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Determination the concentration of insulin-like growth factor-I (IGF-I) in saliva of acromegalic patients, and comparison it with the levels of serum IGF-I.
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Acromegaly is ametabolic disorder characterized by an acquired progressive somatic disfigurement, mainly involving the face, extremities and many other organs, that are associated with systemic manifestations, caused by excessive secretion of growth hormone and a resultant persistent elevation of insulin-like growth factor-I concentrations. In more than 90% of cases originates from a monoclonal benign pituitary adenoma. Aim of this study to assess the level of insulin-like growth factor-I (IGF-I) in saliva of acromegalic patients, and to compare it with the basal levels of serum IGF-I. Sixty specimens of serum and saliva collected from two groups of subjects (forty acromegalic patients and twenty healthy persons). The specimens were centrifuged and stored at -20ºC then IRMA kits were used for estimating insulin like-growth factor-I. The results show that acromegalic patients had significantly higher salivary insulin like growth factor-I concentrations than healthy subjects (mean 21.26 vs. 20.48ng/mL; p=0.041), serum insulin like growth factor-I concentrations (mean 782.21 vs. 199.87ng/mL; p<0.001), there is significant correlation between salivary and serum insulin like growth factor –I in acromegalic group, whiles no significant correlation in control group, Salivary IGF-I concentration may not represented the corresponding serum concentration adequately, so cannot be considered it as alternative diagnostic tool to the acromegalic patients

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Sun Oct 01 2023
Journal Name
Minerva Dental And Oral Science
Salivary interleukin-1β as a biomarker to differentiate between periodontal health, gingivitis, and periodontitis
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Publication Date
Wed Jan 24 2018
Journal Name
The Journal Of Physical Chemistry C
Novel Approach for Fabricating Transparent and Conducting SWCNTs/ITO Thin Films for Optoelectronic Applications
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Publication Date
Sun Aug 24 2014
Journal Name
Wireless Personal Communications
Multi-layer Genetic Algorithm for Maximum Disjoint Reliable Set Covers Problem in Wireless Sensor Networks
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Publication Date
Mon May 01 2023
Journal Name
Kurdish Studies
Establishing Proof Against Those Who Claimed to Contradict Al-Noman in Matters Such as Sales
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Jurisprudential disagreements are a significant source of a vast jurisprudential wealth. Among the manifestations of these disagreements are scholarly critiques raised by some scholars against others, claiming their divergence from the legal evidence or established principles for deducing legal rulings. One such critique is presented by the narrator scholar Abu Bakr Ibn Abi Shaybah, may Allah have mercy on him, directed towards Abu Hanifah al-Nu‘man, may Allah have mercy on him. In his compilation, Ibn Abi Shaybah cited numerous hadiths and traditions that he considered conflicting with the judgments as perceived by Imam Abu Hanifah, may Allah have mercy on him. These issues cover various branches of jurisprudence, including worship, sale

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Publication Date
Mon May 01 2017
Journal Name
2017 24th International Conference On Telecommunications (ict)
Load balancing by dynamic BBU-RRH mapping in a self-optimised Cloud Radio Access Network
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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Publication Date
Fri Oct 26 2018
Journal Name
Al–bahith Al–a'alami
University youth attitudes towards mobile phone Companies advertisements in Social networking sites): :(Facebook as sample
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The advertising has emerged as an effective force and an effective instrument upon with all organizations and companies depend on achieving their goals. In additional to the need to use promote sales, The nature and objective of advertising go beyond the scope of specific personal communication to a broader and more effective range for consumers from multiple groups and combination play need to use as well as the need to use means of communication than com convey the message more professional, The coincides with the rapid and remarkable development of all different media technologies and as much as possible social networking sites including mobile phone companies. The advertising has emerged as an effective force and an effective instrum

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Wed May 11 2022
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Some Methods For A single Imputed A missing Observation In Estimating Nonparametric Regression Function
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In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

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