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Prediction of Deleterious Non-Synonymous Single Nucleotide Polymorphisms (Nssnps) of Human TLR7 Gene
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      Toll-like receptors (TLRs) play a key role in innate immune response activation against viruses. TLR7, one of the TLRs family, is potentially important in controlling viral infection and the production of vaccines against the virus. The wide spectrum of discrepancy in response to antiviral drugs among different populations which is emerged by some pandemics like COVID-19 might be due to their different TLR7 single nucleotide polymorphisms (SNPs). The present study aimed to investigate the consequences of 401 non-synonymous missense SNPs (nsSNPs) within TLR7 on its protein structure, stability, and function by using specific bioinformatics tools. Seven bioinformatics tools were used to investigate 401 TLR7 nsSNPs from the dbSNP database. The results showed that the six variations, rs1171508003 (R262H), rs35160120 (F580S), rs968155471 (H587Q), rs202028806 (Y871D), rs1331496205 (W933S), and rs181600414 (R1004W), were found to be extremely deleterious by all of the employed bioinformatics tools. All six variations showed an impact on the protein’s structure, function, and stability. Among them, Y871D (rs202028806) and R1004W (rs181600414) were revealed as the most damaging nsSNPs. This study suggested that the predicted six damaging variants of TLR7 could indirectly or directly destabilize the structure of protein and deviate its function to some extent.

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Publication Date
Thu Jan 01 2015
Journal Name
Aip Conference Proceedings
Performance measurements of single server fuzzy queues with unreliable server using left and right method
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The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascal's triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely develo

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Publication Date
Fri May 01 2015
Journal Name
Transplantation Proceedings
Prevalence of Polyomavirus Among United Arab Emirates Kidney Transplant Recipients: Results From a Single Center
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

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Publication Date
Sat Jun 28 2014
Journal Name
Iraqi Postgraduate Medical Journal
Comparism Between Transvaginal Cervical Length Measurement and Digital Examination in Prediction of Imminent preterm Delivery
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BACKGROUND: Preterm labour is a major cause of perinatal morbidity and mortality, so it is important to predict preterm delivery using the clinical examination of the cervix and uterine contraction frequency. New markers for the prediction of preterm birth have been developed such as transvaginal ultrasound measurement of cervical length as this method is widely available. OBJECTIVE: To determine, whether transvaginal cervical length measurement predicts imminent preterm delivery better than digital cervical length measurement in women presented with preterm labour and intact membranes. PATIENTS AND METHODS: Two hundred women presented with preterm labour between 24 and 36+6 weeks of gestation were included in this study. All women subjecte

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Publication Date
Wed Nov 13 2019
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Prediction of maternal diabetes and adverse neonatal outcome in normotensive pregnancy using serum uric acid
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Diabetes mellitus, with adverse neonatal events are challenging issues to all obstetricians and pediatricians, where uric acid could play a vital role. We aimed to assess the relationship and prognostic benefits of serum uric acid measured at about 20 weeks’ gestation in normotensive pregnancy, with subsequent maternal diabetes, and neonatal complications. All singleton normotensive pregnant women with normal blood glucose, serum creatinine, and weight before pregnancy, whom attended Medical City Hospital, Department of Obstetrics and Gynecology in Baghdad, were involved and regarded as the case group, on the condition that their serum uric acid measured at 20 weeks’ gestation > 3 mg/dl, but if ≤ 3 mg/dl, they would be regi

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Performance Equations for Household Compressors Depending on Manufacturing Data for Refrigerators and Freezers
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Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
Prediction of Pressure Profile During Multi-Phase Flow in Different Oil Well: A Comparative Study
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Multiphase flow is a very common phenomenon in oil wells. Several correlation models, either analytical or experimental, have been investigated by various studies to investigate this phenomenon. However, no single correlation model was found to produce good results in all flow conditions. 14 models available on the Prosper software were selected for the purpose of calculating the pressure gradient inside wells within a range of different flow conditions. The pressure gradient was calculated using Prosper software, then compared with the measured gradient based on the production log test (PLT) data. This study was conducted on 31 wells from five different oil fields (Kirkuk, Jambur, Bai-Hassan, Al-Ahdab, and Rumaila). It is worth noting t

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