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Comparing the clinical efficacy and safety of high doses of beclomethasone inhaler with medium doses of beclomethasone inhaler combined with oral aminophylline or montelukast tablets in persistent asthmatic Iraqi patients.
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Asthma is a chronic inflammatory disorder of the airways in which many cells and cellular elements play a role. The treatment guidelines recommend theuse of a second controller drug in addition to medium doses of inhaled corticosteroids (ICSs) rather than the use of high doses ICS alone in the treatment of moderate-severe persistent asthma. This study was conducted to compare the clinical efficacy and safety of three treatment regimens in Iraqi patients with moderate-severe persistent asthma.The study included three groups; each group included 15 patients. Patients were administered beclomethasone inhaler alone 1500-2000 μg/day, beclomethasone inhaler 750-1000 μg/day plus oral controlled release aminophylline tablets 450 mg/day or beclomethasone inhaler 750-1000 μg/dayplus oral montelukast tablets 10 mg/day for 4-5 weeks. Patients were followed 2 weeks and 4-5 weeks after the baseline visit. In all of the three groups,significant improvements were noticed in pulmonary function test parameters (FEV1, FVC, FEF50%) and the asthma symptom records (day-time symptoms,night-time symptoms, number of salbutamol puffs per 24 hours), while there were no significant differences among the groups. Regarding side effects, onlythe group of inhaled steroid plus aminophylline tablets showed discontinuation of drug therapy in some patients which could be attributed to the development of serious side effects.It was concluded that the administration of a second controller agent was important to use lower doses of inhaled beclomethasone. It was concluded alsothat montelukast was associated with a lower incidence of serious side effects than aminophylline which could make aminophylline an alternative to montelukast as combination therapy with medium doses ICS in the treatment of moderate-severe persistent asthma

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Publication Date
Thu Sep 23 2021
Journal Name
Egyptian Journal Of Chemistry
Some 3,4,5-Trisubstituted-1,2,4-triazole Synthesis, Antimicrobial Activity, and Molecular Docking Studies
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Publication Date
Sun Jun 01 2025
Journal Name
Methodsx
How mathematical models might predict desertification from global warming and dust pollutants
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Publication Date
Tue Aug 07 2018
Journal Name
Oral And Maxillofacial Surgery
Mandibular war injuries caused by bullets and shell fragments: a comparative study
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Publication Date
Tue Aug 07 2018
Journal Name
Oral And Maxillofacial Surgery
Mandibular war injuries caused by bullets and shell fragments: a comparative study
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Publication Date
Wed Mar 29 2023
Journal Name
Journal Of Robotics
Real-Time SLAM Mobile Robot and Navigation Based on Cloud-Based Implementation
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This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database

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Publication Date
Sat Oct 31 2020
Journal Name
Iraqi Journal Of Agricultural Sciences
RELATIONSHIP BETWEEN PIGMENTS PRODUCTION AND BIOFILM FORMATION FROM LOCAL PSEUDOMONAS AERUGINOSA ISOLATES
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The current study was designed to explore the association between the pigments production and biofilm construction in local Pseudomonas aeruginosa isolates. Out of 143 patients suffering from burns, urinary tract infections (UTI), respiratory tract infections and cystic fibrosis obtained from previous study by Mahmood (2015), twenty two isolates  (15.38%) were identified  from (11) hospitals in Iraq, splitted  into three provinces, Baghdad, Al-Anbar and Karbala for the duration of June 2017 to April 2018.  Characterization was carried out by using microscopical, morphological and biochemical methods which showed that all these isolates belong to P. aeruginosa.  Screening of   biofilm production isolates was carried out by usi

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Publication Date
Tue Feb 06 2018
Journal Name
International Journal Of Gynecology And Obstetrics
FIGO consensus guidelines on placenta accreta spectrum disorders: Prenatal diagnosis and screening
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Recent population studies have shown that placenta accreta spectrum (PAS) disorders remain undiagnosed before delivery in half to two-thirds of cases. In a series from specialist diagnostic units in the USA, around one-third of cases of PAS disorders were not diagnosed during pregnancy. Maternal

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Publication Date
Tue Feb 24 2026
Journal Name
Baghdad Science Journal
EEG Lossless Signal Compression Based on Magnitude Classification and Run Length Encoding
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