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Information Pollution in Iraqi Journalism…Study in Causes and Sources - A research drawn from a Master Degree thesis
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Information pollution is regarded as a big problem facing journalists working in the editing section, whereby journalistic materials face such pollution through their way across the editing pyramid. This research is an attempt to define the concept of journalistic information pollution, and what are the causes and sources of this pollution. The research applied the descriptive research method to achieve its objectives. A questionnaire was used to collect data. The findings indicate that journalists are aware of the existence of information pollution in journalism, and this pollution has its causes and resources.

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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Tue Jan 01 2013
Journal Name
Brain Research Bulletin
A note on the probability distribution function of the surface electromyogram signal
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Publication Date
Sun Jun 21 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Co-Amorphous System: A promising Strategy for Delivering Poorly Water - Soluble Drugs
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Amorphization of drug has been considered as an attractive approach in improving drug solubility and bioavailability. Unlike their crystalline counterparts, amorphous materials lack the long-range order of molecular packing and present the highest energy state of a solid material. Co-amorphous systems (CAM) are an innovative formulation technique by where the amorphous drugs are stabilized via powerful intermolecular interactions by means of a low molecular co-former.

This review highlights the different approaches in the preparation of co-amorphous drug delivery system, the proper selection of the co-formers. In addition, the recent advances in characterization, Industrial scale and formulation will be discussed.

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Refractive index sensor based on a solid-core photonic crystal fiber interferometer
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Photonic crystal fiber interferometers are widely used for sensing applications. In this work, solid core-Photonic crystal fiber based on Mach-Zehnder modal interferometer for sensing refractive index was presented. The general structure of sensor applied by splicing short lengths of PCF in both sides with conventional single mode fiber (SMF-28). To apply modal interferometer theory; collapsing technique based on fusion splicing used to excite higher order modes (LP01 and LP11). Laser diode (1550 nm) has been used as a pump light source. Where a high sensitive optical spectrum analyzer (OSA) was used to monitor and record the transmitted. The experimental work shows that the interference spectrum of Photonic crystal fiber interferometer

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Serum CXCL 9 as a Potential Biomarker for Patients with Ulcerative Colitis
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Background: Ulcerative colitis (UC) is an inflammatory bowel disease restricted to the large intestine, characterized by superficial ulceration. It is a progressive and chronic disease requiring long-term treatment. Although its etiology remains unknown, it is suggested that environmental factors influence genetically susceptible individuals, leading to the onset of the disease. (C-X-C) ligand 9 is a chemokine that belongs to the CXC chemokine family, it plays a role in the differentiation of immune cells such as cytotoxic lymphocytes, natural killer T cells, and macrophages. Its interaction with its corresponding receptor CXCR3 which is expressed by a variety of cells such as effector T cells, CD8+ cytotoxic T cells, and macrophage

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Publication Date
Mon Apr 01 2024
Journal Name
Al-kindy College Medical Journal
Radiological Modalities for the Assessment of Fetal Growth Restriction: A Comprehensive Review
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Fetal growth restriction is a significant contributor to fetal morbidity and mortality. In addition, there are heightened maternal risks associated with surgical operations and their accompanying dangers. Monitoring fetal development is a crucial objective of prenatal care and effective methods for early diagnosis of Fetal growth restriction, allowing prompt management and timely intervention to improve the outcomes. Screening for Fetal growth restriction can be achieved via many modalities; it can be medical, biochemical, or radiological. Some recommended combining more than one for better outcomes. Currently, there is inconsistency about the best method of Fetal growth restriction screening.   In this review, a comprehensive

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Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Natural Products as A Promising Therapy for SARS COV-2; An Overview
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Recently emerging pandemic SARS CoV-2 conquered our world since December 2019. Continuous efforts have been done to find out effective immunization and precise treatment stetratigies A way from therapeutic options that were tried in SARS CoV-2, an increased attention is directed to predict natural products and mainly phytochemicals as collaborative measures for this crisis. In this review, most of the mentioned compounds specially flavonoids (biacalin, hesperidin, quercetin, luteolin,, and phenolic (resveratrol, curcumin, and theaflavin) exert their effect through interfering with the action of one or more of this proteins (spike protein, papain like protease, 3 chymotrypsin like cysteine protease, and RNA dependent RNA 

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Publication Date
Sun Mar 28 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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