In October 2019, Iraq and Lebanon witnessed widespread protests, which aroused the interest of the media, as they began with demands for the provision of services, then escalated with the overthrow of the political system. The researchers chose a satellite channel that represents a direction for a country accused of entering the line of protests. This paper aims to analyze the main bulletin of Al-Alam channel to find out how it deals with the protests in the news. It is classified descriptively, using the survey method and the method of content analysis. The study community was represented by the main news bulletin of Al-Alam channel. The researchers adopted a deliberate sample for the period from 1/10/2019 to 31/12/2019, as the bulletin intensified its coverage of the protests. The research reached a number of results, the most important of which are: framing the news about the protests within the framework of responsibility, and confirming that the demonstrators attacked property and security forces.
atrogenic atrial septal defect (IASD), post Catheter ablation during electrophysiological study simply can be assess with Echocardiography nowadays ablation consider the main line in the managements of patients with various type of arrhythmia. This study aims to de-termine the outcomes of Iatrogenic Atrial Septal Defect (IASD) six months post radiofrequency ablation (RF) procedure of left atrial arrhythmia using non-invasive Transtho-racic Echocardiography (TTE) parameters (LVEF, E/e` and ASD size) with sheath size as predictors of atrial septal defect closure. Patients and methods: A prospective study was con-ducted in Iraqi Centre for Heart Diseases included 47 patients post Electrophysiology procedure and ablation of left atrial SVT were
... Show MoreRecent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.
In this cross-sectional study, 488 apparently healthy individuals with overweight and obesity were participated. Dietary intake was assessed by a Food Frequency Questionnaire (FFQ) and
Background: Preeclampsia (PE) is a major cause of maternal morbidity and mortality, complicating 3-14% of all pregnancies. Although the etiology remains unknown, placental hypoperfusion and diffuse endothelial cell injury are considered to be the central pathological process; many endocrinological changes have been linked to the etiology of preeclampsia including parathyroid hormone and calcium level. Objective: to compare serum parathyroid hormone and total serum calcium levels in mild and severe preeclampsia versus normal pregnancy. Patients and methods: Serum parathyroid hormone (PTH) level and total serum calcium level were measured in thirty normotensive pregnant women and thirty women with mild preeclampsia and thi
... Show MoreSeawater might serve as a fresh‐water supply for future generations to help meet the growing need for clean drinking water. Desalination and waste management using newer and more energy intensive processes are not viable options in the long term. Thus, an integrated and sustainable strategy is required to accomplish cost‐effective desalination via wastewater treatment. A microbial desalination cell (MDC) is a new technology that can treat wastewater, desalinate saltwater, and produce green energy simultaneously. Bio‐electrochemical oxidation of wastewater organics creates power using this method. Desalination and the creation of value‐added by‐products are expected because of this ionic mov
Heat island is known as the increases in air temperature through large and industrial cities compared to surrounding rural areas. In this study, remote sensing technology is used to monitor and track thermal variations within the city center of Baghdad through Landsat satellite images and for the period from 2000 to 2015. Several processors and treatments were applied on these images using GIS 10.6 and ERDAS 2014, such as image correction and extraction, supervised classification, and selection of training samples. Urban areas detection was resulted from the supervised classification linked to the temperature readings of the surface taken from the thermal bands of satellite images. The results showed that the surface temperature of the c
... Show MoreThere is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler
... Show MoreImmune-mediated hepatitis is a severe impendence to human health, and no effective treatment is currently available. Therefore, new, safe, low-cost therapies are desperately required. Berbamine (BE), a natural substance obtained primarily from
This c
HTH Ahmed Dheyaa Al-Obaidi,", Ali Tarik Abdulwahid', Mustafa Najah Al-Obaidi", Abeer Mundher Ali', eNeurologicalSci, 2023
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for