language of insult as it is used by some English news media, namely, ITV News and BBC News .The study is conducted by performing a socio-pragmatic analysis based on some contexts of English news. This study gives a BBC model of insulting language that reveals moments of highly emotional reality. The findings reveal that the use of insult words sometimes embodies a sense of personal hatred as in 'gleeful'. Moreover, the insulting words sometimes reflect racial content as in 'nigger'. It is also found that the wrong use of some positive words leads to an offense as in ‘wheelchair bound’. The presented model also conveys its social and pragmatic significance and offers a specific illustration of derogatory language.
The aim of this study is to find a relationship between oxidative stress and adiponectin in Iraqi patients with acromegaly. The present study included 30 patients with acromegaly disease attending at Al-Yarmuk teaching hospital , and 30 healthy individuals as a control group.The two groups with ages ranging (30-55) years. The results revealed a highly significant elevation in all parameters (GH,IGF-1 , adiponectin , malondialdehyde , and peroxynitrite ) levels in sera of patients when compared with healthy control .It can be concluded that oxidative stress (malondialdehyde and peroxynitrite ) may be valuable in detecting of endocrine diseases like acromegaly .
Many studies of the relationship between COVID-19 and different factors have been conducted since the beginning of the corona pandemic. The relationship between COVID-19 and different biomarkers including ABO blood groups, D-dimer, Ferritin and CRP, was examined. Six hundred (600) patients, were included in this trial among them, 324 (56%) females and the rest 276 (46%) were males. The frequencies of blood types A, B, AB, and O were 25.33, 38.00, 31.33, and 5.33%, respectively, in the case group. Association analysis between the ABO blood group and D-dimer, Ferritin and CRP of COVID-19 patients indicated that there was a statistically significant difference for Ferritin (P≤0.01), but no-significant differences for both D-dimer and CRP.
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Abstract- Asymptomatic or clinically silent kidney stones are possibly serious because, in their expected passage, they may cause infection, obstruction and renal impairment. The purpose of this study was to determine the prevalence of silent kidney stones in a sample of Baghdad population and consider how this value could affect the justification for a screening system. To our best knowledge, this is the first study of its kind conducted in Iraq. We investigated 714 consecutive patients who sustained an abdominal ultrasound at our hospital with further kidney screening. All these patients did not have clinical signs and symptoms of nephrolithiasis. Age, sex, the indication for ultrasound, the size, side, and the number of the disco
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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