Worldwide, there is an increased reliance on COVID-19-related health messages to curb the COVID-19 outbreak. Therefore, it is vital to provide a well-prepared and authentic translation of English-language messages to reach culturally and linguistically diverse audiences. However, few studies, if any, focus on how non-English-speaking readers receive and linguistically accept the lexical choices in the messages translated into their language. The present study tested a sample of translated Arabic COVID-19-related texts that were obtained from the World Health Organization and Australian New South Wales Health websites. This study investigated to that extent Arabic readers would receive translated COVID-19 health messages and whether the translation would affect their preparedness to easily accept and their ability to fully comprehend the messages in terms of the used lexical items. The survey-based research also explored the translation process and methods that would best ensure the messages would reach the target audience with the least loss of meaning. The study concluded that some acceptability issues and comprehensibility failure were detected in the available translated versions as a result of improper word selection, which could be attributed to adopting a literal translation method and uncommon collocations of certain medical terminologies. Therefore, this study recommends that effective translation of COVID-19-related health messages will be achieved by adopting a two-tier translation process, preferably involving a medical specialised translator.
<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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This study aims to find the chemosensitive dysfunction incidence in COVID-19-positive patients and its recovery.
We collected the data from sixty-five patients, all COVID-19 positive, quarantined in-hospital between 5 April 2020 and 17 May 2020, by a questionnaire distributed in the quarantine ward.
Smell dysfunction appeared in 89.23% with or without other symptoms of COVID-19. 39.66% of them recovered the sense of smell. Taste dysfunction found in 83.08% patients with other COVID-19 symptoms. Only 29.63% of them recovered. The recovery took 1–3 weeks, and most
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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Vaccination is a vital cornerstone of public health, which has saved countless lives throughout history. Therefore, achieving high vaccination uptake rates is essential for successful vaccination programs. Unfortunately, vaccine uptake has been hindered by deferent factors and challenges. The objective of this study is to assess COVID-19 vaccine uptake and associated factors among the general population.
This study is a descriptive cross-sectional study conducted in Basmaia city, Baghdad from June to October 2022. Data were collected through a semi-structured questionnaire using multi-stag
This study examined the problem of identifying the vocabulary of the methodology of teaching Arabic language in the faculties of Media. The researcher noticed the existence of an overlap between the syllabuses of the general specialization of the Arabic language and its Media sections in the universities with the special professional vocabulary that suits the study of the media student. Thus ,this study is regarded as a real attempt to present a methodological model of media language that concerns with fillfuling students ‘linguistic and knowledgeable needs relying on measuring their benefits from the methodological Arabic curriculum . Key words:problem, teaching’ methodology of Arabic language, media language.
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Worldwide, hundreds of millions of people have been infected with COVID-19 since December 2019; however, about 20% or less developed severe symptoms. The main aim of the current study was to assess the relationship between the severity of Covid-19 and different clinical and laboratory parameters. A total number of 466 Arabs have willingly joined this prospective cohort. Out of the total number, 297 subjects (63.7%) had negative COVID-19 tests, and thus, they were recruited as controls, while 169 subjects (36.3%) who tested positive for COVID-19 were enrolled as cases. Out of the total number of COVID-19 patients, 127 (75.15%) presented with mild symptoms, and 42 (24.85%) had severe symptoms. The age range for the partic
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